## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX A
Dioxin Workshop Report

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## EPA/600/R-09/027 May 2009



# Summary of U.S. EPA Dioxin Workshop

February 18

− 20, 2009

Cincinnati, Ohio

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH 45268

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— DO NOT CITE OR QUOTE A-ii DISCLAIMER

This document summarizes the discussions presented at the Dioxin Workshop in February 2009, in Cincinnati, OH, as documented by the Session Co-Chairs. This document is not all inclusive or binding. Conclusions a nd recommendations to the U.S. EPA may not represent full consensus. The views expre ssed in this document are those of the Dioxin Workshop Panelists and do not necessarily re flect the views and policies of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not constitute endorsement or r ecommendation for use.

Preferred Citation: U.S. Environmental Protection Agency (U.S. EPA). (2009) Summary of U.S. EPA Dioxin Workshop: February 18

− 20, 2009. U.S. Environmental Protection Agency, National Center for Environmental Assessment, Cincinnati, OH. EPA/600/R-09/027.

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— DO NOT CITE OR QUOTE A-iii TABLE OF CONTENTS

DIOXIN WORKSHOP TEAM ................................................................................................. A-iv ACKNOWLEDGMENTS ......................................................................................................... A-iv

INTRODUCTION ...................................................................................................................... A-1

REFERENCES ............................................................................................................... A-2

SCIENTIFIC WORKSHOP TO INFORM THE TECHNICAL WORK PLAN FOR U.S. EPA’S RESPONSE TO NAS COMMENTS ON THE HEALTH EFFECTS OF DIOXIN PRESENTED IN U.S. EP A’S DIOXIN REASSESSMENT ................................ A-3
SESSION 1: QUANTITATIVE DOSE-RE SPONSE MODELING ISSUES................ A-3 SESSION 2: IMMUNOTOXICITY ............................................................................... A-6 SESSION 3A: DOSE-RESPONSE FOR NEUROTOXICITY AND NONREPRODUCTIVE ENDOCRINE EFFECTS............................................... A-8 SESSION 3B: DOSE-RESPONSE FOR CARDIOVASCULAR TOXICITY AND HEPATOTOXICITY ................................................................................. A-11 SESSION 4A: DOSE-RESPONSE FOR CANCER .................................................... A-13 SESSION 4B: DOSE-RESPONSE FOR REPRODUCTIVE/DEVELOPMENTAL TOXICITY ....................................... A-16SESSION 5: QUANTITATIVE UNCERTAINTY ANALYSIS OF DOSERESPONSE.......................................................................................................... A-20

APPENDIX A: 2009 U.S. EPA DI OXIN WORKSHOP AGENDA........................................ A-24

APPENDIX B: 2009 U.S. EPA DIOXIN WORKSHOP QUESTIONS TO GUIDE PANEL DISCUSSIONS..................................................................................................... A-31

APPENDIX C: 2009 U.S. EPA DIOX IN WORKSHOP DRAFT SELECTION CRITERIA TO IDENTIFY KEY IN VIVO MAMMALIAN STUDIES THAT INFORM DOSE-RESPONSE MODELING FOR 2,3,7,8-TETRACHLORODIBENZO-p- DIOXIN (TCDD)................................................ A-34

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— DO NOT CITE OR QUOTE A-iv DIOXIN WORKSHOP TEAM

The Dioxin Workshop Team, under the leadership of Peter W. Preuss, Director, NCEA, comprised the following members:

National Center for Environmental Assessmen t, Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH 45268 Belinda S. Hawkins Janet Hess-Wilson Glenn Rice Jeff Swartout Linda K. Teuschler Bette Zwayer
Argonne National Laboratory, Argonne, IL 60439 Maryka H. Bhattacharyya Andrew Davidson Mary E. Finster Margaret M. MacDonell David P. Peterson

ACKNOWLEDGMENTS
The Track Group, Alexandria, VA 22312 Kara Hennigan Alan Minton Brandy Quinn
ECFlex, Inc., Fairborn, OH 45324 Dan Heing Heidi Glick Amy Prues Lana Wood
IntelliTech Systems, Inc., Fairborn, OH 45324 Cris Broyles Luella Kessler Stacey Lewis Linda Tackett

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— DO NOT CITE OR QUOTE INTRODUCTION

This document provides a summary of th e Scientific Workshop to Inform EPA’s Response to National Academy of Science Comment s on the Health Effect s of Dioxin in EPA’s 2003 Dioxin Reassessment. The U.S. Environmental Protection Agency (U.S. EPA) and Argonne National Laboratories (ANL), through an inter-Agency agreem ent with the U.S. Department of Energy, convened this scientif ic workshop (“Dioxin Workshop”) on February 18

− 20, 2009, in Cincinnati, Ohio. The goals of the Dioxin Workshop were to identify and address issues related to the dose-res ponse assessment of 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD). This report summarizes the discussions and conclusions from this workshop. Previously, at the request of the U.S. EPA, th e National Academy of Sciences (NAS) prepared a report, Health Risks from Dioxin and Related Co mpounds: Evaluation of the EPA Reassessment (NAS, 2006), which made a number of recomme ndations to improve the U.S. EPA’s risk assessment for TCDD (U.S. EPA, 2003). The 3-day Dioxin Workshop was convened specifically to ensure that the U.S. EPA’s res ponse to the NAS recommendations focuses on the key issues and reflects the mo st meaningful science.
The Dioxin Workshop included se ven scientific sessions: (1) Session 1: Quantitative Dose-Response Modeling Issues (2) Session 2: Immunotoxicity (3) Session 3A: Dose-Response for Neurotoxicity and Nonreproductive Endocrine Effects (4) Session 3B: Dose-Response for Cardiovasc ular Toxicity and Hepatotoxicity (5) Session 4A: Dose-Response for Cancer (6) Session 4B: Dose-Response for Reproductive/Developmental Toxicity (7) Session 5: Quantitative Uncertainty Analysis of Dose-Response
During each session, the U.S. EPA asked a panel of expert scientists to:

• identify and discuss the technical challe nges involved in addressing the key NAS comments on the TCDD dose-response asse ssment in the U.S. EPA Reassessment (U.S. EPA, 2003);

• discuss approaches for addressing the key NAS comments; and

• identify important published, independently peer -reviewed literature, particularly studies describing epidemiologic and in vivo mammalian bioassays, which are expected to be most useful for informing the U.S. EPA’s response.
The sessions were followed by open commen t periods during which members of the audience were invited to address the Panels. At the conclusion of the open comment periods, the Panel Co-Chairs were asked to summarize and pres ent the results of the panel discussions. The summaries could include minority opinions stated by panelists. The main points derived from the session summaries were used to prepare this document. Additionally, this document includes a list of the session panelists and their affiliations and three appendices. Appendix A presents the Dioxin Workshop Agenda. Appendix B identif ies the charge questions presented to the Panel. Appendix C describes draft study sel ection criteria proposed by the Dioxin Workshop Team for consideration by the workshop panelists.

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— DO NOT CITE OR QUOTE REFERENCES NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS review draft, Volumes 1

− 3 (EPA/600/P-00/001Cb, Volume 1). U.S. Environmental Protection Agency, National Center for Environmenta l Assessment, Washington, DC (December). Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

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SCIENTIFIC WORKSHOP TO INFORM TH E TECHNICAL WORK PLAN FOR U.S. EPA’S RESPONSE TO NAS COMMENTS ON THE HEALTH EFFECTS OF DIOXIN PRESENTED IN U.S. EPA’S DIOXIN REASSESSMENT
Dioxin Workshop Co-Chairs: Pe ter W. Preuss and Glenn Rice
The Dioxin Workshop session summaries were prepared by the session panel Co-Chairs with input from the panelists, as requested by the U.S. EPA prior to the workshop. The CoChairs subsequently presented these summarie s to all of the works hop participants during designated periods at the workshop. In these summ aries, the U.S. EPA asked that the Co-Chairs summarize the key issues from the panel discussions. Because the sessions were not designed to achieve consensus among the panelists, the summa ries do not necessarily represent consensus opinions; rather, they reflect the essence of the panel discussions . Some of the specific points may represent the views of multiple panelists, while others only the views of a single panelist. Prior to the summarizations, there were opportu nities for public comments on the discussion topics. Some Co-Chairs met with their sessions ’ panelists after their sessions ended to develop these summaries, while others developed reports based on their personal notes. Because Session 5 was the last session of the workshop—with little time provide d to develop the summary—the Co-Chairs circulated a draft for comment by the Session 5 panelists after the workshop, prior to finalizing the session summary. The U.S. EPA collected the session summaries and then prepared this document. A draft of this documen t was distributed to all of the session Co-Chairs to provide them with a final opportunity to comment and make revisions. Finally, it should be noted that U.S. EPA was not prescriptive to the session Co-Chairs with respect to the format of the presentation materials and provided no specifi c instructions, resulting in unique formats among the session summaries.

SESSION 1: QUANTITATIVE DOSE-RESPONSE MODELING ISSUES This session discussed the general dose-response modeling issues related to TCDD. Many of these issues were highlighted by NAS (2006). There was a general introductory presentation on TCDD kinetics, including info rmation and uncertainti es pertaining to the conversion of administered dos es in animals to human body bur den (BB) and additivity to background issues. This presentation was follo wed by a Panel discussion on the state of the science regarding dioxin dose -response modeling issues.
Session 1 Panelists (Session Co-Cha irs are identified by asterisk)

• Bruce Allen, Bruce Allen Consulting

• Lesa Aylward, Summit Toxicology

• Roger Cooke, Resources for the Future

• Kenny Crump, Louisiana Tech University

• Mike DeVito, U.S. EPA

• Dale Hattis, Clark University

• Rick Hertzberg, Biomath Consulting

• Rob McDowell, U.S. Department of Agriculture

• Jim Olson, State University of Ne w York, University at Buffalo

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— DO NOT CITE OR QUOTE • *Lorenz Rhomberg, Gradient

• Woody Setzer, U.S. EPA

• *Jeff Swartout, U.S. EPA

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-Chair and represent a synopsis of the panel discussions.



## Key Study Selection Criteria The Panel discussed the advantages and di sadvantages of using key study criteria (Appendix C). They concluded that a priori criteria foster transpar ency and consistency, and could deflect a posteriori criticism. However, the Pane l also acknowledged that having a priori criteria could introduce the potenti al for excluding useful data. Although the key study criteria provided by the U.S. EPA listed studies using TCDD only as a criterion, the Panel posed the possibility of using closely related dioxin-like compounds (DLCs) as surrogates for TCDD. The criterion for use of data from mammalian studies only was one criterion that received generalized support due to the lack of extr apolation protocols for nonmammalia n species. The Panel also discussed the specific exposure-du ration criterion and asked if there should be a preference for longer-term rather than acute studies. The Pane l made three suggestions to modify U.S. EPA’s key study selection criteria: (1) Define more relevant expos ure-level (i.e., dose) cut points using tissue concentrations. (2) Reword statistical criteria to include do-it-yourself analysis. (3) Reword the response criteria to cl arify “outside of normal range.”

Dose Metrics The Panel discussed the relative merits of various measures of dose for modeling TCDD dose response. One general conclusion was that tissue concentration (T C) is the preferred metric, especially lipid-adjusted TC, because this measure more closely approximates exposures close to the target tissue when compared to administered doses. However, the Panel acknowledged that these data are often unavailab le. They further noted that BB, which is defined as the concentration of TCDD in the body (ng/kg body weight) (U.S. EPA, 2003), might be useful as a surrogate for TC provided the two measures were proportional.
The Panel suggested that a linear approach to BB estimation, which was utilized by U.S. EPA (2003), is too simplistic because this ap proach does not take into account toxicokinetic issues related to TCDD—e.g., sequ estration in the liver and fat, age-dependent elimination, and changing elimination rates over time. The Pane l recommended the use of kinetic/mechanistic modeling to the extent possible to quantify tissue-based metrics.
The Panel raised the issue of whether the pr eferred dose metric would be different for different endpoints and exposure du rations. This led to the Panel’s comment that the peak exposure might be a more important metric than average BB for variable exposure scenarios. Given this discussion about different exposure du rations being relevant to a specific endpoint, the Panel suggested that the U.S. EPA also cons ider peak measures in dose-response modeling.

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— DO NOT CITE OR QUOTE The last point raised in this part of th e discussion centered on the possibility of dose errors in experimental studies. The Panel highli ghted the need for the U.S. EPA to consider dose error (i.e., uncertainty in the x-axis of the dose-response curv e) when using dose surrogates.
Dose-Response Modeling of Mammalian Bioassays The Panel considered several issues re lated to dose-response modeling of mammalian bioassay data for TCDD: supralinearity and incomp lete response data (“an choring”), defining the benchmark response (BMR) level with respect to establishing the point of departure (POD), and the use of threshold modeling—as further explained below.
The Panel discussed the specific issues of supralinearity and anchoring raised by the U.S. EPA with respect to modeling noncancer endpoi nts. The panel recogni zed that, for many of the most sensitive endpoints, the response at th e lowest dose is high (e.g., quantal responses above 25% and continuous endpoi nts differ substantially from the mean, often implying 100% incidence in the treated animals). This lack of response anchoring at the low end of the doseresponse curve (near the BMR) results in the hi gher responses determining the shape of the

curve. The Panel asked whether new tools might be n eeded or whether the current tools could be applied differently. In the context of developi ng new tools, the Panel emphasized the need for collaboration between biologists and mathematic ians. When discussing application, the Panel suggested that the problem with supralineari ty might be overcome by simply dropping the requirement for using the lower bound on the Be nchmark Dose. In addition, the Panel posed several more approaches for further considerat ion in dose-response modeling by the U.S. EPA: (1) Combine similar data sets to fill in data gaps. (2) Use mechanistic approaches to model the data gaps. (3) Dichotomize continuous data.
Finally, the Panel acknowledged that, in certain situations, there simply may not be enough information to provide meaningful answers.
The Panel discussed the BMR level for esta blishing a POD in the context of deriving a Reference Dose (RfD). The Panel generally ag reed that, while the e ffective dose level (ED 01 

## ) used in the 2003 Reassessment may be useful for comparative analysis across endpoints, the ED 01 

## estimates developed for all endpoints consider ed in the Reassessment were not appropriate for deriving an RfD because they were not based on the effect’s adversity. The panel noted that ED 01 

## also is much lower than typical EPA BMR le vels. The Panel recommended that the U.S. EPA work to define endpoint-specific BMRs base d on the consideration of adversity. Given that the same uncertainty factor framework is applie d to all PODs, the Panel emphasized the need for consistency in BMRs; numerical co nsistency is needed for quantal BMRs and consistency in the choice of biological rele vance should be applied for continuous BMRs. The Panel generally discourag ed threshold modeling by statin g that thresholds are very difficult to pin down and suggested that the lower bound may always be zero.

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— DO NOT CITE OR QUOTE Dose-Response Modeling of Epidemiological Studies The Panel noted that many studies have been published with measured concentrations of TCDD that could be used for dose reconstruction. In this discussion, the Panel acknowledged that use of these data would entail dealing with toxicity equivalence (TEQ) issues and pharmacokinetic (PK) modeling. Pe rtaining to the use of these data for quantitative risk assessment by the U.S. EPA, the Panel posed th e question, “At what point does indirect or confounded human data supersede c ontrolled animal bioassay data ?”, or alternatively, “How much human data uncertainty can we tolerate?” The Panel suggested, at the least, that the epidemiologic data could be used to “ground-tr uth” the animal bioassay modeling results.
Supporting Information The Panel acknowledged that Ah receptor (AhR ) binding affinities are not necessarily tied to endpoint sensitiv ity, but they reiterated the need to consider mechanistic modeling to aid in developing appropriate dose metrics or filling in data gaps in the ex isting dose-response data.

References
NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS Review Draft (EPA/600/P-00/001Cb). U.S. Envi ronmental Protection Agency, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

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SESSION 2: IMMUNOTOXICITY The U.S. EPA plans to consider development of a quantitative dose-response assessment for the immunologic effects associated with TC DD exposure. Such an assessment would be based on information in U.S. EPA (2003), NAS (2006) and key studies identified in thisworkshop. The purpose of this session was to identify and discuss key issues pertaining to doseresponse assessment for dioxin-i nduced immunologic effects.
Session 2 Panelists (Session Co-Cha irs are identified by asterisk)

• Roger Cooke, Resources for the Future

• Rob Goble, Clark University

• *Belinda Hawkins, U.S. EPA

• Nancy Kerkvliet, Oregon State University

• Manolis Kogevinas, Centre for Res earch in Environmental Epidemiology

• Robert Luebke, U.S. EPA

• Paolo Mocarelli, University of Milan

• *Allen Silverstone, State University of New York, Upstate Medical University

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— DO NOT CITE OR QUOTE • Courtney Sulentic, Wright State University

• Nigel Walker, National Institute of Environmental Health Sciences

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-Chair and represent a synopsis of the panel discussions.



## Key Study Selection Criteria The Panel first addressed the Key Study Se lection Criteria proposed by the U.S. EPA (Appendix C). The Panel raised th e issue that the key study criteria do not a pply to most studies designed to investigate immunotoxicity, in cluding those used to calculate ED 01 

## s (U.S. EPA, 2003). The Panel observed that most dioxin i mmunotoxicity studies ar e relatively high dose (>200 ng/kg-d) acute studies and/or use pare nteral rather than oral administration.

The Panel discussed several studies often considered important for assessing the immunotoxic effects of TCDD exposure. The Oughton et al. (1995) mouse bioassay was discussed and, although the study does meet the propos ed criteria, it could not be considered a key study; specifically, the Panel contended that since there were no functional alterations observed or measured in this bioassay, the chan ges in cellular phenotypes are only “suggestive” of immune alterations and cannot be regard ed as having immunopat hologic significance.

The Panel discussed two additional studies for further consideration by the U.S. EPA:

• Baccarelli et al. (2002). Th e Panel discussed this as a potentially key human epidemiological study that shoul d be reviewed and considered further by the U.S. EPA. It measured the level of IgG, demonstrati ng a significant decline relative to dioxin body burdens.

• Smialowicz et al. (2008). The Panel noted th at this study identifie d the antibody response to sheep red blood cells (SRBCs) as the critic al effect, labeling this protocol as a functional assay. The Panel stated that if modeled, the U.S. EPA could calculate the BMR for this endpoint as 1 standard deviation from the control mean.

References
Baccarelli, A., P. Mocarelli, D. G. Patterson et al. 2002. Imm unologic effects of dioxin: New results from Seveso and comparison with other studies. Environ. Health Perspect. 110(12):1169-1173.
NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. Oughton, J.A., C.B. Pereira, G.K. Dekrey, J.M. Collier, A.A. Frank and N.I. Kerkvliet. 1995. Phenotypic analysis of spleen, thymus, and pe ripheral blood cells in aged C57BI/6 mice following long-term exposure to 2,3,7,8-tetrachlorodibenzo- p -dioxin. Toxicol. Sci. 25(1):60-69.

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— DO NOT CITE OR QUOTE Smialowicz, R.J., M.J. DeVito, W.C. Williams and L.S. Birnbaum. 2008. Relative potency based on hepatic enzyme induction predicts immunosuppressive effects of a mixture of PCDDS/PCDFS and PCBS. Toxicol. Appl. Pharmacol. 227(3):477-484.
U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS Review Draft (EPA/600/P-00/001Cb). U.S. Envi ronmental Protection Agency, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

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SESSION 3A: DOSE-RESPONSE FOR NE UROTOXICITY AND NONREPRODUCTIVE ENDOCRINE EFFECTS The U.S. EPA plans to consider development of a quantitative dose-response assessment for neurological and/or nonrep roductive endocrine effects asso ciated with TCDD exposure. Such an assessment would be based on information in U.S. EPA (2003), NAS (2006) and key studies identified in this work shop. The purpose of this session was to identify and discuss key issues pertaining to dose-response assessment for dioxin-i nduced neurological and/or nonreproductive endocrine effects.
Session 3A Panelists (Session Co-C hairs are identified by asterisk)

• *Maryka Bhattacharyya, Ar gonne National Laboratory

• Mike DeVito, U.S. EPA

• Mary Gilbert, U.S. EPA

• Rob Goble, Clark University

• Nancy Kerkvliet, Oregon State University

• Fumio Matsumura, University of California-Davis

• Paolo Mocarelli, University of Milan

• Chris Portier, National Institute of Environmental Health Sciences

• Lorenz Rhomberg, Gradient

• Allen Silverstone, State University of New York, Upstate Medical University

• Marie Sweeney, National Institute of Occupational Safety and Health

• *Bernie Weiss, University of Rochester

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-Chair and represent a synopsis of the panel discussions.



## What Are the Key Questions Regarding These Endpoints? The Panel used the following quest ion to initiate discussion: “ Are there identifiable indices of neurotoxicity and nonreproductive endocrin e effects in anima l studies and human populations?” Under this discussion topic, the Pane l discussed three endpoints: neurotoxicity (with focus on developmental exposures), thyroi d dysfunction (e.g., thyroid hormone deficits), and diabetes. The Panel also addressed the re levance of windows of vul nerability to each

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— DO NOT CITE OR QUOTE endpoint. The Panel acknowledged that, in some cases, the window of expo sure may precede the window of expression of toxicity.
Epidemiological Study Selection Developmental Neurotoxicity The Panel recognized that an unusual feature fo r this endpoint is that there are sufficient human data for dose-response modeling (e.g., Dutch children [Huisman et al., 1995; Patandin et al., 1999] and U.S. children [Jacobson and Jacobson, 1996]) and there is an internal dose metric (serum concentrations). Add itionally, the Panel discussed rece nt studies that address this endpoint in humans (from Japa n [reference not provided] and Holland [e.g., Koopman-Esseboom et al., 1996; Vreugdenhil et al., 2002]). For conti nued investigation into this endpoint, the Panel raised two issues to the U.S. EPA:

• Conduct an evaluation of whethe r a modeled effect can be attributed to TCDD and not some other persistent organic pollutant (POP ), although the Panel reco gnized that it is unlikely U.S. EPA will be able to distinguish among these exposures because other POPs are intrinsic confounders in the Dutch study.

• Allow animal data to inform the dose-re sponse modeling of epidemiological data.
Thyroid Dysfunction The Panel identified the availabi lity of human data for this endpoint (e.g., Calvert et al., 1999; Koopman-Esseboom et al., 1994). Much of the thyroid dysfunction literature has been published since the 2003 Reassessment (e.g., Wang et al., 2005; Baccarelli et al., 2008). The Panel also noted the availability of an internal dose metric (serum concentrations). Additionally, the Panel discussed the mechanistic studies in animals that link TCDD to thyroid dysfunction. For continued investigation into this endpoint, the Panel raised th ree issues for the U.S. EPA to consider:

• Consider the newly available human data since the Reassessment.

• Investigate and clarify of the role of TCDD-induced thyroid dysfunction in developmental neurotoxicity.

• Evaluate and determine whether an effect can be attributed to TCDD or other contaminants.

Diabetes The Panel discussed that data suggest that diabetes incidence in those under 55 years old may be associated with exposure to PCBs. They acknowledged that whethe r this is a dioxin-like compound (DLC) mediated effect or whether other POPs are responsible is still undetermined. The Panel also acknowledged that no animal model exists for th e investigation of xenobioticinduced diabetes, and that separa ting the injury dose level fr om the current body burdens would depend on good pharmacokinetics in humans. For c ontinued investigation in to this endpoint, the Panel listed two issues for the U.S. EPA to consider:

• Results from the Anniston study and the Gr eat Lakes Fishermen study (references not provided) should be examined for dose metrics (both studies examine human PCB exposures).

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— DO NOT CITE OR QUOTE • Changes of adipose tissue status need to be considered, given th at dieting can cause release of lipid-soluble contaminants.

References
Baccarelli, A., S.M. Giacomini, C. Corbetta et al. 2008. Neonatal thyroid function in Seveso 25 years after maternal exposure to dDioxin. PLoS Med. 5(7):e161. doi:10.1371/journal.pmed.0050161.
Calvert, G.M., M.H. Sweeney, J. Deddens a nd D.K. Wall. 1999. Evaluation of diabetes mellitus, serum glucose, and thyroid functi on among United States workers exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin. Occ. Env. Med. 56:270-276.
Huisman, M., C. Koopman-Esseboom, V. Fidl er et al. 1995. Perinatal exposure to polychlorinated biphenyls and di oxins and its effect on neonata l neurological development. Early Hum. Devel. 41(2):111-127.
Jacobson, J.L. and S.W. Jacobson. 1996. Intelle ctual impairment in children exposed to polychlorinated biphenyls in utero . N. Engl. J. Med. 335:783–789.
Koopman-Esseboom, C., N. Weis glas-Kuperus, M.A.J. de Ridder, C.G. Van der Paauw, L.G.M.Th. Tuinstra and P.J.J. Sauer. 1996. E ffects of polychlorinated biphenyl/dioxin exposure and feeding type on infants’ me ntal and psychomotor development. J. Pediatr. 97(5):700-706.
Koopman-Esseboom, C., D.-C. Morse, N. Weisglas -Kuperus et al. 1994. Effects of dioxins and polychlorinated biphenyls on thyr oid hormone status of pregnant women and their infants. Pediatr. Res. 36:468–473.
Patandin, S., C.I. Lanting, P.G.H. Mulder, E.R. Bo ersma, P.J.J. Sauer and N. Weisglas-Kuperus. 1999. Effects of environmental exposure to poly chlorinated biphenyls and dioxins on cognitive abilities in Dutch children at 42 mont hs of age. J. Pediatr. 134:33–41.
NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS Review Draft (EPA/600/P-00/001Cb). U.S. Envi ronmental Protection Agency, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

. Vreugdenhil, H.J., C.I. Lanting, P.G. Mulder, E.R. Boersma and N. Weisglas-Kuperus. 2002. Effects of prenatal PCB and dioxin background exposure on cognitive and motor abilities in Dutch children at school age. J. Pediatr. 140:48–56.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-11 DRAFT

— DO NOT CITE OR QUOTE Wang S.L., P.H. Su, S.B. Jong, Y.L. Guo, W.L. Chou and O. Päpke. 2005. In utero exposure to dioxins and polychlorinated biphe nyls and its relations to thyr oid function and growth hormone in newborns. Environ. H ealth Perspect. 113:1645–1650.

SESSION 3B: DOSE-RESPONSE FOR CARDIOVASCULAR TOXICITY AND HEPATOTOXICITY The U.S. EPA plans to consider development of a quantitative dose-response assessment for cardiovascular and/or hepati c effects associated with TCDD exposure. Such an assessment would be based on information in U.S. EPA (200 3), NAS (2006) and key st udies identified in this workshop. The purpose of this session was to identify and discuss key issues pertaining to dose-response assessment for dioxin-induced cardiovascular and/or hepatic effects.
Session 3B Panelists (Session Co-C hairs are identified by asterisk)

• Bob Budinksy, Dow Chemical

• Manolis Kogevinas, Centre for Res earch in Environmental Epidemiology

• Rob McDowell, U.S. Department of Agriculture

• Jim Olson, State University of Ne w York, University at Buffalo

• Marian Pavuk, Agency for Toxic S ubstances and Disease Registry

• *Jeff Swartout, U.S. EPA

• *Mary Walker, University of New Mexico

• Nigel Walker, National Institute of Environmental Health Sciences

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-chair and represents a synopsis of the panel discussions.



## Key Study Selection Criteria The Panel initially focused on the draft ke y study selection criteria offered by the U.S. EPA (Appendix C). The panel recommended th at for cardiovascular effects, which are not usually observed in rodents, the use of knoc kout mouse models (ApoE KO and LDLR KO) be moved to the “primary” column because only these studies establish the cardiovascular toxicity model in mice.
The panel also was concerned that the gavage procedure can increase mouse blood pressure. Consequently, the panel recommended th at gavage studies not be used for the blood pressure endpoint (i.e., only dietary dosing studies should be considered).
Human Health Endpoints In relation to the hepatic endpoint, the Panel acknowledged the large body of dose response information on hepatic effects in rode nts and that enzyme (mostly CYP1A1) induction was a sensitive effect. However, the Panel cite d the lack of linkage of CYP1A1 to downstream events, which complicates the toxi cological interpretati on of this endpoint, and concluded that

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-12 DRAFT

— DO NOT CITE OR QUOTE the more important liver effects in rodents are probably on the “roa d to cancer.” The Panel noted that hepatic effects were not seen in the epid emiological studies, but acknowledged that these studies were not designed to detect them.
In relation to the cardiovascular endpoint, the Panel identif ied hypertension and ischemic heart disease (IHD) as two key endpoints from the epidemiological studies. The Panel recommended that the U.S. EP A perform a meta-analysis of these data. The Panel also commented that recent animal studies support the observations linking TCDD exposure to IHD and hypertension. In particular, the Nati onal Toxicology Program (NTP) study shows inflammatory and structural effects on resistan t vascular arterioles (NTP, 2006). Additional evidence from the study suggests that the vascul ar effects may be CYP1A1-dependent. The Panel suggested that the NTP study data might be used as a surrogate for dose-response modeling of hypertension and that such an approa ch would be supported by data on the role of AhR in vascular function and remodeling.

POD Issues The Panel was not supportive of 1% of maximal response (ED 01 

## ), which was utilized in the 2003 Reassessment. The Panel concluded that the POD should depend on the specific endpoint and recommended the following to the U.S. EPA:

• For continuous measures, base the BMR on difference from control. Consider the adversity level—at what point do es the endpoint become adverse?

• For incidence data, set the BMR to a fixed-risk level.
Supporting Information The Panel posed several suggestions to the U.S. EPA for reducing uncertainty and improving the knowledge base for TCDD toxicity.

• Use in vitro data to define uncertainties, such as the relative sensitivity between rodents and humans and around the definition of a POD.

• Consider studies on dioxin-like compounds (DLCs).

• Use PK modeling to define the dos e metric for hepatic effects.

• Use body burden or serum concentrati ons for cardiovascular endpoints. Finally, the Panel recommended th at U.S. EPA finish the reasse ssment quickly and establish a definitive plan to review and incorporate new data as they become available.

References
NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-13 DRAFT

— DO NOT CITE OR QUOTE NTP (National Toxicology Program). 2006. Toxicology and Carcinogenesis Studies of 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) (CAS No. 1746-01-6) in Fema le Harlan SpragueDawley Rats (Gavage Studies). U.S. Department of Health and Human Services. NTP TR 521. Research Triangle Park, NC (April).
U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS Review Draft (EPA/600/P-00/001Cb). U.S. Envi ronmental Protection Agency, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

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SESSION 4A: DOSE-R ESPONSE FOR CANCER The U.S. EPA plans to consider development of a quantitative dose-response assessment for cancer associated with TCDD exposure. Such an assessment would be based on information in U.S. EPA (2003), NAS (2006) and key studies identified in this workshop. The purpose of this session was to identify and discuss key issu es pertaining to dose-re sponse assessment for dioxin-induced cancer.
Session 4A Panelists (Session Co-C hairs are identified by asterisk)

• Lesa Aylward, Summit Toxicology

• Kenny Crump, Louisiana Tech University

• Dale Hattis, Clark University

• *Janet Hess-Wilson, U.S. EPA

• Karen Hogan, U.S. EPA

• Manolis Kogevinas, Centre for Res earch in Environmental Epidemiology

• Marian Pavuk, Agency for Toxic S ubstances and Disease Registry

• Chris Portier, National Institute of Environmental Health Sciences

• Lorenz Rhomberg, Gradient

• Jay Silkworth, General Electric

• *Nigel Walker, National Institute of Environmental Health Sciences

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-chair and represent a synopsis of the panel discussions.


## Key Study Selection The Panel discussed both human and rodent studies. In reviewing the epidemiological data, the Panel agreed the EPA should focus on four cohort studies (Dutch cohort, NIOSH cohort, BASF accident cohort, and Hamburg cohort ) and pointed out that there are numerous updates and reevaluations of data now in the literature and othe rs will be published soon. The Panel stated that it is appropriate for the U.S. EPA to consider the increase in total cancers for modeling human cancer data, howev er, Non-Hodgkin's lymphoma, and lung tumors are the main TCDD-related cancer types seen in humans expos ed to TCDD. The Panel suggested the U.S. EPA focus the quantitative dose-response modeling on the human data.

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— DO NOT CITE OR QUOTE In reviewing the rat data, the Panel identifie d four new NTP rodent cancer bioassays with liver and lungs as the main target organs. Ho wever, they suggested that dose-response modeling efforts should model “all cancers” from these NT P data sets as well and use tumor incidence— not individual rats as measures.

Key Study Selection Criteria The Panel discussed whether data for TCDD onl y should be used or if PCB126 could be used to develop a dose-response curve. From this discussion, the Panel reached a general agreement that limiting the dose-response mode ling and cancer assessment to TCDD only would be the best approach.
Regarding the oral dosing regimens, the Panel discussed the differenc es in results from different bioassays. They conclude d that there were insufficient da ta to pick between oral feed (Kociba et al., 1978) and oral gavage (NTP, 2006) studies, but stated “If all aspects of studies were equal, an oral feed study is preferred.” However, given that current data sets are not equal, they agreed that U.S. EPA should consid er both feed and gavage studies.
The Panel put forth the recommendation that studies that include initiation-promotion model data and TgAC transgenic model data from oral exposure studies should be excluded from the primary category in the key study selection crit eria (Appendix C lists the draft study selection criteria distributed prior to th e meeting). Studies from both cl assifications should be moved to the second tier.
The Panel was also unsupportive of the “res ponse magnitude outside the range of normal variability” criterion, as they did not believe it was appl icable to a cancer endpoint.
Critical Endpoints to Consider The Panel recognized that the MOA for TCDD includes cell growth/differentiation dysregulation, that different endpoi nts (tumor types) across species may be expected, and that there are differences in tumor sites across specie s. The Panel further acknowledged that there is insufficient information to determine if rodent tumor types observed are relevant to humans. Thus, the Panel suggests the following:

• U.S. EPA should consider all the obser ved cancer endpoints in its evaluation.
Nonlinear (aka threshold) Versus Linear Dose-Response Modeling The Panel agreed that NTP bioassays appear to demonstrate nonlinea r dose response, but they expressed concern about using animal data to infer slope and dose response for humans. The Panel pointed out that there are differen ces in slopes across different bioassays, and specifically, that some appear li near while others appear nonli near. Given the observation of both nonlinear vs. linear, the Panel concluded that neither could be rule d out for extrapolation below the POD simply based on the available data . One panelist noted that U.S. EPA Cancer Guidelines (U.S. EPA, 2005) stat e that only if one can demonstrat e that the MOA has a threshold dose-response shape, and can exclude all othe r potential linear MOAs, can one use a nonlinear model. Lastly, the Panel noted that there are da ta and rationales to support use of both linear and

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-15 DRAFT

— DO NOT CITE OR QUOTE nonlinear response below POD. From this discussion, the Panel raised one possibility to the U.S. EPA:

• Both linear and nonlinear model functions s hould be considered in the dose-response analysis.

Dose Metrics In considering human data, the Panel expr essed a preference for lipid-adjusted serum levels over body burden (BB), and they expressed concerns over the assumptions used in the back calculation of the BB in the epidemiologic cohorts. In considering the rat data, the Panel supported the use of BB—especia lly lipid-adjusted BB. The Panel, however, did express concern over the sequestering of TCDD in liver and then the use of liver levels in BB calculations.
Supporting Information—Biologically-Based Dose-Response (BBDR) Models and MOA The Panel discussed BBDR. Though once considered an attractive proposition, BBDR models may mask uncertainty within the models , necessitating them to be used with greater caution. The Panel suggested two issu es for the U.S. EPA to consider:

• If there is a published model, use it if it is valid—do not generate a new model.

• Focus on the actual experimental data to drive the analysis.

References
Kociba, R.J., D.G. Keyes, J.E. Beyer et al. 1978. Results of a two-year chronic toxicity and oncogenicity study of 2,3,7,8-tetrachlorodibenzo- p -dioxin in rats. Toxicol. Appl. Pharmacol. 46:279-303.
NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. NTP (National Toxicology Program). 2006. Toxicology and Carcinogenesis Studies of 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) (CAS No. 1746-01-6) in Fema le Harlan SpragueDawley Rats (Gavage Studies). U.S. Department of Health and Human Services. NTP TR 521. Research Triangle Park, NC (April).
U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS Review Draft (EPA/600/P-00/001Cb). U.S. Envi ronmental Protection Agency, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

. U.S. EPA (U.S. Environmental Protection Agen cy). 2005. Guidelines for Carcinogen Risk Assessment. U.S. Environmental Protection Agency Risk Assessment Forum. EPA/630/P-03/001F.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-16 DRAFT

— DO NOT CITE OR QUOTE SESSION 4B: DOSE-RESPONSE FO R REPRODUCTIVE/DEVELOPMENTAL TOXICITY The U.S. EPA plans to consider development of a quantitative dose-response assessment for reproductive and developmental effects associated with TCDD exposure. Such an assessment would be based on information in U.S. EPA (2003), NAS (2006) and key studies identified in this workshop. The purpose of this session was to identify and discuss key issues pertaining to dose-response assessment for dioxin-induced reproducti ve and developmental effects.
Session 4B Panelists (Session Co-C hairs are identified by asterisk)

• Barbara Abbott, U.S. EPA

• Bruce Allen, Bruce Allen Consulting

• Roger Cooke, Resources for the Future

• George Daston, Procter & Gamble

• Mike DeVito, U.S. EPA

• Rob Goble, Clark University

• *Fumio Matsumura, University of California-Davis

• Paolo Mocarelli, University of Milan

• Brian Petroff, University of Kansas

• *Glenn Rice, U.S. EPA

• Marie Sweeney, National Institute of Occupational Safety and Health

• Mary Walker, University of New Mexico

• Bernie Weiss, University of Rochester

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-Chair and represent a synopsis of the panel discussions.



## A Major Question Posed During this Workshop Session was “Are Human Embryos and Infants Less Sensitive to Dioxin Exposu res Than Some Experimental Animals?” The Panel recognized that animal data show a wide range of species sensitivity to dioxin for a given developmental or reproductive endpoint . Presently, there are data for some endpoints that show that human sensitivity is comparable to experimental animals (e.g., semen quality), and for other endpoints the data demonstrate that humans are insensitiv e compared to other species (e.g., cleft palate). La stly, the Panel recogni zed that there are some endpoints for which relative human sensitivity remains uncertain.
Key Study Selection The Panel reviewed the charge questions (Appendix B), discussed them, and listed two issues for the U.S. EPA to consider:

• Concerning key study determination, use a step wise approach that is dependent upon the information available and need ed to address the question.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-17 DRAFT

— DO NOT CITE OR QUOTE • Concerning the key studies informing the POD and the POD endpoint choice, use the POD to depart from what is certain and use a high-c onfidence study that has found effects at a low enough level at whic h other effects are protected.
The Panel also developed Table 1, based on the in formation presented in this session. Table 1 identifies specific reproductive and developmental effects of concern, listing whether an effect has been observed in test animals and epidemiologic cohorts. It also identifies the ED 10 

## estimated by the U.S. EPA (2003) for health eff ects observed in rodent bioassays. If the U.S. EPA did not report an ED 10 

## for an effect, the table identifies a study where the effect was reported and the lowest study dose where the effect was observed. Table 1 also identifies the epidemiologic cohort where the specific reproduc tive and developmental effects were observed.

Epidemiological Study Utility The Panel reviewed the charge questions (Appendix B), discussed them, and made two suggestions to the U.S. EPA:

• Concerning the ability of epidemiological studi es to inform critical effects, start with concordance across species (including hu mans) for the spectrum of effects.

• Concerning the ability of epidemiological st udies to inform dose-response modeling, start with the epidemiology and then go to animal data if the dose response has not been well characterized for an endpoint of interest and compare to animal data as a reality check.
Animal Model Utility The Panel reviewed and disc ussed the charge questions (Appendix B). Table 1, which identifies the effects that occur in animals and also have relevance to humans, summarizes much of this discussion. Regarding the influence of mode of action (MOA) on animal model choice, the Panel concluded that by evaluating concordance among h ealth effects reported in epidemiologic and animal bioassay data, the U.S. EPA could identify a set of plausible reproductive and developmental effects to c onsider. Actual animal and human MOA information is helpful in that it creates comfor t with the animal models and in defining the boundaries of possible effects.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-18 DRAFT

— DO NOT CITE OR QUOTE TABLE 1
Reproductive/Developmental Effects of Concern for Human Health

Endpoint Rodent (ED 10 

## ng/kg-d) Human Notes

Sperm Count/Motility Yes (6.2

− 28; 66

− 200) Yes ED 10 

### bases Mabley et al. (1992a,b) caudal sperm count and daily sperm production range from 6.2

− 28; Gray et al. (1997) epididymal sperm count and total testis sperm counts range from 66

− 200. Sex Ratio No Yes, Seveso Delayed Puberty Males Yes (94) Yu-cheng ED 10 

### basis rat male puberty delay Gray et al. (1997). Need to qualify epidemiology data because of cohort PCDD/PCDFs exposures. Delayed Puberty in Females Yes No in Seveso Gray and Ostby (2002) report delayed puberty in female offspring of pregnant rats receiving a single dose of 1 μ g TCDD/kg on GD 15. Cleft Palate Yes (6300

− 6400) No ED 10 

### basis Birnbaum et al. (1989).
Premature Senescence Yes No, Seveso Fran czak et al. (2006) report that rats prematurely entered reproductive senescence, after receiving cumulative TCDD doses as low as 1.7 μ g TCDD/kg. They considered first occurrence of prolonged interestrous interval (>6 d) as evidence of onset of reproductive senescence.
Hormones E2 Yes Yes, Males— Seveso Li et al. (1995) repo rt serum estradiol-17 β (E2) concentrations induced by equine Chorionic Gonadotropin injection were significantly elevated in female rats orally administered 10 μ g/kg TCDD on PND 22. While E2 decreased dramatically in control animals during the preovulatory LH surge, it did not in TCDD-treated rats. Low Birth Weight Yes (190) Suggestive effect in Seveso in first 8 years after exposure ED 10 

### basis Gray et al. (1997).

Reproductive Cycling (prolongation) Yes Yes, Seveso Prepubertal exposure Franczak et al. (2006) report loss of normal cyclicity in female rats at 8 months of age following a cumulative dose of 1.7 μ g TCDD/kg.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-19 DRAFT

— DO NOT CITE OR QUOTE Supporting Information The Panel reviewed the charge questions (Appendix B), discussed them, and made two suggestions to the U.S. EPA:

• Concerning deviation from default approaches for noncancer endpoints, there needs to be a careful assessment of the POD and the applic ation of uncertainty factors in light of PK/pharmacodynamics (PD), population char acteristics and va riability, and MOA information.

• Concerning the MOA’s ability to clarify endpoi nt and the incorporation of a cascade of cellular event into dose-response for noncancer endpoint, any study that helps inform the dose response should be considered—inclu ding studies not specific to dioxins. Complicated mechanistic models need not be developed. Standard dose-response models can be applied. One can look at the cascade of events in a stepwise, simple way.

References
Birnbaum, L.S., M.W. Harris, L.M. Stoc king et al. 1989. Retinoic acid and 2,3,7,8- tetrachlorodibenzo-p-dioxin selectively enhance teratogenesis in C57BL/6N mice. Toxicol. Appl. Pharmacol. 98:487-500.
Franczak, A., A. Nynca, K.E. Valdez, K.M. Mizinga and B.K. Petroff. 2006. Effects of acute and chronic exposure to the aryl hydrocarbon receptor agonist 2,3,7,8-tetrachlorodibenzop-dioxin on the transition to re productive senescence in female Sprague-Dawley rats. Biol. Reprod. 74:125-130.
Gray, L.E. and J.S. Ostby. 2002. In utero 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD) alters reproductive morphology and function in female ra t offspring. Toxicol. Appl. Pharmacol. 133(2):285-294.
Gray, L.E., J.S. Ostby and W.R. Kelce. 1997. A dose-response analysis of the reproductive effects of a single gestationa l dose of 2,3,7,8-tetrachlorodibenzo -p-dioxin in male Long Evans Hooded rat offspring. Toxicol. Appl. Pharmacol. 146:11-20.
Li, X., D.C. Johnson and K.K. Rozma n. 1995. Reproductive effects of 2,3,7,8- tetrachlorodibenzo-p-dioxin (TCDD) in female rats: ovulation, hormonal regulation, and possible mechanism(s). Toxicol. A ppl. Pharmacol. 133:321-327.
Mably, T.A., D.L. Bjerke, R. W. Moore et al. 1992a. In utero and lactational exposure of male rats to 2,3,7,8-tetrachlorodibe nzo-p-dioxin. 3. Effects on spermatogenesis and reproductive capability. Toxicol. Appl . Pharmacol. 114:118-126.
Mably, T.A., R.W. Moore, R.W. Goy et al. 1992b. In utero and lactational exposure of male rats to 2,3,7,8-tetrachlorodibenzo- p-dioxin. 2. Effects on sexual be havior and the regulation of luteinizing hormone secretion in adulthood. Toxicol. Appl. Pharmacol. 114:108-117.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-20 DRAFT

— DO NOT CITE OR QUOTE NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. NAS Review Draft (EPA/600/P-00/001Cb). U.S. Envi ronmental Protection Agency, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

.

SESSION 5: QUANTITATIVE UNCERTAI NTY ANALYSIS OF DOSE-RESPONSE This session addressed the uncertainty analys is to be considered for the dose-response assessments. The session opened with a presen tation on current estima tes of dioxin exposure levels. Then it focused on the factors to include in the scope of an uncerta inty analysis including dioxin kinetics.
Session 5 Panelists (Session Co-Cha irs are identified by asterisk)

• Bruce Allen, Bruce Allen Consulting

• Lesa Aylward, Summit Toxicology

• Roger Cooke, Resources for the Future

• Kenny Crump, Louisiana Tech University

• Mike DeVito, U.S. EPA

• Dale Hattis, Clark University

• *Rick Hertzberg, Biomath Consulting

• Nancy Kerkvliet, Oregon State University

• Leonid Kopylev, U.S. EPA

• Rob McDowell, U.S. Department of Agriculture

• Lorenz Rhomberg, Gradient

• Woody Setzer, U.S. EPA

• Marie Sweeney, National Institute of Occupational Safety and Health

• *Linda Teuschler, U.S. EPA

Please note that the use of the term “concluded” or “rec ommended” in this summary does not mean that a consensus was reached. Session Summaries were written from the material prepared by the non-EPA/ANL Co-Chair and represent a synopsis of the panel discussions. 

## The Panel summarized the NAS comments rega rding uncertainty. Areas for improvement include:

• Ensure “transparency, thoroughness, and clar ity in quantitative uncertainty analysis

. ”

• Describe and define (quantitat ively to the extent possible) the variability and uncertainty for key assumptions used for each key endpoi nt-specific risk assessment, including choices of data set, point of departur e, dose-response model, and dose metric.

• Incorporate probabilistic m odels to represent the range of plausible values.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-21 DRAFT

— DO NOT CITE OR QUOTE • Assess goodness-of-fit of dose-response models.

• Provide upper and lower bounds on central tenden cy estimates for all statistical estimates.

• When quantification is not possible, clearly st ate it, and explain what would be required to achieve quantification.
Identification of Important Uncertainties The Panel reviewed the charge questions (Appendix B), discussed them, and listed eight issues for consideration by the U.S. EPA:

• Concerning species and strain differences in the U.S. EPA’s Response to NAS, current U.S. EPA procedures do not take this into ac count when selecting one data set for risk assessment. Issues include “Where are human s in the distribution of potencies that can be generated? How likely is it that human re sponse is similar to the selected data? Can we infer inter-individual variability from these differences?”

• Concerning the use of animal data for cross species extrapolation to humans (PK and PD uncertainties), issues to consider include differences in distribution and responses following bolus doses from those of subchroni c and chronic protocol s; uncertainty in liver doses due to sequestration; differen ces in receptor bi nding affinity among congeners; and age factors (e.g., assumption of a lifetime constant daily dose for a cancer extrapolation).

• Concerning the description of AhR response, biochemical changes occur at lower doses than toxicological changes. There should be an effort to identify the biochemical changes that would mark Ah receptor binding to inform the BMR, and, thus, prevent toxicity.

• Concerning model uncertainty, the mathematical model choice depends on endpoint. There should be an effort towards determini ng what is the most se nsitive endpoint(s) for humans and conducting animal studies to model that endpoint(s).

• Concerning exposure and dose response in hum an studies, ensure enough similarity to current human exposure profiles (mixture composition) so that a dose-response assessment can be done. Incorporate new epidemiological studies. Evaluate concordance with animal data and consis tency across studies. Panel-acknowledged uncertainties include exposure estimates fr om person to person, shape of human doseresponse curve, healthy worker effect, and age dependence.

• Concerning POD determination, uncertainty factors are i nherently mathematically inconsistent and that should be conveyed in the discussion of uncertainties when interpreting the POD.

• Concerning dose metric, tissue c oncentration is preferred. It should be evaluated against a background of variability in AhR-binding ex pression. There is uncertainty in what level of binding should be considered, in different cell types, tissues, life stage (development). The relationship between dose metric and causation of adverse effects should be examined.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 A-22 DRAFT

— DO NOT CITE OR QUOTE Low-Dose Extrapolation The Panel reviewed the charge questions and discussed them (Appendix B). The Panel concluded that curve-fitting uncer tainty (for a given dataset, dose metric, and model) can be characterized and is useful, but, by itself, it is an incomplete characterization of uncertainty. The Panel acknowledged the difficulty of fully charac terizing uncertainty, especially quantitatively. Some panelists argued that the problem is in surmountable and that no meaningful uncertainty analysis is likely to be performable. Other panelists contended that, the difficulties notwithstanding, “good-faith” efforts to do somethi ng practical and forthright to characterize uncertainty in low-dose extrapolat ion would be useful and import ant. The Panel clarified “good faith” as meaning a characterization that is usef ul and not misleading to decision makers and is inclusive of approaches that have meaningful su pport in the scientific community as a whole. Being in “good faith” is more important than being complete (i.e., addressing every uncertain element), especially since comple teness is not a realistic goal. From this discussion, the Panel listed four issues for consideration by the U.S. EPA:

• Review alternative data sets, dose metrics, and models to see where consequential uncertainties and impacts on lo w-dose implications arise.

• Consider the impacts of choices among plau sible alternative data sets, dose metrics, models, and other more qualitative choices —issues include how much difference the choices make and also how much relative cred ence should be put to ea ch alternative as a way of gauging and describing th e landscape of imperfect knowledge regarding possibili ties for the true dose-response.

 Hard to do quantitatively, since the factor s are not readily expressed as statistical distributions, but can describe the rationale for believing/ doubting each alternative in terms of available supporti ng evidence, contrary eviden ce, and needed assumptions.

 Expert judgment methods may be helpful in characterizing the relative weights of scientific credibility among alternatives. The expert judgment process, when conducted systematically, can be thought of as adding data to the assessment of credibility of alternatives, rather than as just an opinion poll.

 Information on plausibility of alternativ e low-dose extrapolation approaches can come from external considerations of mode of action, and not just from statistical success at fitting particular (high-dose) data sets.

• Characterizing uncertainty through a variety of approaches could be tried, and their relative merits and shortcomings discussed, as a way forward.

• Consider the sources of potent ial error, particularly in epidemiological data (e.g., TEF uncertainty and variation in congener mixtur es) and if possible qua ntify their impact on the dose-response assessment.
Considerations for Conducting Uncertainty Analysis Overall, the Panel was split on whether U. S. EPA should do quantitative uncertainty analyses. The Panel noted that if done on only so m e of the uncertainties, then results would be misleading and could be misused. Ultimately, the Panel listed seven issues for consideration by the U.S. EPA:

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— DO NOT CITE OR QUOTE • The Panel recapped what some consider as bei ng the first integrated risk assessment, with structured expert judgment and uncertain ty analysis, i.e., the Rasmussen Report (WASH-1400; U.S. Nuclear Regulatory Commission, 1975). In their discussion of the report, the Panel noted that in addition to standard event tree/fault tree modeling, this report also tackled difficult model uncertainty issues involved in accident progression, dispersion of released pollutants in the atmo sphere, environmental transport, exposure, health, and economic impacts. And though th e Panel also recognized that this method was no longer state-of-the-art, the Panel conten ded that it represents a good example of a structured approach and methodolog y that could be built upon.

• The Panel also discussed TEQs used in ep idemiological studies, based on intake, and recognized that the key uncertainty in what was measured was not just intake but also involved PK/PD issues. The Panel acknowledged that the TEQ system is regularly used on a concentration basis, but they expressed co ncern that the qualification becomes lost. TEQs ignore pharmacokinetics and the comm on practice of rounding to orders of magnitude introduces more error.

• Structure the risk assessment along MOA st eps—identify key biochemical measures (~5

− 10) common across toxic endpoi nts and identify the degree of meaningful change in effect or effect variance. Make a table with all options for data set, model, etc.; make best estimates/choices and determine which of these choices matter the most to the

answer.

• Use expert panels—expert judgment can be collected scientifically (procedures are published). But there are known biases; centr al tendency estimates work much better than extremes.

• Use supporting studies to fill in critical data gaps—Info filling methods do exist (e.g., PK modeling). Put short-term studies into the “supporting info” category (unless, of course, the risk assessment is for acute exposures, such as chemical spills).

• Be creative in the analysis of uncertainty. Intermediate steps between AhR binding and the end processes can be hypothesized based on data, experiences, and analogies related to other chemicals.

• The 2003 Reassessment presented potency estimates on wide variety of endpoints/models; needed to be more transparen t in that discussion. Statistical graphics can be used to convey uncertainties.

Reference
U.S. Nuclear Regulatory Commission. 1975. Reactor Safety Study: An Assessment of Accident Risks in U.S. Commercial Nuclear Power Pl ants. WASH-1400 (NUREG -75-014). Washington, DC.

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— DO NOT CITE OR QUOTE APPENDIX A: 2009 U.S. EPA DI OXIN WORKSHOP AGENDA

SCIENTIFIC WORKSHOP TO INFORM THE TECHNICAL WORK PLAN FOR U.S. EPA’S RESPONSE TO NAS COMMENTS ON THE HEALTH EFFECTS OF DIOXIN PRESENTED IN U.S. EPA’S DIOXIN REASSESSMENT
Cincinnati, OH
Date: February 18

− 20, 2009

BACKGROUND/WORKSHOP OBJECTIVE

At the request of the U.S. Environmental Protection Agency (U.S. EPA), the National Academy of Sciences (NAS) prepared a report, Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment (NAS, 2006), that made a number of recommendations to improve the U.S. EPA’ s risk assessment for 2,3,7,8-tetrachlorodibenzop -dioxin (TCDD). In response, the U.S. EPA w ill prepare a technical report that addresses key comments on the dose-response assessment for TCDD. The U.S. EPA intends to develop its response through a transparent process that provides multiple opportunities for input.
To assist in this effort, a Workshop will be held to inform the U. S. EPA’s evaluation of the NAS recommendations. The Workshop will be open to the public. At the Workshop, the U.S. EPA will solicit input from e xpert scientists and the public.
The goal of the Workshop is to ensure th at the U.S. EPA’s response to the NAS comments focuses on the key issues and reflects the most meaningful science. The three main objectives of the Workshop are to (1) identify and discu ss the technical challenges involved in addressing the NAS key comments on the TCDD dos e-response assessment in the U.S. EPA Reassessment (U.S. EPA, 2003), (2) discuss approaches for addressing these comments, and (3) identify key published, independe ntly peer-reviewed literature, particularly studies describing epidemiologic and in vivo mammalian bioassays, which are ex pected to be most useful for informing the U.S. EPA response.
Workshop participants will be encouraged to think broadly about the body of scientific information that can be used to inform the U. S. EPA’s response and to participate in open dialogue regarding ways in which the science can best be used to address the key dose-response issues. This Workshop is similar to scientif ic workshops being conducted under the new review process for the National Ambient Air Quality Standards (NAAQS) 1 

## that assess health-related information for criteria pollutants.

1 

### Please see http://www.epa.gov/ttn/naaqs/ for more information on the new NAAQS review process.

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— DO NOT CITE OR QUOTE The Workshop discussions are expected to build upon two prior publications:
1. Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds (U.S. EPA, 2003). This external review draft provides a com prehensive reasse ssment of dioxin exposure a nd human health effects. This “dioxin reassessment” was submitted in October 2004 to the National Academy of Sciences (NAS) for review.
2. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment (NAS, 2006).
Workshop participants are encouraged to review both of these documents and other relevant materials (e.g., the National Toxicol ogy Program report on TCDD [NTP, 2006]) before the meeting because they provide important insi ghts into the key quest ions and challenges. There are a number of open comment periods that are intended to facilitate a broad discussion of the issues.
Scientists with significant e xpertise and experien ce relevant to the health effects of TCDD or dioxin-like compounds and associated topics will be aske d to serve on “expert panels” for discussions throughout the Workshop. Workshop panelists will include a wide range of experts representing many scie ntific areas needed to a ssess TCDD dose-response (e.g., epidemiology, human and animal toxicology, nuc lear receptor biology, dose-response modeling, risk assessment, and uncertainty analysis). The Workshop paneli sts will be asked to highlight significant and emerging research and to make recommendations to the U.S. EPA regarding the design and scope of the technical response to NAS comments on the dose-response analysis for TCDD—including, but not limited to, recommendations for evaluating associated uncertainty. Open comment periods will follow each panel disc ussion session. Public participation will be encouraged by way of these designated open comm ent periods and, also, by participation in the scientific poster session planned fo r the second evening (February 19).
U.S. EPA will use the input received duri ng this Workshop as the foundation for its development of a technical work plan for re sponding to the NAS co mments on the TCDD doseresponse analysis. The work plan will outlin e the schedule, process, and approaches for evaluating the relevant scientific information and addressing the key issues. The work plan also will identify the key litera ture to be utilized in U.S. EPA’s response.
As a follow-on activity to this Workshop, a pa nel is being establis hed under the Federal Advisory Committee Act (FACA) to guide a nd review the U.S. EPA’s response to NAS comments. The FACA panel will be asked to conduct a consultation with the Agency on the draft technical work plan. At the same time, th e public will also have the opportunity to provide comments to the FACA panel on the work plan. The final technical work plan will guide the development of the technical report that will constitute the U.S. EPA’s response to NAS comments. During the development of this response, the U.S. EPA will seek advice from the FACA panel and the public several times. Finally, the FACA panel will be asked to review the technical report in a public forum.
The preliminary Agenda presented on the fo llowing pages may be revised prior to the Workshop following review by the session Co-Cha irs; the dates and general timing of the

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— DO NOT CITE OR QUOTE sessions, however, will not change. A final Age nda and a set of charge questions, intended to provide general direction for the Workshop discu ssions, will be posted on the Workshop Internet site ( http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm ?deid=199923 ) prior to the meeting.

A poster session will be held on the eveni ng of the second day (February 19). The purpose of this poster session is to provide a fo rum for scientists to present recent studies relevant to TCDD dose-response assessment a nd to encourage open discussion about these presentations.

REFERENCES

NAS (National Academy of Sciences). 2006. Health Risks from Dioxin and Related Compounds: Evaluation of the EPA Reassessment. National Academies Press, Washington, DC (July). Available at http://www.nap.edu/cat alog.php?record_id=11688

. NTP (National Toxicology Program). 2006. Toxicology and Carcinogenesis Studies of 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) (CAS No. 1746-01-6) in Fema le Harlan SpragueDawley Rats (Gavage Studies). U.S. Department of Health and Human Services. NTP TR 521. Research Triangle Park, NC (April).
U.S. EPA (U.S. Environmental Protection Agency). 2003. Exposure and Human Health Reassessm ent of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds, NAS review draft, Volumes 1-3 (EPA/600/P-00/001Cb, Volume 1). U.S. Environmental Protection Agency, National Center for Environmenta l Assessment, Washington, DC (December). Available at http://www.epa.gov/nceawww1/ pdfs /dioxin/nas-review/

.

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— DO NOT CITE OR QUOTE WORKSHOP AGENDA



# Day 1

8:00–9:00 Registration

9:00–9:30 Welcome/Purpose of Meeting/Document Development Process

9:30–9:45 Panel Comments/Questions on Charge



# 9:45–2:45 Session 1: Quantitative Do se-Response Modeling Issues (Hall of Mirrors)

9:45–10:10 Background/Introductory Remarks

10:10–10:35 TCDD Kinetics: Converting Administered Doses in Animals to Human Body Burdens Presenter: Michael Devito

10:35–11:30 Panel Discussion

11:30–1:00 Lunch

1:00–2:00 Panel Discussion cont.

2:00–2:45 Open Comment Period



# 2:45–3:05 Break

3:05–5:15 Session 2: Immunotoxicity (Hall of Mirrors)

3:05–3:15 Background/Introductory Remarks

3:15–4:45 Panel Discussion

4:45–5:15 Open Comment Period

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— DO NOT CITE OR QUOTE 

# Day 2

8:00–8:30 Report-Outs for Sessions 1 and 2 (Hall of Mirrors)

8:00–8:15 Report-Out for 1: Quantitative Dose-Response Modeling Issues

8:15–8:30 Report-Out for 2: Immunotoxicity



# 8:30–11:30 Sessions 3A and 3B (concurrent sessions)

8:30–11:30 Session 3A: Dose-Response for Neurotoxicity and Nonreproductive Endocrine Effects (Hall of Mirrors)

8:30–8:45 Background/Introductory Remarks

8:45–11:00 Panel Discussion

11:00–11:30 Open Comment Period



# 8:30–11:30 Session 3B: Dose-Response for Cardiovascular Toxicity and Hepatotoxicity (Rookwood Room)

8:30–8:45 Background/Introductory Remarks

8:45–11:00 Panel Discussion

11:00–11:30 Open Comment Period



# 11:30–1:00 Lunch

1:00–2:00 Report-Outs for Sessions 3A and 3B (Hall of Mirrors)
The structure of the session report-outs will include the following:

 

## Summary of session presenta tion including minority opinion

 

## Public comments

 

## Discussion

1:00–1:15 Report-Out for 3A: Dose-Response for Neurotoxicity and Nonreproductive Endocrine Effects

1:15–1:30 Open Comment Period

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— DO NOT CITE OR QUOTE 1:30–1:45 Report-Out for 3B: Dose-Respons e for Cardiovascular Toxicity and Hepatotoxicity

1:45–2:00 Open Comment Period



# 2:00–5:15 Sessions 4A and 4B (concurrent sessions)

2:00–5:15 Session 4A: Dose-Response for Cancer (Hall of Mirrors)

2:00–2:15 Background/Introductory Remarks

2:15–4:45 Panel Discussion

4:45–5:15 Open Comment Period



# 2:00–5:15 Session 4B: Dose-Response for Reproductive/Developmental Toxicity (Rookwood Room)

2:00–2:15 Background/Introductory Remarks

2:15–4:45 Panel Discussion

4:45–5:15 Open Comment Period



# 6:45–8:15 Poster Session (Rosewood Room)



# Day 3

8:30–9:30 Report-Outs for Sessions 4A and 4B (Hall of Mirrors)

8:30–8:45 Report-Out for 4A: Dose-Response for Cancer

8:45–9:00 Open Comment Period

9:00–9:15 Report-Out for 4B: Dose-Response for Reproductive/Developmental Toxicity

9:15–9:30 Open Comment Period

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— DO NOT CITE OR QUOTE 

# 9:30–3:30 Session 5: Quantitative Uncertainty Analysis of DoseResponse (Hall of Mirrors)

9:30–9:40 Background/Introductory Remarks

9:40–10:10 Evidence of a Decline in Background Dioxin Exposures in Americans Between the 1990s and 2000s Presenter: Matt Lorber



# 10:10–10:30 Break

10:30–11:30 Panel Discussion

11:30–1:00 Lunch

1:00–2:15 Panel Discussion cont.

2:15

− 2:30 Break

2:30–3:00 Open Comment Period

3:00–3:15 Report-Out for 5: Quantitative Uncertainty Analysis of DoseResponse

3:15–3:30 Closing Remarks



# 3:30 Adjourn

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— DO NOT CITE OR QUOTE APPENDIX B: 2009 U.S. EPA DIOXIN WORKSHOP

QUESTIONS TO GUIDE PANEL DISCUSSIONS

SESSION 1

Dose Metric Considering all of the endpoints or target tissues, and species that U.S. Environmental Protection Agency (U.S. EPA)’s dose-response modeling might evaluate, what are the best measures of dose (e.g., ingested, tissue concentrations, body bur den, receptor occupancy, other surrogate) and why?

Developing Dose-Response Mode ls from Mammalian Bioassays How best can the point of de parture (POD) be determined when the response range is incompletely characterized (i.e., high response at the lowest dose or low response at the highest dose; observed in several key 2,3,7,8-Tetrachlo rodibenzo-p-Dioxin [T CDD] studies)?
If considered to be biologically plausible, how can a threshold be incorporated into a doseresponse function (e.g., for TCDD cancer data)?
How can nonmonotonic responses be incorpor ated into the dose -response function?

Developing Dose-Response Models from Epidemiological Studies How can the epidemiological data be utilized best to inform the TCDD exposure-response modeling? Which epidemiological studies are most relevant?

Supporting Information For those toxicological endpoints th at are Ah receptor-mediated, how would the receptor kinetics influence the shape of the dose-response curve? How would downstream cellular events affect the shape of the dose-response curve? How can th is cascade of cellular events be incorporated into a quantitative model of dose-response?

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— DO NOT CITE OR QUOTE SESSIONS 2, 3A, 3B, 4A, AND 4B
Key Study Selection For this endpoint, what refinements should be ma de to the draft criteria for selection of key studies?
What are the specific effects of concer n for human health for this endpoint?

Based on the draft criteria for the selection of key studies, what are the key studies informing the shape of the dose-response curv e above the POD and the choice of the POD for this endpoint?

Epidemiological Study Utility How and to what extent do the epidemiological data inform the choice of critical effect?
How can the epidemiological data inform the quantitative dose -response modeling?

Animal Model Utility Are there types of effects observed in animal mo dels that are more relevant to humans than others? To what extent does information on mode of action (MOA) influence the choice of animal model (species, strain, sex)?

Supporting Information
Are there studies that establish a sufficient justif ication for departure from the default procedures that address the shape of the dose-response curve below the POD under the cancer guidelines?
Are there studies that establish a sufficient just ification for departing from U.S. EPA’s default approaches for noncancer endpoints?
To what extent can MOA information clarify th e identification of endpoints of concern and doseresponse metric for this endpoint? How can the cascade of cellular events for this endpoint be incorporated into a quantita tive model of dose response?

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— DO NOT CITE OR QUOTE SESSION 5
For cancer and noncancer TCDD dose-response a ssessments, U.S. EPA is interested in developing a quantitative uncertain ty analysis addressing both pa rameter and model uncertainty, if feasible. Uncertainties will include, among others, choice of endpoint; underlying study uncertainties; choice of dose metric; interspecies extrapolations such as kinetic uncertainties; and choice of dose-response model, including thre shold models. The U.S. EPA is currently examining techniques and tools for uncertainty analysis—including Bayesian and frequentist approaches.

Identification of Important Uncertainties What are the major uncertainties pertai ning to modeling the animal data? Consider the dose metric (species or tissu e specificity), vehicle of administration, exposure frequency, exposure duration, and POD determination (e.g., benchmark response selection or no-observed-adverse-eff ect level/lowest-observed-adverse-effect level identification).
What are the major uncertainties pertaining to dose-response modeli ng below the POD? Consider how receptor kinetics and downstream cellular event information might be used to bound the uncertainties associated with dose-response modeling below the POD.
What are the major uncertainties in cross-sp ecies extrapolation (e.g., half-lives, tissue distribution, and toxicodynamics)? Consider the primary species dosed with TC DD: mice, hamsters, rats, guinea pigs, and monkeys.
What are the major uncertainties pertaining to intrahuman variability? Consider what data sets would be usef ul to represent sensitive subpopulations.
What are other significant sources of uncerta inty for the cancer and noncancer assessments?

Considerations for Conducting Uncertainty Analysis What data sets could be used to quantify uncertainties in cancer and noncancer TCDD doseresponse assessments? Consider dioxin-like compound dose-response data. Consider MOA information.
What are the appropriate techni ques for the TCDD dose-response un certainty analysis, and what are their respective strengths and weaknesses of these approaches as applied to TCDD?

## This document is a draft for review purpos es only and does not constitute Agency policy 1/15/10 A-34 DRAFT: DO NOT CITE OR QUOTEAPPENDIX C: 2009 U.S. EPA DIOXIN WORKSHOPDRAFT SELECTION CRITERIA TO IDENTIFY KEYINVIVOMAMMALIAN STUDIES THAT INFORM DOSE-RESPONSE MODELING FOR2,3,7,8-TETRACHLORODIBENZO- p-DIOXIN (TCDD)aSelection RationaleStudy FeaturePrimarybSecondarycCurrently ExcludedChemical, purity,matrix/mediumTCDD-only doses included, purity specified,matrix in which TCDD is administered is identifiedTCDD purity or matrix not clearly identifiedStudies of dioxin-like compounds(DLCs) or mixturesPeer reviewIndependently peer-reviewed, publicly available Supplementary materials accompanyingpeer-reviewed publicationNot formally peer-reviewed; literaturenot publicly availableStudy design,execution, andreportingClearly documented and consistent with standardtoxicological principles, testing protocols,and practice (i.e., endpoint-appropriate,particularly for negative findings)Testing protocol provides incompletecoverage of relevant endpoint-specificmeasures, particularly for negative findingsStudies not meeting standardprinciples and practicesStudy subject:species, strain, andsensitivity for givenendpoint; litter; lifestage; genderMammalian speciesStrain and gender identifiedAnimal age at beginningof treatment identifiedLitter confounders (within/between) accounted forMammalian species,in vivo, but onlystudying an artificially sensitive subject(e.g., knockout mouse)Non-mammalian or notin vivoExposure routeOralParenteral (e.g., intravenous, intramuscular,intraperitoneal, subcutaneous)Inhalation, dermal, ocularDose levelLowest dose≤200 ng/kg-d for noncancerendpoints and≤1μg/kg-d for cancerLowest dose >200 ng/kg-d for noncancerendpoints, or >1.0μg/kg-d for cancerExposure frequency,duration, and timingDosing regimen characterized and explainedCharacterization/explanationmissing or cannot be determinedControlsAppropriate and well characterizedEffect reported, but with no negative controlResponseEffect relevant to human healthMagnitude outside range of normal variabilityPrecursor effects, or adaptive responsespotentially relevant to human healthLethalityStatistical evaluationClearly described and appropriate to the endpointand study design (e.g., per error variance,magnitude of effect)Limited statistical contextaNAS (2006) commented that the selection of data sets for quantitative dose-response modeling needed to be more transparent. These draft criteria areoffered for consideration at the kickoffworkshop. These criteria would be used toidentify candidate studiesof non-human mammals that would be used todefine the point-of-departure (POD). Thesecriteria are not designed forhazard identification or weight-of-evidence determinations. Studies addressing dataother than direct TCDD dose-response in mammals (including toxicokinetic data on absorption, distribution, metabolism, or elimination; information onphysiologically-based pharmacokinetic [PBPK] modeling, and mode of action data) will be evaluated separately.bPresents preliminary draft criteria for evaluating a study being considered for estimating a POD in a TCDD dose-response model.cPresents preliminary draft criteria thatcould qualify a study as primary with support from other lines of evidence (e.g., PBPK modeling), when no study for anendpoint meets the “primary” criteria.

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX B

Evaluation of Cancer and Noncancer Epidemiological Studies for Inclusion in TCDD Dose-Response Assessment

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-ii CONTENTS—Appendix B: Evaluation of Ca ncer and Noncancer Epidemiological Studies for Inclusion in TCDD Do se-Response Assessment

LIST OF TABLES.................................................................................................................

.... B-iii

APPENDIX B. EVALUATION OF CANCER AND NONCANCER EPIDEMIOLOGICAL STUDIES FOR INCLUSION IN TCDD DOSE-RESPONSE ASSESSMENT

................................................................... B-1 B.1. EVALUATION OF CANCER STUDIES.............................................................. B-1 B.1.1. NIOSH Cohort Studies ............................................................................... B-1 B.1.2. BASF Cohort Studies.................................................................................. B-8 B.1.3. The Hamburg Cohort ................................................................................B-11 B.1.4. The Seveso Cohort Studies ....................................................................... B-16 B.1.5. The Chapaevsk Study ...............................................................................B-22 B.1.6. The Air Force Health (“Ranch Hands”) Study ......................................... B-23 B.1.7. Other Studies of Potential Re levance to Dose-Response Modeling

......... B-26 B.2. EVALUATION OF NONCANCER STUDIES ................................................... B-31 B.2.1. NIOSH Cohort .......................................................................................... B-31 B.2.2. BASF Cohort ............................................................................................ B-33 B.2.3. Hamburg Cohort ....................................................................................... B-35 B.2.4. The Seveso Women’s Health Study ......................................................... B-36 B.2.5. Other Seveso Noncancer Studies.............................................................. B-45 B.2.6. Chapaevsk Study....................................................................................... B-54 B.2.7. Air Force Health (“Ranch Hands”) Study ................................................ B-55 B.2.8. Other Noncancer Studies of Dioxin..........................................................B-56 B.3. REFERENCES ..................................................................................................... B-60

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— DO NOT CITE OR QUOTE B-iii LIST OF TABLES
B-1. Fingerhut et al., 1991—All cance r sites, site-specific analysis

................................... B-1 B-2. Steenland et al., 1999—All cancer si tes com bined, site-specific analysis .................. B-2 B-3. Steenland et al., 2001— All cancer sites com bined...................................................... B-4 B-4. Cheng et al., 2006—All cancer sites combined........................................................... B-5 B-5. Collins et al., 2009—All cancer site s com bined, site-specific analysis....................... B-6 B-6. Zober et al., 1990—All cancer site s com bined, site-specific analysis......................... B-8 B-7. Ott and Zober, 1996—All cancer sites combined........................................................ B-9 B-8. Manz et al., 1991—All cancer site s com bined, site-specific analyses ...................... B-11 B-9. Flesch-Janys et al., 1995; Flesch-Jan ys et al., 1996 erratum —All cancer sites combined.................................................................................................................... B-12 B-10. Flesch-Janys et al., 1998—All cancer sites com bined, site-specific analysis ........... B-13 B-11. Becher et al., 1998—All cancer sites com bined........................................................ B-14 B-12. Bertazzi et al., 2001—All cancer site s com bined, site-specific analyses .................. B-16 B-13. Pesatori et al., 2003—All cancer si tes com bined, site-specific analyses................... B-17 B-14. Consonni et al., 2008—All cancer si tes com bined, site-specific analyses ................ B-18 B-15. Baccarelli et al., 2006—Site-specific analysis........................................................... B-19 B-16. Warner et al., 2002—B reast cancer incidence

........................................................... B-21 B-17. Revich et al., 2001—All cancer site s com bined, and site-specific analyses ............. B-22 B-18. Akhtar et al., 2004—A ll cancer sites com bined and site-specific analyses............... B-23 B-19. Michalek and Pavuk, 2008—All cancer sites combined

........................................... B-24 B-20. ‘t Mannetje et al., 2005—All cancer sites com bined, site specific analyses ............. B-26 B-21. McBride et al., 2009b—All cancer si tes com bined, site-specific analysis................ B-27 B-22. McBride et al., 2009a—All cancer si tes com bined, site-specific analysis ................ B-28 B-23. Hooiveld et al., 1998—All cancer si tes com bined, site-specific analysis ................. B-29 B-24. Steenland et al., 1999—Mortality (noncancer).......................................................... B-31 B-25. Collins et al., 2009—Mortality (noncancer).............................................................. B-32

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— DO NOT CITE OR QUOTE B-iv LIST OF TABLES (continued)
B-26. Ott and Zober, 1996—Mortality (noncancer)............................................................ B-33 B-27. Flesch-Janys et al., 1995; Flesch-Janys et al., 1996 erratum —Mortality (noncancer) ................................................................................................................ B-35 B-28. Eskenazi et al., 2002a—Men strual cycle characteristics ........................................... B-36

B-29. Eskenazi et al., 2002b—Endom etriosis ..................................................................... B-37 B-30. Eskenazi et al., 2003—Birth outcomes...................................................................... B-39 B-31. Warner et al., 2004—Age at menarche...................................................................... B-40

B-32. Eskenazi et al ., 2005—Age at m enopause................................................................. B-41 B-33. Warner et al., 2007—Ovarian function...................................................................... B-42

B-34. Eskenazi et al ., 2007—Uterine leiomyom a ............................................................... B-43 B-35. Mocarelli et al., 2008—Semen quality ...................................................................... B-45 B-36. Mocarelli et al., 2000—Sex ratio............................................................................... B-46 B-37. Baccarelli et al., 2008— Neonatal th yroid function ................................................... B-47 B-38. Alaluusua et al., 2004—Oral hygiene........................................................................ B-48 B-39. Bertazzi et al., 2001—M ortality (Noncancer) ........................................................... B-50 B-40. Consonni et al., 2008—Mortality (Noncancer) ......................................................... B-51 B-41. Baccarelli et al., 2005—Chloracne ............................................................................ B-52 B-42. Baccarelli et al, 2002 an d 2004—Immunological effects.......................................... B-53 B-43. Revich et al., 2001—Mortality (noncancer) and reproductive health

....................... B-54 B-44. Michalek and Pavuk, 2008—Diabetes....................................................................... B-55 B-45. McBride et al., 2009a—Mortality (Noncancer)......................................................... B-56 B-46. McBride et al., 2009b—Mortality (noncancer) ......................................................... B-58 B-47. Ryan et al., 2002—Sex ratio...................................................................................... B-59

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— DO NOT CITE OR QUOTE B-1 APPENDIX B. EVALUATION OF CANCER AND NONCANCER 1 EPIDEMI OLOGICAL STUDIES FOR INCLUSION IN TCDD 2 DOSE-RESPONSE ASSESSMENT 3 4 5 B.1. EVALUATION OF CANCER STUDIES 6
B.1.1. NIOSH Cohort Studies 7
8 Table B-1. Fingerhut et al., 1991— All ca ncer sites, site-specific analysis 9 10
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The data sources to ascertain vital status and cause of death information were the Social Security death file s, the National Death Index, and the Internal Revenue Service. Vital status could be determined for 98% of the cohort. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. While the authors provide compelling arguments that suggest risks are not unduly biased by lack of cigarette smoking data, they acknowledge potential biases that could exist for other occupational exposure (e.g., asbestos) for which data were lacking. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. There was not a statistically significant linear trend of increasing mortality with increased duration of exposure. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration not satisfied. This study used duration of exposure, at an individual level, as a surrogate measure of TCDD. Duration of expos ure determined by numb er of years workers were involved in processes involving TCDD contamination. Exposure was determined by reviewing, at each plant, operating conditions, jo b duties, records of TCDD levels in industrial hygiene samples, intermediate reactants, pro ducts, and wastes. Exposure assessment was limited and the uncertainty related to exposure measures not fully addressed. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. This is the larges t of the occupational cohorts that has been exposedto TCDD. The cohort consisted of 5,172 workers and a total of 265 cancer deaths. Sitespecific mortality analyses, in cluding soft tissue sarcoma ( n = 4), was limited by small numbers.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-2 Response Criteria satisfied. New England Journal of Medicine, 1991; 324:212–218. Authors address the possibility of bias from lack of control for potential confounders such as smoking and other occupational exposures. They address limitations of using death certificates for identifying certain causes of deaths, and limitations of using duration of employment as an exposure metric. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. Si nce this study used duration of exposure as the exposure metric, doseresponse relationships cannot be quantified. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Models incorporated period of latency, and a surrogate measure of cumulative TCDD exposure was modeled. The follow-up interval was sufficiently long (1942–1987).

Conclusion Overall, quantitative exposure data are lacking on an individual-level basis. Further doseresponse analysis should consider updated data for this cohort that includes serum-based measures of TCDD, in addition to an extension of the follow-up period. Given these limitations, this study is not further evaluated for TCDD dose-response assessment. 

## 1 2 Table B-2. Steenland et al., 1999—All cancer sites combined, site-specific 3 analysis 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The study evalua ted mortality from all cancer sites (combined). As described in the paper, the sources of vital status and cause of death information were received from the Social Security death files, the Na tional Death Index, and the Internal Revenue Service. Vital status was known for 99.4% of the cohort members, cause of death information is available for 98% of the decedents. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Occupational exposure to asbestos and 4-aminobiphenyl contributed to some excess cancer, but no evidence of confounding for the relationship between TCDD and all cancer mortality was detected following removal of workers who died of bladder cancer. No information is available for cigarette smoking, although dose-response patterns were stronger for nonsmoking related cancers. This finding suggests that smoking is not responsible for excess cancer risk that was observed in the cohort. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. When a 15-year lag interval was incorporated into the exposure metric a statistically significant dose-response pattern was observed for all cancer sites combined with both a con tinuous measure of TCDD ( p = 0.05) as well as one that was logtransformed ( p < 0.001).

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-3 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. The study cond ucted detailed sensitivity analyses and evaluated different assumptions regarding latency, log-transformed TCDD exposures, and half-life values for TCDD. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. This is the largest of the occupational cohorts with exposures to TCDD. The cohort consisted of 5,132 male workers and a total of 377 cancer deaths. This permits characterization of risk for all cancer sites (combined).

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Journal of the Nationa l Cancer Institute, 1999; 91(9):779–786. The authors discussed the potential for bias from smoking, and other occupational exposures for which data for both were lacking at an individual basis. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Exposure scores assign ed on an individual level using a job-exposure matrix. The job-exposure matrix was based on estimated factor of contact with TCDD in each job, level of TCCD contamination of materi als at each plant over time, and proportion of day worker could be in contact with materials. These factors were multiplied together to derive a daily exposure score, which was acc umulated over the working history of each worker to obtain a cumu lative measure of TCDD. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. The follow-up of the cohort extended from 1942 until the end of 1993. Greater than 25 years of follow-up have accrued in cohort allowing for latency to be examined. Different assumptions on the half -life of TCDD were evaluated and produced similar results. Latency intervals were incorporat ed, with strongest associations noted with an interval of 15 years.

Conclusion This study meets the criteria and considerations noted above but has been superseded andupdated by Steenland et al. (2001). Therefore, this study was considered for further doseresponse analyses. 

## 1 2 3 4 5 6 7 8 9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-4 Table B-3. Steenland et al., 2001—All cancer sites combined 1 2
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The study evalua ted mortality from all cancer sites (combined). As described by Steenland et al., (1999) the sources of vital status and cause of death information were received from the Social Security death f iles, the National Death Index, and the Internal Revenue Service. Vital status was known for 99.4% of the co hort members, cause of death information is available for 98% of the decedents. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Occupational exposure to asbestos and 4-aminobiphenyl contributed to some excess cancer, but no evidence of confounding for the relationship between TCDD and all cancer mortality was detected following removal of workers who died of bladder cancer. No information is available for cigarette smoking, although dose-response patterns were similar between smoking and nonsmoking related cancers. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Increased risk estimates were observed in the higher cumulative exposure categories. The dose-response curve was not linear at higher doses. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Exposure metrics considered included cumula tive TCDD, log10TCDD, average exposure, and a cubic spline model was also evaluated. Exposure response relationships were also evaluated using TEQs. Exposure scores were assigned on an individual level using a job-exposure matrix. The job-exposure matrix was based on es timated factor of contact with TCDD in each job, level of TCCD contamina tion of materials at each plant over time, and proportion of day worker could be in contact with materials. Se rum levels were measured in 199 workers at one of 8 plants in 1998. Different estimate of the half-life of TCDD were used, and similar results were produced. The paper presented a range in risk estimates thereby conveying the range of uncertainties in risk estimates derived using different measures of exposure. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. This is the largest of the occupational cohorts with exposures to TCDD. The cohort consisted of 3,538 male workers and a total of 256 cancer deaths.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied Am J Epidem, 2001, 154( 5):451–458. However, additional details to assess uncertainties associated with characterizing serum data in a subset of workers to remainder of cohort are lacking. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-5 Response Criteria satisfied. The metrics consider ed included cumulative TCDD, log10TCDD, average exposure, and a cubic spline model was also evalua ted. Exposure response relationships were also evaluated using TEQs. Serum lipid TCDD measurements from 170 workers whose TCDD levels were greater than 10 ppt (the upper ranges of a background level) were used along with JEM information, work histories, and a pharmacokinetic elimination model to estimate dose rates per unit exposure score. In this regression model, the estimated TCDD level at the time of last exposure was mode led as a function of exposure scores. The coefficient relating serum levels and exposure scores was then used to estimate serum TCDD levels over time from occupational exposure (minus the background level) for all 3,538 workers. Time-specific serum levels were then integrated over time to derive a cumulative serum lipid concentratio n due to occupational ex posure for each worker. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Greater than 25 years of follow-up have accrued in cohort allowing for latency to be examined. Different assumptions on the half-life of TCDD were evaluated producing similar results.

Conclusion Overall, criterion has been satisfied and it is recommended that this study be considered for dose-response analysis. 

## 1 2 Table B-4. Cheng et al., 2006—All cancer sites combined 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The study evalua ted cancer mortality. The vital status and the information regarding the cause of death were ex tracted from the Social Security death files, the National Death Index, and the Internal Reve nue Service (Steenland et al., 1999). Vital status was known for 99.4% of the cohort members, while cause of death information is available for 98% of the decedents. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. This is the same data set used in the Steenland et al., (2001) paper. Occupational exposure to asbestos and 4-amin obiphenyl contributed to some excess cancer, but no evidence of confounding for the relationship between TCDD and all cancer mortality was detected following removal of workers who died of bladder cancer. No information is available for cigarette smoking, although dose-response patterns were similar between smoking and nonsmoking related cancers. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Slope coefficien ts are available for all cancers combined under a varying set of assumptions. Little evidence of an association was found when lag interval was not taken into account. Associa tions strengthened with incorpor ation of a 10 to 15 year lag interval. Dose-response was nonlinear at higher exposures, suggesting a nonlinear relationship or increased exposure misclassification at higher levels.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-6 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Compared to the 1 st 

### order models, the concentration, and age dependent model (CADM) provided a better fit for the serum sampling data. CADM model exposure estimates are higher than those based on an age only, constant 8.7-year half-life model. As discussed by Aylward et al. (2005b), model exposure estimates are influenced not only by choice of elimination model, but also by choices in regression procedure (e.g., log transformation, use of intercept, and incorporation of background dose term). Other limitations or uncertainties in exposure assessment include the following

• 

### Job-exposure matrix based on limited sampling data, and subjective judgment on contact

times and factors

• 

### Inability to take into account inter-individual variability in TCDD elimination kinetics

• 

### Dose-rate regressions are based on a small sample of the cohort with serum measures;

therefore, regression results may not be representative of remainder of the cohort. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Largest cohort of TCDD exposed wo rkers. The risk estimates are based on a total of 256 cancer deaths.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Risk Analysis, 2006; 4:1059–1071. Additional details to assess uncertainties associated with characterizing se rum data can be found in Aylward et al. (2005b); Risk Anal. 25(4):945–956. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Cumula tive serum lipid concentrations were estimated for each worker. No other dioxin-like compounds were assessed in this analysis. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Concentration an d age-dependence of TCDD elimination and two compartments (hepatic and adipose tissue) were taken into account when estimating TCDD exposures. Nearly 50 years of follow-up were available permitting an evaluation of latency.

Conclusion This study met the main criteria and consid erations. These data were considered for further dose-response analyses. 

## 1 2 Table B-5. Collins et al., 2009—All cancer sites combined, site-specific 3 analysis 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Vital status complete for all but two workers.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-7 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. No information collected on smoking status, but no excess in lung cancer or nonmalignant respiratory diseases note d. Analyses took into account potential for exposure to pentachlorophenol. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. No dose-res ponse pattern was observed with all cancer sites combined, however, a dose-response pattern was observed with soft tissue sarcoma. The study found no association between TCDD and death from most types of cancer. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. The authors used these serum from 280 former TCP workers to estimate historical exposure levels of TCDD, furans, and polychlorinated biphenyls for all 1,615 workers. Exposure assessment included detailed work history, industrial hygiene monitoring, and the presence of chloracne cases among groups of workers. This data was integrated into a 1-compartment, first-order pharmacokinetic to determine the average TCDD dose associated with jobs in each group, after accounting fo r the presence of background exposures estimated from the residual serum TC DD concentration in the sampled individuals. The authors did not evaluate departures from linearity, or examine skewness at higher exposures. Exposure levels were not provided. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Largest study of workers employed in one center, and a total of 177 deaths from cancer were observed. Limited pr ecision for soft tissue sarcomas for which a positive association has been demonstrated.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in Am J Epidemiol, 2009, 170(4):501–506. The authors discuss limitations of using death certificates for identifying deaths from soft tissue sarcoma for which a positive association was noted, assumptions in exposure characteriza tion, and effects of cigarette smoking. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. This study has the largest number of serum samples obtained from a specific plant. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. While the cohort did have sufficient follow-up, no evaluation of possible latent effects was presented.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-8Conclusion Study is not suitable for further evaluation or dose-response modeling since an exposureresponse relationship was not demonstrated. Th e evaluation of exposure metrics and latency considerations should be expanded beyond that presented in the paper. Previous analyses of these same workers found positive associati ons between cancer mortality and TCDD (Steenland et al., 2001). The reasons for the discrepancy in the findings from the two papers may be due to Steenland et al.’ s use of nonlinear exposure metric s, incorporation of a 15-year lag interval, or differences in the TCDD exposure estimates themselves.



## 1 B.1.2. BASF Cohort Studies 2
3 Table B-6. Z ober et al., 1990—All ca ncer sites combined, site-specific 4 analysis 5 6
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. A large component of the cohort (94 out of 247 workers) was assembled by actively seeking out workers who were alive in 1986 through the “Dioxin Investigation Programme.” As a result, it is like ly a number of deaths were missed due to the recruitment of survivors. This underascertainment is supported by much lower all cancer SMR one component of the cohort (SMR = 0.48, 95% CI: 0.13–1.23) relative to the general population. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. See above discussion of underascertainment in mortality for some of the cohort members. Althoug h it is likely that other co-exposures occurred (e.g., among firefighters), confounding could only occur if these co-exposures were associated with both the endpoint and exposure (TCDD) being considered. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. Workers were not categorized on the basis of their exposure, but rather their mortality experience compared to control cohort and the general population. The design of the study does not allow for dose-response to be examined. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration not satisfied. Although y ears since first exposure was examined, exposure assessment was based on working in various occupational cohorts. Since there was no quantitative assignment of TCDD exposures, the associated uncertainties could not be evaluated. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration not satisfied. There were only 23 cancer deaths in the entire cohort. As such, this study lacked adequate statistical power to detect cancer mortality differences that were moderate in magnitude.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-9 1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Int Arch Occup Envir Health, 1990, 62:139–157. The authors address issues related to the healthy worker effect, multiple comparisons, smoking, and small size of the cohort. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. Risks were derive d by comparing mortality rates of the three cohort subsets relative to a control cohort and the general population by time since first exposure categories. Workers were not assigned exposure s. There were no quantitative estimates of TCDD exposure. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. While the study was able to indirectly look at variations in risk estimates related to latency by using time since exposure , there were no quantitative estimates of TCDD exposure.

Conclusion This study is not suitable for dose-response analysis, as it failed the inclusion criteria. Most notably, the lack of exposure data does not permit the use of these data for a dose-response analysis. 

## 1 2 Table B-7. Ott and Zober, 1996—All cancer sites combined 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Mortality ascerta inment appeared to be fairly complete. The ascertainment of cancer incidence is more diffi cult to judge as geogra phical area not covered by a cancer registry. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Information was collected on smoking status, body mass index, and other occupational exposures, however a large portion of the cohort was firefighters who may have been exposed to other occupational carcinogens. However, the recruitment of survivors may results in under-ascertainment of mortality. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Increased cancer incidence was observed in the highest TCDD cumulative exposure category. Ri sks were most pronounced when a period of 20 years since first exposure was incorporated into the model. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-10 Response Consideration satisfied. Cumulative m easure of TCDD expressed was derived from serum measures. Exposure was also estimated by ch loracne status of the cohort members. The authors have not addressed the potential impli cation of deriving TCDD exposure estimates for the whole cohort using sera data that were available for only about half of the cohort. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Fo r all cancer sites combined, there were 31 deaths. It is the smallest of the occupational cohorts, but the deaths can be grouped into quartiles to allow for evaluation of dose-response relationships.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Occupational and Environmental Medicine, 1996, 53:606–612. A large component of the cohort (94 out of 247 workers) was assembled by actively seeking out workers who were alive in 1986 through the “D ioxin Investigation Programme.” As a result, it is likely a number of deaths were missed due to the recruitment of survivors. This underascertainment is supported by much lo wer all cancer SMR one co mponent of the cohort (SMR = 0.48, 95% CI: 0.13–1.23) relative to the general population (Zober et al., 1990). 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum samples, taken in 1989, were available for 138 surviving workers out of 254 and allowed for cumulative TCDD levels to be estimated using regression techniques in the remainder of the cohort. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Exposure assignment took into the affect that body mass index had on TCDD half-lives. TCDD levels estimates through back-extrapolation of serum levels based on half-life estimates obtained from previous st udies. Latency was considered with stronger association observed in external comparisons incorporating a late ncy of 20 years. The followup of the cohort was lengthy (>50 years).

Conclusion Given a part of the cohort was based solely on survivors in the in the mid-1980s, the SMR statistic derived from this study underestimates excess mortality relative to the general population. The cohort also includes a fair numb er of firefighters who are recognized to be exposed to other carcinogenic agents—these exposures may be confounding the associations that were reported. However, exposure to TCDD was quantified and the effective dose and oral exposure estimable. Therefore, quantitativ e dose-response analyses were considered for these data.



## 1 2 3 4 5 6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-11 B.1.3. The Hamburg Cohort 1
2 Table B-8. Manz et al., 1991—All can cer sites combined, site-specific 3 analyses 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Deaths were identified through medical records of the cohort members. A review of death cer tificates of the identified cancer deaths found a high degree of concordance (51/54). One of the 136 noncancer death certificates examined indicated an “occult” neoplasm. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Smoking data were similar between exposed and nonexposed cohort based on independent samples. Occupational exposure for which individual data are lacking unlikely to explain dose-response with TCDD. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Dose-response patterns across three levels of exposure observed among those who started work before 1954, and among those who worked for 20 years or longer. Dose-response patterns not evident across whole cohort, among those with less than 20 years of employment, or among those who started after 1954. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Categorical exposures were based on TCDD concentrations in precursor materials, products, waste, and soil from the plant grounds, measured after the plant closed in 1984. Exposure uncertainty examined using a separate group of 48 workers who provided adipose tissue samples. Other surrogate measures of exposure were considered in this study, including duration of exposure and year of first employment. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all cancer sites combined, ther e were 65 cancer deaths for the comparison to the comparison cohort of gas workers. The study is underpowered to look at site-specific cancers.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Lance,t 1991, 338:959–964. The authors discussed potential for misclassification using death certificates, health y worker effect and their related use of a comparison cohort of gas supply workers, other occupational exposures present at the plant, potential impact and the lack of smoking data. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. Exposure consisted of a large DLC component that was not quantified. Given crude TCDD exposure categorization data, no quantitative exposure metric was derived.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-12 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Exposure metrics were constructed that took into account duration of exposure, and periods when exposure was highest. However, exposure estimates did not consider lagged exposure.

Conclusion This study is not amenable to further TC DD dose-response analysis because it consisted of a large DLC component that was quantified and no quantitative exposure metric was derived. The dose-response patterns of risks observed across the three exposure groups provide compelling support for an association between TCDD and cancer mortality, particularly, given the associations observed when analyses restricted to those who were hired when TCDD exposures were known to be much higher, and among those who worked for at least 20 years. Subsequent studies improved the exposure assessment through the use of serum measures. 

## 1 2 Table B-9. Flesch-Janys et al., 1995; Flesch-Janys et al., 1996 erratum—All 3 cancer sites combined 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Medical records used to identify deaths over the period 1952–1992. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Similarity in sm oking rates between control cohort and the exposed workers was similar based on independent surveys. Occupational exposures to benzene, and dimethyl sulfate were unlikely to bias dose -response pattern observed as these exposures occurred in production departments with low-medium levels of exposure. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Dose-response relationship observed across 6 exposure categories, with the cohort of gas supply workers used as the referent. 4. Consideration Consideration satisfied. Expo sure assessment methodology is clear and adequately characterizes individual-level ex posures. The limitations and uncertainties in the exposure assessment are considered. Response The exposure measure was an integrated TCDD concentration over time estimate that backcalculated TCDD exposures to the end of the em ployment. Categorical and continuous TCDD exposures were examined in relation to the health outcome. These efforts improve the exposure assessment of earlier studies. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all cancer sites combined, there were 124 deaths in the exposed cohort, and 283 in the cohort of gas supply work ers. No site-specific cancers were examined in this paper.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-13 1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 1995, 1442:1165–1175. The authors discuss the potential role of other occupational exposures (i.e., dimethyl sulfate, solvents, and benzene), smoking, and suitability of the comparison co hort of gas supply workers. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum and adipose tissu es were used to estimate TCDD exposure in 190 workers. A one-compartment fi rst-order kinetic model was used to estimate exposure at end of exposure for these workers. Regression methods were then used to estimates TCDD exposures for all workers. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. Exposure was ba sed on half-life estimates from individuals with repeated serum measures. Other dioxin-like compounds were considered with the TOTTEQ exposure metric. No consideration, however, was given to latency or lagged exposures.

Conclusion The exposure data used within this study are well-suited to a dose-response analysis given the associations observed, the characterization of exposure using serum, and quality of ascertainment of cancer outcomes. However, subsequent methods have been applied to the cohort to derive different exposures to TCDD using area under the curve approaches, which updates the analysis herein. Therefore, subseq uent studies (i.e., Becher et al., 1998) will supersede this evaluation. 

## 1 2 Table B-10. Flesch-Janys et al., 1998—All cancer sites combined, site3 specific analysis 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Mortality follow-up was extended until the end of 1992, an increase in 3 years from previous analyses of the cohort. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Exposure was we ll characterized using sera data. While serum samples provided only from a subsample of surviving workers, these levels were consistent with expected levels in different production departments. The authors examined other potential occupational co-exposures (e.g., β -hexachlorocyclohexane) and indirectly examined the potential effect of smoking on th e associations that were detected. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. A dose-response relationship across quartiles of TCDD was observed with cancer mortality based on the SMR statistic (SMRs = 1.24, 1.34, 1.34, 1.73), and a linear test for trend was statistically significant ( p = 0.01).

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-14 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. The exposure m easure was an integrated TCDD concentration over time estimate that back-calculated TCDD exposures to the end of the employment. Categorical and continuous TCDD exposures were ex amined in relation to the health outcome. These efforts improve the exposure assessment of earlier studies. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all cancer sites combined, there were 124 cancer deaths.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect, 1998, 106(2):655–662. The authors address uncertainties in the estimation of exposure, describe the potential for confounding from β

2,4,5-T, hexachlorocyclohexane, and cigarette smoki ng. In fact, they show ed that blood levels of TCDD were not associated with smoking in a sub-sample suggesting little bias from lack of smoking data. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum samples, taken from 190 workers were used to derive TCDD levels for the entire co hort. Methods used to estimate exposure took in to account elimination of TCDD during employment periods when exposur e took place, and the methods of the area under the curve was used as it takes into account variations in concentration over time, and reflects cumulative exposure. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Exposure estimated ba sed on half-lives observed in individuals with repeated samples. Area under the curve appr oach was used which is an improvement from past characterizations of exposure in this cohort.

Conclusion The study provides data suitable for dose-response modeling. Derivation of exposure was done using current understanding of elimination of TCDD. Estimates of risks were derived from external comparisons to the general population that are unlikely to be biased by healthy worker effect, but risks generated using internal cohort comparisons would be preferable. Becher et al,. (1998) assessed this same data taking cancer latency into account, therefore Flesch-Janys et al., (1998) will not be furt her considered for dose-response modeling. 

## 1 2 Table B-11. Becher et al., 1998—All cancer sites combined 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Medical records used to identify deaths over the period 1952–1992. The follow-up interval was lengthy.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-15 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Ri sks adjusted for exposures to TEQ, β -hexachlorbenzene, and employment characteristics. Smoking was shown to be similar to the comparison cohort of gas workers. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. A variety of exposure measures for both TCDD and TEQs found positive associations with cancer mortality. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. The exposure m easure was an integrated TCDD concentration over time estimate that back-calculated TCDD exposures to the end of the employment. Categorical and continuous TCDD exposures were ex amined in relation to the health outcome. Different models explored the shape of the dose-response curve. These efforts improve the exposure assessment of earlier studies. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all cancer sites combined, there were 124 cancer deaths.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect, 1998, 106(2):663–670. The authors discuss uncertainties associated with their use of expos ure metrics, inability to evaluate effects for PCDD/Fs other than dioxin due to high correlations with β -HCH, and inability to characterize risks associated with ex posures in children. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. The authors derived a measure of cumulative dose as a time-dependent variable (“area under curve”) using serum measures available in a sample of 275 workers. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. TCDD levels estimates through back-extrapolation of serum levels based on half-life estimates obtained from previous studies. Latency was considered, and a variety of exposure metrics including nonlinear relationships were evaluated.

Conclusion In this paper, a variety of exposure metr ics were found to be positively associated with cancer mortality. The additional lifetime risk of cancer corresponded to a daily intake of 1pg ranged between .01 and 0.001. This study was modeled in the 2003 Reassessment and is considered for further dose-response evaluations herein.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-16 B.1.4. The Seveso Cohort Studies 1
2 Table B-12. Bertazzi et al., 2001—All cancer sites co mbined, site-specific 3 analyses 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Mortality appears to be well captured from the vital statistics registries in the region (99% complete). Vital status was ascertained using similar methods for both the exposed and reference populations. Both cancer and noncancer mortality outcomes were evaluated. Ideally, would have evaluate d incident rather than decedent outcomes for

cancer. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Individual-level data on potentia l confounders (i.e., age, calendar period, and gender) were adjusted for. Information from other independent surveys suggests similarity between smoking behaviors across the regions. Comparison of cancer mortality rates before the time of the accident between the regions also revealed no differences. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied (fo r all cancers combined). No sta tistically significant excesses noted in Zone A, or Zone B relative to reference area. Evidence of an exposure-response relationship was detected for lymphatic and hematopoietic tissues by number of years since first exposure. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration not satisfied. Subjects were assigned to one of the zones (A, B, R, or reference) based on offi cial residence on the day of the accident or at entry into the area. Exposure misclassification is likely and lack of individual-level data precludes an examination of this source of error. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. In total, 27, and 222, cancer deaths were found among residents of Zones A, and B, respectively. This allo wed examined of gender-specific effects.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 2001 Jun 1; 153(11):1031–1044. Authors discuss completeness of mortality ascertainment, diagnos tic accuracy of death certificates particularly with respect to diabetes, limited available of blood dioxin measures that did not permit estimation of TCDD dose on an individual-level basis. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-17 Response Criteria not satisfied. In dividual-level exposure data are unavailable. Exposure based on place of residence at time of the explosion. Soil sampling performed indicated considerable variability in TCDD levels within each region. In addition, place of residency at time of explosion does not ensure individuals were at their home around the time of the accident. 3. Criteria The effective dose and oral exposure ca n be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. An ecological measure of exposure (region of residency at time of accident) was used to categorize individuals according to their possible exposure. Latencies were considered. While such an approach has value for identifying wherever excesses occurred among highly exposed populations, it is not precise enough to conduct a quantitative dose-response analysis.

Conclusion The lack of individual-level exposure data precludes quantitative dose-response modeling using these data. 

## 1 2 Table B-13. Pesatori et al., 2003—All ca ncer sites combined, site-specific 3 analyses 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Mortality appears to be well captured from the vital statistics registries in the region (99% complete). 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Individual-level data on potentia l confounders (i.e., age, calendar period, and gender) were adjusted for. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. While excesse s of mortality were observed for several health conditions in Zone A, a dose-response pattern was not observed across Zones A, B and R. Among men, excess mortality observed in zone A included chronic ischemic disease, and chronic obstructive pulmonary diseases. Among females, an excess in Zone A was observed with hypertension. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration not satisfied. Subjects were assigned to one of the zones (A, B, R, or reference) based on offi cial residence on the day of the accident or at entry into the area. Exposure misclassification is likely and lack of individual-level data precludes an examination of this source of error. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-18 Response Consideration satisfied. Only 39 deaths observed among men in Zone A; 39 deaths observed among their female counterparts. Among females, only 3 deaths from hypertension observed in Zone A, and only 4 deaths observed among males for chronic obstructive pulmonary disease.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Occup Env Med, 1998; 55:126–131. Authors discuss limitations such as residency-based exposure assignment, absence of smoking, differential and death certification in exposed versus nonexposed areas. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. In dividual-level exposure data are unavailable. Exposure based on place of residence at time of the explosion. Soil sampling performed indicated considerable variability in TCDD levels within each region. In addition, place of residency at time of explosion does not ensure in dividuals were at their home around the time of the accident. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. An ecological measure of exposure (region of residency at time of accident) was used to categorize individuals according to their possible exposure. Latencies were considered. While such an approach has value for identifying wherever excesses occurred among highly exposed populations, it is not precise enough to conduct a quantitative dose-response analysis.

Conclusion No dose-response patterns evident in the study, and the study lacked quantifiable measures of TCDD at an individual-l evel basis. The data are not well suited for dose-response analysis. 

## 1 2 Table B-14. Consonni et al., 2008—All ca ncer sites combined, site-specific 3 analyses 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Mortality appears to be well captured from the vital statistics registries in the region (99% complete. Bo th cancer and noncancer mortality evaluated), although diagnostic accuracy of death certificates is likely low. Ideally, would have evaluated incident rather than decedent outcomes for cancer. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Individual-level data on potentia l confounders (i.e., age, calendar period, and gender) were adjusted for. Comparis on of cancer mortality rates before the time of the accident between the regions also revealed no differences. Information from other independent surveys suggests similarity between smoking behaviors across the regions. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-19 Response Consideration satisfied for some outcomes. For all cancer sites co mbined, no evidence of dose-response was observed relative to general population across Zones A, B and R. Only statistically significant excess found in Zone A was for chronic rheumatic disease but based on only three deaths. Higher cancer excesses were found in Zone A after a latency period was incorporated; however, no dose-response relationship observed with this latency period. Evidence of an exposure-response relationship was detected for lymphatic and hematopoietic tissues by zone of residence. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration not satisfied. Subjects were assigned to one of the zones (A, B, R, or reference) based on offi cial residence on the day of the accident or at entry into the area. Exposure misclassification is likely and lack of individual-level data precludes an examination of this source of error. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. In total, 42, 244, and 1,848 cancer deaths were found among residents of Zones A, B, and R respectively.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 2008, 167:847–858. Authors discuss potential for selection bias, limitation of residential based measure of exposure, similarities of mortality ascertainment in exposed and referent populations, and multiple testing. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. In dividual-level exposure data are unavailable. Exposure based on place of residence at time of the explosion. Soil sampling performed indicated considerable variability in TCDD levels within each region. In addition, place of residency at time of explosion does not ensure in dividuals were at their home around the time of the accident. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. An ecological measure of exposure (region of residency at time of accident) was used to categorize individuals according to their possible exposure. Latencies were considered. While such an approach has value for identifying wherever excesses occurred among highly exposed populations, it is not precise enough to conduct a quantitative dose-response analysis.

Conclusion The lack of individual-level exposure data precludes quantitative dose-response modeling using these data. 

## 1 2 Table B-15. Baccarelli et al., 2006—Site-specific analysis 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-20 Response Consideration satisfied. Polymerase chain reaction (PCR) methods were used to describe outcome measures. The prevalence of t(14; 18) was estimated as those individuals having a t(14; 18) positive blood sample divided by the t(14; 18) frequency (number of copies per million lymphocytes). 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Questionnaire data were used to collect information on cigarette smoking. Other potential confounders (age, smoking status, and duration of smoking). In addition, both exposure and outcome we re objectively and accurately measured. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration was not satisfied. Associatio ns were detected between the frequency of t(14; 18) and plasma TCDD levels as well as zone of residence at the time of the explosion. No association was detected for these exposure meas ures and prevalence of t(14; 18). A doseresponse trend was detected for TCDD and the mean number of t(14;1 8) translocations/10 6 

### lymphocytes, however the relevance of t(14; 18) in lymphocytes to Non-Hodgin’s lymphoma is uncertain. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. The authors highlight that exposure metrics represent both past and current body burdens. They employ several different exposure metrics of TCDD: place of residence (Zone A, B, R or reference), categorical serum measures, a linear term, log (base 10) transformed TCDD, and individuals with chloracne diagnosed after the accident. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Analyses are made using 72 highly exposed, and 72 low exposed individuals.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Carcinogenesis, 200 6, 27(10):2001–2007. The authors discuss the limitation of using t(14; 18) translocations as an outcome measure, and the uncertain role it plays in the development of non-Hodgkin’s lymphoma. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. A total of 144 subjects were included in the study. This included 72 subjects who had low exposures, and 72 who had high exposures based on serum concentrations. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. A variety of measures were employed including current TCDD levels, as well as surrogates of exposure at the time of the accident.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-21 Conclusion While an association was observed with the frequency of t(14; 18) translocation, it is uncertain whether this translates into an increased risk of non-Hodgkin’s lymphoma. Given the speculative nature of this endpoint and lack of demonstrated adverse effect, dose-response analyses for this outcome were not conducted. 

## 1 2 Table B-16. Warner et al., 2002—Breast cancer incidence 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Diagnoses of incident breast cancer were based on interview and information from medical records appears thorough. Of the 15 cases of breast cancer, 13 were confirmed by pathology and the remaining 2 by surgery report only. Three cases of breast cancer were excluded which represents a large pr oportion of the total cases identified. This would reduce sample size and could result in bias if the exclusion was association with TCDD exposure. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Information was co llected on an extensive series of risk factors by using an interviewer administered questionnaire. Participation rates for the survey were fairly good (80%). 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Limited evidence (not statistically significant) of a dose-response when TCDD was analyzed as a categorical vari able; only one breast cancer case was in the referent exposure category. In the analysis of TCDD as a continuous measure (log 10 

### TCDD), the hazard ratio associated wi th a 10-fold increase in TCDD serum levels was 2.1 (95% CI: 1.0–4.6). 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Different expos ure metrics were considered in these analyses (categorical, continuous, measures on a log-scale) . Exposure data are of high quality as they are based on serum samples taken among women near the time of the accident. As such, exposure assignment is not dependent on as many assumption as used in occupational cohorts were back-extrapolation for many years had to be performed. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration somewhat satisfied. Inadequate follow-up for cancer limited the number of cases available. Sample size also limited the co nclusions draw from the categorical analysis based on very few cases for some exposure categories.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Paper published in Environ Health Perspect, 2002 Jul, 110(7):625–628. . A major limitation of the study is the small number of incident cases of breast cancer (n = 15), discussed important strengths of the study including characterization of TCDD using serum collected near the time of the accident.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-22 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum was used to estimate TCDD levels in 981 of 1271 eligible women who had lived in either of the two contaminated sites in 1976. Data represent an objective measure of TCDD near the time of the exposure. Data obtained near the time of exposure which minimized the potential for exposure misclassification. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Exposu re characterized using serum measur es obtained close to the time of the accident.

Conclusion While characterization of exposure and availability of other risk factor data at an individuallevel basis are important strengths of this study, small sample size (n = 15 cases) based on inadequate follow-up is a key limitation. Qu antitative dose-response analyses were conducted using this study, but continued follow-up of the study population or consideration of all cancer outcomes would be valuable. 

## 1 2 B.1.5. The Chapaevsk Study 3
4 Table B-17. Revich et al., 2001—All can cer sites co mbined, and site-specific 5 analyses 6 7
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration cannot be evaluated. Insufficient details are provided in the paper to gauge the completeness and coverage of the cancer regist ry and mortality data. Health outcomes were studied on the basis of information in the official medical statistics. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Given that this is an ecological study, bias may be present. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration cannot be evaluated. Dose-response was not evaluated as exposure was based on residency in the region vs. no residency. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration not satisfied. No indivi dual-level exposure estimates were used. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. A total of 476 cancer deaths were observed among males, and 376 cancer deaths observed among females. The precision of the SMRs is demonstrated with fairly narrow confidence intervals for many causes of death.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-23 1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria not satisfied. Published in Chemosphere, 2001, 43(4–7):951–966. Authors do not address the completeness of the mortality follow- up, and whether there are differences in death registrations between regions. The authors do acknowledge, however, that new investigations being undertaken would characterize exposure using serum-based measures. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. It is a cross-s ectional study that compares mortality rates between regions. No individual-level exposure data available. 3. Criteria The effective dose and oral exposure can be reasonably estimated an d the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. No individual-level exposure estimates were used in the study.

Conclusion These cancer data are cross-sectional in nature and not appropriate for a dose-response analysis. 

## 1 2 B.1.6. The Air Force Health (“Ranch Hands”) Study 3
4 Table B-18. Akhtar et al., 2004—All can cer sites co mbined and site-specific 5 analyses 6 7
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Cancer incidence and mortality based on information from repeated medical examinations, medical r ecords and death certificate. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. The risk estimates were adjusted for a number of factors measured on an individual level including smoking. However, analyses are unable to distinguish between exposure to TCDD and 2,4-D as both were used in equal parts in the formulation of Agent Orange. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. There is evidence of a dose-response for all cancers and for some site-specific cancers (i.e., malignant melanoma, and prostate cancer). 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. High quality exposure data for most veterans was collected, so extrapolation to other members of the cohort was not required. The serum dioxin measurements also correlated we ll with reported skin exposure to herbicide in Vietnam, but collection of the samples 25 years later required back-extrapolation.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-24 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. In total, 117 inci dence cancers identified in the Ranch Hands cohort. For those sites with a dose-response association, malignant melanoma and prostate cancer, there were 16 and 34 incident cases, respectively.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in J Occup Environ Med, 2004, 46(2):123–136. Authors highlight that this is only cancer incidence study in US veterans, and the lengthy interval of follow-up (35–40 years)–both important strengths of the study. They addressed potential bias from healthy-worker effect, an d uncertainties surrounding the estimation of TCDD exposure (extrapolation 30 years after exposure), as we ll as exposure to other chemical exposures. Study uses incident outcomes for cancer. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Individual exposure es timates are based on measur ements of dioxin serum lipid concentrations. They were available for 1,009 Ranch Hands and 1,429 in the comparison cohort. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. TCDD exposures at the end of duty were estimated by back-extrapolating 1987 serum values.

Conclusion The major limitation of the study is the inability to isolate effects of TCDD from other chemicals used in the formulati on of the herbicides. This limitation precludes dose-response modeling of the TCDD and cancer outcomes data. 

## 1 2 Table B-19. Michalek and Pavu k, 2008—All cancer sites combined 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Cancer incidence wa s ascertained through the use of medical records. Death certificate were used to identify some malignancies. Little data is provided on the number of individuals lost to follow-up, however the same mechanisms of case ascertainment were applied to both the comparison and Ranch Hand cohorts. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Information collected from repeated physical examinations allowed for the adjustment of risk factors such as smoking. Agent Orange was a 50% mixture of 2,4-D and TCDD; therefore, potential for confounding by other coexposures is likely. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-25 Response Consideration satisfied for some comparison s. Statistically signifi cant associations were noted with cancer incidence and TCDD when anal yses were restricted to workers who served at most two years in Southeast Asia and those who sprayed more than 30 days before 1967. 4. Consideration Exposure assessment methodology is clear and adequately charact erizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Initial TCDD dose we re estimated at the end of the tour of duty for the Ranch Hands. Individual-level serum dioxin measurements correlated well with correlated with days of sprayi ng and calendar period of servi ce, but collection of the samples roughly 20 years later required back-extrapolation. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. A total of 347 inci dent cases of cancer were used in the analyses. For stratified analyses, statistical power is more limited. For example, only 67 incident cancer in the subset of workers who spent less th an 2 years in Southeast Asia, and sprayed for at least 30 days before 1967.

1. Criteria Study is published in the peer-reviewed scie ntific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied J Occup Environ Med 2008; 50:330–340. The authors discuss issues related to exposure misclassification error, and suggest approaches for improving characterization of days of spraying. Congener specific data were unavailable, thereby not allowing for congener specific risks or adjustments to be made. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. TCDD data was available for 986 veterans in the Ranch Hand cohort, and 1,597 members of the comparison cohort. 3. Criteria The effective dose and oral exposure ca n be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. TCDD exposures at the end of duty were estimated by back-extrapolating 1987 serum values.

Conclusion Ranch Hand veterans were exposed to other contaminants in the herbicides that were mixed, thereby making it difficult to determine independent effects of TCDD on cancer. In particular, 2,4-D has been shown to be associ ated with some cancers, notable cancer of the prostate. In our view, this limitation precludes dose-response modeling of TCDD and cancer using data from this cohort.



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## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-26 B.1.7. Other Studies of Potential Relevance to Dose-Response Modeling 1
2 Table B-20. ‘t Mannetje et al., 2005—All ca ncer sites combined, site specific 3 analyses 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. National records for death registrations through the New Zealand Health Information Serv ice (NZHIS). Subjects not regist ered as having died during the study period were confirmed to be actually alive and resident in New Zealand using the New Zealand Electoral Roll, drivers’ li cense, and social security records. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Seventeen percent of workers were lost to follow up but it is unclear if bias resulted. The dichotomous exposure measure was based on exposure to TCDD, chlorinated dioxins and phenoxy herbicides, so confounding is a possibility by these coexposures. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Dose-response ev idence for duration of employment and elevated mortality noted only in synthesis workers. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Exposure measures were limited to duration of employment and exposed/unexposed. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all cancer sites combined, there were 43 cancer deaths among the production workers, and 35 such deaths among th e sprayers. Site-specific cancer analyses are limited by small sample sizes.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria not satisfied Occup Env Med, 2005; 62:34–40. A high percentage of the cohort was lost to follow-up (17%). The authors fail to mention this important limitation in this paper. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. This study used duration of exposure, at an individual level, as a surrogate measure of TCDD. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. Exposure was defi ned according to duration, and not concentrations of TCDD. Latency intervals were not evaluated.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-27 Conclusion Overall, quantitative exposure data are lacking for TCDD and limited dose-response relationships were observed across duration of exposure categories. Furthermore confounding by coexposures is a possibility. Taken together, these data are not suitable for inclusion in a dose-response analysis 

## 1 2 Table B-21. McBride et al., 2009b—All cancer sites combined, site-specific 3 analysis 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The New Zealan d Health Information Service Mortality Collection and the Registrar-General’s Index to Deaths. Additional searches were based on the last known address from the work record; the electoral roll and the habitation index; the telephone book; the internet; and Terranet property info rmation database. An additional search was carried out through the Births, Deaths, and Ma rriages office of the New Zealand Department of Internal Affairs. Lastly, automated personnel and pension records were also used to locate past New Plymouth workers and identify some deaths. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Considerable amount of workers were lost to follow up (22%), b ut it is unclear if bias resulted. The dichotomous exposure measure was based on exposure to TCDD, chlorinated dioxins and phenoxy herbicides, so confounding is a possibility by these coexposures. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. There was no examination of dose-response effects. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Dichotomous exposure (exposed/unexposed) and duration of employment were examined from job exposure classification assessed via occupational history records industrial hygienists/factory personnel knowledge and questionnaires. Authors discuss limitations in the assignment of exposure among cohort members. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration not satisfied. A low number of deaths (n = 76) may have limited ability to detect effects small in magnitude and exposure-response relationships.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in Occup Medicine, 2009; 59(4):255–263. The authors highlight cohort lost to follow-up, the limited size of the cohort, differences in cohort definitions between sprayers and producers, and the potential for other exposures during employment at the plant. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-28 Response Criteria not satisfied. TCDD exposures were not quantified. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. Effective dose could not be estimated given the lack of individual-level exposure data.

Conclusion The study lacks the quantification of exposures at an individual level precluded dose-response analysis. 

## 1 2 Table B-22. McBride et al., 2009a—All ca ncer sites combined, site-specific 3 analysis 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The New Zealan d Health Information Service Mortality Collection and the Registrar-General’s Index to Deaths were used to identify deaths. Additional searches were based on the last known address from the work record; the electoral roll and the habitation index; the telephone book; the internet; and several other public databases in New Zealand. An additional search was carried out through the Births, Deaths, and Marriages office of the New Zealand Department of Internal Affairs. Lastly, automated personnel and pension records were also used to locate past New Plymouth workers and identify some deaths. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Workers lost to fo llow-up were an unlikely so urce of bias especially for internal analyses. Confounding by other coexposures (e.g., 2,4,6-TCP) unlikely to have resulted in bias, due to presumed poor correlation with TCDD. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. The linear test for trend for TCDD exposure was not statistically significant for all cancer sites (combined), as well as lung cancer mortality. Dose-response relationships were not apparent across quartiles of TCDD exposure for all cancer sites combined, digestive cancers, lung cancer, soft tissue sarcomas or Non-Hodgkin’s Lymphoma. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Cumulative exposure to TCDD as a time-dependent metric was estimated for each worker from serum samples, but the authors did not examine a continuous measure of TCDD exposure (lagged or unlagged). 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-29 1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in J Occup Environ Med 51:1049-1056. This paper discussed the 22% of the cohort lost to follow-up, differences in cohort definitions between sprayers and producers, and the potential for other exposures during employment at the plant. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum measures availa ble for 346 workers were used to derive TCDD exposures for the entire cohort using th e area under the curve approach. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria satisfied. Effective dose could be estimated from serum-derived cumulative exposure estimates.

Conclusion Given that no dose-response associations were found, the data are not suited to dose-response analysis. 

## 1 2 Table B-23. Hooiveld et al., 1998—All cancer sites combined, site-specific 3 analysis 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Outcomes were mo rtality. Few deaths expected to be missed since only 5% of the cohort was lost to follow-up or had emigrated. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Although dioxin-like compounds (PCDDs, PCDFs, and PCBs) were measured in the serum samples, these were not incorporated into th e analysis. Therefore, confounding cannot be ruled out as an explanation of the reported association. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. A dose-response pa ttern was observed for internal cohort comparison for all cancer mortality, with RRs of 5.0 and 5.6 for the medium and high exposure, respectively. Dose-response patterns ev ident fort lung cancer as well. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Detailed occupational histories to assign dichotomous exposures (exposed/unexposed) based on maximum exposure levels. Although serum data also collected for TCDD and other coexposures (PCDDs, PCDFs, and PCBs), study only presents data for TCDD exposure. TCDD exposures at time of maximum exposure were extrapolated from measured serum.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-30 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration not satisfied for internal cohort comparisons in either men or women. Among men, only 7 cancer deaths were observed among those in the unexposed part of the cohort, and 51 among exposed workers. For external cohort comparisons, a total of 20 deaths were observed.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 1998, 147:891–901. The authors address potential limitations of estimating TCDD exposure from a sub-sample of surviving workers, lack of smoking data, the healthy worker effect, and relevance of other occupational exposures. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum samples were obta ined from 94 of 144 subjects who were asked to participate in serum measurement study. Of these, a further 44 excluded due to absence due to holiday or work (n = 22), and nonexposed workers excluded because matching exposed worker not participating (n = 20). TCDD levels were extrapolated to the time of maximum exposure. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response Criteria not satisfied. Exposures assigned based on levels at maximum exposure. Assignment of exposure based on nonrepresentative sample of 50 survivors among the occupational cohort.

Conclusion The small number of identified cancer deat hs, limitations in terms of the exposure assignment (based on nonrepresentative sample, and maximum exposure level) and concern over potential confounding by coexposures preclude using th ese data for a dose-response analysis. 

## 1 2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-31 B.2. EVALUATION OF NONCANCER STUDIES 1
B.2.1. NIOSH Cohort 2
3 Table B-24. Steenland et al., 1999—Mortality (noncancer) 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The study evalua ted mortality from all cancer sites (combined). As described in the paper, the sources of vital status and cause of death information were received from the Social Security death files, the Na tional Death Index, and the Internal Revenue Service. Vital status was known for 99.4% of the cohort members, cause of death information is available for 98% of the decedents. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. External co mparisons for all-cause and cardiovascular mortality do not appear to be affected by the “healthy wo rker effect” as similar patterns were observed with internal cohort comparisons. Nonetheless, internal cohort comparisons are unable to adjust for many of the indi vidual-level risk factors fo r cardiovascular disease. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. A dose-response relationship was observed with ischemic heart disease (linear test for trend p = 0.05), and with TCDD on a log-transformed scale the p-value was <0.001. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. The study cond ucted detailed sensitivity analyses and evaluated different assumptions regarding latency, log-transformed TCDD exposures, and half-life values for TCDD. Associations were strong er for log-transformed values, and latency intervals of 15 years. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. This is the largest of the occupational cohorts with exposures to TCDD. The cohort consisted of 5,132 male workers and a total of 456 deaths from ischemic heart disease. This permits characterization of risk for all cancer sites (combined)

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied Journal of the Nationa l Cancer Institute, 1999, 91(9):779–786. The authors discussed the potential for bias from smoking, and other occupational exposures for which data for both were lacking at an individual basis. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-32 Response Criteria not satisfied. Exposure scores assigned at an individual level based on job-exposure matrix (JEM). The JEM was based on estimated factor of contact with TCDD in each job, level of TCCD contamination of materials at each plant over time, and proportion of day worker could be in contact with materials. Th ese factors were multiplied together to derive a daily exposure score, which was accumulated ov er the working history of each worker to obtain a cumulative measure of TCDD. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. The follow-up of the cohort extended from 1942 until the end of 1993. Greater than 25 years of follow-up have accrued in cohort allowing for latency to be examined. Different assumptions on the half -life of TCDD were evaluated and produced similar results. Latency intervals were incorporat ed, with strongest associ ations noted no lag. Suggests mechanisms occur at the same time as exposure. However, noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

Conclusion TCDD exposures were quantified in this study, and a dose-response relationship was observed with ischemic heart disease mortality. The sample size was sufficient, and the follow-up interval was lengthy. However, no individual-level data were available for cardiovascular conditions, and the inability to adjust for these exposures introduces considerable uncertainty into the risk estimates. Furthermore, noncancer mortality is not considered a viable endpoint for dose-response analysis. 

## 1 2 Table B-25. Collins et al., 2009—Mortality (noncancer) 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Vital status complete for all but two workers. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. No information collected on smoking status, but no excess in lung cancer or nonmalignant respiratory diseases note d. Analyses took into account potential for exposure to pentachlorophenol. External cohort comparisons should be interpreted cautiously due to healthy worker effect, but internal cohort comparisons should not be influence by this bias. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. No statistically significant mortality excess for any noncancer mortality outcome evaluated. This included ischemic heart disease, stroke, nonmalignant respiratory disease, ulcers, cirrhosis, and extern al causes of death (accidents). Modeling of continuous measure of TCDD was not related to diabetes, ischemic heart disease, or nonmalignant respiratory mortality. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-33 Response Consideration satisfied. The authors used these serum from 280 former TCP workers to estimate historical exposure levels of TCDD, furans, and polychlorinated biphenyls for all 1,615 workers. Exposure assessment included detailed work history, industrial hygiene monitoring, and the presence of chloracne cases among groups of workers. This data was integrated into a 1-compartment, first-order pharmacokinetic to determine the average TCDD dose associated with jobs in each group, after accounting fo r the presence of background exposures estimated from the residual serum TC DD concentration in the sampled individuals. The authors did not evaluate departures from linearity, or examine skewness at higher exposures. No presentation of exposure levels was provided. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. A total of 662 deaths were observed. Of these, 218 were from ischemic heart disease, and 16 from diabetes (two outcomes for which associations have been noted elsewhere).

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in Am J Epidemiol, 2009, 170(4):501–506. The authors discuss potential for exposure misclassification, large si ze of the cohort, lengthy follow-up interval, and large number of workers who provided serum from which TCDD exposures were estimated. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. This study has the greatest number of serum samples obtained from a specific plant. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. Noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

Conclusions No dose-response associations were noted for noncancer mortality outcomes. The data are, therefore, not suited for dose-response modeling. 

## 1 2 B.2.2. BASF Cohort 3
4 Table B-26. Ott and Z ober, 1996—Mortality (noncancer) 5 6
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Mortality ascertainment appeared to be fairly complete. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-34 Response Consideration satisfied. Information was collected on smoking status, body mass index, and other occupational exposures, however a large portion of the cohort was firefighters who may have been exposed to other occupational carcinogens. However, the recruitment of survivors may results in under-ascertainment of mortality. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. For external cohort comparisons across the three TCDD exposure categories, there was no dose-r esponse pattern observed for an y of the noncancer causes of death. Cox regression risk estimates for all cause or circulatory disease mortality when TCDD was modeled as a continuous variable were not statistically significant. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. Cumulative m easure of TCDD expressed was derived from serum measures. Exposure was also estimated by ch loracne status of the cohort members. The authors have not addressed the potential impli cation of deriving TCDD exposure estimates for the whole cohort using sera data that were available for only about half of the cohort. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all causes of death, there were 92 deat hs, while 37 circulatory deaths. Many of the cause-specific death ha d less than 5 deaths in the upper exposure category.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Occup Environ Med, 1996, 53:606–612. A large component of the cohort was assembled by actively seeking out workers who were alive in the mid 1980s. As a result, it is likely a number of deaths were missed. This is supported by much lower SMRs in this component of the cohort published in earlier studies of the cohort. This underascertainment of mortality results in biased SMR statistics (under estimated). The authors do highlight the value of the serum based measures to estimate TCDD exposure 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum samples, taken in 1989, were available for 138 surviving workers out of 254 and allowed for cumulative TCDD levels to be estimated using regression techniques in the remainder of the cohort. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. Exposure assignment took into the affect that body mass index had on TCDD half-lives. TCDD levels estimates through back-extrapolation of serum levels based on half-life estimates obtained from previous st udies. Latency was considered with stronger association observed in external comparisons incorporating a late ncy of 20 years. The followup of the cohort was lengthy (>50 years). However, noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-35 Conclusion No associations noted with any noncancer deaths. External comparisons should be treated cautiously especially for cardiovascular mortality which is recognized to often be biased by the healthy-worker effect. In the absence of any outcome w ith an association with TCDD exposure, no dose-response analyses of these data are recommended.



## B.2.3. Hamburg Cohort 1
2 Table B-27. Flesch-Jan ys et al., 1995; Flesch-Janys et al., 1996 erratum— 3 Mortality (noncancer) 4 5
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Medical records used to identify deaths over the period 1952–1992. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Similarity in sm oking rates between control cohort and the exposed workers was similar based on independent surveys. Occupational exposures to benzene, and dimethyl sulfate were unlikely to bias dose -response pattern observed as these exposures occurred in production departments with low to medium levels of TCDD exposure. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Dose-response relationship observed for all-cause mortality, cardiovascular mortality, and ischemic heart di sease mortality across 6 exposure categories, with the cohort of gas supply workers used as the referent. The linear tests for trend for these three outcomes were all statistically significant ( p < 0.05). 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Consideration satisfied. The exposure m easures was an integrated TCDD concentration over time estimate that back-calculated TCDD exposures to the end of the employment. Categorical and continuous TCDD exposures were ex amined in relation to the health outcome. These efforts improve the exposure assessment of earlier studies. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For all causes of death combined, there were 414 deaths in the exposed cohort, and 943 in the cohort of gas supply workers. A total of 157 and 76 deaths from cardiovascular disease, and ischemic h eart disease were noted. The corresponding number in the cohort of gas supply workers was 459, and 205, respectively.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 1995, 1442:1165–1175. The authors discuss the potential role of other occupational exposures (i.e., dimethyl sulfate, solvents, benzene), smoking, and suitability of the comparison co hort of gas supply workers.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-36 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum and adipose tissu es were used to estimate TCDD exposure in 190 workers. A one-compartment fi rst-order kinetic model was used to estimate exposure at end of exposure for these workers. Regression methods were then used to estimates TCDD exposures for all workers. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. Ex posure based on half-life estimates from individuals with repeated serum measures. Other dioxin-like compounds were considered with the TOTTEQ exposuremetric. Noncancer mortality, however, is not a viable endpoint to consider for further doseresponse analysis.

Conclusion Although, the exposure data used within this study are well-suited to a dose-response analysis for all-cause and cardiovascular mortality given the associations observed, use of noncancer mortality endpoint is not amenable for further dose-response analysis.



## B.2.4. The Seveso Women’s Health Study 1
2 Table B-28. Eskenaz i et al., 2002a—Menstrual cycle characteristics 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Information was al so obtained from medical records for all obstetric and gynecologic conditions. Information on menstrual cycles was obtained from questionnaires. Women were asked about length of cycles, regularity, how many days flow lasted, and heaviness of menstrual flow (scanty, moderate, or heavy). Measurement error is likely for the subjective nature of self-reported menstrual parameters but specificity and sensitivity is difficult to ascertain due to lack of validation data for these measures. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Detailed risk f actor information was collected from questionnaire, allowing for the potential confounding influence of many risk factors to be controlled for. The length of cycle study findings may have been affected by the presence of a few outliers. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied . A positive dose-response relatio nship was found with TCDD among women who were premenarcheal at time of the ex plosion and longer menstrual cycle. Increased TCDD resulted in a reduced odds of scanty me nstrual flow. No association was noted with these two outcomes among postmenarcheal women. A decreased risk of irregular cycles was observed with higher TCDD levels.
4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-37 Response Criteria satisfied. Serum concentrations of TCDD offer improved exposure assessment, although delineating the critical exposure window is challenging given the nature of the very high initial exposure. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Cohort was large enough as analyses were conducted on 301 women.

1. Criteria Study is published in the peer-reviewed scie ntific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 2002; 156(4) 383–392. Limitations included an inability to assess affects on menstrual cycle at time bo dy burdens were the highest (at time of the accident). Also, TCDD was estima ted for 1976, not concurrent with their cycles in the previous year, and a large number of women were excl uded due to intrauterine device or oral contraceptive use. Strengths included population- based nature of study, with characterization of exposure using serum, and levels of other polychlorinated dibenzo-p-dioxins and dibenzofurans were at background levels. Findings for length of menstrual cycle may be unduly influenced by the presence of some outliers. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. The study population was based on 301 women as those who were over the age of 44 were excluded, as well as women with surgical of natural menopause, women with Turner’s syndrome, those who had been pregnant or breastfed in the past year, and those who had used an intrauterine device or oral contraceptives. For 272 women, TCDD levels were based on serum data provided in 1976; TCDD levels were back-extrapolated to 1976 levels for the other 29 women. 3. Criteria The effective dose and oral exposure can be reasonably estimated an d the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response had to be a nonfatal endpoint. Response Criteria satisfied. Ideally, TCDD exposure s would be concurrent with reporting of cycle characteristics. Herein, TCDD exposures were based on levels in 1976; however, given the long half-life of TCDD and the same follow-up interval for all women, TCDD exposures in 1976 should correlate well with levels near the ti me of interview. Further, the critical window of exposure can be estimated for the women that were premenarcheal at the time of the accident (13 years).

Conclusion This study meets all of the criteria and considerations for further dose-response analysis. The determination of the relevant time interval over which TCDD dose should be considered is uncertain . 

## 1 2 Table B-29. Eskenazi et al., 2002b—Endometriosis 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration not satisfied. Results of a pilot study showed that ultrasounds had excellent specificity and sensitivity for ovarian endometriosis.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-38 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. More than half of the women were classified as ‘uncertain’ with respect to endometriosis disease status. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. While an increa sed risk of endometriosis was observed across the 3 TCDD categories, these risks were not statistically significant relative to the lowest exposure category. The test for trend based on a continuous measure (log 10 

### TCDD) was also not statistically significant.
4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Criteria satisfied. Serum concentrations of TCDD offer improved exposure assessment, although delineating the critical exposure window is challe nging given the nature of the very high initial exposure. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration not satisfied. Only a tota l of 19 cases of endometriosis were identified.

1. Criteria Study is published in the peer-reviewed scie ntific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect 2002; 110(7) 629–634. Author’s highlight that this is the first study to examine the relationship between TCDD and endometriosis, and the availability of sera data to estimate TCDD levels. Limitations included the small number of women with endometriosis, and inability to confirm disease status using laparoscopy. Finally, young women may have been underrepresented due to cultural difficulties in examining women who had never been sexually active. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Eligible study subjects were women between 1 month and 40 years of age at time of accident. These analyses excluded virg ins, those with Turner’s syndrome, and women who refused the examination of ultrasound. Serum data were available for the 601 participants on which the analyses are based. Of these, 559 had serum measures taken in 1976/77, 25 between 1978 and 1981, and 17 women in 1996. 3. Criteria The effective dose and oral exposure can be reasonably estimated an d the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response has to be a nonfatal endpoint. Response Criteria not satisfied. TCDD exposure was estimated at the time of “conception attempt” using serum measures, with extrapolation from 1976 levels using half-life assumptions. It is difficult to identify the relevant time interval over which TCDD dose should be considered for dose-response analysis. The critical window of exposure is unknown.

Conclusion The lack of a statistically significant associ ation coupled with a large number of women for which endometriosis disease status was “uncertain”, precludes the use ofthese data to conduct doseresponse analysis.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-39 Table B-30. Eskenazi et al., 2003—Birth outcomes 1 2
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration not satisfied. Outcomes were identified through self-reported questionnaires. Women were found to over-report birth weight, and have a tendency to underreport birth defects in children. As a large number of women in Seveso underwent voluntary abortion in the first year after the explosion, an awareness bias may have contributed to differential reporting of pregnancy histories. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. See above. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. There was no association between spontaneous abortions and log 10 

### TCDD, or with births small for gestational age. An inverse association with birth weight was noted in first eight years following the accident as were the number of births small for gestational age; however, none achieved statistical significance at p < 0.05.
4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Criteria satisfied. Serum concentrations of TCDD offer improved exposure assessment, although delineating the critical exposure window is challenging given the nature of the very high initial exposure. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For spontaneous abortions there were 769 pregnancies. Fetal growth and gestational age analysis was carried out on 608 singleton births that occurred postexplosion.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect, 2003, 111(7):947–953. The authors highlight potential limitation of reliance on self-reported data to ascertain pregnancy outcomes. They also address the relevance of paternal exposures to TCDD on the developing fetus—such exposure data were not considered in this study. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. A total of 745 women in the SWHS had reported getting pregnant, of these 510 women were pregnant after the explosion (888 pregnancies). Analyses of spontaneous abortions based on 476 women (excludes those with voluntary abortion, ectopic pregnancy, or molar pregnancy. TCDD measured for 413 women in 1976/77, 12 women between 1978 and 1981, and 1996 for 19 women. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-40 Response Criteria not satisfied. TCDD exposures were extrapolated to 1976 values. However, it is difficult to identify the relevant time interval over which TCDD dose should be considered for dose-response analysis.

Conclusion The findings of the study are somewhat limited due to the reliance on self-reported information for pregnancy outcomes, and lack of paternal exposures. The findings were not statistically significant. Taken together, quantitative dose-re sponse analyses for this study population is not recommended. 

## 1 2 Table B-31. Warner et al., 2004—Age at menarche 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. In this study age at menarche was based on retrospective recall 5 to 19 years before the interview. Previous work suggests moderate to high correlations between actual and recalled menarche, misclassification of outcome would bias risk estimates towards the null (assuming nondifferential misclassification.) 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Data collected from self-reported questionnaires allow for the potential confounding influence of many risk factors to be taken into account. Some misclassification of outcome may bias risk estimates towards the null. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. There was no association between TCDD levels and the age at menarche with either the continuous or categorical measures of TCDD.
4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Criteria satisfied. Serum concentrations of TCDD offer improved exposure assessment, although delineating the critical exposure window is challenging given the nature of the very high initial exposure. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Cohort was large enough as analyses were performed using 282 women who were premenarcheal at the time of the explosion.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect, 2004, 112:1289–1292. Authors discuss use of pooled serum from residents of the unexposed zone, and that those in lowest exposure group had high exposures relative with contemporary levels for the area. Strengths of study include use of serum to estimate TCDD exposure. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-41 Response Criteria satisfied. The SWHS included women between 1 month and 40 years of age at time of accident who attempted to get pregnant after the ex plosion (n = 463). This study is restricted to those who were premenarcheal at the time of the explosion (n = 282). Serum was collected for these women, primarily in 1976–1977 (n = 257), between 1978 and 1981 for 23, and in 1996–1997 for the 2 remaining women. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. TC DD exposures in 1976 were estimated by extrapolation serum levels obtained after this date using the Filser model. Both categorical and continuous measures of exposure were modeled. In utero measures of exposure are likely most relevant exposure based on findings from animal studies.

Conclusion No association between TCDD levels and age at menarche was found. There may be some misclassification of age at menarche based on self-report, and biologically, the most relevant dose as suggested by animal studies occurs in utero. Additionally, it is difficult to identify the relevant time interval over which TCDD dose should be considered for dose-response analysis. For these reasons, these data are not suited to a dose-response analysis. 

## 1 2 Table B-32. Eskenazi et al., 2005—Age at menopause 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Outcome measures were obtained based on self-reported data collected from questionnaires. Studies have shown that self-reports of age at menopause are reported with accuracy and reliability, and am ong women with surgical menopause, the selfreported age correlated well with that on the medical records. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Data obtained from the questionnaire allow for the potential confounding influence of several potential confounders to be controlled for. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. Although risks of earlier menopause increased in the first four quintiles, with a statistically significant trend, no increased risk was noted in the highest exposure category (hazard ratio = 1.0 relative to lowest exposure group). Study authors suggest this is due to the “inverted U” do se response often seen with hormonally active compounds. Additionally, no statistically significant association was noted with log 10 

### TCDD for the individual quintiles. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Criteria satisfied. Serum concentrations of TCDD offer improved exposure assessment, although delineating the critical exposure window is challenging given the nature of the very high initial exposure.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-42 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. The study included 616 women. Of these, 260 were premenopausal, 169 classified as natural menopause, 83 as surgical menopause, 24 as impending menopause, 33 as premenopausal, and 58 in an “other” category.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect, 113:858–862 (2005). Authors highlight this is first study to look at relationship between dioxin and age at menopause. Other limitations of the study include lowest exposure group ( ≤ 20.4 ppt) includes exposures level that are far higher than background, and age at menopause was based on retrospective recall. Strength of study is ability to characterize TCDD using serum measures. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. The Seveso Women’s Health Study collected serum sample which allowed TCDD exposures to be characterized. Those women (n = 616) who had not reached natural menopause at the time of the accident were included in the study. Serum measures collected in 1976/77 were available for 564 women, for 28 women, sera was collected between 1978 and 1981, while for 24 women, sera was collected in 1996/97. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. TCDD levels were estimated at the time of the explosion using available information on TCDD half-life. However, it is difficult to identify the relevant time interval over which TCDD dose should be considered for dose-response analysis. The critical window of exposure can be estimated but is large and highly uncertain.

Conclusion The findings do not provide strong support for a dose-response relationship. As such, they are not well suited to a quantitative dose-response analysis. 

## 1 2 Table B-33. Warner et al., 2007—Ovarian function 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Ovarian cyst analysis based on women who underwent ultrasound (n = 310). Ovarian follicle analysis based on self-report on menstrual cycle and done in women in pre-ovulatory cycle (n = 96) at time of ultrasound. Hormonal analysis based on women in last 14 days of cycle (n = 129). 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Data collected from self-reported questionnaires allow for the potential confounding influence of many risk factors to be taken into account. Some misclassification of outcome based on self-reports of menstrual cycle may bias risk estimates towards the null.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-43 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. There was no association between serum TCDD levels and the number or size of ovarian follicles. TCDD was also not associated wit the odds of ovulation. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertaintie s in the exposure assessment are considered. Response Criteria satisfied. Serum concentrations of TCDD offer improved exposure assessment, although delineating the critical exposure window is challenging given the nature of the very high initial exposure. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Cohort was large enough as analyses were performed using 129 women for ovulation outcome, and hormone analyses based on 87 women in luteal, and 55 in midluteal phases.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environ Health Perspect, 2007,115:336–340. An important limitation cited by the authors was that women may not have been exposed at critical period (prenatally). Phases of the cycle may also have been misclassi fied as this was based on self-reported data. Strength, first study to have examined ovarian function and TCDD exposures. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. The SWHS included women between 1 month and 40 years of age at time of accident who were between 20–40 years of age an d not using oral contraceptives at follow-up (n = 363).Of these, serum wa s collected for 330 women between 1976 and 1977, between 1978 and 1982 for 25 women, and between 1996 and 1997 for 8 women. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. The women may not have been exposed at critical period (prenatally).

Conclusion No association between TCDD levels and ovarian function was found. There may be some misclassification of period of the cycle based on self-report, and biologically, the most relevant dose as suggested by animal studies occurs in utero. For these reasons, these data are not suited to a dose-response analysis. 

## 1 2 Table B-34. Eskenazi et al., 2007—Uterine leiomyoma 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-44 Response Consideration satisfied. Outcomes were dete rmined using two definitions: current fibroids, or past diagnosis of fibroids. Fo r past diagnosis of fibroids, self-reported data and medical records were used to determine whether women were previously diagnosed with fibroids, these were confirmed with medical records. A total of 25 women indicated they had never been diagnosed with fibroids. Medical records indicate a past diagno sis for these women, and they were classified as such. For current fibroids, this was determined at the time of the interview for 634 women using transvaginal ultrasound examinations. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. In the SWHS questi onnaires were administered to the participants and detailed data for reproductive characteristics, smoking, body mass index, and alcohol use were collected so risks could readily be adjusted for these covariates. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied, but inversely. An inverse dose-response pattern with the percentage of women diagnosed (current & past history–combined) with fibroids across 3 categories of exposure. Namely, the percentages of women with fibroids in the ≤ 20, 20.1–75.0, and >75.0 ppt categories were 41.1%, 26.8%, and 20.0%, respectively. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. A variety of different exposure metrics were considered including linear, categorical, splines, and log 10 

### TCDD. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. A total of 251 women were found to have fibroids, and there were 62, 110, and 79 women with fibroids diagnosed in the 3 TCDD exposure categories.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 2007, 166:79–87. In this study, the authors found an inverse association between TCDD and uterine leiomyoma risk. The authors highlighted strengths of the study that included the longitudinal design, serum measures taken at an individual-level basis and most taken within 2 years of the accident, ability to include outcomes among those who did not take an ultrasound by using an adapted statistical approach. An important limitation that was the differences in risk by the stage of development could not be assessed as all women were expose d postnatally, and only 4 cases were observed among those who were premenarch eal at the time of exposure. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Final sample consisted of 956 women in the Seveso Women’s Health Study without a history of fibroids. For 872 of these women, serum was collected in 1976 and 1977. For 56 women, TCDD was measured in women between 1978 and 1981, and for 28 women the serum was collected in 1996. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-45 Response Criteria not satisfied. TC DD exposures were back extrapolated to expected levels in 1976 (at the time of the accident). However, it is diffi cult to identify the releva nt time interval over which TCDD dose should be considered for dose -response analysis. Th e critical window of exposure is unknown.

Conclusion The data suggest an inverse (protective) effect between fibroids and exposure to TCDD. As such, these data are not suited to further dose-response analyses. 

## 1 2 B.2.5. Other Seveso Noncancer Studies 3
4 Table B-35. Mocarelli et al., 2008—Semen quality 5 6
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Serum levels of TCDD were measured on an individual basis for men in exposed areas; pooled samples from men in uncontaminated areas were measured to assess background TCDD exposure levels. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. While compliance rates may have introduced some possible bias, this does not seem likely as different effects noted between the 22–31 and 32–39 year old age groups. Information collected for other risks factors, which have been used as adjustment factors in the models. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Figure 3 suggests dose-response relationship among those aged 1–9 at the time of the accident for sperm concentration and motility. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Serum concentratio ns of TCDD offer improved exposure assessment, although delineating the critical exposure window is challenging. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Analyses are based on 135 males exposed to TCDD.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environmental Health Perspective s, 2008, 116(1):70–77. The authors describe strengths associated with characteri zation of exposure (using serum samples), and representativeness of study population. Limitation of study includes low compliance (but high for semen sample studies), namely, 60% among a group of healthy men. The compliance rate was higher among exposed group (69%). 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-46 Response Criteria satisfied. Involved male s, < 16 years old at time of accident. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria satisfied. TCDD exposures were based on serum samples. Serum samples were drawn (in 1997/1998) from participants whose 1976 samples were above 15 ppt. Pooled samples obtained in 1997/98 were used to describe background TCDD levels in uncontaminated areas. The associated between TCDD exposure and semen quality was found statistically significant for the bo ys with 1 and 9 years of age at the time of the accident. This provides a critical window of exposure to estimate TCDD concentration.

Conclusion Health outcomes are exposures are well ch aracterized using serum data. However, the men exposed between the ages of 1 and 9 to elevat ed TCDD levels had reduced semen quality 22 years later. It is difficult to discern whether this effect is a consequence of the initial high exposure between 1 and 9 years of age or a func tion of the cumulative exposure for this entire exposure window beginning at the early age. Nonetheless, quantitative dose-response analyses for this outcome were conducted. 

## 1 2 Table B-36. Mocarelli et al., 2000—Sex ratio 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Birth records examined for those who lived in parents who lived in the area and who provided serum samples. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Paternal TCDD exposures were associated with an increased probability of female births ( p = 0.008). 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Serum samples were used to estimate maternal and paternal TCDD levels. No discussion of exposure levels in reference population. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Statistically significant findings achieved.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria not satisfied. The Lancet, 2000, 355:1858–1863. There is no discussion on the strengths and limitations of this study.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-47 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum levels of TCDD were obtained from parents using samples provided in 1976/77. Serum measures available for 296 mothers and 239 fathers. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. Serum based measures of TCDD were obtained shortly after the accident. TCDD levels were also extrapolated to the time of conception. However, it is difficult to identify the relevant time interval over which TCDD dose should be considered for dose-response analysis. The critical window of exposure is unknown.

Conclusion The data from this study demonstrate a positive dose-response relationship with paternal TCDD levels at the time of the accident and incr eased likelihood for female births. However, It is difficult to identify the relevant time interval over which TCDD dose should be considered; specifically, it is difficult to discern whether this effect is a consequence of the initial high exposure during childhood or a func tion of the cumulative exposure for this entire exposure window beginning at the early age. Using the initial exposures in a dose-response model would yield LOAELs that are too high to be relevant to factor into the RfD calculation. Dose-response analysis for this outcom e is, therefore, was not conducted. 

## 1 2 Table B-37. Baccarelli et al., 2008—Neonatal thyroid function 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Measures of b-TSH are taken using a standardized protocol 72 hours after birth. These b-TSH measures are taken on all newborns born in the region of Lombardy of which Seveso if a part of. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied for component of the study based on plasma dioxin measures. For the comparisons involving place of residence at the ti me of the accident, exposure misclassification is likely given variability in soil TCDD exposure levels within these areas. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Mean neonatal b- TSH was 0.98μU/ml [0.90–1.08] in the reference area, 1.35μU/ml [1.22–1.49] in zone B, and 1.66μU/ml [1.19–2.31] in zone A ( p < 0.001). The plotted frequency distributions have similar shapes, but have shifted to the right for areas of higher exposures. Neonatal b-TSH was correlated with current maternal plasma TCDD ( β -0.47, p < 0.001) in the 51 newborns for which individual maternal serum TCDD values were available. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-48 Response Consideration satisfied. TEQs were measured among the 38 women for which serum samples were available and were defined for a mixture of dioxin-like compounds. Maternal mean total TEQs (PCDDs, PCDFs, coplanar PCBs, and noncoplanar PCBs) was 41.8 ppt. Two measures of exposure included place of residence at time of accident and plasma samples obtained from mothers at the time of delivery. Similarities in positive dose-response relationships give stronger weight to the findings. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied for exposure metric th at was based on ‘place of residence’. For plasma based estimate of maternal TCDD there were only 51 mother-child pairs. Only seven children in total were found to have b-TSH levels in excess of 5 uU/ml; this implies limited statistical power involving this health outcome.

1. Criteria Study is published in the peer-reviewed scie ntific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. PLOS Medicine 2008; 5(7)1133–1142. The authors discuss the strength of the study related to characterizatio n of exposure using serum sampling, and ability to adjust for factors related to b-TSH or TCDD levels (gender, birth weight, birth order, maternal age, hospital and type of delivery. They also highlight that a limitation of study was that the influence of mother-child dioxin transfer through colostrum could not be assessed because no information on breastfeeding before b-TSH measurement was available. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. In the population-based study, eligible women who resided in zones A and B at the time of the accident (n = 1,772) were matche d to nonexposed women. In the study based on plasma dioxin measurements, participants were the 51 children born to 38 women from zones A, B, R, or a reference zone for which plas ma dioxin measurements were available. 3. Criteria The effective dose and oral exposure can be reasonably estimated an d the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response has to be a nonfatal endpoint. Response Criteria satisfied. Maternal TCDD levels were estimated at the time of delivery based on plasma samples, and the critical window of exposure can be defined as the 9 month gestation period.

Conclusion The data provide an opportunity for quantitative dose-response analyses. 

## 1 2 Table B-38. Alaluusua et al., 2004—Oral hygiene 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Ascertainment of de ntal health was done blin d to place of residence, used standard protocol for caries developed by the WHO, and the clinical examination supplemented by radiographic examination. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-49 Response Consideration satisfied. Additional risk f actor information was collect ed on questionnaires. These factors were considered as adjustment f actors. Findings potentially susceptible to participation biases. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Increased preval ence of developmental enamel effects found with increased TCDD serum measures. Namely, pr evalence in unexposed region was 26%, whereas in the low, middle, and high TCCD groups the prevalence was 10, 40, and 60%, respectively. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. TCDD exposure level based on serum lipid s. No discussion of exposure levels in reference population. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Criteria satisfied. Despite small numbers , statistically significant findings were achieved.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Environmental Health Perspectives, 2004, 112(13)1313–1318. Authors mention two important strength of the study: characterization of TCDD exposure using serum collected shortly after the time of the accident, and the fact th at developmental defects are permanent in nature. Therefore, they represen t a health outcome can ev aluated years later. Little discussion was made of the impact of differential compliance rates between the exposed (74%) and nonexposed (58%) groups. Authors mention two important strength of the study: characterization of TCDD exposure using seru m collected shortly after the time of the accident, and the fact that developmental defect s are permanent in nature. Therefore, they represent a health outcome can evaluated years late r. Little discussion was made of the impact of differential compliance rates between the exposed (74%) and nonexposed (58%) groups. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum levels of TCDD could be estimated for children in exposed areas. No serum levels were available for reference group of children, and assumption of zero exposure was made. This seems reasonable. 3. Criteria The effective dose and oral exposure ca n be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria satisfied. It is difficult to discern whether this effect is a consequence of the initial high exposure during childhood or a function of the cumulative exposure of the entire exposure window beginning at early age. However, assumptions can be made regarding the critical window of exposu re and the relevant dose can be calculated.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-50 Conclusion The considerations for conducting a dose-response analysis have been satisfied with the study population of only thos e subjects who lived in the ABR zone at the time of the accident; exposure data are unavailable for those in the re ferent area. While is difficult to identify therelevant time interval over which TCDD dose should be considered, quantitative doseresponse analysis for this outcome was conducted. 

## 1 2 Table B-39. Bertazzi et al ., 2001—Mortality (Noncancer) 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied for some causes of death, but not others. Mortality appears to be well captured from the vital statistics registries in the region (99% complete). Some health outcomes (e.g., diabetes) are subject to misc lassification using death certificate data. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Although individual-level data for individual risk factors are not available, the potential for confounding is likely minimal. For e.g., independent surveys suggests similarity between smoking behaviors across the regions. Exposure misclassification based on place of residency likely to bi as risk estimates towards the null. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied for most cause s of death. An exception was the dose-response relationship was observed for chronic obstructiv e pulmonary disease across Zones A, and B. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration not satisfied. Exposure classification was based on the address of the residence on the date of the accident or when the person first entered the area. Although TCDD blood levels were also measured, these were not examined with respect to health outcomes. The lack of individual-level da ta also precluded an examination of these uncertainties. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. A total of 494 non-cancer deaths were found among residents of Zones A, and B, respectively. This allo wed examined of gender-specific effects.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations.Response Criteria satisfied. Am J Epidemiol, 2001, 153:1031–1044. Authors discuss lack of individuallevel exposure data and other risk factors (e .g., smoking), difficulties in extrapolating to background levels, diagnostic accuracy of using death certificates. Strengths included similarities between exposed an d comparison population for several risk factors, completeness of follow-up, and consistent methods to id entify mortality outcomes in the exposed and comparison populations. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-51 Response Criteria not satisfied. In dividual-level exposure data are unavailable. Exposure based on place of residence at time of the explosion. Soil sampling performed indicated considerable variability in TCDD levels within each region. In addition, place of residency at time of explosion does not ensure individuals were at their home around the time of the accident. 3. Critieria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. An ecological measure of exposure (region of residency at time of accident) was used to categorize individuals according to their possible exposure. Latencies were considered. While such an approach has value for identifying whether excesses occurredamong highly exposed populations, it is not precise enough to conduct a quantitative doseresponse analysis. Furthermore, noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

Conclusion Study is not suitable for dose-response analysis due to mortality as endpoint and lack of individual-level exposure data. 

## 1 2 Table B-40. Consonni et al., 2008—Mortality (Noncancer) 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied for some causes of death, but not others. Mortality appears to be well captured from the vital statistics registries in the region (99% complete). Some health outcomes (e.g., diabetes) are subject to misc lassification using death certificate data. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Although individual-level data for individual risk factors are not available, the potential for confounding is likely minimal. For e.g., information from other independent surveys suggests similarity between smoking behaviors across the regions. Exposure misclassification based on place of residency is likely to bias risk estimates towards the null. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. Statistically significant association noted in most highly exposed area for chronic rheumatic disease and chronic ob structive pulmonary disease. Dose-response pattern noted across Zones A, B and R for ci rculatory disease mortality 5–9 years after the accident. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration not satisfied. Lack of individual-level data precludes an examination of these uncertainties. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-52 Response Consideration satisfied for some causes of death but not others. For example, only three deaths from diabetes occurred among residents of Zone A. The limitation related to statistical power is exacerbated for stratified analyses ca rried out by number of years since the accident.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Am J Epidemiol, 2008, 167:847–858. Authors discuss potential for selection bias, limitation of residential based measure of exposure, similarities of mortality ascertainment in exposed and referent populations, and multiple testing. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. In dividual-level exposure data are unavailable. Exposure based on place of residence at time of the explosion. Soil sampling performed indicated considerable variability in TCDD levels within each region. In addition, place of residency at time of explosion does not ensure individuals were at their home around the time of the accident. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. An ecological measure of exposure (region of residency at time of accident) was used to categorize individuals according to their possible exposure. Latencies were considered. While such an approach has value for identifying whether excesses occurredamong highly exposed populations, it is not precise enough to conduct a quantitative doseresponse analysis. Furthermore, noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

Conclusion Study is not suitable further dose-response evaluation due to noncancer morality endpoint. 

## 1 2 Table B-41. Baccarelli et al., 2005—Chloracne 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Chloracne cas es identified using standardized criteria. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Plasma TCDD was a ssociated with an increased risk of chloracne. The odds ratios increased in a dose-response pattern across zone of residence. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Authors discussed implications of differential elimination rates by age and body growth.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-53 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. A total of 101 chlo racne cases were identified, and 211 controls were selected. Statistically significant findings were observed in several comparisons.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. British Journal of Derm atology, 2005, 152, 459–465. The authors detail the limited statistical power they had available in the study. They also highlight a strength of the study that included uniqueness of age and sex distribution of chloracne cases, characterization of TCDD that could be done using sera samples, and availability of both clinical and epidemiological data. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. TCDD was estimated in both chloracne cases and control using serum

measures. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria satisfied. Serum based measures of TCDD were obtained shortly after the accident. Chloracne is thought to be caused by the initial high exposure.

Conclusion Exposure to TCDD at sufficiently high levels is recognized to cause chloracne. This study provides limited relevance to dose-response modeling of TCDD as exposure levels typically observed in the general population are much lower. 

## 1 2 Table B-42. Baccarelli et al, 2002 and 2004—Immunological effects 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Common methods we re used to describe blood levels of plasma immunoglobulins (IgA, IgG, and IgM) and complement components (C3 and C4). 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Both exposure and outcome were ob jectively and accurately measured. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration satisfied. Plasma IgG levels were inversely related with TCDD. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Both categorical (quintiles) and continuous measures of TCDD were examined in the dose-response analysis.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-54 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Analyses are made using 72 highly exposed, and 72 low exposed individuals.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Toxicology letters, 2004, 149:287–293 and Environ Health Perspect, 2002, 110(12):1169–1173. The authors highlight that few studies have looked at immunological effects of TCDD in humans, that the current study was able to exclude those with concurrent medical conditions, and the ability to characterize exposure using serum measures. Limitations addressed were the uncertainty about the clinical relevance of the dose-response pattern found, and the relatively small size of the study population. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. A total of 120 subjects were included in the study. This included 62 randomly selected from the high exposed zone, and 58 selected from the reference area. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. Do se-response relationships were exam ined using current TCDD levels. However, it is difficult to identify the relevant time interval over which TCDD dose should be considered for dose-response analysis.

Conclusion An inverse dose-respons e association between IgG and TCDD was observed, however, because the relationship can not be described in terms of clinical relevance with respect to a specific health outcome, it is our view that these dataare not suited to dose-response modeling. 

## 1 2 B.2.6. Chapaevsk Study 3
4 Table B-43. Revich et al., 2001—Morta lity (noncancer) and reproductive 5 health 6 7
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration cannot be evaluated. Insufficient details are provided in the paper to gauge the completeness and coverage of the cancer regist ry and mortality data. Health outcomes were studied on the basis of information in the official medical statistics 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. It is an ecological study. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-55 Response Consideration cannot be evaluated. Dose-response was not evaluated as exposure was based on residency in the region vs. no residency. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration not satisfied. No indivi dual-level exposure estimates were used. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. Population-based da ta over several years were used to make ecological comparisons.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in Chemosphere, 2001, 43(4–7):951–966. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. It is a cross-s ectional study that compares mortality rates between regions. No individual-level exposure data available. 3. Criteria The effective dose and oral exposure can be reasonably estimated an d the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. No exposure estimates were used in the study.

Conclusion These cancer data are cross-sectional in nature and not appropriate for a dose-response analysis.



## B.2.7. Air Force Health (“Ranch Hands”) Study 1
2 Table B-44. Michalek and Pavuk, 2008—Diabetes 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. Prevalent diabet es identified from medical records from repeated medical check-ups. Preferred method of ascertaining outcome relative to use of death certificates. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Adjustment was made for a number of risk factors related to diabetes (e.g., BMI, family history, smoking). However, Agent Orange was a 50% mixture of 2,4-D and TCDD; therefore, potential for confounding by other coexposures is likely. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-56 Response Consideration satisfied. The RR for an increase in 10 units was 1.29 ( p < 0.001), and the risks across the background, low and high exposure categories, relative to the unexposed were 0.86, 1.45, and 1.68. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Initial TCDD dose we re estimated at the end of the tour of duty for the Ranch Hands. Individual-level serum dioxi n measurements correlated well with correlated with days of spraying and calendar period of service, but collection of the samples roughly 20 years later required back-extrapolation. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. There were a total of 439 cases of diabetes identified.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. J Occup Environ Medicine, 2008, 50:330–340. The authors address strengths and limitations related to the accu racy of the one-compar tment pharmacokinetic model, impact of the covariate time spent in Southeast Asia, and potential exposure misclassification on days sprayed. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. TCDD estimates were derived using serum samples. However, Ranch Hand veterans were exposed to other compounds in the herbicides, such as 2,4-D. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria satisfied. TCDD levels at the end of service were estimated. Extrapolation was done using a half-life of 7.6 years. Exposures were grouped into comparison, background, low and high. This allows for a shape of the dose-response curve to be evaluated. A continuous measure of TCDD was also examined (log 10 

### TCDD).

Conclusion Ranch Hand veterans were exposed to other contaminants in the herbicides that were mixed, thereby making it difficult to determine independ ent effects of TCDD on diabetes. In our view, this limitation precludes dose-response modeling of TCDD and diabetes using data from this cohort. 

## 1 2 B.2.8. Other Noncancer Studies of Dioxin 3
4 Table B-45. McBride et al., 2009a —Mortality (Noncancer) 5 6
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-57 Response Consideration satisfied. The New Zealan d Health Information Service Mortality Collection and the Registrar-General’s Index to Deaths were used to identify deaths. Additional searches were based on the last known address from the work record; the electoral roll and the habitation index; the telephone book; the internet; and Terranet property information database. An additional search was carried out through the Births, Deaths, and Marriages office of the New Zealand Department of Internal Affairs. Lastly, automated personnel and pension records were also used to locate past Ne w Plymouth workers and identify some deaths. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration satisfied. Workers lost to fo llow-up were an unlikely so urce of bias especially for internal analyses. Confounding by other coexposures (e.g., 2,4,6-TCP) unlikely to have resulted in bias, due to presumed poor correlation with TCDD. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. There was no cause of death among those considered for which a dose-response trend was observed across four exposure categories of TCDD. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Dichotomous exposure (exposed/unexposed) and duration of employment were examined from job exposure classification assessed via occupational history records industrial hygienists/factory personnel knowledge and questionnaires. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration not satisfied.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in J Occup Environ Med, 2009, 51:1049–1056. The other studies in the cohort highlight the 22% of the cohort lost to follow-up, the limited size of the cohort tissue sarcomas, differences in cohort definitions between sprayers and producers, and the potential for other exposures during employment at the plant. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria satisfied. Serum measures availa ble for 346 workers were used to derive TCDD exposures for the entire cohort using th e area under the curve approach. 3. Criteria The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. Dichotomous exposure assessment did not allow individual estimates of dose to be developed. However, noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

Conclusion A considerable portion of the cohort was lo st to follow-up, and no dose-response associations noted. As a result, the data are not suited to dose-response analysis. 

## 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-58 Table B-46. McBride et al., 2009b—Mortality (noncancer) 1 2
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration satisfied. The New Zealan d Health Information Service Mortality Collection and the Registrar-General’s Index to Deaths were used to identify deaths. Additional searches were based on the last known address from the work record; the electoral roll and the habitation index; the telephone book; the internet; and Terranet property information database. An additional search was carried out through the Births, Deaths, and Marriages office of the New Zealand Department of Internal Affairs. Lastly, automated personnel and pension records were also used to locate past Ne w Plymouth workers and identify some deaths. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. Considerable amount of workers were lost to follow up (22%), but it is unclear if bias resulted. The dichotomous exposure measure was based on exposure to TCDD, chlorinated dioxins and phenoxy herbicides, so confounding is a possibility by these coexposures. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. Because no individual exposure estimates were available for these analyses, dose-response could not be evaluated. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration satisfied. Consideration satisfied. Dichotomous exposure (exposed/unexposed) and duration of employment were examined from job exposure classification assessed via occupational history records industrial hygienists/factory personnel knowledge and questionnaires. Authors discuss limitations in the assignment of exposure among cohort members. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria satisfied. Published in Occup Medicine, 2009, 59(4):255–263. The authors highlight cohort lost to follow-up, the limited size of the cohort, differences in cohort definitions between sprayers and producers, and the potential for other exposures during employment at the plant. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed. Response Criteria not satisfied. Exposures were not quantified. The dichotomous exposure measure was based on exposure to TCDD, chlorinated dioxins and phenoxy herbicides. 3. Critiera The effective dose and oral exposure can be reasonably estimated and the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-59 Response Effective dose could not be estimated given the lack of individual-level exposure data. Noncancer mortality is not a viable endpoint to consider for further dose-response analysis.

Conclusion The study lacks the quantification of exposures at an individual level, and a considerableportion of the cohort was lost to follow-up. As a result, the data are not suited to doseresponse analysis. 

## 1 2 Table B-47. Ryan et al., 2002—Sex ratio 3 4
1. Consideration Methods used to ascertain health ou tcomes identified were unbiased, highly sensitive, and specific. Response Consideration not satisfied. Company records were used to identify births, the date of birth, and the sex of the child. No information was provided on the expected completeness of identifying births in this manner. Moreover, the study was expanded to include workers who heard about the study in a public forum. Therefore, the study could be influenced by participation bias. 2. Consideration Risk estimates are not susceptible to biases from confounding exposures or from study design or statistical analysis. Response Consideration not satisfied. See above. 3. Consideration Study demonstrates an association between TCDD and adverse health effect with evidence of an exposure-response relationship. Response Consideration not satisfied. The study compared birth ratios among men and women employed at the plant to the general population. No categories of exposure were examined. 4. Consideration Exposure assessment methodology is clear and adequately characterizes individual-level exposures. The limitations and uncertainties in the exposure assessment are considered. Response Consideration not satisfied. This is not relevant as no analyses were done in relation to exposure levels. 5. Consideration Study size and follow-up are large enough to yield precise estimates of risk and ensure adequate statistical power. Response Consideration satisfied. For the categorie s of exposure used (yes/no), and the stratified analyses by sex and subcohort, the study allows for the birth ratios to be estimated with sufficient precision.

1. Criteria Study is published in the peer-reviewed sc ientific literature and has an appropriate discussion of the strengths and limitations. Response Criteria not satisfied. Published in Envi ron Health Perspect, 2002, 110(11):A699–A701. The authors discussed the limitations of using serum collected many years after they stopped working to estimate TCDD exposures when the preferred metric would be TCDD levels at the time of conception. They did not address issues about the representativeness of the study participants to the entire cohort of workers, nor did they address the limitation of not being able to conduct dose-response analyses using individual-level TCDD data. 2. Criteria Exposure must be primarily TCDD and is properly quantified so that dose-response relationships can be assessed.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-60 Response Criteria not satisfied. While serum measures were available for 84 of the 198 participants of the study, birth ratios were compared between the cohort of 2,4,5-T and 2,4,5-trichlorphgenol workers relative to the city of Ufa. There was no attempt to derive birth ratios in relation to exposure levels. The serum data were only used to demonstrate that these workers, on average, had TCDD levels 30 times higher than Ufa residents. 3. Criteria The effective dose and oral exposure can be reasonably estimated an d the measures of exposure are consistent with the current biological understanding of dose. The reported dose is consistent with a toxicologically relevant dose. Latency and appropriate window(s) of exposure examined. Response ha s to be a nonfatal endpoint. Response Criteria not satisfied. TCDD exposures were based on seru m measures taken in some cases many years after children were born; no attempt was made to back-extrapolate to the time of conception.

Conclusion The data are not suitable for dose-response modeling. Risk estimates have not been derived in relation to TCDD exposure levels. There exist uncertainties about the representativeness of the participants in relation to the cohort as a whole, and insufficient details are provided to evaluate the extent in which all births were identified. While these data should not be used for quantitative dose-response modeling, the much lowe r M/F birth ratio among exposed fathers is consistent with the finding by Mocarelli et al, and lends support to those findings. 

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## 20
Flesch-Janys, D; Berger, J; Gurn, P; et al. (1995) Exposure to polychlorinated dioxins and furans (PCDD/F) and 

## 21 mortality in a cohort of workers from a herbicide-producing plant in Hamburg, Federal Republic of Germany. Am J 

## 22 Epidemiol 142(11):1165

− 1175. 

## 23
Flesch-Janys, D; Becher, H; Gurn, P; et al. (1996) Elimination of polychlorinated dibenzo-p-dioxins and 

## 24 dibenzofurans in occupationally exposed persons. J Tox Environ Health 47(4):363

− 378. 

## 25
Flesch-Janys, D; Steind orf, K; Gurn, P; et al. (1998) Estimation of the cumulated exposure to polychlorinated 

## 26 dibenzo-p-dioxins/furans and standardized mortality ratio anal ysis of cancer mortality by dose in an occupationally 

## 27 exposed cohort. Environ Health Perspect 106(Suppl 2):655

− 662. 

## 28
Hooiveld, M; Heederik, DJ; Kogevinas, M; et al. (1998) Second follow-up of a Dutch cohort occupationally 

## 29 exposed to phenoxy herbicides, chlorophenols, and contaminants. Am J Epidemiol 147(9):891

− 901. 

## 30
Manz, A; Berger, J; Dwyer, JH; et al . (1991) Cancer mortality among workers in chemical plant contaminated with 

## 31 dioxin. Lancet 338(8773):959

− 964. 

## 32
McBride, DI; Collins, JJ; Humphry, NF; et al. (2009a) Mortality in workers exposed to 2,3,7,8-tetrachlorodibenzo

## 33 p-dioxin at a trichlorophenol plant in New Zealand. J Occup Environ Med 51(9):1049-1056. 

## 34
McBride, DI; Burns, CJ; Herbison, GP; et al. (2009b) Mortality in employees at a New Zealand agrochemical 

## 35 manufacturing site. Occup Med (Oxford, England) 59(4):255

− 263. 

## 36
Michalek, JE; Pavuk, M. (200 8) Diabetes and cancer in veterans of Op eration Ranch Hand after adjustment for 

## 37 calendar period, days of spraying, and time spent in Southeast Asia. J Occup Environ Med 50(3):330

− 340. 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE B-62 Mocarelli, P; Gerthoux, PM; Ferrari, E; et al. (2000) Paternal concentrations of dioxin an d sex ratio of offspring. 

## 1 Lancet 355(9218):1858

− 1863. 

## 2
Mocarelli, P; Gerthoux, PM; Patterson, DG, Jr.; et al . (2008) Dioxin exposure, from infancy through puberty, 

## 3 produces endocrine disruption and affects human se men quality. Environ Health Perspect 116(1):70

− 77. 

## 4
Ott, MG; Zober, A. (1996) Cause specific mortality and cancer incidence among employees exposed to 

## 5 2,3,7,8-TCDD after a 1953 reactor acci dent. Occup Environ Med 53(9):606

− 612. 

## 6
Pesatori, AC; Consonni, D; Bachetti, S; et al. (2003) Short- and long-term morbidity and mortality in the population 

## 7 exposed to dioxin after the “Seves o accident”. Ind Health 41(3):127

− 138. 

## 8
Revich, B; Aksel, E; Ushakova, T; et al. (2001) Dioxin exposure and public health in Chapaevsk, Russia. 

## 9 Chemosphere 43(4

− 7):951

− 966. 

## 10
Ryan, JJ; Amirova, Z; Carrier, G. (2002) Sex ratios of children of Russian pesticide producers exposed to dioxin. 

## 11 Environ Health Perspect
, 110(11):A699-701. 

## 12
Steenland, K; Piacitelli, L; Deddens, J; et al. (1999) Can cer, heart disease, and diabet es in workers exposed to 

## 13 2,3,7,8-tetrachlorodibenzo-p-dioxin. J Natl Cancer I 91(9):779

− 786. 

## 14
Steenland, K; Deddens, J; Piacitelli, L. (2001) Risk a ssessment for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) 

## 15 based on an epidemiologic study. Am J Epidemiol 154(5):451-458. 

## 16
’t Mannetje, A; McLean, D; Cheng, S; et al. (2005) Mortality in New Zealand workers exposed to phenoxy 

## 17 herbicides and dioxins. Occup Environ Med 62(1):34

− 40. 

## 18
Warner, M; Eskenazi, B; Mocarelli, P; et al. (2002) Seru m dioxin concentrations and breast cancer risk in the 

## 19 Seveso Women’s Health Study. Environ Health Perspect 110(7):625

− 628. 

## 20
Warner, M; Samuels, S; Mocarelli, P; et al. (2004) Serum dioxin concentrations and age at menarche. Environ 

## 21 Health Perspect 112(13):1289

− 1292. 

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Warner, M; Eskenazi, B; Olive, DL; et al. (2007) Serum dioxin concentrations and quality of ovarian function in 

## 23 women of Seveso. Environ Health Perspect 115(3):336

− 340. 

## 24
Zober, A; Messerer, P; Huber, P. (1990) Thirty-four-year mortality follow-up of BASF employees exposed to 

## 25 2,3,7,8-TCDD after the 1953 accident. In t Arch Occup Environ Health 62(2):139

− 157. 

## 26

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX C
Kinetic Modeling

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE C-ii CONTENTS—APPENDIX C: Kinetic Modeling

APPENDIX C. KINETIC MODELING................................................................................... C-1 1 C.1. LITERATURE SEARCH STRATEGY AND RESULTS—IDENTIFYING 2 RECE NT PUBLICATIONS FOR UP DATING TCDD TO XICOKINETIC 3 MODEL INPUT PARAMETERS............................................................................... C-1 4 C.1.1. Data Bases Searched ....................................................................................... C-1 5 C.1.2. Literature Search Strategy and Approach .......................................................C-2 6 C.1.2.1

. Chemical Search Terms—DIALOG Search................................... C-2 C.1.2.2. Primary Search Terms (Species)—DIALOG Search ..................... C-2 C.1.2.3. Secondary Search Terms (Toxicology)—DIALOG Search ........... C-3 C.1.3. Citation Screening Procedures and Results..................................................... C-3 7 C.1.4. References Selected for More Deta iled Review for Updating the PBPK 8 Models

............................................................................................................. C-6 9 C.1.5. Brief Descriptions of DIALOG Bi bliographic Data Bases Searched

............. C-8 10 C.2. TOXICOKINETIC MODELING CODE (EMOND ET AL., 2005)

........................ C-10 11 C.2.1. Human Standard Model................................................................................. C-10 12 C.2.1.1. Model Code................................................................................... C-10 C.2.1.2

. Input File....................................................................................... C-20 C.2.2. Human Gestational Model............................................................................. C-21 13 C.2.2.1

. Model Code................................................................................... C-21 C.2.2.2. Input File....................................................................................... C-35 C.2.3. Rat Standard Model.......................................................................................C-36 14 C.2.3.1

. Model Code................................................................................... C-36 C.2.3.2. Input Files ..................................................................................... C-46 C.2.3.2.1

. Cantoni et al. (1981). .................................................. C-46 15 C.2.3.2.2. Chu et al. (2007). ........................................................C-46 16 C.2.3.2.3. Crofton et al. (2005)....................................................C-47 17 C.2.3.2.4. Fattore et al. (2000).....................................................C-48 18 C.2.3.2.5. Hassoun et al. (2000). ................................................. C-48 19 C.2.3.2.6. Kitchin and Woods (1979).......................................... C-49 20 C.2.3.2.7. Kociba et al. (1976) (13 weeks).................................. C-50 21 C.2.3.2.8. Kociba et al. (1978) (female) (104 weeks).

................ C-51 22 C.2.3.2.9. Kociba et al. (1978) (m ale) (104 weeks). ................... C-51 23 C.2.3.2.10. Latchoumycandane and Mathur. (2002)..................... C-52 24 C.2.3.2.11. Li et al. (1997).............................................................C-53 25 C.2.3.2.12. Murray et al. (1979). ...................................................C-53 26 C.2.3.2.13. NTP (1982) (female) (chronic). .................................. C-54 27 C.2.3.2.14. NTP (1982) (male) (chronic). ..................................... C-55 28 C.2.3.2.15. NTP (2006) 31 weeks. ................................................C-55 29 C.2.3.2.16. NTP (2006) 53 weeks. ................................................C-56 30 C.2.3.2.17. NTP (2006) 2 year. .....................................................C-57 31 C.2.3.2.18. Sewall et al. (1995). .................................................... C-58 32 C.2.3.2.19. Shi et al. (2007), adult portion. ................................... C-58 33 C.2.3.2.20. Van Birgelen et al. (1995)........................................... C-59 34

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— DO NOT CITE OR QUOTE C-iii CONTENTS (continued) 1 2 3 C.2.3.2.21. Vanden Heuvel et al. (1994). ...................................... C-60 4 C.2.4. Rat Gestational Model...................................................................................C-60 5 C.2.4.1. Model Code................................................................................... C-60 C.2.4.2. Input Files ..................................................................................... C-74 C.2.4.2.1. Bell et al. (2007). ........................................................ C-74 6 C.2.4.2.2. Hojo et al. (2002). ....................................................... C-75 7 C.2.4.2.3. Ikeda et al. (2005). ...................................................... C-76 8 C.2.4.2.4. Kattainen et al. (2001)................................................. C-77 9 C.2.4.2.5. Markowski et al. (2001).............................................. C-78 10 C.2.4.2.6. Miettinen et al. (2006)................................................. C-78 11 C.2.4.2.7. Murray et al. (1979). ...................................................C-79 12 C.2.4.2.8. Nohara et al. (2000). ...................................................C-80 13 C.2.4.2.9. Ohsako et al. (2001)....................................................C-81 14 C.2.4.2.10. Schantz et al. (1996) and Amin et al. (2000). ............. C-82 15 C.2.4.2.11

. Seo et al. (1995). ......................................................... C-82 16 C.2.4.2.12. Shi et al. (2007)...........................................................C-83 17 C.2.5. Mouse Standard Model .................................................................................C-84 18 C.2.5.1. Model Code................................................................................... C-84 C.2.5.2. Input Files ..................................................................................... C-94 C.2.5.2.1. Hassoun et al. (1998) (13 weeks)................................ C-94 19 C.2.5.2.2. NTP (1982) (male) (chronic). ..................................... C-96 20 C.2.5.2.3. Smialowicz et al. (2008). ............................................ C-96 21 C.2.5.2.4. Toth et al. (1979) (1 year)........................................... C-97 22 C.2.5.2.5. Toth et al. (1979) (2 year)........................................... C-98 23 C.2.5.2.6. White et al. (1986). ..................................................... C-99 24 C.2.6. Mouse Gestational Model ...........................................................................C-100 25 C.2.6.1. Model Code................................................................................. C-100 C.2.6.2. Input Files ................................................................................... C-113 C.2.6.2.1. Keller et al. (2007). ................................................... C-113 26 C.2.6.2.2. Li et al. (2005)...........................................................C-114 27 C.3. TOXICOKINETIC MODELING RESULTS FOR KEY ANIMAL 28 BIOASSAY STUDIES ............................................................................................C-115 29 C.3.1. Nongestational Studies ................................................................................ C-115 30 C.3.1.1. Cantoni et al. (1981) ................................................................... C-115 C.3.1.2. Chu et al. (2007) .........................................................................C-117 C.3.1.3. Crofton et al. (2005)....................................................................C-119 C.3.1.4. Fattore et al. (2000)..................................................................... C-122 C.3.1.5

. Hassoun et al. (1998) .................................................................. C-124 C.3.1.6. Hassoun et al. (2000) ..................................................................C-126 C.3.1.7. Kitchin and Woods (1979).......................................................... C-129 C.3.1.8. Kociba et al. (1976).....................................................................C-132 C.3.1.9. Kociba et al. (1978) Female........................................................C-134 31

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— DO NOT CITE OR QUOTE C-iv CONTENTS (continued) 1 2 3 C.3.1.10

. Kociba et al. (1978) Male ........................................................... C-136 C.3.1.11

. Latchoumycandane and Mathur (2002)...................................... C-138 C.3.1.12

. Li et al. (1997).............................................................................C-139 C.3.1.13. NTP (1982)—Female Rats, Chronic...........................................C-143 C.3.1.14. NTP (1982)—Male Rats, Chronic ..............................................C-144 C.3.1.15. NTP (1982)—Female Mice, Chronic .........................................C-146 C.3.1.16. NTP (1982)—Male Mice, Chronic.............................................C-148 C.3.1.17

. NTP (2006) 31 Weeks ................................................................ C-150 C.3.1.18. NTP (2006) 53 Weeks ................................................................ C-152 C.3.1.19. NTP (2006) 2 Years....................................................................C-154 C.3.1.20. Sewall et al. (1995) ..................................................................... C-156 C.3.1.21. Smialowicz et al. (2008) ............................................................. C-158 C.3.1.22. Toth et al., 1 Year (1979)............................................................C-160 C.3.1.23. Van Birgelen (1995) ...................................................................C-162 C.3.1.24. Vanden Heuvel et al. (1994) ....................................................... C-164 C.3.1.25. White et al. (1986) ...................................................................... C-167 C.3.2. Gestational Studies...................................................................................... C-170 4 C.3.2.1. Bell et al. (2007) ......................................................................... C-170 C.3.2.2. Hojo et al. (2002) ........................................................................ C-171 C.3.2.3. Ikeda et al. (2005) ....................................................................... C-173 C.3.2.4. Kattainen et al. (2001)................................................................. C-174 C.3.2.5. Keller et al. (2007) ...................................................................... C-175 C.3.2.6. Li et al. (2006) 3-Day..................................................................C-177 C.3.2.7. Markowski et al. (2001).............................................................. C-178 C.3.2.8. Mietinnen et al. (2006)................................................................C-180 C.3.2.9. Murray et al. (1979) Gestational Portion ....................................C-181 C.3.2.10. Murray et al. (1979) Adult Portion ............................................. C-183 C.3.2.11. Nohara et al. (2000) ....................................................................C-185 C.3.2.12. Ohsako et al. (2001)....................................................................C-186 C.3.2.13. Schantz et al. (1995) and Amin et al. (2000) .............................. C-188 C.3.2.14. Seo et al. (1995) .......................................................................... C-189 C.3.2.15. Shi et al. (2007) Gestational Portion........................................... C-191 C.3.2.16. Shi et al. (2007) Adult Portion.................................................... C-192 C.4. REFERENCES........................................................................................................ C-196 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-1 DRAFT

— DO NOT CITE OR QUOTE APPENDIX C. KINETIC MODELING 1 2 3 C.1. LITERATURE SEARCH STRATEGY AND RESULTS —IDENTIFYING RECENT 4 PUBLICATIONS FOR UPDATING TCDD TOXICOKINETIC MODEL INPUT 5 PARAMETERS 6 The purpose of this literature search was to identify recent publications that address the 7 input parameters for the physiologically based pharmacokinetic (PBPK) models Aylward and 8 colleagues described in 2004–2005 and Emond and colleagues described in 2004–2006. This 9 literature search was part of the U.S. Environm ental Protection Agency (E PA)’s preparation of a 10 response to the National Acad emy of Sciences’ review ( Health Risks from Dioxin and Related 11 Compounds: Evaluation of the EPA Reassessment , NAS, 2006]) of EPA Reassessment of Health 12 Risks From Dioxin and Related Compounds (2003 Reassessment, U.S. EPA, 2003). English13 only references from 2003 to May 2009 were search ed using bibliographic data bases relevant to 14
health effects and toxicol ogy of 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD). The search 15
focused on toxicokinetic data that could be used to update the dynamic disposition of 16 2,3,7,8-TCDD in mice, rats, guinea pigs, monkeys, and humans. 17 In the primary search, EPA identified 775 distinct citations based on th e literature search 18 criteria described below. EPA also performe d an independent supplemental search to avoid 19 missing key studies. EPA identified 28 papers for fu rther analysis that appeared on first review 20 to report data to update the input paramete rs of the Aylward a nd Emond PBPK models; 21
considerations for selection are described in Section C.1.3. 22
23
C.1.1. Data Bases Searched 24 EPA used the following DIALOG bi bliographic da ta bases in the primary search. Brief 25 descriptions of the DIALOG data bases searched are provid ed in Section C.1.5. 26
27
1. File 6: NTIS 28
2. File 41: Pollution Abstracts 29
3. File 55: Biosis 30
4. File 153: IPA Toxicology 31
5. File 155: MedLine 32
6. File 156: ToxFile 33

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-2 DRAFT

— DO NOT CITE OR QUOTE 7. File 157: Biosis Toxicology 1
8. File 159: CancerLit 2
9. File 336: RTECS 3 4 The PUBMED data base was used for the supplemental search. 5
6
C.1.2. Literature Search Strategy and Approach 7 The prim ary search used a tiered key-word approach, as documented below. The 8 principal search term was the Chemical Abstract Service Registry Number (CASRN) or specific 9 chemical name, 2,3,7,8-tetrachlorodibenzo- p -dioxin or 2,3,7,8-TCDD. Th e next tier of search 10 terms was species, and finally toxi cokinetic keywords, as listed be low. The period of the search 11 was 2003 through May 2009, and articles we re limited to English language. 12 The supplemental PUBMED search was limited to the most recent five years (2004 to 13 present) and used four combinations of key words: 14
15

• TCDD + pharmacokinetic + humans, 16

• TCDD + toxicokinetic + humans, 17

• TCDD + pharmacokinetic + animals, and 18

• TCDD + toxicokinetic + animals. 19 20

C.1.2.1. Chemical Search Terms

— DIALOG Search 21

• CASRN: 1746-01-6 22

• 2,3,7,8-tetrachlorodibenzo- p -dioxin 23

• 2,3,7,8-TCDD 24 25

C.1.2.2. Primary Search Terms (Species)

— DIALOG Search 26

• Guinea pig(s) 27

• Human(s) 28

• Monkey(s) 29

• Mouse 30

• Mice 31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-3 DRAFT

— DO NOT CITE OR QUOTE • Rodent(s) 1

• Rat(s) 2 3
C.1.2.3. Secondary Search Terms (Toxicology)

— DIALOG Search 4
5 1. Absor*
2. ADME 3. Aryl hydrocarbon receptor 4. AhR
5. Bioavail*
6. Biliar*
7. Biotransform* 8. Cytochrome
9. CYP*
10. CYP1A1
11. CYP1A2 12. Diet, dietary, diets 13. Disposit*
14. Distrib*
15. Drink* 16. Elimin*
17. Excret* 18. Epidemiolog*
19. Feces 20. Feed*
21. First order kinetics
22. Food*
23. Gastro* 24. Gavage*
25. Half-life
26. Induct* 27. Ingest*
28. In silico
29. Kinetic*
30. Liver 31. Lymph* 32. Mechanism (1w) action
33. Metabo*
34. Oral*
35. P450 36. Partition coefficient
37. PBPK 38. Pharmacodynamic*
39. Pharmacokinetic* 40. Physiologically based 41. pharmacokinetic
42. Protein bind*
43. Toxicokinetic*
44. Urin*

1 ADME = absorption, distribution, metabolism, elimination; AhR = aryl hydrocarbon receptor; CYP = 

## 2 cytochrome P450; 

## * = truncated; 1w = terms are within 1 word of each other and in the order 3 specified (see search term 32 4 5 6 C.1.3. Citation Screening Procedures and Result s 7 Initial DIALOG searches resulted in a very large number of citati on hits. Therefore, 8 some title and key word restrictions were applied iteratively to screen out less relevant citations 9 (e.g., requiring some search terms in title, requiring 2,3,7,8-TCDD rather than just TCDD). 10 Then, using reference management software, pooled information obtained from the various 11
DIALOG data bases was screened to remove duplicates. Citations then were numbered 12 sequentially (as a unique identi fier). Information retrieve d included the following (when 13 available): author(s), publica tion year, title, source document name, volume, and page numbers. 14

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-4 DRAFT

— DO NOT CITE OR QUOTE The DIALOG search and duplicate removal pr ocedure produced 775 unique citations. In 1 the next step, all 775 citations we re screened for potential appli cability to updating parameters in 2 the Aylward and Emond PBPK models. Of thes e 775 citations, 26 were selected for more 3 detailed review to determine their potential ap plicability, and full publica tions were retrieved. 4 Two citations were added from the supplemental search, giving a total of 28 articles identified 5
for further review. 6 Bibliographic information for the 28 articles selected for full review is provided in the 7
reference list at the end of th is section. Table C-1 summarizes the model input parameters 8 potentially addressed by the selected articles. 9 During 2003 to May 2009, the authors of the two kinetic models under consideration 10 published several articles. For the Emond model, which was first published in 2004 (Emond et 11 al., 2004), two subsequent papers have been pu blished (Emond et al., 2005, 2006). The Aylward 12 model, which originated from the 1995 papers by Carrier et al. (1995a, b), was later updated by 13 the same group (Aylward et al., 2004, 2005). The major change implemented in the last two 14 papers was the description of a desorption proce ss in the digestive tract. The transfer rate 15 described is slow, but for a low body burden of TC DD, this process remains significant. This 16 concept was reported in 2002 by Moser and McL achlan (2002). The major modifications 17 expected to update the Emond m odel are (1) consideration of the desorption process in the 18 gastrointestinal tract and (2) rearrangement of the elimination constant, which will have a 19 negligible impact on the simulation. These ch anges are motivated by plausible observations 20 reported in the literature. 21 Because of the body burden found in humans and the importance of selecting an 22 appropriate dose metric in human risk assessment, the physiological model is an important tool 23 for assessing the kinetics following exposure to TCDD (Kim et al., 2003). Based on the 24 literature identified in this search, the major contri butions that should be reviewed with respect to 25 the Aylward and Emond kinetic models are not m odes of action or pharmacokinetic mechanisms, 26 but rather information for verifying or impr oving the accuracy of some model parameters. 27 Pharmacokinetics typically refers to four dis tinct steps including ab sorption, distribution, 28 metabolism, and excretion. Physiologically-based models consider each step. In the model each 29 step is parameterized to reflect better predic tions of the real obse rvations. Occasionally, 30 reviewing th ese models is essential to determin e if any key processes or parameters might be 31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-5 DRAFT

— DO NOT CITE OR QUOTE described with better accuracy. This perspective underlies the revi ew of the literature described 1 here. The review indicates TCDD disposition has become recognized as relatively significant 2 since the publication of the Emond and Aylward models. The literature that provides 3 information related to improving these models, however, is limite d. For the benefit of this 4 exercise, EPA selected the literatu re that would likely contribute significantly to model response, 5 or to clarify or confirm different key issues driving the model re sults. Regarding the two TCDD 6 models, the two major issues that should be evaluated with respect to the recent literature 7 identified are the elimination profile and the induction of CYP1A2. 8 Reviewing the elimination variation in differe nt species and testing variable elimination 9 with a data set appears to be appropriate. Th e literature reports that various factors might 10 influence elimination rate. Recent publications report the influence of di verse predictors such 11 age, body fat, or smoking habit on the elimination half-life (Milbrath et al., 2009; Kerger et al., 12 2006, 2007). Determining whether using the Milbrath et al. information would help account for 13 intraspecies variability in elim ination rate in the Emond and Ay lward kinetic models would be 14 useful. In 2006, Emond et al. reviewed the influence of body fat mass and CYP1A2 induction on 15 the pharmacokinetics of TCDD. These two f actors appear to cont ribute significantly to 16
elimination and their influences seem to be driven by TCDD body burden. Mullerova and 17 Kopecky (2007) discussed the influence of adip ose tissue and the “yo-yo” effects on various 18 diseases that might be influenced by persis tent organic pollutant distribution. One group 19 explored the importance of variable elimination and compared these pred ictions to first-order 20 elimination using the Aylward and Emond models and supported these approaches for risk 21 assessment (Heinzl et al., 2007). Two groups of authors considered a one-compartment model to 22
derive the elimination half-lif e (Aylward et al., 2009; Nada l et al., 2008). Comparing the 23 half-life they obtained using this approach for a range of body burden to the variable elimination 24
half-life would be interesting. 25 The second important mechanism driving the di stribution and elimination of TCDD is the 26 induction of CYP1A2, identified as the major ligand protein in liver (Dilib erto et al., 1997). For 27 that process, authors suggested different aspe cts that should be inve stigated, including the 28
im portance of the dose metrics in the target tissue and the inducible level of CYP1A2 (Wilkes 29 et al., 2008; Staskal et al., 2005). Other papers address the intras pecies variability of lethal 30 potency in mature species versus the developing fetus (Kransler et al., 2007; Korkalainen et al., 31

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— DO NOT CITE OR QUOTE 2004). Still others point out pronounced differences among sp ecies (namely, guinea pigs, 1 hamsters, mice, and rats) (Bohonowych and Denis on, 2007), as observed in studies of long-term 2
effects of low TCDD dose in li ver and in studies comparing he patic accumulation and clearance 3 of TCDD (Korenaga et al., 2007; Boverhof et al ., 2005). The interspeci es variation of the 4 binding affinity constant of AhR also has been reported (Connor and Aylward, 2006; Nohara 5 et al., 2006). 6
The articles identified in this literature review should be adequate to update the Aylward 7 and Emond models, which need to be evaluated acco rding to the same structure of compartments 8
described in the literature by the two model authors. 9
10
C.1.4. References Selected for More Detailed Re view for Updating the PBPK Models 11 Aylward, LL; Brunet, RC; Carrier, G; et al. (2004) Concentration-dependent TCDD elimination kinetics in humans: toxicokinetic modeling for moderately to highly exposed adults from Seveso, Italy, and Vienna, Austria, and impact on dose estimates for the NIOSH cohort. J Expo Anal Environ Epidemiol 15(1):51

− 65.
Aylward, LL; Brunet, RC; Starr, TB; et al. (2005) Exposure reconstruction for the TCDD-exposed NIOSH cohort using a concentration- and age-dependent model of elimination. Risk Anal 25(4):945

− 956.
Aylward, LL; Bodner, KM; Collins, JJ; et al. (2009) TC DD exposure estimation for workers at a New Zealand 2,4,5-T manufacturing facility based on serum sampling data. J Expo Sci Environ Epidemiol. doi: 10.1038/jes.2009.31.
Bohonowych, JE; Denison, MS. (2007) Persistent binding of ligands to the aryl hydrocarbon receptor. Toxicol Sci 98(1):99–109.
Boverhof, DR; Burgoon, LD; Tashiro, C; et al. (2005) Temporal and dose-dependent hepatic gene expression patterns in mice provide new insights into TCDD-mediated hepatotoxicity. Toxicol Sci 85(2):1048

− 1063.
Connor, KT; Aylward, LL. (2006) Human response to dioxin: aryl hydrocarbon receptor (AhR) molecular structure, function, and dose-response data for enzyme induction indicate an impaired human AhR. J Toxicol Environ Health B 9(2):147

− 171.
Heinzl, H; Mittlback, M; Edler, L. (2007) On the transla tion of uncertainty from toxicokinetic to toxicodynamic models - the TCDD example. Chemosphere 67(9):S365

− S374.
Irigaray, P; Mejean, L; Laurent, F. (2005) Behaviour of dioxin in pig adipocytes. Food Chem Toxicol 43(3):457

− 460.
Kerger, BD; Leung, HW; Scott, P; et al. (2006) Age- an d concentration-dependent elimination half-life of 2,3,7,8- tetrachlorodibenzo-p-dioxin in Seveso children. Environ Health Perspect 114(10):1596

− 1602.
Kerger, BD; Leung, HW; Scott, PK; et al. (2007) Refinements on the age-dependent half-life model for estimating child body burdens of polychlorodibenzodioxins and dibenzofurans. Chemosphere 67(9):S272

− S278.
Kim, AH; Kohn, MC; Nyska, A; et al. (2003) Area unde r the curve as a dose metric for promotional responses following 2,3,7,8-tetrachlorodibenzo-p-dioxin exposure. Toxicol Appl Pharmacol 191(1):12

− 21.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-7 DRAFT

— DO NOT CITE OR QUOTE Korenaga, T; Fukusato, T; Ohta, M; et al. (2007) Long-term effects of subcutaneously injected 2,3,7,8- tetrachlorodibenzo-p-dioxin on the liver of rhesus monkeys. Chemosphere 67(9):S399

− S404.
Korkalainen, M; Tuomisto, J; Pohjanvirta, R. (2004) Primary structure an d inducibility by 2,3,7,8- tetrachlorodibenzo-p-dioxin (TCDD) of aryl hydrocarbon receptor repres sor in a TCDD-sensitive and a TCDDresistant rat strain. Biochem Biophys Res Communications 315(1):123

− 131.
Kransler, KM; McGarrigle, BP; Olson, JR. (2007) Comparative developmental toxicity of 2,3,7,8- tetrachlorodibenzo-p-dioxin in the hamster, rat and guinea pig. Toxicology 229(3):214

− 225.
Maruyama, W; Yoshida, K; Tanaka, T; et al. (2002) Dete rmination of tissue-blood pa rtition coefficients for a physiological model for humans, and estimation of dioxin concentration in tissues. Chemosphere 46(7):975

− 985.
Maruyama, W; Yoshida, K; Tanaka, T; et al. (2003) Simulation of dioxin accumulation in human tissues and analysis of reproductive risk. Chemosphere 53(4):301-313.
Maruyama, W; Aoki, Y. (2006) Estimated cancer risk of dioxins to humans using a bioassay and physiologically based pharmacokinetic model. Toxicol Appl Pharmacol 214(2):188

− 198.
Milbrath, MO; Wenger, Y; Chang, C-W; et al. (2009) Apparent Half-Lives of Dioxins, Furans, and Polychlorinated Biphenyls as a Function of Age, Body Fat, Smoking Status, and Breast-Feeding. Environ Health Perspect 117(3):417

− 425.
Moser, GA; McLachlan, MS. (2002) Modeling digestiv e tract absorption and desorption of lipophilic organic contaminants in humans. Environ Sci Technol 36(15):3318

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Mullerova, D; Kopecky, J. (2007) White adipose tissue: st orage and effector site for environmental pollutants. Physiol Res 56(4):375

− 381.
Nadal, M; Perello, G; Schuhmacher, M; et al. (2008) Concentrations of PCDD/PCDFs in plasma of subjects living in the vicinity of a hazardous wast e incinerator: Follow-up and modeling validation. Chemosphere 73(6):901

− 906.
Nohara, K; Ao, K; Miyamoto, Y; et al. (2006) Comparison of the 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)- induced CYP1A1 gene expression profile in lymphocytes from mice, rats, and humans: Most potent induction in humans. Toxicology 225(2-3):204

− 213.
Olsman, H; Engwall, M; Kammann, U; et al. (2007) Relative differences in aryl hydrocarbon receptor-mediated response for 18 polybrominated and mixed halogenated dibenzo-p-dioxins and -furans in cell lines from four different species. Environ Toxicol Chem 26(11):2448

− 2454.
Saghir, SA; Lebofsky, M; Pinson, DM; et al. (2005) Validat ion of Haber's Rule (doseX time=constant) in rats and mice for monochloroacetic acid and 2,3,7,8-tetrachlorodibenzo-p-dioxin under conditions of kinetic steady state. Toxicology 215(1

− 2):48

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Schecter, A; Pavuk, M; Popke, O; et al. (2003) Dioxin, dibenzofuran, and coplanar PCB Levels in Laotian blood and milk from Agent Orange-sprayed and nonsprayed areas, 2001. J Toxicol Environ Health A 66(21):2067

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Staskal, DF; Diliberto, JJ; Devito, MJ; et al. (2005) Inhi bition of human and rat CYP1A2 by TCDD and dioxin-like chemicals. Toxicol Sci 84(2):225

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Toyoshiba, H; Walker, NJ; Bailer, AJ ; et al. (2004) Evaluation of toxic equivalency factors for induction of cytochromes P450 CYP1A1 and CYP1A2 enzyme activity by dioxin-like compounds. Toxicol Appl Pharmacol 194(2):156

− 168.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-8 DRAFT

— DO NOT CITE OR QUOTE Wilkes, JG; Hass, BS; Buzatu, DA; et al. (2008) Modelin g and assaying dioxin-like biological effects for both dioxin-like and certain non-dioxin-like compounds. Toxicol Sci 102(1):187

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## C.1.5. Brief Descriptions of DIALOG Bib liographic Data Bases Searched 1 The National Technical Infor mation Service (NTIS) database comprises summaries of 2 U.S. government-sponsored research, development, and engineering, plus analyses prepared by 3 federal agencies, their contract ors, or grantees. It is th e means through which unclassified, 4 publicly available, unlimited distri bution reports are made available for sale from 240 agencies. 5 Additionally, some state and local government agencies contribute summaries of their reports to 6 the database. NTIS also provides access to the results of government-s ponsored research and 7 development from countries outside the United States . Organizations that cu rrently contribute to 8 the NTIS database include but are not limited to the following: the Japan Ministry of 9 International Trade and Industry (MITI); labor atories administered by the United Kingdom 10 Department of Industry; the German Federal Mi nistry of Research and Technology (BMFT); and 11 the French National Center for Scientific Research (CNRS). 12 Pollution Abstracts provides access to e nvironmental information that combines 13 information on scientific research and government policies in a single resource. Topics of 14 growing concern are extensively covered from the standpoints of atmosphere, emissions, 15 mathematical models, effects on people and anim als, and environmental action in response to 16 global pollution issues. This data base also contains material from conference proceedings and 17
hard-to-find summarized documents along with information from prim ary journals in the field of 18 pollution. 19 BIOSIS Previews® contains citations from Biological Abstracts® (BA) and Biological 20 Abstracts/Reports, Reviews, and Meetings® (B A/RRM) (formerly BioResearch Index®), the 21 major publications of BIOSIS®. These publica tions constitute the major English-language 22 service providing comprehensiv e worldwide coverage of rese arch in the biological and 23 biomedical sciences. Biological Abstracts incl udes approximately 350,000 accounts of original 24 research yearly from nearly 5,000 primary jour nal and monograph titles. BA/RRM includes an 25 additional 200,000+ citations a year from mee ting abstracts, reviews, books, book chapters, 26 notes, letters, and selected reports. 27

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-9 DRAFT

— DO NOT CITE OR QUOTE IPA Toxicology provides focused toxico logy information on all phases of the 1 development and use of drugs and on professional pharmaceutical practice. The scope of the 2 database ranges from the clinical and practical to the theoretical aspects of toxico logy literature. 3 A unique feature of abstracts re porting clinical studi es is the inclusion of the study design, 4 number of patients, dosage, dosage forms, and dosage schedule. 5 Medical Literature, Analysis, and Retrie val System Online (MEDLINE®), produced by 6 the U.S. National Library of Medicine (NLM), is NLM’s premier bibliographic database. It 7 contains more than 15 million references to jour nal articles in life sciences with a concentration 8 on biomedicine. The broad coverage of the data base includes basic biomed ical research and the 9
clinical sciences sinc e 1950, including nursing, de ntistry, veterinary medicine, pharmacy, allied 10 health, and pre-clinical scienc es. MEDLINE® also covers life sciences that are vital to 11 biomedical practitioners, researchers, and e ducators, including some aspects of biology, 12 environmental science, marine bi ology, and plant and animal scie nce, as well as biophysics and 13 chemistry. MEDLINE® is indexed using NL M's controlled vocabulary, Medical Subject 14 Headings (MeSH®). Approximately 400,000 records are added per year, of which more than 76 15 percent are in English. MEDLINE® contains AIDSLINE, HealthSTAR, Toxline, In Process 16 (formerly known as Pre-MEDLINE®), In Data Review, and POPLINE. 17 ToxFile covers the toxicological, pharm acological, biochemical, and physiological 18 effects of drugs and other chemicals. Advers e drug reactions, chemica lly induced diseases, 19 carcinogenesis, mutagenesis, teratogenesis, environmental pollution, waste disposal, radiation, 20 and food contamination are typical areas of c overage. The databases Environmental Mutagen 21 Information Center (EMIC), Developmental a nd Reproductive Toxicology (DART), and Toxic 22 Substances Control Act Test Submissions (TSCATS) are included in ToxFile. It is not clearly 23 stated whether the Chemical Carcinogenesis Re search Information System (CCRIS), Hazardous 24 Substances Data Bank (HSDB), or Genetic Toxicology Data Bank (GENE-TOX) are included in 25 ToxFile. Consequently, a separate, on-line search was conducted to ensure that these databases 26
were searched. 27 BIOSIS® Toxicology contains citations from BA and BA/R RM (formerly BioResearch 28 Index®), the major publications of BIOSIS®, that focus on toxicology and related topics. 29 Records are drawn from journa l articles, conference papers, monographs and book chapters, 30 notes, letters, and reports, as well as original re search. U.S. patent r ecords are also included. 31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-10 DRAFT

— DO NOT CITE OR QUOTE CANCERLIT® is produced by the Internati onal Cancer Research DataBank Branch 1 (ICRDB) of the U.S. National Cancer Institute. The database consists of bibliographic records 2 referencing cancer research publications dating from 1963 to 2002. Most records contain 3 abstracts, and all records contain citation inform ation and additional descriptive fields such as 4 document type and language. Beginning with the June 1983 CANCERLIT update, records from 5 the MEDLINE® database dealing with cancer topics have been added to CANCERLIT. 6 The Registry of Toxic Effects of Chemical Substances (RTECS®) is a comprehensive 7 database of basic toxicity information for over 150,000 chemical substances including 8 prescription and non-prescription drugs, food a dditives, pesticides, fungicides, herbicides, 9 solvents, diluents, chemical wastes, reaction produc ts of chemical waste, and substances used in 10 both industrial and household situations. Reports of the toxic effects of each compound are 11
cited. In addition to toxic eff ects and general toxicology review s, data on skin and/or eye 12 irritation, mutation, reproductive consequences and tumorigenicity are provided. Federal 13 standards and regulations, National Institute for Occupational Safety and Health (NIOSH) 14 recommended exposure limits and information on the activities of EPA, NIOSH, National 15 Toxicology Program (NTP), and Occupational Safety and Health Administration (OSHA) 16 regarding the substance are also included. The toxic effects are li nked to literature citations from 17 both published and unpublished governmental reports, and published articles from the scientific 18
literature. The database corres ponds to the print version of th e RTECS®, formerly known as the 19 Toxic Substances List, which was started in 197 1. Originally prepared by the NIOSH, the 20 RTECS® database is now produced and di stributed by Symyx Technologies, Inc. 21
22
C.2. TOXICOKINETIC MODELING CO DE (Emond et al., 2005) 23 C.2.1. Human Standard Model 24 C.2.1.1. Model Code 25
PROGRAM : 'Three Compartment PBPK Mode l for TCDD in Human: Standard Model 26 (Non-Gestation)' 27
28 !HUM_NON_GEST_ICF_F083109.csl 29 !***************************************************** 30 31 INITIAL !INITIALIZATION OF PARAMETERS 32

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-11 DRAFT

— DO NOT CITE OR QUOTE 1!SIMULATION PARAMETERS ==== 2 CONSTANT EXP_TIME_ON = 0. ! TIME AT WHICH EXPOSURE BEGINS 3 (HOUR) 4 CONSTANT EXP_TIME_OFF = 6.132e5 ! TIME AT WHICH EXPOSURE ENDS 5 (HOUR) 6 CONSTANT DAY_CYCLE = 24.0 ! NUMBER OF HOURS BETWEEN DOSES 7 (HOUR) 8 CONSTANT BCK_TIME_ON = 6.132e5 ! TIME AT WHICH BACKGROUND 9 EXPOSURE BEGINS (HOUR) 10 CONSTANT BCK_TIME_OFF = 6.132e5 ! TIME AT WHICH BACKGROUND 11 EXPOSURE ENDS (HOUR) 12 13!EXPOSURE DOSES 14 CONSTANT MSTOTBCKGR = 0.0 ! ORAL BACKGROUND EXPOSURE DOSE 15 (NG/KG) 16 CONSTANT MSTOT = 1.0E-7 ! ORAL EXPOSURE DOSE (NG/KG) 17 CONSTANT DOSEIV = 0.0 ! INJECTED DOSE (NG/KG) 18 CONSTANT MW = 322.0 ! MOLECULAR WEIGHT (G/MOL) 19 MSTOT_NM = MSTOT/MW ! CONVERTS THE DOSE TO NMOL/KG 20 MSTOT_NMBCKGR = MSTOTBCKGR/MW !CONVERTS THE BACKGROUND DOSE 21 TO NMOL/KG 22 DOSEIV_NM = DOSEIV/MW ! CONVERTS THE INJECTED DOSE TO 23 NMOL/KG 24 25!INITIAL GUESS OF THE FREE CONCENTRATION IN THE LIGAND 26 (COMPARTMENT INDICATED BELOW) ==== 27 CONSTANT CFLLI0 = 0.0 ! LIVER (NMOL/L) 28 29!BINDING CAPACITY (AhR) FO R NON LINEAR BINDING (COMPARTMENT 30 INDICATED BELOW) === 31 CONSTANT LIBMAX = 0.35 ! LIVER (NMOL/L) 32 33! PROTEIN AFFINITY CONSTANTS (1A2 OR AhR, COMPARTMENT INDICATED 34 BELOW) === 35 CONSTANT KDLI = 0.1 ! LIVER (AhR) (NMOL/L) WANG ET AL.. 1997 36 CONSTANT KDLI2 = 40.0 ! LIVER (1A2) (NMOL/L) EMOND ET AL. 2004 37 38!EXCRETION AND ABSORPTION CONSTANTS 39 CONSTANT KST = 0.01 ! GASTRIC RATE CONSTANT (HR-1), EMOND 40 ET AL., 2005 41 CONSTANT KABS = 0.06 ! INTESTINAL ABSORPTION CONSTANT (HR-1), 42 EMOND E T AL. 2005 43 44!ELIMINATION CONSTANTS 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-12 DRAFT

— DO NOT CITE OR QUOTE CONSTANT CLURI = 4.17D-8 ! URINARY CLEARANCE (L/HR), EMOND ET 1 AL., 2005 2 CONSTANT KELV = 1.1e-3 ! INTERSPECIES VARIABLE ELIMINATION 3 CONSTANT (1/HOUR) 4 5!CONSTANT TO DIVIDE THE AB SORPTION INTO LYMPHATIC AND PORTAL 6 FRACTIONS 7 CONSTANT A = 0.7 ! LYMPHATIC FRACTION, WANG ET AL. 8 (1997) 9 10 !PARTITION COEFFICIENTS 11 CONSTANT PF = 1.0e2 ! ADIPOSE TISSUE/BLOOD, WANG ET AL. 12 1997 13 CONSTANT PRE = 1.5 ! REST OF THE BODY/BLOOD, WANG ET AL. 14 1997 15 CONSTANT PLI = 6.0 ! LIVER/BLOOD, WANG ET AL. 1997 16 17!PARAMETERS FOR INDUCTION OF CYP1A2 18 CONSTANT PAS_INDUC = 1.0 ! INCLUDE INDUCTION? (1 = YES, 0 = NO) 19 CONSTANT CYP1A2_1OUTZ = 1.6e3 ! DEGRADATION CONCENTRATION 20 CONSTANT OF 1A2 (NMOL/L) 21 CONSTANT CYP1A2_1A1 = 1.6e 3 ! BASAL CONCENTRATION OF 1A1 22 (NMOL/L) 23 CONSTANT CYP1A2_1EC50 = 1.3e2 ! DISSOCIATION CONSTANT TCDD-CYP1A2 24 (NMOL/L) 25 CONSTANT CYP1A2_1A2 = 1.6e 3 ! BASAL CONCENTRATION OF 1A2 26 (NMOL/L) 27 CONSTANT CYP1A2_1KOUT = 0.1 ! FIRST ORDER RATE OF DEGRADATION 28 (H-1) 29 CONSTANT CYP1A2_1TAU = 0.25 ! HOLDING TIME (H) 30 CONSTANT CYP1A2_1EMAX = 9.3e3 ! MAXIMUM INDUCTION OVER BASAL 31 EFFECT (UNITLESS) 32 CONSTANT HILL = 0.6 !HILL CONSTANT; COOPERATIVELY LIGAND 33 BINDING EFFECT CONS TANT (UNITLESS) 34 ! DIFFUSIONAL PERMEABILITY FRACTION 35 CONSTANT PAFF = 0.12 ! ADIPOSE (UNITLESS) 36 CONSTANT PAREF = 0.03 ! REST OF BODY (UNITLESS) 37 CONSTANT PALIF = 0.35 ! LIVER (UNITLESS) 38 39!TISSUE BLOOD FLOW EXPRESSED AS A FRACTION OF CARDIAC OUTPUT 40

========= 41 CONSTANT QFF = 0.05 ! ADIPOSE TI SSUE BLOOD FLOW FRACTION 42 (UNITLESS), KRISHNAN 2008 43 CONSTANT QLIF = 0.26 ! LIVER (UNITLESS), KRISHNAN 2008 44 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-13 DRAFT

— DO NOT CITE OR QUOTE !COMPARTMENT TISSUE BLOOD EX PRESSED AS A FRACTION OF THE TOTAL 1 COMPARTMENT VOLUME ========= 2 CONSTANT WFB0 = 0.050 ! ADIPOSE TISSUE, WANG ET AL. 1997 3 CONSTANT WREB0 = 0.030 ! REST OF THE BODY, WANG ET AL. 1997 4 CONSTANT WLIB0 = 0.266 ! LIVER, WANG ET AL. 1997 5 6!EXPOSURE SCENARIO FOR UNIQUE OR REPETITIVE WEEKLY OR MONTHLY 7 EXPOSURE 8 !NUMBER OF EXPOSURES PER WEEK 9 CONSTANT WEEK_LACK = 0.0 ! DELAY BEFORE EXPOSURE ENDS 10 (WEEK) 11 CONSTANT WEEK_PERIOD = 168.0 ! NUMBER OF HOURS IN THE WEEK 12 (HOURS) 13 CONSTANT WEEK_FINISH = 168.0 ! TIME EXPOSURE ENDS (HOURS) 14 !NUMBER OF EXPOSURES PER MONTH 15 CONSTANT MONTH_LACK = 0.0 ! DELAY BEFORE EXPOSURE BEGINS 16 (MONTH) 17 18!SET FOR BACKGROUND EXPOSURE=========== 19 !TIME CONSTANT FO R BACKGROUND EXPOSURE=========== 20 CONSTANT Day_LACK_BG = 0.0 ! DELAY BEFORE EXPOSURE BEGINS 21 (HOUR) 22 CONSTANT Day_PERIOD_BG = 24.0 ! LENGTH OF EXPOSURE (HOUR) 23 24!TIME CONSTANT FOR WEEKLY EXPOSURE 25 CONSTANT WEEK_LACK_BG = 0.0 ! DELAY BEFORE BACKGROUND 26 EXPOSURE BEGINS (WEEK) 27 CONSTANT WEEK_PERIOD_BG = 168.0 ! NUMBER OF HOURS IN THE WEEK 28 (HOURS) 29 CONSTANT WEEK_FINISH_BG = 168.0 ! TIME EXPOSURE ENDS (HOURS) 30 31! CONSTANT USED IN CARDIAC OUTPUT EQUATION 32 CONSTANT QCC = 15.36 ! (L/KG-H), EMOND ET AL. 2004 33 34! COMPARTMENT LIPID EXPRESSE D AS THE FRACTION OF TOTAL LIPID 35 !Data from Emonds Thesis 2001 36 CONSTANT F_TOTLIP = 0.8000 ! ADIPOSE TISSUE (UNITLESS) 37 CONSTANT B_TOTLIP = 0.0057 ! BLOOD (UNITLESS) 38 CONSTANT RE_TOTLIP = 0.0190 ! REST OF THE BODY (UNITLESS) 39 CONSTANT LI_TOTLIP = 0.0670 ! LIVER (UNITLESS) 40 CONSTANT MEANLIPID = 974.0 41 42 END ! END OF THE INITIAL SECTION 43 44 45 DYNAMIC ! DYNAMIC SI MULATION SECTION 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-14 DRAFT

— DO NOT CITE OR QUOTE ! 1 ALGORITHM IALG = 2 ! GEAR METHOD 2 CINTERVAL CINT = 10.0 ! COMMUNICATION INTERVAL 3 MAXTERVAL MAXT = 1.0e+10 !MAXIMUM INTERVAL CALCULATION 4 MINTERVAL MINT = 1.0E -10 !MINIMUM INTERVAL CALCULATION 5 VARIABLE T = 0.0 6 CONSTANT TIMELIMIT = 1.752e5 !SIMULATION LIMIT TIME (HOUR) 7 CONSTANT Y0 = 0.0 ! AGE (YEARS) AT BEGINNING OF SIMULATION 8 CONSTANT GROWON = 1.0 ! INCLUDE BODY WEIGHT AND HEIGHT 9 GROWTH? (1 = YES, 0 = NO) 10 CINTXY = CINT 11 PFUNC = CINT 12 13DAY=T/24.0 ! TIME IN DAYS 14 WEEK =T/168.0 ! TIME IN WEEKS 15 MONTH =T/730.0 ! TIME IN MONTHS 16 YEAR=Y0+T/8760.0 ! TIME IN YEARS 17 GYR =Y0 + growon*T/8760.0 ! TI ME FOR USE IN GROWTH EQUATION (YEARS) 18 19 DERIVATIVE ! PORTION OF CODE THAT SOLVES DIFFERENTIAL EQUATIONS 20 21! CHRONIC OR SUBCHR ONIC EXPOSURE SCENARIO ======= 22 ! NUMBER OF EXPOSURES PER DAY 23 DAY_LACK = EXP_TIME_ON ! DELAY BEFORE EXPOSURE BEGINS (HOURS) 24 DAY_PERIOD = DAY_CYCLE ! EXPOSURE PERIOD (HOURS) 25 DAY_FINISH = CINTXY ! LENGTH OF EXPOSURE (HOURS) 26 MONTH_PERIOD = TIMELIMIT ! EXPOSURE PERIOD (MONTHS) 27 MONTH_FINISH = EXP_TIME_OFF ! LENGTH OF EXPOSURE (MONTHS) 28 29 30! NUMBER OF EXPOSURES PER DAY AND MONTH 31 DAY_FINISH_BG = CINTXY 32 MONTH_LACK_BG = BCK_TIME_ON !DELAY BEFORE BACKGROUD EXPOSURE 33 BEGINS (MONTHS) 34 MONTH_PERIOD_BG = TIMELIMIT ! BACKGROUND EXPOSURE PERIOD 35 (MONTHS) 36 MONTH_FINISH_BG = BCK_TIME_OFF ! LENGTH OF BACKGROUND EXPOSURE 37 (MONTHS) 38 39B = 1.0-A ! FRACTION OF DIOXIN ABSORB ED IN THE PORTAL FRACTION OF THE 40 LIVER 41 42!HUMAN BODY WEI GHT GROW TH EQUATION======== 43 ! POLYNOMIAL REGR ESSION EXPRESSION WRITTEN 44 !APRIL 10 2008, OPTIMIZED WITH DATA OF PELEKIS ET AL. 2001 45 ! POLYNOMIAL REGRESSION EX PRESSION WRITTEN WITH 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-15 DRAFT

— DO NOT CITE OR QUOTE !HUH AND BOLCH 2003 FOR BMI CALCULATION 1 2! BODY WEIGHT CALCULATION 3 WT0 = (0.0006*GYR**3 - 0.0912*GYR**2 + 4.32*GYR + 3.652) 4 5! BODY MASS INDEX CALCULATION 6 BH = -2D-5*GYR**4+4.2D-3* GYR**3.0-0.315*GYR**2.0+9.7465*GYR+72.098 7 !HEIGHT EQUATION FORMULA TED FOR USE FROM 0 TO 70 YEARS 8 BHM= (BH/100.0) !HUMAN HEIGHT IN METERS (BHM) 9 HBMI= WT0/(BHM**2.0) ! HUMAN BODY MASS INDEX (BMI) 10 11! ADIPOSE TISSUE FRACTION 12 WT0GR= WT0*1.0e3 ! BODY WEIGHT IN GRAMS 13 WF0= -6.36D-20*WT0GR**4.0 +1.12D- 14*WT0GR**3.0 -5.8D-10* WT0GR**2.0 +1.2D14 5*WT0GR+5.91D-2 15 16! LIVER,VOLUME, 17 ! APPROACH BASED ON LUECKE (2007) 18 WLI0= (3.59D-2 -(4.76D-7*WT0GR )+(8.50D-12*WT0GR**2.0)-(5.45D-17*WT0GR**3.0)) 19 20WRE0 = (0.91 -(WLIB0*WLI0+WFB0 *WF0+WLI0+WF0))/(1.0+WREB0) 21 !REST OF THE BODY FRACTION; UPDATED FOR EPA 22 ASSESSMENT 23 QREF = 1.0-(QFF+QLIF) !REST OF BODY BLOOD FLOW 24 QTTQF = QFF+QREF+QLIF ! SUM MUST EQUAL 1 25 26!COMPARTMENT VO LUME (L OR KG) ========= 27 WF = WF0 * WT0 ! ADIPOSE 28 WRE = WRE0 * WT0 ! REST OF THE BODY 29 WLI = WLI0 * WT0 ! LIVER 30 WB=0.075*WT0 ! BLOOD 31 32!COMPARTMENT TISSUE BLOOD (L OR KG) ========= 33 WFB = WFB0 * WF ! ADIPOSE 34 WREB = WREB0 * WRE ! REST OF THE BODY 35 WLIB = WLIB0 * WLI ! LIVER 36 !CARDIAC OUTPUT FOR THE GIVEN BODY WEIGHT 37 QC= QCC*(WT0**0.75) ! [L BLOOD/HOUR] 38 39 QF = QFF*QC ! ADIPOSE TISSUE BLOOD FLOW RATE [L/HR] 40 QLI = QLIF*QC ! LIVER TISSUE BLOOD FLOW RATE [L/HR] 41 QRE = QREF*QC !REST OF THE BODY BLOOD FLOW RATE [L/HR] 42 43 QTTQ = QF+QRE+QLI ! TOTAL FLOW RATE [L/HR] 44 45!PERMEABILITY ORGAN FLOW [L/HR]======= 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-16 DRAFT

— DO NOT CITE OR QUOTE PAF = PAFF*QF ! ADIPOSE 1 PARE = PAREF*QRE ! REST OF THE BODY 2 PALI = PALIF*QLI ! LIVER TISSUE 3 4! ABSORPTION SECTION 5 ! INTRAVENOUS 6 IV = DOSEIV_NM * WT 0 !AMOUNT IN NMOL 7 MSTTBCKGR = MSTOT_NMBCKGR *WT0 !AMOUNT IN (NMOL) 8 MSTT = MSTOT_NM * WT0 !AMOUNT IN NMOL 9 10!REPETITIVE ORAL BACKGROUND EXPOSURE SCENARIOS 11 DAY_EXPOSURE_BG = PULSE(DAY_LACK _BG,DAY_PERIOD_BG,DAY_FINISH_BG) 12 WEEK_EXPOSURE_BG = 13 PULSE(WEEK_LACK_BG,WEEK_PERIOD_BG,WEEK_FINISH_BG) 14 MONTH_EXPOSURE_BG = 15 PULSE(MONTH_LACK_BG,MONTH_PERIOD_BG,MONTH_FINISH_BG) 16 17 MSTTCH_BG = 18 (DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG)*MSTTBCK 19 GR 20 MSTTFR_BG = MSTTBCKGR/CINT 21 22 CYCLE_BG =DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG 23 24 25! CONDITIONAL ORAL EXPOSURE (BACKGROUND EXPOSURE) 26 IF (MSTTCH_BG.EQ.MSTTBCKGR) THEN 27 ABSMSTT_GB= MSTTFR_BG 28 ELSE 29 ABSMSTT_GB = 0.0 30 END IF 31 32 33!REPETITIVE ORAL MAIN EXPOSURE SCENARIO 34 DAY_EXPOSURE = PULSE(DAY_LACK,DAY_PERIOD,DAY_FINISH) 35 WEEK_EXPOSURE = PULSE(WEEK_LACK,WEEK_PERIOD,WEEK_FINISH) 36 MONTH_EXPOSURE = PULSE(MONTH_LA CK,MONTH_PERIOD,MONTH_FINISH) 37 38 MSTTCH = (DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE)*MSTT 39 CYCLE = DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE 40 MSTTFR=MSTT/CINT 41 42!CONDITIONAL ORAL EXPOSURE 43 IF (MSTTCH.EQ.MSTT) THEN 44 ABSMSTT= MSTTFR 45 ELSE 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-17 DRAFT

— DO NOT CITE OR QUOTE ABSMSTT = 0. 1 END IF 2 3CYCLETOT=INTEG(CYCLE,0.0) 4 5! MASS Balance CHANGE IN THE LUMEN 6 RMSTT= -(KST+KABS)*MST+ABSMSTT +A BSMSTT_GB ! RATE OF CHANGE 7 (NMOL/H) 8 MST = INTEG(RMSTT,0.) !AMOUNT REMAINING IN GI TRACT (NMOL) 9 10! ABSORPTION IN LYMPH CIRCULATION 11 LYRMLUM = KABS*MST*A 12 LYMLUM = INTEG(LYRMLUM,0.0) 13 14! ABSORPTION IN PORTAL CIRCULATION 15 LIRMLUM = KABS*MST*B 16 LIMLUM = INTEG(LIRMLUM,0.0) 17 18! PERCENT OF DOSE REMAINING IN THE GI TRACT 19 PRCT_remain_GIT = 100.0*MST/(MSTT+1E-30) 20 21!IV ABSORTPI ON SCENARIO --------- 22 IVR= IV/PFUNC ! RATE FO R IV INFUSION IN BLOOD 23 EXPIV= IVR * (1.0-STEP(PFUNC)) 24 IVDOSE = integ(EXPIV,0.0) 25 26!SYSTEMIC BLOOD COMPARTMENT 27 ! MODIFICATION OCT 8 2009 28 CB=(QF*CFB+QRE*CREB+QLI*CLIB+ EXPIV+LYRMLUM)/(QC+CLURI) ! 29 CA = CB !CONCENTRATION (NMOL/L) 30 31!CB=(QF*CFB+QRE*CREB+QLI* CLIB+EXPIV+LYRMLUM-RAURI)/QC ! 32 ! CA = CB ! CONCENTRATION (NMOL/L) 33 34!URINARY EXCRETION BY KIDNEY 35 ! MODIFICATION OCT 8 2009 36 RAURI = CLURI *CB 37 AURI = INTEG(RAURI,0.0) 38 39 40 !CONCENTRATION UNIT 41 PRCT_B = 100.0*CB/(MSTT+1E-30) ! PERCENT OF DOSE 42 CBSNGKGLIADJ = CB*MW/(0.55*B _TOTLIP) !serum concentrat ion in lipid adjust (PG/G 43 LIPID=PPT) 44 CBPPT = CBSNGKGLIADJ 45 CBNGKG = CB*M W 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-18 DRAFT

— DO NOT CITE OR QUOTE 1 CBpptRH = CB*MW*10000/(0.55*MEANLIPID) !SERUM CONCENTRATION IN LIPID 2 ADJUST (PG/G LIPID=PPT) 3 4AUC_CBSNGKGLIADJ=INTEG(CBSNGKGLIADJ,0.0) 5 6!ADIPOSE TISSUE COMPARTMENT 7 RAFB= QF*(CA-CFB)-PAF*(CFB-CF/ PF) !(NMOL/HR) 8 AFB = INTEG(RAFB,0.0) !(NMOL) 9 CFB = AFB/WFB !(NMOL/KG) 10 !TISSUE SUBCOMPARTMENT 11 RAF = PAF*(CFB-CF/PF) !(NMOL/HR) 12 AF = INTEG(RAF,0.0) !(NMOL) 13 CF = AF/WF !(NMOL/KG) 14 15!POST SIMULATION UNIT CONVERSION 16 CFTOTAL = (AF + AFB)/(WF + WFB) ! TOTAL CONCENTRATION NMOL/ML 17 PRCT_F = 100.0*CFTOTAL/(MSTT+1E-30) 18 CFNGKG =CFTOTAL*MW 19 20!REST OF TH E BODY COMPARTMENT======== 21 RAREB= QRE*(CA-CREB)-PARE* (CREB-CRE/PRE) !(NMOL/HR) 22 AREB = INTEG(RAREB,0.0) !(NMOL) 23 CREB = AREB/WREB !(NMOL/KG) 24 !TISSUE SUBCOMPARTMENT 25 RARE = PARE*(CREB-CRE/PRE) !(NMOL/HR) 26 ARE = INTEG(RARE,0.0) !(NMOL) 27 CRE = ARE/WRE !(NMOL/KG) 28 29!POST SIMULATION UNIT CONVERSION 30 CRETOTAL = (ARE + AREB)/(WRE + WREB ) ! TOTAL CONCENTRATION IN NMOL/ML 31 PRCT_RE = 100.0*CRETOTAL/(MSTT+1E-30) ! PERCENT OF DOSE 32 33!LIVER COMPARTMENT 34 !TISSUE BLOOD SUBCOMPARTMENT 35 RALIB = QLI*(CA-CLIB)-PALI*(CLIB-CFLLIR)+L IRMLUM !(NMOL/HR) 36 ALIB = INTEG(RALIB,0.0) !(NMOL) 37 CLIB = ALIB/WLIB 38 !TISSUE SUBCOMPARTMENT 39 RALI = PALI*(CLIB-CFLLIR)-REXCLI !(NMOL/HR) 40 ALI = INTEG(RALI,0.0) !(NMOL) 41 CLI = ALI/WLI !(NMOL/KG) 42 43 44!FREE TCDD IN LIVER 45 ! MODIFICATION OCTOBER 8 2009 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-19 DRAFT

— DO NOT CITE OR QUOTE CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR)) & 1 +((CYP1A2_1O3*CFLLIR/(KDL I2+CFLLIR)*PAS_INDUC)))-CFLLI,CFLLI0) ! 2 CONCENTRATION OF FREE TCDD IN LIVER 3 CFLLIR=DIM(CFLLI,0.0) 4 5 !MODIFIED FROM: 6 !PARAMETER (LIVER_1RMN = 1.0E-30) 7 ! CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR & ! 8 +LIVER_1RMN))+((CYP1A2_1O3*C FLLIR/(KDLI2+CFLLIR & 9 ! +LIVER_1RMN)*PAS_INDUC)))-CFLLI,CFLLI0) 10 ! CFLLIR=DIM(CFLLI,0.0) 11 12 13 CBNDLI= LIBMAX*CFLLIR/(KDLI+CFLLIR) !CONC OF TCDD BOUDN TO AhR 14 15 !CBNDLI= LIBMAX*CFLLIR/(KDLI+CF LLIR+LIVER_1RMN) !CONC BIND 16 17!POST SIMULATION UNIT CONVERSION 18 CLITOTAL = (ALI + ALIB)/(WLI + WLIB) ! TOTAL CONCENTRATION IN NMOL/ML 19 PRCT_LI = 100.0*CLITOTAL/(MSTT+1.0E-30) 20 rec_occ_AHR= 100.0*CFLLIR/(KDLI+CFLLIR+ 1.0) ! PERCENT BOUND TO AhR 21 OCCUPANCY 22 PROT_occ_1A2= 100.0*CFLLIR/(KDLI2+CFLLIR) ! PERCENT BOUND TO 1A2 23 OCCUPANCY 24 CLINGKG= CLITOTAL*MW ![NG TCDD/KG] 25 CBNDLINGKG = CBNDLI*MW 26 27!FRACTION INCREASE OF INDUCTION OF CYP1A2 28 fold_ind=CYP1A2_1OUT/CYP1A2_1A2 29 VARIATIONOFAC =(CYP1A2_1 OUT-CYP1A2_1A2)/CYP1A2_1A2 30 31!VARIABLE ELIMINATI ON BASED ON THE CYP1A2 32 KBILE_LI_T = Kelv*VARIATIONOFAC! 33 34REXCLI = KBILE_LI_T*CFLLIR*WLI ! DOSE-DEPENDENT RATE OF BILLIARY 35 EXCRETION OF DIOXIN 36 EXCLI = INTEG(REXCLI,0.0) !TOTAL AMOUNT OF DIOXIN EXCRETED 37 38!CHEMICAL IN CYP450 (1A2) COMPARTMENT 39 !PARAMETER FOR INDUCTION OF CYP1A2 40 41 CYP1A2_1KINP = CYP1A2_1KOUT*CYP1 A2_1OUTZ ! BASAL RATE OF CYP1A2 42 PRODUCTION SET EQUAL TO BASAL RATE OF DE GRDATION AT STEADY STATE 43 44! MODIFICATION OCTOBER 8 2009 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-20 DRAFT

— DO NOT CITE OR QUOTE CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1.0 + CYP1A2_1EMAX *(CBNDLI+1.0e1 30)**HILL & 2 /(CYP1A2_1EC50**HILL + (CBNDLI+1.0e-30)**HILL)) & 3 - CYP1A2_1KOUT*CYP1A2_1OUT, CYP1A2_1OUTZ) ! LEVELS OF CYP1A2 4 ! MODEIFIED FROM: 5 !PARAMETER (CYP1A2_1RMN = 1e-30) 6 !CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1 + CYP1A2_1EMAX *(CBNDLI & 7 ! +CYP1A2_1RMN)**HILL/(CYP1A2_1EC 50 + (CBNDLI + CYP1A2_1RMN)**HILL) & 8 ! +CYP1A2_1RMN) - CYP1A2_1KOUT*CYP1A2_1& 9 ! OUT, CYP1A2_1OUTZ) 10 11 ! EQUATIONS INCORPORATING DELAY OF CYP1A2 PRODUCTION (NOT USED IN 12 SIMULATIONS) 13 CYP1A2_1RO2 = (CYP1A2_1OUT - CYP1A2_1O2)/ CYP1A2_1TAU 14 CYP1A2_1O2 =INTEG(CYP1A2_1RO2, CYP1A2_1A1) 15 CYP1A2_1RO3 = (CYP1A2_1O2 - CYP1A2_1O3)/ CYP1A2_1TAU 16 CYP1A2_1O3 =INTEG(CYP1A2_1RO3, CYP1A2_1A2) 17 18!CHECK MASS BALANCE 19 BDOSE= LYMLUM+LIMLUM+IVDOSE 20 BMASSE = EXCLI+AURI+AFB+AF+AREB+ARE+ALIB+ALI 21 BDIFF = BDOSE-BMASSE 22 ! BODY BURDEN IN TER MS OF CONCENTRATION (NG/KG) 23 BBNGKG = (AFB+AF+AREB+ARE+ALIB+ALI)*MW/WT0 ! 24 25!COMMAND END OF THE SIMULATION 26 TERMT (T.GE. TIMELIMIT, 'Time limit has been reached.') 27 28 END ! END OF THE DERIVATIVE SECTION 29 END ! END OF THE DYTNAMIC SECTION 30 END ! END OF THE PROGRAM 31 32
C.2.1.2. Input File 33 % base file nam e = "TESTJULY2009.m" 34 %clear @variable 35 output @clear 36 prepare @clear year T CLINGKG CFNG KG CBSNGKGLIADJ BBN GKG CBNDLINGKG 37 CBNGKG 38 %output @all 39 % PARAMETERS FOR SIMULATION 40 CINT = 1 %0.5 41 EXP_TIME_ON = 0. % TIME AT WHICH EXPOSURE BEGINS (HOUR) 42 EXP_TIME_OFF = 613200 %324120 % HOUR/YEAR !TIME AT WHICH EXPOSURE 43 ENDS (HOUR) 44 DAY_CYCLE = 24 % NUM BER OF HOURS BETWEE N DOSES (HOUR) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-21 DRAFT

— DO NOT CITE OR QUOTE BCK_TIME_ON = 613200 %324120 % TIME AT WHICH BACKGROUND 1 EXPOSURE BEGINS (HOUR) 2 BCK_TIME_OFF = 613200 %324120 % TIME AT WHICH BACKGROUND 3 EXPOSURE ENDS (HOUR) 4 TIMELIMIT = 613200 %324120 %324120 % SIMULATION TIME LIMIT (HOUR) 5 MSTOTBCKGR = 0. % ORAL BACKGROUND EXPOSURE DOSE (UG/KG) 6 7 % oral dose oral dose oral dose 8 MSTOT = 9.97339283634997E-07 % ORAL DAILY EXPOSURE DOSE (NG/KG) 9 DOSEIV = 0 %NG/KG 10 % oral dose oral dose oral dose 11 12 MEANLIPID = 730 % 13 PAS_INDUC= 1 % I NDUCTION INCLUDED? (1=YES, 0=NO) 14 15
C.2.2. Human Gestational Model 16 C.2.2.1. Model Code 17
PROGRAM : 'Three Compartment PBPK Mode l for TCDD in Human (Gestation)' 18 ! Parameters were change may 16, 2002 19 ! Come from {8MAI_CHR_PRE-EXP_GD} 20 ! Come from {12_Mouse_GD}file 21 !******************************************** 22 !{{IMPORTANT-IMPORTANT-IMPORTANT-IMPORTANT}} 23 ! REDUCTION OF MOTHER AND FETUS COMPARTMENT 24 ! 2M_R_TCDD_JULY2002 ////(JULY 18,2002)//// 25 !TCDD_RED_4Species_2003_4 ////(APR 8 ,2003)//// 26 !TCDD_RED_4Species_2003_9 ////(APR 17 ,2003)//// 27 !TCDD_RED_4Species_2003_12 ////(APR 17 ,2003)//// 28 !***************************************************** 29 !APRIL 18 2003 30 !TCDD_4C_4SP_2003 ////(APR 18 ,2003)//// 31 ! was ''Gest 4 species 1.csl'' but update July 2009 32 33 !GEST_HUM_0_45Y_4_ICF_afterKKf ix_v3_humangestational.csl 34 !HUM_GESTATIONAL _ICF_F083109.csl 35 !HUM_GESTATION AL_ICF_F100709.csl 36 !***************************************************** 37 38!Legend/Legend/Legend/Legend/ Legend/Legend/Legend/Legend/ 39 !Legend for this PBPK model 40 !Mating: control the tenure of exchange between fetus and 41 !Mother and also cont rol imitated tissue growth 42 !Control: WTFE, WPLA0, QPLAF 43 !(for rat, mouse, human, and monkey) 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-22 DRAFT

— DO NOT CITE OR QUOTE !Control transfer from mother to fetus and fetus to mother by TRANSTIME_ON 1 !SWITCH_trans = 0 NO TRANSFER 2 !SWITCH_trans = 1 TRANSFER OCCURS 3 ! These switches are also controlled by mating parameters 4 5 INITIAL ! 6 7!SIMULATION PARAMETERS 8 CONSTANT PARA_ZERO = 1e-30 9 CONSTANT EXP_TIME_ON = 0.0 !TIME AT WHICH EXPOSURE BEGINS 10 (HOURS) 11 CONSTANT EXP_TIME_OFF = 530.0 !TIME AT WHICH EXPOSURE ENDS (HOURS) 12 CONSTANT DAY_CYCLE = 24.0 !NUMBER OF HOURS BETWEEN DOSES 13 (HOURS) 14 CONSTANT BCK_TIME_ON = 0.0 !TIME AT WHICH BA CKGROUND EXPOSURE 15 BEGINS (HOURS) 16 CONSTANT BCK_TIME_OFF = 0.0 !TIME AT WHICH BA CKGROUND EXPOSURE 17 ENDS (HOURS) 18 CONSTANT TRANSTIME_ON = 0.0 !CONTROL TRANSFER FROM MOTHER TO 19 FETUS AT 9 WEEKS OR 1512 HOURS OF GESTATION 20 21! INTRAVENOUS SEQUENCY 22 CONSTANT IV_LACK = 0.0 23 CONSTANT IV_PERIOD = 0.0 24 25!PREGNANCY PARAMETER 26 CONSTANT MATTING = 0.0 !BEGINNING OF MATING (HOUR) 27 CONSTANT PFETUS = 4.0 !PARTITION COEFFICIENT 28 CONSTANT CLPLA_FET = 1.0e-3 !CLEARANCE TRANSFER FOR MOTHER TO 29 FETUS (L/HR) 30 31!CONSTANT EXPOSURE CONTROL 32 !ACUTE, SUBCHRONIC, CHRONIC EXPOSURE ===== 33 !OR BACKGROUND EXPOSURE (IN THIS CASE 3 TIMES A DAY)=== 34 CONSTANT MSTOTBCKGR = 0.0 ! ORAL BACKGROUND EXPOSURE DOSE 35 (NG/KG) 36 CONSTANT MSTOT = 0.0 ! ORAL EXPOSURE DOSE (NG/KG) 37 38!ORAL ABSORPTION 39 ! MSTT= MSTOT/1000 *WT0 *1/322*1000 !AMOUNT IN NMOL 40 MSTOT_NM = MSTOT/MW !CONVERTS THE DOSE TO NMOL/KG 41 42!INTRAVEN OUS ABSORPTION 43 CONSTANT DOSEIV = 0.0 ! INJECTED DOSE (NG/KG) 44 DOSEIV_NM = DOSEIV/MW ! CONVERTS THE INJECTED DOSE TO NMOL/KG 45 CONSTANT DOSEIVLATE = 0.0 !INJECTED DOSE LATE (UG/KG) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-23 DRAFT

— DO NOT CITE OR QUOTE DOSEIVNMlate = DOSEIVLATE/MW !AMOUNT IN NMOL/G 1 2!INITIAL GUESS OF THE FREE CONCENTRATION IN THE LIGAND 3 (COMPARTMENT INDICATED BELOW)==== 4 CONSTANT CFLLI0 = 0.0 !LIVER (NMOL/L) 5 CONSTANT CFLPLA0 = 0.0 !PLACENTA (NMOL/L) 6 7!BINDING CAPACITY (AhR) FO R NON LINEAR BINDING (COMPARTMENT 8 INDICATED BELOW) (NMOL/L) === 9 CONSTANT LIBMAX = 0.35 ! LIVER (NMOL/L) 10 CONSTANT PLABMAX = 0.2 !TEMPORARY PARAMETER 11 12!PROTEIN AFFINITY CONSTANTS (1A2 OR AhR, COMPARTMENT INDICATED 13 BELOW) (NMOL/ML)=== 14 CONSTANT KDLI = 0.1 !LIVER (AhR) (NMO L/L), WANG ET AL. 1997 15 CONSTANT KDLI2 = 40.0 !LIVER (1A2) (NMOL/L), EMOND ET AL. 2004 16 CONSTANT KDPLA = 0.1 !ASSUME IDENTICAL TO KDLI (AhR) 17 18!EXCRETION AND ABSORPTION CONSTANT 19 CONSTANT KST = 0.01 ! GASTRIC RATE CONST ANT (HR-1), EMOND ET AL. 20 2005 21 CONSTANT KABS = 0.06 ! INTESTINAL ABSORP TION CONSTANT (HR-1), 22 EMOND ET AL. (2005) 23 24!INTERSPECIES ELIMINATION CONSTANT 25 !TEST ELIMINATION VARIABLE, EMOND ET AL. 2005 26 CONSTANT KELV = 1.1e-3 !4.0D-3 ! INTERSPECIES VARIABLE 27 ELIMINATION CONSTANT (1/HOUR) 28 29! ELIMINATION CONSTANTS 30 CONSTANT CLURI = 4.17e-8 ! URINARY CLEARANCE (L/HR), EMOND ET AL. 31 2005 32 33! CONSTANT TO DIVIDE THE ABSORPTION INTO LYMPHATIC AND PORTAL 34 FRACTIONS 35 CONSTANT A = 0.7 ! LYMPHATIC FRACTION, WANG ET AL. 1997 36 37!PARTITION COEFFICIENTS 38 CONSTANT PF = 1.0e2 ! ADIPOSE TISSUE/BLOOD, WANG ET AL. 1997 39 CONSTANT PRE = 1.5 ! REST OF THE BODY/BLOOD, WANG ET AL. 1997 40 CONSTANT PLI = 6.0 ! LIVER/BL OOD, WANG ET AL. 1997 41 CONSTANT PPLA = 1.5 ! TEMPORARY PARAMETER NOT CONFIGURED, 42 WANG ET AL. 1997 43 44!PARAMETER FOR INDUCTION OF CYP 1A2, WANG ET AL. 1997 45 CONSTANT PAS_INDUC = 1.0 ! INCLUDE INDUCTION? (1 = YES, 0 = NO) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-24 DRAFT

— DO NOT CITE OR QUOTE CONSTANT CYP1A2_1OUTZ = 1.6e3 ! DEGRADATION CONCENTRATION 1 CONSTANT OF 1A2 (NMOL/L) 2 CONSTANT CYP1A2_1A1 = 1.6e3 ! BASAL CONCENTRATION OF 1A1 (NMOL/L) 3 CONSTANT CYP1A2_1EC50 = 1.3e2 ! DISSOCIATION CONSTANT TCDD-CYP1A2 4 (NMOL/L) 5 CONSTANT CYP1A2_1A2 = 1.6e3 !BASAL CONCENTRATION OF 1A2 (NMOL/ML) 6 CONSTANT CYP1A2_1KOUT = 0.1 ! FIRST ORDER RATE OF DEGRADATION (H-1) 7 CONSTANT CYP1A2_1TAU = 0.25 !HOLDING TIME (H) 8 CONSTANT CYP1A2_1EMAX = 9.3e3 ! MAXIMUM INDUCTION OVER BASAL 9 EFFECT (UNITLESS) 10 CONSTANT HILL = 0.6 !HILL CONSTANT; COOPERATIVELY LIGAND 11 BINDING EFFECT CONS TANT (UNITLESS) 12 13!DIFFUSIONAL PERMEABILITY FRACTION, WANG ET AL (1997) 14 CONSTANT PAFF = 0.12 ! ADIPOSE (UNITLESS) 15 CONSTANT PAREF = 0.03 ! REST OF THE BODY (UNITLESS) 16 CONSTANT PALIF = 0.35 ! LIVER (UNITLESS) 17 CONSTANT PAPLAF = 0.3 ! OPTIMIZED PARAMETER 18 19 !TISSUE BLOOD FLOW EXPRESSED AS A FRACTION OF CARDIAC OUTPUT, 20 KRISHNAN 2007 21 CONSTANT QFF = 0.05 ! ADIPOSE TISSUE BLOOD FLOW FRACTION 22 (UNITLESS), KRISHNAN 2008 23 CONSTANT QLIF = 0.26 ! LIVER (UNITLESS), KRISHNAN 2008 24 25 !===FRACTION OF TISSUE BLOOD WEIGHT Wang et al . (1997) 26 CONSTANT WFB0 = 0.050 !ADIPOSE TISSUE, WANG ET AL. 1997 27 CONSTANT WREB0 = 0.030 !REST OF THE BODY, WANG ET AL. 1997 28 CONSTANT WLIB0 = 0.266 !LIVER, WANG ET AL. 1997 29 CONSTANT WPLAB0 = 0.500 !ASSUME HIGHLY VASCULARIZED 30 31 ! EXPOSURE SCENARIO FOR UNIQUE OR REPETITIVE WEEKLY OR MONTHLY 32 EXPOSURE 33 ! NUMBER OF EXPOSURES PER WEEK 34 CONSTANT WEEK_LACK = 0.0 !DELAY BEFORE EXPO SURE ENDS (WEEK) 35 CONSTANT WEEK_PERIOD = 168.0 ! NUMBER OF H OURS IN THE WEEK 36 (HOUR S) 37 CONSTANT WEEK_FINISH = 168.0 ! TIME EXPOSURE ENDS (HOURS) 38 39 ! NUMBER OF EXPOSURES PER MONTH 40 CONSTANT MONTH_LACK = 0.0 !DELAY BEFORE EXPOSURE BEGINS 41 (MONTHS) 42 43 !======= CONSTANT FOR BA CKGROUND EXPOSURE=========== 44 CONSTANT Day_LACK_BG = 0.0 ! DELAY BEFORE EXPOSURE BEGINS 45 (HOURS) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-25 DRAFT

— DO NOT CITE OR QUOTE CONSTANT Day_PERIOD_BG = 24.0 !LENGTH OF EXPOSURE (HOURS) 1 2 ! NUMBER OF EXPOSURES PER WEEK 3 CONSTANT WEEK_LACK_BG = 0.0 !DELAY BE FORE BACKGROUD EXPOSURE 4 BEGINS (WEEK) 5 CONSTANT WEEK_PERIOD_BG = 168.0 ! NUMBER OF HOURS IN THE WEEK 6 (HOURS) 7 CONSTANT WEEK_FINISH_BG = 168.0 !TIME EXPOSURE ENDS (HOURS) 8 9 10 ! CONSTANT USED IN CARDIAC OUTPUT EQUATION 11 CONSTANT QCC = 15.36 ![L/KG-H], EMOND ET AL. 2004 12 13 ! COMPARTMENT LIPID EXPRESSED AS THE FRACTION OF TOTAL LIPID 14 !Data from Emonds Thesis 2001 15 CONSTANT F_TOTLIP = 0.8000 ! ADIPOSE TISSUE (UNITLESS) 16 CONSTANT B_TOTLIP = 0.0057 ! BLOOD (UNITLESS) 17 CONSTANT RE_TOTLIP = 0.0190 ! REST OF THE BODY (UNITLESS) 18 CONSTANT LI_TOTLIP = 0.0670 ! LIVER (UNITLESS) 19 CONSTANT PLA_TOTLIP = 0.019 ! PLACENTA (UNITLESS) 20 CONSTANT FETUS_TOTLIP = 0.019 ! FETUS (UNITLESS) 21 22 CONSTANT MEANLIPID = 974 23 24 END ! END OF THE INITIAL SECTION 25 26 DYNAMIC ! DYNAMIC SI MULATION SECTION 27 28 ALGORITHM IALG = 2 ! GEAR METHOD 29 CINTERVAL CINT = 0.1 ! COMMUNICATION INTERVAL 30 MAXTERVAL MAXT = 1.0e+10 ! MAXIMUM CALCULATION INTERVAL 31 MINTERVAL MINT = 1.0E-10 ! MINIMUM CALCULATION INTERVAL 32 VARIABLE T = 0.0 33 CONSTANT TIMELIMIT = 100 !SIMULATION LIMIT TIME (HOUR) 34 CONSTANT Y0 = 0.0 ! AGE (YEARS) AT BEGINNING OF 35 SIMULATION 36 CONSTANT GROWON = 1.0 ! INCLUDE BO DY WEIGHT AND HEIGHT 37 GROWTH? (1=YES, 0=NO) 38 39CINTXY = CINT 40 PFUNC = CINT 41 42!TIME TRANSF ORMATION 43 DAY= T/24.0 44 WEEK =T/168.0 45 YEAR=Y0+T/8760.0 ! TIME IN YEARS 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-26 DRAFT

— DO NOT CITE OR QUOTE GYR =Y0 + growon*T/8760.0 ! TIME FOR USE IN GROWTH EQUATION 1 2 DERIVATIVE ! PORTION OF CODE THAT SOLVES DIFFERENTIAL EQUATIONS 3 4 !====== CHRONIC OR SUBCHRONI C EXPOSURE SCENARIO ======= 5 ! NUMBER OF EXPOSURES PER DAY 6 7DAY_LACK = EXP_TIME_ON ! DELAY BEFORE EXPOSURE BEGINS (HOURS) 8 DAY_PERIOD = DAY_CYCLE ! EXPOSURE PERIOD (HOURS) 9 DAY_FINISH = CINTXY ! LENGTH OF EXPOSURE (HOURS) 10 MONTH_PERIOD = TIMELIMIT ! EXPOSURE PERIOD (MONTHS) 11 MONTH_FINISH = EXP_TIME_OFF ! LENGTH OF EXPOSURE (MONTHS) 12 13 14 ! NUMBER OF EXPOSURES PER DAY AND MONTH 15 DAY_FINISH_BG = CINTXY 16 MONTH_LACK_BG = BCK_TIME_ON !DELAY BEFORE BACKGROUND 17 EXPOSURE BEGINS (MONTHS) 18 MONTH_PERIOD_BG = TIMELIMIT !BACKGROUND EXPOSURE PERIOD 19 (MONTHS) 20 MONTH_FINISH_BG = BCK_TIME_OFF !LENGTH OF BACKGROUND EXPOSURE 21 (MONTHS) 22 23 ! INTRAVENOUS LATE 24 IV_FINISH = CINTXY 25 B = 1-A ! FRACTION OF DIOXIN ABSO RBED IN THE PORTAL FRACTION OF THE 26 LIVER 27 28 ! MOTHER BODY WEI GHT GROWTH EQUATION 29 ! MODIFICATION TO ADAPT THIS MODEL AT HUMAN MODEL 30 ! BECAUSE LINEAR DESCRIPTION IS NO T GOOD ENOUGH FOR MOTHER GROWTH 31 ! MOTHER BODY WEIGHT GROWTH 32 ! HUMAN BODY WEIGHT (0 TO 45 YEARS) 33 ! POLYNOMIAL REGRESSION EXPRESSION WRITTEN 34 !APRIL 10 2008, OPTIMIZED WITH DATA OF PELEKIS ET AL. 2001 35 ! POLYNOMIAL REGRESSION EX PRESSION WRITTEN WITH 36 !HUH AND BOLCH 2003 FOR BMI CALCULATION 37 38 ! BODY WEIGHT CALCULATION. UNI T IN KG FOR GESTATIONAL PORTION 39 40WT0 = (0.0006*GYR**3 - 0.0912*GYR**2 + 4.32*GYR + 3.652) 41 42!BODY M ASS INDEX CALCULATION 43 44 BH = -2D-5*GYR* *4+4.2D-3*GYR**3.0-0.315*GYR**2.0+9.7465*GYR+72.098 45 !HEIGHT EQUATION FORMULATED FOR USE FROM 0 TO 70 YEARS 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-27 DRAFT

— DO NOT CITE OR QUOTE BHM= (BH/100.0)!HUMAN HEIGHT IN METER (BHM) 1 HBMI= WT0/(BHM**2.0) ! HUMAN BODY MASS INDEX (BMI) 2 3 4 !MODIFICATION IN KG 5 RTESTGEST= T-MATTING ! STARTING TIME FOR FETAL GROWTH 6 TESTGEST=DIM(RTESTGEST,0.0) 7 ! GROWTH OF FETAL TISSUE 8 GESTATTION_FE=((4d-15*TESTGEST**4 -3 d-11*TESTGEST**3 +1d-7*TESTGEST**2 - 9 8d-5*TESTGEST +0.0608)) 10 WTFER= DIM(GESTATTION_FE,0.0) ! FETAL COMPARTMENT WEIGHT 11 WTFE= WTFER 12 13 !///////////////////////////////////////////////////// ////////////////// 14 ! FAT GROWTH EXPRESSION LINEAR DURING PREGNANCY 15 ! FROM O'FLAHERTY_1992 16 !///////////////////////////////////////////////////// ////////////////// 17 18 WT0GR= WT0*1.0e3 ! MO THER BODY WEIGHT IN G 19 20 WF0 =(-6.36D-20*WT0GR **4.0 +1.12D-14*WT0GR**3.0 & 21 -5.8D-10*WT0GR **2.0+1.2D-5*WT0GR+5.91D-2) ! MOTHER FAT 22 COMPARTMENT GROWTH 23 24 !///////////////////////////////////////////////////// ////////////////// 25 ! WPLA PLACENTA GROWTH EXPRESSI ON, SINGLE EXPONENTIAL WITH OFFSET 26 ! FROM O'FLAHERTY_1992 ! FOR EACH PUP 27 !///////////////////////////////////////////////////// ////////////////// 28 !SAME EQUATION THEN THE FORST MOD EL. BODY WEIGHT KEPT IN G 29 !A CORRECTION FOR THE BODY WE IGHT (WTO(KG)*1000 = WTOGR) 30 31 WPLA0N_HUMAN= (850*exp(-9.434*(exp(-5.23d-4*(TESTGEST))))) 32 WPLA0R = WPLA0N_HUMAN/WT0GR 33 WPLA0W = DIM(WPLA0R,0.0) ! PLACENTA WEIGHT 34 WPLA0=WPLA0W 35 36 !///////////////////////////////////////////////////// ////////////////// 37 ! QPLA PLACENTA GROWTH EXPRESSION , DOUBL E EXPONENTIAL WITH OFFSET 38 ! FROM O'FLAHERTY_1992 39 !///////////////////////////////////////////////////// ////////////////// 40 41 QPLAF_HUMAN= SWITCH_trans*((1d- 10*TESTGEST**3.0 -5D-7*TESTGEST**2.0 42 +0.0017*TESTGEST+1.1937)/QC) 43 GEST_QPLAF=DIM(QPLAF_HUMAN,0.0) ! PLACENTA BLOOD FLOW RATE 44 QPLAF =GEST_QPLAF 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-28 DRAFT

— DO NOT CITE OR QUOTE ! LIVER,VOLUME (HUMAN 0 TO 70 YEARS) 1 ! APPROACH BASED ON LUECKE (2007) 2 WLI0= (3.59D-2 -(4.76D-7*WT0GR)+(8.50D -12*WT0GR**2.0)-(5.45D-17*WT0GR**3.0)) ! 3 LIVER VOLUME IN GROWING HUMAN 4 5 ! VARIABILITY OF REST OF THE BODY DEPENDS ON OTHER ORGAN 6 WRE0 = (0.91-(WLIB0*WLI0+WFB0*WF0 + WPLAB0*WPLA0 + WLI0 + WF0 + 7 WPLA0))/(1+WREB0) 8 QREF = 1-(QFF+QLIF+QPLAF) !REST BODY BLOOD FLOW (ML/HR) 9 QTTQF = QFF+QREF+QLIF+ QPLAF ! SUM MUST EQUAL 1 10 11 ! COMPARTMENT TISSUE BLOOD VOLUME (L) ========= 12 WF = WF0 * WT0 ! ADIPOSE TISSUE 13 WRE = WRE0 * WT0 ! REST OF THE BODY 14 WLI = WLI0 * WT0 ! LIVER 15 WPLA= WPLA0* WT0 ! PLACENTA 16 17 ! COMPARTMENT TISSUE VOLUME (L) ========= 18 WFB = WFB0 * WF ! ADIPOSE TISSUE 19 WREB = WREB0 * WRE ! REST OF THE BODY 20 WLIB = WLIB0 * WLI ! LIVER 21 WPLAB = WPLAB0* WPLA ! PLACANTA 22 23 ! TOTAL VOLUME OF COMPARTMENT (L)====== 24 WFT = WF ! TOTAL ADIPOSE TISSUE 25 WRET = WRE ! TOTAL REST OF THE BODY 26 WLIT = WLI ! TOTAL LIVER TISSUE 27 WPLAT= WPLAB ! TOTAL PLACENTA TISSUE 28 29 ! CONSTANT USED IN CARDIAC OUTPUT EQUATION 30 31 ! UNIT CHANGED ON JULY 14 2009 (L/HR) 32 QC= QCC*(WT0)**0.75 33 34 QF = QFF*QC ! ADIPOSE TISSUE BLOOD FLOW RATE (L/HR) 35 QLI = QLIF*QC ! LIVER TISSUE BLOOD FLOW RATE (L/HR) 36 QRE = QREF*QC !REST OF THE BODY BLOOD FLOW RATE (L/HR) 37 QPLA = QPLAF*QC !PLACENTA TISSUE BLOOD FLOW RATE (L/HR) 38 QTTQ = QF+QRE+QLI+QPLA !TOTAL FLOW RATE (L/HR) 39 40 ! ========= DIFFUSI ONAL PERMEABILITY FACTORS FRACTION ORGAN FLOW 41

========= 42 PAF = PAFF*QF ! ADIPOSE TISSUE BLOOD FLOW RATE (L/HR) 43 PARE = PAREF*QRE ! REST OF THE BODY BLOOD FLOW RATE (L/HR) 44 PALI = PALIF*QLI ! LIVER TISSUE BLOOD FLOW RATE (L/HR) 45 PAPLA = PAPLAF*QPLA ! PLACENTA TISSUE BLOOD FLOW RATE (L/HR) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-29 DRAFT

— DO NOT CITE OR QUOTE 1 !************************************** 2 ! ABSORPTION SECTION 3 ! ORAL 4 ! INTRAPERITONEAL 5 ! SUBCUTANEOUS 6 ! INTRAVENOUS 7 !************************************** 8 9 !BACKGROUND EXPOSURE 10 !EXPOSURE FOR STEADY STATE CONSIDERATION 11 !REPETITIVE EXPOSURE SCENARIO 12 13 MSTOT_NMBCKGR = MSTOTBCKGR/322 !AMOUNT IN NMOL/G 14 MSTTBCKGR =MSTOT_NMBCKGR *WT0 15 16 DAY_EXPOSURE_BG = PULSE(DAY_LACK _BG,DAY_PERIOD_BG,DAY_FINISH_BG) 17 WEEK_EXPOSURE_BG = 18 PULSE(WEEK_LACK_BG,WEEK_PERIOD_BG,WEEK_FINISH_BG) 19 MONTH_EXPOSURE_BG = 20 PULSE(MONTH_LACK_BG,MONTH_PERIOD_BG,MONTH_FINISH_BG) 21 22 MSTTCH_BG = 23 (DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG)*MSTTBCK 24 GR 25 MSTTFR_BG = MSTTBCKGR/CINT 26 27 CYCLE_BG =DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG 28 29 ! CONDITIONAL ORAL EXPOSURE (BACKGROUND EXPOSURE) 30 31 IF (MSTTCH_BG.EQ.MSTTBCKGR) THEN 32 ABSMSTT_GB= MSTTFR_BG 33 ELSE 34 ABSMSTT_GB = 0.0 35 END IF 36 37 CYCLETOTBG=INTE G(CYCLE_BG,0.0) 38 39 !************************************** 40 !MULTIROUTE EXPOSURE 41 !REPETITIVE EXPOSURE SCENARIO 42 !************************************** 43 MSTT= MSTOT_NM * WT0 !AMOUNT IN NMOL 44 DAY_EXPOSURE = PULSE(DAY_LACK,DAY_PERIOD,DAY_FINISH) 45 WEEK_EXPOSURE = PULSE(WEEK_LACK,WEEK_PERIOD,WEEK_FINISH) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-30 DRAFT

— DO NOT CITE OR QUOTE MONTH_EXPOSURE = PULSE(MONTH_LA CK,MONTH_PERIOD,MONTH_FINISH) 1 2 MSTTCH = (DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE)*MSTT 3 4 MSTTFR = MSTT/CINT 5 6 CYCLE = DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE 7 8 SUMEXPEVENT= INTEG (CYCLE,0.0) !NUM BER OF CYCLES GENERATED DURING 9 SIMULATION 10 11 ! CONDITIONAL ORAL EXPOSURE 12 IF (MSTTCH.EQ.MSTT) THEN 13 ABSMSTT= MSTTFR 14 ELSE 15 ABSMSTT = 0.0 16 END IF 17 18 19CYCLETOT=INTEG(CYCLE,0.0) 20 21 ! MASS CHANGE IN THE LUMEN 22 RMSTT= -(KST+KABS)*MST +ABSMSTT +ABSMSTT_GB ! RATE OF CHANGE 23 (NMOL/H) 24 MST = INTEG(RMSTT,0.0) !AMOUNT REMAINING IN DUODENUM 25 (NMOL) 26 27 ! ABSORPTION IN LYMPH CIRCULATION 28 LYRMLUM = KABS*MST*A 29 LYMLUM = INTEG(LYRMLUM,0.0) 30 31 ! ABSORPTION IN PORTAL CIRCULATION 32 LIRMLUM = KABS*MST*B 33 LIMLUM = INTEG(LIRMLUM,0.0) 34 35 36!IV ABSORPTION SCENARIO--------- 37 IV= DOSEIV_NM * WT0 !AMOUNT IN NMOL 38 IVR= IV/PFUNC ! RATE FO R IV INFUSION IN BLOOD 39 EXPIV= IVR * (1-STEP(PFUNC)) 40 IVDOSE = integ(EXPIV,0.0) 41 42!IV LATE IN THE CYCLE 43 !MODIFICATION JANUARY 13 2004 44 IV_RlateR = DOSEIVNMlate*WT0 45 IV_EXPOSURE=PULSE(IV_LACK,IV_PERIOD,IV_FINISH) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-31 DRAFT

— DO NOT CITE OR QUOTE 1IV_lateT = IV_EXPOSURE *IV_RlateR 2 IV_late = IV_lateT/CINT 3 4 SUMEXPEVENTIV= integ(IV_EXPOSURE,0.0) !NUMBER OF CYCLE GENERATE 5 DURING SIMULATION 6 7!SYSTEMIC BLOOD COMPARTMENT 8 ! MODIFICATION OCT 8 2009 9 CB=(QF*CFB+QRE*CREB+QLI*CLIB+EXPIV+ LYRMLUM+QPLA*CPLAB+IV_late)/(QC 10 +CLURI) ! 11 CA = CB ! CONCENTRATION (NMOL/L) 12 13!CB=(QF*CFB+QRE*CREB+QLI*CLIB+EXPIV+LYRMLUM+QPLA*CPLAB+IV_late14 RAURI)/QC !(NMOL/L) 15 16!URINARY EXCRETION BY KIDNEY 17 ! MODIFICATION OCT 8 2009 18 RAURI = CLURI *CB 19 AURI = INTEG(RAURI,0.0) 20 21!RAURI = CLURI * CRE 22 !AURI = INTEG(RAURI,0.0) 23 24!UNIT CONVERSION POST SIMULATION 25 CONSTANT MW=322 !MOLECULAR WEIGHT (NG/NMOL) 26 CONSTANT SERBLO = 0.55 27 CONSTANT UNITCORR = 1.0e3 28 29CBSNGKGLIADJ = CB*MW/(0.55*B_TOTLI P) !NG SERUM LI PID ADJUSTED/KG 30 AUCBS_NGKGLIADJ=i nteg(CBSNGKGLIADJ,0.) 31 CBNGKG= CB*MW !NG/KG 32 PRCT_B = 100.0*CB/(MSTT+1E-30) !PERCENT OF ORAL DOSE IN BLOOD 33 PRCT_BIV = 100.0*CB/(IV_Rla teR+1E-30) ! PERCENT OF IV DOSE IN BLOOD 34 35!ADIPOSE COMPARMTENT 36 !TISSUE BLOOD SUBCOMPARTMENT 37 RAFB= QF*(CA-CFB)-PAF*(CFB-CF/PF) !(NMOL/H) 38 AFB = INTEG(RAFB,0.0) !(NMOL) 39 CFB = AFB/WFB !(NMOL/L) 40 !TISSUE SUBCOMPARTMENT 41 RAF = PAF*(CFB-CF/PF) !(NMOL/H) 42 AF = INTEG(RAF,0.0) !(NMOL) 43 CF = AF/WF !(NMOL/L) 44 45!UNIT CONVERSION POST SIMULATION 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-32 DRAFT

— DO NOT CITE OR QUOTE CFTOTAL= (AF + AFB)/(WF + WFB) ! TOTAL CONCENTRATION IN NMOL/ML 1 PRCT_F = 100.0*CFTOTAL/(MSTT+1E-30) !PERCENT OF ORAL DOSE IN FAT 2 PRCT_FIV = 100.0*CFTOTAL/(IV_RlateR+1E- 30) !PERCENT OF IV DOSE IN FAT 3 CFNGKG=CFTOTAL*MW ! FAT CONCENTRATION IN NG/KG 4 AUCF_NGKGH=integ(CFNGKG,0.) 5 6 7!REST OF THE BODY COMPARTMENT 8 !TISSUE BLOOD SUBCOMPARTMENT 9 RAREB= QRE *(CA-CREB)-PARE*(CRE B-CRE/PRE) !(NMOL/H) 10 AREB = INTEG(RAREB,0.0) !(NMOL) 11 CREB = AREB/WREB !(NMOL/L) 12 !TISSUE SUBCOMPARTMENT 13 RARE = PARE*(CREB - CRE/PRE) !(NMOL/H) 14 ARE = INTEG(RARE,0.0) !(NMOL) 15 CRE = ARE/WRE !(NMOL/L) 16 ARETOT = ARE +AREB 17 18!POST SIMULATION UNIT CONVERSION 19 CRETOTAL= (ARE + AREB)/(WRE + WREB) ! TOTAL CONCENTRATION 20 (NMOL/L) 21 PRCT_RE = 100.0*CRETOTAL/(MSTT+1E-30) ! PERCENT OF ORAL DOSE IN REST OF 22 BODY 23 PRCT_REIV = 100.0*CRETOTAL/(IV_RlateR+1E-30) ![ PERCENT OF IV DOSE IN REST 24 OF BODY 25 CRENGKG=CRETOTAL*MW ! REST OF THE BODY CONCENTRATION 26 (NG/KG) 27 28 29!LIVER COMPARTMENT 30 !TISSUE BLOOD SUBCOMPARTMENT 31 RALIB = QLI*(CA-CLIB)-PALI*(CLI B-CFLLIR)+LIRMLUM ! (NMOL/HR) 32 ALIB = INTEG(RALIB,0.0) !(NMOL) 33 CLIB = ALIB/WLIB !(NMOL/L) 34 !TISSUE SUBCOMPARMTENT 35 RALI = PALI*(CLIB - CFLLIR)-REXCL I ! (NMOL/HR) 36 ALI = INTEG(RALI,0.0) !(NMOL) 37 CLI = ALI/WLI !(NMOL/L) 38 39!FREE TCDD CONCENTRATION IN LIVER 40 ! MODIFICATION OCTOBER 8 2009 41 CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR)) & 42 +((CYP1A2_1O3*CFLLIR/(KDL I2+CFLLIR)*PAS_INDUC)))-CFLLI,CFLLI0) 43 CFLLIR= DIM(CFLLI,0.0) ! FR EE TCDD CONCENTRATION IN LIVER 44 !MODIFIED FROM: 45 !PARAMETER (LIVER_1RMN = 1.0E-30) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-33 DRAFT

— DO NOT CITE OR QUOTE ! CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR & 1 !+LIVER_1RMN))+((CYP1A2_1O3*CFLLIR/(KDLI2 + CFLLIR & 2 !+LIVER_1RMN)*PAS_INDUC)))-CFLLI,CFLLI0) 3 !CFLLIR=DIM(CFLLI,0.0) 4 5 ! MODIFICATION OCTOBER 8 2009 6 CBNDLI= LIBMAX*CFLLIR/(KDLI+CFLLIR) !BOUND CONCENTRATION (NMOL/L) 7 8!POST SIMULATION UNIT CONVERSION 9 CLITOTAL= (ALI + ALIB)/(WLI + WLIB ) ! TOTAL CONCENTRATION (NMOL/L) 10 PRCT_LI = 100.0*CLITOTAL/(MSTT+1E-30) ! PERCENT OF ORAL DOSE IN LIVER 11 PRCT_LIIV = 100.0*CLITOTAL/(IV_RlateR+1E-30) ! PERCENT OF IV DOSE IN LIVER 12 Rec_occ= CFLLIR/(KDLI+CFLLIR) 13 CLINGKG=CLITOTAL*MW ! LIVER CONCENTRATION IN NG/KG 14 AUCLI_NGKGH=integ(CLINGKG,0.0) 15 CBNDLINGKG = CBNDLI*MW ! BOUN D CONCENTRATION IN NG/KG 16 AUCBNDLI_NGKGH =INTEG(CBNDLINGKG,0.0) 17 18 !FRACTION INCREASE OF INDUCTION OF CYP1A2 19 fold_ind=CYP1A2_1OUT/CYP1A2_1A2 20 VARIATIONOFAC =(CYP1A2_1 OUT-CYP1A2_1A2)/CYP1A2_1A2 21 22 !VARIABLE ELIMINATION BASED ON THE CYP1A2 23 ! MODIFICATION OCTOBER 8 2009 24 KBILE_LI_T = Kelv*VARIATIONOFAC! ! DOSE-DEPENDENT EXCRETION RATE 25 CONSTANT 26 27REXCLI = KBILE_LI_T*CFLLIR*WLI ! DOSE-DEPENDENT BILLIARY EXCRETION 28 RATE 29 EXCLI = INTEG(REXCLI,0.0) 30 31 !KBILE_LI_T =((CYP1A2_1OUT-CYP 1A2_1A2)/CYP1A2_1A2)*Kelv ! 32 33 34 !CHEMICAL IN CYP450 (1A2) COMPARTMENT 35 36 CYP1A2_1KINP = CYP1A2_1KOUT* CYP1 A2_1OUTZ ! BASAL PRODCUTION RATE OF 37 CYP1A2 SET EQUAL TO BA SAL DEGREDATION RATE 38 39! MODIFICATION OCTOBER 8 2009 40 CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1.0 + CYP1A2_1EMAX *(CBNDLI+1.0e41 30)**HILL & 42 /(CYP1A2_1EC50**HILL + (CBNDLI+1.0e-30)**HILL)) & 43 - CYP1A2_1KOUT*CYP1A2_1OUT, CYP1A2_1OUTZ) 44 !MODIFIED FROM: 45 !PARAMETER (CYP1A2_1RMN = 1E-30) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-34 DRAFT

— DO NOT CITE OR QUOTE !CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1 + CYP1A2_1EMAX *(CBND& 1 !LI +CYP1A2_1RMN)**HILL/(CYP1A 2_1EC50 + (CBNDLI + CYP1A2_1& 2 !RMN)**HILL) +CYP1A2_1RMN) - CYP1A2_1KOUT*CYP1A2_1& 3 !OUT, CYP1A2_1OUTZ) 4 5 ! EQUATIONS INCORPORATING DELAY OF CYP1A2 PRODUCTION (NOT USED IN 6 SIMULATIONS) 7 CYP1A2_1RO2 = (CYP1A2_1OUT - CYP1A2_1O2)/ CYP1A2_1TAU 8 CYP1A2_1O2 =INTEG(CYP1A2_1RO2, CYP1A2_1A1) 9 10 CYP1A2_1RO3 = (CYP1A2_1O2 - CYP1A2_1O3)/ CYP1A2_1TAU 11 CYP1A2_1O3 =INTEG(CYP1A2_1RO3, CYP1A2_1A2) 12 13!PLACENTA COMPARTMENT 14 !TISSUE BLOOD SUBCOMPARTMENT 15 RAPLAB= QPLA*(CA - CPLAB)-PAPLA*( CPLAB -CFLPLAR) ! NMOL/HR) 16 APLAB = INTEG(RAPLAB,0.0) ! (NMOL) 17 CPLAB = APLAB/(WPLAB+1E-30) ! (NMOL/ML) 18 !TISSUE SUBCOMPARTMENT 19 RAPLA = PAPLA*(CPLAB-CFLPLAR)-RAMPF + RAFPM ! (NMOL/HR) 20 APLA = INTEG(RAPLA,0.0) ! (NMOL) 21 CPLA = APLA/(WPLA+1e-30) ! (NMOL/ML) 22 23! NEW EQUATION AUGUST 28 2009 24 PARAMETER (PARA_ZERO = 1.0E-30) 25 CFLPLA= IMPLC(CPLA-(CFLPLAR*PPLA +(PLABMAX*CFLPLAR/(KDPLA& 26 +CFLPLAR+PARA_ZERO)))-CFLPLA,CFLPLA0) 27 CFLPLAR=DIM(CFLPLA,0.0) 28 29!POST SIMULATION UNIT CONVERSION 30 CPLATOTAL = ((APLAB+APLA)/(WPLAB+WPLA)) 31 PRCT_PLA = (CPLATOTAL/(MSTT+1E-30))*100 32 PRCT_PLAIV = (CPLATOTAL/(IV_RlateR+1E-30))*100 33 34!FETUS COMPARTMENT 35 RAFETUS= RAMPF-RAFPM 36 AFETUS=INTEG(RAFETUS,0.0) 37 CFETUS=AFETUS/(WTFE+1.0e-30) 38 CFETOTAL= CFETUS 39 CFETUS_v = CFETUS/PFETUS 40 41!POST SIMULATION UNIT CONVERSION 42 CFETUSNGKG = CFETUS*MW !(NG/KG) 43 PRCT_FE = 100.0*CFETOTAL/(MSTT+1E-30) 44 PRCT_FEIV = 100.0*CFETOTAL/(IV_RlateR+1E-30) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-35 DRAFT

— DO NOT CITE OR QUOTE !TRANSFER OF DIOXIN FROM PLACENTA TO FETUS 1 !FETAL EXPOSURE ONLY DURING EXPOSURE 2 3 IF (T.LT.TRANSTIME_ON) THEN 4 SWITCH_trans = 0.0 5 ELSE 6 SWITCH_trans = 1 7 END IF 8 9!TRANSFER OF DIOXIN FROM PLACENTA TO FETUS 10 ! MODIFICATION 26 SEPTEMBER 2003 11 12 RAMPF = (CLPLA_FET*CPLA)*SWITCH_trans 13 AMPF=INTEG(RAMPF,0.0) 14 15!TRANSFER OF DIOXIN FROM FETUS TO PLACENTA 16 RAFPM = (CLPLA_FET*CFETUS_v)*SWITCH_trans! 17 AFPM = INTEG(RAFPM,0.0) 18 19!CHECK MA SS BALANCE ---------- 20 BDOSE= IVDOSE +LYMLUM+LIMLUM 21 BMASSE = EXCLI+AURI+AFB+AF+AREB+A RE+ALIB+ALI+APLA+APLAB+AFETUS ! 22 BDIFF = BDOSE-BMASSE 23 24!BODY BURDEN (NMOL) 25 BODY_BURDEN = AFB+AF+AREB+ARE+ALIB+ALI+APLA+APLAB 26 27!BODY BURDEN CONCENTRATION (NG/KG) 28 BBNGKG =(AFB+AF+AREB+ARE+AL IB+ALI+APLA+APLAB)*MW/WT0 29 30 ! END SIMULATION COMMAND 31 32 TERMT (T.GE. TimeLimit, 'Time limit has been reached.') 33 34 END ! END OF THE DERIVATIVE SECTION 35 END ! END OF THE DYNAMIC SECTION 36 END ! END OF THE PROGRAM 37 38
C.2.2.2. Input File 39 output @clear 40 prepare @clear T year CLINGKG CFNGKG CBSNGKGL IADJ BBNGKG CBNDLINGKG 41 CBNGKG 42 43 CINT = 1 %168 %100 %INTEGRATION TIME 44 %EXPOSURE SCENARIO 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-36 DRAFT

— DO NOT CITE OR QUOTE EXP_TIME_ON = 0 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 1 EXP_TIME_OFF = 401190 %TIM E AT WHICH EXPOSU RE ENDS (HOUR) 2 DAY_CYCLE = 24 %NUMBER OF HOURS BETWEEN DOSES (HOUR) 3 BCK_TIME_ON = 401190 %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 4 (HOUR) 5 BCK_TIME_OFF = 401190 %TIME AT WHICH BACKGROUND EXPOSURE ENDS 6 (HOUR) 7 IV_LACK = 401190 8 IV_PERIOD = 401190 9 %GESTATION CONTROL 10 MATTING = 393120 % BE GINNING OF MATING (HOU R) AT 45 YEARS OLD 11 TIMELIMIT = 399840 %SIMULATION TIME LIMIT (HOUR) 12 TRANSTIME_ON = 394632 % TR ANSFER FROM MOTHER TO FETUS AT 1512 13 HOURS GESTATION 14 %EXPOSURE DOSE 15 MSTOT = 9.97339283634997E-07 % NG OF TCDD PER KG OF BW 16 MSTOTBCKGR = 0. %0.1 % ORAL BACKGROUND EXPOSURE DOSE (NG/KG) 17 DOSEIV = 0. %10 18 DOSEIVLATE = 0. %10 19 20% TRANFER MOTHER TO FETUS CLEARANCE 21 CLPLA_FET = 0.001 % MOTHER TO FETUS TRANFER CLEARANCE (L/HR) 22 23
C.2.3. Rat Standard Model 24 C.2.3.1. Model Code 25
PROGRAM : 'Three Compartment PBPK Model in Rat: Standard Model (Non26 Gestation)' 27
28 !Rat_Dioxin_3C June09_2clean_i cf_afterKKfix_v3_ratnongest.csl 29 !RAT_NON_GEST_ICF_F083109.CSL 30 !RAT_NON_GEST_ICF_F100609.CSL 31 !***************************************************** 32 33 INITIAL ! INITIALIZATION OF PARAMETERS 34 35!SIMULATION PARAMETERS 36 CONSTANT PARA_ZERO = 1d-30 37 CONSTANT EXP_TIME_ON = 0.0 ! TIME AT WHICH EXPOSURE BEGINS 38 (HOURS) 39 CONSTANT EXP_TIME_OFF = 900.0 ! TIME AT WHICH EXPOSURE ENDS 40 (HOURS) 41 CONSTANT DAY_CYCLE = 900.0 ! NUMBER OF HOURS BETWEEN DOSES 42 (HOURS) 43

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-37 DRAFT

— DO NOT CITE OR QUOTE CONSTANT BCK_TIME_ON = 0.0 ! TIME AT WHICH BACKGROUND 1 EXPOSURE BEGINS (HOURS) 2 CONSTANT BCK_TIME_OFF = 0.0 ! TIME AT WHICH BACKGROUND 3 EXPOSURE ENDS (HOURS) 4 5 CONSTANT MW=322 !MOLECULAR WEIGHT (NG/NMOL) 6 CONSTANT SERBLO = 0.55 7 CONSTANT UNITCORR = 1000 8 9 10!EXPOSURE DOSES 11 CONSTANT MSTOTBCKGR = 0.0 !ORAL BACKGROUND EXPOSURE DOSE 12 (UG/KG) 13 CONSTANT MSTOT = 10 !ORAL EXPOSURE DOSE (UG/KG) 14 CONSTANT MSTOTsc = 0.0 !SUBCUTANE OUS EXPOSURE DOSE (UG/KG) 15 CONSTANT DOSEIV = 0.0 ! INJECTED DOSE (UG/KG) 16 17!ORAL DOSE 18 MSTOT_NM = MSTOT/MW !AMOUNT IN NMOL/G 19 MSTOT_NMBCKGR = MSTOTBCKGR/MW !AMOUNT IN NMOL/G 20 21!INTRAVENOUS DOSE 22 DOSEIV_NM = DOSEIV/MW !AMOUNT IN NMOL/G 23 24!INITIAL GUESS OF THE FREE CONCENTRATION IN THE LIGAND 25 (COMPARTMENT INDICATED BELOW)==== 26 CONSTANT CFLLI0 = 0.0 !LIVER (NMOL/ML) 27 28!BINDING CAPACITY (AhR) FO R NON LINEAR BINDING (COMPARTMENT 29 INDICATED BELOW) (NMOL/ML) === 30 CONSTANT LIBMAX = 3.5e-4 ! LIVER (NMOL/ML), WANG ET AL. 1997 31 32! PROTEIN AFFINITY CONSTANTS (1A2 OR AhR, COMPARTMENT INDICATED 33 BELOW) (NMOL/ML)=== 34 CONSTANT KDLI = 1.0e-4 ! LIVER (AhR) (N MOL/ML), WANG ET AL. 1997 35 CONSTANT KDLI2 = 4.0e-2 !LIVER (1A2) (NMOL/ML), EMOND ET AL. 36 2004 37 38!EXCRETION AND ABSORPTION CONSTANT [RAT] 39 CONSTANT KST = 0.36 ! GASTRIC RATE CONSTANT (HR-1), WANG ET 40 AL. (1997) 41 CONSTANT KABS = 0.48 !INTESTINAL ABSORPTI ON CONSTANT (HR42 1), WANG ET AL. 1997 43 44!URINARY ELIMI NATION CLEARANCE (ML/HR) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-38 DRAFT

— DO NOT CITE OR QUOTE CONSTANT CLURI = 0.01 !URINARY CLEARANCE (ML/HR), EMOND ET 1 AL. 2004 2 3!INTERSPECIES VARIABLE ELIMINATION 4 CONSTANT KELV = 0.15 ! INTERSPECIES VARIABLE ELIMINATION 5 CONSTANT (1/HOUR) (OPTIMIZED), EMOND ET AL. 2004 6 7! CONSTANT TO DIVIDE THE ABSORPTION INTO LYMPHATIC AND PORTAL 8 FRACTIONS 9 CONSTANT A = 0.7 ! LYMPHATIC FRACTION, WANG ET AL. 1997 10 11!PARTITION COEFFICIENTS 12 CONSTANT PF = 100 ! ADIPOSE TISSUE/BLOOD, WANG ET AL. 1997 13 CONSTANT PRE = 1.5 ! REST OF THE BODY/BLOOD, WANG ET AL. 14 1997 15 CONSTANT PLI = 6.0 ! LIVER/BLOOD, WANG ET AL. 1997 16 17!PARAMETER FOR INDUCTION OF CYP 1A2 [MOUSE] === 18 CONSTANT PAS_INDUC = 1.0 ! INCLUDE INDUCTION? (1 = YES, 0 = NO) 19 CONSTANT CYP1A2_1OUTZ = 1.6 ! DEGRADATION CONCENTRATION 20 CONSTANT OF 1A2 (NMOL/ML), WANG ET AL. 1997 21 CONSTANT CYP1A2_1A1 = 1.6 ! BASAL CONCENTRATION OF 1A1 22 (NMOL/ML), WANG ET AL. 1997 23 CONSTANT CYP1A2_1EC50 = 0.13 ! DISSOCIATION CONSTANT TCDD24 CYP1A2 (NMOL/ML) , WANG ET AL. 1997 25 CONSTANT CYP1A2_1A2 = 1.6 ! BASAL CONCENTRATION OF 1A2 26 (NMOL/ML) Wang et al (1997) 27 CONSTANT CYP1A2_1KOUT = 0.1 ! FIRST ORDER RATE OF DEGRADATION 28 (H-1), WANG ET AL. 1997 29 CONSTANT CYP1A2_1TAU = 0.25 ! HOLDING TIME (H), WANG ET AL. 1997 30 CONSTANT CYP1A2_1EMAX = 600 ! MAXIMUM INDUCTION OVER BASAL 31 EFFECT (UNITLESS), WANG ET AL. 1997 32 CONSTANT HILL = 0.6 !HILL CONSTANT; COOPERATIVELY LIGAND 33 BINDING EFFECT CONS TANT (UNITLESS) 34 35!TISSUE BLOOD FLOW EXPRESSED AS A FRACTION OF CARDIAC OUTPUT 36 CONSTANT QFF = 0.069 ! ADIPOSE TISSUE BLOOD FLOW FRACTION 37 (UNITLESS), WANG ET AL. 1997 38 CONSTANT QLIF = 0.183 ! LIVER ( UNITLESS), WANG ET AL. 1997 39 40!DIFFUS IONAL PERMEABILITY FRACTION 41 CONSTANT PAFF = 0.0910 ! ADIPOSE (UNITLESS), WANG ET AL. 1997 42 CONSTANT PAREF = 0.0298 ! REST OF THE BODY (UNITLESS), WANG ET 43 AL. 1997 44 CONSTANT PALIF = 0.35 ! LIVER ( UNITLESS), WANG ET AL. 1997 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-39 DRAFT

— DO NOT CITE OR QUOTE !FRACTION OF TISSUE VOLUME (UNITLESS) 1 CONSTANT WLI0 = 0.0360 ! LIVER, WANG ET AL. 1997 2 CONSTANT WF0 = 0.069 ! BLOOD, WANG ET AL. 1997 3 4!COMPARTMENT TISSUE BLOOD EX PRESSED AS A FRACTION OF THE TOTAL 5 COMPARTMENT VOLUME ========= 6 CONSTANT WFB0 = 0.050 ! ADIPOSE TISSUE, WANG ET AL. 1997 7 CONSTANT WREB0 = 0.030 ! REST OF THE BODY, WANG ET AL. 1997 8 CONSTANT WLIB0 = 0.266 ! LIVER , WANG ET AL. 1997 9 10!EXPOSURE SCENARIO FOR UNIQUE OR REPETITIVE WEEKLY OR MONTHLY 11 EXPOSURE 12 ! NUMBER OF EXPOSURES PER WEEK 13 CONSTANT WEEK_LACK = 0.0 ! DELAY BEFORE EXPOSURE ENDS 14 (WEEK) 15 CONSTANT WEEK_PERIOD = 168.0 ! NUMBER OF HOURS IN THE WEEK 16 (HOURS) 17 CONSTANT WEEK_FINISH = 168.0 ! TIME EXPOSURE ENDS (HOURS) 18 19!NUMBER OF EXPOSURES PER MONTH 20 CONSTANT MONTH_LACK = 0.0 ! DELAY BEFORE EXPOSURE BEGINS 21 (MONTH) 22 23!SET FOR BACKGROUND EXPOSURE=========== 24 !CONSTANT FO R BACKGROUND EXPOSURE=========== 25 CONSTANT Day_LACK_BG = 0.0 ! DELAY BEFORE EXPOSURE BEGINS 26 (HOURS) 27 CONSTANT Day_PERIOD_BG = 24.0 ! LENGTH OF EXPOSURE (HOURS) 28 29!NUMBER OF EXPOSURES PER WEEK 30 CONSTANT WEEK_LACK_BG = 0.0 ! DELAY BEFORE BACKGROUND 31 EXPOSURE (WEEK) 32 CONSTANT WEEK_PERIOD_BG = 168.0 !NUMBER OF HOURS IN THE WEEK 33 (HOURS) 34 CONSTANT WEEK_FINISH_BG = 168.0 ! TIME EXPOSURE ENDS (HOURS) 35 36!GROWTH CONSTANT FOR RAT 37 !CONSTANT FOR MOTHER BODY WEIGHT GROWTH ====== 38 CONSTANT BW_T0 = 250.0 !CHANGED FOR SIMULATION 39 40! CONSTANT USED IN CARDIAC OUTPUT EQUATION 41 CONSTANT QCCAR =311.4 !CONSTANT (ML/MIN/K G), WANG ET AL. 42 43! COMPARTMENT LIPID EXPRE SSED AS THE FRACTION OF TOTAL LIPID 44 CONSTANT F_TOTLIP = 0.855 !ADIPOSE TISSUE (UNITLESS) 45 CONSTANT B_TOTLIP = 0.0033 !BLOOD (UNITLESS) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-40 DRAFT

— DO NOT CITE OR QUOTE CONSTANT RE_TOTLIP = 0.019 !REST OF THE BODY (UNITLESS) 1 CONSTANT LI_TOTLIP = 0.06 !LIVER (UNITLESS) 2 3 END !END OF THE INITIAL SECTION 4 5 DYNAMIC !DYNAMIC SIMULATION SECTION 6 7 ALGORITHM IALG = 2 ! GEAR METHOD 8 CINTERVAL CINT = 0.1 ! COMMUNICATION INTERVAL 9 MAXTERVAL MAXT = 1.0e+10 ! MAXIMUM CALCULATION INTERVAL 10 MINTERVAL MINT = 1.0E-10 ! MINIMUM CALCULATION INTERVAL 11 VARIABLE T = 0.0 12 CONSTANT TIMELIMIT = 900.0 !SIMULATION TIME LIMIT (HOURS) 13 CINTXY = CINT 14 PFUNC = CINT 15 16!TIME CONVERSION 17 DAY=T/24.0 ! TIME IN DAYS 18 WEEK =T/168.0 ! TIME IN WEEKS 19 MONTH =T/730.0 ! TIME IN MONTHS 20 YEAR=T/8760.0 ! TIME IN YEARS 21 22 23 DERIVATIVE ! PORTION OF CODE THAT SOLVES DIFFERENTIAL EQUATIONS 24 25!CHRONIC OR SU BCHRONIC EXPOSURE SCENARIO ======= 26 !NUMBER OF EXPOSURES PER DAY 27 DAY_LACK = EXP_TIME_ON ! DELAY BEFORE EXPOSURE BEGINS 28 (HOURS) 29 DAY_PERIOD = DAY_CYCLE ! EXPOSURE PERIOD (HOURS) 30 DAY_FINISH = CINTXY ! LENGTH OF EXPOSURE (HOURS) 31 MONTH_PERIOD = TIMELIMIT ! EXPOSURE PERIOD (MONTHS) 32 MONTH_FINISH = EXP_TIME_OFF ! LENGTH OF EXPOSURE (MONTHS) 33 34!NUMBER OF EXPOSURES PER DAY AND MONTH 35 DAY_FINISH_BG = CINTXY ! LENGTH OF EXPOSURE (HOURS) 36 MONTH_LACK_BG = BCK_TIME_ON ! DELAY BEFORE BACKGROUND 37 EXPOSURE BEGINS (MONTHS) 38 MONTH_PERIOD_BG = TIMELIMIT ! BACKGROUND EXPOSURE PERIOD 39 (MONTHS) 40 MONTH_FINISH_BG = BCK_TIME_OFF ! LENGTH OF BACKGROUND 41 EXPOSURE (MONTHS) 42 43 44 B = 1-A ! FRACTION OF DI OXIN ABSOR BED IN THE PORTAL 45 FRACTION OF THE LIVER 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-41 DRAFT

— DO NOT CITE OR QUOTE 1! BODY WE IGHT GROWTH EQUATION======== 2 PARAMETER (BW_RMN = 1.0E-30) 3 WT0= (BW_T0 *(1.0+(0.41*T)/(1402.5+T+BW_RMN))) 4 5!VARIABILITY OF REST OF THE BODY DEPEND OTHERS ORGAN 6 WRE0 = (0.91 - (WLIB0*WLI0 + WFB0*WF0 + WLI0 + WF0))/(1.0+WREB0) !REST OF 7 THE BODY FRACTION; UPDATED FOR EPA ASSESSMENT 8 QREF = 1.0-(QFF+QLIF) !REST OF BODY BLOOD FLOW 9 QTTQF = QFF+QREF+QLIF ! SUM MUST EQUAL 1 10 11!COMPARTMENT VOLUME (G) ========= 12 WF = WF0 * WT0 ! ADIPOSE 13 WRE = WRE0 * WT0 ! REST OF THE BODY 14 WLI = WLI0 * WT0 ! LIVER 15 16!COMPARTMENT TISSUE BLOOD VOLUME (G) ========= 17 WFB = WFB0 * WF ! ADIPOSE 18 WREB = WREB0 * WRE ! REST OF THE BODY 19 WLIB = WLIB0 * WLI ! LIVER 20 21!CARDIAC OUTPU T FOR THE GIVE N BODY WEIGHT 22 QC= QCCAR*60.0*(WT0/UNITCORR)**0.75 23 24! COMPARTMENT BLOOD FLOW (ML/HR) 25 QF = QFF*QC ! ADIPO SE TISSUE BLOOD FLOW RATE 26 QLI = QLIF*QC ! LIVER TISSUE BLOOD FLOW RATE 27 QRE = QREF*QC ! REST OF THE BODY BLOOD FLOW RATE 28 QTTQ = QF+QRE+QLI ! TOTAL FLOW RATE 29 30!PERMEABILITY ORGAN FLOW (ML/HR) 31 PAF = PAFF*QF ! ADIPOSE 32 PARE = PAREF*QRE ! REST OF THE BODY 33 PALI = PALIF*QLI ! LIVER TISSUE 34 35!CONDITIONAL ORAL EXPOSURE (BACKGROUND EXPOSURE) 36 !EXPOSURE + !REPETITIVE EXPOSURE SCENARIO 37 IV= DOSEIV_NM * WT0 !AMOUNT IN NMOL 38 MSTT= MSTOT_NM * WT0 !AMOUNT IN NMOL 39 MSTTBCKGR =MSTOT_NMBCKGR *WT0 40 41!REPE TITIVE ORAL BACKGROUND EXPOSURE SCENARIOS 42 DAY_EXPOSURE_BG = 43 PULSE(DAY_LACK_BG,DAY_PERIOD_BG,DAY_FINISH_BG) 44 WEEK_EXPOSURE_BG = 45 PULSE(WEEK_LACK_BG,WEEK_PERIOD_BG,WEEK_FINISH_BG) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-42 DRAFT

— DO NOT CITE OR QUOTE MONTH_EXPOSURE_BG = 1 PULSE(MONTH_LACK_BG,MONTH_PERIOD_BG,MONTH_FINISH_BG) 2 3MSTTCH_BG = 4 (DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG)*MSTTBCK 5 GR 6 MSTTFR_BG = MSTTBCKGR/CINT 7 8CYCLE_BG =DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG 9 10 IF (MSTTCH_BG.EQ.MSTTBCKGR) THEN 11 ABSMSTT_GB= MSTTFR_BG 12 ELSE 13 ABSMSTT_GB = 0.0 14 END IF 15 16 17!REPETITIVE OR AL MAIN EXPOSURE SCENARIO 18 DAY_EXPOSURE = PULSE(DAY_LACK,DAY_PERIOD,DAY_FINISH) 19 WEEK_EXPOSURE = PULSE(WEEK _LACK,WEEK_PERIOD,WEEK_FINISH) 20 MONTH_EXPOSURE = PULSE(MONTH_LACK,MONTH_PERIOD,MONTH_FINISH) 21 22MSTTCH = (DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE)*MSTT 23 CYCLE = DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE 24 MSTTFR = MSTT/CINT 25 26SUMEXPEVENT= integ (CYCLE,0.0) !NUMBER OF CYC LE GENERATE DURING 27 SIMULATION 28 29 30!CONDITIONAL ORAL EXPOSURE 31 IF (MSTTCH.EQ.MSTT) THEN 32 ABSMSTT= MSTTFR 33 ELSE 34 ABSMSTT = 0.0 35 END IF 36 37CYCLETOT=INTEG(CYCLE,0.0) 38 39!MASS CHANGE IN THE LUMEN 40 RMSTT = -(KST+KABS)*MST+ABSMS TT +ABSMSTT_GB ! RATE OF CHANGE 41 (NMOL/H) 42 MST = INTEG(RMSTT,0.0) !AM OUNT OF STAY IN DUODENUM (NMOL) 43 44!ABSORPTION IN LYMPH CIRCULATION 45 LYRMLUM = KABS*MST*A 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-43 DRAFT

— DO NOT CITE OR QUOTE LYMLUM = INTEG(LYRMLUM,0.0) 1 2!ABSORPTION IN PORTAL CIRCULATION 3 LIRMLUM = KABS*MST*B 4 LIMLUM = INTEG(LIRMLUM,0.0) 5 6!PERCENT OF DO SE REMAINING IN THE GI TRACT 7 PRCT_remain_GIT = (MST/(MSTT+PARA_ZERO))*100.0 8 9!ABSORPTION of Dioxin by IV route--------- 10 IVR= IV/PFUNC ! RATE FO R IV INFUSION IN BLOOD 11 EXPIV= IVR * (1.0-STEP(PFUNC)) 12 IVDOSE = integ(EXPIV,0.0) 13 14!SYSTEMIC BLOOD COMPARTMENT 15 ! MODIFICATION ON OCTOBER 6, 2009 16 CB=(QF*CFB+QRE*CREB+QLI*CLIB+ EXPIV+LYRMLUM)/(QC+CLURI) ! 17 CA = CB 18 19!URINARY EXCRETION BY KIDNEY 20 ! MODIFICATION ON OCTOBER 6, 2009 21 RAURI = CLURI *CB 22 AURI = INTEG(RAURI,0.0) 23 24!CONVERSION EQUATION POST SIMULATION 25 PRCT_B = (CB/(MSTT+PARA_ZERO))*100.0 26 CBNGKG = CB*MW*UNITCORR ![NG/KG] 27 28 29 CBSNGKGLIADJ= (CB*MW*UNITCORR*(1.0/ B_TOTLIP)*(1.0/SERBLO))![NG of TCDD 30 Serum/Kg OF LIPIP] 31 32!ADIPOSE TISSUE COMPARTMENT 33 !TISSUE BLOOD SUBCOMPARTMENT 34 RAFB = QF*(CA-CFB)-PAF*(CFB-CF/PF) !(NMOL/HR) 35 AFB = INTEG(RAFB,0.0) !(NMOL) 36 CFB = AFB/WFB !(NMOL/ML) 37 !TISSUE SUBCOMPARTMENT 38 RAF = PAF*(CFB-CF/PF) !(NMOL/HR) 39 AF = INTEG(RAF,0.0) !(NMOL) 40 CF = AF/WF !(NMOL/ML) 41 42!CONVERSION EQUATION POST SIMULATION 43 CFTOTAL = (AF + AFB)/(WF + WFB) !TOTAL CONCENTRATION IN NMOL/ML 44 PRCT_F = (CFTOTAL/(MSTT+PARA _ZERO))*100.0 ! PRCENT OF DOSE IN FAT 45 CFNGKG = CFTOT AL*MW*UNITCORR ! CONCENTRATION [NG/KG] 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-44 DRAFT

— DO NOT CITE OR QUOTE 1!REST OF THE BODY COMPARTMENT 2 ! TISSUE BLOOD SUBCOMPARTMENT 3 RAREB= QRE*(CA-CREB)-PARE*(CREB-CRE /PRE) !(NMOL/HR) 4 AREB = INTEG(RAREB,0.0) !(NMOL) 5 CREB = AREB/WREB !(NMOL/ML) 6 ! TISSUE COMPARTMENT 7 RARE = PARE*(CREB - CRE/PRE) !(NMOL/HR) 8 ARE = INTEG(RARE,0.0) !(NMOL) 9 CRE = ARE/WRE !(NMOL/ML) 10 11!CONVERSION EQUATION POST SIMULATION 12 CRETOTAL= (ARE + AREB)/(W RE + WREB) ! TOTAL CONCENTRATION IN 13 NMOL/ML 14 PRCT_RE = (CRETOTAL/(MSTT+PARA_ZERO))*100.0 15 CTREPGG= CRETOTAL*MW*UNITCORR !(PG/ML) 16 AUC_REPPG = integ(CTREPGG,0.0) 17 18!LIVER COMPARTMENT 19 !TISSUE BLOOD COMPARTMENT 20 RALIB = QLI*(CA-CLIB)-PALI*(CLIB-CFLLIR)+LIRMLUM !(NMOL/HR) 21 ALIB = INTeg(RALIB,0.0) !(NMOL) 22 CLIB = ALIB/WLIB 23 !TISSUE COMPARTMENT 24 RALI = PALI*(CLIB-CFLLIR)-REXCLI !(NMOL/HR) 25 ALI = integ(RALI,0.0) !(NMOL) 26 CLI = ALI/WLI !(NMOL/ML) 27 28 29 PARAMETER (LIVER_1RMN = 1.0E-30) 30 CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR & 31 +LIVER_1RMN))+((CYP1A2_1O3*C FLLIR/(KDLI2+CFLLIR & 32 +LIVER_1RMN)*PAS_INDUC)))-CFLLIR,CFLLI0) ! FREE TCDD CONCENTRATION IN 33 LIVER 34 CFLLIR=DIM(CFLLI,0.0) 35 36CBNDLI= LIBMAX*CFLLIR/(KDL I+CFLLIR+LIVER_1RMN) !BOUND 37 CONCENTRATION 38 39!CONVERSION EQUATION POST SIMULATION 40 CLITOTAL= (ALI + ALIB)/(WLI + WLIB) ! TOTAL CONCENTRATION IN 41 NMOL/ML 42 PRCT_LI = (CLITOTA L/(MSTT+PARA_ZERO))*100.0 43 rec_occ_AHR= (CFLLIR/(KDLI+CFLLIR+1 ))*100.0 ! PERCENT OF AhR 44 OCC UPANCY 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-45 DRAFT

— DO NOT CITE OR QUOTE PROT_occ_1A2= (CFLLIR/(KDLI2+CFLLIR ))*100.0 ! PERCENT OF 1A2 1 OCCUPANCY 2 CLINGKG =(CLITOTAL*MW*UNITCORR) 3 CBNDLINGKG = CBNDLI*MW*UNITCORR 4 AUCLI_NGKGH=INTEG(CLINGKG,0.0) 5 CLINGG=CLITOTAL*MW 6 7!VARIABLE ELIMINATION HALF- LIFE BASED ON THE CONCENTRATION OF 8 CYP1A2 9 KBILE_LI_T =((CYP1A2_1OUT-CYP1A2_1A2)/CYP1A2_1A2)*Kelv ! INDUCED 10 BILIARY EXCRETION RATE CONSTANT 11 12REXCLI= (KBILE_LI_T*CFLLIR*WLI) ! DOSE-DEPENDENT BILIARY EXCRETION 13 RATE 14 EXCLI = INTEG(REXCLI,0.0) 15 16!CHEMICAL IN CYP450 (1A2) COMPARTMENT 17 !===PARAMETER FOR INDUCTION OF CYP1A2 18 19CYP1A2_1KINP = CYP1A2_1KOUT* CY P1A2_1OUTZ ! BASAL RATE OF CYP1A2 20 PRODUCTION SET EQUAL TO BASAL RATE OF DEGREDATION 21 22 23! MODIFICATION ON OCTOBER 6, 2009 24 CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1.0 + CYP1A2_1EMAX *(CBNDLI+1.0e25 30)**HILL & 26 /(CYP1A2_1EC50**HILL + (CBNDLI+1.0e-30)**HILL)) &- 27 - CYP1A2_1KOUT*CYP1A2_1OUT, CYP1A2_1OUTZ) 28 29 ! EQUATIONS INCORPORATING DELAY OF CYP1A2 PRODUCTION (NOT USED IN 30 SIMULATIONS) 31 32CYP1A2_1RO2 = (CYP1A2_1OUT - CYP1A2_1O2)/ CYP1A2_1TAU 33 CYP1A2_1O2 =INTEG(CYP1A2_1RO2, CYP1A2_1A1) 34 CYP1A2_1RO3 = (CYP1A2_1O2 - CYP1A2_1O3)/ CYP1A2_1TAU 35 CYP1A2_1O3 =INTEG(CYP1A2_1RO3, CYP1A2_1A2) 36 37 ! ------------CHECK MASS BALANCE ---------- 38 BDOSE= LYMLUM+LIMLUM+IVDOSE 39 BMASSE = EXCLI+AURI+AFB+AF+AREB+ARE+ALIB+ALI 40 BDIFF = BDOSE-BMASSE 41 42 !---------------BODY BURD EN--------------- --------- 43 BBNGKG =(((AFB+AF+AREB+ ARE+ALI B+ALI)*MW)/(WT0/UNITCORR)) ! 44 ! ------------ END OF THE SIMULATION COMMAND ---------- 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-46 DRAFT

— DO NOT CITE OR QUOTE TERMT (T.GE. TimeLimit, 'Time limit has been reached.') 1 2 END ! END OF THE DERIVATIVE SECTION 3 END ! END OF THE DYNA MIC SIMULATION SECTION 4 END ! END OF THE PROGRAM. 5 6
C.2.3.2. Input Files 7 C.2.3.2.1. Cantoni et al. (1981). 8 output @clear 9 prepare @clear 10 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 11 12 %Cantoni et al. 1981 13 %protocol: oral exposure 1 dose/week for 45 weeks; female CD-COBS rats 14 %dose levels: 0.01, 0.1, 1 ug/kg 1 dose/week for 45 weeks 15 %dose levels: 10, 100, 1000 ng/kg 1 dose/week for 45 weeks 16 %dose levels equivalent to: 1.43, 14. 3 143 ng/kg 7 days/week for 45 weeks 17 18 MAXT = 0.01 19 CINT = 0.1 20 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 21 EXP_TIME_OFF = 7560 %TIM E AT WHICH EXPOSURE ENDS (HOUR) 22 DAY_CYCLE = 168 23 BCK_TIME_ON = 0. %T IME AT WHICH BACKGROUND EXPOSURE BEGINS 24 (HOUR) 25 BCK_TIME_OFF = 0. %TIM E AT WHICH BACKGROUND EXPOSURE ENDS 26 (HOUR) 27 TIMELIMIT = 7584 %SIMULATION TIME LIMIT (HOUR) 28 BW_T0 = 125 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 29 (G) 30 31 %EXPOSURE DOSE SCENARIOS (UG/KG) 32 %MSTOT = 0.01 % EXPOSURE DOSE IN UG/KG 33 %MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 34 MSTOT = 1 % EXPOSURE DOSE IN UG/KG 35 36
C.2.3.2.2. Chu et al. (2007). 37 output @clear 38 prepare @clear 39 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 40 41 % Chu et al. 2007 42 %protocol: oral exposure daily for 28 days 43

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-47 DRAFT

— DO NOT CITE OR QUOTE %dose levels: 0.0025, 0.025, 0.250, 1.0 ug/kg every day for 28 days 1 % dose levels = 2.5, 25, 250, 1000 ng/kg every day for 28 days 2 MAXT = 0.01 3 CINT = 0.1 4 EXP_TIME_ON = 0. %delay before begin exposure (HOUR ) 5 weeks after start of 5 experiment (age = 12 weeks) 6 EXP_TIME_OFF = 672. %T IME EXPOSURE STOP (HOUR); 30 doses, 1 every two 7 weeks 8 DAY_CYCLE = 24. % once every two weeks 9 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 10 BCK_TIME_OFF = 0. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 11 TIMELIMIT = 672. %SIMULATION LIMIT TIME (HOUR) 12 BW_T0 = 200. % Body weight at the beginni ng of the simulation (g); 13 corresponds to 12 week old female 14 15 %EXPOSURE DOSE SCENARIOS (UG/KG) 16 %MSTOT = 0.0025 % ORAL EXPOSURE DOSE (UG/KG) 17 %MSTOT = 0.025 % ORAL EXPOSURE DOSE (UG/KG) 18 %MSTOT = 0.250 % ORAL EXPOSURE DOSE (UG/KG) 19 MSTOT = 1.0 % ORAL EXPOSURE DOSE (UG/KG) 20 21
C.2.3.2.3. Crofton et al. (2005). 22 output @clear 23 prepare @clear 24 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 25 26 % Crofton et al. 2005 27 %protocol: oral exposure daily for 4 days 28 %dose levels: 0.0001, 0.003, 0.01, 0.03, 0.1, 0.3, 1, 3, and 10 ug/kg every day for four days 29 %dose levels: 0.1, 3, 10, 30, 100, 300, 1000, 3000, and 10000 ng/kg every day for four days 30 31 MAXT = 0.01 32 CINT = 0.1 33 EXP_TIME_ON = 0. %delay before begin exposure (HOUR ) 5 weeks after start of 34 experiment (age = 12 weeks) 35 EXP_TIME_OFF = 96. %T IME EXPOSURE STOP (HOUR); 30 doses, 1 every two 36 weeks 37 DAY_CYCLE = 24. % once every two weeks 38 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 39 BCK_TIME_OFF = 0. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 40 TIMELIMIT = 96. %SIMULATION LIMIT TIME (HOUR) 41 BW_T0 = 250 % B ody weight at the beginning of the simulation (g); corresponds 42 to 12 week old female 43 44 %EXPOSURE DOSE SCENARIOS (UG/KG) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-48 DRAFT

— DO NOT CITE OR QUOTE MSTOT = 0.0001 % ORAL EXPOSURE DOSE (UG/KG) 1 %MSTOT = 0.003 % ORAL EXPOSURE DOSE (UG/KG) 2 %MSTOT = 0.01 % ORAL EXPOSURE DOSE (UG/KG) 3 %MSTOT = 0.03 % ORAL EXPOSURE DOSE (UG/KG) 4 %MSTOT = 0.1 % ORAL EXPOSURE DOSE (UG/KG) 5 %MSTOT = 0.3 % ORAL EXPOSURE DOSE (UG/KG) 6 %MSTOT = 1. % ORAL EXPOSURE DOSE (UG/KG) 7 %MSTOT = 3. % ORAL EXPOSURE DOSE (UG/KG) 8 MSTOT = 10. % ORAL EXPOSURE DOSE (UG/KG) 9 10
C.2.3.2.4. Fattore et al. (2000). 11 output @clear 12 prepare @clear 13 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 14 15 % Fattore et al. 2000 16 %built and check in August 7 2009 17 %protocol: oral exposure in di et for 13 weeks; SD rats 18 %dose levels: 0.02, 0.1, 0.2, 2 ug/kg 7 days/week for 13 weeks 19 %dose levels equivalent to: 20, 100, 200, 2000 ng/kg 7 days/week for 13 weeks 20 21 MAXT = 0.01 22 CINT = 0.1 23 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 24 EXP_TIME_OFF = 2184 %TIM E AT WHICH EXPOSURE ENDS (HOUR) 25 DAY_CYCLE = 24 26 BCK_TIME_ON = 0. %T IME AT WHICH BACKGROUND EXPOSURE BEGINS 27 (HOUR) 28 BCK_TIME_OFF = 0. %TIM E AT WHICH BACKGROUND EXPOSURE ENDS 29 (HOUR) 30 TIMELIMIT = 2184 %SIMULATION TIME LIMIT (HOUR) 31 BW_T0 = 150 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 32 (G) 33 34 %EXPOSURE DOSE SCENARIOS (UG/KG) 35 %MSTOT = 0.02 % EXPOSURE DOSE IN UG/KG 36 %MSTOT = 0.1 % EXPO SURE DOSE IN UG/KG 37 %MSTOT = 0.2 % EXPO SURE DOSE IN UG/KG 38 MSTOT = 2 % EXPOSURE DOSE IN UG/KG 39 40
C.2.3.2.5. Hassoun et al. (2000). 41 output @clear 42 prepare @clear 43 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-49 DRAFT

— DO NOT CITE OR QUOTE 1 % Hassoun et al. 2000 2 %protocol: oral exposure for 13 weeks; SD rats 3 %dose levels: 0.003, 0.010, 0.022, 0.046 0.1 ug/kg 5 days/weeks for 13 weeks 4 %dose levels equivalent to: 3, 10, 22, 46 100 ng/kg 5 days/weeks for 13 weeks 5 %dose levels equivalent to: 2.14, 7.14, 15.7, 32.9, 71.4 ng/kg 7 days/weeks for 13 weeks 6 7 MAXT = 0.01 8 CINT = 0.1 9 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 10 EXP_TIME_OFF = 2184. %TIME EXPOSURE STOP (HOUR) 11 DAY_CYCLE = 24. 12 WEEK_PERIOD = 168. 13 WEEK_FINISH = 119. 14 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 15 BCK_TIME_OFF = 0. %TIM E OF BACKGROUND EXPOSURE STOP (HOUR) 16 TIMELIMIT = 2184. %SIMULATION LIMIT TIME (HOUR) 17 BW_T0 = 215. % Body weight at the beginning of the simulation (g) 18 19 %EXPOSURE DOSE SCENARIOS (UG/KG) 20 %MSTOT = 0.003 % exposure dose ug/kg 21 %MSTOT = 0.010 % exposure dose ug/kg 22 %MSTOT = 0.022 % exposure dose ug/kg 23 %MSTOT = 0.046 % exposure dose ug/kg 24 MSTOT = 0.1 % exposure dose ug/kg 25 26
C.2.3.2.6. Kitchin and Woods (1979). 27 output @clear 28 prepare @clear 29 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 30 31 % Kitchin and Woods 1979 32 %dose levels: 0.0006, 0.002, 0.004, 0.020, 0.060, 0.200, 0.600, 2.000, 5.000, 20.000 ug/kg 33 single oral gavage 34 % dose levels = 0.6, 2, 4, 20, 60, 200, 600, 2000, 5000, 20000 ng/kg single oral gavage with 35 estimated 0.2 ng/kg/day background dose 36 MAXT = 0.01 37 CINT = 0.1 38 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 39 EXP_TIME_OFF = 23. %TIME EXPOSURE STOP (HOUR) 40 DAY_CYCLE = 24. % once every two weeks 41 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 42 BCK_TIME_OFF = 72. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 43 TIMELIMIT = 72. %SIMULATION LIMIT TIME (HOUR) 44 BW_T0 = 225. % Body weight at the begi nning of the simulation (g) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-50 DRAFT

— DO NOT CITE OR QUOTE 1 %EXPOSURE DOSE SCENARIOS (UG/KG) 2 %MSTOT = 0.0006 % ORAL EXPOSURE DOSE (UG/KG) 3 %MSTOT = 0.002 % ORAL EXPOSURE DOSE (UG/KG) 4 %MSTOT = 0.004 % ORAL EXPOSURE DOSE (UG/KG) 5 %MSTOT = 0.020 % ORAL EXPOSURE DOSE (UG/KG) 6 %MSTOT = 0.060 % ORAL EXPOSURE DOSE (UG/KG) 7 %MSTOT = 0.200 % ORAL EXPOSURE DOSE (UG/KG) 8 %MSTOT = 0.600 % ORAL EXPOSURE DOSE (UG/KG) 9 %MSTOT = 2.000 % ORAL EXPOSURE DOSE (UG/KG) 10 %MSTOT = 5.000 % ORAL EXPOSURE DOSE (UG/KG) 11 MSTOT = 20.000 % ORAL EXPOSURE DOSE (UG/KG) 12 13
C.2.3.2.7. Kociba et al. (1976) (13 weeks). 14 output @clear 15 prepare @clear 16 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 17 18 % Kociba et al, 1976. 19 %built and check in August 7 2009 20 %protocol: 5 days/week exposur e for 13 weeks; SD rats 21 %dose levels: 0.001, 0.01, 0.1, 1 ug/kg 5 days/week for 13 weeks 22 %dose levels: 1, 10, 100, 1000 ng/kg 5 days/week for 13 weeks 23 %dose levels equivalent to: 0.714, 7.14, 71.4, 714 ng/kg/d (adj) 7 days/week for 13 weeks 24 25 26 MAXT = 0.01 27 CINT = 0.1 28 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 29 EXP_TIME_OFF = 2184 %T IME AT WHICH EXPOSURE ENDS (HOUR) 30 WEEK_PERIOD = 168 31 WEEK_FINISH = 119 32 DAY_CYCLE = 24 33 BCK_TIME_ON = 0. % TI ME AT WHICH BACKGROUND EXPOSURE BEGINS 34 (HOUR) 35 BCK_TIME_OFF = 0. %T IME AT WHICH BACKGROUND EXPOSURE ENDS 36 (HOUR) 37 TIMELIMIT = 4368 %SIMULATION TIME LIMIT (HOUR) 38 BW_T0 = 180 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 39 (G) 40 41 42 %EXPOSURE DOSE SCENARIOS (UG/KG) 43 %MSTOT = 0.001 % EXPOSURE DOSE IN UG/KG 44 %MSTOT = 0.01 % EXPO SURE DOSE IN UG/KG 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-51 DRAFT

— DO NOT CITE OR QUOTE %MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 1 MSTOT = 1 % EXPOSURE DOSE IN UG/KG 2 3
C.2.3.2.8. Kociba et al. (1978) (f emale) (104 weeks). 4 output @clear 5 prepare @clear 6 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 7 8 % Kociba et al, 1978. 9 %built and check in August 7 2009 10 %protocol: daily dietary exposure for 104 weeks; SD rats 11 %dose levels: 0.001, 0.01, 0.1 ug/kg 7 days/week for 104 weeks 12 %dose levels: 1, 10, 100 ng/kg 7 days/week for 104 weeks 13 14 MAXT = 0.01 15 CINT = 0.1 16 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 17 EXP_TIME_OFF = 17472 %TIME AT WHICH EX POSURE ENDS (HOUR) 18 DAY_CYCLE = 24 19 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 20 (HOUR) 21 BCK_TIME_OFF = 0. %TIME AT WHICH BACKGROUND EXPOSURE ENDS 22 (HOUR) 23 TIMELIMIT = 17472 %SIMULATION TIME LIMIT (HOUR) 24 BW_T0 = 180 % BODY WEIGHT AT THE BEGINNING OF THE 25 SIMULATION (G) 26 27 %EXPOSURE DOSE SCENARIOS (UG/KG) 28 %MSTOT = 0.001 % EXPOSURE DOSE IN UG/KG 29 %MSTOT = 0.01 % EXPOSURE DOSE IN UG/KG 30 MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 31 32
C.2.3.2.9. Kociba et al. (1978) (male) (104 weeks). 33 output @clear 34 prepare @clear 35 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 36 37 % Kociba et al, 1978. 38 %built and check in August 7 2009 39 %protocol: daily dietary exposure for 104 weeks; SD rats 40 %dose levels: 0.001, 0.01, 0.1 ug/kg 7 days/week for 104 weeks 41 %dose levels: 1, 10, 100 ng/kg 7 days/week for 104 weeks 42 43 MAXT = 0.01 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-52 DRAFT

— DO NOT CITE OR QUOTE CINT = 0.1 1 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 2 EXP_TIME_OFF = 17472 %TIME AT WHICH EX POSURE ENDS (HOUR) 3 DAY_CYCLE = 24 4 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 5 (HOUR) 6 BCK_TIME_OFF = 0. %TIME AT WHICH BACKGROUND EXPOSURE ENDS 7 (HOUR) 8 TIMELIMIT = 17472 %SIMULATION TIME LIMIT (HOUR) 9 BW_T0 = 250 % BODY WEIGHT AT THE BEGINNING OF THE 10 SIMULATION (G) 11 12 %EXPOSURE DOSE SCENARIOS (UG/KG) 13 %MSTOT = 0.001 % EXPOSURE DOSE IN UG/KG 14 %MSTOT = 0.01 % EXPOSURE DOSE IN UG/KG 15 MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 16 17
C.2.3.2.10. Latchoumycandane and Mathur. (2002). 18 output @clear 19 prepare @clear 20 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 21 22 % Latchoumycandane and Mathur, 2002. 23 %built and check in August 7 2009 24 %protocol: 1 time per day for 45 days oral gavage 25 %dose levels: 0.001, 0.01, 0.1 ug/kg daily for 45 days 26 %dose levels: 1, 10, 100 ng/kg daily for 45 days 27 28 MAXT = 0.01 29 CINT = 0.1 30 EXP_TIME_ON = 0. % TIME AT WHICH EXPOSURE BEGINS (HOUR) 31 EXP_TIME_OFF = 1080 % TIME AT WHICH EX POSURE ENDS(HOUR) 32 DAY_CYCLE = 24 33 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 34 (HOUR) 35 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 36 (HOUR) 37 TIMELIMIT = 1104 % SIMULATION TIME LIMIT (HOUR) 38 BW_T0 = 200 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 39 (G) 40 41 %EXPOSURE DOSE SCENARIOS (UG/KG) 42 %MSTOT = 0.001 % EXPOSURE DOSE IN UG/KG 43 %MSTOT = 0.01 % EXPOSURE DOSE IN UG/KG 44 MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-53 DRAFT

— DO NOT CITE OR QUOTE C.2.3.2.11. Li et al. (1997). 1 output @clear 2 prepare @clear 3 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 4 5 % Li et al 1997 6 % created 1/10/10 7 % Non-gestational rat model 8 % dose levels: 3, 10, 30, 100, 300, 1000, 3000, 10000, 30000 nkd one dose via gavage, sacrificed 9 24 hrs later 10 11 MAXT = 0.1 12 CINT = 0.1 13 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 14 EXP_TIME_OFF = 24. %TIME EXPOSURE STOP (HOUR) 15 DAY_CYCLE = 24. 16 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 17 BCK_TIME_OFF = 0. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 18 TIMELIMIT = 24. %SIMULATION LIMIT TIME (HOUR) 19 BW_T0 = 56.5 % Body weight at the begi nning of the simulation (g) 20 21 %EXPOSURE DOSE SCENARIOS (UG/KG) 22 MSTOT = 0.003 % ORAL EXPOSURE DOSE (UG/KG) 23 %MSTOT = 0.01 % ORAL EXPOSURE DOSE (UG/KG) 24 %MSTOT = 0.03 % ORAL EXPOSURE DOSE (UG/KG) 25 %MSTOT = 0.1 % ORAL EXPOSURE DOSE (UG/KG) 26 %MSTOT = 0.3 % ORAL EXPOSURE DOSE (UG/KG) 27 %MSTOT = 1. % ORAL EXPOSURE DOSE (UG/KG) 28 %MSTOT = 3. % ORAL EXPOSURE DOSE (UG/KG) 29 %MSTOT = 10. % ORAL EXPOSURE DOSE (UG/KG) 30 %MSTOT = 30. % ORAL EXPOSURE DOSE (UG/KG) 31 32
C.2.3.2.12. Murray et al. (1979). 33 output @clear 34 prepare @clear 35 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 36 37 % Murray et al 1979 38 %built and check in August 7 2009 39 %protocol: dietary exposure for 3 generations (assume 120 day exposure for each) 40 %dose levels: 0.001 0.01, 0.1 ug/kg/d 41 %dose levels: 1, 10, 100 ng/kg/d 42 43 MAXT = 0.01 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-54 DRAFT

— DO NOT CITE OR QUOTE CINT = 0.1 1 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 2 EXP_TIME_OFF = 2880 %TIME AT WHICH EX POSURE ENDS (HOUR); 3 CORRESPONDS TO 120 DAYS OF EXPOSURE 4 DAY_CYCLE = 24. 5 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 6 (HOUR) 7 BCK_TIME_OFF = 0. %TIME AT WHICH BACKGROUND EXPOSURE ENDS 8 (HOUR) 9 TIMELIMIT = 2880 %SIMULATION TIME LIMIT (HOUR) 10 BW_T0 = 4.5 % BODY WEIGHT AT THE BEGINNING OF THE 11 SIMULATION (G) 12 13 %EXPOSURE DOSE SCENARIOS (UG/KG) 14 %MSTOT = 0.001 % ORAL EXPOSURE DOSE IN UG/KG 15 %MSTOT = 0.01 % ORAL EXPOSURE DOSE IN UG/KG 16 MSTOT = 0.1 % ORAL EXPOSURE DOSE IN UG/KG 17 18
C.2.3.2.13. NTP (1982) (female) (chronic). 19 output @clear 20 prepare @clear 21 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 22 23 % NTP 1982 24 %built and check in August 7 2009 25 %protocol: twice weekly gavage for 104 weeks + 3 week observation period 26 %dose levels: 0.005, 0.025, 0.25 ug/kg biweekly for 104 weeks + 3 week observation period 27 %dose levels: 5, 25, 250 ng/kg biweekly for 104 weeks + 3 week observation period 28 %dose levels equivalent to: 1.43, 7.14, 71.4 ng/kg/d (adj) 29 30 MAXT = 0.01 31 CINT = 0.1 32 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 33 EXP_TIME_OFF = 17472 %TIME AT WHICH EXPO SURE ENDS (HOUR) 34 DAY_CYCLE = 84 35 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 36 (HOUR) 37 BCK_TIME_OFF = 0. %TIME AT WHICH BACKGROUND EXPOSURE ENDS 38 (HOUR) 39 TIMELIMIT = 17976 %SIMULATION TIME LIMIT (HOUR) 40 BW_T0 = 250 % BODY WEIGHT AT THE BEGINNING OF THE 41 SIMULATION (G) 42 43 %EXPOSURE DOSE SCENARIOS (UG/KG) 44 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-55 DRAFT

— DO NOT CITE OR QUOTE 1%MSTOT = 0.005 % EXPOSURE DOSE IN UG/KG 2 %MSTOT = 0.025 % EXPOSURE DOSE IN UG/KG 3 MSTOT = 0.25 % EXPOSURE DOSE IN UG/KG 4 5
C.2.3.2.14. NTP (1982) (male) (chronic). 6 output @clear 7 prepare @clear 8 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 9 10 % NTP 1982 11 %built and check in August 7 2009 12 %protocol: twice weekly gavage for 104 weeks + 3 week observation period 13 %dose levels: 0.005, 0.025, 0.25 ug/kg biweekly for 104 weeks + 3 week observation period 14 %dose levels: 5, 25, 250 ng/kg biweekly for 104 weeks + 3 week observation period 15 %dose levels equivalent to: 1.43, 7.14, 71.4 ng/kg/d (adj) 16 17 MAXT = 0.01 18 CINT = 0.1 19 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 20 EXP_TIME_OFF = 17472 %TIME AT WHICH EXPO SURE ENDS (HOUR) 21 DAY_CYCLE = 84 22 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 23 (HOUR) 24 BCK_TIME_OFF = 0. %TIME AT WHICH BACKGROUND EXPOSURE ENDS 25 (HOUR) 26 TIMELIMIT = 17976 %SIMULATION TIME LIMIT (HOUR) 27 BW_T0 = 350 % BODY WEIGHT AT THE BEGINNING OF THE 28 SIMULATION (G) 29 30 %EXPOSURE DOSE SCENARIOS (UG/KG) 31 32 33%MSTOT = 0.005 % EXPOSURE DOSE IN UG/KG 34 %MSTOT = 0.025 % EXPOSURE DOSE IN UG/KG 35 MSTOT = 0.25 % EXPOSURE DOSE IN UG/KG 36 37
C.2.3.2.15. NTP (2006) 31 weeks. 38 output @clear 39 prepare @clear 40 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 41 42 % NTP 2006 43 %built and check in August 7 2009 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-56 DRAFT

— DO NOT CITE OR QUOTE %protocol: oral exposure for 31 weeks; SD rats 1 %Rat_Dioxin_3C June09_2clean.csl 2 %RAT_NON_GEST_ICF_F083109.CSL (now 09-11-09) 3 %dose levels: 0.003, 0.010, 0.022, 0.046, 0.1 ug/kg 5 days/week for 31 weeks 4 %dose levels equivalent to: 3, 10, 22, 46, 100 ng/kg 5 days/week for 31 weeks 5 %dose levels equivalent to: 2.14, 7.14, 15.7, 32.9, 71.4 ng/kg 7 days/week for 31 weeks 6 7 MAXT = 0.01 8 CINT = 0.1 9 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 10 EXP_TIME_OFF = 17640 %TIME EXPOSURE STOP (HOUR) 11 DAY_CYCLE = 24 12 WEEK_PERIOD = 168 13 WEEK_FINISH = 119 14 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 15 BCK_TIME_OFF = 0. %TIM E OF BACKGROUND EXPOSURE STOP (HOUR) 16 TIMELIMIT = 5208 %SIMULATION LIMIT TIME (HOUR) 17 BW_T0 = 215 % Body weight at the beginning of the simulation (g) 18 19 %EXPOSURE DOSE SCENARIOS (UG/KG) 20 %MSTOT = 0.003 % exposure dose ug/kg 21 %MSTOT = 0.010 % exposure dose ug/kg 22 %MSTOT = 0.022 % exposure dose ug/kg 23 %MSTOT = 0.046 % exposure dose ug/kg 24 MSTOT = 0.1 % exposure dose ug/kg 25 26
C.2.3.2.16. NTP (2006) 53 weeks. 27 output @clear 28 prepare @clear 29 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 30 31 % NTP 2006 32 %built and check in August 7 2009 33 %protocol: oral exposure for 53 weeks; SD rats 34 %Rat_Dioxin_3C June09_2clean.csl 35 %RAT_NON_GEST_ICF_F083109.CSL (now 09-11-09) 36 %dose levels: 0.003, 0.010, 0.022, 0.046, 0.1 ug/kg 5 days/week for 53 weeks 37 %dose levels equivalent to: 3, 10, 22, 46, 100 ng/kg 5 days/week for 53 weeks 38 %dose levels equivalent to: 2.14, 7.14, 15.7, 32.9, 71.4 ng/kg 7 days/week for 53 weeks 39 40 MAXT = 0.01 41 CINT = 0.1 42 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 43 EXP_TIME_OFF = 17640 %TIME EXPOSURE STOP (HOUR) 44 DAY_CYCLE = 24 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-57 DRAFT

— DO NOT CITE OR QUOTE WEEK_PERIOD = 168 1 WEEK_FINISH = 119 2 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 3 BCK_TIME_OFF = 0. %TIM E OF BACKGROUND EXPOSURE STOP (HOUR) 4 TIMELIMIT = 8904 %SIMULATION LIMIT TIME (HOUR) 5 BW_T0 = 215 % Body weight at the beginning of the simulation (g) 6 7 %EXPOSURE DOSE SCENARIOS (UG/KG) 8 %MSTOT = 0.003 % exposure dose ug/kg 9 %MSTOT = 0.010 % exposure dose ug/kg 10 %MSTOT = 0.022 % exposure dose ug/kg 11 %MSTOT = 0.046 % exposure dose ug/kg 12 MSTOT = 0.1 % exposure dose ug/kg 13 14
C.2.3.2.17. NTP (2006) 2 year. 15 output @clear 16 prepare @clear 17 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 18 19 % NTP 2006 20 %built and check in August 7 2009 21 %protocol: oral exposure for 105 weeks; SD rats 22 %dose levels: 0.003, 0.010, 0.022, 0.046, 0.1 ug/kg 5 days/week for 105 weeks 23 %dose levels equivalent to: 3, 10, 22, 46, 100 ng/kg 5 days/week for 105 weeks 24 %dose levels equivalent to: 2.14, 7.14, 15.7, 32.9, 71.4 ng/kg 7 days/week for 105 weeks 25 26 MAXT = 0.01 27 CINT = 0.1 28 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 29 EXP_TIME_OFF = 17640 %T IME AT WHICH EXPOSURE ENDS (HOUR) 30 DAY_CYCLE = 24 31 WEEK_PERIOD = 168 32 WEEK_FINISH = 119 33 BCK_TIME_ON = 0. %T IME AT WHICH BACKGROUND EXPOSURE BEGINS 34 (HOUR) 35 BCK_TIME_OFF = 0. %T IME AT WHICH BACKGROUND EXPOSURE ENDS 36 (HOUR) 37 TIMELIMIT = 17640 %SIMULATION TIME LIMIT (HOUR) 38 BW_T0 = 215 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 39 (G) 40 41 %EXPOSURE DOSE SCENARIOS (UG/KG) 42 %MSTOT = 0.003 % EXPOSURE DOSE IN UG/KG 43 %MSTOT = 0.010 % EXPOSURE DOSE IN UG/KG 44 %MSTOT = 0.022 % EXPOSURE DOSE IN UG/KG 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-58 DRAFT

— DO NOT CITE OR QUOTE %MSTOT = 0.046 % EXPOSURE DOSE IN UG/KG 1 MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 2 3
C.2.3.2.18. Sewall et al. (1995). 4 output @clear 5 prepare @clear 6 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 7 8 % Sewall et al. 1995 9 %Rat_Dioxin_3C June09_2clean.csl 10 %RAT_NON_GEST_ICF_F083109.CSL (now 09-11-09) 11 %protocol: gavage every 2 weeks for 30 weeks 12 %dose levels: 0.049, 0.1498, 0.49, and 1.75 ug/kg every two weeks 13 %dose levels: 3.5, 10.7, 35, and 125 ng/kg/d or 49, 149.8, 490, and 1750 ng/kg every two weeks 14 15 MAXT = 0.01 16 CINT = 0.1 17 EXP_TIME_ON = 0. %delay before begin exposure (HOUR ) 5 weeks after start of 18 experiment (age = 12 weeks) 19 EXP_TIME_OFF = 5030 %TIME EXPOSURE STOP (HOUR); 30 doses, 1 every two 20 weeks 21 DAY_CYCLE = 336. % once every two weeks 22 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 23 BCK_TIME_OFF = 0. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 24 TIMELIMIT = 5040 %SIMULATION LIMIT TIME (HOUR) 25 BW_T0 = 250 % B ody weight at the beginning of the simulation (g); corresponds 26 to 12 week old female 27 28 %EXPOSURE DOSE SCENARIOS (UG/KG) 29 MSTOT = 0.049 % ORAL EXPOSURE DOSE (UG/KG) 30 %MSTOT = 0.1498 % ORAL EXPOSURE DOSE (UG/KG) 31 %MSTOT = 0.49 % ORAL EXPOSURE DOSE (UG/KG) 32 %MSTOT = 1.75 % ORAL EXPOSURE DOSE (UG/KG) 33 34
C.2.3.2.19. Shi et al. (2007), adult portion. 35 output @clear 36 prepare @clear 37 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 38 39 % Shi et al 2007 40 %built and check in August 7 2009 41 %protocol: gavage once per week for 322 days 42 %dose levels: 0.001, 0.005, 0.05 and 0.2 ug TCDD: kg body weight by gavage once per week 43 %dose levels: 1, 5, 50 and 200 ng/kg ng TCDD:kg body weight by gavage once per week 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-59 DRAFT

— DO NOT CITE OR QUOTE % dose equivalent adjusted 0.143, 0.714, 7.14 and 28.6 ng/kg/d 1 2 MAXT = 0.0001 3 CINT = 0.1 4 EXP_TIME_ON = 504. % TIME AT WHICH EX POSURE BEGINS (HOUR) 5 EXP_TIME_OFF = 7728 %TIME AT WHICH EX POSURE ENDS (HOUR); 6 CORRESPONDS TO 322 DAYS OF EXPOSURE 7 DAY_CYCLE = 168. 8 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE 9 BEGINS (HOUR) 10 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 11 (HOUR) 12 TIMELIMIT = 7728 %SIMULATION TIME LIMIT (HOUR) 13 BW_T0 = 4.5 % BODY WEIGHT AT THE BEGINNING OF THE 14 SIMULATION (G) 15 16 %EXPOSURE DOSE SCENARIOS (UG/KG) 17 %MSTOT = 0.001 % ORAL EXPOSURE DOSE IN UG/KG 18 %MSTOT = 0.005 % ORAL EXPOSURE DOSE IN UG/KG 19 %MSTOT = 0.05 % ORAL EXPOSURE DOSE IN UG/KG 20 MSTOT = 0.2 % ORAL EXPOSU RE DOSE IN UG/KG 21 22
C.2.3.2.20. Van Birgelen et al. (1995). 23 output @clear 24 prepare @clear 25 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 26 27 % Van Birgelen et al. (1995) 28 %protocol: daily dietary exposure for 13 weeks 29 %dose levels: 0.0135, 0.0264, 0.0469, 0.320, 1.024 ug/kg every day for 13 weeks 30 % dose levels = 13.5, 26.4, 46.9, 320, 1024 ng/kg every day for 13 weeks 31 MAXT = 0.01 32 CINT = 0.1 33 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 34 EXP_TIME_OFF = 2184. %TIME EXPOSURE STOP (HOUR) 35 DAY_CYCLE = 24. % once every two weeks 36 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 37 BCK_TIME_OFF = 0. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 38 TIMELIMIT = 2184. %SIMULATION LIMIT TIME (HOUR) 39 BW_T0 = 150. % Body weight at the begi nning of the simulation (g) 40 41 %EXPOSURE DOSE SCENARIOS (UG/KG) 42 %MSTOT = 0.0135 % ORAL EXPOSURE DOSE (UG/KG) 43 %MSTOT = 0.0264 % ORAL EXPOSURE DOSE (UG/KG) 44 %MSTOT = 0.0469 % ORAL EXPOSURE DOSE (UG/KG) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-60 DRAFT

— DO NOT CITE OR QUOTE %MSTOT = 0.320 % ORAL EXPOSURE DOSE (UG/KG) 1 MSTOT = 1.024 % ORAL EXPOSURE DOSE (UG/KG) 2 3
C.2.3.2.21. Vanden Heuvel et al. (1994). 4 output @clear 5 prepare @clear 6 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 7 8 % Vanden Heuvel et al., 1994. 9 %built and check in August 7 2009 10 %protocol: single gavage 11 %Rat_Dioxin_3C June09_2clean.csl 12 %RAT_NON_GEST_ICF_F083109.CSL (now 09-11-09) 13 %dose levels: 0.00005, 0.0001, 0.001, 0.010, 0.1, 1, 10 ug/ kg/d + 4 days post treatment 14 %dose levels equivalent to: 0.05, 0.1, 1, 10, 100, 1000, 10000 ng/kg/d + 4 days post treatment 15 16 MAXT = 0.01 17 CINT = 0.01 18 EXP_TIME_ON = 0. %delay before begin exposure (HOUR) 19 EXP_TIME_OFF = 120 %TIME EXPOSURE STOP (HOUR) 20 DAY_CYCLE = 120 21 BCK_TIME_ON = 0. %DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 22 BCK_TIME_OFF = 0. %TIME OF BACKGROUND EXPOSURE STOP (HOUR) 23 TIMELIMIT = 120 %SIMULATION LIMIT TIME (HOUR) 24 BW_T0 = 250 % Body weight at the begi nning of the simulation (g) 25 26 %EXPOSURE DOSE SCENARIOS (UG/KG) 27 28%MSTOT = 0.00005 % exposure dose ug/kg 29 %MSTOT = 0.0001 % exposure dose ug/kg 30 %MSTOT = 0.001 % exposure dose ug/kg 31 %MSTOT = 0.01 % exposure dose ug/kg 32 %MSTOT = 0.1 % exposure dose ug/kg 33 MSTOT = 1 % exposure dose ug/kg 34 %MSTOT = 10 % exposure dose ug/kg 35 36
C.2.4. Rat Gestational Model 37 C.2.4.1. Model Code 38
PROGRAM : 'Three Compartment PBPK Mode l for TCDD in Rat (Gestation)' 39 ! Parameters were change May 16, 2002 40 ! Come from {8MAI_CHR_PRE-EXP_GD} 41 ! Come from {12_Mouse_GD}file 42 !******************************************** 43

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-61 DRAFT

— DO NOT CITE OR QUOTE !{{IMPORTANT-IMPORTANT-IMPORTANT-IMPORTANT}} 1 ! REDUCTION OF MOTHER AND FETUS COMPARTMENT 2 ! 2M_R_TCDD_JULY2002 ////(JULY 18,2002)//// 3 !TCDD_RED_4Species_2003_4 ////(APR 8 ,2003)//// 4 !TCDD_RED_4Species_2003_9 ////(APR 17 ,2003)//// 5 !TCDD_RED_4Species_2003_12 ////(APR 17 ,2003)//// 6 !***************************************************** 7 !APRIL 18 2003 8 !TCDD_4C_4SP_2003 ////(APR 18 ,2003)//// 9 ! was ''Gest 4 species 1.csl'' but update July 2009 10 11 !DevTCDD4Species_ICF_a fterKKfix_v3_ratgest.csl 12 !RAT_GESTATIONAL_ICF_F083109.csl 13 !RAT_GESTATIONAL_ICF_F100609.csl 14 !***************************************************** 15 16!Legend/Legend/Legend/Legend/ Legend/Legend/Legend/Legend/ 17 !Legend for this PBPK model 18 !Mating: control the tenure of exchange between fetus and 19 !Mother and also cont rol imitated tissue growth 20 !Control: WTFE, WFO, WPLA0, QPLAF,WT0 21 !(for rat, mouse, human, and monkey) 22 !Control transfer from mother to fe tus or fetus to mother by TRANSTIME_ON 23 !SWITCH_trans = 0 NO TRANSFER 24 !SWITCH_trans = 1 TRANSFER OCCURS 25 !Gest_off = 1 26 !Gest_on= 0.0 27 ! These switches are also controlled by mating parameters 28 29 INITIAL ! 30 31!SIMULATION PARAMETERS ==== 32 CONSTANT PARA_ZERO = 1E-30 33 CONSTANT EXP_TIME_ON = 0.0 ! TIME AT WHICH EXPOSURE BEGINS 34 (HOURS) 35 CONSTANT EXP_TIME_OFF = 530 ! TIME AT WHICH EXPO SURE ENDS (HOURS) 36 CONSTANT DAY_CYCLE = 24.0 ! NUMBER OF HOURS BETWEEN DOSES 37 (HOURS) 38 CONSTANT BCK_TIME_ON = 0.0 ! TIME AT WHICH BACKGROUND EXPOSURE 39 BEGINS (HOURS) 40 CONSTANT BCK_TIME_OFF = 0.0 ! TIME AT WHICH BACKGROUND EXPOSURE 41 ENDS (HOURS) 42 CONSTANT TRANSTIME_ON = 144.0 !CONTROL TRANSFER FROM MOTHER TO 43 FETUS AT GESTATIONAL DAY 6 44 45!UNIT CONVER SION 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-62 DRAFT

— DO NOT CITE OR QUOTE CONSTANT MW=322 ! MOLECUL AR WEIGHT (NG/NMOL) 1 CONSTANT SERBLO = 0.55 2 CONSTANT UNITCORR = 1000 3 4 5!INTRAVENOUS SEQUENCE 6 constant IV_LACK = 0.0 7 constant IV_PERIOD = 0.0 8 9!PREGNANCY PARAMETER ==== 10 CONSTANT MATTING = 0.0 !BEGINNING OF MATING (HOUR) 11 CONSTANT N_FETUS = 10.0 !NUMBER OF FETUS PRESENT 12 13!CONSTANT EXPOSURE CONTROL =========== 14 !ACUTE, SUBCHRONIC , CHRONIC EXPOSURE ===== 15 !OR BACKGROUND EXPOSURE (IN THIS CASE 3 TIMES A DAY)=== 16 CONSTANT MSTOTBCKGR = 0.0 ! ORAL BACKGROUND EXPOSURE DOSE 17 (UG/KG) 18 CONSTANT MSTOT = 0.0 ! ORAL EXPOSURE DOSE (UG/KG) 19 20!ORAL ABSORPTION 21 MSTOT_NM = MSTOT/MW ! CONVERTS THE DOSE TO NMOL/G 22 23 !INTRAVENOUS ABSORPTION 24 CONSTANT DOSEIV = 0.0 ! INJECTED DOSE (UG/KG) 25 DOSEIV_NM = DOSEIV/MW ! CONVERTS THE INJECTED DOSE TO NMOL/G 26 CONSTANT DOSEIVLATE = 0.0 ! INJECTED DOSE LATE (UG/KG) 27 DOSEIVNMlate = DOSEIVLATE/MW !AMOUNT IN NMOL/G 28 29!INITIAL GUESS OF THE FREE CONCENTRATION IN THE LIGAND 30 (COMPARTMENT INDICATED BELOW)==== 31 CONSTANT CFLLI0 = 0.0 !LIVER (NMOL/ML) 32 CONSTANT CFLPLA0 = 0.0 !PLACENTA (NMOL/ML) 33 34!BINDING CAPACITY (AhR) FOR NON LINEAR BINDING (COMPARTMENT 35 INDICATED BELOW) (NMOL/ML) === 36 CONSTANT LIBMAX = 3.5E-4 ! LIVER (NMOL/ML), WANG ET AL. 1997 37 CONSTANT PLABMAX = 2.0E-4 !TEMPORARY PARAMETER 38 39! PROTEIN AFFINITY CONSTANTS (1A2 OR Ah R, COMPARTMENT INDICATED 40 BELOW) (NMOL/ML)=== 41 CONSTANT KDLI = 1.0E-4 !LIVER (AhR) (NMOL/ML), WANG ET AL. 1997 42 CONSTANT KDLI2 = 4.0E-2 !LIVER (1A2) (NMOL/ML), EMOND ET AL. 2004 43 CONSTANT KDPLA = 1.0E-4 !TEMPORARY PARAM ETER; ASSUME IDENTICAL 44 TO KDLI (AhR) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-63 DRAFT

— DO NOT CITE OR QUOTE !EXCRETION AND ABSORPTION CONSTANT 1 CONSTANT KST = 0.36 ! GASTRIC RATE CONSTANT (HR-1), WANG ET AL. 2 1997 3 CONSTANT KABS = 0.48 !INTESTINAL ABSORPTION CONSTANT (HR-1) ), 4 WANG ET AL. 1997 5 6! ELIMINATION CONSTANTS 7 CONSTANT CLURI = 0.01 ! URINARY CLEARANCE (ML/HR), EMOND ET AL. 8 2004 9 10!INTERSPECIES ELIMINATION VARIABLE 11 CONSTANT kelv = 0.15 ! INTERSPECIES VARIABLE ELIMINATION 12 CONSTANT (1/HOUR) 13 14 ! CONSTANT TO DIVIDE THE AB SORPTION INTO LYMPHATIC AND PORTAL 15 FRACTIONS 16 CONSTANT A = 0.7 ! LYMPHATIC FRACTION, WANG ET AL. 1997 17 18!PARTITION COEFFICIENTS 19 CONSTANT PF = 100 ! ADIPOSE TISSUE/ BLOOD, WANG ET AL. 1997 20 CONSTANT PRE = 1.5 ! REST OF THE BODY/BLOOD, WANG ET AL. 1997 21 CONSTANT PLI = 6.0 ! LIVER/BLOOD, WANG ET AL. 1997 22 CONSTANT PPLA = 1.5 ! TEMPORARY PARAMETER NOT CONFIGURED, 23 WANG ET AL. 1997 24 25!PARAMETER FOR INDUCTION OF CYP 1A2, WANG ET AL. 1997 26 CONSTANT PAS_INDUC = 1.0 ! INCLUDE INDUCTION? (1 = YES, 0 = NO) 27 CONSTANT CYP1A2_1OUTZ = 1.6 ! DEGRADATION CONCENTRATION 28 CONSTANT OF 1A2 (NMOL/ML) 29 CONSTANT CYP1A2_1A1 = 1.6 ! BASAL CONCENTRATIO N OF 1A1 (NMOL/ML) 30 CONSTANT CYP1A2_1EC50 = 0.13 ! DISSOCIATION CONSTANT TCDD-CYP1A2 31 (NMOL/ML) 32 CONSTANT CYP1A2_1A2 = 1.6 !BASAL CONCENTRATIO N OF 1A2 (NMOL/ML) 33 CONSTANT CYP1A2_1KOUT = 0.1 ! FIRST ORDER RATE OF DEGRADATION (H-1) 34 CONSTANT CYP1A2_1TAU = 0.25 !HOLDING TIME (H) 35 CONSTANT CYP1A2_1EMAX = 600 ! MAXIMUM INDUCTION OVER BASAL 36 EFFECT (UNITLESS) 37 CONSTANT HILL = 0.6 !HILL CONSTANT; COOPERATIVELY LIGAND 38 BINDING E FFECT CONS TANT (UNITLESS) 39 40!DIFFUSIONAL PERMEABILITY FRACTION 41 CONSTANT PAFF = 0.0910 !ADIPOSE (UNITLES S), WANG ET AL. 1997 42 CONSTANT PAREF = 0.0298 !R EST OF THE BODY (UNITLESS), WANG ET AL. 43 1997 44 CONSTANT PALIF = 0.3500 !LIVER (UNITLESS), WANG ET AL. 1997 45 CONSTANT PAPLAF = 0.3 !TEMPORARY PARAMETER NOT CONFIGURED 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-64 DRAFT

— DO NOT CITE OR QUOTE 1 !FRACTION OF TISSUE WEIGHT ========= 2 CONSTANT WLI0 = 0.0360 !LIVER, WANG ET AL. 1997 3 4!TISSUE BLOOD FLOW EXPRESSED AS A FRACTION OF CARDIAC OUTPUT 5 CONSTANT QFF = 0.069 ! ADIPOSE TISSUE BLOOD FLOW FRACTION 6 (UNITLESS), WANG ET AL. 1997 7 CONSTANT QLIF = 0.183 !LIVER (UNITLESS), WANG ET AL. 1997 8 9!COMPARTMENT TISSUE BLOOD EXPR ESSED AS A FRACTION OF THE TOTAL 10 COMPARTMENT VOLUME 11 CONSTANT WFB0 = 0.050 !ADIPOSE TISSUE, WANG ET AL. 1997 12 CONSTANT WREB0 = 0.030 !REST OF THE BODY, WANG ET AL. 1997 13 CONSTANT WLIB0 = 0.266 !LIVER, WANG ET AL. 1997 14 CONSTANT WPLAB0 = 0.500 !TEMPORARY PARAM ETER NOT CONFIGURED 15 16!EXPOSURE SCENARIO FOR UNIQUE OR REPETITIVE WEEKLY OR MONTHLY 17 EXPOSURE 18 !NUMBER OF EXPOSURES PER WEEK 19 CONSTANT WEEK_LACK = 0.0 !DELAY BEFORE EXPO SURE ENDS (WEEK) 20 CONSTANT WEEK_PERIOD = 168 ! NUMBER OF HOURS IN THE WEEK (HOURS) 21 CONSTANT WEEK_FINISH = 168 ! TIME EXPOSURE ENDS (HOURS) 22 23!NUMBER OF EXPOSURES PER MONTH 24 CONSTANT MONTH_LACK = 0.0 !DELAY BEFORE EXPOSURE BEGINS 25 (MONTHS) 26 27!CONSTANT FOR BACKGROUND EXPOSURE=========== 28 CONSTANT Day_LACK_BG = 0.0 !DELAY BEFORE EXPOSURE BEGINS (HOURS) 29 CONSTANT Day_PERIOD_BG = 24 !LENGTH OF EXPOSURE (HOURS) 30 31!NUMBER OF EXPOSURES PER WEEK 32 CONSTANT WEEK_LACK_BG = 0.0 !DELAY BE FORE BACKGROUD EXPOSURE 33 BEGINS (WEEKS) 34 CONSTANT WEEK_PERIOD_BG = 168 !NUMBER OF HOURS IN THE WEEK 35 (HOURS) 36 CONSTANT WEEK_FINISH_BG = 168 !TIME EXPOSURE ENDS (HOURS) 37 38!INITIAL BODY W EIGHT 39 CONSTANT BW_T0 = 250 ! WANG ET AL. 1997 40 CONSTANT RATIO_RATF_MOUSEF = 1.0 !RATIO OF FETUS MOUSE/RAT AT 41 GESTATIONAL DAY 22 42 43! COMPARTMENT LIPID EXPRESSED AS THE FRACTION OF TOTAL LIPID, POULIN 44 ET AL 2002 45 CONSTANT F_TOTLIP = 0.855 ! ADIPOSE TISSUE (UNITLESS) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-65 DRAFT

— DO NOT CITE OR QUOTE CONSTANT B_TOTLIP = 0.0023 ! BLOOD (UNITLESS) 1 CONSTANT RE_TOTLIP = 0.019 ! REST OF THE BODY (UNITLESS) 2 CONSTANT LI_TOTLIP = 0.060 ! LIVER (UNITLESS) 3 CONSTANT PLA_TOTLIP = 0.019 4 CONSTANT FETUS_TOTLIP = 0.019 5 6 END ! END OF THE INITIAL SECTION 7 8 DYNAMIC ! DYNAMIC SI MULATION SECTION 9 ALGORITHM IALG = 2 ! GEAR METHOD 10 CINTERVAL CINT = 0.1 ! COMMUNICATION INTERVAL 11 MAXTERVAL MAXT = 1.0e+10 ! MAXIMUM CALCULATION INTERVAL 12 MINTERVAL MINT = 1.0E-10 ! MINIMUM CALCULATION INTERVAL 13 VARIABLE T = 0.0 14 CONSTANT TIMELIMIT = 100 !SIMULATION LIMIT TIME (HOURS) 15 CINTXY = CINT 16 PFUNC = CINT 17 18!TIME CONVERSION 19 DAY = T/24 ! TIME IN DAYS 20 WEEK = T/168 ! TIME IN WEEKS 21 MONTH = T/730 ! TIME IN MONTHS 22 YEAR = T/8760 ! TIME IN YEARS 23 24 DERIVATIVE ! PORTION OF CODE THAT SOLVES DIFFERENTIAL EQUATIONS 25 26!CHRONIC OR SUBCHRONI C EXPOSURE SCENARIO ======= 27 !NUMBER OF EXPOSURES PER DAY 28 DAY_LACK = EXP_TIME_ON ! DELAY BEFORE EXPOSURE BEGINS (HOURS) 29 DAY_PERIOD = DAY_CYCLE ! EXPOSURE PERIOD (HOURS) 30 DAY_FINISH = CINTXY ! LENGTH OF EXPOSURE (HOURS) 31 MONTH_PERIOD = TIMELIMIT ! EXPOSURE PERIOD (MONTHS) 32 MONTH_FINISH = EXP_TIME_OFF ! LENGTH OF EXPOSURE (MONTHS) 33 34!NUMBER OF EXPOSURES PER DAY AND MONTH 35 DAY_FINISH_BG = CINTXY 36 MONTH_LACK_BG = BCK_TIME_ON !DELAY BEFORE BACKGROUD EXPOSURE 37 BEGINS (MONTHS) 38 MONTH_PERIOD_BG = TIMELIMIT !BACKGROUND EXPOSURE (MONTHS) 39 MONTH_FINISH_BG = BCK_TIME_OFF !LENGTH OF BACKGROUND EXPOSURE 40 (MONTHS) 41 42!INTRAVENOUS LATE 43 IV_FINISH = CINTXY 44 B = 1-A ! FRACTION OF DIOXIN ABSO RBED IN THE PORTAL FRACTION OF THE 45 LIVER 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-66 DRAFT

— DO NOT CITE OR QUOTE 1 2 !FETUS,VOLUME,FETUS,VOLUME,FETUS,VOLUME,FETUS,VOLUME,FETUS,VOLUM 3 E,FETUS,VOLUME 4 ! FROM OFLAHERTY_1992 5 6 RTESTGEST= T-MATTING 7 TESTGEST=DIM(RTESTGEST,0.0) 8 9 WTFER_RODENT= (2.3d-3*EXP(1.49d- 2*(TESTGEST))+1.3d-2)*Gest_on 10 WTFER = (WTFER_RODENT*RAT IO_RATF_MOUSEF*N_FETUS) 11 WTFE = DIM(WTFER,0.0) 12 13! 14 FAT,VOLUME,FAT,VOLUME,FAT,VOLUME,FAT,VOLUME,FAT,VOLUME,FAT,VOLU 15 ME,FAT,VOLUME 16 ! FAT GROWTH EXPRESSION LINEAR DURING PREGNANCY 17 ! FROM O'FLAHERTY_1992 18 19 WF0= (((9.66d-5*(TESTGEST))*gest_on)+0.069) 20 21! PLACENTA,VOLUME, PLACENTA,VOLUME, PLACENTA,VOLUME, 22 PLACENTA,VOLUME 23 ! WPLA PLACENTA GROW TH EXPRESSION, SINGLE EXPONENTIAL WITH OFFSET 24 ! FROM O'FLAHERTY_1992 ! FOR EACH PUP 25 26 WPLA0N_RODENT = (0.6/(1+(5d+ 3*EXP(-0.0225*(TESTGEST)))))*N_FETUS 27 WPLA0R = (WPLA0N_R ODENT/WT0)*Gest_on 28 WPLA0 = DIM(WPLA0R,0.0) 29 30! PLACENTA,FLOW RATE, PLACENTA ,FLOW RATE, PLACENTA,FLOW RATE, 31 PLACENTA,FLOW RATE 32 ! QPLA PLACENTA GROWTH EXPRESSI ON, DOUBLE EXPONENTIAL WITH OFFSET 33 ! FROM O'FLAHERTY_1992 34 35QPLARF = (1.67d-7 *exp(9.6d-3*(TESTGEST)) & 36 +1.6d-3*exp(7.9d-3*(TESTGEST ))+0.0)*Gest_on*SWITCH_trans 37 QPLAF=DIM(QPLARF,0.0) !FRACTION OF FLOW RATE IN PLACENTA 38 39! GESTATION CONTROL 40 IF (T.LT.MATTING) THEN 41 Gest_off = 1.0 42 Gest_on= 0.0 43 ELSE 44 Gest_off = 0.0 45 Gest_on = 1.0 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-67 DRAFT

— DO NOT CITE OR QUOTE END IF 1 2! MOTHER BODY WEIGHT GROWTH EQUATION======== 3 ! MODIFICATION TO ADAPT THIS MODEL AT HUMAN MODEL 4 ! BECAUSE LINEAR DESCRIPTION IS NOT GOOD ENOUGH FOR MOTHER GROWTH 5 ! MOTHER BODY WEIGHT GROWTH 6 7PARAMETER (BW_RMN = 1.0E-30) 8 WT0= BW_T0 *(1+(0 .41*T)/(1402.5+T+BW_RMN)) 9 10 ! VARIABILITY OF REST OF THE BODY DEPENDS ON OTHER ORGANS 11 WRE0 = (0.91 - (WLIB0*WLI0 + WFB0 *WF0 +WPLAB0*WPLA0 + WLI0 + WF0 + 12 WPLA0))/(1+WREB0) ! REST OF THE BODY FRACTION; UPDATED FOR EPA 13 ASSESSMENT 14 QREF = 1-(QFF+QLIF+QPLAF) !REST OF BODY BLOOD FLOW RATE (ML/HR) 15 QTTQF = QFF+QREF+QLI F+QPLAF ! SUM MUST EQUAL 1 16 17! COMPARTMENT VOLUME (ML OR G) ========= 18 WF = WF0 * WT0 ! ADIPOSE TISSUE 19 WRE = WRE0 * WT0 ! REST OF THE BODY 20 WLI = WLI0 * WT0 ! LIVER 21 WPLA= WPLA0* WT0 ! PLACENTA 22 23! COMPARTMENT TISSUE BLOOD (ML OR G) ========= 24 WFB = WFB0 * WF ! ADIPOSE TISSUE 25 WREB = WREB0 * WRE ! REST OF THE BODY 26 WLIB = WLIB0 * WLI ! LIVER 27 WPLAB = WPLAB0* WPLA ! PLACANTA 28 29! CARDIAC OUTPUT FOR THE GIVEN BODY WEIGHT (ML/H) ========= 30 !QC= QCCAR*60*(WT0/1000.0)**0.75 31 CONSTANT QCC=18684.0 ! EQUIVALENT TO 311.4 * 60 32 QC= QCC*(WT0/UNITCORR)**0.75 33 34!COMPARTMENT BLOOD FLOW RATE (ML/HR) 35 QF = QFF*QC !ADIPOSE TISSUE BLOOD FLOW RATE 36 QLI = QLIF*QC !LIVER TISSUE BLOOD FLOW RATE 37 QRE = QREF*QC !REST OF THE BODY BLOOD FLOW RATE 38 QPLA = QPLAF*QC !PLACENTA TISSUE BLOOD FLOW RATE 39 QTTQ = QF+QRE+QLI +QPLA !TOTAL FLOW RATE 40 41!PERMEABILITY OR GAN FLOW (ML/HR)========= 42 PAF = PAFF*QF ! ADIPOSE TISSUE 43 PARE = PAREF*QRE ! REST OF THE BODY 44 PALI = PALIF*QLI ! LIVER TISSUE 45 PAPLA = PAPLAF*QPLA ! PLACENTA 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-68 DRAFT

— DO NOT CITE OR QUOTE 1!************************************** 2 ! ABSORPTION SECTION 3 ! ORAL 4 ! INTRAPERITONEAL 5 ! INTRAVENOUS 6 !************************************** 7 8!REPETITIVE ORAL BACKGROUND EXPOSURE SCENARIO 9 10 MSTOT_NMBCKGR = MSTOTBCKGR/MW ! CONVERTS THE BACKGROUND DOSE 11 TO NMOL/G 12 MSTTBCKGR =MSTOT_NMBCKGR *WT0 13 14 DAY_EXPOSURE_BG = PULSE(DAY_LACK _BG,DAY_PERIOD_BG,DAY_FINISH_BG) 15 WEEK_EXPOSURE_BG = 16 PULSE(WEEK_LACK_BG,WEEK_PERIOD_BG,WEEK_FINISH_BG) 17 MONTH_EXPOSURE_BG = 18 PULSE(MONTH_LACK_BG,MONTH_PERIOD_BG,MONTH_FINISH_BG) 19 20 MSTTCH_BG = 21 (DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG)*MSTTBCK 22 GR 23 MSTTFR_BG = MSTTBCKGR/CINT 24 25 CYCLE_BG =DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG 26 27! CONDITIONAL ORAL EXPOSURE (BACKGROUND EXPOSURE) 28 29 IF (MSTTCH_BG.EQ.MSTTBCKGR) THEN 30 ABSMSTT_GB= MSTTFR_BG 31 ELSE 32 ABSMSTT_GB = 0.0 33 END IF 34 35 CYCLETOTBG=INTE G(CYCLE_BG,0.0) 36 37!REPETITIVE ORAL EXPOSURE SCENARIO 38 39 MSTT= MSTOT_NM * WT0 !AMOUNT IN NMOL 40 41 DAY_EXPOSURE = PULSE(DAY_LACK,DAY_PERIOD,DAY_FINISH) 42 WEEK_EXPOSURE = PULSE(WEEK_LACK,WEEK_PERIOD,WEEK_FINISH) 43 MONTH_EXPOSURE = PULSE(MONTH_LA CK,MONTH_PERIOD,MONTH_FINISH) 44 45 MSTTCH = (DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE)*MSTT 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-69 DRAFT

— DO NOT CITE OR QUOTE MSTTFR = MSTT/CINT 1 2 CYCLE = DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE 3 SUMEXPEVENT= INTEG (CYCLE,0.0) ! NUMBER OF CYCLE GENERATE DURING 4 SIMULATION 5 6! CONDITIONAL ORAL EXPOSURE 7 IF (MSTTCH.EQ.MSTT) THEN 8 ABSMSTT= MSTTFR 9 ELSE 10 ABSMSTT = 0.0 11 END IF 12 13 14CYCLETOT=INTEG(CYCLE,0.0) 15 16! MASS CHANGE IN THE LUMEN 17 RMSTT= -(KST+KABS)*MST +ABSMSTT +ABSMSTT_GB ! RATE OF CHANGE 18 (NMOL/H) 19 MST = INTEG(RMSTT,0.0) !AMOUNT REMAINING IN DUODENUM 20 (NMOL) 21 22! ABSORPTION IN LYMPH CIRCULATION 23 LYRMLUM = KABS*MST*A 24 LYMLUM = INTEG(LYRMLUM,0.0) 25 26! ABSORPTION IN PORTAL CIRCULATION 27 LIRMLUM = KABS*MST*B 28 LIMLUM = INTEG(LIRMLUM,0.0) 29 30 31 ! -----IV EXPOSURE --------- 32 33IV= DOSEIV_NM * WT0 !AMOUNT IN NMOL 34 IVR= IV/PFUNC ! RATE FO R IV INFUSION IN BLOOD 35 EXPIV= IVR * (1.0-STEP(PFUNC)) 36 IVDOSE = integ(EXPIV,0.0) 37 38!------IV LA TE IN THE CYCLE 39 ! MODIFICATION ON January 13 2004 40 IV_RlateR = DOSEIVNMlate*WT0 41 IV_EXPOSURE=PULSE(IV_LACK,IV_PERIOD,IV_FINISH) 42 43IV_lateT = IV_EXPOSURE *IV_RlateR 44 IV_late = IV_lateT/CINT 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-70 DRAFT

— DO NOT CITE OR QUOTE SUMEXPEVENTIV= integ (IV_EXPOSUR E,0.0) !NUMBER OF CYCLE GENERATE 1 DURING SIMULATION 2 3!SYSTEMIC CONCENTRATION OF TCDD 4 5! MODIFICATION ON OCTOBER 6, 2009 6 CB= 7 (QF*CFB+QRE*CREB+QLI*CLIB+EXPIV+LY RMLUM+QPLA*CPLAB+IV_late)/(QC+CL 8 URI) ! 9 CA = CB ! CONCENTRATION (NMOL/ML) 10 11 12!URINARY EXCRETION BY KIDNEY 13 ! MODIFICATION ON OCTOBER 6, 2009 14 RAURI = CLURI *CB 15 AURI = INTEG(RAURI,0.0) 16 17 18 19!UNIT CONVERSION POST SIMULATION 20 CBSNGKGLIADJ=(CB*MW*UNITCORR*(1.0/ B_TOTLIP)*(1.0/SERBLO))![NG of TCDD 21 Serum/Kg OF LIPIP] 22 AUCBS_NGKGLIADJ=i nteg(CBSNGKGLIADJ,0.0) 23 24PRCT_B = (CB/(MSTT+1E-30))*100.0 !P ERCENT OF ORAL DOSE IN BLOOD 25 PRCT_BIV = (CB/(IV_RlateR+1E-30 ))*100.0 ! PERCENT OF IV DOSE IN BLOOD 26 CBNGKG= CB*MW*UNITCORR 27 28 29!ADIPOSE COMPARTMENT 30 !TISSUE BLOOD COMPARTMENT 31 RAFB= QF*(CA-CFB)-PAF*(CFB-CF/PF) !(NMOL/H) 32 AFB = INTEG(RAFB,0.0) !(NMOL) 33 CFB = AFB/WFB !(NMOL/ML) 34 !TISSUE COMPARTMENT 35 RAF = PAF*(CFB-CF/PF) !(NMOL/H) 36 AF = INTEG(RAF,0.0) !(NMOL) 37 CF = AF/WF !(NM/ML) 38 39!UNIT CONVERSION POST SIMULATION 40 CFTOTAL= (AF + AFB)/(WF + WFB) ! TOTAL CONCENTRATION IN NMOL/ML 41 CFTFREE = CFB + CF !TOTAL FR EE CONCENTRATION IN FAT (NM/ML) 42 PRCT_F = (CFTOTAL/(MSTT+1E-30)) *100.0 ! PERCENT OF ORAL DOSE IN FAT 43 PRCT_FIV = (CFTOTAL/(IV_RlateR+1E -30))*100.0 ! PERCENT OF IV DOSE I N FAT 44 CFNGKG=CFTOTAL*MW*UNITCORR ! FAT CONCENTRATION NG/KG 45 AUCF_NGKGH=integ(CFNGKG,0.0) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-71 DRAFT

— DO NOT CITE OR QUOTE 1!REST OF THE BODY COMPARTMENT 2 RAREB= QRE *(CA-CREB)-PARE* (CREB-CRE/PRE) !(NMOL/H) 3 AREB = INTEG(RAREB,0.0) !(NMOL) 4 CREB = AREB/WREB !(NMOL/H) 5 !TISSUE COMPARTMENT 6 RARE = PARE*(CREB - CRE/PRE) !(NMOL/H) 7 ARE = INTEG(RARE,0.0) !(NMOL) 8 CRE = ARE/WRE !(NMOL/ML) 9 10!UNIT CONVERSION POST SIMULATION 11 CRETOTAL= (ARE + AREB)/(WRE + WREB) ! TOTAL CONCENTRATION IN 12 NMOL/ML 13 PRCT_RE = (CRETOTAL/(MSTT+1E-30))*1 00.0 ! PERCENT OF ORAL DOSE IN REST 14 OF THE BODY 15 PRCT_REIV = (CRETOTAL/(IV_RlateR+1E- 30))*100.0 !PERCENT OF IV DOSE IN 16 REST OF THE BODY 17 CRENGKG=CRETOTAL*MW*UNITCORR ! REST OF THE BODY CONCENTRATION 18 IN NG/KG 19 20 21!LIVER COMPARTMENT 22 !TISSUE BLOOD COMPARTMENT 23 RALIB = QLI*(CA-CLIB)-PALI*(CLIB-CFLLIR)+LIRMLUM ! 24 ALIB = INTEG(RALIB,0.0) !(NMOL) 25 CLIB = ALIB/WLIB !(NMOL/ML) 26 !TISSUE COMPARTMENT 27 RALI = PALI*(CLIB - CFLLIR)-REXCLI ! (NMOL/HR) 28 ALI = INTEG(RALI,0.0) !(NMOL) 29 CLI = ALI/WLI !(NMOL/ML) 30 31!FREE TCDD CONCENTRATIO N IN LIVER COMPARTMENT 32 PARAMETER (LIVER_1RMN = 1.0E-30) 33 CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR & 34 +LIVER_1RMN))+((CYP 1A2_1O3*CFLLIR/(KDLI2 + CFLLIR & 35 +LIVER_1RMN )*PAS_INDUC)))-CFLLI,CFLLI0) 36 CFLLIR=DIM(CFLLI,0.0) ! FREE CONCENTRATION IN LIVER 37 38CBNDLI= LIBMAX*CFLLIR/(KDL I+CFLLIR+LIVER_1RMN) !BOUND 39 CONCENTRATION 40 41!VARIABLE ELIMINATION BASED ON THE CYP1A2 42 KBILE_LI_T =((CYP1A2_1OUT-CYP1A2_1A2)/CYP1A2_1A2)*Kelv ! INDUCED 43 BILIARY EXCRETION RATE CONSTANT IN LIVER 44 REXCLI = KBILE_LI _T*CFLLIR*WLI ! DOSE-DEPENDENT BILIARY EXCRETION 45 RATE 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-72 DRAFT

— DO NOT CITE OR QUOTE EXCLI = INTEG(REXCLI,0.0) 1 2!UNIT CONVERSION POST SIMULATION 3 CLITOTAL= (ALI + ALIB)/(WLI + WL IB) ! TOTAL CONCENTRATION IN NMOL/ML 4 PRCT_LI = (CLITOTAL/(MSTT+1E-30))*100 5 PRCT_LIIV = (CLITOTAL/(IV_RlateR+1E-30))*100.0 6 Rec_occ= CFLLIR/(KDLI+CFLLIR) 7 CLINGKG=CLITOTAL*MW*UNITCO RR ! LIVER CONCENTRATION NG/KG 8 AUCLI_NGKGH=INTEG(CLINGKG,0.0) 9 CBNDLINGKG = CBNDLI*MW*UNITCORR 10 AUCBNDLI_NGKGH =INTEG(CBNDLINGKG,0.0) 11 12 13!CHEMICAL IN CYP450 (1A2) COMPARTMENT 14 CYP1A2_1KINP = CYP1A2_1KOUT* CYP1A2_1OUTZ 15 16 17! MODIFICATION ON OCTOBER 6, 2009 18 CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1.0 + CYP1A2_1EMAX *(CBNDLI+1.0e19 30)**HILL & 20 /(CYP1A2_1EC50**HILL + (CBNDLI+1.0e-30)**HILL)) & 21 - CYP1A2_1KOUT*CYP1A2_1OUT, CYP1A2_1OUTZ) 22 23 ! EQUATIONS INCORPORATING DELAY OF CYP1A2 PRODUCTION (NOT USED IN 24 SIMULATIONS) 25 26 CYP1A2_1RO2 = (CYP1A2_1OUT - CYP1A2_1O2)/ CYP1A2_1TAU 27 CYP1A2_1O2 =INTEG(CYP1A2_1RO2, CYP1A2_1A1) 28 29 CYP1A2_1RO3 = (CYP1A2_1O2 - CYP1A2_1O3)/ CYP1A2_1TAU 30 CYP1A2_1O3 =INTEG(CYP1A2_1RO3, CYP1A2_1A2) 31 32 ! TRANSFER OF DIOXIN FROM PLACENTA TO FETUS 33 ! FETAL EXPOSURE ONLY DURING EXPOSURE 34 35 IF (T.LT.TRANSTIME_ON) THEN 36 SWITCH_trans = 0.0 37 ELSE 38 SWITCH_trans = 1.0 39 END IF 40 41 !TRANSFER OF DIOXIN FROM PLACENTA TO FETUS 42 ! MODIFICATION 26 SEPTEMBER 2003 43 44 CONSTANT PFETUS= 4.0 ! 45 CONSTANT CLPLA_FET = 0.17 ! 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-73 DRAFT

— DO NOT CITE OR QUOTE 1 RAMPF = (CLPLA_FET*CPLA) *SWITCH_trans 2 AMPF=INTEG(RAMPF,0.0) 3 4 !TRANSFER OF DIOXIN FROM FETUS TO PLACENTA 5 RAFPM = (CLPLA_FET*CFETUS_v)*SWITCH_trans ! 6 AFPM = INTEG(RAFPM,0.0) 7 8 ! TCDD IN PLACENTA (MOTHER) COMPARTMENT 9 RAPLAB= QPLA*(CA - CPLAB)-PAPLA *(CPLAB -CFLPLAR) ! NMOL/H) 10 APLAB = INTEG(RAPLAB,0.0) ! (NMOL) 11 CPLAB = APLAB/(WPLAB+1E-30) ! (NMOL/ML) 12 RAPLA = PAPLA*(CPLAB-CFLPLAR)-RAMPF + RAFPM ! (NMOL/H) 13 APLA = INTEG(RAPLA,0.0) ! (NMOL) 14 CPLA = APLA/(WPLA+1e-30) ! (NMOL/ML) 15 16 17 PARAMETER (PARA_ZERO = 1.0E-30) 18 CFLPLA= IMPLC(CPLA-(CFLPLAR*PPLA +(PLABMAX*CFLPLAR/(KDPLA& 19 +CFLPLAR+PARA_ZERO)))-CFLPLA,CFLPLA0) 20 CFLPLAR=DIM(CFLPLA,0.0) 21 22!UNIT CONVERSION POST SIMULATION 23 CPLATOTAL= (APLA + APLAB) /((WPLA + WPLAB)+1e-30)! TOTAL 24 CONCENTRATION IN NMOL/ML 25 PRCT_PLA = (CPLATOTAL/(MSTT+1E-30))*100 26 PRCT_PLAIV = (CPLATOTAL/(IV_RlateR+1E-30))*100 27 28 29!FETUS COMPARTMENT 30 RAFETUS= RAMPF-RAFPM 31 AFETUS=INTEG(RAFETUS,0.0) 32 CFETUS=AFETUS/(WTFE+1E-30) 33 CFETOTAL= CFETUS 34 CFETUS_v = CFETUS/PFETUS 35 36! UNIT CONVERSION POST SIMULATION 37 CFETUSNGKG = CFETUS*MW*UNITCORR !(NG/KG) 38 AUC_FENGKGH = INTEG(CFETUSNGKG,0.0) 39 PRCT_FE = (CFETOTAL/(MSTT+1E-30))*100 40 PRCT_FEIV = (CFETOTAL/(IV_RlateR+1E-30))*100 41 42 43 ! ------------CONTROL MASS BALANCE ---------- 44 BDOSE= IVDOSE +LYMLUM+LIMLUM 45 BMASSE = EXCLI+AURI+AFB+AF+AREB +ARE+ALIB+ALI+APLA+APLAB+AFETUS 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-74 DRAFT

— DO NOT CITE OR QUOTE BDIFF = BDOSE-BMASSE 1 2!BODY BURDEN (NG) 3 BODY_BURDEN = AFB+AF+AREB+ARE+ALIB+ALI+APLA+APLAB ! 4 BBFETUSNG = AFETUS*MW*UNITCORR ! UNIT (NG) 5 ! BODY BURDEN IN TERMS OF CONCENTRATION (NG/KG) 6 BBNGKG 7 =(((AFB+AF+AREB+ARE+ALIB+ALI+APLA +APLAB)/WT0)*MW*UNITCORR) ! 8 AUC_BBNGKGH=INTEG(BBNGKG,0.0) 9 10 11 ! ------------CO MMAND OF THE END OF SIMULATION ---------- 12 TERMT (T.GE. TimeLimit, 'Time limit has been reached.') 13 END ! END OF THE DERIVATIVE SECTION 14 END ! END OF THE DYNAMIC SECTION 15 END ! END OF THE PROGRAM 16 17
C.2.4.2. Input Files 18 C.2.4.2.1. Bell et al. (2007). 19 output @clear 20 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 21 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 22 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 23 24 %output @nciout=1 T BBFETUSN G %AJS turned off 9/21/09 25 26 %Bell et al. 2007 (rat species) 27 %protocol: exposure daily dose in diet for 12 weeks followed by a two week mating time and 21 28 day gestation period 29 %DevTCDD4Species.csl 30 %RAT_GESTATIONAL_ICF_F083109.csl (now 09-11-09) 31 %dose levels: 0.0024, 0.008, 0.046 ug/kg/d with 0.00003 ug/kg/d background 32 %dose levels: 2.4, 8, 46 ng/kg/d with 0.03 ng/kg/day background 33 34%EXPOSURES SCENARIOS 35 MAXT =.1 36 CINT = 0.1 % 37 EXP_TIME_ON = 0 % delay before begin exposure (HOUR) 38 EXP_TIME_OFF = 2856 % TI ME EXPOSURE STOP (HOUR) 12 weeks exposure + 2 39 weeks for mating + 21 days gestation with exposure 40 DAY_CYCLE = 24 41 BCK_TIME_ON = 0. % DELAY BEFORE BACKGROUND EXPOSURE (HOUR) 42 BCK_TIME_OFF = 2856. % TIME OF BACKGROUND EXPOSURE STOP (HOUR) 43 IV_LACK = 505. 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-75 DRAFT

— DO NOT CITE OR QUOTE IV_PERIOD = 505. 1 TIMELIMIT = 2856 % SIMULATION LIMIT TIME (HOUR) 2 BW_T0 = 85 3 MATTING = 2352 % BEGINNING MATTING (HOUR) 4 TRANSTIME_ON = 2496 % SHOULD BE MATTING TIME + 6 DAYS(144 HOURS) 5 N_FETUS = 10 6 7 %EXPOSURE DOSE SCENARIOS (UG/KG) 8 %MSTOT = 0.00243 % ORAL EXPOSURE DOSE (UG/KG) 9 10 %MSTOT = 0.008 % ORAL EXPOSURE DOSE (UG/KG) 11 12 MSTOT = 0.0461 % ORAL EXPOSURE DOSE (UG/KG) 13 14
C.2.4.2.2. Hojo et al. (2002). 15
%TO BE USED AFTER THE 16 %clear variable 17 output @clear 18 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 19 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 20 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 21 %Hojo et al. 2002 22 %protocol: Single oral dose at GD8 23 %dose levels: 0.02 0.06, and 0.18 ug/kg at GD8 24 %dose levels: 20, 60, 180 ng/kg at GD8 25 % author provided the body weight for each group at the beginning of gestation (g) 26 %20 ng/kg BW = 275g 27 %60 ng/kg BW = 262g 28 %180 ng/kg BW = 278g 29 30 %EXPOSURES SCENARIOS 31 MAXT=0.1 32 CINT =0.1 % 33 EXP_TIME_ON = 192 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 34 EXP_TIME_OFF = 505 % TIME AT WHICH EXPOSURE ENDS (HOUR) 35 DAY_CYCLE = 505 36 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 37 (HOUR) 38 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 39 (HOUR) 40 IV_LACK = 505 41 IV_PERIOD = 505 42 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 43 % BW_T0 = 190 44 MATTING = 0. % BEGINNING OF MATING (HOUR) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-76 DRAFT

— DO NOT CITE OR QUOTE TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 1 N_FETUS = 10 2 3 %EXPOSURE DOSE SCENARIOS (UG/KG) 4 5%MSTOT = 0.02 % ORAL EXPOSURE DOSE IN UG/KG 6 %BW_T0 = 275 % AT 20 NG/KG, BW = 271g 7 8%MSTOT = 0.06 % ORAL EXPOSURE DOSE IN UG/KG 9 %BW_T0 = 262 % AT 60 NG/KG, BW = 275g 10 11MSTOT = 0.18 % ORAL EXPOSURE DOSE IN UG/KG 12 BW_T0 = 278 % AT 180 NG/KG, BW = 262g 13 14
C.2.4.2.3. Ikeda et al. (2005). 15 %clear variable 16 output @clear 17 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 18 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 19 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 20 21 %Ikeda et al. 2005 (rat species) 22 %protocol: loading dose of 400 ng/kg followed by weekly maintenance doses of 80 ng/kg for 6 23 weeks, 24 %dose levels: 0.4 ug/kg/day followed by weekly 0.08 ug/kg/day 25 %dose levels: 400 ng/kg/day followed by weekly 80 ng/kg/day 26 27%EXPOSURES SCENARIOS 28 MAXT =.1 29 CINT = 0.1 % 30 EXP_TIME_ON = 0 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 31 EXP_TIME_OFF = 1008 % TIME AT WHICH EXPOSU RE ENDS (HOUR); PRE32 MATING (2 WEEKS) + MATING (1 WEEK) + GESTATION (3 WEEKS) 33 DAY_CYCLE = 168 % WEEKLY CYCLE 34 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 35 (HOUR) 36 BCK_TIME_OFF = 167. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 37 (HOUR) 38 IV_LACK = 505. 39 IV_PERIOD = 505. 40 TIMELIMIT = 1008 % SIMULATION TIME LIMIT (HOUR) 41 BW_T0 = 250 42 MATTING = 504 % BEGINNING OF MATING (HOUR) 43 TRANSTIME_ON = 648 % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 44 N_FETUS = 10 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-77 DRAFT

— DO NOT CITE OR QUOTE 1 %EXPOSURE DOSE SCENARIOS (UG/KG) 2 MSTOT = 0.08 % ORAL EXPOSURE DOSE IN UG/KG 3 MSTOTBCKGR = 0.32 % BACKGROUND EXPOSU RE IN UG/KG 4 5
C.2.4.2.4. Kattainen et al. (2001). 6 %clear variable 7 output @clear 8 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 9 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 10 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 11 12 %Kattainen et al. 2001 13 %protocol: Single gavage at GD15 14 %dose levels: 0.03 0.1, 0.3, 1 ug/kg at GD15 15 %dose levels: 30, 100 300, 1000 ng/kg at GD15 16 17 18 19 MAXT=0.1 20 CINT =0.1 21 22%EXPOSURES SCENARIOS 23 EXP_TIME_ON = 336 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 24 EXP_TIME_OFF = 340 % TIME AT WHICH EXPOSURE ENDS (HOUR) 25 DAY_CYCLE = 505 26 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE 27 BEGINS (HOUR) 28 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 29 (HOUR) 30 IV_LACK = 505 31 IV_PERIOD = 505 32 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 33 BW_T0 = 190 34 MATTING = 0. % BEGINNING OF MATING (HOUR) 35 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 36 HOURS) 37 N_FETUS = 10 38 39 %EXPOSURE DOSE SCENARIOS (UG/KG) 40 %MSTOT = 0.03 % ORAL EXPOSURE DOSE IN UG/KG 41 %MSTOT = 0.1 % ORAL EXPOSURE DOSE IN UG/KG 42 %MSTOT = 0.3 % ORAL EXPOSURE DOSE IN UG/KG 43 MSTOT = 1 % ORAL EXPOSURE DOSE IN UG/KG 44 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-78 DRAFT

— DO NOT CITE OR QUOTE C.2.4.2.5. Markowski et al. (2001). 1 %clear variable 2 output @clear 3 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 4 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 5 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 6 7 %Markowski et al.2001 8 %protocol: Single gavage at GD18 9 %dose levels: 0.02 0.06, 0.18, 1 ug/kg at GD18 10 %dose levels: 20, 60, 180 ng/kg at GD18 11 12 13 %EXPOSURES SCENARIOS 14 MAXT=0.1 15 CINT =0.1 % 16 EXP_TIME_ON = 408 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 17 EXP_TIME_OFF = 415 % TIME AT WHICH EXPOSURE ENDS (HOUR) 18 DAY_CYCLE = 505 19 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 20 (HOUR) 21 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 22 (HOUR) 23 IV_LACK = 505 24 IV_PERIOD = 505 25 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 26 BW_T0 = 190 27 MATTING = 0. % BEGINNING OF MATING (HOUR) 28 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 29 N_FETUS = 10 30 31 %EXPOSURE DOSE SCENARIOS (UG/KG) 32 %MSTOT = 0.02 % ORAL EXPOSURE DOSE IN UG/KG 33 %MSTOT = 0.06 % ORAL EXPOSURE DOSE IN UG/KG 34 MSTOT = 0.18 % ORAL EXPOSURE DOSE IN UG/KG 35 36
C.2.4.2.6. Miettinen et al. (2006). 37 %clear variable 38 output @clear 39 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 40 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 41 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 42 43 %Miettinnen et al 2006 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-79 DRAFT

— DO NOT CITE OR QUOTE %protocol: Single oral dose at GD15 1 %dose levels: 0.03 0.1, 0.3, 1 ug/kg at GD15 2 %dose levels: 30, 100, 300, 1000 ng/kg at GD15 3 4MAXT=0.1 5 CINT =0.1 % 6 7%EXPOSURES SCENARIOS 8 EXP_TIME_ON = 336 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 9 EXP_TIME_OFF = 340 % TIME AT WHICH EXPOSURE ENDS (HOUR) 10 DAY_CYCLE = 505 11 BCK_TIME_ON = 0. % TI ME AT WHICH BACKGROUND EXPOSURE BEGINS 12 (HOUR) 13 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 14 (HOUR) 15 IV_LACK = 505 16 IV_PERIOD = 505 17 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 18 BW_T0 = 180 19 MATTING = 0. % BEGINNING OF MATING (HOUR) 20 TRANSTIME_ON = 144. % SHOU LD BE MATING TIME + 6 DAYS (144 HOURS) 21 N_FETUS = 10 22 23 %EXPOSURE DOSE SCENARIOS (UG/KG) 24 %MSTOT = 0.03 % ORAL EXPOSURE DOSE IN UG/KG 25 %MSTOT = 0.1 % ORAL EXPOSURE DOSE IN UG/KG 26 %MSTOT = 0.3 % ORAL EXPOSURE DOSE IN UG/KG 27 MSTOT = 1 % ORAL EXPOSURE DOSE IN UG/KG 28 29
C.2.4.2.7. Murray et al. (1979). 30 %clear variable 31 output @clear 32 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 33 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 34 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 35 36 %output @nciout=1 T BBFETUSN G %AJS turned off 9/21/09 37 38 %Murray et al.1979 (rat species) 39 %protocol: dietary exposure for 90 da ys followed by gestation (21 days) 40 %dose levels: 0.001 0.01, 0.1 ug/kg/d 41 %dose levels: 1, 10, 100 ng/kg/d 42 43%EXPOSURES SCENARIOS 44 MAXT =.1 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-80 DRAFT

— DO NOT CITE OR QUOTE CINT = 0.1 % 1 EXP_TIME_ON = 0 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 2 EXP_TIME_OFF = 2660 % TIME AT WHICH EXPO SURE ENDS (HOUR) 3 DAY_CYCLE = 24 4 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 5 (HOUR) 6 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 7 (HOUR) 8 IV_LACK = 2664 9 IV_PERIOD = 2664 10 TIMELIMIT = 2664 % SIMULATION TIME LIMIT (HOUR) 11 BW_T0 = 85 12 MATTING = 2160 % BEGINNING OF MATING (HOUR) 13 TRANSTIME_ON = 2304 % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 14 N_FETUS = 10 15 16 %EXPOSURE DOSE SCENARIOS (UG/KG) 17 %MSTOT = 0.001 % ORAL EXPOSURE DOSE IN UG/KG 18 %MSTOT = 0.01 % ORAL EXPOSURE DOSE N UG/KG 19 MSTOT = 0.1 % ORAL EXPOSURE DOSE N UG/KG 20 21
C.2.4.2.8. Nohara et al. (2000). 22 %clear variable 23 output @clear 24 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 25 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 26 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 27 28 %Nohara et al 2000 29 %protocol: exposure daily dose in diet 30 %dose levels: 0.0125, 0.050, 0.2 or 0.8 ug TCDD:kg body weight by gavage on GD15. 31 %dose levels: 12.5, 50, 200 or 800 ng TCDD: kg body weight by gavage on GD15. 32 33MAXT=0.1 34 CINT =0.1 % 35 36%EXPOSURES SCENARIOS 37 EXP_TIME_ON = 336 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 38 EXP_TIME_OFF = 340 % TIME AT WHICH EXPOSURE ENDS (HOUR) 39 DAY_CYCLE = 505 TIME AT WHICH BACKGROUND EXPOSURE BEGINS (HOUR) 40 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 41 (HOUR) 42 IV_LACK = 505 43 IV_PERIOD = 505 44 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-81 DRAFT

— DO NOT CITE OR QUOTE BW_T0 = 180 1 MATTING = 0. % BEGINNING OF MATING (HOUR) 2 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 3 N_FETUS = 10 4 5 %EXPOSURE DOSE SCENARIOS (UG/KG) 6 %MSTOT = 0.0125 % ORAL EXPOSURE DOSE IN UG/KG 7 %MSTOT = 0.050 % ORAL EXPOSURE DOSE IN UG/KG 8 %MSTOT = 0.2 % ORAL EXPOSU RE DOSE IN UG/KG 9 MSTOT = 0.8 % ORAL EXPOSURE DOSE IN UG/KG 10 11
C.2.4.2.9. Ohsako et al. (2001). 12
%TO BE USED AFTER THE 13 %clear variable 14 output @clear 15 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 16 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 17 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 18 19 %Ohsako et al. 2001 20 %protocol: exposure SINGLE DOSE AT GD15 21 %dose levels: 0.0125, 0.05, and 0.2 and 0.8 ug/kg AT GD15 22 %dose levels: 12.5, 50, 200 and 800 ng/kg AT GD15 23 24 %EXPOSURES SCENARIOS 25 MAXT=0.001 26 CINT =0.1 % 27 EXP_TIME_ON = 360 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 28 EXP_TIME_OFF = 505 % TIME AT WHICH EXPOSURE ENDS (HOUR) 29 DAY_CYCLE = 505 30 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 31 (HOUR) 32 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 33 (HOUR) 34 IV_LACK = 505 35 IV_PERIOD = 505 36 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 37 BW_T0 = 200 38 MATTING = 0. % BEGINNING OF MATING (HOUR) 39 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 40 N_FETUS = 10 41 42 %EXPOSURE DOSE SCENARIOS (UG/KG) 43 44%MSTOT = 0.0125 % ORAL EXPOSURE DOSE IN UG/KG 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-82 DRAFT

— DO NOT CITE OR QUOTE %MSTOT = 0.05 % ORAL EXPOSURE DOSE IN UG/KG 1 %MSTOT = 0.20 % ORAL EXPOSURE DOSE IN UG/KG 2 MSTOT = 0.80 % ORAL EXPOSURE DOSE IN UG/KG 3 4
C.2.4.2.10. Schantz et al. (1996) and Amin et al. (2000). 5 output @clear 6 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 7 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 8 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 9 10 %Amin et al 2000 (rat species ) and Schantz et al 1995 11 %protocol: Daily doses dur ing gestation day 10 to 16 12 %DevTCDD4Species.csl 13 %RAT_GESTATIONAL_ICF_F083109.csl (now 09-11-09) 14 %dose levels: 25 and 100 ug/kg/day 15 %dose levels: 0.25 and 0.100 ng/kg/day 16 17%EXPOSURES SCENARIOS 18 MAXT =.1 19 CINT = 0.1 % 20 EXP_TIME_ON = 240. % delay before begin exposure (HOUR) 21 EXP_TIME_OFF = 384. % TI ME EXPOSURE STOP (HOUR) 12 weeks exposure + 2 22 weeks for mating + 21 days gestation with exposure 23 DAY_CYCLE = 24 % weekly cycle 24 BCK_TIME_ON = 1000. % DELAY BEFORE BACKGROUND EXPOSURE 25 (HOUR) 26 BCK_TIME_OFF = 1000. % TIME OF BACKGROUND EXPOSURE STOP (HOUR) 27 IV_LACK = 505. 28 IV_PERIOD = 505. 29 TIMELIMIT = 384. % SIMULATION LIMIT TIME (HOUR) 30 BW_T0 = 250. 31 MATTING = 0 % BEGINNING MATTING (HOUR) 32 TRANSTIME_ON = 144. % SHOULD BE MATTING TIME + 6 DAYS(144 HOURS) 33 N_FETUS = 10 34 35 %EXPOSURE DOSE SCENARIOS (UG/KG) 36 %MSTOT = .025 % ORAL EXPOSURE DOSE (UG/KG) 37 MSTOT = .100 38 MSTOTBCKGR = 0 % Background Exposure (UG/KG) 39 40
C.2.4.2.11. Seo et al. (1995). 41 %clear variable 42 output @clear 43

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-83 DRAFT

— DO NOT CITE OR QUOTE prepare @clear T CLINGKG CFNG KG CBSNGKGLIADJ BBNGKG CFETUSNGKG 1 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 2 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 3 4 %Seo et al. 1995 5 %protocol: exposure GD 10-16 6 %DevTCDD4Species.csl 7 %RAT_GESTATIONAL_ICF_F083109.csl (now 09-11-09) 8 %dose levels: 0.025 and 0.1 ug/kg GD 10-16 9 %dose levels: 25 and 100 ng/kg GD 10-16 10 11MAXT=0.1 12 CINT =0.1 13 14%EXPOSURES SCENARIOS 15 EXP_TIME_ON = 240 % delay before begin exposure (HOUR) 16 EXP_TIME_OFF = 385 % TIME EXPOSURE STOP (HOUR) 17 DAY_CYCLE = 24 18 BCK_TIME_ON = 0. % DELAY BEFORE BACKGROUND EXPOSURE 19 (HOUR) 20 BCK_TIME_OFF = 0. % TIME OF BACKGROUND EXPOSURE STOP (HOUR) 21 IV_LACK = 505 22 IV_PERIOD = 505 23 TIMELIMIT = 504 % SIMULATION LIMIT TIME (HOUR) 24 BW_T0 = 190 25 MATTING = 0. % BEGINNING MATING (HOUR) 26 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 27 HOURS) 28 N_FETUS = 10 29 30 %EXPOSURE DOSE SCENARIOS (UG/KG) 31 MSTOT = 0.025 % ORAL EXPOSURE DOSE (UG/KG) 32 %MSTOT = 0.1 % ORAL EXPOSURE DOSE (UG/KG) 33 34
C.2.4.2.12. Shi et al. (2007). 35 %clear variable 36 output @clear 37 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 38 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 39 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 40 %output @nciout=1 T BBFETUSN G %AJS turned off 9/21/09 41 42 %Shi et al 2007 43 %protocol: exposure at GD14 and GD21 orl exposure 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-84 DRAFT

— DO NOT CITE OR QUOTE %dose levels: 0.001, 0.005, 0.05 and 0.2 ug TCDD:kg body weight by gavage on GD14 and 1 GD21. 2 %dose levels: 1, 5, 50 and 200 ng/kg ng TCDD:kg body weight by gavage on GD14 and GD21. 3 % dose equivalent adjusted 0.143, 0.714, 7.14 and 28.6 ng/kg/d 4 5 MAXT=0.001 6 CINT =0.1 % 7 CFLI0 = 0 8 CFPLA0 = 0 9 %EXPOSURES SCENARIOS 10 EXP_TIME_ON = 312 % TIME AT WHICH EXPOSURE BEGINS (HOUR) 11 EXP_TIME_OFF = 485 % TIME AT WHICH EXPOSURE ENDS (HOUR) 12 DAY_CYCLE = 168 13 BCK_TIME_ON = 0. % TI ME AT WHICH BACKGROUND EXPOSURE BEGINS 14 (HOUR) 15 BCK_TIME_OFF = 0. % TI ME AT WHICH BACKGROUND EXPOSURE ENDS 16 (HOUR) 17 IV_LACK = 505 18 IV_PERIOD = 505 19 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 20 BW_T0 = 190 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 21 (G) 22 MATTING = 0. % BEGINNING OF MATING (HOUR) 23 TRANSTIME_ON = 144. % SHOU LD BE MATING TIME + 6 DAYS (144 HOURS) 24 N_FETUS = 10 25 26 %EXPOSURE DOSE SCENARIOS (UG/KG) 27 %MSTOT = 0.001 % ORAL EXPOSURE DOSE IN UG/KG 28 MSTOT = 0.005 % ORAL EXPOSURE DOSE IN UG/KG 29 %MSTOT = 0.05 % ORAL EXPOSURE DOSE IN UG/KG 30 %MSTOT = 0.2 % ORAL EXPOSURE DOSE IN UG/KG 31 32
C.2.5. Mouse Standard Model 33 C.2.5.1. Model Code 34
PROGRAM: ' Three Compartment PBPK M odel for TCDD in Mice: Standard Model 35 (Non-Gestation)' 36
37 !Mice_Dioxin_3C_June09_1_icf_aft erKKfix_v3_mousenongest.csl 38 !MICE_NON_GESTAT_ICF_F083109.csl 39 !MICE_NON_GESTAT_ICF_F093009.csl 40 !MICE_NON_GESTAT_ICF_F100609.csl 41 !***************************************************** 42 43

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-85 DRAFT

— DO NOT CITE OR QUOTE INITIAL ! INITIALIZATION OF PARAMETERS 1 2!SIMULATION PARAMETERS ==== 3 CONSTANT PARA_ZERO = 1D-30 4 CONSTANT EXP_TIME_ON = 0.0 ! TIME AT WHICH EXPOSURE BEGINS 5 (HOURS) 6 CONSTANT EXP_TIME_OFF = 2832 ! TIME AT WHICH EXPOSURE ENDS 7 (HOURS) 8 CONSTANT DAY_CYCLE = 24 ! NUMBER OF HOURS BETWEEN DOSES 9 (HOURS) 10 CONSTANT BCK_TIME_ON = 0.0 ! TIME AT WHICH BACKGROUND 11 EXPOSURE BEGINS (HOURS) 12 CONSTANT BCK_TIME_OFF = 0.0 ! TIME AT WHICH BACKGROUND 13 EXPOSURE ENDS (HOURS) 14 15 CONSTANT MW=322 ! MOLECUL AR WEIGHT (NG/NMOL) 16 CONSTANT SERBLO = 0.55 17 CONSTANT UNITCORR = 1000 18 19!CONSTANT EXPOSURE CONTROL =========== 20 !ACUTE, SUBCHRONIC , CHRONIC EXPOSURE ===== 21 !OR BACKGROUND EXPOSURE (IN THIS CASE 3 TIMES A DAY)=== 22 CONSTANT MSTOTBCKGR = 0.0 !ORAL BAC KGROUND EXPOSURE DOSE 23 (UG/KG) 24 CONSTANT MSTOT = 0.15 !ORAL EXPOSURE DOSE (UG/KG) 25 CONSTANT MSTOTsc = 0.0 ! SUBCUTANEOUS EXPOSURE DOSE (UG/KG) 26 27!ORAL ABSORPTION 28 MSTOT_NM = MSTOT/MW !AMOUNT IN NMOL/G 29 30! INTRAVEN OUS ABSORPTION 31 CONSTANT DOSEIV = 0.0 !INJECTED DOSE (UG/KG) 32 DOSEIV_NM = DOSEIV/MW ! CONVER TS THE INJECTED DOSE TO NMOL/G 33 34!INITIAL GUESS OF THE FREE CONCENTRATION IN THE LIGAND (COMPARTMENT 35 INDICATED BELOW)==== 36 CONSTANT CFLLI0 = 0.0 !LIVER (NMOL/ML) 37 38!BINDING CAPACITY (AhR) FOR NON LINEAR BINDING (COMPARTMENT 39 INDICATED BELOW) (NMOL/ML) 40 CONSTANT LIBMAX = 3.5e-4 ! LIVER (NM OL/ML), WANG ET AL. 1997 41 42 ! PROTEIN AFFINITY CONSTANTS (1A2 OR AhR, COMPARTMENT INDICATED 43 BELOW) (NMOL/ML)=== 44 CONSTANT KDLI = 1.0e-4 !LIVER (AhR)(N MOL/ML), WANG ET AL. 1997 45 CONSTANT KDLI2 = 2.0e-2 !LIVER (1A2)(NMOL/ML), EMOND ET AL. 2004 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-86 DRAFT

— DO NOT CITE OR QUOTE 1 !===EXCRETION AND ABSORPTI ON CONSTANT (OPTIMIZED) 2 CONSTANT KST = 0.3 ! GASTRIC RATE CONSTANT (HR-1), 3 CONSTANT KABS = 0.48 !INTESTINAL ABSORPTION CONSTANT (HR-1) ), 4 WANG ET AL. 1997 5 6 ! ELIMINATION CONSTANTS 7 CONSTANT CLURI = 0.09 ! URINARY CLEARANCE (ML/HR) 8 9 ! ==test elimination variable 10 constant kelv = 0.4 ! INTERSPECIES VAR IABLE ELIMINATI ON CONSTANT 11 (1/HOUR) 12 13 ! CONSTANT TO DIVIDE THE ABSORP TION INTO LYMPHATIC AND PORTAL 14 FRACTIONS 15 CONSTANT A = 0.7 ! LYMPHATIC FRACTION, WANG ET AL. 1997 16 17 !PARTITION COEFFICIENTS OPTIMIZED 18 CONSTANT PF = 400 ! ADIPOSE TISSUE/BLOOD 19 CONSTANT PRE = 3 ! REST OF TH E BODY/BLOOD, WANG ET AL. 2000 20 CONSTANT PLI = 6 ! LIVER/BLOOD, WANG ET AL. 1997 21 22 !===PARAMETER FOR INDUCTION OF CYP 1A2 23 CONSTANT PAS_INDUC= 1.0 ! INCLUDE INDUCTION? (1 = YES, 0 = NO) 24 CONSTANT CYP1A2_1OUTZ = 1.6 ! DEGRADATION CONCENTRATION CONSTANT 25 OF 1A2 (NMOL/ML) 26 CONSTANT CYP1A2_1A1 = 1.5 ! BA SAL CONCENTRATION OF 1A1 (NMOL/ML) 27 CONSTANT CYP1A2_1EC50 = 0.13 ! DI SSOCIATION CONSTANT TCDD-CYP1A2 28 (NMOL/ML) 29 CONSTANT CYP1A2_1A2 = 1.5 ! BA SAL CONCENTRATION OF 1A2 (NMOL/ML) 30 CONSTANT CYP1A2_1KOUT = 0.1 ! FIRST ORDER RATE OF DEGRADATION (H-1) 31 CONSTANT CYP1A2_1TAU = 1.5 ! HOLDING TIME (H) 32 CONSTANT CYP1A2_1EMAX = 600 ! MAXIMUM INDUCTION OVER BASAL EFFECT 33 (UNITLESS) 34 CONSTANT HILL = 0.6 !HILL CONSTANT; COOPERATIVELY LIGAND 35 BINDING EFFECT CONS TANT (UNITLESS) 36 !DIFFUSIONAL PERMEABILITY FRACTION 37 CONSTANT PAFF = 0.12 ! ADIPOSE (UNITLE SS), WANG ET AL. 2000 38 CONSTANT PAREF = 0.03 ! REST OF THE BODY (UNITLESS) 39 CONSTANT PALIF = 0.35 ! LIVER (UNITLESS) 40 41!COMPARTMENT TISSUE BLOOD VOLUME ========= 42 CONSTANT W LI0 = 0.0549 ! LIVER, ILSI 1994 43 CONSTANT WF0 = 0.069 ! ADIPOSE 44 45!TISSUE BLOOD FLOW EXPRESSED AS A FRACTION OF CARDIAC OUTPUT 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-87 DRAFT

— DO NOT CITE OR QUOTE CONSTANT QFF = 0.070 ! ADIPOSE TISSUE BLO OD FLOW FRACTION 1 (UNITLESS), LEUNG ET AL. 1990 2 CONSTANT QLIF = 0.161 ! LIVER (UNITLESS) ILSI ET AL. 1994 3 4!COMPARTMENT TISSUE BLOOD EXPR ESSED AS A FRACTION OF THE TOTAL 5 COMPARTMENT VOLUME 6 CONSTANT WFB0 = 0.050 ! ADIPOSE TISSUE, WANG ET AL. 1997 7 CONSTANT WREB0 = 0.030 ! REST OF THE BODY, WANG ET AL. 1997 8 CONSTANT WLIB0 = 0.266 ! LIVER, WANG ET AL. 1997 9 10! EXPOSURE SCENARIO FOR UNIQUE OR REPETITIVE WEEKLY OR MONTHLY 11 EXPOSURE 12 ! NUMBER OF EXPOSURES PER WEEK 13 CONSTANT WEEK_LACK = 0.0 ! DELAY BEFORE EXPOSURE ENDS (WEEK) 14 CONSTANT WEEK_PERIOD = 168 ! NUM BER OF HOURS IN THE WEEK (HOURS) 15 CONSTANT WEEK_FINISH = 120 ! TIME EXPOSURE ENDS (HOURS) 16 17! NUMBER OF EXPOSURES PER MONTH 18 CONSTANT MONTH_LACK = 0.0 ! DELAY BEFORE EXPOSURE (MONTH) 19 20!SET FOR BACKGROUND EXPOSURE=========== 21 !CONSTANT FOR BACKGROUND EXPOSURE=========== 22 CONSTANT Day_LACK_BG = 0.0 ! DELAY BEFORE EXPOSURE BEGINS (HOURS) 23 CONSTANT Day_PERIOD_BG = 24 ! LENGTH OF EXPOSURE (HOURS) 24 25! NUMBER OF EXPOSURES PER WEEK 26 CONSTANT WEEK_LACK_BG = 0.0 ! DELAY BEFORE BACKGROUD EXPOSURE 27 (WEEK) 28 CONSTANT WEEK_PERIOD_BG = 168 !NUMBE R OF HOURS IN TH E WEEK (HOURS) 29 CONSTANT WEEK_FINISH_ BG = 168 ! TIME EXPOSURE ENDS (HOURS) 30 31!GROWTH CONSTANT FOR RAT AND MOUSE 32 !CONSTANT FOR MOTHER BODY WEIGHT GROWTH ====== 33 CONSTANT BW_T0 = 20 !CHANGED FOR SIMULATION 34 35!CONSTANT USED IN CARDIAC OUTPUT EQUATION, KRISHNAN 2001 36 CONSTANT QCCAR =275 !CONSTANT (ML/MIN/KG) 37 38! COMPARTMENT LIPID EXPRESSE D AS THE FRACTION OF TOTAL LIPID 39 CONSTANT F_TOTLIP = 0.855 !ADIPOSE TISSUE (UNITLESS) 40 CONSTANT B_TOTLI P = 0.0033 !BLOOD (UNITLESS) 41 CONSTANT RE_TOTLIP = 0.019 !REST OF THE BODY (UNITLESS) 42 CONSTANT LI_TOTLIP = 0.06 !LIVER (UNITLESS) 43 44 END ! END OF THE INITIAL SECTION 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-88 DRAFT

— DO NOT CITE OR QUOTE DYNAMIC ! DYNAMIC SI MULATION SECTION 1 2 ALGORITHM IALG = 2 !GEAR METHOD 3 CINTERVAL CINT = 1.0 !COMMUNICATION INTERVAL 4 MAXTERVAL MAXT = 1.0e+10 !MAXIMUM CALCULATION INTERVAL 5 MINTERVAL MINT = 1.0E-10 !MINIMUM CALCULATION INTERVAL 6 VARIABLE T = 0.0 !HOUR 7 CONSTANT TIMELIMIT = 2904.0 !SIMULATION TIME LIMIT (HOURS) 8 CINTXY = CINT 9 PFUNC = CINT 10 11!TIME CONVERSION 12 DAY = T/24.0 ! TIME IN DAYS 13 WEEK = T/168.0 ! TIME IN WEEKS 14 MONTH = T/730.0 ! TIME IN MONTHS 15 YEAR = T/8760.0 ! TIME IN YEARS 16 17!NMAX =MAX(T,CTFNGKG) 18 nmax =max(T,CFNGKG) 19 20 DERIVATIVE ! PORTION OF CODE THAT SOLVES DIFFERENTIAL EQUATIONS 21 22!CHRONIC OR SUBCHR ONIC EXPOSURE SCENARIO ======= 23 !NUMBER OF EXPOSURES PER DAY 24 DAY_LACK = EXP_TIME_ON ! DELAY BEFORE EXPOSURE BEGINS (HOURS) 25 DAY_PERIOD = DAY_CYCLE ! EXPOSURE PERIOD (HOURS) 26 DAY_FINISH = CINTXY ! LENGTH OF EXPOSURE (HOURS) 27 MONTH_PERIOD = TIMELIMIT ! EXPOSURE PERIOD (MONTHS) 28 MONTH_FINISH = EXP_TIME_OFF ! LENGTH OF EXPOSURE (MONTHS) 29 30!NUMBER OF EXPOSURES PER DAY AND MONTH 31 DAY_FINISH_BG = CINTXY 32 MONTH_LACK_BG = BCK_TIME_ON ! DELAY BEFORE BACKGROUD EXPOSURE 33 BEGINS (MONTHS) 34 MONTH_PERIOD_BG = TIMELIMIT ! BACKGROUND EXPOSURE PERIOD 35 (MONTHS) 36 MONTH_FINISH_BG = BCK_TIME_OFF ! LENGTH OF BACKGROUND EXPOSURE 37 (MONTHS) 38 39! FRACTION OF DIOXIN ABSORBED IN THE PORTAL FRACTION OF THE LIVER 40 B = 1.0-A 41 42 43!GROWTH UP E QUATION (G) 44 45 PARAMETER (BW_RMN = 1.0E-30) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-89 DRAFT

— DO NOT CITE OR QUOTE WT0= (BW_T0 *(1.0+(0.41*T)/(1402.5+T+BW_RMN))) 1 2! VARIABILITY OF REST OF THE BODY DEPENDS ON OTHER ORGANS 3 !REST OF THE BODY FRAC TION; UPDATED FOR EPA ASSESSMENT 4 WRE0 = (0.91 - (WLIB0*WLI0 + WFB0 *WF0 + WLI0 + WF0))/(1+WREB0) 5 6 ! REST OF THE BODY BLOOD FLOW FRACTION 7 QREF = 1.0-(QFF+QLIF) !REST OF BODY BLOOD FLOW (ML/HR) 8 !SUMMATION OF BLOOD FLOW FRACTION (SHOULD BE EQUAL TO 1) 9 QTTQF = QFF+QREF+QLIF ! SUM MUST EQUAL 1 10 11!COMPARTMENT VOLUME (G) 12 WF = WF0 * WT0 ! ADIPOSE 13 WRE = WRE0 * WT0 ! REST OF THE BODY 14 WLI = WLI0 * WT0 ! LIVER 15 16!COMPARTMENT TISSUE BLOOD (G) 17 WFB = WFB0 * WF ! ADIPOSE 18 WREB = WREB0 * WRE ! REST OF THE BODY 19 WLIB = WLIB0 * WLI ! LIVER 20 21!CARDIAC OUTPUT FOR THE GIVEN BODY WEIGHT 22 QC= QCCAR*60*(WT0/1000.0)**0.75 23 24 QF = QFF*QC ! ADIPOSE TISSUE BLOOD FLOW RATE (ML/HR) 25 QLI = QLIF*QC ! LIVER TISSUE BLOOD FLOW RATE (ML/HR) 26 QRE = QREF*QC ! REST OF THE BODY BLOOD FLOW RATE (ML/HR) 27 28 QTTQ = QF+QRE+QLI !T OTAL FLOW RATE (ML/HR) 29 30!PERMEABILITY ORGAN FLOW (ML/HR) ======= 31 PAF = PAFF*QF ! ADIPOSE TISSUE 32 PARE = PAREF*QRE ! REST OF THE BODY 33 PALI = PALIF*QLI ! LIVER TISSUE 34 35!ABSORPTION SECTION 36 !ORAL 37 !BACKGROUND EXPOSURE 38 !EXPOSURE FOR STEADY STATE CONSIDERATION 39 !REPETITIVE EXPOSURE SCENARIO 40 41 MSTOT_NMBCKGR = MSTOTBCKGR /322 !AMOUNT IN NMOL/G 42 MSTTBCKGR =MSTOT_NMBCKGR *WT0 43 44!REPETITIVE OR AL BACKGROUND EXPOSURE SCENARIOS 45 DAY_EXPOSURE_BG = PULSE(DAY_LACK _BG,DAY_PERIOD_BG,DAY_FINISH_BG) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-90 DRAFT

— DO NOT CITE OR QUOTE WEEK_EXPOSURE_BG = 1 PULSE(WEEK_LACK_BG,WEEK_PERIOD_BG,WEEK_FINISH_BG) 2 MONTH_EXPOSURE_BG = 3 PULSE(MONTH_LACK_BG,MONTH_PERIOD_BG,MONTH_FINISH_BG) 4 5 MSTTCH_BG = 6 (DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG)*MSTTBCK 7 GR 8 MSTTFR_BG = MSTTBCKGR/CINT 9 10 totalBG= integ (MSTTCH_BG,0.0) 11 CYCLE_BG =DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG 12 13 14!CONDITIONAL ORAL EXPOSURE (BACKGROUND EXPOSURE) 15 IF (MSTTCH_BG.EQ.MSTTBCKGR) THEN 16 ABSMSTT_GB= MSTTFR_BG 17 ELSE 18 ABSMSTT_GB = 0.0 19 END IF 20 21!EXPOSURE + !REPETI TIVE EXPOSURE SCENARIO 22 IV= DOSEIV_NM * WT0 !AMOUNT IN NMOL 23 MSTT= MSTOT_NM * WT0 !AMOUNT IN NMOL 24 25 DAY_EXPOSURE = PULSE(DAY_LACK,DAY_PERIOD,DAY_FINISH) 26 WEEK_EXPOSURE = PULSE(WEEK_LACK,WEEK_PERIOD,WEEK_FINISH) 27 MONTH_EXPOSURE = PULSE(MONTH_LA CK,MONTH_PERIOD,MONTH_FINISH) 28 29 MSTTCH = (DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE)*MSTT 30 CYCLE = DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE 31 32 SUMEXPEVENT= integ (CYCLE,0.0)*cin t !NUMBER OF CYCLE GENERATE DURING 33 SIMULATION 34 35 MSTTFR = MSTT/CINT 36 37! CONDITIONAL ORAL EXPOSURE 38 IF (MSTTCH.EQ.MSTT) THEN 39 ABSMSTT= MSTTFR 40 ELSE 41 ABSMSTT = 0.0 42 END IF 43 44CYCLETOT=INTEG(CYCLE,0.0) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-91 DRAFT

— DO NOT CITE OR QUOTE 1!MASS CHANGE IN THE LUMEN 2 RMSTT= -(KST+KABS)*MST+ABSMSTT +A BSMSTT_GB ! RATE OF CHANGE 3 (NMOL/H) 4 MST = INTEG(RMSTT,0.0) !AMOUNT OF STAY IN DUODENUM (NMOL) 5 6!ABSORPTION IN LYMPH CIRCULATION 7 LYRMLUM = KABS*MST*A 8 LYMLUM = INTEG(LYRMLUM,0.0) 9 10!ABSORPTION IN PORTAL CIRCULATION 11 LIRMLUM = KABS*MST*B 12 LIMLUM = INTEG(LIRMLUM,0.0) 13 14!PERCENT OF DOSE REMAINING IN THE GI TRACT 15 PRCT_remain_GIT = (MST/(MSTT+1E-30))*100 16 17 RFECES = KST*MST + REXCLI 18 FECES = INTEG(RFECES,0.0) 19 prctFECES = (FECES/(BDOSE_TOTAL+1E-30))*100 20 21 22!ABSORPTION OF DI OXIN BY IV ROUTE--------- 23 IVR= IV/PFUNC ! RATE FO R IV INFUSION IN BLOOD 24 EXPIV= IVR * (1.0-STEP(PFUNC)) 25 IVDOSE = integ(EXPIV,0.0) 26 27!SYSTEMIC BLOOD CONCENTRATION (NMOL/ML) 28 ! MODIFICATION ON OCTOBER 6, 2009 29 CB=(QF*CFB+QRE*CREB+QLI*CLIB+ EXPIV+LYRMLUM)/(QC+CLURI) ! 30 CA = CB 31 32!URINARY EXCRETION BY KIDNEY 33 ! MODIFICATION ON OCTOBER 6, 2009 34 RAURI = CLURI *CB 35 AURI = INTEG(RAURI,0.0) 36 37 prctAURI = (AURI/(BDOSE_TOTAL+1E-30))*100 38 39 40!UNIT CONVERSION POST SIMULATION 41 PRCT_B = (CB/(MSTT+1E-30))*100 ! PERCENT OF DOSE/G TISSUE 42 CBNGKG=CB*MW*UNITCORR 43 CBSNGKGLIADJ= (CB*MW*UNITCORR*(1.0/ B_TOTLIP)*(1.0/SERBLO))![NG of TCDD 44 Serum/Kg OF LIPIP] 45 CBPMOL_KG= CB*UNITCORR*UNITCORR !CONCENTRATION IN PMOL/KG 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-92 DRAFT

— DO NOT CITE OR QUOTE CBNGG = CB*MW 1 !ADIPOSE TISSUE COMPARTMENT 2 !TISSUE BLOOD SUBCOMPARTMENT 3 RAFB = QF*(CA-CFB)-PAF*(CFB-CF /PF) !(NMOL/HR) 4 AFB = INTEG(RAFB,0.0) !(NMOL) 5 CFB = AFB/WFB !(NMOL/ML) 6 !TISSUE SUBCOMPARTMENT 7 RAF = PAF*(CFB-CF/PF) !(NMOL/HR) 8 AF = INTEG(RAF,0.0) !(NMOL) 9 CF = AF/WF !(NMOL/ML) 10 11!POST SIMULATION UNIT CONVERSION 12 CFTOTAL = (AF + AFB)/(WF + WFB) ! TOTAL CONCENTRATION IN FAT(NM/ML) 13 PRCT_F = (CFTOTAL/(MSTT+1E-30 ))*100 ! PERCENT OF DOSE IN FAT 14 CFNGKG = CFTOTAL*MW*UNITCORR 15 CFUGG=(CFTOTAL*MW)/UNITCORR 16 CFPMOL_KG= CFTOTAL*UNITCORR*UNITCORR !CONCENTRATION IN 17 PMOL/KG 18 CFNGG = CFTOTAL*MW 19 20!REST OF THE BODY COMPARTMENT 21 !TISSUE BLOOD SUBCOMPARTMENT 22 RAREB= QRE*(CA-CREB)-PARE*(CREB-CR E/PRE) !(NMOL/HR) 23 AREB = INTEG(RAREB,0.0) !(NMOL) 24 CREB = AREB/WREB !(NMOL/ML) 25 !TISSUE SUBCOMPARTMENT 26 RARE = PARE*(CREB - CRE/PRE) !(NMOL/HR) 27 ARE = INTEG(RARE,0.0) !(NMOL) 28 CRE = ARE/WRE !(NMOL/ML) 29 30!POST SIMULATION UNIT CONVERSION 31 CRETOTAL= (ARE + AREB)/(WRE + WREB) ! CONCENTRATION AT STEADY 32 STATE 33 PRCT_RE = (CRETOTAL/(MSTT+1E-30))*100 34 35 36!LIVER COMPARTMENT 37 !TISSUE BLOOD SUBCOMPARTMENT 38 RALIB = QLI*(CA-CLIB)-PALI*(CLIB- CFLLIR)+LIRMLUM !(NMOL/HR) 39 ALIB = INTeg(RALIB,0.0) !(NMOL) 40 CLIB = ALIB/WLIB 41 !TISSUE SUBCOMPARTMENT 42 RALI = PALI*(CLIB-CFLLIR)-REXCLI !(NMOL/HR) 43 ALI = integ(RALI,0.0) !(NMOL) 44 CLI = ALI/WLI !(NMOL/ML) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-93 DRAFT

— DO NOT CITE OR QUOTE !FREE TCCD CONCENTR ATION IN LIVER (NMOL/ML) 1 PARAMETER (LIVER_1RMN = 1.0E-30) 2 CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLI & 3 +LIVER_1RMN))+((CYP1A2_1O3*CFLLIR/(KDLI2+CFLLIR & 4 +LIVER_1RMN)* PAS_INDUC)))-CFLLI,CFLLI0) 5 CFLLIR=DIM(CFLLI,0.0) ! FREE CONCENTRATION IN LIVER 6 7 CBNDLI= LIBMAX*CFLLIR/(KDLI+ CFLLIR+LIVER_1RMN) !BOUND 8 CONCENTRATION 9 10!POST SIMULATION UNIT CONVERSION 11 CLITOTAL= (ALI + ALIB)/(WLI + WLIB)! 12 PRCT_LI = (CLITOTAL/(MSTT+1E-30)) *100 ! PERCENT OF DOSE IN LIVER 13 rec_occ_AHR= (CFLLIR/(KDLI+CFLLIR+ 1E-30))*100.0 ! PERCENT OF AhR 14 OCCUPANCY 15 PROT_occ_1A2= (CFLLIR/(KDLI2+CFLLIR ))*100.0 ! PERCENT OF 1A2 OCCUPANCY 16 CLINGKG =(CLITOTAL*MW*UNITCORR) 17 CBNDLINGKG = CBNDLI*MW*UNITCORR 18 CLIUGG=(CLITOTAL*MW)/UNITCORR 19 CLIPMOL_KG= CLITOTAL*UNITCORR*UNITCORR !CONCENTRATION IN 20 PMOL/KG 21 CLINGG = CLITOTAL*MW 22 23!Fraction increase of induction of CYP1A2 24 fold_ind=(CYP1A2_1OUT/CYP1A2_1A2) 25 VARIATIONOfAC =(CYP1A2_1O UT-CYP1A2_1A2)/CYP1A2_1A2 26 27!VARIABLE ELIMINATION BASED ON THE CYP1A2 28 KBILE_LI_T =((CYP1A2_1OUT-CYP1A2_1A2 )/CYP1A2_1A2)*Kelv !INDUCED BILIARY 29 EXCRETION RATE CONSTANT 30 31 REXCLI= (KBILE_LI_T*CFLLIR*WLI) !DOSE-DEPENDENT EXCRETION RATE 32 EXCLI = INTEG(REXCLI,0.0) 33 34!CHEMICAL IN CYP450 (1A2) COMPARTMENT 35 !EQUATION FOR INDUCTION OF CYP1A2 36 37 CYP1A2_1KINP = CYP1A2_1KOUT* CYP1A2_1OUTZ 38 39! MODIFICATION ON OCTOBER 6, 2009 40 CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1.0 + CYP1A2_1EMAX *(CBNDLI+1.0e41 30)**HILL & 42 /(CYP1A2_1EC50**HILL + (CBNDLI+1.0e-30)**HILL)) & 43 - CYP1A2_1KOUT*CYP1A2_1OUT, CYP1A2_1OUTZ) 44 ! EQUATIONS INC ORPORATING DELAY OF CYP1A2 PRODUCTION (NOT USED IN 45 SIMULATIONS) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-94 DRAFT

— DO NOT CITE OR QUOTE 1 CYP1A2_1RO2 = (CYP1A2_1OUT - CYP1A2_1O2)/ CYP1A2_1TAU 2 CYP1A2_1O2 =INTEG(CYP1A2_1RO2, CYP1A2_1A1) 3 CYP1A2_1RO3 = (CYP1A2_1O2 - CYP1A2_1O3)/ CYP1A2_1TAU 4 CYP1A2_1O3 =INTEG(CYP1A2_1RO3, CYP1A2_1A2) 5 6! MASS BALANCE CONTROL 7 BDOSE= LYMLUM+LIMLUM+IVDOSE 8 BMASSE = EXCLI+AURI+AFB+AF+AREB+ARE+ALIB+ALI 9 BDIFF = BDOSE-BMASSE 10 ! AMOUNT TOTAL PRESENT IN THE GI TRACT 11 BDOSE_TOTAL =LYMLUM+LIMLUM+FECES 12 13!BODY BURDEN IN NG 14 Body_burden =(AFB+AF+AREB+ARE+ALIB+ALI)*MW 15 16!BODY BURDEN CONCENTRATION (NG/KG) 17 BBNGKG =(((AFB+AF+AREB+ARE+ALI B+ALI)*MW)/(WT0/UNITCORR)) ! 18 19!COMMAND FOR END OF SIMULATION 20 TERMT (T.GE. TimeLimit, 'Time limit has been reached.') 21 22 END ! END OF THE DERIVATIVE SECTION 23 END ! END OF THE DYNAMIC SECTION 24 END ! END OF PROGRAM 25 26
C.2.5.2. Input Files 27 C.2.5.2.1. Hassoun et al. (1998) (13 weeks). 28 output @clear 29 prepare @clear 30 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 31 32 % Hassoun et al 1998 33 %built and check in August 7 2009 34 %protocol: oral e xposure single dose 35 %dose levels: 0.00045, 0.0015, 0.015, 0.15 ug/kg singl e dose + 7 days post exposure 36 %dose levels: 0.45, 1.5, 15, 150 ng/kg single dose + 7 days post exposure 37 %dose levels equivale nt 0.321, 1.07, 10.7, 107 ng/kg/day 38 39 MAXT = 0.01 40 CINT = 0.1 41 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 42 EXP_TIME_OFF = 2184 %2208 %TIM E AT WHICH EXPOSU RE ENDS (HOUR) 43 DAY_CYCLE = 24 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-95 DRAFT

— DO NOT CITE OR QUOTE WEEK_PERIOD = 168 1 WEEK_FINISH = 119 2 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 3 (HOUR) 4 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 5 (HOUR) 6 TIMELIMIT = 2208 %SIMULATION TIME LIMIT (HOUR) 7 BW_T0 = 23 % BODY WE IGHT AT THE BEGINNING OF THE SIMULATION (G) 8 9 10 %EXPOSURE DOSE SCENARIOS (UG/KG) 11 %MSTOT = 0.00045 % EXPOSURE DOSE IN UG/KG 12 %MSTOT = 0.0015 % EXPOSURE DOSE IN UG/KG 13 %MSTOT = 0.015 % EXPOSURE DOSE IN UG/KG 14 MSTOT = 0.150 % EXPOSURE DOSE IN UG/KG 15 16 NTP (1982) (female) (chronic) 17 %RAT2.m 18 %clear variable 19 output @clear 20 prepare @clear 21 prepare T CLINGKG CFNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 22 %output @nciout=168 T SUMEXPEVENT 23 24 25 % NTP subchronic Mice exposure 1982. 26 %built and check in September 20, 2009 27 %protocol: repetitive doses 28 %MICE_NON_GESTAT_ICF_F092009.csl (now 09-20-09) 29 %dose levels: 0.02, 0.1, 1 ug/kg/biweekly, ug/ kg for 104 weeks + 3 weeks post treatment 30 %dose levels: 20, 100 and 1000 ng/kg/Biweekly,ng/kg for 104 weeks + 3 weeks post treatment 31 %dose levels equivalent to: 5.71, 28.57, 285.1 ng/kg/d 32 33 MAXT = 0.01 34 CINT = 0.1 35 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 36 EXP_TIME_OFF = 17472 %TIM E AT WHICH EXPOSU RE ENDS (HOUR) 37 DAY_CYCLE = 84 38 BCK_TIME_ON = 0. %T IME AT WHICH BACKGROUND EXPOSURE BEGINS 39 (HOUR) 40 BCK_TIME_OFF = 0. %TIM E AT WHICH BACKGROUND EXPOSURE ENDS 41 (HOUR) 42 TIMELIMIT = 17976 %SIMULATION TIME LIMIT (HOUR) 43 BW_T0 = 23 % BODY WEIGHT AT THE BE GI NNING OF THE SIMULATION 44 (G) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-96 DRAFT

— DO NOT CITE OR QUOTE 1 %EXPOSURE DOSE SCENARIOS (UG/KG) 2 MSTOT = 0.02 % EXPOSURE DOSE IN UG/KG 3 %MSTOT = 0.1 % EXPOSURE DOSE IN UG/KG 4 %MSTOT = 1.0 % EXPOSURE DOSE IN UG/KG 5 6
C.2.5.2.2. NTP (1982) (male) (chronic). 7 %RAT2.m 8 %clear variable 9 output @clear 10 prepare @clear 11 prepare T CLINGKG CFNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 12 %output @nciout=168 T SUMEXPEVENT 13 14 % NTP subchronic Mice exposure 1982. 15 %built and check in September 20, 2009 16 %protocol: repetitive doses 17 %dose levels: 0.005, 0.025, 0.25 ug/kg/biweekly, ug/ kg for 104 weeks + 3 weeks post treatment 18 %dose levels: 5, 25 and 250 ng/kg/Biweekly,ng/ kg for 104 weeks + 3 weeks post treatment 19 %dose levels equivale nt to: 1.4, 7.1, 71 ng/kg/d 20 21 MAXT = 0.01 22 CINT = 0.1 23 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 24 EXP_TIME_OFF = 17472 %TIM E AT WHICH EXPOSU RE ENDS (HOUR) 25 DAY_CYCLE = 84 26 BCK_TIME_ON = 0. % TI ME AT WHICH BACKGROUND EXPOSURE BEGINS 27 (HOUR) 28 BCK_TIME_OFF = 0. %TIM E AT WHICH BACKGROUND EXPOSURE ENDS 29 (HOUR) 30 TIMELIMIT = 17976 %SIMULATION TIME LIMIT (HOUR) 31 BW_T0 = 25 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 32 (G) 33 34 35 %EXPOSURE DOSE SCENARIOS (UG/KG) 36 %MSTOT = 0.005 % EXPOSURE DOSE IN UG/KG 37 %MSTOT = 0.025 % EXPOSURE DOSE IN UG/KG 38 MSTOT = 0.25 % EXPOSURE DOSE IN UG/KG 39 40
C.2.5.2.3. Smialowicz et al. (2008). 41 output @clear 42 prepare @clear 43 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-97 DRAFT

— DO NOT CITE OR QUOTE 1 % Smialowicz et al, 2008. 2 %built and check in August 7 2009 3 %protocol: oral e xposure single dose 4 %protocol: 5/7 gavage for 13 wk; Female B6C3F1 mice 5 %dose levels: 0, 0.0015, 0.015, 0.15, 0.45 ug/kg 6 %dose levels: 0, 1.5, 15, 150, 450 nkd (0, 1.07, 10.7, 107, 321 nkd adj) 7 8 MAXT = 0.01 9 CINT = 0.1 10 TIMELIMIT = 2184 %SIMULATION TIME LIMIT (HOUR) 11 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 12 EXP_TIME_OFF = 2180 %T IME AT WHICH EXPOSURE ENDS (HOUR) 13 DAY_CYCLE = 24 14 WEEK_PERIOD = 168 15 WEEK_FINISH = 119 16 BCK_TIME_ON = 0. %TIM E AT WHICH BACKGROUND EXPOSURE BEGINS 17 (HOUR) 18 BCK_TIME_OFF = 0. %T IME AT WHICH BACKGROUND EXPOSURE ENDS 19 (HOUR) 20 BW_T0 = 28 % BODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 21 (G) 22 23 %EXPOSURE DOSE SCENARIOS (UG/KG) 24 %MSTOT = 0.0015 % EXPOSURE DOSE IN UG/KG 25 %MSTOT = 0.015 % EXPOSURE DOSE IN UG/KG 26 %MSTOT = 0.150 % EXPOSURE DOSE IN UG/KG 27 MSTOT = 0.450 % EXPOSURE DOSE IN UG/KG 28 29
C.2.5.2.4. Toth et al. (1979) (1 year). 30 output @clear 31 prepare @clear 32 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 33 34 % Toth et al 1979 35 %built and check in August 7 2009 36 %protocol: oral e xposure single dose 37 %dose levels: 7, 700, 7000 ng/kg 1/week for 52 weeks (1 year) 38 %dose levels: 0.007, 0.7 and 7 ug/kg 1/week for 52 weeks (1 year) 39 %dose equivalent: 1, 100, 1000 ng/kg/day 40 41 MAXT = 0.01 42 CINT = 0.1 43 TIMELIMIT = 8736 44 EXP_TIME_ON = 0. %TIM E AT WHICH EXPOSURE BEGINS (HOUR) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-98 DRAFT

— DO NOT CITE OR QUOTE EXP_TIME_OFF = 8736 %2208 %T IME AT WHICH EXPOSURE ENDS (HOUR) 1 DAY_CYCLE = 168 2 WEEK_PERIOD = 8760 3 WEEK_FINISH = 8760 4 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 5 (HOUR) 6 BCK_TIME_OFF = 0. %TIM E AT WHICH BACKGROUND EXPOSURE ENDS 7 (HOUR) 8 BW_T0 = 27 % B ODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 9 (G) 10 11 12 %EXPOSURE DOSE SCENARIOS (UG/KG) 13 %MSTOT = 0.007 % EXPOSURE DOSE IN UG/KG 14 %MSTOT = 0.7 % EXPOSURE DOSE IN UG/KG 15 MSTOT = 7 % EXPOSURE DOSE IN UG/KG 16 17
C.2.5.2.5. Toth et al. (1979) (2 year). 18 output @clear 19 prepare @clear 20 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 21 22 % Toth et al 1979 23 %built and check in August 7 2009 24 %protocol: oral e xposure single dose 25 %dose levels: 7, 700, 7000 ng/kg 1/week for 52 weeks (1 year) 26 %dose levels: 0.007, 0.7 and 7 ug/kg 1/week for 52 weeks (1 year) 27 %dose levels equivalent: 1, 100, 1000 ng/kg/day 28 29 MAXT = 0.01 30 CINT = 0.1 31 TIMELIMIT = 15576 %WEEKLY GAVAGE FOR 1 YEAR; LIFETIME FOLLOW-UP 32 (AVG 424-649 DAYS); USED MAXIMUM OF 649 DAYS 33 EXP_TIME_ON = 0. %TIM E AT WHICH EXPOSURE BEGINS (HOUR) 34 EXP_TIME_OFF = 8736 %2208 %t IME AT WHICH EXPOSURE ENDS (HOUR) 35 DAY_CYCLE = 168 36 WEEK_PERIOD = 8760 37 WEEK_FINISH = 8760 38 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 39 (HOUR) 40 BCK_TIME_OFF = 0. %TIM E AT WHICH BACKGROUND EXPOSURE ENDS 41 (HOUR) 42 BW_T0 = 27 % B ODY WEIGHT AT THE BEGI NNING OF THE SIMULATION 43 (G) 44 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-99 DRAFT

— DO NOT CITE OR QUOTE 1 %EXPOSURE DOSE SCENARIOS (UG/KG) 2 %MSTOT = 0.007 % EXPOSURE DOSE IN UG/KG 3 %MSTOT = 0.7 % EXPOSURE DOSE IN UG/KG 4 MSTOT = 7 % EXPOSURE DOSE IN UG/KG 5 6
C.2.5.2.6. White et al. (1986). 7 output @clear 8 prepare @clear 9 prepare T CLINGKG C FNGKG CBSNG KGLIADJ BBNGKG CBNDLINGKG 10 11 % White et al 1986 12 %built and check in August 7 2009 13 14 %protocol: oral e xposure single dose 15 %dose levels: 0.714, 3.57, 7.14, 35.71, 71.43, 142.86 ng /kg/d ug/kg 1/day for 14 consecutive 16 days 17 %dose have been modified following Jeff email on Friday August 21 2009 18 %dose levels: 10, 50, 100, 500, 1000, 2000 ng /kg/d ug/kg 1/day for 14 consecutive days 19 %dose levels: 0.010, 0.050, 0.100, 0.500, 1.0, 2.0 ug /kg/d ug/kg 1/day for 14 consecutive days 20 21 MAXT = 0.01 22 CINT = 0.1 23 TIMELIMIT = 336 24 EXP_TIME_ON = 0. %TIME AT WHICH EXPOSURE BEGINS (HOUR) 25 EXP_TIME_OFF = 336 %TIME AT WHICH EXPOSURE ENDS (HOUR) 26 DAY_CYCLE = 24 27 WEEK_PERIOD = 336 28 WEEK_FINISH = 336 29 BCK_TIME_ON = 0. %TIME AT WHICH BACKGROUND EXPOSURE BEGINS 30 (HOUR) 31 BCK_TIME_OFF = 0. %TIME AT WH ICH BACKGROUND EXPOSURE ENDS (HOUR) 32 BW_T0 = 23 % BODY WE IGHT AT THE BEGINNING OF THE SIMULATION (G) 33 34 %EXPOSURE DOSE SCENARIOS (UG/KG) 35 %MSTOT = 0.010 % EXPOSURE DOSE IN UG/KG 36 %MSTOT = 0.050 % EXPOSURE DOSE IN UG/KG 37 %MSTOT = 0.100 % EXPOSURE DOSE IN UG/KG 38 %MSTOT = 0.500 % EXPOSURE DOSE IN UG/KG 39 %MSTOT = 1 % EXPOSURE DOSE IN UG/KG 40 MSTOT = 2 % EXPOSURE DOSE IN UG/KG 41 42
43

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-100 DRAFT

— DO NOT CITE OR QUOTE C.2.6. Mouse Gestational Model 1 C.2.6.1. Model Code 2
PROGRAM : 'Three Compartment PBPK Mode l for TCDD in Mice (Gestation)' 3 ! Parameters were change may 16, 2002 4 ! Come from {8MAI_CHR_PRE-EXP_GD} 5 ! Come from {12_Mouse_GD}file 6 !******************************************** 7 !{{IMPORTANT-IMPORTANT-IMPORTANT-IMPORTANT}} 8 ! REDUCTION OF MOTHER AND FETUS COMPARTMENT 9 ! 2M_R_TCDD_JULY2002 ////(JULY 18,2002)//// 10 !TCDD_RED_4Species_2003_4 ////(APR 8 ,2003)//// 11 !TCDD_RED_4Species_2003_9 ////(APR 17 ,2003)//// 12 !TCDD_RED_4Species_2003_12 ////(APR 17 ,2003)//// 13 !***************************************************** 14 !APRIL 18 2003 15 !TCDD_4C_4SP_2003 ////(APR 18 ,2003)//// 16 ! was ''Gest 4 species 1.csl'' but update July 2009 17 18 !DevTCDD4Species_ICF_aft erKKfix_v3_ratgest.csl 19 !MICE_GESTATIONAL_ICF_F092309.csl 20 !MICE_GESTATIONAL_ICF_F100609.csl 21 !***************************************************** 22 23!Legend/Legend/Legend/Legend/ Legend/Legend/Legend/Legend/ 24 !Legend for this PBPK model 25 !Mating: control the tenure of exchange between fetus and 26 !Mother and also cont rol imitated tissue growth 27 !Ctrl: WTFE, WFO, WPLA0, QPLAF,WT0 28 !(for rat, mouse, human, and monkey) 29 !Control transfer from mother to fetus and fetus to mother by TRANSTIME_ON 30 !SWITCH_trans = 0 NO TRANSFER 31 !SWITCH_trans = 1 TRANSFER OCCURS 32 !Gest_off = 1 33 !Gest_on= 0. 34 ! These switches are also controlled by mating parameters 35 36 INITIAL ! 37 38!SIMULATION PARAMETERS ==== 39 CONSTANT PARA_ZERO = 1E-30 40 CONSTANT EXP_TIME_ON = 288. ! TIME AT WHICH EXPOSURE BEGINS 41 (HOURS) 42 CONSTANT EXP_TIME_OFF = 504 ! TIME AT WHICH EXPO SURE ENDS (HOURS) 43 CONSTANT DAY_CYCLE = 504. ! NUMBER OF HOURS BETWEEN DOSES 44 (HOURS) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-101 DRAFT

— DO NOT CITE OR QUOTE CONSTANT BCK_TIME_ON = 0.0 ! TIME AT WHICH BACKGROUND EXPOSURE 1 BEGINS (HOURS) 2 CONSTANT BCK_TIME_OFF = 0.0 ! TIME AT WHICH BACKGROUND EXPOSURE 3 ENDS (HOURS) 4 CONSTANT TRANSTIME_ON = 144 !CONTROL TRANSFER FROM MOTHER TO 5 FETUS AT GESTATIONAL DAY 6 6 7!UNIT CONVERSION 8 CONSTANT MW=322 ! MOLECUL AR WEIGHT (NG/NMOL) 9 CONSTANT SERBLO = 0.55 10 CONSTANT UNITCORR = 1000 11 12!INTRAVENOUS SEQUENCY 13 constant IV_LACK = 0.0 14 constant IV_PERIOD = 0.0 15 16!PREGNANCY PARAMETER ==== 17 CONSTANT MATTING = 0.0 !BEGINNING OF MATING (HOUR) 18 CONSTANT N_FETUS = 10 !NUMBER OF FETUS PRESENT 19 20!CONSTANT EXPOSURE CONTROL =========== 21 !ACUTE, SUBCHRONIC , CHRONIC EXPOSURE ===== 22 !OR BACKGROUND EXPOSURE (IN THIS CASE 3 TIMES A DAY)=== 23 CONSTANT MSTOTBCKGR = 0.0 ! ORAL BACKGROUND EXPOSURE DOSE 24 (UG/KG) 25 CONSTANT MSTOT = 0.0 ! ORAL EXPOSURE DOSE (UG/KG) 26 27!ORAL ABSORPTION 28 MSTOT_NM = MSTOT/MW !CONVERTS THE DOSE TO NMOL/G 29 30 ! INTRAVEN OUS ABSORPTION 31 CONSTANT DOSEIV = 0.0 ! INJECTED DOSE (UG/KG) 32 DOSEIV_NM = DOSEIV/MW ! CONVERTS THE INJECTED DOSE TO NMOL/G 33 CONSTANT DOSEIVLATE = 0.0 ! INJECTED DOSE LATE (UG/KG) 34 DOSEIVNMlate = DOSEIVLATE/MW !AMOUNT IN NMOL/G 35 36!INITIAL GUESS OF THE FREE CONCENTRATION IN THE LIGAND 37 (COMPARTMENT INDICATED BELOW)==== 38 CONSTANT CFLLI0 = 0.0 !LIVER (NMOL/ML) 39 CONSTANT CFLPLA0 = 0.0 !PLACENTA (NMOL/ML) 40 41!BINDING CAPACI TY (AhR) FOR NON LINEAR BINDING (COMPARTMENT 42 INDICATED BELOW) (NMOL/ML) === 43 CONSTANT LIBMAX = 3.5E-4 ! LIVER (NMOL/ML), WANG ET AL. 1997 44 CONSTANT PLABMAX = 2.0E-4 !TEMPORARY PARAMETER 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-102 DRAFT

— DO NOT CITE OR QUOTE ! PROTEIN AFFINITY CONSTANTS (1A2 OR AhR, COMPARTMENT INDICATED 1 BELOW) (NMOL/ML)=== 2 CONSTANT KDLI = 1.0E-4 !LIVER (AhR) (NMOL/ML), WANG ET AL. 1997 3 CONSTANT KDLI2 = 4.0E-2 !LIVER (1A2) (NMOL/ML), EMOND ET AL. 2004 4 CONSTANT KDPLA = 1.0E-4 !TEMPORARY PARAMETER (AhR) 5 6!EXCRETION AND ABSORPTION CONSTANT 7 CONSTANT KST = 0.3 ! GASTRIC RATE CONSTANT (HR-1) 8 CONSTANT KABS = 0.48 !INTESTINAL ABSORPTION CONSTANT (HR-1) ), 9 WANG ET AL. 1997 10 11 ! ELIMINATION CONSTANTS 12 CONSTANT CLURI = 0.09 ! URINARY CLEARANCE (ML/HR) 13 14 !TEST ELIMINATION VARIABLE 15 constant kelv = 0.4 ! INTERSPECIES VAR IABLE ELIMINATI ON CONSTANT 16 (1/HOUR) 17 18! CONSTANT TO DIVIDE THE AB SORPTION INTO LYMPHATIC AND PORTAL 19 FRACTIONS 20 CONSTANT A = 0.7 ! LYMPHATIC FRACTION, WANG ET AL. 1997 21 22!PARTITION COEFFICIENTS 23 CONSTANT PF = 400 ! ADIPOSE TISSUE/BLOOD 24 CONSTANT PRE = 3 ! REST OF THE BODY/BLOOD, WANG ET AL. 2000 25 CONSTANT PLI = 6 ! LIVER/BLOOD, WANG ET AL. 1997 26 CONSTANT PPLA = 3 ! TEMPORARY PARAMETER NOT CONFIGURED 27 28!PARAMETER FOR INDUCTION OF CY P 1A2, WANG ET AL. 1997 OR OPTIMIZED 29 CONSTANT PAS_INDUC = 1 ! INCLUDE INDUCTION? (1 = YES, 0 = NO) 30 CONSTANT CYP1A2_1OUTZ = 1.6 ! DEGRADATION CONCENTRATION 31 CONSTANT OF 1A2 (NMOL/ML) (OPTIMIZED) 32 CONSTANT CYP1A2_1A1 = 1.5 ! BASAL CONCENTRATIO N OF 1A1 (NMOL/ML), 33 WANG ET AL . (2000) 34 CONSTANT CYP1A2_1EC50 = 0.13 ! DISSOCIATION CONSTANT TCDD-CYP1A2 35 (NMOL/ML) 36 CONSTANT CYP1A2_1A2 = 1.5 !BASAL CONCENTRATION OF 1A2 37 (NMOL/ML),WANG ET AL. (2000) 38 CONSTANT CYP1 A2_1KOUT = 0.1 ! FIRST ORDER RATE OF DEGRADATION (H-1) 39 CONSTANT CYP1A2_1TAU = 1.5 !HOLDING TIME (H) (OPTIMIZED), WANG ET 40 AL . (2000) 41 CONSTANT CYP1A2_1EMAX = 600 ! MAXIMUM INDUCTION OVER BASAL 42 EFFECT (UNITLESS) 43 CONSTANT HILL = 0.6 !HILL CONSTANT; COOPERATIVELY LIGAND 44 BINDING EFFECT CONS TANT (UNITLESS) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-103 DRAFT

— DO NOT CITE OR QUOTE !DIFFUSIONAL PERMEABILI TY FRACTION, WANG ET AL. 1997 1 CONSTANT PAFF = 0.12 !ADIPOSE (UNITLESS) OPTIMIZED, WANG ET AL. 2 2000 3 CONSTANT PAREF = 0.03 !REST OF TH E BODY (UNITLESS) 4 CONSTANT PALIF = 0.35 !LIVER (UNITLESS) 5 CONSTANT PAPLAF = 0.03 !TEMPORARY PARAMETER NOT CONFIGURED 6 7!FRACTION OF TISSUE WEIGHT ========= 8 CONSTANT WLI0 = 0.0549 !LIVER ILSI (1994) 9 10!TISSUE BLOOD FLOW EXPRESSED AS A FRACTION OF CARDIAC OUTPUT 11 CONSTANT QFF = 0.070 ! ADIPOSE TISSUE BLOOD FLOW FRACTION 12 (UNITLESS), LEUNG ET AL. 1990 13 CONSTANT QLIF = 0.161 !LIVER (UNITLESS), ILSI 1994 14 15!COMPARTMENT TISSUE BLOOD EXPR ESSED AS A FRACTION OF THE TOTAL 16 COMPARTMENT VOLUME 17 CONSTANT WFB0 = 0.050 !ADIPOSE TISSUE, WANG ET AL. 1997 18 CONSTANT WREB0 = 0.030 !REST OF THE BODY, WANG ET AL. 1997 19 CONSTANT WLIB0 = 0.266 !LIVER, WANG ET AL. 1997 20 CONSTANT WPLAB0 = 0.500 !TEMPORARY PARAM ETER NOT CONFIGURED 21 22!EXPOSURE SCENARIO FOR UNIQUE OR REPETITIVE WEEKLY OR MONTHLY 23 EXPOSURE 24 !NUMBER OF EXPOSURES PER WEEK 25 CONSTANT WEEK_LACK = 0.0 !DELAY BEFORE EXPO SURE ENDS (WEEK) 26 CONSTANT WEEK_PERIOD = 168 ! NUMBER OF HOURS IN THE WEEK (HOURS) 27 CONSTANT WEEK_FINISH = 168 ! TIME EXPOSURE ENDS (HOURS) 28 29!NUMBER OF EXPOSURES PER MONTH 30 CONSTANT MONTH_LACK = 0.0 !DELAY BEFORE EXPOSURE BEGINS 31 (MONTH) 32 33!CONSTANT FOR BACKGROUND EXPOSURE=========== 34 CONSTANT Day_LACK_BG = 0.0 ! DELAY BEFORE EXPOSURE BEGINS (HOUR) 35 CONSTANT Day_PERIOD_BG = 24 !LENGTH OF EXPOSURE (HOUR) 36 37!NUMBER OF EXPOSURES PER WEEK 38 CONSTANT W EEK_LACK_BG = 0.0 !DELAY BE FORE BACKGROUD EXPOSURE 39 (WEEK) 40 CONSTANT WEEK_PERIOD_BG = 168 ! NUMBER OF HOURS IN THE WEEK 41 (HOURS) 42 CONSTANT WEEK_FINISH_BG = 168 !TIME EXPOSURE ENDS (HOURS) 43 44!INITIAL BODY WEIGHT 45 CONSTANT BW_T0 = 30 ! WANG ET AL. 1997 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-104 DRAFT

— DO NOT CITE OR QUOTE CONSTANT RATIO_RATF_MOUSEF = 0.2 !RATIO OF FETUS MOUSE/RAT AT 1 GESTATIONAL DAY 22 2 ! FOR RAT (1) AND FOR MOUSE (0.2) 3 4!COMPARTMENT LIPID EXPRESSED AS THE FRACTION OF TOTAL LIPID, POULIN 5 ET AL. 2002 6 CONSTANT F_TOTLIP = 0.855 ! ADIPOSE TISSUE (UNITLESS) 7 CONSTANT B_TOTLIP = 0.0033 ! BLOOD (UNITLESS) 8 CONSTANT RE_TOTLIP = 0.019 ! REST OF THE BODY (UNITLESS) 9 CONSTANT LI_TOTLIP = 0.060 ! LIVER (UNITLESS) 10 CONSTANT PLA_TOTLIP = 0.019 ! PLACENTA (UNITLESS) 11 CONSTANT FETUS_TOTLIP = 0.019 ! FETUS (UNITLESS) 12 13 END ! END OF THE INITIAL SECTION 14 15 DYNAMIC ! DYNAMIC SI MULATION SECTION 16 ALGORITHM IALG = 2 ! GEAR METHOD 17 CINTERVAL CINT = 0.1 ! COMMUNICATION INTERVAL 18 MAXTERVAL MAXT = 1.0e+10 ! MAXIMUM CALCULATION INTERVAL 19 MINTERVAL MINT = 1.0E-10 ! MINIMUM CALCULATION INTERVAL 20 VARIABLE T = 0.0 21 CONSTANT TIMELIMIT = 313 !SIMULATION LIMIT TIME (HOUR) 22 CINTXY = CINT 23 PFUNC = CINT 24 25!TIME CONVERSION 26 DAY = T/24 ! TIME IN DAYS 27 WEEK = T/168 ! TIME IN WEEKS 28 MONTH = T/730 ! TIME IN MONTHS 29 YEAR = T/8760 ! TIME IN YEARS 30 31 DERIVATIVE ! PORTION OF CODE THAT SOLVES DIFFERENTIAL EQUATIONS 32 33!CHRONIC OR SUBCHRONI C EXPOSURE SCENARIO ======= 34 !NUMBER OF EXPOSURES PER DAY 35 DAY_LACK = EXP_TIME_ON ! DELAY BEFORE EXPOSURE BEGINS (HOURS) 36 DAY_PERIOD = DAY_CYCLE ! EXPOSURE PERIOD (HOURS) 37 DAY_FINISH = CINTXY ! LENGTH OF EXPOSURE (HOURS) 38 MONTH_PERIOD = TIMELIMIT ! EXPOSURE PERIOD (MONTHS) 39 MONTH_FINISH = EXP_TIME_OFF ! LENGTH OF EXPOSURE (MONTHS) 40 41!NUMBER OF EXPOSURES PER DAY AND MONTH 42 DAY_ FINISH_BG = CINTXY 43 MONTH_LACK_BG = BCK_TIME_ON !DELAY BEFORE BACKGROUD EXPOSURE 44 BEGINS (MONTHS) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-105 DRAFT

— DO NOT CITE OR QUOTE MONTH_PERIOD_BG = TIMELIMIT !BACKGROUND EXPOSURE PERIOD 1 (MONTHS) 2 MONTH_FINISH_BG = BCK_TIME_OFF !LENGTH OF BACKGROUND EXPOSURE 3 (MONTHS) 4 5!INTRAVENOUS LATE 6 IV_FINISH = CINTXY 7 B = 1-A ! FRACTION OF DIOXIN ABSO RBED IN THE PORTAL FRACTION OF THE 8 LIVER 9 10 11 !FETUS,VOLUME,FETUS,VOLUME,FETUS,VOLUME,FETUS,VOLUME,FETUS,VOLUM 12 E,FETUS,VOLUME 13 ! FROM OFLAHERTY_1992 14 15 RTESTGEST= T-MATTING 16 TESTGEST=DIM(RTESTGEST,0.0) 17 18 WTFER_RODENT= (2.3d-3*EXP(1.49d- 2*(TESTGEST))+1.3d-2)*Gest_on 19 WTFER = (WTFER_RODENT*RAT IO_RATF_MOUSEF*N_FETUS) 20 WTFE = DIM(WTFER,0.0) 21 22! 23 FAT,VOLUME,FAT,VOLUME,FAT,VOLUME,FAT,VOLUME,FAT,VOLUME,FAT,VOLU 24 ME,FAT,VOLUME 25 ! FAT GROWTH EXPRESSION LINEAR DURING PREGNANCY 26 ! FROM O'FLAHERTY_1992 27 28 WF0= (((9.66d-5*(TESTGEST))*gest_on)+0.069) 29 30! PLACENTA,VOLUME, PLACENTA,VOLUME, PLACENTA,VOLUME, 31 PLACENTA,VOLUME 32 ! WPLA PLACENTA GROW TH EXPRESSION, SINGLE EXPONENTIAL WITH OFFSET 33 ! FROM O'FLAHERTY_1992 ! FOR EACH PUP 34 35 WPLA0N_RODENT = (0.6/(1+(5d+ 3*EXP(-0.0225*(TESTGEST)))))*N_FETUS 36 WPLA0R = (WPLA0N_R ODENT/WT0)*Gest_on 37 WPLA0 = DIM(WPLA0R,0.0) 38 39! PLACENTA,FLOW RATE, PLACENTA ,FLOW RATE, PLACENTA,FLOW RATE, 40 PLACENTA,FLOW RATE 41 ! QPLA PLACENTA GROWTH EXPRESSI ON, DOUBLE EXPONENTIAL WITH OFFSET 42 ! FROM O'FLAHERTY_1992 43 44QPLARF = (1.67d-7 *exp(9.6d-3*(TESTGEST)) & 45 +1.6d-3*exp(7.9d-3*(TESTGEST ))+0.0)*Gest_on*SWITCH_trans 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-106 DRAFT

— DO NOT CITE OR QUOTE QPLAF=DIM(QPLARF,0.0) !FRACTION OF FLOW RATE IN PLACENTA 1 2! GESTATION CONTROL 3 IF (T.LT.MATTING) THEN 4 Gest_off = 1 5 Gest_on= 0.0 6 ELSE 7 Gest_off = 0.0 8 Gest_on = 1 9 END IF 10 11! MOTHER BODY WEIGHT GROWTH EQUATION======== 12 ! MODIFICATION TO ADAPT THIS MODEL AT HUMAN MODEL 13 ! BECAUSE LINEAR DESCRIPTION IS NOT GOOD ENOUGH FOR MOTHER GROWTH 14 ! MOTHER BODY WEIGHT GROWTH 15 16PARAMETER (BW_RMN = 1.0E-30) 17 WT0= BW_T0 *(1.0+( 0.41*T)/(1402.5+T+BW_RMN)) 18 19 ! VARIABILITY OF REST OF THE BODY DEPENDS ON OTHER ORGANS 20 WRE0 = (0.91 - (WLIB0*WLI0 + WFB0 *WF0 +WPLAB0*WPLA0 + WLI0 + WF0 + 21 WPLA0))/(1.0+WREB0) ! REST OF TH E BODY FRACTION; UPDATED FOR EPA 22 ASSESSMENT 23 QREF = 1.0-(QFF+QLIF+QPLAF) !REST OF BODY BLOOD FLOW RATE (ML/HR) 24 QTTQF = QFF+QREF+QLI F+QPLAF ! SUM MUST EQUAL 1 25 26! COMPARTMENT VOLUME (ML OR G) ========= 27 WF = WF0 * WT0 ! ADIPOSE TISSUE 28 WRE = WRE0 * WT0 ! REST OF THE BODY 29 WLI = WLI0 * WT0 ! LIVER 30 WPLA= WPLA0* WT0 ! PLACENTA 31 32! COMPARTMENT TISSUE BLOOD (ML OR G) ========= 33 WFB = WFB0 * WF ! ADIPOSE TISSUE 34 WREB = WREB0 * WRE ! REST OF THE BODY 35 WLIB = WLIB0 * WLI ! LIVER 36 WPLAB = WPLAB0* WPLA ! PLACANTA 37 38! CARDIAC OUTPUT FOR THE GIVEN BODY WEIGHT 39 !QC= QCCAR*60*(WT0/1000.0)**0.75 40 CONSTANT QCC=16500 ! EQUIVALENT TO 275 * 60 41 QC= QCC*(WT0/UNITCORR)**0.75 42 43!COMPARTMENT B LOOD FLOW RATE (ML/HR) 44 QF = QFF*QC !ADIPOSE TISSUE BLOOD FLOW RATE 45 QLI = QLIF*QC !LIVER TISSUE BLOOD FLOW RATE 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-107 DRAFT

— DO NOT CITE OR QUOTE QRE = QREF*QC !REST OF THE BODY BLOOD FLOW RATE 1 QPLA = QPLAF*QC !PLACENTA TISSUE BLOOD FLOW RATE 2 QTTQ = QF+QRE+QLI+QPLA !TOTAL FLOW RATE 3 4!PERMEABILITY OR GAN FLOW (ML/HR)========= 5 PAF = PAFF*QF ! ADIPOSE TISSUE 6 PARE = PAREF*QRE ! REST OF THE BODY 7 PALI = PALIF*QLI ! LIVER TISSUE 8 PAPLA = PAPLAF*QPLA ! PLACENTA 9 10!************************************** 11 ! ABSORPTION SECTION 12 ! ORAL, 13 ! INTRAPERITONEAL, 14 ! INTRAVENOUS 15 !************************************** 16 17!REPETITIVE ORAL BACKGROUND EXPOSURE SCENARIO 18 19 MSTOT_NMBCKGR = MSTOTBCKGR/322 !AMOUNT IN NMOL/G 20 MSTTBCKGR =MSTOT_NMBCKGR *WT0 21 22 DAY_EXPOSURE_BG = PULSE(DAY_LACK _BG,DAY_PERIOD_BG,DAY_FINISH_BG) 23 WEEK_EXPOSURE_BG = 24 PULSE(WEEK_LACK_BG,WEEK_PERIOD_BG,WEEK_FINISH_BG) 25 MONTH_EXPOSURE_BG = 26 PULSE(MONTH_LACK_BG,MONTH_PERIOD_BG,MONTH_FINISH_BG) 27 28 MSTTCH_BG = 29 (DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG)*MSTTBCK 30 GR 31 MSTTFR_BG = MSTTBCKGR/CINT 32 33 CYCLE_BG =DAY_EXPOSURE_BG*WEEK_EXPOSURE_BG*MONTH_EXPOSURE_BG 34 35! CONDITIONAL ORAL EXPOSURE (BACKGROUND EXPOSURE) 36 37 IF (MSTTCH_BG.EQ.MSTTBCKGR) THEN 38 ABSMSTT_GB= MSTTFR_BG 39 ELSE 40 ABSMSTT_GB = 0.0 41 END IF 42 43 CYCLETOTBG=INTE G(CYCLE_BG,0.0) 44 45!REPETITIVE ORAL EXPOSURE SCENARIO 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-108 DRAFT

— DO NOT CITE OR QUOTE 1 MSTT= MSTOT_NM * WT0 !AMOUNT IN NMOL 2 3 DAY_EXPOSURE = PULSE(DAY_LACK,DAY_PERIOD,DAY_FINISH) 4 WEEK_EXPOSURE = PULSE(WEEK_LACK,WEEK_PERIOD,WEEK_FINISH) 5 MONTH_EXPOSURE = PULSE(MONTH_LA CK,MONTH_PERIOD,MONTH_FINISH) 6 7 MSTTCH = (DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE)*MSTT 8 MSTTFR = MSTT/CINT 9 10 CYCLE = DAY_EXPOSURE*WEEK_EXPOSURE*MONTH_EXPOSURE 11 SUMEXPEVENT= INTEG (CYCLE,0.0)/cin t !NUMBER OF CYCLES GENERATED 12 DURING SIMULATION 13 14! CONDITIONAL ORAL EXPOSURE 15 IF (MSTTCH.EQ.MSTT) THEN 16 ABSMSTT= MSTTFR 17 ELSE 18 ABSMSTT = 0.0 19 END IF 20 21 22CYCLETOT=INTEG(CYCLE,0.0) 23 24! MASS CHANGE IN THE LUMEN 25 RMSTT= -(KST+KABS)*MST +ABSMSTT +ABSMSTT_GB ! RATE OF CHANGE 26 (NMOL/H) 27 MST = INTEG(RMSTT,0.0) !AMOUNT REMAINING IN DUODENUM 28 (NMOL) 29 30! ABSORPTION IN LYMPH CIRCULATION 31 LYRMLUM = KABS*MST*A 32 LYMLUM = INTEG(LYRMLUM,0.0) 33 34! ABSORPTION IN PORTAL CIRCULATION 35 LIRMLUM = KABS*MST*B 36 LIMLUM = INTEG(LIRMLUM,0.0) 37 38 39 ! -----IV EXPOSURE --------- 40 41IV= DOSEIV_NM * WT0 !AMOUNT IN NMOL 42 IVR= IV/PFUNC ! RATE FO R IV INFUSION IN BLOOD 43 EXPIV= IVR * (1.0-STEP(PFUNC)) 44 IVDOSE = integ(EXPIV,0.0) 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-109 DRAFT

— DO NOT CITE OR QUOTE !------IV late in the cycle 1 ! MODIFICATION ON January 13 2004 2 IV_RlateR = DOSEIVNMlate*WT0 3 IV_EXPOSURE=PULSE(IV_LACK,IV_PERIOD,IV_FINISH) 4 5IV_lateT = IV_EXPOSURE *IV_RlateR 6 IV_late = IV_lateT/CINT 7 8 SUMEXPEVENTIV= integ (IV_EXPOSUR E,0.0) !NUMBER OF CYCLE GENERATE 9 DURING SIMULATION 10 11!SYSTEMIC CONCENTRATION OF TCDD 12 ! MODIFICATION ON OCTOBER 6, 2009 13 14 CB=(QF*CFB+QRE*CREB+QLI*CLIB+EXPIV+ LYRMLUM+QPLA*CPLAB+IV_late)/(QC 15 +CLURI) ! 16 CA = CB ! CONCENTRATION (NMOL/ML) 17 18!URINARY EXCRETION BY KIDNEY 19 !MODIFICATION ON OCTOBER 6, 2009 20 RAURI = CLURI *CB 21 AURI = INTEG(RAURI,0.0) 22 23!UNIT CONVERSION POST SIMULATION 24 CBSNGKGLIADJ=(CB*MW*UNI TCORR*(1/B_TOTLIP)*( 1/SERBLO))![NG of TCDD 25 Serum/Kg OF LIPIP] 26 AUCBS_NGKGLIADJ=i nteg(CBSNGKGLIADJ,0.0) 27 28PRCT_B = (CB/(MSTT+1E-30))*100 ! PERCENT OF ORAL DOSE IN BLOOD 29 PRCT_BIV = (CB/(IV_RlateR+1E-30)) *100 ! PERCENT OF IV DOSE IN BLOOD 30 CBNGKG= CB*MW*UNITCORR 31 CBNGG = CB*MW 32 33!ADIPOSE COMPARTMENT 34 !TISSUE BLOOD COMPARTMENT 35 RAFB= QF*(CA-CFB)-PAF*(CFB-CF/PF) !(NMOL/H) 36 AFB = INTEG(RAFB,0.0) !(NMOL) 37 CFB = AFB/WFB !(NMOL/ML) 38 !TISSUE COMPARTMENT 39 RAF = PAF*(CFB-CF/PF) !(NMOL/H) 40 AF = INTEG(RAF,0.0) !(NMOL) 41 CF = AF/WF !(NMOL/ML) 42 43!UNIT CONVERSION POST SIMULATION 44 CFTOTAL= (AF + AFB)/(WF + WFB) ! TOTAL CONCENTRATION IN NMOL/ML 45 CFTFREE = CFB + CF !TOTAL FR EE CONCENTRATION IN FAT (NM/ML) 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-110 DRAFT

— DO NOT CITE OR QUOTE PRCT_F = (CFTOTAL/(MSTT+1E-30)) *100 ! PERCENT OF ORAL DOSE IN FAT 1 PRCT_FIV = (CFTOTAL/(IV_RlateR+1E- 30))*100 ! PERCENT OF IV DOSE IN FAT 2 CFNGKG=CFTOTAL*MW*UNITCORR ! FAT CONCENTRATION IN NG/KG 3 AUCF_NGKGH=integ(CFNGKG,0.0) 4 CFNGG = CFTOTAL*MW 5 6!REST OF THE BODY COMPARTMENT 7 RAREB= QRE *(CA-CREB)-PARE* (CREB-CRE/PRE) !(NMOL/H) 8 AREB = INTEG(RAREB,0.0) !(NMOL) 9 CREB = AREB/WREB !(NMOL/H) 10 !TISSUE COMPARTMENT 11 RARE = PARE*(CREB - CRE/PRE) !(NMOL/H) 12 ARE = INTEG(RARE,0.0) !(NMOL) 13 CRE = ARE/WRE !(NMOL/ML) 14 15!UNIT CONVERSION POST SIMULATION 16 CRETOTAL= (ARE + AREB)/(WRE + WREB) ! TOTAL CONCENTRATION IN 17 NMOL/ML 18 PRCT_RE = (CRETOTAL/(MSTT+1E-30))*100 ! PERCENT OF ORAL DOSE IN REST OF 19 BODY 20 PRCT_REIV = (CRETOTAL/(IV_RlateR+1E-30)) *100 ![ PERCENT OF IV DOSE IN REST 21 OF THE BODY ] 22 CRENGKG=CRETOTAL*MW*UNITCORR ! REST OF THE BODY CONCENTRATION 23 IN NG/KG 24 25 26!LIVER COMPARTMENT 27 !TISSUE BLOOD COMPARTMENT 28 RALIB = QLI*(CA-CLIB)-PALI*(CLIB-CFLLIR)+LIRMLUM ! 29 ALIB = INTEG(RALIB,0.0) !(NMOL) 30 CLIB = ALIB/WLIB !(NMOL/ML) 31 !TISSUE COMPARTMENT 32 RALI = PALI*(CLIB - CFLLIR)-REXCLI ! (NMOL/HR) 33 ALI = INTEG(RALI,0.0) !(NMOL) 34 CLI = ALI/WLI !(NMOL/ML) 35 36!FREE TCDD IN LIVER COMPARTMENT 37 PARAMETER (LIVER_1RMN = 1.0E-30) 38 CFLLI= IMPLC(CLI-(CFLLIR*PLI+(LIBMAX*CFLLIR/(KDLI+CFLLIR & 39 +LIVER_1RMN))+((CYP 1A2_1O3*CFLLIR/(KDLI2 + CFLLIR & 40 +LIVER_1RMN )*PAS_INDUC)))-CFLLI,CFLLI0) 41 CFLLIR=DIM(CFLLI,0.0) ! FREE CONCENTRATION IN LIVER 42 43CBNDLI= LIBMAX*CFLLIR/(KDL I+CFLLIR+LIVER_1RMN) !BOUND 44 CONCENT RATION 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-111 DRAFT

— DO NOT CITE OR QUOTE !VARIABLE ELIMINATION BASED ON THE CYP1A2 1 KBILE_LI_T =((CYP1A2_1OUT-CYP1A2_1A2)/CYP1A2_1A2)*Kelv ! INDUCED 2 BILIARY EXCRETION RATE CONSTANT 3 REXCLI = KBILE_LI_T*CFLLIR*WL I ! DOSE-DEPENDENT EXCRETION RATE 4 EXCLI = INTEG(REXCLI,0.0) 5 6!UNIT CONVERSION POST SIMULATION 7 CLITOTAL= (ALI + ALIB)/(WLI + WL IB) ! TOTAL CONCENTRATION IN NMOL/ML 8 PRCT_LI = (CLITOTAL/(MSTT+1E-30 ))*100 ! PERCENT ORAL DOSE IN LIVER 9 PRCT_LIIV = (CLITOTAL/(IV_RlateR+1E -30))*100 ! PERCENT IV DOSE IN LIVER 10 Rec_occ= CFLLIR/(KDLI+CFLLIR) 11 CLINGKG=CLITOTAL*MW*UNITCORR ! LIVER CONCENTRATION IN NG/KG 12 AUCLI_NGKGH=INTEG(CLINGKG,0.0) 13 CBNDLINGKG = CBNDLI*MW*UNITCORR 14 AUCBNDLI_NGKGH =INTEG(CBNDLINGKG,0.0) 15 CLINGG = CLITOTAL*MW 16 17!CHEMICAL IN CYP450 (1A2) COMPARTMENT 18 CYP1A2_1KINP = CYP1A2_1KOUT* CYP1 A2_1OUTZ ! BASAL RATE OF CYP1A2 19 PRODUCTION SET EQUAL TO BASAL RATE OF DEGREDATION 20 21! MODIFICATION ON OCTOBER 6, 2009 22 CYP1A2_1OUT =INTEG(CYP1A2_1KINP * (1.0 + CYP1A2_1EMAX *(CBNDLI+1.0e23 30)**HILL & 24 /(CYP1A2_1EC50**HILL + (CBNDLI+1.0e-30)**HILL)) & 25 - CYP1A2_1KOUT*CYP1A2_1OUT, CYP1A2_1OUTZ) 26 27 ! EQUATIONS INCORPORATING DELAY OF CYP1A2 PRODUCTION (NOT USED IN 28 SIMULATIONS) 29 30CYP1A2_1RO2 = (CYP1A2_1OUT - CYP1A2_1O2)/ CYP1A2_1TAU 31 CYP1A2_1O2 =INTEG(CYP1A2_1RO2, CYP1A2_1A1) 32 33 CYP1A2_1RO3 = (CYP1A2_1O2 - CYP1A2_1O3)/ CYP1A2_1TAU 34 CYP1A2_1O3 =INTEG(CYP1A2_1RO3, CYP1A2_1A2) 35 36 ! TRANSFER OF DIOXIN FROM PLACENTA TO FETUS 37 ! FETAL EXPOSURE ONLY DURING EXPOSURE 38 39 IF (T.LT.TRANSTIME_ON) THEN 40 SWITCH_trans = 0.0 41 ELSE 42 SWITCH_trans = 1 43 END IF 44 45 !TRANSF ER OF DIOXIN FROM PLACENTA TO FETUS 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-112 DRAFT

— DO NOT CITE OR QUOTE ! MODIFICATION 26 SEPTEMBER 2003 1 2 CONSTANT PFETUS= 4 ! 3 CONSTANT CLPLA_FET = 0.17 ! 4 5 RAMPF = (CLPLA_FET*CPLA) *SWITCH_trans 6 AMPF=INTEG(RAMPF,0.0) 7 8 !TRANSFER OF DIOXIN FROM FETUS TO PLACENTA 9 RAFPM = (CLPLA_FET*CFETUS_v)*SWITCH_trans ! 10 AFPM = INTEG(RAFPM,0.0) 11 12 ! TCDD IN PLACENTA MOTHER COMPARTMENT 13 RAPLAB= QPLA*(CA - CPLAB)-PAPLA *(CPLAB -CFLPLAR) ! NMOL/H) 14 APLAB = INTEG(RAPLAB,0.0) ! (NMOL) 15 CPLAB = APLAB/(WPLAB+1E-30) ! (NMOL/ML) 16 RAPLA = PAPLA*(CPLAB-CFLPLAR)-RAMPF + RAFPM ! (NMOL/H) 17 APLA = INTEG(RAPLA,0.0) ! (NMOL) 18 CPLA = APLA/(WPLA+1e-30) ! (NMOL/ML) 19 20 PARAMETER (PARA_ZERO = 1.0E-30) 21 CFLPLA= IMPLC(CPLA-(CFLPLAR*PPLA +(PLABMAX*CFLPLAR/(KDPLA& 22 +CFLPLAR+PARA_ZERO)))-CFLPLA,CFLPLA0) 23 CFLPLAR=DIM(CFLPLA,0.0) 24 25!UNIT CONVERSION POST SIMULATION 26 CPLATOTAL= (APLA + APLAB) /((WPLA + WPLAB)+1e-30)! TOTAL 27 CONCENTRATION IN NMOL/ML 28 PRCT_PLA = (CPLATOTAL/(MSTT+1E-30))*100 29 PRCT_PLAIV = (CPLATOTAL/(IV_RlateR+1E-30))*100 30 CPLANGG = CPLATOTAL*MW 31 32!FETUS COMPARTMENT 33 RAFETUS= RAMPF-RAFPM 34 AFETUS=INTEG(RAFETUS,0.0) 35 CFETUS=AFETUS/(WTFE+1E-30) 36 CFETOTAL= CFETUS 37 CFETUS_v = CFETUS/PFETUS 38 39! UNIT CONVERSION POST SIMULATION 40 CFETUSNGKG = CFETUS*MW*UNITCORR !(NG/KG) 41 AUC_FENGKGH = INTEG(CFETUSNGKG,0.0) 42 PRCT_FE = (CFETOTAL/(MSTT+1E-30))*100 43 PRCT_FEIV = (CFETOTAL/(IV_RlateR+1E-30))*100 44 CFETUSNGG = CFETOTAL*MW 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-113 DRAFT

— DO NOT CITE OR QUOTE ! ------------CONTROL MASS BALANCE ---------- 1 BDOSE= IVDOSE +LYMLUM+LIMLUM 2 BMASSE = EXCLI+AURI+AFB+AF+AREB +ARE+ALIB+ALI+APLA+APLAB+AFETUS 3 BDIFF = BDOSE-BMASSE 4 5!BODY BURDEN (NG) 6 BODY_BURDEN = AFB+AF+AREB+ARE+ALIB+ALI+APLA+APLAB ! 7 BBFETUSNG = AFETUS*MW*UNITCORR ! NG 8 ! BODY BURDEN IN TERMS OF CONCENTRATION (NG/KG) 9 BBNGKG 10 =(((AFB+AF+AREB+ARE+ALIB+ALI+APLA +APLAB)/WT0)*MW*UNITCORR) ! 11 AUC_BBNGKGH=INTEG(BBNGKG,0.0) 12 13 14 ! ------------CO MMAND OF THE END OF SIMULATION ---------- 15 TERMT (T.GE. TimeLimit, 'Time limit has been reached.') 16 END ! END OF THE DERIVATIVE SECTION 17 END ! END OF THE DYNAMIC SECTION 18 END ! END OF THE PROGRAM 19 20
C.2.6.2. Input Files 21 C.2.6.2.1. Keller et al. (2007). 22
%TO BE USED AFTER THE 23 %clear variable 24 output @clear 25 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 26 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 27 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 28 %output @nciout=10 T SUMEXPEVENT wt0 29 %kELLER ET AL 2007 30 %protocol: SINGLE DOSE from GD13 31 %dose levels: 0.01, 0.100 1 ug/kg at GD13 32 %dose levels: 10, 100 1000 ng/kg at GD13 33 34 %EXPOSURES SCENARIOS 35 MAXT=0.01 36 CINT =0.1 37 EXP_TIME_ON = 312. % TIME AT WHICH EXPOSURE BEGINS(HOUR) 38 EXP_TIME_OFF = 330 % TIME AT WHICH EXPOSURE ENDS (HOUR) 39 DAY_CYCLE = 505 40 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 41 (HOUR) 42 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 43 (HOUR) 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-114 DRAFT

— DO NOT CITE OR QUOTE IV_LACK = 505 1 IV_PERIOD = 505 2 TIMELIMIT = 504 % SIMULATION TIME LIMIT (HOUR) 3 BW_T0 = 24 4 MATTING = 0. % BEGINNING OF MATING (HOUR) 5 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 6 N_FETUS = 10 7 8 %EXPOSURE DOSE SCENARIOS (UG/KG) 9 10%MSTOT = 0.01 % ORAL EXPOSURE DOSE IN UG/KG 11 %MSTOT = 0.1 % ORAL EXPOSURE DOSE IN UG/KG 12 MSTOT = 1 % ORAL EXPOSURE DOSE IN UG/KG 13 14
C.2.6.2.2. Li et al. (2005). 15
%TO BE USED AFTER THE 16 %clear variable 17 output @clear 18 prepare @clear T CLINGKG CFNG KG C BSNGKGLIADJ BBNGKG CFETUSNGKG 19 AUCLI_NGKGH AUCF_NGKGH AUCBS_NGKGLIADJ AUC_BBNGKGH 20 AUC_FENGKGH CBNDLINGKG AUCBNDLI_NGKGH 21 %output @nciout=10 T SUMEXPEVENT 22 %LI ET AL 2006 23 %protocol: exposure repetitiv e DOSE from GD1 to GD3 24 %dose levels: 0.002, 0.050 AND 0.10 ug/kg/day at GD1 TO GD8 25 %dose levels: 2, 50 and 100 ng/kg/day from GD1 to GD8 26 27 %EXPOSURES SCENARIOS 28 MAXT=0.001 29 CINT =0.1 30 EXP_TIME_ON = 0. % TIME AT WHICH EXPOSURE BEGINS (HOUR) 31 EXP_TIME_OFF = 70 % TIME AT WHICH EXPOSURE ENDS (HOUR); 2 HOURS 32 LESS THAN GD8; SET EQUAL TO 70 TO BE SURE ONLY 3 DOSES ADMINISTERED 33 % BECAUSE i STARTED TIME 0 FOR GD1 34 DAY_CYCLE = 24 35 BCK_TIME_ON = 0. % TIME AT WHICH BACKGROUND EXPOSURE BEGINS 36 (HOUR) 37 BCK_TIME_OFF = 0. % TIME AT WHICH BACKGROUND EXPOSURE ENDS 38 (HOUR) 39 IV_LACK = 505 40 IV_PERIOD = 505 41 TIMELIMIT = 216 % SIMULATION TIME LIMIT (HOUR) 42 BW_T0 = 27 43 MATTING = 0. % BEGINNING OF MATING (HOUR) 44 TRANSTIME_ON = 144. % SHOULD BE MATING TIME + 6 DAYS (144 HOURS) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-115 DRAFT

— DO NOT CITE OR QUOTE N_FETUS = 10 1 2 %EXPOSURE DOSE SCENARIOS (UG/KG) 3 4MSTOT = 0.002 % ORAL EXPOSURE DOSE IN UG/KG 5 %MSTOT = 0.05 % ORAL EXPOSURE DOSE IN UG/KG 6 %MSTOT = 0.10 % ORAL EXPOSURE DOSE IN UG/KG 7 8
C.3. TOXICOKINETIC MODELING RESU LTS FOR KEY ANIMAL B IOASSAY 9 STUDIES 10 The simulated TCDD serum-adjusted lipid conc entrations reported in this appendix for 11 the rodent bioassays were conve rted to TCDD concentrations in rodent whole blood. Initially, 12 EPA multiplied the serum-adjusted lipid concentr ations by 0.0033, the ratio of lipid content to 13 total serum volume, then by 0.55, the value of th e hematocrit. This product yields the TCDD 14 concentration in whole rodent blood as predicte d by the PBPK model. EPA assumed that the 15
same whole blood TCDD concentrati on would result in the same eff ects in humans and rodents. 16 This conversion accomplishes the following: 17
18
1. Allows the human equivalent dose (HED) to be based on equivalent blood concentration 19 (that represents serum plus erythrocyte TCDD) , which is proportional to tissue exposure; 20
2. Avoids criticism that the total blood concentr ation is normalized to serum lipid alone in 21 an unbalanced way (thus EPA does not cont radict Centers for Disease Control and 22 Prevention (CDC) data or methods); 23
3. Factors out any impact of the lipid content used in th e PBPK model; and 24
4. TCDD concentration in whole blood is encour aged for use in the assessments by the NAS 25 (NAS, 2006, p. 43); see additional information in Section 3.3. 26 27
C.3.1. Nongestational Studies 28 C.3.1.1. Cantoni et al. (1981) 29
Type: Rat Dose: 10, 100, 1000 ng/kg/week
Strain: CD-COBS rats Route: Oral gavage Body weight: BW set to 125g Regime: 1 dose/week for 45 weeks
Sex: Female Simulation time: 7,584 hours (45 weeks + 24 hours before sacrifice)

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-116 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,018 2,040 (@ 7,392 hours) 982 1.43 CADM - - - Emond 4,868 14,649 (@ 7,392 hours) 4,242 14.29 CADM - - - Emond 27,559 125,300 (@ 7,392 hours) 21,996 142.86 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 247 328 (@ 7,398 hours) 235 1.43 CADM 374 431 431
Emond 2,175 2,860 (@ 7,399 hours) 1,837 14.29 CADM 3,884 4,330 4,330
Emond 20,488 26,978 (@ 7,399 hours) 16,255 142.86 CADM 39,067 43,329 43,329 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 175 200 (@ 7,431 hours) 177 1.43 CADM 250 280 244
Emond 837 938 (@ 7,427 hours) 780 14.29 CADM 1,209 1,352 1,167
Emond 4,739 5,374 (@ 7,424 hours) 4,145 142.86 CADM 10,050 11,224 9,734 BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 26.1 31.7 (@ 7,398 hours) 25.6 1.43 CADM 32.0 35.0 35.0
Emond 170 210 (@ 7,398 hours) 149 14.29 CADM 225 243 243

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-117 DRAFT

— DO NOT CITE OR QUOTE Emond 1,336 1,695 (@ 7,398 hours) 1,088 142.86 CADM 2,106 2,266 2,266 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 6.04 7.76 (@ 7,396 hours) 5.88 1.43 CADM - - - Emond 23.7 29.1 (@ 7,396 hours) 21.6 14.29 CADM - - - Emond 66.8 80.0 (@ 1 hours) 62.0 142.86 CADM - - -



## C.3.1.2. Chu et al. (2007) 1
Type: Rat Dose: 2.5, 25, 250, and 1,000 ng/kg-day
Strain: Sprague-Dawley Route: Oral gavage Body weight: 200 g Regime: 1 dose per day for 28 days
Sex: Female Simulation time: 672 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 696 1,295 (@ 648 hours) 1,036 2.5 CADM - - - Emond 4,222 8,403 (@ 648 hours) 5,727 25 CADM - - - Emond 26,889 62,067 (@ 648 hours) 35,103 250 CADM - - - Emond 93,213 230,320 (@ 648 hours) 122,200 1,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-118 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 148 268 (@ 652 hours) 255 2.5 CADM - - -
Emond 1,777 2,953 (@ 653 hours) 2,806 25 CADM - - -
Emond 19,232 30,262 (@ 653 hours) 28,668 250 CADM - - -
Emond 77,819 120,400 (@ 653 hours) 113,890 1,000 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 108 180 (@ 668 hours) 180 2.5 CADM - - -
Emond 660 1,020 (@ 659 hours) 1,015 25 CADM - - -
Emond 4,210 6,433 (@ 655 hours) 6,354 250 CADM - - -
Emond 14,576 22,610 (@ 655 hours) 22,280 1,000 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 16.1 27.5 (@ 652 hours) 26.9 2.5 CADM - - -
Emond 138 222 (@ 652 hours) 214 25 CADM - - -
Emond 1,239 1,935 (@ 652 hours) 1,842 250 CADM - - -
Emond 4,801 7,444 (@ 652 hours) 7,067 1,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-119 DRAFT

— DO NOT CITE OR QUOTE BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 4.15 6.51 (@ 652 hours) 6.21 2.5 CADM - - - Emond 20.5 28.5 (@ 652 hours) 27.4 25 CADM - - - Emond 63.3 76.0 (@ 652 hours) 74.7 250 CADM - - - Emond 90.2 99.0 (@ 653 hours) 98.3 1,000 CADM - - -



## C.3.1.3. Crofton et al. (2005) 1
Type: Rats Dose: 0, 0.1, 3, 10, 30, 100, 300, 1000, 3000, and 10,000 ng/kg-day
Strain: Long Evans Route: Oral gavage Body weight: 4 weeks old BW set to 190 g Regime: One dose per day for four days

Sex: Female Simulation time: 96 hours 

## 2

a 

### The CADM model was not run because th e dosing duration is lower than th e resolution of the model (1 week) 

## 3 4 5 BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 11.1 22.4 (@ 72 hours) 13.5 0.1 CADM - - - Emond 269 605 (@ 72 hours) 321 3 CADM - - - Emond 763 1,873 (@ 72 hours) 892 10 CADM - - - Emond 1,905 5,202 (@ 72 hours) 2,169 30 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-120 DRAFT

— DO NOT CITE OR QUOTE Emond 5,104 15,972 (@ 72 hours) 5,605 100 CADM - - - Emond 12,706 44,982 (@ 72 hours) 13,509 300 CADM - - - Emond 36,170 143,340 (@ 72 hours) 37,554 1000 CADM - - - Emond 99,645 420,850 (@ 72 hours) 102,860 3000 CADM - - - Emond 321,480 1,392,100 (@ 72 hours) 334,220 10,000
CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 0.919 1.55 (@ 75 hours) 1.18 0.1 CADM - - -
Emond 37.4 62.6 (@ 76 hours) 53.3 3 CADM - - -
Emond 145 242 (@ 77 hours) 214 10 CADM - - -
Emond 494 818 (@ 78 hours) 742 30 CADM - - -
Emond 1,839 3,025 (@ 78 hours) 2,793 100 CADM - - -
Emond 5,925 9,692 (@ 78 hours) 9,028 300 CADM - - -
Emond 20,717 33,738 (@ 79 hours) 31,564 1000 CADM - - -
Emond 63,511 103,140 (@ 79 hours) 96,545 3000 CADM - - -
Emond 212,890 344,910 (@ 79 hours) 321,960 10,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-121 DRAFT

— DO NOT CITE OR QUOTE FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1.00 1.93 (@ 96 hours) 1.93 0.1 CADM - - -
Emond 24.6 45.9 (@ 96 hours) 45.9 3 CADM - - -
Emond 70.3 129 (@ 96 hours) 129 10 CADM - - -
Emond 177 317 (@ 96 hours) 317 30 CADM - - -
Emond 480 838 (@ 96 hours) 838 100 CADM - - -
Emond 1,206 2,065 (@ 96 hours) 2,065 300 CADM - - -
Emond 3,452 5,836 (@ 96 hours) 5,836 1000 CADM - - -
Emond 9,522 16,050 (@ 96 hours) 16,050 3000 CADM - - -
Emond 30,657 51,918 (@ 96 hours) 51,918 10,000 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 0.138 0.224 (@ 79 hours) 0.223 0.1 CADM - - -
Emond 4.04 6.56 (@ 78 hours) 6.44 3 CADM - - -
Emond 13.3 21.5 (@ 78 hours) 21.0 10 CADM - - -
Emond 39.3 63.5 (@ 78 hours) 61.5 30 CADM - - -
Emond 129 208 (@ 78 hours) 200 100 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-122 DRAFT

— DO NOT CITE OR QUOTE Emond 384 618 (@ 77 hours) 590 300 CADM - - -
Emond 1,270 2,041 (@ 77 hours) 1,942 1000 CADM - - -
Emond 3,793 6,094 (@ 77 hours) 5,784 3000 CADM - - -
Emond 12,595 20,226 (@ 77 hours) 19,154 10,000 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 0 0.115 (@ 75 hours) 0 0.1 CADM - - - Emond 2 2.47 (@ 76 hours) 2 3 CADM - - - Emond 4 6.42 (@ 76 hours) 5 10 CADM - - - Emond 10 14.1 (@ 76 hours) 12 30 CADM - - - Emond 22 29.9 (@ 76 hours) 27 100 CADM - - - Emond 41 51.9 (@ 77 hours) 49 300 CADM - - - Emond 68 80.2 (@ 1 hours) 77 1000 CADM - - - Emond 90 98.6 (@ 1 hours) 96 3000 CADM - - - Emond 104 108 (@ 1 hours) 107 10,000 CADM - - - 

## 1 2 C.3.1.4. Fattore et al. (2000) 3
Type: Rat Dose: 20, 200, 2,000 ng/kg-day
Strain: Sprague Dawley Route: Dietary

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-123 DRAFT

— DO NOT CITE OR QUOTE Body weight: 7 weeks old (BW 150g) Regime: 13 weeks

Sex: Female and male Simulation time: 2,184 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 5,282 8,259 (@ 2,160 hours) 6,135 20 CADM - - - Emond 31,761 56,170 (@ 2,160 hours) 35,183 200 CADM - - - Emond 262,030 497,250 (@ 2,160 hours) 287,690 2,000 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 2,448 3,228 (@ 2,164 hours) 3,078 20 CADM 4,471 5,639 5,639
Emond 24,136 30,245 (@ 2,164 hours) 28,709 200 CADM 45,337 56,499 56,499 Emond 234,170 288,020 (@ 2,164 hours) 272,590 2,000 CADM 454,031 565,103 565,103 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 890 1,113 (@ 2,166 hours) 1,101 20 CADM 1,545 1,796 1,756
Emond 5,355 6,542 (@ 2,165 hours) 6,430 200 CADM 13,351 15,604 15,292
Emond 44,176 54,246 (@ 2,165 hours) 53,140 2,000 CADM 131,259 153,534 150,516

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-124 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 187 242 (@ 2,164 hours) 233 20 CADM 261 324 324
Emond 1,556 1,940 (@ 2,164 hours) 1,850 200 CADM 2,496 3,084 3,084
Emond 14,432 17,797 (@ 2,164 hours) 16,891 2,000 CADM 24,836 30,674 30,674 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 24.9 29.8 (@ 2,164 hours) 28.8 20 CADM - - - Emond 69.4 76.0 (@ 2,164 hours) 74.7 200 CADM - - - Emond 104 106 (@ 2,164 hours) 106 2,000 CADM - - -



## C.3.1.5. Hassoun et al. (1998) 1
Type: Mice Dose: 0, 0.45, 1.5, 15, 150 ng/kg-day. Background exposure dose (default) = 0.05 ng/kg-day
Strain: B6C3F1 Route: Oral gavage Body weight: 8 to 9 weeks old (BW set to 23g) Regime: 5 days/week for 13 weeks

Sex: Female Simulation time: 2208 hours* (2,184h + 24h post exposure)

a 

### No background has been considered here for this simulation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-125 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 90.5 167 (@ 2,112 hours) 123 0.321 CADM - - - Emond 240 441 (@ 2,112 hours) 297 1.07 CADM - - - Emond 1,350 2,753 (@ 2,112 hours) 1,396 10.7 CADM - - - Emond 7,328 19,496 (@ 2,112 hours) 6,587 107 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 19.5 33.0 (@ 2,116 hours) 28.1 0.321 CADM 14.8 24.5 23.2
Emond 66.7 106 (@ 2,116 hours) 87.4 1.07 CADM 59.4 91.9 84.2
Emond 680 966 (@ 2,117 hours) 736 10.7 CADM 768 1,000 825
Emond 6,768 9,000 (@ 2,117 hours) 6,482 107 CADM 8,343 10,306 7,863 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 58.6 91.9 (@ 2,135 hours) 89.4 0.321 CADM 56.5 85.9 82.7
Emond 156 228 (@ 2,130 hours) 219 1.07 CADM 152 210 199
Emond 884 1,149 (@ 2,124 hours) 1,075 10.7 CADM 690 815 735
Emond 4,818 5,946 (@ 2,120 hours) 5,347 107 CADM 2,770 3,224 2,684

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-126 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 5.97 9.50 (@ 2,117 hours) 8.93 0.321 CADM 7.43 11.4 (@ 2,121 hours) 10.9
Emond 16.9 25.3 (@ 2,116 hours) 23.2 1.07 CADM 20.9 29.3 27.7
Emond 117 158 (@ 2,116 hours) 135 10.7 CADM 119 145 127
Emond 849 1,100 (@ 2,116 hours) 865 107 CADM 727 875 694 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 0.564 0.885 (@ 2,116 hours) 0.771 0.321 CADM - - - Emond 1.47 2.15 (@ 2,116 hours) 1.83 1.07 CADM - - - Emond 7.58 9.83 (@ 2,116 hours) 8.07 10.7 CADM - - - Emond 30.3 35.9 (@ 2,117 hours) 29.8 107 CADM - - - 

## 1 2 C.3.1.6. Hassoun et al. (2000) 3
Type: Rat Dose: 0, 3, 10, 22, 46, 100 ng/kg-day (2.14, 7.14, 15.7, 32.9, and 71.4 ng/kg-day adjusted doses)
Strain: Sprague Dawley Route: Oral gavage Body weight: 8 weeks old (BW=215g) Regime: 5 days/week for 13 weeks

Sex: Female Simulation time: 2184 hours

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-127 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,068 1,720 (@ 2,112 hours) 1,303 2.14 CADM - - - Emond 2,542 4,246 (@ 2,112 hours) 2,901 7.14 CADM - - - Emond 4,489 7,835 (@ 2,112 hours) 4,947 15.7 CADM - - - Emond 7,718 14,206 (@ 2,112 hours) 8,277 32.9 CADM - - - Emond 13,960 27,367 (@ 2,112 hours) 14,637 71.4 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 267 399 (@ 2,116 hours) 349 2.14 CADM - - -
Emond 888 1,259 (@ 2,117 hours) 1,079 7.14 CADM - - -
Emond 1,948 2,689 (@ 2,117 hours) 2,278 15.7 CADM - - -
Emond 4,055 5,484 (@ 2,117 hours) 4,607 32.9 CADM - - -
Emond 8,775 11,692 (@ 2,117 hours) 9,754 71.4 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 179 243 (@ 2,126 hours) 235 2.14 CADM - - -
Emond 427 553 (@ 2,124 hours) 528 7.14 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-128 DRAFT

— DO NOT CITE OR QUOTE Emond 755 958 (@ 2,123 hours) 908 15.7 CADM - - -
Emond 1,299 1,627 (@ 2,122 hours) 1,529 32.9 CADM - - -
Emond 2,350 2,928 (@ 2,121 hours) 2,727 71.4 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 27.4 38.9 (@ 2,116 hours) 35.7 2.14 CADM - - -
Emond 76.9 105 (@ 2,116 hours) 93.7 7.14 CADM - - -
Emond 153 205 (@ 2,116 hours) 180 15.7 CADM - - -
Emond 295 390 (@ 2,116 hours) 339 32.9 CADM - - -
Emond 600 785 (@ 2,116 hours) 674 71.4 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 6.28 8.48 (@ 2,116 hours) 7.67 2.14 CADM - - - Emond 13.7 17.5 (@ 2,116 hours) 15.7 7.14 CADM - - - Emond 22.0 27.1 (@ 2,116 hours) 24.4 15.7 CADM - - - Emond 32.8 39.2 (@ 2,116 hours) 35.6 32.9 CADM - - - Emond 47.5 55.0 (@ 2,116 hours) 50.6 71.4 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-129 DRAFT

— DO NOT CITE OR QUOTE C.3.1.7. Kitchin and Woods (1979) 1
Type: Rats Dose: 0, 0.6, 2, 4, 20, 60, 200, 600, 2000, 5000, 20000 ng/kg-day
Strain: Sprague-Dawley Route: Oral gavage Body weight: 200 to 250 g (BW set to 225 g) Regime: Single dose

Sex: Female Simulation time: 24 hours

a 

### The CADM model was not run because th e dosing duration is lower than the resolution of the model (1 week). 

## 2 3 4 BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 46.8 69.5 (@ 0 hours) 18.0 0.6 CADM - - - Emond 122 232 (@ 0 hours) 57.1 2 CADM - - - Emond 221 463 (@ 0 hours) 109 4 CADM - - - Emond 896 2,318 (@ 0 hours) 462 20 CADM - - - Emond 2,291 6,949 (@ 0 hours) 1,165 60 CADM - - - Emond 6,393 23,185 (@ 0 hours) 3,073 200 CADM - - - Emond 16,676 69,657 (@ 0 hours) 7,345 600 CADM - - - Emond 50,090 232,550 (@ 0 hours) 19,637 2,000 CADM - - - Emond 120,130 581,930 (@ 0 hours) 43,511 5,000 CADM - - - Emond 475,600 2,332,100 (@ 0 hours) 158,970 20,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-130 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 3.99 3.81 (@ 4 hours) 1.60 0.6 CADM - - -
Emond 11.7 12.9 (@ 4 hours) 6.01 2 CADM - - -
Emond 23.4 26.3 (@ 4 hours) 13.2 4 CADM - - -
Emond 129 143 (@ 6 hours) 85.2 20 CADM - - -
Emond 422 463 (@ 8 hours) 305 60 CADM - - -
Emond 1,525 1,666 (@ 9 hours) 1,194 200 CADM - - -
Emond 4,822 5,258 (@ 10 hours) 3,987 600 CADM - - -
Emond 16,606 18,081 (@ 11 hours) 14,296 2,000 CADM - - -
Emond 41,973 45,674 (@ 11 hours) 36,821 5,000 CADM - - -
Emond 167,820 182,580 (@ 11 hours) 149,280 20,000 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 2.11 3.03 (@ 72 hours) 3.03 0.6 CADM - - -
Emond 5.54 9.57 (@ 72 hours) 9.57 2 CADM - - -
Emond 10.1 18.2 (@ 72 hours) 18.2 4 CADM - - -
Emond 42.1 76.4 (@ 72 hours) 76.4 20 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-131 DRAFT

— DO NOT CITE OR QUOTE Emond 110 192 (@ 72 hours) 192 60 CADM - - -
Emond 317 512 (@ 72 hours) 512 200 CADM - - -
Emond 851 1,250 (@ 72 hours) 1,250 600 CADM - - -
Emond 2,621 3,481 (@ 58 hours) 3,462 2,000 CADM - - -
Emond 6,361 8,049 (@ 45 hours) 7,887 5,000 CADM - - -
Emond 25,402 31,187 (@ 35 hours) 29,738 20,000 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 0.429 0.341 (@ 9 hours) 0.331 0.6 CADM - - -
Emond 1.18 1.14 (@ 8 hours) 1.09 2 CADM - - -
Emond 2.24 2.27 (@ 8 hours) 2.15 4 CADM - - -
Emond 10.7 11.3 (@ 8 hours) 10.4 20 CADM - - -
Emond 31.8 33.8 (@ 7 hours) 30.3 60 CADM - - -
Emond 105 112 (@ 7 hours) 98 200 CADM - - -
Emond 315 337 (@ 7 hours) 288 600 CADM - - -
Emond 1,049 1,123 (@ 7 hours) 945 2,000 CADM - - -
Emond 2,621 2,806 (@ 7 hours) 2,343 5,000 CADM - - -
Emond 10,469 11,215 (@ 7 hours) 9,299 20,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-132 DRAFT

— DO NOT CITE OR QUOTE BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 0.284 0.407 (@ 3 hours) 0.238 0.6 CADM - - - Emond 0.728 1.07 (@ 3 hours) 0.476 2 CADM - - - Emond 1.30 1.94 (@ 3 hours) 0.798 4 CADM - - - Emond 4.90 7.74 (@ 2 hours) 2.95 20 CADM - - - Emond 11.2 18.4 (@ 2 hours) 7.03 60 CADM - - - Emond 25.1 40.8 (@ 1 hours) 16.7 200 CADM - - - Emond 45.8 68.2 (@ 1 hours) 33.0 600 CADM - - - Emond 73.3 93.1 (@ 1 hours) 59.1 2,000 CADM - - - Emond 90.9 104 (@ 1 hours) 79.9 5,000 CADM - - - Emond 106 110 (@ 1 hours) 101 20,000 CADM - - - 

## 1 2 C.3.1.8. Kociba et al. (1976) 3
Type: Rats Dose: 1, 10, 100, 1000 ng/kg-day
Strain: Sprague-Dawley (Spartan) Route: Oral gavage

Body weight: 170–190 g (bw=180g) Regime: 5 days/week for 13 weeks
Sex: Female Simulation time: 4,368 hours (13wk exposed + 13 wk post exposures)

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-133 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 398 761 (@ 2,112 hours) 163 0.714 CADM - - - Emond 1,817 4,196 (@ 2,112 hours) 372 7.143 CADM - - - Emond 9,002 26,872 (@ 2,112 hours) 820 71.43 CADM - - - Emond 60,388 226,470 (@ 2,112 hours) 2,072 714.3 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 70.9 140 (@ 2,116 hours) 21.4 0.714 CADM 89.0 192 12.1
Emond 595 1,259 (@ 2,117 hours) 62.4 7.143 CADM 970 2,007 29.0
Emond 5,391 11,693 (@ 2,117 hours) 183 71.43 CADM 9,841 20,170 88.0
Emond 51,476 112,580 (@ 2,117 hours) 670 714.3 CADM 98,617 201,814 455 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 68.3 114 (@ 2,129 hours) 28.8 0.714 CADM 120 190 43.0
Emond 313 553 (@ 2,124 hours) 66.2 7.143 CADM 456 787 67.0
Emond 1,552 2,925 (@ 2,121 hours) 148 71.43 CADM 3,036 5,748 117
Emond 10,415 21,127 (@ 2,120 hours) 379 714.3 CADM 28,382 55,013 274

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-134 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 9.03 16.1 (@ 2,116 hours) 3.41 0.714 CADM 11.5 20.0 3.75
Emond 53.7 105 (@ 2,116 hours) 8.44 7.143 CADM 65.3 126 6.22
Emond 377 785 (@ 2,116 hours) 20.8 71.43 CADM 553 1,113 12.0
Emond 3,230 6,961 (@ 2,116 hours) 62.4 714.3 CADM 5,401 10,967 37.0 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 2.44 4.17 (@ 2,116 hours) 1.02 0.714 CADM - - - Emond 10.1 17.5 (@ 2,116 hours) 2.30 7.143 CADM - - - Emond 33.2 55.0 (@ 2,116 hours) 4.95 71.43 CADM - - - Emond 69.7 98.2 (@ 2,117 hours) 11.7 714.3 CADM - - -



## C.3.1.9. Kociba et al. (1978) Female 1
Type: Rats Dose: 0, 1, 10, 100 ng/kg-day
Strain: Sprague-Dawley (Spartan) Route: Dietary

Body weight: 170–190 g (bw=180) Regime: 104 weeks
Sex: Female Simulation time: 17,472 hours

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-135 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 853 1,058 (@ 17,448 hours) 929 1 CADM - - - Emond 3,942 5,098 (@ 17,448 hours) 3,943 10 CADM - - - Emond 21,246 31,697 (@ 17,448 hours) 20,441 100 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 192 226 (@ 17,452 hours) 218 1 CADM 292 333 333
Emond 1,618 1,742 (@ 17,452 hours) 1,665 10 CADM 2,981 3,342 3,342
Emond 14,892 15,673 (@ 17,452 hours) 14,907 100 CADM 29,917 33,432 33,432 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 147 165 (@ 17,457 hours) 164 1 CADM 196 229 181
Emond 680 713 (@ 17,454 hours) 706 10 CADM 861 1,015 789
Emond 3,663 3,788 (@ 17,454 hours) 3,731 100 CADM 6,756 7,939 6,203 BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 21.2 24.3 (@ 17,452 hours) 23.8 1 CADM 26.0 27.0 27.0
Emond 131 140 (@ 17,452 hours) 136 10 CADM 169 176 176

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-136 DRAFT

— DO NOT CITE OR QUOTE Emond 989 1,039 (@ 17,452 hours) 994 100 CADM 1,546 1,601 1,601 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 5.11 5.77 (@ 17,452 hours) 5.59 1 CADM - - - Emond 20.0 21.1 (@ 17,452 hours) 20.4 10 CADM - - - Emond 59.9 61.5 (@ 17,452 hours) 60.1 100 CADM - - -



## C.3.1.10. Kociba et al. (1978) Male 1
Type: Rats Dose: 0, 1, 10, 100 ng/kg-day
Strain: Sprague-Dawley (Spartan) Route: Dietary

Body weight: Body weight approximated to be 250 g Regime: 104 weeks

Sex: Male Simulation time: 17,472 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 860 1,079 (@ 17,448 hours) 938 1 CADM - - - Emond 3,945 5,153 (@ 17,448 hours) 3,916 10 CADM - - - Emond 21,334 32,658 (@ 17,448 hours) 20,460 100 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-137 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 194 229 (@ 17,452 hours) 221 1 CADM - - - Emond 1,616 1,723 (@ 17,452 hours) 1,649 10 CADM - - - Emond 14,898 15,671 (@ 17,452 hours) 14,912 100 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 148 167 (@ 17,456 hours) 166 1 CADM - - - Emond 680 709 (@ 17,454 hours) 703 10 CADM - - - Emond 3,677 3,803 (@ 17,453 hours) 3,747 100 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 21.4 24.6 (@ 17,452 hours) 24.1 1 CADM - - - Emond 131 139 (@ 17,452 hours) 134 10 CADM - - - Emond 991 1,041 (@ 17,452 hours) 995 100 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 5.15 5.83 (@ 17,452 hours) 5.64 1 CADM - - - Emond 20.0 21.0 (@ 17,452 hours) 20.3 10 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-138 DRAFT

— DO NOT CITE OR QUOTE Emond 60.0 61.5 (@ 17,452 hours) 60.1 100 CADM - - -



## C.3.1.11. Latchoumycandane and Mathur (2002) 1
Type: Rat Dose: 0, 1, 10, 100 ng/kg-day
Strain: Wistar Route: Mouth pipetting Body weight: 45 days old (BW set to 200g) Regime: 1/day for 45 days

Sex: Male Simulation time: 1,104 hours (1,080 daily exposure and 24 hours before sacrifice)

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 437 754 (@ 1,056 hours) 630 1 CADM - - - Emond 2,579 4,505 (@ 1,056 hours) 3,274 10 CADM - - - Emond 15,092 29,672 (@ 1,056 hours) 17,698 100 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 79.7 138 (@ 1,060 hours) 128 1 CADM 116 217 217
Emond 911 1,423 (@ 1,060 hours) 1,282 10 CADM 1,669 2,550 2,550
Emond 9,650 14,015 (@ 1,061 hours) 12,439 100 CADM 17,681 25,915 25,915 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 70.7 113 (@ 1,072 hours) 112 1 CADM 150 220 220

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-139 DRAFT

— DO NOT CITE OR QUOTE Emond 420 608 (@ 1,065 hours) 592 10 CADM 744 1,009 1,009
Emond 2,467 3,425 (@ 1,062 hours) 3,273 100 CADM 5,719 7,866 7,866 BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 9.68 15.9 (@ 1,060 hours) 15.2 1 CADM 14.0 22.2 22.2
Emond 77.5 117 (@ 1,060 hours) 108 10 CADM 106 157 157
Emond 651 933 (@ 1,060 hours) 842 100 CADM 988 1,439 1,439 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 2.67 4.12 (@ 1,060 hours) 3.85 1 CADM - - - Emond 13.8 18.8 (@ 1,060 hours) 17.5 10 CADM - - - Emond 48.8 59.0 (@ 1,060 hours) 56.0 100 CADM - - -



## C.3.1.12. Li et al. (1997) 1
Type: Rats Dose: 0, 3, 10, 30, 100, 300, 1000, 3000, 10000, 30000 ng/kg/day
Strain: Sprague-Dawley Route: Gastric intubation Body weight: 22 day old, 55 to 58 g (BW set to 56.5 g) Regime: One dose for one day

Sex: Female Simulation time: 24 hours 

## 2

a 

### The CADM model was not run because th e dosing duration is lower than th e resolution of the model (1 week) 

## 3 4 5 6 7 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-140 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Model Time-weighted Ave Max Terminal
Emond 147 259 (@ 1 hours) 98.9 3 CADM - - - Emond 440 862 (@ 1 hours) 295 10 CADM - - - Emond 1,156 2,581 (@ 1 hours) 757 30 CADM - - - Emond 3,232 8,585 (@ 1 hours) 2,026 100 CADM - - - Emond 8,266 25,780 (@ 0 hours) 4,865 300 CADM - - - Emond 23,875 86,088 (@ 0 hours) 12,873 1,000 CADM - - - Emond 66,081 258,670 (@ 0 hours) 33,013 3,000 CADM - - - Emond 212,650 864,770 (@ 0 hours) 100,410 10,000 CADM - - - Emond 649,740 2,633,500 (@ 0 hours) 294,620 30,000 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Model Time-weighted Ave Max Terminal
Emond 14.7 18.6 (@ 4 hours) 11.9 3 CADM - - -
Emond 55.0 65.2 (@ 5 hours) 47.6 10 CADM - - -
Emond 185 210 (@ 6 hours) 170 30 CADM - - -
Emond 690 768 (@ 7 hours) 666 100 CADM - - -
Emond 2,248 2,473 (@ 8 hours) 2,240 300 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-141 DRAFT

— DO NOT CITE OR QUOTE Emond 7,938 8,671 (@ 9 hours) 8,094 1,000 CADM - - -
Emond 24,474 26,639 (@ 9 hours) 25,267 3,000 CADM - - -
Emond 82,349 89,464 (@ 9 hours) 85,597 10,000 CADM - - -
Emond 245,610 265,670 (@ 10 hours) 255,390 30,000 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Model Time-weighted Ave Max Terminal
Emond 8.75 12.7 (@ 24 hours) 12.7 3 CADM - - -
Emond 26.6 38.0 (@ 24 hours) 38.0 10 CADM - - -
Emond 70.8 98.9 (@ 24 hours) 98.9 30 CADM - - -
Emond 202 273 (@ 24 hours) 273 100 CADM - - -
Emond 530 689 (@ 24 hours) 689 300 CADM - - -
Emond 1,573 1,958 (@ 24 hours) 1,958 1,000 CADM - - -
Emond 4,433 5,358 (@ 24 hours) 5,358 3,000 CADM - - -
Emond 14,428 17,119 (@ 24 hours) 17,119 10,000 CADM - - -
Emond 44,361 51,948 (@ 22 hours) 51,898 30,000 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Model Time-weighted Ave Max Terminal
Emond 1.60 1.70 (@ 8 hours) 1.68 3 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-142 DRAFT

— DO NOT CITE OR QUOTE Emond 5.33 5.66 (@ 8 hours) 5.56 10 CADM - - -
Emond 15.9 16.9 (@ 8 hours) 16.5 30 CADM - - -
Emond 52.8 56.2 (@ 7 hours) 54.5 100 CADM - - -
Emond 158 169 (@ 7 hours) 163 300 CADM - - -
Emond 525 561 (@ 7 hours) 539 1,000 CADM - - -
Emond 1,574 1,684 (@ 7 hours) 1,611 3,000 CADM - - -
Emond 5,240 5,610 (@ 7 hours) 5,360 10,000 CADM - - -
Emond 15,758 16,815 (@ 7 hours) 16,041 30,000 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Model Time-weighted Ave Max Terminal
Emond 1 1.37 (@ 3 hours) 1 3 CADM - - - Emond 3 4.10 (@ 2 hours) 2 10 CADM - - - Emond 6 10.5 (@ 2 hours) 5 30 CADM - - - Emond 16 25.9 (@ 2 hours) 12 100 CADM - - - Emond 31.25 50.1 (@ 1 hours) 24.58 300 CADM - - - Emond 56.75 79.8 (@ 1 hours) 47.65 1,000 CADM - - - Emond 81.29 98.4 (@ 1 hours) 73.34 3,000 CADM - - - Emond 99.77 108 (@ 1 hours) 95.70 10,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-143 DRAFT

— DO NOT CITE OR QUOTE Emond 108.04 111 (@ 1 hours) 106.23 30,000 CADM - - -



## C.3.1.13. NTP (1982)

— Female Rats, Chronic 1

Type: 

## Rat Dose: 10, 50 and 500 ng/kg/wk, two doses per week
Strain: 

## Osborne-Mendel Route: Oral gavage Body weight 6 weeks old (BW set to 250g) Regime: Biweekly

Sex: Female Simulation time 17,976 hours (107 weeks)= (104 weeks of exposure + 3 weeks observation post-treatment)

a 

### The CADM model simulates for 104 weeks only (17,472 hours) . As a result, the terminal values from the CADM model are overestimated compared to the Emond model, wh ich considered an additional 3 weeks post exposure.

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,072 1,719 (@ 17,388 hours) 685 1.4 CADM - - - Emond 3,111 6,054 (@ 17,388 hours) 1,622 7.1 CADM - - - Emond 16,207 45,310 (@ 17,388 hours) 6,253 71 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 263 310 (@ 17,394 hours) 143 1.4 CADM 15,318 20,170 7,102
Emond 1,163 1,338 (@ 17,394 hours) 474 7.1 CADM 30,700 40,353 14,200
Emond 10,596 12,182 (@ 17,395 hours) 3,134 71 CADM 30,700 40,353 14,200

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-144 DRAFT

— DO NOT CITE OR QUOTE FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 185 200 (@ 17,412 hours) 124 1.4 CADM 4,655 5,748 2,107
Emond 537 569 (@ 17,409 hours) 297 7.1 CADM 9,064 11,224 3,964
Emond 2,798 2,973 (@ 17,404 hours) 1,173 71 CADM 17,879 22,172 7,671 BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 27.7 31.2 (@ 17,393 hours) 16.9 1.4 CADM 855 1,113 403
Emond 98.5 110 (@ 17,393 hours) 46.6 7.1 CADM 1,695 2,208 787
Emond 720 814 (@ 17,393 hours) 241 71 CADM 3,375 4,395 1,556 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 6.34 7.28 (@ 17,392 hours) 4.17 1.4 CADM - - - Emond 16.5 18.5 (@ 17,392 hours) 9.37 7.1 CADM - - - Emond 52.3 56.4 (@ 17,393 hours) 29.1 71 CADM - - -



## C.3.1.14. NTP (1982)

— Male Rats, Chronic 1

Type: 

## Rat Dose: 10, 50 and 500 ng/kg/wk, two doses per week
Strain: 

## Osborne-Mendel Route: Oral gavage Body weight 6 weeks old (BW set to 350g) Regime: Biweekly (Simulation has been perform using female BW

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-145 DRAFT

— DO NOT CITE OR QUOTE Sex: Male Simulation time 17,976 hours (107 weeks)= (104 weeks of exposure + 3 weeks observation post-treatment)

a 

### The CADM model simulates for 104 weeks only (17,472 hours) . As a result, the terminal values from the CADM model are overestimated compared to the Emond model, wh ich considered an additional 3 weeks post exposure.

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,072 1,750 (@ 17,388 hours) 681 1.4 CADM - - - Emond 3,116 6,301 (@ 17,388 hours) 1,622 7.1 CADM - - - Emond 16,272 47,951 (@ 17,388 hours) 6,269 71 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 263 306 (@ 17,394 hours) 141 1.4 CADM - - - Emond 1,162 1,334 (@ 17,394 hours) 473 7.1 CADM - - - Emond 10,598 12,170 (@ 17,395 hours) 3,140 71 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 185 199 (@ 17,412 hours) 123 1.4 CADM - - - Emond 538 569 (@ 17,409 hours) 298 7.1 CADM - - - Emond 2,809 2,983 (@ 17,404 hours) 1,185 71 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-146 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 27.7 30.9 (@ 17,393 hours) 16.8 1.4 CADM - - - Emond 98.6 110 (@ 17,393 hours) 46.6 7.1 CADM - - - Emond 721 816 (@ 17,393 hours) 242 71 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 6.33 7.22 (@ 17,392 hours) 4.14 1.4 CADM - - - Emond 16.4 18.4 (@ 17,392 hours) 9.36 7.1 CADM - - - Emond 52.3 56.3 (@ 17,393 hours) 29.1 71 CADM - - -



## C.3.1.15. NTP (1982)

— Female Mice, Chronic 1

Type: Mice Dose: 40, 200 and 2000ng/kg/wk, two doses during the week
Strain: B6C3F1 Route: Oral gavage Body weight 6 weeks old (BW set to 23g) Regime: Biweekly

Sex: Female Simulation time 17,976 hours (107 weeks)= (104 weeks of exposure + 3 weeks observation post-treatment)

a 

### The mice chronic exposure could not be simulated with the CADM model because this model simulates for only 123 days.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-147 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,064 2,684 (@ 17,220 hours) 569 5.7 CADM - - - Emond 3,184 10,915 (@ 17,388 hours) 1,334 28.6 CADM - - - Emond 17,406 93,992 (@ 17,220 hours) 4,899 286 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 486 587 (@ 17,227 hours) 209 5.7 CADM - - - Emond 2,206 2,629 (@ 17,395 hours) 682 28.6 CADM - - - Emond 20,515 24,353 (@ 17,396 hours) 4,232 286 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 733 789 (@ 17,324 hours) 436 5.7 CADM - - - Emond 2,194 2,337 (@ 17,404 hours) 1,059 28.6 CADM - - - Emond 12,003 12,861 (@ 17,400 hours) 4,151 286 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 91.2 103 (@ 17,225 hours) 48.5 5.7 CADM - - - Emond 325 370 (@ 17,393 hours) 130 28.6 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-148 DRAFT

— DO NOT CITE OR QUOTE Emond 2,367 2,740 (@ 17,393 hours) 615 286 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 6.13 7.32 (@ 17,225 hours) 3.44 5.7 CADM - - - Emond 16.1 18.9 (@ 17,393 hours) 7.68 28.6 CADM - - - Emond 51.8 67.8 (@ 2 hours) 23.6 286 CADM - - -



## C.3.1.16. NTP (1982)

— Male Mice, Chronic 1

Type: Mice Dose: 10, 50 and 500ng/kg/wk, two doses during the week
Strain: B6C3F1 Route: Oral gavage Body weight 6 weeks old (BW set to 25g) Regime: Biweekly

Sex: Male Simulation time 17,976 hours (107 weeks)= (104 weeks of exposure + 3 weeks observation post-treatment)

a 

### The mice chronic exposure could not be simulated with the CADM model because this model simulates for only 123 days.

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 420 842 (@ 17,136 hours) 270 1.4 CADM - - - Emond 1,240 3,302 (@ 17,304 hours) 644 7.1 CADM - - - Emond 6,118 25,730 (@ 17,388 hours) 2,204 71 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-149 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 137 165 (@ 17,142 hours) 76.7 1.4 CADM - - - Emond 599 723 (@ 17,311 hours) 247 7.1 CADM - - - Emond 5,331 6,328 (@ 17,395 hours) 1,382 71 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 289 314 (@ 17,243 hours) 202 1.4 CADM - - - Emond 854 918 (@ 17,407 hours) 496 7.1 CADM - - - Emond 4,217 4,490 (@ 17,402 hours) 1,799 71 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 32.2 36.3 (@ 17,141 hours) 21.1 1.4 CADM - - - Emond 109 123 (@ 17,309 hours) 55.8 7.1 CADM - - - Emond 701 802 (@ 17,393 hours) 235 71 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 2.54 3.04 (@ 17,141 hours) 1.67 1.4 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-150 DRAFT

— DO NOT CITE OR QUOTE Emond 7.06 8.41 (@ 17,309 hours) 3.87 7.1 CADM - - - Emond 26.8 32.4 (@ 2 hours) 12.1 71 CADM - - -



## C.3.1.17. NTP (2006) 31 Weeks 1
Type: Rat Dose: 0, 3, 10, 22, 46, 100 ng/kg-day
Strain: Sprague Dawley Route: Oral gavage Body weight: 8 weeks old (BW=215g) Regime: 5 days/weeks for 31 weeks

Sex: Female and male Simulation time: 5208 hours (31 weeks)

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,284 1,792 (@ 3,960 hours) 1,360 2.14 CADM - - - Emond 2,932 4,356 (@ 3,960 hours) 2,989 7.14 CADM - - - Emond 5,075 7,958 (@ 3,960 hours) 5,039 15.7 CADM - - - Emond 8,629 14,416 (@ 3,960 hours) 8,417 32.9 CADM - - - Emond 15,503 27,738 (@ 5,136 hours) 14,877 71.4 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 341 425 (@ 3,964 hours) 371 2.14 CADM - - -
Emond 1,077 1,312 (@ 4,133 hours) 1,125 7.14 CADM - - -
Emond 2,298 2,760 (@ 3,965 hours) 2,336 15.7 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-151 DRAFT

— DO NOT CITE OR QUOTE Emond 4,698 5,599 (@ 3,965 hours) 4,711 32.9 CADM - - -
Emond 10,036 11,910 (@ 5,141 hours) 9,956 71.4 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 220 256 (@ 4,141 hours) 245 2.14 CADM - - -
Emond 502 571 (@ 4,139 hours) 545 7.14 CADM - - -
Emond 868 979 (@ 4,138 hours) 926 15.7 CADM - - -
Emond 1,476 1,657 (@ 4,137 hours) 1,558 32.9 CADM - - -
Emond 2,653 2,979 (@ 5,144 hours) 2,776 71.4 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 34.2 41.2 (@ 3,964 hours) 37.6 2.14 CADM - - -
Emond 91.7 109 (@ 4,132 hours) 97.2 7.14 CADM - - -
Emond 178 210 (@ 3,964 hours) 184 15.7 CADM - - -
Emond 339 398 (@ 4,132 hours) 346 32.9 CADM - - -
Emond 683 799 (@ 5,140 hours) 687 71.4 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-152 DRAFT

— DO NOT CITE OR QUOTE BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 7.48 8.84 (@ 3,964 hours) 7.98 2.14 CADM - - - Emond 15.6 17.9 (@ 4,132 hours) 16.1 7.14 CADM - - - Emond 24.4 27.5 (@ 3,964 hours) 24.8 15.7 CADM - - - Emond 35.7 39.6 (@ 3,964 hours) 36.0 32.9 CADM - - - Emond 50.9 55.4 (@ 5,140 hours) 51.1 71.4 CADM - - -



## C.3.1.18. NTP (2006) 53 Weeks 1
Type: Rat Dose: 0, 3, 10, 22, 46, 100 ng/kg-day
Strain: Sprague Dawley Route: Oral gavage Body weight: 8 weeks old (BW=215g) Regime: 5 days/weeks for 105 weeks

Sex: Female and male Simulation time: 8904 hours (53 weeks)

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,354 1,792 (@ 3,960 hours) 1,367 2.14 CADM - - - Emond 3,056 4,359 (@ 8,832 hours) 2,993 7.14 CADM - - - Emond 5,259 7,958 (@ 3,960 hours) 5,052 15.7 CADM - - - Emond 8,918 14,460 (@ 8,832 hours) 8,438 32.9 CADM - - - Emond 16,001 27,846 (@ 8,832 hours) 14,916 71.4 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-153 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 365 425 (@ 3,964 hours) 373 2.14 CADM - - -
Emond 1,138 1,312 (@ 8,837 hours) 1,127 7.14 CADM - - -
Emond 2,407 2,760 (@ 3,965 hours) 2,344 15.7 CADM - - -
Emond 4,902 5,611 (@ 8,837 hours) 4,726 32.9 CADM - - -
Emond 10,443 11,943 (@ 8,837 hours) 9,989 71.4 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 233 256 (@ 8,845 hours) 247 2.14 CADM - - -
Emond 525 572 (@ 8,843 hours) 546 7.14 CADM - - -
Emond 904 979 (@ 8,842 hours) 928 15.7 CADM - - -
Emond 1,533 1,661 (@ 8,841 hours) 1,562 32.9 CADM - - -
Emond 2,750 2,987 (@ 8,840 hours) 2,785 71.4 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 36.4 41.2 (@ 3,964 hours) 37.8 2.14 CADM - - -
Emond 96.4 109 (@ 8,836 hours) 97.3 7.14 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-154 DRAFT

— DO NOT CITE OR QUOTE Emond 186 210 (@ 8,836 hours) 185 15.7 CADM - - -
Emond 354 399 (@ 8,836 hours) 347 32.9 CADM - - -
Emond 709 802 (@ 8,836 hours) 689 71.4 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 8.17 9.30 (@ 17,572 hours) 8.43 2.14 CADM - - - Emond 16.6 18.0 (@ 17,572 hours) 16.2 7.14 CADM - - - Emond 25.6 27.6 (@ 17,572 hours) 24.9 15.7 CADM - - - Emond 37.3 39.7 (@ 17,572 hours) 36.2 32.9 CADM - - - Emond 52.7 55.5 (@ 17,572 hours) 51.2 71.4 CADM - - -



## C.3.1.19. NTP (2006) 2 Years 1
Type: Rat Dose: 0, 3, 10, 22, 46, 100 ng/kg-day
Strain: Sprague Dawley Route: Oral gavage Body weight: 8 weeks old (BW=215g) Regime: 5 days/weeks for 105 weeks

Sex: Female and male Simulation time: 17,640 hours* (105 weeks)

a 

### The CADM model simulates for 104 weeks only (17,472 hours) . As a result, the terminal values from the CADM model may be underestimated compared to the Emond mo del, which considers the full 105 weeks of exposure.

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,408 1,910 (@ 17,568 hours) 1,444 2.14 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-155 DRAFT

— DO NOT CITE OR QUOTE Emond 3,137 4,389 (@ 17,568 hours) 3,007 7.14 CADM - - - Emond 5,393 8,039 (@ 17,568 hours) 5,079 15.7 CADM - - - Emond 9,129 14,542 (@ 17,568 hours) 8,468 32.9 CADM - - - Emond 16,361 27,991 (@ 17,568 hours) 14,951 71.4 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 385 460 (@ 17,572 hours) 403 2.14 CADM 632 715 715
Emond 1,177 1,320 (@ 17,573 hours) 1,135 7.14 CADM 2,127 2,387 2,387
Emond 2,487 2,779 (@ 17,573 hours) 2,361 15.7 CADM 4,691 5,252 5,252
Emond 5,051 5,637 (@ 17,573 hours) 4,749 32.9 CADM 9,822 10,984 10,984
Emond 10,734 11,976 (@ 17,573 hours) 10,018 71.4 CADM 21,366 23,880 23,880 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 243 271 (@ 17,581 hours) 261 2.14 CADM 302 355 277
Emond 541 575 (@ 17,579 hours) 549 7.14 CADM 667 787 611
Emond 930 985 (@ 17,578 hours) 934 15.7 CADM 1,242 1,463 1,138
Emond 1,574 1,667 (@ 17,577 hours) 1,568 32.9 CADM 2,369 2,787 2,173
Emond 2,821 2,995 (@ 17,576 hours) 2,792 71.4 CADM 4,890 5,748 4,489

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-156 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 38.1 44.0 (@ 17,572 hours) 40.4 2.14 CADM 46.0 48.0 48.0
Emond 99.5 109 (@ 17,572 hours) 97.9 7.14 CADM 125 130 130
Emond 192 211 (@ 17,572 hours) 186 15.7 CADM 257 267 267
Emond 364 400 (@ 17,572 hours) 348 32.9 CADM 520 538 538
Emond 729 804 (@ 17,572 hours) 691 71.4 CADM 1,110 1,149 1,149 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 8.17 9.30 (@ 17,572 hours) 8.43 2.14 CADM - - - Emond 16.6 18.0 (@ 17,572 hours) 16.2 7.14 CADM - - - Emond 25.6 27.6 (@ 17,572 hours) 24.9 15.7 CADM - - - Emond 37.3 39.7 (@ 17,572 hours) 36.2 32.9 CADM - - - Emond 52.7 55.5 (@ 17,572 hours) 51.2 71.4 CADM - - - 

## 1 2 C.3.1.20. Sewall et al. (1995) 3
Type: Rat Dose: 49, 149.8, 490, and 1750 ng/kg every two weeks or 3.5, 10.7, 35, and 125 ng/kg-day
Strain: Sprauge-Dawley Route: Oral gavage Body weight: 12 wk old (BW set to 250g) Regime: Once every 2 weeks for 30 weeks

Sex: Female Simulation time: 5040 hours 

## 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-157 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,813 7,535 (@ 4,704 hours) 1,587 3.5 CADM - - - Emond 3,916 21,297 (@ 4,704 hours) 3,189 10.7 CADM - - - Emond 9,163 66,137 (@ 4,704 hours) 6,945 35 CADM - - - Emond 24,608 228,370 (@ 4,704 hours) 17,298 125 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 550 901 (@ 4,711 hours) 459 3.5 CADM - - -
Emond 1,605 2,632 (@ 4,712 hours) 1,229 10.7 CADM - - -
Emond 5,072 8,350 (@ 4,712 hours) 3,618 35 CADM - - -
Emond 17,683 29,256 (@ 4,713 hours) 12,011 125 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 310 383 (@ 4,765 hours) 290 3.5 CADM - - -
Emond 670 827 (@ 4,763 hours) 590 10.7 CADM - - -
Emond 1,569 1,957 (@ 4,760 hours) 1,304 35 CADM - - -
Emond 4,217 5,376 (@ 4,757 hours) 3,303 125 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-158 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 51.4 72.5 (@ 4,710 hours) 45.3 3.5 CADM - - -
Emond 130 189 (@ 4,710 hours) 106 10.7 CADM - - -
Emond 364 546 (@ 4,710 hours) 274 35 CADM - - -
Emond 1,164 1,793 (@ 4,710 hours) 824 125 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 10.2 15.8 (@ 2 hours) 9.18 3.5 CADM - - - Emond 19.8 34.4 (@ 1 hours) 17.0 10.7 CADM - - - Emond 37.0 63.2 (@ 1 hours) 31.4 35 CADM - - - Emond 63.1 90.9 (@ 1 hours) 55.2 125 CADM - - - 

## 1 2 C.3.1.21. Smialowicz et al. (2008) 3
Type: Mice Dose: 0, 1.5, 15, 150, 450 ng/kg-day
Strain: B6C3F1 Route: Oral gavage Body weight: 13 wk old (BW set to 28g) Regime: 5 days/week for 13 weeks

Sex: Female Simulation time: 2184

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-159 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 241 449 (@ 2,112 hours) 307 1.07 CADM - - - Emond 1,358 2,821 (@ 2,112 hours) 1,460 10.7 CADM - - - Emond 7,385 20,036 (@ 2,112 hours) 6,978 107 CADM - - - Emond 17,438 54,346 (@ 2,112 hours) 15,650 321 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 67.1 107 (@ 2,116 hours) 91.5 1.07 CADM 59.0 92.0 88.0
Emond 683 971 (@ 2,117 hours) 787 10.7 CADM 767 1,000 907
Emond 6,784 9,010 (@ 2,117 hours) 7,043 107 CADM 8,349 10,306 8,998
Emond 20,218 26,379 (@ 2,117 hours) 20,405 321 CADM 25,344 31,006 26,967 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 156 229 (@ 2,130 hours) 225 1.07 CADM 151 210 204
Emond 885 1,155 (@ 2,124 hours) 1,111 10.7 CADM 689 815 774
Emond 4,831 5,979 (@ 2,120 hours) 5,591 107 CADM 2,771 3,224 2,937
Emond 11,420 14,037 (@ 2,119 hours) 12,920 321 CADM 6,337 7,509 6,688

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-160 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 17.0 25.5 (@ 2,116 hours) 23.9 1.07 CADM 21.0 29.0 29.0
Emond 117 159 (@ 2,116 hours) 141 10.7 CADM 119 145 135
Emond 852 1,103 (@ 2,116 hours) 923 107 CADM 727 875 778
Emond 2,304 2,958 (@ 2,116 hours) 2,419 321 CADM 1,961 2,370 2,080 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1.48 2.17 (@ 2,116 hours) 1.90 1.07 CADM - - - Emond 7.60 9.86 (@ 2,116 hours) 8.42 10.7 CADM - - - Emond 30.3 36.0 (@ 2,117 hours) 31.1 107 CADM - - - Emond 51.1 58.1 (@ 2,117 hours) 51.8 321 CADM - - -



## C.3.1.22. Toth et al., 1 Year (1979) 1
Type: Mice Dose: 7, 700, 7000 ng/kg/week
Strain: Swiss/H/Riop Route: Gastric intubation Body weight: 10 weeks old (BW= 27g) Regime: 1/week for 52 weeks

Sex: Female and male Simulation time: 8,736 hours*

a 

### According to the protocol in the paper, the mice were exposed for 52 weeks. However, the post exposure treatment was for an additional 60–285 days. For this simulation, we modeled 52 weeks because we have already reached the maximum when the dosing ends. We did not simulate the scenario using the CADM model because this mice model can only simulate for a maximum of 123 days.

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-161 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 315 889 (@ 8,568 hours) 308 1 CADM - - - Emond 7,814 63,673 (@ 7,896 hours) 6,014 100 CADM - - - Emond 50,105 610,490 (@ 8,568 hours) 34,155 1,000 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 94.1 131 (@ 8,575 hours) 91.5 1 CADM - - - Emond 7,337 10,132 (@ 7,905 hours) 5,669 100 CADM - - - Emond 70,180 97,655 (@ 8,577 hours) 51,986 1,000 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 215 247 (@ 8,613 hours) 230 1 CADM - - - Emond 5,337 5,912 (@ 8,594 hours) 4,997 100 CADM - - - Emond 34,239 38,825 (@ 8,588 hours) 30,516 1,000 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 23.4 28.4 (@ 8,574 hours) 24.3 1 CADM - - - Emond 929 1,189 (@ 7,902 hours) 781 100 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-162 DRAFT

— DO NOT CITE OR QUOTE Emond 7,564 10,044 (@ 8,574 hours) 5,965 1,000 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1.93 2.65 (@ 8,573 hours) 1.90 1 CADM - - - Emond 31.8 58.4 (@ 2 hours) 27.7 100 CADM - - - Emond 78.6 103 (@ 2 hours) 72.7 1,000 CADM - - -



## C.3.1.23. Van Birgelen (1995) 1
Type: Rat Dose: 0, 13.5, 26.4, 46.9, 320, 1024 ng/kgday
Strain: Sprague Dawley Route: Oral gavage Body weight: 150 g Regime: Once per day for 13 weeks
Sex: Female Simulation time: 2184 hours (13 weeks) BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 3,969 6,098 (@ 2,160 hours) 4,665 13.5 CADM - - - Emond 6,479 10,258 (@ 2,160 hours) 7,457 26.4 CADM - - - Emond 9,968 16,284 (@ 2,160 hours) 11,313 46.9 CADM - - - Emond 47,606 86,065 (@ 2,160 hours) 52,581 320 CADM - - - Emond 137,820 258,910 (@ 2,160 hours) 151,680 1024 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-163 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1,655 2,208 (@ 2,164 hours) 2,107 13.5 CADM - - -
Emond 3,228 4,216 (@ 2,164 hours) 4,017 26.4 CADM - - -
Emond 5,719 7,366 (@ 2,164 hours) 7,008 46.9 CADM - - -
Emond 38,484 47,999 (@ 2,164 hours) 45,537 320 CADM - - - Emond 121,640 150,410 (@ 2,164 hours) 142,510 1024 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 669 843 (@ 2,167 hours) 835 13.5 CADM - - -
Emond 1,092 1,357 (@ 2,166 hours) 1,342 26.4 CADM - - -
Emond 1,680 2,071 (@ 2,166 hours) 2,045 46.9 CADM - - -
Emond 8,027 9,816 (@ 2,165 hours) 9,639 320 CADM - - -
Emond 23,234 28,519 (@ 2,165 hours) 27,954 1024 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 132 173 (@ 2,164 hours) 167 13.5 CADM - - -
Emond 240 308 (@ 2,164 hours) 296 26.4 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-164 DRAFT

— DO NOT CITE OR QUOTE Emond 404 513 (@ 2,164 hours) 492 46.9 CADM - - -
Emond 2,437 3,031 (@ 2,164 hours) 2,887 320 CADM - - -
Emond 7,521 9,310 (@ 2,164 hours) 8,846 1024 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 19.9 24.2 (@ 2,164 hours) 23.4 13.5 CADM - - - Emond 29.0 34.3 (@ 2,164 hours) 33.2 26.4 CADM - - - Emond 38.8 45.0 (@ 2,164 hours) 43.7 46.9 CADM - - - Emond 79.1 85.2 (@ 2,164 hours) 84.1 320 CADM - - - Emond 97.5 101 (@ 2,164 hours) 101 1024 CADM - - -



## C.3.1.24. Vanden Heuvel et al. (1994) 1
Type: Rat Dose: 0.05, 0.1, 1, 10, 100, 1000, 10000 ng/kg-day
Strain: Sprague Dawley Route: Oral gavage Body weight: 10 weeks old (BW 225 to 275g) (BW=250g) Regime: Single dose

Sex: Female Simulation time: 24 hours* 

## 2

a 

### 1 week is the minimum that can be simulated with the Aylward model 

## 3 4 5 BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 3.13 5.90 (@ 0 hours) 1.50 0.05 Aylward - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-165 DRAFT

— DO NOT CITE OR QUOTE Emond 6.21 11.9 (@ 0 hours) 2.97 0.1 Aylward - - - Emond 58.0 118 (@ 0 hours) 28.0 1 Aylward - - - Emond 484 1,183 (@ 0 hours) 234 10 Aylward - - - Emond 3,569 11,963 (@ 0 hours) 1,622 100 Aylward - - - Emond 26,736 119,860 (@ 0 hours) 9,984 1,000 Aylward - - - Emond 240,660 1,200,300 (@ 0 hours) 72,090 10,000 Aylward - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg) Model Time-weighted Ave Max Terminal
Emond 0.230 0.311 (@ 3 hours) 0.114 0.05 Aylward - - 0.0140
Emond 0.465 0.624 (@ 3 hours) 0.232 0.1 Aylward - - 0.0320
Emond 5.04 6.34 (@ 4 hours) 2.61 1 Aylward - - 0.950
Emond 59.7 67.9 (@ 5 hours) 34.0 10 Aylward - - 52.7
Emond 733 800 (@ 8 hours) 477 100 Aylward - - 1,342
Emond 8,215 8,918 (@ 10 hours) 5,941 1,000 Aylward - - 15,967
Emond 84,520 91,628 (@ 11 hours) 64,335 10,000 Aylward - - 162,773 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg) Model Time-weighted Ave Max Terminal
Emond 0.137 0.261 (@ 83 hours) 0.259 0.05 Aylward - - 0.780

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-166 DRAFT

— DO NOT CITE OR QUOTE Emond 0.272 0.518 (@ 84 hours) 0.515 0.1 Aylward - - 1.57
Emond 2.57 4.90 (@ 85 hours) 4.86 1 Aylward - - 15.3
Emond 22.0 41.4 (@ 89 hours) 41.0 10 Aylward - - 125
Emond 170 293 (@ 88 hours) 288 100 Aylward - - 739
Emond 1,354 1,905 (@ 69 hours) 1,824 1,000 Aylward - - 5,779
Emond 12,571 15,593 (@ 40 hours) 13,735 10,000 Aylward - - 55,825 BODY BURDEN (ng/kg)
Metric Dose (ng/kg) Model Time-weighted Ave Max Terminal
Emond 0.0267 0.028 (@ 9 hours) 0.0272 0.05 Aylward - - 0.0450
Emond 0.0534 0.056 (@ 9 hours) 0.0542 0.1 Aylward - - 0.0900
Emond 0.532 0.561 (@ 9 hours) 0.531 1 Aylward - - 0.900
Emond 5.29 5.59 (@ 8 hours) 5.02 10 Aylward - - 9.00
Emond 53.0 56.3 (@ 7 hours) 46.1 100 Aylward - - 90.0
Emond 527 562 (@ 7 hours) 424 1,000 Aylward - - 900
Emond 5,258 5,610 (@ 7 hours) 4,082 10,000 Aylward - - 9,000 BOUND LIVER (ng/kg)
Metric Dose (ng/kg) Model Time-weighted Ave Max Terminal
Emond 0.0192 0 (@ 4 hours) 0.00963 0.05 Aylward - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-167 DRAFT

— DO NOT CITE OR QUOTE Emond 0.0380 0 (@ 4 hours) 0.0191 0.1 Aylward - - - Emond 0.351 1 (@ 3 hours) 0.180 1 Aylward - - - Emond 2.75 4 (@ 3 hours) 1.48 10 Aylward - - - Emond 16.1 26 (@ 2 hours) 9.48 100 Aylward - - - Emond 57.7 77 (@ 2 hours) 40.7 1,000 Aylward - - - Emond 100 107 (@ 2 hours) 90.4 10,000 Aylward - - -



## C.3.1.25. White et al. (1986) 1
Type: Mice Dose: 10, 50, 100, 500, 1000, 2000 ng/kg-day
Strain: B6C3F1 Route: Oral gavage Body weight: 7 weeks old (BW set to 23g) Regime: 1/day for 14 days

Sex: Female Simulation time: 336 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 603 1,502 (@ 312 hours) 785 10 CADM - - - Emond 2,250 6,387 (@ 312 hours) 2,742 50 CADM - - - Emond 3,934 11,970 (@ 312 hours) 4,650 100 CADM - - - Emond 14,772 53,188 (@ 312 hours) 16,394 500 CADM - - - Emond 26,844 102,960 (@ 312 hours) 29,229 1,000 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-168 DRAFT

— DO NOT CITE OR QUOTE Emond 49,896 201,110 (@ 312 hours) 53,697 2,000 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 216 375 (@ 317 hours) 343 10 CADM 217 468 (336h) 463 Emond 1,279 2,164 (@ 317 hours) 1,997 50 CADM 1,775 3,261 (336h) 3,261 Emond 2,707 4,525 (@ 317 hours) 4,184 100 CADM 3,999 6,923 (336h) 6,923 Emond 14,802 24,165 (@ 317 hours) 22,383 500 CADM 22,705 36,362 (336h) 36,362 Emond 30,278 49,034 (@ 317 hours) 45,414 1,000 CADM 46,309 73,145 (336h) 73,145 Emond 61,381 98,703 (@ 317 hours) 91,363 2,000 CADM 93,577 146,695 (336h) 146,695 FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 279 507 (@ 336 hours) 507 10 CADM 316 537 (336h) 537 Emond 1,056 1,846 (@ 336 hours) 1,846 50 CADM 1,029 1,564 (336h) 1,564 Emond 1,854 3,195 (@ 333 hours) 3,195 100 CADM 1,662 2,470 (336h) 2,470 Emond 7,008 11,868 (@ 324 hours) 11,816 500 CADM 5,711 8,594 (336h) 8,594 Emond 12,746 21,566 (@ 323 hours) 21,424 1,000 CADM 10,498 15,993 (336h) 15,993 Emond 23,691 40,177 (@ 322 hours) 39,843 2,000 CADM 19,990 30,726 (336h) 30,726

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-169 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 37.7 65.9 (@ 317 hours) 63.8 10 CADM 47.9 85.9 (336h) 85.9
Emond 175 297 (@ 317 hours) 284 50 CADM 207 342 (336h) 342
Emond 338 570 (@ 316 hours) 542 100 CADM 388 624 (336h) 624 Emond 1,597 2,637 (@ 316 hours) 2,480 500 CADM 1,761 2,754 (336h) 2,754 Emond 3,137 5,153 (@ 316 hours) 4,830 1,000 CADM 3,455 5,387 (336h) 5,387 Emond 6,186 10,118 (@ 316 hours) 9,459 2,000 CADM 6,836 10,643 (336h) 10,643 BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 3.49 5.32 (@ 316 hours) 4.82 10 CADM - - - Emond 11.4 16.4 (@ 317 hours) 15.1 50 CADM - - - Emond 18.1 25.1 (@ 317 hours) 23.4 100 CADM - - - Emond 44.2 56.2 (@ 317 hours) 53.8 500 CADM - - - Emond 59.3 71.9 (@ 317 hours) 69.7 1,000 CADM - - - Emond 74.4 86.1 (@ 317 hours) 84.3 2,000 CADM - - -



## 1 2 3 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-170 DRAFT

— DO NOT CITE OR QUOTE C.3.2. Gestational Studies 1 C.3.2.1. Bell et al. (2007) 2
Type: Rat Dose: 2.4, 8, and 46 ng/kg-day with a 0.03 ng/kg-day background
Strain: Han/Wistar Route: Dietary Body weight: 6 weeks (BW= 85g) Regime: 12 weeks prior to mating, during the two week mating period, and during gestation
Sex: Female Simulation time: 2,352 hr (98 days) prior to gestation + 504 hr (21 days) during gestation for a total of 2,856 hours

a 

### Time averages are computed duri ng the gestation period only.

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2.43 1,998 4,977,500 2,452 (@ 2,352 hours) 1,745

8.03 4,539 11,602,000 5,781 (@ 2,352 hours) 4,023

46.03 15,952 41,518,000 22,096 (@ 2,352 hours) 14,275
LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2.43 381 914,700 437 (@ 2,356 hours) 321

8.03 1,201 2,970,500 1,351 (@ 2,356 hours) 1,044

46.03 6,638 16,802,000 7,260 (@ 2,356 hours) 5,980
FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2.43 233 585,680 263 (@ 2,336 hours) 211
8.03 528 1,365,300 589 (@ 2,335 hours) 487

46.03 1,851 4,885,900 2,039 (@ 2,334 hours) 1,739

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-171 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2.43 43.0 94,428 44.5 (@ 2,836 hours) 43.4
8.03 113 258,160 118 (@ 2,836 hours) 114
46.03 506 1,204,800 529 (@ 2,836 hours) 509 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2.43 17.2 8,674 39.7 (@ 2,530 hours) 6.53
8.03 37.7 19,002 86.7 (@ 2,529 hours) 14.4
46.03 118 59,628 271 (@ 2,527 hours) 45.9 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2.43 8.13 20,295 8.98 (@ 2,356 hours) 7.24
8.03 16.8 43,248 18.2 (@ 2,356 hours) 15.4
46.03 42.7 112,990 44.7 (@ 2,356 hours) 40.5



## C.3.2.2. Hojo et al. (2002) 1
Type: 

## Rat Dose: 20, 60 and 180 ng/kg
Strain: 

## Sprague Dawley Route: Oral gavage Body weight 20 ng/kg BW = 271g 60 ng/kg BW = 275g 180 ng/kg BW = 262g Regime: Single dose on GD8

Sex: Female Simulation time 24 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 1,285 177,790 3,534 (@ 192 hours) 402
60 3,295 452,060 10,477 (@ 192 hours) 1,002

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-172 DRAFT

— DO NOT CITE OR QUOTE 180 8,465 1,114,200 31,887 (@ 192 hours) 2,396 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 128 20,554 144 (@ 198 hours) 43.2
60 420 72,340 465 (@ 200 hours) 147
180 1,364 250,820 1,497 (@ 201 hours) 497 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 32.5 17,253 63.0 (@ 281 hours) 49.4
60 86.4 44,093 161 (@ 284 hours) 124
180 226 108,730 398 (@ 286 hours) 301 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 10.6 3,054 11.3 (@ 200 hours) 8.67
60 31.8 8,702 33.8 (@ 199 hours) 23.6
180 95.0 24,747 101 (@ 199 hours) 63.4 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 15.9 2,334 18.4 (@ 206 hours) 1.64
60 39.8 5,829 45.7 (@ 205 hours) 4.10
180 96.3 13,866 110 (@ 203 hours) 9.72 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 4.88 759 7.74 (@ 194 hours) 1.75
60 11.2 1,848 18.5 (@ 194 hours) 4.26
180 23.6 4,157 38.5 (@ 193 hours) 9.65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-173 DRAFT

— DO NOT CITE OR QUOTE C.3.2.3. Ikeda et al. (2005) 1
Type: Rat Dose: 400 ng/kg single dose and 80 ng/kg weekly maintenance dose
Strain: 

## Sprague Dawley Route: Oral gavage Body weight: 10 weeks (BW= 250g) Regime: Initial single loading dose, 2 weekly maintenance doses prior to gestation and 2 weekly maintenance doses during gestation
Sex: Female Simulation time: 504 hr (21 days) prior to gestation + 504 hr (21 days) during gestation for a total simulation of 1,008 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

16.5 18,103 18,249,000 80,047 (@ 144 hours) 8,009 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

16.5 7,755 7,817,300 17,016 (@ 150 hours) 2,698 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

16.5 2,087 2,103,900 3,663 (@ 184 hours) 1,028 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

16.5 548 552,590 1,085 (@ 149 hours) 262 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

16.5 45.9 46,290 245 (@ 679 hours) 30.2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-174 DRAFT

— DO NOT CITE OR QUOTE BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

16.5 44.0 44,361 63.8 (@ 149 hours) 26.8



## C.3.2.4. Kattainen et al. (2001) 1
Type: Rat Dose: 30, 100, 300, and 1,000 ng/kg
Strain: Han/Wistar (Kuopio) and Long/Evans (Turku/AB) crossing. Route: Oral gavage

Body weight: BW not specified (BW set to 190g)* Regime: Single dose on GD15

Sex: Female Simulation time: 24 hours

a 

### Derelanko and Hollinger (1995).

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 1,763 151,690 4,703 (@ 336 hours) 632
100 4,944 423,680 15,679 (@ 336 hours) 1,761
300 12,712 1,054,600 47,253 (@ 336 hours) 4,327 1,000 37,039 2,878,700 158,470 (@ 336 hours) 11,429 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 193 19,784 219 (@ 342 hours) 78.9
100 713 79,889 793 (@ 344 hours) 324
300 2,298 276,990 2,533 (@ 345 hours) 1,150 1,000 8,054 1,032,300 8,830 (@ 345 hours) 4,412

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-175 DRAFT

— DO NOT CITE OR QUOTE FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 42.8 12,439 82.8 (@ 426 hours) 77.5
100 123 34,712 230 (@ 431 hours) 217
300 327 86,670 571 (@ 431 hours) 536 1,000 981 238,680 1,551 (@ 425 hours) 1,435 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 15.9 2,562 16.9 (@ 343 hours) 14.1
100 52.7 8,273 56.2 (@ 343 hours) 44.2
300 158 24,176 168 (@ 343 hours) 125 1,000 524 78,767 561 (@ 343 hours) 395 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 4.86 828 6.90 (@ 372 hours) 2.53
100 13.2 2,221 18.2 (@ 372 hours) 6.89
300 31.5 5,200 42.3 (@ 371 hours) 16.2 1,000 82.2 12,907 106 (@ 369 hours) 39.6 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 6.58 634 10.7 (@ 338 hours) 2.73
100 15.8 1,642 26.3 (@ 338 hours) 7.28
300 31.6 3,538 50.6 (@ 337 hours) 16.3 1,000 57.1 7,095 80.1 (@ 337 hours) 34.8



## C.3.2.5. Keller et al. (2007) 1
Type: Mouse Dose: 10, 100, and 1000 ng/kg
Strain: CBA/J and C3H/HeJ Route: Oral

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-176 DRAFT

— DO NOT CITE OR QUOTE Body weight: Not specified (24 g used in the simulation) Regime: Single dose on GD13

Sex: Female Simulation time: 504 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

10 296 18,384 788 (@ 312 hours) 48.4
100 2,365 149,060 7,884 (@ 312 hours) 374 1,000 18,764 1,083,900 78,825 (@ 312 hours) 2,454 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

10 30.6 2,046 39.8 (@ 316 hours) 4.90
100 371 28,867 421 (@ 319 hours) 62.7 1,000 4,214 388,320 4,697 (@ 321 hours) 833 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

10 22.4 7,075 41.1 (@ 386 hours) 35.9
100 188 57,462 333 (@ 396 hours) 291 1,000 1,591 425,300 2,441 (@ 392 hours) 2,064 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

10 5.57 1,024 5.99 (@ 319 hours) 4.99
100 54.3 9,170 59.0 (@ 318 hours) 41.9 1,000 530 79,818 581 (@ 318 hours) 323

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-177 DRAFT

— DO NOT CITE OR QUOTE FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

10 2.57 386 3.80 (@ 337 hours) 0.795
100 21.8 3,109 30.0 (@ 334 hours) 6.42 1,000 179 22,097 233 (@ 329 hours) 42.6 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

10 1.74 115 3.14 (@ 315 hours) 0.305
100 11.5 857 23.5 (@ 314 hours) 2.30 1,000 46.7 4,430 79.8 (@ 314 hours) 13.3



## C.3.2.6. Li et al. (2006) 3-Day 1
Type: Mouse Dose: 2, 50, and 100 ng/kg-day
Strain: NIH Route: Oral gavage Body weight: 25-28 g (used 27 g in the simulation) Regime: Daily exposure from GD1 to GD3

Sex: Female Simulation time: 72 hours 

## 2 3 BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2 87.5 6,305 216 (@ 48 hours) 75.1
50 1,564 112,720 4,906 (@ 48 hours) 1,312
100 2,823 203,490 9,547 (@ 48 hours) 2,313 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2 8.98 647 15.1 (@ 52 hours) 9.10
50 333 23,971 539 (@ 53 hours) 402
100 718 51,738 1,156 (@ 53 hours) 888

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-178 DRAFT

— DO NOT CITE OR QUOTE FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2 17.0 1,227 31.1 (@ 72 hours) 31.1
50 315 22,704 548 (@ 72 hours) 548
100 576 41,460 984 (@ 72 hours) 984 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2 2.29 165 3.51 (@ 55 hours) 3.43
50 53.6 3,863 82.2 (@ 54 hours) 77.1
100 105 7,598 162 (@ 53 hours) 150 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2 0.00 0 0.000 (@ 72 hours) 0.00
50 0.0 0 0.000 (@ 72 hours) 0.00
100 0.0 0 0.000 (@ 72 hours) 0.00 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

2 0.538 38.8 0.864 (@ 51 hours) 0.498
50 8.24 594 13.5 (@ 2 hours) 8.16
100 13.6 981 23.7 (@ 2 hours) 13.6 

## 1 2 C.3.2.7. Markowski et al. (2001) 3
Type: Rat Dose: 20, 60 and 180 ng/kg
Strain: Holtzman rats Route: Oral gavage Body weight: BW not specified (BW set to 190g)* Regime: Single dose on GD18

Sex: Female Simulation time: 24 hours

a 

### Derelanko and Hollinger (1995).

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-179 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 1,234 71,255 3,029 (@ 408 hours) 471
60 3,184 184,690 9,096 (@ 408 hours) 1,317
180 8,152 465,030 27,457 (@ 408 hours) 3,193 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 123 8,315 142 (@ 414 hours) 56.5
60 409 29,656 459 (@ 415 hours) 213
180 1,333 103,210 1,478 (@ 416 hours) 790 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 28.0 4,437 55.6 (@ 498 hours) 55.5
60 74.0 11,462 144 (@ 504 hours) 144
180 195 28,948 363 (@ 504 hours) 363 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 10.6 1,013 11.3 (@ 415 hours) 10.2
60 31.7 2,989 33.7 (@ 415 hours) 29.5
180 94.7 8,834 101 (@ 415 hours) 85.7 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 1.26 157 1.93 (@ 448 hours) 1.43
60 3.21 395 4.79 (@ 449 hours) 3.63
180 7.80 943 11.3 (@ 449 hours) 8.69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-180 DRAFT

— DO NOT CITE OR QUOTE BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

20 4.75 299 7.61 (@ 410 hours) 2.12
60 11.0 729 18.2 (@ 410 hours) 5.47
180 23.2 1,621 38.1 (@ 409 hours) 12.9



## C.3.2.8. Mietinnen et al. (2006) 1
Type: Rat Dose: 30, 100, 300 and 1000 ng/kg
Strain: cross-breeding ofHan/Wistar and LongEvans rats Route: Oral gavage

Body weight: BW 11 weeks (BW set to 180g) Regime: Single dose on GD15

Sex: Female Simulation time: 24 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 1,756 151,180 4,641 (@ 336 hours) 721
100 4,922 422,480 15,471 (@ 336 hours) 1,758
300 12,657 1,052,000 46,647 (@ 336 hours) 4,994 1,000 36,874 2,872,800 156,480 (@ 336 hours) 11,423 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 193 19,697 219 (@ 342 hours) 78.8
100 711 79,610 791 (@ 344 hours) 323
300 2,293 276,280 2,529 (@ 345 hours) 1,149 1,000 8,044 1,030,600 8,822 (@ 345 hours) 4,409

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-181 DRAFT

— DO NOT CITE OR QUOTE FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 43.1 12,461 82.9 (@ 425 hours) 77.4
100 124 34,793 231 (@ 430 hours) 217
300 329 86,906 572 (@ 430 hours) 536 1,000 988 239,390 1,555 (@ 424 hours) 1,436 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 15.9 2,560 16.9 (@ 343 hours) 14.1
100 52.7 8,269 56.2 (@ 343 hours) 44.1
300 158 24,169 168 (@ 343 hours) 125 1,000 524 78,769 561 (@ 343 hours) 395 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 4.83 824 6.87 (@ 372 hours) 2.52
100 13.1 2,213 18.1 (@ 372 hours) 6.87
300 31.3 5,182 42.1 (@ 371 hours) 16.2 1,000 81.7 12,867 105 (@ 369 hours) 39.5 BOUND LIVER (ng/kg) and AUC ( (ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

30 6.56 632 10.7 (@ 338 hours) 2.72
100 15.8 1,639 26.3 (@ 338 hours) 7.27
300 31.6 3,533 50.5 (@ 337 hours) 16.3 1,000 57.0 7,090 80.1 (@ 337 hours) 34.8



## C.3.2.9. Murray et al. (1979) Gestational Portion 1
Type: Rat Dose: 1, 10, and 100 ng/kg-day
Strain: Sprague Dawley Route: Diet oral dose

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-182 DRAFT

— DO NOT CITE OR QUOTE Body weight: 6- to 7 week (Bw= 85g) Regime: Once per day for 90 days prior to gestation and during gestation
Sex: Female Simulation time: 2160 hr (90 days ) prior gestation + 504 hr (21 days) for a total simulation of 2664 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

1 897 2,389,400 1,291 (@ 2,160 hours) 926
10 4,691 12,497,000 6,780 (@ 2,160 hours) 4,708
100 26,219 69,849,000 42,272 (@ 2,160 hours) 25,849 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

1 129 342,940 186 (@ 2,164 hours) 133
10 1,271 3,385,700 1,657 (@ 2,164 hours) 1,298
100 12,492 33,279,000 15,332 (@ 2,164 hours) 12,876 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

1 105 280,460 142 (@ 2,146 hours) 112
10 551 1,467,700 682 (@ 2,143 hours) 569
100 3,080 8,204,300 3,682 (@ 2,142 hours) 3,162 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

1 15.4 41,059 21.8 (@ 2,644 hours) 21.4
10 108 286,920 141 (@ 2,644 hours) 137
100 847 2,257,100 1,060 (@ 2,644 hours) 1,017

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-183 DRAFT

— DO NOT CITE OR QUOTE FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

1 1.77 4,720 21.7 (@ 2,339 hours) 3.54
10 8.22 21,889 99.8 (@ 2,337 hours) 16.7
100 37.4 99,722 453 (@ 2,334 hours) 77.0 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

1 3.79 10,101 5.06 (@ 2,163 hours) 3.96
10 17.1 45,522 20.5 (@ 2,164 hours) 17.6
100 55.1 146,790 61.0 (@ 2,164 hours) 56.8



## C.3.2.10. Murray et al. (1979) Adult Portion 1
Type: Rat Dose: 1, 10, and 100 ng/kg-day
Strain: Sprague Dawley Route: Dietary Body weight: BW set to 4.5 g Regime: 120 days
Sex: Female Simulation time: 2880 hours

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 619 832 (@ 2,856 hours) 785 1 CADM - - - Emond 3,241 4,181 (@ 2,856 hours) 3,717 10 CADM - - - Emond 18,038 24,433 (@ 2,856 hours) 19,844 100 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-184 DRAFT

— DO NOT CITE OR QUOTE LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 128 180 (@ 2,859 hours) 173 1 CADM - - - Emond 1,273 1,618 (@ 2,860 hours) 1,540 10 CADM - - - Emond 12,601 15,281 (@ 2,860 hours) 14,460 100 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 106 139 (@ 2,865 hours) 138 1 CADM - - - Emond 556 665 (@ 2,864 hours) 657 10 CADM - - - Emond 3,095 3,604 (@ 2,862 hours) 3,534 100 CADM - - - BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 14.8 20.0 (@ 2,860 hours) 19.6 1 CADM - - - Emond 105 130 (@ 2,860 hours) 126 10 CADM - - - Emond 837 1,003 (@ 2,860 hours) 957 100 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 3.77 4.95 (@ 2,859 hours) 4.77 1 CADM - - - Emond 17.1 20.3 (@ 2,859 hours) 19.5 10 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-185 DRAFT

— DO NOT CITE OR QUOTE Emond 55.3 60.9 (@ 2,860 hours) 59.4 100 CADM - - -



## C.3.2.11. Nohara et al. (2000) 1
Type: Rat Dose: 12.5, 50, 200 or 800 ng TCDD/kg
Strain: Holtzman rats Route: Oral gavage Body weight: BW not specified (BW set to 190g)* Regime: Single dose on GD15

Sex: Female Simulation time: 24 hours

a 

### Derelanko and Hollinger (1995).

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 816 69,459 1,933 (@ 336 hours) 290
50 2,724 235,070 7,736 (@ 336 hours) 981
200 8,912 752,170 31,022 (@ 336 hours) 3,110
800 30,121 2,378,900 125,030 (@ 336 hours) 9,532 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 73.9 7,084 86.2 (@ 341 hours) 28.3
50 336 35,736 378 (@ 343 hours) 143
200 1,492 175,300 1,651 (@ 344 hours) 722
800 6,387 810,340 7,011 (@ 345 hours) 3,449 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 19.7 5,736 38.1 (@ 419 hours) 35.4
50 67.6 19,362 129 (@ 427 hours) 121
200 229 62,032 410 (@ 431 hours) 385

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-186 DRAFT

— DO NOT CITE OR QUOTE 800 803 197,830 1,288 (@ 425 hours) 1,194 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 6.63 1,088 7.05 (@ 343 hours) 6.10
50 26.4 4,212 28.1 (@ 343 hours) 22.9
200 105 16,259 112 (@ 343 hours) 85.1
800 420 63,228 449 (@ 343 hours) 319 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 2.25 385 3.26 (@ 371 hours) 1.17
50 7.43 1,263 10.5 (@ 372 hours) 3.89
200 22.8 3,802 31.0 (@ 372 hours) 11.8
800 68.1 10,862 88.5 (@ 369 hours) 33.6 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 3.24 298 5.12 (@ 338 hours) 1.27
50 9.66 959 16.0 (@ 338 hours) 4.18
200 24.8 2,695 40.7 (@ 337 hours) 12.2
800 51.9 6,315 75.0 (@ 337 hours) 30.6



## C.3.2.12. Ohsako et al. (2001) 1
Type: 

## Rat Dose: 12.5, 50, 200, and 800 ng/kg-day

Strain: 

## Holtzmann Route: Oral gavage Body weight 10 weeks (200g ) Regime: Single dose on GD15
Sex: Female Simulation time 24 hours

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-187 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 845 63,918 2,016 (@ 360 hours) 304
50 2,763 212,870 7,928 (@ 360 hours) 1,020
200 9,022 677,090 31,557 (@ 360 hours) 3,239
800 30,504 2,148,100 127,220 (@ 360 hours) 9,983 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 76.8 6,595 89.0 (@ 365 hours) 30.1
50 340 32,557 383 (@ 367 hours) 152
200 1,504 157,600 1,657 (@ 368 hours) 768
800 6,426 724,530 7,026 (@ 369 hours) 3,689 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 19.6 4,897 38.4 (@ 446 hours) 36.9
50 65.8 16,240 128 (@ 455 hours) 124
200 223 51,709 404 (@ 458 hours) 393
800 780 165,660 1,270 (@ 453 hours) 1,224 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 6.84 966 7.24 (@ 367 hours) 6.38
50 26.6 3,693 28.4 (@ 367 hours) 23.7
200 106 14,210 112 (@ 367 hours) 88.3
800 421 55,466 449 (@ 367 hours) 334 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 1.69 274 2.50 (@ 397 hours) 1.16

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-188 DRAFT

— DO NOT CITE OR QUOTE 50 5.48 881 7.91 (@ 398 hours) 3.79
200 16.8 2,629 23.3 (@ 398 hours) 11.4
800 50.2 7,518 66.4 (@ 396 hours) 32.3 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

12.5 3.34 274 5.25 (@ 362 hours) 1.33
50 9.76 863 16.1 (@ 362 hours) 4.34
200 25.0 2,396 40.7 (@ 361 hours) 12.7
800 52.1 5,566 75.1 (@ 361 hours) 31.7 

## 1 2 C.3.2.13. Schantz et al. (1995) and Amin et al. (2000) 3
Type: Rat Dose: 25 and 100 ng/kg-day
Strain: Sprague Dawley Route: Oral gavage Body weight: BW not specified (BW set to 250g) Regime: Daily doses from GD 10 - 16

Sex: Female Simulation time: 384 hours; time averages are calculated from the beginning of the dosing 

## 4 5 BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 2,670 384,750 6,800 (@ 360 hours) 3,190
100 8,341 1,201,700 24,522 (@ 360 hours) 9,706 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 512 73,705 871 (@ 365 hours) 778
100 2,371 341,460 4,009 (@ 366 hours) 3,662

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-189 DRAFT

— DO NOT CITE OR QUOTE FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 169 24,329 307 (@ 384 hours) 307
100 532 76,559 949 (@ 384 hours) 949 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 45 6,492 76.6 (@ 365 hours) 74
100 176 25,401 298 (@ 365 hours) 287 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 25 3,628 30.4 (@ 343 hours) 27
100 74.0 10,655 88.1 (@ 342 hours) 77.8 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 10 1,440 14.4 (@ 364 hours) 13
100 25 3,628 34.2 (@ 364 hours) 32 

## 1 2 C.3.2.14. Seo et al. (1995) 3
Type: Rat Dose: 25 and 100 ng/kg-day
Strain: Sprague Dawley Route: Oral gavage Body weight: BW not specified (BW set to 190g) Regime: Daily from GD 10 - 16

Sex: Female Simulation time: 384 hours; time averages are calculated from the beginning of the dosing 

## 4 5 6 7 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-190 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 2,655 766,430 6,796 (@ 384 hours) 2,748
100 8,319 2,372,700 24,284 (@ 384 hours) 8,333 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 506 163,400 972 (@ 389 hours) 606
100 2,358 767,640 4,486 (@ 389 hours) 2,871 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 173 66,734 358 (@ 436 hours) 339
100 545 207,420 1,105 (@ 433 hours) 1,037 BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 45.3 16,124 87.5 (@ 389 hours) 73.6
100 177 61,908 339 (@ 389 hours) 271 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 24.7 5,826 29.8 (@ 343 hours) 10.6
100 72.6 16,930 86.6 (@ 342 hours) 30.2 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

25 9.92 2,937 15.4 (@ 388 hours) 11.0
100 25.1 7,349 36.1 (@ 388 hours) 27.7 

## 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-191 DRAFT

— DO NOT CITE OR QUOTE C.3.2.15. Shi et al. (2007) Gestational Portion 1
Type: Rat Dose: 1, 5, 50 and 200 ng/kg
Strain: Sprague Dawley Route: Oral gavage Body weight: BW not specified (BW set to 190g)* Regime: Single dose on GD14 and GD21

Sex: Female Simulation time: 504 hours

a 

### Derelanko and Hollinger (1995).

BLOOD CONCENTRATIONS (ng/kg) (Serum lipid adjusted) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

0.143 17.9 9,014 173 (@ 480 hours) 74.7
0.714 81.1 40,871 840 (@ 480 hours) 329
7.14 621 312,880 8,016 (@ 480 hours) 2,310
28.6 1,975 995,020 31,730 (@ 312 hours) 6,960 LIVER CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

0.143 1.16 583 8.44 (@ 484 hours) 5.63
0.714 6.87 3,462 46.8 (@ 485 hours) 35.2
7.14 96.9 48,840 576 (@ 486 hours) 499
28.6 465 234,480 2,581 (@ 487 hours) 2,328 FAT CONCENTRATIONS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

0.143 1.31 662 5.66 (@ 504 hours) 5.66
0.714 6.02 3,032 25.2 (@ 504 hours) 25.2
7.14 46.9 23,608 188 (@ 504 hours) 188
28.6 150 75,504 591 (@ 504 hours) 591

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-192 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

0.143 0.229 116 1.08 (@ 487 hours) 1.07
0.714 1.12 565 5.32 (@ 487 hours) 5.23
7.14 10.7 5,389 50.8 (@ 487 hours) 49.4
28.6 41.3 20,788 196 (@ 487 hours) 190 FETUS (ng/kg) and AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

0.143 0.103 52.0 0.430 (@ 343 hours) 0.151
0.714 0.470 237 1.91 (@ 344 hours) 0.681
7.14 3.53 1,781 13.8 (@ 345 hours) 5.04
28.6 10.6 5,354 41.0 (@ 345 hours) 15.1 BOUND LIVER (ng/kg) an d AUC ((ng/kg) • hr)
Metric Dose (ng/kg-day) Adjusted dose Time-weighted Ave Area Under the Curve Max Terminal

0.143 0.0780 39.3 0.566 (@ 483 hours) 0.341
0.714 0.348 175 2.31 (@ 483 hours) 1.49
7.14 2.44 1,231 16.0 (@ 314 hours) 9.67
28.6 6.67 3,360 40.8 (@ 313 hours) 24.8



## C.3.2.16. Shi et al. (2007) Adult Portion 1
Type: Rat Dose: 1, 5, 50 and 200 ng/kg
Strain: Sprague Dawley Route: Oral gavage Body weight: BW set to 4.5 g Regime: Weekly doses for 11 months
Sex: Female Simulation time: 8040 hours

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-193 DRAFT

— DO NOT CITE OR QUOTE BLOOD CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 188 262 (@ 7,561 hours) 210 0.143 CADM - - - Emond 592 844 (@ 7,560 hours) 603 0.714 CADM - - - Emond 2,882 5,023 (@ 7,560 hours) 2,679 7.14 CADM - - - Emond 7,665 16,103 (@ 7,560 hours) 6,825 28.6 CADM - - - LIVER CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 26.1 36.5 (@ 7,564 hours) 29.6 0.143 CADM - - - Emond 118 159 (@ 7,564 hours) 120 0.714 CADM - - - Emond 1,068 1,415 (@ 7,565 hours) 970 7.14 CADM - - - Emond 4,119 5,450 (@ 7,565 hours) 3,574 28.6 CADM - - - FAT CONCENTRATIONS (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 32.5 40.0 (@ 7,583 hours) 36.7 0.143 CADM - - - Emond 102 120 (@ 7,584 hours) 106 0.714 CADM - - - Emond 497 571 (@ 7,584 hours) 475 7.14 CADM - - - Emond 1,322 1,527 (@ 7,584 hours) 1,217 28.6 CADM - - -

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-194 DRAFT

— DO NOT CITE OR QUOTE BODY BURDEN (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 3.94 4.99 (@ 7,566 hours) 4.45 0.143 CADM - - - Emond 14.0 17.2 (@ 7,566 hours) 14.5 0.714 CADM - - - Emond 90.8 112 (@ 7,566 hours) 84.4 7.14 CADM - - - Emond 300 374 (@ 7,566 hours) 266 28.6 CADM - - - BOUND LIVER (ng/kg)
Metric Dose (ng/kg-day) Adjusted dose Model Time-weighted Ave Max Terminal

Emond 1.18 1.60 (@ 7,563 hours) 1.31 0.143 CADM - - - Emond 3.62 4.75 (@ 7,563 hours) 3.70 0.714 CADM - - - Emond 15.6 19.7 (@ 7,564 hours) 14.7 7.14 CADM - - - Emond 33.5 40.7 (@ 7,564 hours) 31.2 28.6 CADM - - - 

## 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-195 DRAFT

— DO NOT CITE OR QUOTE Table C-1. Model input parameters potentially addressed by selected 1 articles 2 3 Model input parameters potentially addressed

ArticlesAbsorptionDesorptionDistributionEliminationKineticsInduction CYP1A1InterspeciesdifferencesAge DifferencesAryl hydrocarbonreceptor (AhR)Mode of actionPartitioncoefficient



### Aylward et al., 2004 ● ● ● ● ● Aylward et al., 2005 ● ● ● ● ● Aylward et al., 2009 ● Bohonowych and Denison, 2007 ● ● ● Boverhof et al., 2005 ● ● Connor and Aylward, 2006 ● ● ● Heinzl et al., 2007 ● ● Irigaray et al., 2005 ● ● Kerger et al., 2006 ● ● ● Kerger et al., 2007 ● Kim et al., 2003 ● Korenaga et al., 2007 ● ● Korkalainen et al., 2004 ● ● Kransler et al., 2007 ● ● Maruyama et al., 2002 ● ● ● Maruyama et al., 2003 ● ● ● Maruyama and Aoki, 2006 ● ● ● Millbrath et al., 2009 ● ● ● ● Moser and McLachlan, 2002 ● ● Mullerova and Kopecky, 2007 ● Nadal et al., 2009 ● ● Nohara et al., 2006 ● ● Olsman et al., 2007 ● Saghir et al., 2005 ● ● ● Schecter et al., 2003 ● ● Staskal et al., 2005 ● ● Toyoshiba et al., 2004 ● ● ● Wilkes et al., 2009 ●

a 

### Partition coefficient estimates and CYP parameter value estimates were derived from Wang et al. (1997, 2000) and 

## 4 Santostefano et al. (1998). 

## 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 C-196 DRAFT

— DO NOT CITE OR QUOTE C.4. REFERENCES 1 Amin, S; Moore, RW; Peterson, RE; et al. (2000) Gestatio nal and lactational exposure to TCDD or coplanar PCBs 

## 2 alters adult expression of saccharin preference behavior in female rats. Neurotoxicol Teratol 22(5):675–682. 

## 3
Aylward, LL; Brunet, RC; Ca rrier, G; et al. (2005a) Concentration-dependent TCDD elimination kinetics in 

## 4 humans: toxicokinetic modeling for moderately to highly exposed adults from Seveso, Italy, and Vienna, Austria, 

## 5 and impact on dose estimates for the NIOSH coho rt. J Exp Anal Environ Epidemiol 15:51–65. 

## 6
Aylward, LL; Brunet, RC; Starr, TB; et al. (2005b) Exposure reconstruction for the TCDD-exposed NIOSH cohort 

## 7 using a concentration- and age-dependent model of elimination. Risk Anal 25(4):945–956. 

## 8
Aylward, LL; Bodner, KM; Collins, JJ; et al. (2009) TC DD exposure estimation for workers at a New Zealand 

## 9 2,4,5-T manufacturing facility based on serum sampling data. J Expo Sci Environ Epidemiol. 3 June; 

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32

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX D
Epidemiological Kinetic Modeling

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-ii CONTENTS—APPENDIX D: Epidem iological Kinetic Modeling 1 LIST OF TABLES.................................................................................................................

.... D-iii 2 3 APPENDIX D. EPIDEMIOLOGICAL KINETIC MODELING ............................................ D-1 4 D.1. BACCARELLI ET AL. (2008) MODELING......................................................... D-1 5 D.1.1. Input File for Exposure During Pregnancy................................................ D-1 6 D.1.2. Table of Results for Baccarelli et al. (2008).............................................. D-1 7 D.2. MOCARELLI ET AL. (2008) MODELING .......................................................... D-2 8 D.2.1. Input File for Exposure for Puls e to Measurem ent 0.5 Years After the 9 Seveso Pulse Dose ..................................................................................... D-2 10 D.2.2. Input File for Exposure from Pulse to the End of the Critical W indow 11 3.8 Years After the Seveso Pulse Dose...................................................... D-2 12 D.2.3. Input File for Continuous Exposure for 10 Years...................................... D-3 13 D.2.4. Tables of Results for Mocarelli et al. (2008) ............................................. D-4 14 D.3. ALALUUSUA ET AL. (2004) MODELING ......................................................... D-4 15 D.3.1. Input File for Exposure for Puls e to Measurem ent 0.5 Years After the 16 Seveso Pulse Dose ..................................................................................... D-4 17 D.3.2. Input File for Exposure from Pulse to the End of the Critical W indow 18 2.5 Years After the Seveso Pulse Dose...................................................... D-5 19 D.3.3. Input File for Continuous Exposure for 5 Years........................................ D-5 20 D.3.4. Tables of Results fo r Alaluusua et al. (2004)

............................................ D-6 21 D.4. ESKANAZI ET AL. (2002) MODELING.............................................................. D-7 22 D.4.1. Input File for Exposure for Puls e to Measurem ent 0.5 Years After the 23 Seveso Pulse Dose ..................................................................................... D-7 24 D.4.2. Input File for Exposure from Pulse to the End of the Critical W indow 25 6.7 Years After the Seveso Pulse Dose...................................................... D-8 26 D.4.3. Input File for Continuous Exposure for 13 Years...................................... D-8 27 D.4.4. Tables of Results for Eskanazi et al. (2002) .............................................. D-9 28 D.5. REFERENCES...................................................................................................... D-10 29

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-iii LIST OF TABLES

D-1. Estimated continuous in take corresponding to maternal serum concentration in 1 Figure 2A

........................................................................................................................ D-1 2
D-2. Estimated maximum intake corresponding to m aternal serum concentration in 3 Figure 2A ........................................................................................................................ D-2 4
D-3. Matching critical window average after pu lse to critical window average for 5 continuous intake run...................................................................................................... D-4 6
D-4. Matching critical window peak after pulse to peak critical window concentration 7 for continuous intake run

................................................................................................ D-4 8
D-5. Matching critical window average after pu lse to critical window average for 9 continuous intake run...................................................................................................... D-6 10
D-6. Matching critical window peak af ter pulse to peak critical window 11 concentration for continuous intake run

......................................................................... D-7 12
D-7. Matching critical window average after pu lse to critical window average for 13 continuous intake run...................................................................................................... D-9 14
D-8. Matching critical window peak af ter pulse to peak critical window 15 concentration for continuous intake run

......................................................................... D-9 16

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-1 APPENDIX D. EPIDEMIOLOGICAL KINETIC MODELING 1 2 3 D.1. BACCARELLI ET AL. (2008) MODELING 4
D.1.1. Input File for Exposure During Pregnancy 5 CINT = 1 %168 %100 %integration time 6 %Exposure scenario 7 EXP_TIME_ON = 0 % delay before begin exposure (HOUR) 8 EXP_TIME_OFF = 401190 %TIME EXPOSURE STOP (HOUR) 9 DAY_CYCLE = 24 %TIME 10 BCK_TIME_ON = 401190 %DELAY BEFORE BAC KGROUND EXP (HOUR) 11 BCK_TIME_OFF = 401190 %TIM E OF BACKGROUND EXP STOP (HOUR) 12 IV_LACK = 401190 13 IV_PERIOD = 401190 14 %GESTATION CONTROL 15 MATTING = 262800 % BEGINNING MATTING ( HOUR)at 30 years old 16 TIMELIMIT = 269184 %SIMULATION LIMIT TIME (HOUR) 17 TRANSTIME_ON = 264312 % EXCHANGE MOTHER FETUS 1512 HOUR POST 18 MATTING 19 %Exposure dose 20 MSTOT = 0.021 % ng of TCDD /kg of BW 21 MSTOTBCKGR = 0. %0.1 % ORAL BACKGROUND EXPOSURE DOSE (nG/KG) 22 DOSEIV = 0. %10 23 DOSEIVLATE = 0. %10 24 25% TRANFER MOTHER TO FETUS CLEARANCE 26 CLPLA_FET = 0.001 % MOTHER TO FETUS TRANFERT CLEARANCE(L/HR) 27 28 D.1.2. Table of Results for Baccarelli et al. (2008) 29 Table D-1. Estimated continuous inta ke corresponding to maternal serum 30 concentration in Figure 2A 31 32 Variable Value Notes
Infant b-TSH 5 uU/mL BMR Maternal lipid adjusted serum 270 ng/kg From Figure 2A
Intake 0.024 ng/kg-day From Emon d model, pregnancy at 30 years 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-2 Table D-2. Estimated maximum intake corresponding to maternal serum 1 concentration in Figure 2A 2 3 Variable Value Notes
Infant b-TSH -- -- Maternal lipid adjusted serum 309.5 ng/kg Maximum from Figure 2A
Intake 0.030 ng/kg-day From Emon d model, pregnancy at 30 years 4
D.2. MOCARELLI ET AL. ( 2008) MODELING 5 D.2.1. Input File for Exposure for Pulse to Measurement 0.5 Years After the Seveso Pulse 6 Dose 7 CINT = 1. % 8 EXP_TIME_ON = 54312. % Dela y before begin exposure (HOUR) 6.2 years 9 EXP_TIME_OFF = 54335. %324120 % HOUR/YEAR !TIME EXPOSURE STOP 10 (HOUR) 6.2 years + 23 hours 11 DAY_CYCLE = 24. % TIME 12 BCK_TIME_ON = 0. % D ELAY BEFORE BACKGROUND EXP (HOUR) 13 BCK_TIME_OFF = 613200 % TIME OF BACKGROUND EXP STOP (HOUR) 14 TIMELIMIT = 58692. % half a year (July 1976 until January 1977) past 6.2 years 15 MSTOTBCKGR = 3.7E-4 % OR AL BACKGROUND EXPOSURE DOSE (UG/KG) 16 17 % oral dose oral dose oral dose 18 MSTOT = 232.4 % Seveso, ORAL DAILY EXPOSURE DOSE (NG/KG) 19 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 20 % oral dose oral dose oral dose 21 22 MEANLIPID = 731 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 23 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 24 25 %human variable parameter 26 MALE = 1. 27 FEMALE = 0. 28 Y0 = 0. % 0 years old at the beginning of the simulation 29 30 D.2.2. Input File for Exposure from Pulse to th e End of the Critical Window 3.8 Years 31 After the Seveso Pulse Dose 32
CINT = 1. % 33 EXP_TIME_ON = 54312. % Dela y before begin exposure (HOUR) 6.2 years 34 EXP_TIME_OFF = 54335. %324120 % HOUR/YEAR !TIME EXPOSURE STOP 35 (HOUR) 6.2 years + 23 hours 36 DAY_CYCLE = 24. % TIME 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-3 BCK_TIME_ON = 0. % D ELAY BEFORE BACKGROUND EXP (HOUR) 1 BCK_TIME_OFF = 613200. % TIME OF BACKGROUND EXP STOP (HOUR) 2 TIMELIMIT = 87600. % 10 years 3 MSTOTBCKGR = 3.7e-4 % OR AL BACKGROUND EXPOSURE DOSE (UG/KG) 4 5 % oral dose oral dose oral dose 6 MSTOT = 232.5 % Serves o, ORAL DAILY EXPOSURE DOSE (NG/KG) 7 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 8 % oral dose oral dose oral dose 9 10 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 11 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 12 13 %human variable parameter 14 MALE = 1. 15 FEMALE = 0. 16 Y0 = 0. % 0 years old at the beginning of the simulation 17 18 D.2.3. Input File for Continuous Exposure for 10 Years 19
CINT = 1. % 20 EXP_TIME_ON = 0. % De lay before begin exposure (HOUR) 21 EXP_TIME_OFF = 87600. % HOUR/YEAR !TIME EXPOSURE STOP (HOUR) 22 DAY_CYCLE = 24. % TIME 23 BCK_TIME_ON = 0. %324120 % DELAY BEFORE BA CKGROUND EXP (HOUR) 24 BCK_TIME_OFF = 613200 %324120 % TI ME OF BACKGROUND EXP STOP (HOUR) 25 TIMELIMIT = 87600. % 10 years 26 MSTOTBCKGR = 0. %3.35E-4 % ORAL BACKGROUND EX POSURE DOSE (UG/KG) 27 28 % oral dose oral dose oral dose 29 MSTOT = 3.903 % Seveso, ORAL DAILY EXPOSURE DOSE (NG/KG) 30 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 31 % oral dose oral dose oral dose 32 33 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 34 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 35 36 %human variable parameter 37 MALE = 1. 38 FEMALE = 0. 39 Y0 = 0. % 0 years old at the beginning of the simulation 40 41 42 43 44 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-4 D.2.4. Tables of Results for Mocarelli et al. (2008) 1
2 Table D-3. Matching critical window average after pulse to critical window 3 average for continuous intake run 4 5

Person modeled, beginning at age 0 Lipid adjusted serum (1976) ng/kg

from Figure 3E Pulse dose, 0.5 year lag time (ng/kg) Average lipid adjusted serum 3.8 years after incident (ng/kg) Continuous intake for 10 years (ng/kg-day) Boy, 1st quartile 68 8.135 57.72 0.008024 Boy, 4th quartile 733 232.5 580.5 0.2128 

## 6 7 Table D-4. Matching critical window peak after pulse to peak critical 8 window concentration for continuous intake run 9 10

Person modeled, beginning at age 0 Lipid adjusted serum (1976) ng/kg

from Figure 3E Pulse dose, 0.5 year lag time (ng/kg) Peak lipid adjusted serum

after incident (ng/kg) Continuous intake for 10 years (ng/kg-day) Boy, 1st quartile 68 8.135 248.0 0.03194 Boy, 4th quartile 733 232.5 6674 3.904 

## 11 12 D.3. ALALUUSUA ET AL. (2004) MODELING 13
D.3.1. Input File for Exposure for Pulse to Measurement 0.5 Years After the Seveso Pulse 14 Dose 15
CINT = 1. % 16 EXP_TIME _ON = 21900. % Delay before begin exposure (HOUR) 2.5 years 17 EXP_TIME_OFF = 21923. % 21900+23 % HOUR/YEAR !TIME EXPOSURE STOP 18 (HOUR) 2.5 years and 23 hours 19 DAY_CYCLE = 24. % TIME 20 BCK_TIME_ON = 0. % D ELAY BEFORE BACKGROUND EXP (HOUR) 21 BCK_TIME_OFF = 613200. % TIME OF BACKGROUND EXP STOP (HOUR) 22 TIMELIMIT = 26280. % half a year (July 1976 until January 1977) past 2.5 years 23 MSTOTBCKGR = 3.7e-4 % ORAL BACKGROUND EXPOSURE DOSE (UG/KG) 24 25 % oral dose oral dose oral dose 26 MSTOT = 24.22 % Seves o, ORAL DAILY EXPOSURE DOSE (NG/KG) 27 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 28 % oral dose oral dose oral dose 29 30

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-5 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 1 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 2 3 %human variable parameter 4 MALE = 1. 5 FEMALE = 0. 6 Y0 = 0. % 0 years old at the beginning of the simulation 7 8 D.3.2. Input File for Exposure from Pulse to th e End of the Critical Window 2.5 Years 9 After the Seveso Pulse Dose 10
CINT = 1. % 11 EXP_TIME_ON = 21900. % Delay before begin exposure (HOUR) 2.5 years 12 EXP_TIME_OFF = 21923. % 324120 % HOUR/YEAR !TIME EXPOSURE STOP 13 (HOUR) 2.5 years and 23 hours 14 DAY_CYCLE = 24. % TIME 15 BCK_TIME_ON = 0. % 324120 % DELAY BEFORE BA CKGROUND EXP (HOUR) 16 BCK_TIME_OFF = 613200. % 324120 % TIME OF BACKGROUND EXP STOP (HOUR) 17 TIMELIMIT = 43800. % 5 years 18 MSTOTBCKGR = 3.7e-4 % ORAL BACKGROUND EXPOSURE DOSE (UG/KG) 19 20 % oral dose oral dose oral dose 21 MSTOT = 24.22 % Seveso, ORAL DAILY EXPOSURE DOSE (NG/KG) 22 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 23 % oral dose oral dose oral dose 24 25 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 26 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 27 28 %human variable parameter 29 MALE = 1. 30 FEMALE = 0. 31 Y0 = 0. % 0 years old at the beginning of the simulation 32 33 D.3.3. Input File for Continuous Exposure for 5 Years 34
CINT = 1. % 35 EXP_TIME_ON = 0. % De lay before begin exposure (HOUR) 36 EXP_TIME_OFF = 43800. % 324120 % HOUR/YEAR !TIME EXPOSURE STOP (HOUR) 37 DAY_CYCLE = 24. % TIME 38 BCK_TIME_ON = 0. % 324120 % DELAY BEFORE BAC KGROUND EXP (HOUR) 39 BCK_TIME_OFF = 613200. % 324120 % TIME OF BACKGROUND EXP STOP (HOUR) 40 TIMELIMIT = 43800. % End of critical window (5 years) 41 MSTOTBCKGR = 0. % ORAL BAC KGROUND EXPOSURE DOSE (UG/KG) 42 43 % oral dose oral dose oral dose 44 MSTOT = 0.03486 % Seves o, ORAL DAILY EXPOSURE DOSE (NG/KG) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-6 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 1 % oral dose oral dose oral dose 2 3 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 4 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 5 6 %human variable parameter 7 MALE = 1. 8 FEMALE = 0. 9 Y0 = 0. % 0 years old at the beginning of the simulation 10 11 D.3.4. Tables of Results for Alaluusua et al. (2004) 12 Table D-5. Matching critical window average after pulse to critical window 13 average for continuous intake run 14 15

Person modeled, beginning at age 0 Lipid adjusted serum (1976) ng/kg

estimated from

tertile bins a 

### Pulse dose, 0.5 year lag time (ng/kg) Average lipid adjusted serum 2.5 years after incident (ng/kg) Continuous intake for 5years (ng/kgday) Boy, 1st tertile 130 24.22 110.8 0.03486 Boy, 2nd tertile 383 108.9 322.7 0.1578 Boy, 3rd tertile 1830 1041 1538 1.511 Girl, 1st tertile 130 23.03 110.8 0.03211 Girl, 2nd tertile 383 105.3 324.4 0.1481 Girl, 3rd tertile 1830 1015 1546 1.427 Boy and girl, averaged, 1st tertile 130 - - 0.03349

Boy and girl, averaged, 2nd tertile 383 - - 0.1530

Boy and girl, averaged, 3rd tertile 1830 - - 1.469



## 16

a 

### Mean of tertile bin assuming a lognorma l distribution of serum concentrations. 

## 17

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-7 Table D-6. Matching critical window peak after pulse to peak critical 1 window concentration for continuous intake run 2 3

Person modeled, beginning at age 0 Lipid adjusted serum (1976) ng/kg

estimated from tertile bins Pulse dose, 0.5 year lag time (ng/kg) Peak lipid adjusted serum

after incident (ng/kg) Continuous intake for 5years (ng/kgday) Boy, 1st tertile 130 24.22 618.8 0.2113 Boy, 2nd tertile 383 108.9 2700 1.783 Boy, 3rd tertile 1830 1041 24706 31.35 Girl, 1st tertile 130 23.02 588.0 0.1882 Girl, 2nd tertile 383 105.3 2610 1.642 Girl, 3rd tertile 1830 1015 24113 29.52 Boy and girl, averaged, 1st tertile 130 - - 0.1998

Boy and girl, averaged, 2nd tertile 383 - - 1.713

Boy and girl, averaged, 3rd tertile 1830 - - 30.44



## 4

a 

### Mean of tertile bin assuming a lognorma l distribution of serum concentrations. 

## 5 6 7 D.4. ESKANAZI ET AL. (2002) MODELING 8
D.4.1. Input File for Exposure for Pulse to Measurement 0.5 Years After the Seveso Pulse 9 Dose 10
CINT = 1. % 11 EXP_TIME _ON = 58692. % Dela y before begin exposure (HOUR) 6.7 years 12 EXP_TIME_OFF = 58715. % HOUR/YEAR !TIME EXPOSURE STOP (HOUR) 6.7 years + 13 23 hours 14 DAY_CYCLE = 24. % TIME 15 BCK_TIME_ON = 0. %324120 % DELAY BEFORE BA CKGROUND EXP (HOUR) 16 BCK_TIME_OFF = 613200. %324120 % TIME OF BACKGROUND EXP STOP (HOUR) 17 TIMELIMIT = 63072. % half a year (July 1976 until January 1977) past 6.7 years 18 MSTOTBCKGR = 3.7e-4 % OR AL BACKGROUND EXPOSURE DOSE (UG/KG) 19 20 % oral dose oral dose oral dose 21 MSTOT = 7193 % Seves o, ORAL DAILY EXPOSURE DOSE (NG/KG) 22 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 23 % oral dose oral dose oral dose 24 25 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 26

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-8 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 1 2 %human variable parameter 3 MALE = 0. 4 FEMALE = 1. 5 Y0 = 0. % 0 years old at the beginning of the simulation 6 7 D.4.2. Input File for Exposure from Pulse to th e End of the Critical Window 6.7 Years 8 After the Seveso Pulse Dose 9
CINT = 1. % 10 EXP_TIME_ON = 58692. % Dela y before begin exposure (HOUR) 6.7 years 11 EXP_TIME_OFF = 58715. %324120 % HOUR/YEAR !TIME EXPOSURE STOP 12 (HOUR) 6.7 years + 23 hours 13 DAY_CYCLE = 24. % TIME 14 BCK_TIME_ON = 0. %324120 % DELAY BEFORE BA CKGROUND EXP (HOUR) 15 BCK_TIME_OFF = 613200 %324120 % TI ME OF BACKGROUND EXP STOP (HOUR) 16 TIMELIMIT = 113880. % 13 years 17 MSTOTBCKGR = 3.7e-4 % OR AL BACKGROUND EXPOSURE DOSE (UG/KG) 18 19 % oral dose oral dose oral dose 20 MSTOT = 7193 % Seves o, ORAL DAILY EXPOSURE DOSE (NG/KG) 21 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 22 % oral dose oral dose oral dose 23 24 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 25 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 26 27 %human variable parameter 28 MALE = 0. 29 FEMALE = 1. 30 Y0 = 0. % 0 years old at the beginning of the simulation 31 32 D.4.3. Input File for Continuous Exposure for 13 Years 33
CINT = 1. % 34 EXP_TIME_ON = 0. % De lay before begin exposure (HOUR) 35 EXP_TIME_OFF = 113880. %324120 % HOUR/YEAR !TIME EXPOSURE STOP 36 (HOUR) 13 years 37 DAY_CYCLE = 24. % TIME 38 BCK_TIME_ON = 0. %324120 % DELAY BEFORE BA CKGROUND EXP (HOUR) 39 BCK_TIME_OFF = 613200. %324120 % TIME OF BACKGROUND EXP STOP (HOUR) 40 TIMELIMIT = 113880. % 13 years 41 MSTOTBCKGR = 0. %3.35E-4 % ORAL BACKGROUND E X POSURE DOSE (UG/KG) 42 43 % oral dose oral dose oral dose 44 MSTOT = 166 % Seves o, ORAL DAILY EXPOSURE DOSE (NG/KG) 45

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-9 DOSEIV = 0 % 40 %50 %5 %0.5 %0.3 %0.2 %0.1%0.05%0.3 %NG/KG 1 % oral dose oral dose oral dose 2 3 MEANLIPID = 730 % 711 %664 %778 %468 %671 %730 %662 %592%615%730% 4 PAS_INDUC= 1 % NON INDUCTION (0) CONTROLE DE L'INDUCTION 5 6 %human variable parameter 7 MALE = 0. 8 FEMALE = 1. 9 Y0 = 0. % 0 years old at the beginning of the simulation 10 11 D.4.4. Tables of Results for Eskanazi et al. (2002) 12 Table D-7. Matching critical window average after pulse to critical window 13 average for continuous intake run 14 15

Person modeled, beginning at age 0 Lipid adjusted serum (adjusted to 1976- 1977 levels) ng/kg

from Figure 1A Pulse dose, 0.5 year lag time (ng/kg) Average lipid adjusted serum 6.7 years after incident (ng/kg) Continuous intake for 13 years (ng/kg-day) Girl, estrous cycle 28.5 days 166 28.40 114.0 0.01660

Girl, estrous cycle 29 days 693 215.5 455.1 0.1224

Girl, estrous cycle 29.5 days 2020 1008 1295 0.5693

Girl, estrous cycle 30 days 8450 7193 5179 4.054



## 16 Table D-8. Matching critical window peak after pulse to peak critical 17 window concentration for continuous intake run 18 19

Person modeled, beginning at age 0 Lipid adjusted serum (adjusted to 1976- 1977 levels) ng/kg

from Figure 1A Pulse dose, 0.5 year lag time (ng/kg) Peak lipid adjusted serum

after incident (ng/kg) Continuous intake for 13 years (ng/kg-day) Girl, estrous cycle 28.5 days 166 28.40 838.2 0.1800

Girl, estrous cycle 29 days 693 215.5 6183 3.148

Girl, estrous cycle 29.5 days 2020 1008 28316 20.86

Girl, estrous cycle 30 days 8450 7193 198240 166.6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE D-10 1 D.5. REFERENCES 2 Alaluusua, S; Calderara, P; Gerthoux, PM; et al. (2004) Developmental dental aberrations after the dioxin accident 

## 3 in Seveso. Environ Health Perspect 112(13):1313

− 1318. 

## 4
Baccarelli, A; Giacomini, SM; Corbetta, C; et al. (2008) Neonatal thyroid functio n in Seveso 25 years after maternal 

## 5 exposure to dioxin. PLoS Med 5(7):e161. 

## 6
Eskenazi, B; Mocarelli, P; Warner, M; et al. (2002). Seru m dioxin concentrations and endometriosis: a cohort study 

## 7 in Seveso, Italy. Environ Health Perspect 110(7): 629

− 634. 

## 8
Mocarelli, P; Gerthoux, PM; Patterson, DG, Jr.; et al . (2008) Dioxin exposure, from infancy through puberty, 

## 9 produces endocrine disruption and affects human se men quality. Environ Health Perspect 116(1):70

− 77. 

## 10
11

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX E
Noncancer Benchmark Dose Modeling

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-ii CONTENTS—APPENDIX E: Noncancer Benchmark Dose Modeling

APPENDIX E. NONCANCER BE NCHMARK DOSE MODELING

.................................. E-1 E.1. BMDS INPUT TABLES............................................................................................. E-1 E.1.1. Amin et al. (2000).......................................................................................... E-1 E.1.2. Bell et al. (2007a)........................................................................................... E-1 E.1.3. Cantoni et al. (1981) ...................................................................................... E-2 E.1.4. Crofton et al. (2005)....................................................................................... E-2 E.1.5. DeCaprio et al. (1986).................................................................................... E-3 E.1.6. Hojo et al. (2002) ........................................................................................... E-4 E.1.7. Kattainen et al. (2001).................................................................................... E-4 E.1.8. Keller et al. (2007, 2008a, b) ......................................................................... E-5 E.1.9. Kociba et al. (1978)........................................................................................ E-5 E.1.10. Latchoumycandane and Mathur (2002)......................................................... E-6 E.1.11. Li et al. (1997)................................................................................................ E-6 E.1.12. Li et al. (2006)................................................................................................ E-6 E.1.13. Markowski et al. (2001)................................................................................. E-7 E.1.14. Mietinnin et al. (2006) ................................................................................... E-7 E.1.15. National Toxicology Program (1982)............................................................ E-8 E.1.16. National Toxicology Program (2006)............................................................ E-8 E.1.17. Ohsako et al. (2001)..................................................................................... E-10 E.1.18. Schantz et al. (1996) .................................................................................... E-10 E.1.19. Shi et al. (2007)............................................................................................ E-11 E.1.20. Smialowicz et al. (2008) .............................................................................. E-11 E.1.21. Toth et al. (1979).......................................................................................... E-12 E.1.22. Van Birgelen et al. (1995)............................................................................ E-12 E.1.23. White et al. (1986) ....................................................................................... E-13 E.2. ALTERNATE DOSE: BLOO D SERUM BMDS RESULTS

.................................. E-14 E.2.1. Amin et al. (2000): Saccharin Consumed, Female (0.25%) ........................ E-14 E.2.1.1. Summary Table of BMDS Modeling Results ............................. E-14 E.2.1.2. Figure for Selected Model: Linear, N onconstant Variance......... E-15 E.2.1.3. Output File for Selected Model: L inear, Nonconstant Variance....................................................................................... E-15 E.2.1.4. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-18 E.2.1.5. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-18 E.2.2. Amin et al. (2000): Saccharin Consumed, Female (0.50%) ........................ E-21 E.2.2.1. Summary Table of BMDS Modeling Results ............................. E-21 E.2.2.2. Figure for Selected Model: Linear, N onconstant Variance......... E-22 E.2.2.3. Output File for Selected Model: L inear, Nonconstant Variance....................................................................................... E-22 E.2.2.4. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-25

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-iii CONTENTS (continued)

E.2.2.5. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-25 E.2.3. Amin et al. (2000): Saccharin Preference Ratio, Fe male (0.25%)............... E-28 E.2.3.1. Summary Table of BMDS Modeling Results ............................. E-28 E.2.3.2. Figure for Selected Model: Linear, N onconstant Variance......... E-29 E.2.3.3. Output File for Selected Model: L inear, Nonconstant Variance....................................................................................... E-29 E.2.3.4. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-32 E.2.3.5. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-32 E.2.4. Amin et al. (2000): Saccharin Preference Ratio, Fe male (0.50%)............... E-35 E.2.4.1. Summary Table of BMDS Modeling Results ............................. E-35 E.2.4.2. Figure for Selected Model: Linear, Constant Variance............... E-35 E.2.4.3. Output File for Selected M odel: L inear, Constant Variance....... E-36 E.2.4.4. Figure for Unrestricted Mode l: Pow er, Constant Variance, Power Unrestricted...................................................................... E-38 E.2.4.5. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted...................................................... E-38 E.2.5. Bell et al. (2007): Balano-Preput ial Separation in Male Pups (10% extra risk)............................................................................................ E-41 E.2.5.1. Summary Table of BMDS Modeling Results ............................. E-41 E.2.5.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

............................................................. E-42 E.2.5.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

............................................................. E-42 E.2.5.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

................................................................................. E-44 E.2.5.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

................................................................................. E-44 E.2.6. Bell et al. (2007): Balano-Preput ial Separation in Male Pups (5% extra risk).............................................................................................. E-46 E.2.6.1. Summary Table of BMDS Modeling Results ............................. E-46 E.2.6.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

............................................................. E-47 E.2.6.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

............................................................. E-47 E.2.6.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

................................................................................. E-49 E.2.6.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

....................................................................... E-49 E.2.7. Cantoni et al. (1981): Urinary Copro-Porhyrins

.......................................... E-51 E.2.7.1. Summary Table of BMDS Modeling Results ............................. E-51

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-iv CONTENTS (continued)

E.2.7.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................... E-52 E.2.7.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................... E-52 E.2.7.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted ................................ E-55 E.2.7.5. Output file for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted ................................ E-55 E.2.7.6. Figure for Unrestricted Mode l: Hill, Nonconstant Variance, n Unrestricted

.............................................................................. E-58 E.2.7.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted.............................................................. E-58 E.2.7.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-61 E.2.7.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted...................................................... E-61 E.2.8. Cantoni et al. (1981) : Urinary Porphyrins

................................................... E-64 E.2.8.1. Summary Table of BMDS Modeling Results ............................. E-64 E.2.8.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1.................................................... E-65 E.2.8.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................... E-65 E.2.9. Crofton et al. (2005): Serum T4................................................................... E-68 E.2.9.1. Summary Table of BMDS Modeling Results ............................. E-68 E.2.9.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1.................................................... E-69 E.2.9.3. Output File for Selected M odel: Exponential (M4), Constant Variance, P ower Restricted ≥ 1.................................................... E-69 E.2.9.4. Figure for Unrestricted Mode l: Exponential (M5), Constant Variance, P ower Unrestricted...................................................... E-72 E.2.9.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted

...................................... E-73 E.2.9.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted

................................................................................. E-76 E.2.9.7. Output File for Unrestri cted Model: Hill, Constant Variance, n Unrestricted

.............................................................. E-76 E.2.9.8. Figure for Unrestricted Mode l: Pow er, Constant Variance, Power Unrestricted...................................................................... E-79 E.2.9.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted...................................................... E-79 E.2.10. Hojo et al. (2002): DRL Reinforce Per Min ................................................ E-82 E.2.10.1. Summary Table of BMDS Modeling Results ............................. E-82 E.2.10.2. Figure for Selected Model: Exponental (M4) ............................. E-83

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E.2.10.3. Output File for Select ed Model: Exponential (M4)

.................... E-83 E.2.11. Hojo et al. (2002): DRL Response Per Min................................................. E-86 E.2.11.1. Summary Table of BMDS Modeling Results ............................. E-86 E.2.11.2. Figure for Selected Model: Exponential (M4) ............................ E-87 E.2.11.3. Output File for Select ed Model: Exponential (M4)

.................... E-87 E.2.12. Kattainen et al. (2001): 3rd Mo lar Mesio-Distal L ength (Molar Development)............................................................................................... E-90 E.2.12.1. Summary Table of BMDS Modeling Results ............................. E-90 E.2.12.2. Figure for Selected Model: Hill, Nonconstant Variance, n Restricted >1, Bound Hit

............................................................. E-91 E.2.12.3. Output File for Selected M odel: Hill, Nonconstant Variance, n Restricted >1, Bound Hit

.......................................................... E-91 E.2.12.4. Figure for Unrestricted Mode l: Hill, Nonconstant Variance, n Unrestricted

.............................................................................. E-94 E.2.12.5. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted.............................................................. E-94 E.2.13. Kattainen et al. (2001): Females 3rd Molar Eruption.................................. E-97 E.2.13.1. Summary Table of BMDS Modeling Results ............................. E-97 E.2.13.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

............................................................. E-97 E.2.13.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

............................................................. E-98 E.2.13.4. Figure for Unrestricted Mode l: Log-Logistic, Unrestricted

........ E-99 E.2.13.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-100 E.2.14. Kattainen et al., 2001: 3rd molar length in pups........................................ E-101 E.2.14.1. Summary Table of BM DS m odeling results ............................. E-101 E.2.14.2. Figure for selected model: Hill.................................................. E-102 E.2.14.3. Output for selected model: Hill................................................. E-102 E.2.14.4. Figure for additional model pr es ented: Hill, unrestricted ......... E-105 E.2.14.5. Output for additional model presented: Hill, unrestricted......... E-105 E.2.15. Keller et al. (2006): Missing Ma ndibular Molars in CBA J Mice

............. E-108 E.2.15.1. Summary Table of BMDS Modeling Results ........................... E-108 E.2.15.2. Figure for Selected Model: Multistage, 1-Degree..................... E-109 E.2.15.3. Output File for Selected Model: Multistage, 1-Degree

............. E-109 E.2.16. Kociba et al. (1978): Urinary C oproporphyrins, F emales (Table 2).......... E-111 E.2.16.1. Summary Table of BMDS Modeling Results ........................... E-111 E.2.17. Kociba et al. (1978): Uropor phyrin per Creatinine, Fem ales .................... E-113 E.2.17.1. Summary Table of BMDS Modeling Results ........................... E-113 E.2.17.2. Figure for Selected Model: Linear, Constant Variance............. E-114 E.2.17.3. Output File for Selected M odel: L inear, Constant Variance..... E-114
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## E.2.18. Latchoumycandane and Mathur (2002): Daily Sperm Production............ E-117 E.2.18.1. Summary Table of BMDS Modeling Results ........................... E-117 E.2.18.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-118 E.2.18.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-118 E.2.18.4. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted

............................................................................... E-121 E.2.18.5. Output File for Unrestri cted Model: Hill, Constant Variance, n Unrestricted

............................................................ E-121 E.2.19. Li et al. (1997): Follicle-Stimulating Hormone ......................................... E-123 E.2.19.1. Summary Table of BMDS Modeling Results ........................... E-123 E.2.19.2. Figure for Selected Model: Power............................................. E-124 E.2.19.3. Output for Selected Model: Power............................................ E-124 E.2.19.4. Figure for Unrestricted Model: Power, Unrestricted................. E-127 E.2.19.5. Output for Unrestricted Model: Power, Unrestricted................ E-127 E.2.20. Li et al. (2006): Horm one Levels (Estradiol)............................................. E-130 E.2.20.1. Summary Table of BMDS Modeling Results ........................... E-130 E.2.20.2. Figure for Selected Model: Linear, Constant Variance............. E-131 E.2.20.3. Output File for Unrestrict ed Model: Linear, Constant Variance

..................................................................................... E-131 E.2.20.4. Figure for Unrestricted Mode l: Exponential (M5), Constant Variance, P ower Unrestricted.................................................... E-134 E.2.20.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted

.................................... E-134 E.2.20.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted

............................................................................... E-137 E.2.20.7. Output File for Unrestri cted Model: Hill, Constant Variance, n Unrestricted

............................................................ E-137 E.2.20.8. Figure for Unrestricted Mode l: Pow er, Constant Variance, Power Unrestricted.................................................................... E-140 E.2.20.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted.................................................... E-140 E.2.21. Li et al. (2006): Horm one Levels (Progesterone)

...................................... E-143 E.2.21.1. Summary Table of BMDS Modeling Results ........................... E-143 E.2.21.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-144 E.2.21.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................. E-144 E.2.21.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-147 E.2.21.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-147

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## E.2.21.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted............................................................ E-150 E.2.21.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-150 E.2.21.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-153 E.2.21.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-153 E.2.22. Markowski et al. (2001) : FR10 Run Opportunities

................................... E-156 E.2.22.1. Summary Table of BMDS Modeling Results ........................... E-156 E.2.22.2. Figure for Selected Model: Exponential (M2) .......................... E-156 E.2.22.3. Output File for Select ed Model: Exponential (M2)

.................. E-157 E.2.23. Markowski et al. (2001): FR2 Revolutions................................................ E-160 E.2.23.1. Summary Table of BMDS Modeling Results ........................... E-160 E.2.23.2. Figure for Selected Model: Exponential (M5) .......................... E-161 E.2.23.3. Output File for Select ed Model: Exponential (M5)

.................. E-161 E.2.23.4. Figure for Unrestricted Model: Power, Unrestricted................. E-164 E.2.23.5. Output for Unrestricted Model: Power, Unrestricted................ E-164 E.2.24. Markowski et al. (2001): FR5 Run Opp .................................................... E-167 E.2.24.1. Summary Table of BMDS Modeling Results ........................... E-167 E.2.24.2. Figure for Selected Model: Hill................................................. E-168 E.2.24.3. Output File for Selected Model: Hill......................................... E-168 E.2.24.4. Figure for Unrestricted Model: Power, Unrestricted................. E-171 E.2.24.5. Output File for Unrestrict ed Model: Power, Unrestricted

......... E-171 E.2.25. Mietinnin et al. (2006): Cariogenic Lesions in P ups ................................. E-174 E.2.25.1. Summary Table of BMDS Modeling Results ........................... E-174 E.2.25.2. Figure for Selected Model: Log-Logistic.................................. E-174 E.2.25.3. Output File for Sel ected Model: Log-Logistic

.......................... E-175 E.2.25.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-176 E.2.25.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-177 E.2.26. National Toxicology Program (1982): Male Mice, Toxic H epatitis.......... E-178 E.2.26.1. Summary Table of BMDS Modeling Results ........................... E-178 E.2.26.2. Figure for Selected Model: Multistage, 2nd Degree ................. E-179 E.2.26.3. Output File for Selected Model: Multistage, 2nd Degree

......... E-179 E.2.27. National Toxicology Program (2006): Alveolar Metaplasia

..................... E-181 E.2.27.1. Summary Table of BMDS Modeling Results ........................... E-181 E.2.27.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-182 E.2.27.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-182
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## E.2.28. National Toxicology Program (2006): Gingival Hyperplasia Squamous, 2 Years..................................................................................... E-184 E.2.28.1. Summary Table of BMDS Modeling Results ........................... E-184 E.2.28.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-185 E.2.28.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-185 E.2.28.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-187 E.2.28.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-187 E.2.29. National Toxicology Program (2006): Heart, Cardiomyopathy................ E-189 E.2.29.1. Summary Table of BMDS Modeling Results ........................... E-189 E.2.29.2. Figure for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

........................................................... E-189 E.2.29.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

................................................. E-190 E.2.30. National Toxicology Program ( 2006): Hepatocyte Hypertrophy, 2 Years

.......................................................................................................... E-191 E.2.30.1. Summary Table of BMDS Modeling Results ........................... E-191 E.2.30.2. Figure for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

........................................................... E-192 E.2.30.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

................................................. E-193 E.2.31. National Toxicology Program (200 6): Liver, E osinophilic Focus, Multiple...................................................................................................... E-194 E.2.31.1. Summary Table of BMDS Modeling Results ........................... E-194 E.2.31.2. Figure for Selected Model: Probit............................................. E-195 E.2.31.3. Output File for Selected Model: Probit ..................................... E-195 E.2.32. National Toxicology Program (200 6): Liver, Fatty Change, Diffuse

........ E-197 E.2.32.1. Summary Table of BMDS Modeling Results ........................... E-197 E.2.32.2. Figure for Selected Model: W eibull, Power Restricted ≥ 1 ....... E-198 E.2.32.3. Output File for Select ed Model: W eibull, Power Restricted ≥ 1.............................................................................. E-198 E.2.33. National Toxicology Program (2006): Liver Necrosis

.............................. E-200 E.2.33.1. Summary Table of BMDS Modeling Results ........................... E-200 E.2.33.2. Figure for Selected Model: Log-Probit ..................................... E-200 E.2.33.3. Output File for Sel ected Model: Log-Probit

............................. E-201 E.2.34. National Toxicology Program (2006): Liver, Pigmentation...................... E-202 E.2.34.1. Summary Table of BMDS Modeling Results ........................... E-202 E.2.34.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-203
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## E.2.34.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1.............................................................................. E-203 E.2.35. National Toxicology Program (2006): Liver, T oxic Hepatopathy ............ E-205 E.2.35.1. Summary Table of BMDS Modeling Results ........................... E-205 E.2.35.2. Figure for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

........................................................... E-205 E.2.35.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

................................................. E-206 E.2.35.4. Figure for Unrestricted Mode l: Multistage, 2-Degree, Betas Unrestricted

............................................................................... E-208 E.2.35.5. Output File for Unrestricted Model: Multistage, 2-Degree, Betas Unrestricted

..................................................................... E-208 E.2.36. National Toxicology Program (200 6): Lung, Alveolar to Bronchiolar Epithelial Metaplasia (Alveolar Epith elium , Metaplasia, Bronchiolar) .... E-210 E.2.36.1. Summary Table of BMDS Modeling Results ........................... E-210 E.2.36.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-211 E.2.36.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-211 E.2.37. National Toxicology Program (200 6): Oval Cell Hyperplasia, 2 Years

.......................................................................................................... E-213 E.2.37.1. Summary Table of BMDS Modeling Results ........................... E-213 E.2.37.2. Figure for Selected Model: Probit............................................. E-213 E.2.37.3. Output File for Selected Model: Probit ..................................... E-214 E.2.38. National Toxicology Program (2006): Toxic Hepatopathy

....................... E-215 E.2.38.1. Summary Table of BMDS Modeling Results ........................... E-215 E.2.38.2. Figure for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

........................................................... E-216 E.2.38.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound Hit

................................................. E-216 E.2.38.4. Figure for Unrestricted M odel: Multistage, 2-Degree, Betas Unrestricted

..................................................................... E-218 E.2.38.5. Output File for Unrestricted Model: Multistage, 2-Degree, Betas Unrestricted

..................................................................... E-218 E.2.39. Ohsako et al. (2001): Anogenital Distance in Male Pups.......................... E-220 E.2.39.1. Summary Table of BMDS Modeling Results ........................... E-220 E.2.39.2. Figure for Selected Model: Hill................................................. E-221 E.2.39.3. Output File for Selected Model: Hill......................................... E-221 E.2.39.4. Figure for Unrestricted Model: Hill, Unrestricted

..................... E-224 E.2.39.5. Output File for Unrestricted Model: Hill, Unres tricted............. E-224 E.2.40. Schantz et al. (1996): Maze Errors Per Block, Fem ale.............................. E-227 E.2.40.1. Summary Table of BMDS Modeling Results ........................... E-227 E.2.40.2. Figure for Selected Model: Linear, Constant Variance............. E-228

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## E.2.40.3. Output File for Selected M odel: Linear, Constant Variance..... E-228 E.2.40.4. Figure for Unrestricted Mode l: Pow er, Constant Variance, Power Unrestricted.................................................................... E-231 E.2.40.5. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted.................................................... E-231 E.2.41. Shi et al. (2007): Estradiol ......................................................................... E-234 E.2.41.1. Summary Table of BMDS Modeling Results ........................... E-234 E.2.41.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-235 E.2.41.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-235 E.2.41.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-238 E.2.41.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-238 E.2.41.6. Figure for Unrestricted Mode l: Hill, Nonconstant Variance, n Unrestricted

............................................................................ E-241 E.2.41.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-241 E.2.41.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-244 E.2.41.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-244 E.2.42. Smialowicz et al. (2008): PFC per 10^6 Cells........................................... E-247 E.2.42.1. Summary Table of BMDS Modeling Results ........................... E-247 E.2.42.2. Figure for Selected Model: Linear, N onconstant Variance....... E-248 E.2.42.3. Output File for Selected Model: L inear, Nonconstant Variance..................................................................................... E-248 E.2.42.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-251 E.2.42.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-251 E.2.42.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-254 E.2.42.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-254 E.2.42.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-257 E.2.42.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-257 E.2.43. Smialowicz et al. (2008): PFC per Spleen................................................. E-260 E.2.43.1. Summary Table of BMDS Modeling Results ........................... E-260 E.2.43.2. Figure for Selected Model: Linear, N onconstant Variance....... E-261

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## E.2.43.3. Output File for Selected Model: Linear, Nonconstant Variance..................................................................................... E-261 E.2.43.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-264 E.2.43.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-264 E.2.43.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-267 E.2.43.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-267 E.2.43.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-270 E.2.43.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-270 E.2.44. Toth et al. (1978): Amyloidosis................................................................. E-273 E.2.44.1. Summary Table of BMDS Modeling Results ........................... E-273 E.2.44.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-274 E.2.44.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-274 E.2.44.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-276 E.2.44.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-276 E.2.44.6. Figure for Unrestricted Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-278 E.2.44.7. Output File for Unrestrict ed Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-278 E.2.45. Toth et al. (1978): Skin Lesions................................................................. E-280 E.2.45.1. Summary Table of BMDS Modeling Results ........................... E-280 E.2.45.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-281 E.2.45.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1

.............................................................................. E-281 E.2.45.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-283 E.2.45.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-283 E.2.46. Van Birgelen et al. (1995a): Hepatic Retinol............................................. E-285 E.2.46.1. Summary Table of BMDS Modeling Results ........................... E-285 E.2.46.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-287
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## E.2.46.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, Power Restricted ≥ 1............................. E-287 E.2.46.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-290 E.2.46.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-290 E.2.46.6. Figure for Unrestricted Mode l: Hill, Nonconstant Variance, n Unrestricted

............................................................................ E-293 E.2.46.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-293 E.2.46.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-296 E.2.46.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-296 E.2.47. Van Birgelen et al. (1995a ): Hepatic Retinol Palm itate ............................ E-299 E.2.47.1. Summary Table of BMDS Modeling Results ........................... E-299 E.2.47.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-300 E.2.47.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-300 E.2.47.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-303 E.2.47.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-303 E.2.47.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-306 E.2.47.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-306 E.2.47.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-309 E.2.47.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-309 E.2.48. Van Birgelen et al. (1995a): Plasm a FT4................................................... E-312 E.2.48.1. Summary Table of BMDS Modeling Results ........................... E-312 E.2.48.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-313 E.2.48.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................. E-314 E.2.48.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-316 E.2.48.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-317
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## E.2.48.6. Figure for Unrestricted Mode l: Hill, Nonconstant Variance, n Unrestricted ............................................................................ E-319 E.2.48.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-320 E.2.48.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-322 E.2.48.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-322 E.2.49. Van Birgelen et al . (1995a): Plasm a TT4 .................................................. E-325 E.2.49.1. Summary Table of BMDS Modeling Results ........................... E-325 E.2.49.2. Figure for Selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-327 E.2.49.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-327 E.2.49.4. Figure for Unrestricted Model: Exponential (M5), Constant Variance, Power Unrestricted

.................................... E-330 E.2.49.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted

.................................... E-330 E.2.49.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted

............................................................................... E-333 E.2.49.7. Output File for Unrestri cted Model: Hill, Constant Variance, n Unrestricted

............................................................ E-333 E.2.49.8. Figure for Unrestricted Mode l: Pow er, Constant Variance, Power Unrestricted.................................................................... E-336 E.2.49.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted.................................................... E-336 E.2.50. White et al. (1986): CH50.......................................................................... E-338 E.2.50.1. Summary Table of BMDS Modeling Results ........................... E-338 E.2.50.2. Figure for Selected Model: Hill, Nonconstant Variance, n Restricted >1, Bound Hit

........................................................... E-340 E.2.50.3. Output File for Selected Model: Hill, Nonconstant Variance, n Restricted >1, Bound Hit

....................................... E-340 E.2.50.4. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-343 E.2.50.5. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-343 E.3. ADMINISTERED DOSE BMDS RESULTS......................................................... E-346 E.3.1. Amin et al. (2000): Saccharin Consumed, Female (0.25%) ...................... E-346 E.3.1.1. Summary Table of BMDS Modeling Results ........................... E-346 E.3.1.2. Figure for Selected Model: Linear, N onconstant Variance....... E-347 E.3.1.3. Output file for Selected Model: L inear, Nonconstant Variance..................................................................................... E-347 E.3.2. Amin et al. (2000): Saccharin Consumed, Female (0.50%) ...................... E-349

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## E.3.2.1. Summary Table of BMDS Modeling Results ........................... E-349 E.3.2.2. Figure for Selected Model: Linear, N onconstant Variance....... E-350 E.3.2.3. Output File for Selected Model: L inear, Nonconstant Variance..................................................................................... E-350 E.3.3. Amin et al. (2000): Saccharin Preference Ratio, Fe male (0.25%)............. E-353 E.3.3.1. Summary Table of BMDS Modeling Results ........................... E-353 E.3.3.2. Figure for Selected Model: Linear, N onconstant Variance....... E-353 E.3.3.3. Output File for Selected Model: L inear, Nonconstant Variance..................................................................................... E-354 E.3.4. Amin et al. (2000): Saccharin Preference Ratio, Fe male (0.50%)............. E-356 E.3.4.1. Summary Table of BMDS Modeling Results ........................... E-356 E.3.4.2. Figure for Selected Model: Linear, N onconstant Variance....... E-357 E.3.4.3. Output File for Selected Model: L inear, Nonconstant Variance..................................................................................... E-357 E.3.5. Bell et al. (2007): Balano-Preputia l Separation in Male Pups (10% Extra Risk)

................................................................................................. E-359 E.3.5.1. Summary Table of BM DS m odeling results ............................. E-359 E.3.5.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-360 E.3.5.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-360 E.3.5.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-362 E.3.5.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-362 E.3.6. Bell et al. (2007): Balano-Preputia l Separation in Male Pups (5% Extra Risk)

................................................................................................. E-364 E.3.6.1. Summary Table of BMDS Modeling Results ........................... E-364 E.3.6.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-365 E.3.6.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-365 E.3.6.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-367 E.3.6.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-367 E.3.7. Cantoni et al. (1981): Urinary Copro-Porhyrins

........................................ E-369 E.3.7.1. Summary Table of BMDS Modeling Results ........................... E-369 E.3.7.2. Figure for Selected Model: Probit............................................. E-369 E.3.7.3. Output File for Selected Model: Probit ..................................... E-370 E.3.8. Cantoni et al. (1981) : Urinary Porphyrins

................................................. E-371 E.3.8.1. Summary Table of BMDS Modeling Results ........................... E-371 E.3.8.2. Figure for Selected Model: Linear, N onconstant Variance....... E-372

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## E.3.8.3. Output File for Selected Model: Linear, Nonconstant Variance..................................................................................... E-373 E.3.9. Crofton et al. (2005): Serum T4................................................................. E-375 E.3.9.1. Summary Table of BMDS Modeling Results ........................... E-375 E.3.9.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1.................................................. E-376 E.3.9.3. Output File for selected Model: Exponential (M4), Constant Variance, Power Restricted ≥ 1

................................... E-376 E.3.10. DeCaprio et al. (1986): Ab solute Kidney W eight, Males.......................... E-379 E.3.10.1. Summary Table of BMDS Modeling Results ........................... E-379 E.3.10.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-380 E.3.10.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-380 E.3.11. DeCaprio et al. (1986): Abso lute Thym us Weight, Males ........................ E-383 E.3.11.1. Summary Table of BMDS Modeling Results ........................... E-383 E.3.11.2. Figure for Selected Model: Po wer, N onconstant Variance, Power Restricted ≥ 1, Bound Hit................................................ E-384 E.3.11.3. Output File for Selected Model: Pow er, Nonconstant Variance, Power Restricted ≥ 1, Bound Hit ............................... E-384 E.3.12. DeCaprio et al. (1986) : B ody Weight, Females......................................... E-387 E.3.12.1. Summary Table of BMDS Modeling Results ........................... E-387 E.3.12.2. Figure for Selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-388 E.3.12.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-388 E.3.13. DeCaprio et al. ( 1986): B ody Weight, Males ............................................ E-391 E.3.13.1. Summary Table of BMDS Modeling Results ........................... E-391 E.3.13.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-392 E.3.13.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-392 E.3.14. DeCaprio et al. (1986): Re lative Brain W eight, Males.............................. E-395 E.3.14.1. Summary Table of BMDS Modeling Results ........................... E-395 E.3.14.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1.................................................. E-396 E.3.14.3. Output File for Selected Model: Exponential (M4), Constant Variance, Power Restricted ≥ 1

................................... E-396 E.3.15. DeCaprio et al. (1986): Rela tive Liver W eight, Females .......................... E-399 E.3.15.1. Summary Table of BMDS Modeling Results ........................... E-399 E.3.15.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-400
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## E.3.15.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, Power Restricted ≥ 1............................. E-400 E.3.16. DeCaprio et al. (1986): Re lative Liver W eight, Males.............................. E-403 E.3.16.1. Summary Table of BMDS Modeling Results ........................... E-403 E.3.16.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-404 E.3.16.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-404 E.3.17. DeCaprio et al. (1986): Rela tive Thymus W eight, Males ......................... E-407 E.3.17.1. Summary Table of BMDS Modeling Results ........................... E-407 E.3.17.2. Figure for selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-408 E.3.17.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-408 E.3.18. Hojo et al. (2002): DRL Reinforce per Min .............................................. E-411 E.3.18.1. Summary Table of BMDS Modeling Results ........................... E-411 E.3.18.2. Figure for Selected Model: Linear, Constant Variance............. E-412 E.3.18.3. Output File for Selected M odel: L inear, Constant Variance..... E-412 E.3.19. Hojo et al. (2002): DRL Response per Min............................................... E-415 E.3.19.1. Summary Table of BMDS Modeling Results ........................... E-415 E.3.19.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1.................................................. E-416 E.3.19.3. Output File for Selected Model: Exponential (M4), Constant Variance, Power Restricted ≥ 1

................................... E-416 E.3.20. Kattainen et al. (2001): 3rd Mo lar Mesio-Distal L ength (Molar Development)............................................................................................. E-419 E.3.20.1. Summary Table of BMDS Modeling Results ........................... E-419 E.3.20.2. Figure for Selected Model: Hill, Nonconstant Variance, n Restricted >1, Bound Hit

........................................................... E-420 E.3.20.3. Output File for Selected Model: Hill, Nonconstant Variance, n Restricted >1, Bound Hit

....................................... E-420 E.3.21. Kattainen et al. (2001): Females 3rd Molar Eruption................................ E-423 E.3.21.1. Summary Table of BMDS Modeling Results ........................... E-423 E.3.21.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-424 E.3.21.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-424 E.3.22. Keller et al. (2006): Missing Ma ndibular Molars in CBA J Mice

............. E-426 E.3.22.1. Summary Table of BMDS Modeling Results ........................... E-426 E.3.22.2. Figure for Selected Model: Multistage, 1-Degree, Betas Restricted ≥ 0

.............................................................................. E-427 E.3.22.3. Output File for Selected Model: Multistage, 1-Degree, Betas Restricted ≥ 0

.................................................................... E-427

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## E.3.23. Kociba et al. (1978): Urinary C oproporphyrins, Females (Table 2).......... E-429 E.3.23.1. Summary Table of BMDS Modeling Results ........................... E-429 E.3.23.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-430 E.3.23.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-430 E.3.24. Kociba et al. (1978): Uropor phyrin per Creatinine, Fem ales .................... E-433 E.3.24.1. Summary Table of BMDS Modeling Results ........................... E-433 E.3.24.2. Figure for Selected Model: Linear, Constant Variance............. E-434 E.3.24.3. Output File for Selected M odel: L inear, Constant Variance..... E-434 E.3.25. Latchoumycandane and Mathur (2002): Daily sperm Production............. E-437 E.3.25.1. Summary Table of BMDS Modeling Results ........................... E-437 E.3.25.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-438 E.3.25.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-438 E.3.26. Li et al. (2006): Horm one Levels (Estradiol)............................................. E-441 E.3.26.1. Summary Table of BMDS Modeling Results ........................... E-441 E.3.26.2. Figure for Selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-442 E.3.26.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-442 E.3.27. Li et al. (2006): Horm one Levels (Progesterone)

...................................... E-445 E.3.27.1. Summary Table of BMDS Modeling Results ........................... E-445 E.3.27.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-446 E.3.27.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-446 E.3.28. Markowski et al. (2001): FR10 Run Opp .................................................. E-449 E.3.28.1. Summary Table of BMDS Modeling Results ........................... E-449 E.3.28.2. Figure for Selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-450 E.3.28.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-450 E.3.29. Markowski et al. (2001): FR2 Revolutions................................................ E-453 E.3.29.1. Summary Table of BMDS Modeling Results ........................... E-453 E.3.29.2. Figure for Selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-454 E.3.29.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-454 E.3.30. Markowski et al. (2001): FR5 Run Opp .................................................... E-457 E.3.30.1. Summary Table of BMDS Modeling Results ........................... E-457
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## E.3.30.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit........................................................... E-458 E.3.30.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-458 E.3.31. Mietinnin et al. (2006): Caries................................................................... E-461 E.3.31.1. Summary Table of BMDS Modeling Results ........................... E-461 E.3.31.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-462 E.3.31.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-462 E.3.32. National Toxicology Program (1982): Male Mice, Toxic H epatitis.......... E-464 E.3.32.1. Summary Table of BMDS Modeling Results ........................... E-464 E.3.32.2. Figure for Selected Model: Logistic.......................................... E-464 E.3.32.3. Output file for Selected Model: Logistic................................... E-465 E.3.33. National Toxicology Program (2006): Alveolar Metaplasia

..................... E-466 E.3.33.1. Summary Table of BMDS Modeling Results ........................... E-466 E.3.33.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-467 E.3.33.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-467 E.3.34. National Toxicology Program (2006): Gingival Hyperplasia Squa mous, 2 Years..................................................................................... E-469 E.3.34.1. Summary Table of BMDS Modeling Results ........................... E-469 E.3.34.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-470 E.3.34.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-470 E.3.34.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-472 E.3.34.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted

............................................................................... E-472 E.3.35. National Toxicology Program (2006): Heart, Cardiomyopathy................ E-474 E.3.35.1. Summary Table of BMDS Modeling Results ........................... E-474 E.3.35.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-474 E.3.35.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-475 E.3.36. National Toxicology Program ( 2006): Hepatocyte Hypertrophy, 2 Years

.......................................................................................................... E-476 E.3.36.1. Summary Table of BMDS Modeling Results ........................... E-476 E.3.36.2. Figure for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit

........................................................... E-477
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## E.3.36.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit........................................................... E-477 E.3.37. National Toxicology Program (200 6): Liver, E osinophilic Focus, Multiple...................................................................................................... E-479 E.3.37.1. Summary Table of BMDS Modeling Results ........................... E-479 E.3.37.2. Figure for Selected Model: W eibull, Power Restricted ≥ 1, Bound Hit .................................................................................. E-479 E.3.37.3. Output File for Select ed Model: W eibull, Power Restricted ≥ 1, Bound Hit........................................................... E-480 E.3.38. National Toxicology Program (200 6): Liver, Fatty Change, Diffuse

........ E-481 E.3.38.1. Summary Table of BMDS Modeling Results ........................... E-481 E.3.39. Figure for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0

.............................................................................................. E-482 E.3.40. Output File for Selected M odel: Multistage, 2- Degree, Betas Restricted ≥ 0

.............................................................................................. E-482 E.3.41. National Toxicology Program (2006): Liver Necrosis

.............................. E-484 E.3.41.1. Summary Table of BMDS Modeling Results ........................... E-484 E.3.41.2. Figure for Selected Model: LogProbit....................................... E-485 E.3.41.3. Output File for Sel ected Model: Log-Probit

............................. E-485 E.3.42. National Toxicology Program (2006): Liver, Pigmentation...................... E-487 E.3.42.1. Summary Table of BMDS Modeling Results ........................... E-487 E.3.42.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-487 E.3.42.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-488 E.3.43. National Toxicology Program (200 6): Lung, Alveolar to Bronchiolar Epithelial M etaplasia (Alveola r Epithelium, Metaplasia, Bronchiolar) ............................................................................................... E-489 E.3.43.1. Summary Table of BMDS Modeling Results ........................... E-489 E.3.43.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-490 E.3.43.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-490 E.3.44. National Toxicology Program (200 6): Oval Cell Hyperplasia, 2 Years

.......................................................................................................... E-492 E.3.44.1. Summary Table of BMDS Modeling Results ........................... E-492 E.3.44.2. Figure for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0

.............................................................................. E-492 E.3.44.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0

.................................................................... E-493 E.3.45. National Toxicology Program (2006): Toxic Hepatopathy

....................... E-494 E.3.45.1. Summary Table of BMDS Modeling Results ........................... E-494 E.3.45.2. Figure for Selected Mode l: Gamm a, Power Restricted ≥ 1........ E-495

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## E.3.45.3. Output file for Selected Model: Gamma, Power Restricted ≥ 1.............................................................................. E-495 E.3.45.4. Figure for Unrestricted Model: Weibull, Power Restricted ≥ 1

.............................................................................. E-497 E.3.45.5. Output File for Unrestri cted Model: Weibull, Power Restricted ≥ 1

.............................................................................. E-497 E.3.46. Ohsako et al. (2001): Anogenital PND120................................................ E-499 E.3.46.1. Summary Table of BMDS Modeling Results ........................... E-499 E.3.46.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-500 E.3.46.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................ E-500 E.3.47. Schantz et al. (1996): Maze Errors Per Block, Fem ale.............................. E-503 E.3.47.1. Summary Table of BMDS Modeling Results ........................... E-503 E.3.47.2. Figure for Selected Model: Linear, Constant Variance............. E-504 E.3.47.3. Output File for Selected Model: L inear, Constant Variance..................................................................................... E-504 E.3.48. Shi et al. (2007): Estradiol ......................................................................... E-506 E.3.48.1. Summary Table of BMDS Modeling Results ........................... E-506 E.3.48.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-508 E.3.48.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-508 E.3.49. Smialowicz et al. (2008): PFC per 10^6 Cells........................................... E-511 E.3.49.1. Summary Table of BMDS Modeling Results ........................... E-511 E.3.49.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1.................................................. E-512 E.3.49.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................. E-512 E.3.50. Smialowicz et al. (2008): PFC per Spleen................................................. E-515 E.3.50.1. Summary Table of BMDS Modeling Results ........................... E-515 E.3.50.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................. E-516 E.3.50.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................. E-516 E.3.51. Toth et al. (1978): Amyloidosis................................................................. E-519 E.3.51.1. Summary Table of BMDS Modeling Results ........................... E-519 E.3.51.2. Figure for Selected Model: Multistage, 1-Degree, Betas Restricted ≥ 0

.............................................................................. E-519 E.3.51.3. Output File for Selected Model: Multistage, 1-Degree, Betas Restricted ≥ 0

.................................................................... E-519 E.3.52. Toth et al. (1978): Skin Lesions................................................................. E-521 E.3.52.1. Summary Table of BMDS Modeling Results ........................... E-521

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## E.3.52.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1.............................................................................. E-522 E.3.52.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1

.............................................................................. E-522 E.3.53. Van Birgelen et al. (1995a): Hepatic Retinol............................................. E-524 E.3.53.1. Summary Table of BMDS Modeling Results ........................... E-524 E.3.53.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-525 E.3.53.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1............................. E-526 E.3.53.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-528 E.3.53.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-529 E.3.53.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-531 E.3.53.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-532 E.3.53.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-534 E.3.53.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-535 E.3.54. Van Birgelen et al. (1995a ): Hepatic Retinol Palm itate ............................ E-537 E.3.54.1. Summary Table of BMDS Modeling Results ........................... E-537 E.3.54.2. Figure for Selected Model: Hill, Nonconstant Variance, n Unrestricted

............................................................................... E-539 E.3.54.3. Output File for Selected Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-539 E.3.54.4. Figure for Unrestricted Model: L inear, Nonconstant Variance..................................................................................... E-542 E.3.54.5. Output File for Unrestrict ed Model: Linear, Nonconstant Variance

..................................................................................... E-542 E.3.54.6. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-545 E.3.54.7. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-545 E.3.54.8. Figure for Unrestricted Mode l: Exponential (M5), Constant Variance, P ower Unrestricted.................................................... E-548 E.3.54.9. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted

.................................... E-548 E.3.55. Van Birgelen et al. (1995a): Plasm a FT4................................................... E-551 E.3.55.1. Summary Table of BMDS Modeling Results ........................... E-551
2

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## E.3.55.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, Power Restricted ≥ 1.................................................. E-552 E.3.55.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1............................. E-553 E.3.55.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-555 E.3.55.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted .............................. E-556 E.3.55.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

............................................................ E-558 E.3.55.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted............................................................ E-559 E.3.55.8. Figure for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-561 E.3.55.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted.................................................... E-561 E.3.56. Van Birgelen et al . (1995a): Plasm a TT4 .................................................. E-564 E.3.56.1. Summary Table of BMDS Modeling Results ........................... E-564 E.3.56.2. Figure for Selected Model: Exponential (M2), Constant Variance, P ower Restricted ≥ 1.................................................. E-565 E.3.56.3. Output File for Selected Model: Exponential (M2), Constant Variance, Power Restricted ≥ 1

................................... E-566 E.3.56.4. Figure for Unrestricted Model: Exponential (M5), Constant Variance, Power Unrestricted

.................................... E-569 E.3.56.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted

.................................... E-569 E.3.56.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted

............................................................................... E-572 E.3.56.7. Output File for Unrestri cted Model: Hill, cons tant Variance, n Unrestricted............................................................ E-572 E.3.56.8. Figure for Unrestricted Mode l: Pow er, Constant Variance, Power Unrestricted.................................................................... E-575 E.3.56.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted.................................................... E-575 E.3.57. White et al. (1986): CH50.......................................................................... E-578 E.3.57.1. Summary Table of BMDS Modeling Results ........................... E-578 E.3.57.2. Figure for Selected Model: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-579 E.3.57.3. Output File for Selected M odel: Hill, Constant Variance, n Restricted >1, Bound Hit

........................................................... E-579 E.4. REFERENCES........................................................................................................ E-582

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-1 APPENDIX E. NONCANCER BENCHMARK DOSE MODELING 1 2 3 

## E.1. BMDS INPUT TABLES 4 

## E.1.1. Amin et al. (2000) 5 

## Administered Dose (ng/kg-day)
0 25 a 

## 100 Internal Dose (ng/kg blood) b 

## 0 6,800 24,522 Endpoint (n = 10) (n = 10) (n = 10) Saccharin consumed, female (0.25%) 31.67 ± 26.64 24.60 ± 11.98 10.70 ± 5.33 Saccharin consumed, female (0.50%) 22.40 ± 15.98 11.38 ± 7.66 4.54 ± 3.33 Saccharin preference ratio, female (0.25%) 82.14 ± 13.35 58.12 ± 33.88 54.87 ± 19.51 Saccharin preference ratio, female (0.50%) 72.73 ± 24.64 44.48 ± 32.85 33.77 ± 24.64

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

6 7 

## E.1.2. Bell et al. (2007a) 8 

## Administered Dose (ng/kg-day)
0 2.4 a 

## 8 46 Internal Dose (ng/kg blood) b 

## 0 1,998 4,539 15,952 Endpoint (n = 30) (n = 30) (n = 30) (n = 30) Balano-preputial separation, male pups 1/30 (3%) 5/30 (17%) 6/30 (20%) 15/30 (50%)

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-2 E.1.3. Cantoni et al. (1981) 1 

## Administered Dose (ng/kg-day)
0 1.43 a 

## 14.3 143 Internal Dose (ng/kg blood) b 

## 0 1,018 4,868 27,559 Endpoint (n = 4) (n = 4) (n = 3) (n = 3) Urinary coporphyrins 0.74 ± 0.35 1.81 ± 0.83 c 

## 2.73 ± 1.50 d 

## 3.00 ± 2.60 d


## Urinary porphyrins 2.27 ± 0.49 5.55 ± 0.85 c 

## 7.62 ± 1.79 c 

## 196.89 ± 63.14 d

a 

## LOAEL b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05). d 

## Statistically significant as compared to control ( p < 0.01).

2 3 

## E.1.4. Crofton et al. (2005) 4 

## Administered Dose (ng/kg-day)
0 0.1 3 10 30 a 

## 100 b 

## 300 1,000 3,000 10,000 Internal Dose (ng/kg blood) c



### 0 11.3 273 773 1,922 51,11 12,624 35,697 98,088 316,540


## Endpoint (n = 14) (n = 6) (n = 12) (n = 6) (n = 6) (n = 6) (n = 6) (n = 6) (n = 6) (n = 4)

Serum T4 100.00 ± 15.44 96.27 ± 14.98 98.57 ± 18.11 99.76 ± 19.04 93.32 ± 12.11 70.94 ± 12.74 62.52 ± 14.75 52.68 ± 22.73 54.66 ± 19.71 49.15 ± 11.17

a 

## NOAEL b 

## LOAEL

c 

## From the Emond PRPK model described in 3.3.

5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-3 E.1.5. DeCaprio et al. (1986) 1 

## Administered Dose (ng/kg-day)
0 0.12 0.61 a 

## 4.9 b 

## 26 Internal Dose (ng/kg blood) c


## n/a n/a n/a n/a n/a Endpoint (n = 10) (n = 10) (n = 11) (n = 10) (n = 4) Absolute kidney weight, males 5.49 ± 0.54 5.14 ± 0.38 4.71 ± 0.4 4.3±0.47 d


## - Absolute thymus weight, males 0.56 ± 0.16 0.45 ± 0.07 0.44 ± 0.11 0.35±0.53 e 

## -
Body weight, males 713 ± 47.43 682 ± 50.6 651 ± 63.02 603±63.25 d 

## 433 ± 76 f 

## Relative brain weight, males 0.54 ± 0.05 0.56 ± 0.05 0.6 ± 0.05 0.65±0.05 d


## -
Relative liver weight, males 4.54 ± 0.73 4.1 ± 0.44 5.36 ± 2.02 5.63±0.92 d


## - Relative thymus weight, males 0.08 ± 0.02 0.07 ± 0.01 0.07 ± 0.01 0.06±0.01 d


## - Administered Dose (ng/kg-day)
0 0.12 0.68 4.86 31 Internal Dose (ng/kg blood) c


## 0 n/a n/a n/a n/a Endpoint

(n = 8) (n = 10) (n = 9) (n = 10) (n = 4)
Body weight, females 602 ± 33.94 583 ± 69.57 570 ± 66 531 ± 44.27 d 

## 351 ± 98 f 

## Relative liver weight, females 4.3 ± 0.74 4.49 ± 1.11 4.27 ± 0.48 5.54 ± 1.36 d 

## 4.3 ± 0.74

a 

## NOAEL b 

## LOAEL.

c 

## Internal dose not calculated us ing the Emond PBPK (ginuea pigs). d 

## Statistically significant as compared to control ( p < 0.05).

e 

## Statistically significant as compared to control ( p < 0.01). f 

## Statistically significant as compared to control ( p < 0.001).

2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-4 E.1.6. Hojo et al. (2002) 1 

## Administered Dose (ng/kg-day)
0 20 a 

## 60 180 Internal Dose (ng/kg blood) b 

## 0 1,285 3,295 8,465 Endpoint (n = 5) (n = 5) (n = 6) (n = 5) DRL reinforce per min 0.09 ± 0.45 0.54 ± 0.82 1.27 ± 0.54 0.74 ± 0.44 DRL response per min 18.46 ± 7.99 -0.99 ± 10.96 -4.52 ± 7.19 -0.41 ± 15.23

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

2 3 

## E.1.7. Kattainen et al. (2001) 4 

## Administered Dose (ng/kg-day)
0 30 a 

## 100 300 1,000 Internal Dose (ng/kg blood) b 

## 0 1,763 4,944 12,712 37,039 Endpoint (n = 16) (n = 17) (n = 15) (n = 12) (n = 19)
3 rd 

## molar mesio-distal length (molar development) 1.86 ± 0.07 1.58 ± 0.19

c 

## 1.6 ± 0.27 c 

## 1.5 ± 0.22 c 

## 1.35 ± 0.51

c



## Females 3 rd 

## molar eruption 1/16 (10%) 3/17 (20%) 4/15 (30%) 6/12 (50%)

c 

## 13/19 (70%)

c

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05).

5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-5 E.1.8. Keller et al. (2007, 2008a, b) 1 

## Administered Dose (ng/kg-day)
0 10 a 

## 100 1,000 Internal Dose (ng/kg blood) b 

## Endpoint 0 296 2,365 18,764

Missing mandibular molars in CBA J mice 0/29 (0%) 2/23 (10%) 6/29 (20%) 30/30 (100%)

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

2 3 

## E.1.9. Kociba et al. (1978) 4 

## Administered Dose (ng/kg-day)
0 1 a 

## 10 b 

## 100 Internal Dose (ng/kg blood) c 

## 0 853 3,942 21,246 Endpoint (n = 5) (n = 5) (n = 5) (n = 5) Urinary coproporphyrin, females 9.8 ± 1.3 8.6 ± 2 16.4 ± 4.7 d 

## 17.4 ± 4 d


## Uroporphyrin per creatinine, females 0.157 ± 0.05 0.143 ± 0.04 0.181 ± 0.05 0.296 ± 0.07 d

a 

## NOAEL b 

## LOAEL.

c 

## From the Emond PRPK model described in 3.3. d 

## Statistically significant as compared to control ( p < 0.05).

5 6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-6 E.1.10. Latchoumycandane and Mathur (2002) 1 

## Administered Dose (ng/kg-day)
0 1 a 

## 10 100 Internal Dose (ng/kg blood) b 

## 0 437 2,579 15,092 Endpoint (n = 6) (n = 6) (n = 6) (n = 6) Daily sperm production 22.19 ± 2.67 15.67 ± 2.65 c 

## 13.65 ± 2.19 c 

## 13.1 ± 3.16 c

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05).

E.1.11. Li et al. (1997) 2 

## Administered Dose (ng/kg-day)

0 3 a 10 b 30 100 300 1,000 3,000 10,000 30,000 

## Internal Dose (ng/kg blood) c



### 0 147 440 1,156 3,232 8,266 23,875 66,081 212,650 649,740 

## Endpoint (n = 10) (n =10) (n = 10) (n = 10) (n = 10) (n = 10) (n = 10) (n = 10) (n = 10) (n = 10)



## FSH 23.86 ± 29.65 22.16 ± 48.51 85.23 ± 94.33 73.30 ± 48.51 126.14 ± 159.01 132.10 ± 115.89 116.76 ± 51.21 304.26 ± 153.62 346.88 ± 150.93 455.11 ± 285.68

a 

## NOAEL b 

## LOAEL.

c 

## From the Emond PRPK model described in 3.3.

3 4 

## E.1.12. Li et al. (2006) 5 

## Administered Dose (ng/kg-day)
0 2 a 

## 50 100 Internal Dose (ng/kg blood) b 

## 0 87.5 1,564 2,823 Endpoint (n = 10) (n = 10) (n = 10) (n = 10)

Serum estradiol 10. ± 12.48 20 ± 19.97 24.74 ± 15.00 17.90 ± 18.31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-7 Serum progesterone 65.25 ± 11.10 43.36 ± 40.48

c 

## 27.46 ± 33.30 25.19 ± 43.756

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.01).

1 2 

## E.1.13. Markowski et al. (2001) 3 

## Administered Dose (ng/kg-day)
0 20 a 

## 60 180 Internal Dose (ng/kg blood) b 

## 0 1,234 3,184 8,152 Endpoint (n = 7) (n = 4) (n = 6) (n = 7) FR10 run opp 13.29 ± 8.65 11.25 ± 5.56 5.75 ± 3.53 7 ± 6.01
FR2 revolutions 119.29 ± 69.9 108.5 ± 61 56.5 ± 31.21 68.14 ± 33.23 FR5 run opp 26.14 ± 12.28 23.5 ± 7.04 12.8 ± 6.17 13.14 ± 7.14

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

E.1.14. Mietinnin et al. (2006) 4 

## Administered Dose (ng/kg-day)
0 30 a 

## 100 300 1,000 Internal Dose (ng/kg blood) b 

## 0 1,756 4,922 12,657 36,874 Endpoint (n = 42) (n = 29) (n = 15) (n = 24) (n = 32)
Cariogenic lesions in pups 25/42 (60%) 23/29 (79%) b 

## 19/25 (76%) 20/24 (83%) c 

## 29/32 (91%) c

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05).

5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-8 E.1.15. National Toxicology Program (1982) 1


## Administered Dose (ng/kg-day)
0 1.43 a 

## 7.14 71.4 Internal Dose (ng/kg blood) b 

## 0 420 1,240 6,118 Endpoint (n = 73) (n = 49) (n = 49) (n = 50) Toxic hepatitis, male mice 1/73 (1.4%) 5/49 (10%) 5/49 (6.1%) 44/50 (88%)

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

2

3 

## E.1.16. National Toxicology Program (2006) 4 

## Administered Dose (ng/kg-day)
0 2.14 a 

## 7.14 15.7 32.9 71.4 Internal Dose (ng/kg blood) b 

## 0 1,408 3,137 5,393 9,128 16,361 Endpoint (n = 10) (n = 10) (n = 10) (n = 10) (n = 10) (n = 10)
Alveolar metaplasia 2/53 (0%) 19/54 (40%) c, 

## 33/53 (60%) c 

## 35/52 (70%) c 

## 45/53 (80%) c 

## 46/52 (90%) c 

## Gingival hyperplasia squamous, 2 years 1/53 (2%) 7/54 (13%) d 

## 14/53 (26%) c 

## 13/53 (25%) c 

## 15/53 (28%) c 

## 16/53 (30%) c 

## Liver, hepatocyte hypertrophy, 2 years 0/53 (0%) 19/54 (40%) c, 

## 19/53 (40%) c 

## 42/53 (80%) c 

## 41/53 (80%) c 

## 52/53 (100%) c


## Heart, cardiomyopathy 10/53 (19%) 12/54 (22%) 22/53 c 

## (42%) 25/52 c 

## (48%) 32/53 c 

## (60%) 36/52 c 

## (69%) Liver, eosinophilic focus, multiple 3/53 (6%) 8/54 (15%) 14/53 (26%) 17/53 (32%) 22/53 (42%) 42/53 (79%)
Liver, fatty change, diffuse 0/53 (0%) 2/54 (4%) 12/53 c 

## (23%) 17/53 c 

## (32%) 30/53 c 

## (57%) 48/53 c 

## (91%)
Liver, necrosis 1/53 (2%) 4/54 (7%) 4/53 (8%) 8/53 d 

## (15%) 10/53 c 

## (19%) 17/53 c 

## (32%) Liver, pigmentation 4/53 9/54 34/53 c 

## 48/53 c 

## 52/53 c 

## 53/53 c

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-9 Administered Dose (ng/kg-day)
0 2.14 a 

## 7.14 15.7 32.9 71.4 Internal Dose (ng/kg blood) b 

## 0 1,408 3,137 5,393 9,128 16,361 Endpoint (n = 10) (n = 10) (n = 10) (n = 10) (n = 10) (n = 10) (8%) (17%) (64%) (91%) (98%) (100%)
Liver, toxic hepatopathy 0/53 (0%) 2/54 (4%) 8/53 (15%) 30/53 (57%) 45/50 (85%) 53/53 (100%)
Oval cell hyperplasia, 2 years 0/53 (0%) 4/54 (10%) d 

## 3/53 (10%) 20/53 (40%) c 

## 38/53 (70%) d 

## 53/53 (100%) c 

## Lung, alveolar to bronchiolar epithelial metaplasia (Alveolar epithelium, metaplasia, bronchiolar) 2/53 (4%) 19/54 c 

## (35%) 33/53 c 

## (62%) 35/52 c 

## (67%) 45/53 c 

## (85%) 46/52 c 

## (89%)

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.01). d 

## Statistically significant as compared to control ( p < 0.05).

1 2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-10 E.1.17. Ohsako et al. (2001) 1 

## Administered Dose (ng/kg-day)
0 12.5 a 

## 50 b 

## 200 800 Internal Dose (ng/kg blood) c 

## 0 845 2,763 9,022 30,504 Endpoint (n = 12) (n = 10) (n = 10) (n = 10) (n = 12)

Anogenital PND120 28.91 ± 3.54 28.08 ± 2.52 25.31 ± 3.59 d 

## 26.07 ± 3.59 e 

## 23.87 ± 2.36 d

a 

## NOAEL for selected endpoint. b 

## LOAEL for selected endpoint.

c 

## From the Emond PRPK model described in 3.3. d 

## Statistically significant as compared to control ( p < 0.01).

e 

## Statistically significant as compared to control ( p < 0.05).

2 3 

## E.1.18. Schantz et al. (1996) 4 

## Administered Dose (ng/kg-day)
0 25 100 Internal Dose (ng/kg blood) a 

## 0 6,800 24,522 Endpoint (n = 10) (n = 10) (n = 10) Maze errors per block 3.55 ± 0.64 2.76 ± 0.81 b 

## 2.34 ± 0.81 c

a 

## From the Emond PRPK model described in 3.3. b 

## Statistically significant as compared to control ( p < 0.05).

c 

## Statistically significant as compared to control ( p < 0.001).

5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-11 E.1.19. Shi et al. (2007) 1 

## Administered Dose (ng/kg-day)
0 0.143 a 

## 0.714 b 

## 7.14 28.6 Internal Dose (ng/kg blood) c 

## 0 188 592 2,882 7,665 Endpoint (n = 10) (n = 10) (n = 10) (n = 10) (n = 10)

Serum estradiol 102.86 ± 41.41 86.19 ± 19.58 63.33 ± 29.36 d 

## 48.1 ± 18.82 d 

## 38.57 ± 22.59 d

a 

## NOAEL. b 

## LOAEL.

c 

## From the Emond PRPK model described in 3.3. d 

## Statistically significant as compared to control ( p < 0.05).

2 3 

## E.1.20. Smialowicz et al. (2008) 4 

## Administered Dose (ng/kg-day)
0 1.07 a 

## 10.7 107 321 Internal Dose (ng/kg blood) b 

## 0 241 1,358 7,385 17,438 Endpoint (n = 15) (n = 14) (n = 15) (n = 15) (n = 8) PFC per 10 6 

## Cells 1491 ± 716 1129 ± 171 c 

## 945 ± 516 c 

## 677 ± 465 c 

## 161 ± 117 c 

## PFC per spleen 27.8 ± 13.4 21 ± 13.6 c 

## 17.6 ± 9.4 c 

## 12.6 ± 8.7 c 

## 3 ± 3.1 c

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05).

5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-12 E.1.21. Toth et al. (1979) 1 

## Administered Dose (ng/kg-day)
0 1 a 

## 100 1,000 Internal Dose (ng/kg blood) b 

## 0 316 7,814 50,105 Endpoint (n =38) (n = 44) (n = 44) (n = 43) Amyloidosis 0/38 (0%) 5/44 (11%) 10/44 (23%) 17/43 (40%)
Skin Lesions 0/38 (0%) 5/44 (11%) 13/44 (30%) 25/43 (58%)

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

2 3 

## E.1.22. Van Birgelen et al. (1995) 4

Administered Dose (ng/kg-day)

0 14 a 26 47 320 1,024
Internal Dose (ng/kg blood) b

0 3,969 6,479 9,968 47,606 137,820 Endpoint n = 8 n = 8 n = 8 n = 8 n = 8 n = 8 Hepatic retinol 14.9 ± 8.77 8.4 ± 3.39 c 8.2 ± 2.26 c 5.1 ± 0.85 c 2.2 ± 0.85 c 0.6 ± 0.57 c

Hepatic retinol palmitate 472 ± 271.53 94 ± 67.88 c 107 ± 76.37 c 74 ± 39.6 c 22 ± 22.63 c 3 ± 2.83 c

Plasma FT4 23.4 ± 3.11 24.5 ± 5.66 22.4 ± 2.83 19.3 ± 9.33 16.3 ± 4.24 c 10.3 ± 4.81 c

Plasma TT4 40.9 ± 6.79 41.4 ± 5.37 41.4 ± 6.51 32.3 ± 7.35 c 33.6 ± 6.22 c 25.5 ± 7.64 c

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05).

5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-13 E.1.23. White et al. (1986) 1 

## Administered Dose (ng/kg-day)
0 10 a 

## 50 100 500 1,000 2,000 Internal Dose (ng/kg blood) b 

## 0 602 2,250 3,934 14,772 26,844 49,896 Endpoint (n = 8) (n = 8) (n = 8) (n = 8) (n = 8) (n = 8) (n = 8)
CH50 91 ± 14.14 

### 54 ± 8.5 c 

## 63 ± 11 c 

## 56 ± 26 c 

## 41 ± 17 c 

## 32 ± 17 c 

## 17 ± 17 c

a 

## LOAEL. b 

## From the Emond PRPK model described in 3.3.

c 

## Statistically significant as compared to control ( p < 0.05).

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-14 E.2. ALTERNATE DOSE: BLOOD SERUM BMDS RESULTS 1 

## E.2.1. Amin et al. (2000): Sacchari n Consumed, Female (0.25%) 2 

## E.2.1.1. Summary Table of BMDS Modeling Results 3



## Model Degrees of freedom Variance p -value a 

## χ 2 

## Test statistic χ 2 

## p value b 

## AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

Linear c 

## 1 0.00 0.35 0.55 179.21 7.2E+03 4.8E+03 nonconstant variance Polynomial 1 0.00 0.35 0.55 179.21 7.2E+03 4.8E+03 nonconstant variance
Power 1 0.00 0.35 0.55 179.21 7.2E+03 4.8E+03 nonconstant variance, power restricted ≥ 1, bound hit
Power d 

## 0 0.00 0.00 NA 180.86 6.6E+03 2.7E+03 nonconstant variance, power unrestricted
Linear 1 0.00 0.00 0.95 191.69 5.3E+03 3.5E+03 constant variance Polynomial 1 0.00 0.00 0.95 191.69 5.3E+03 3.5E+03 constant variance
Power 1 0.00 0.00 0.95 191.69 5.3E+03 3.5E+03 constant variance, power restricted ≥ 1, bound hit
Power 0 0.00 0.00 NA 193.68 5.2E+03 1.3E+03 constant variance, power unrestricted

4

a 

## Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a 5 

## constant variance model should be selected. 6 b 

## Values <0.1 fail to meet BMDS goodness-of-fit criteria. 7
c 

## Best-fitting model as assessed by lowest-AIC cri terion, bolded, presented in this appendix. 8 d 

## Alternate model also presented in this appendix. 9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-15 E.2.1.2. Figure for Selected Model: Linear, Nonconstant Variance 1

5 10 15 20 25 30 35 40 45 50

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Linear Model with 0.95 Confidence Level

13:42 11/16 2009 BMD BMDL Linear

2 3 4 

## E.2.1.3. Output File for Selected Mode l: L inear, Nonconstant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_25_s_c.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_25_s_c.plt 11 Mon Nov 16 13:42:20 2009 12

==================================================================== 13 14 Rel Male Thymus wt, Tbl 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Signs of the polynomial coefficients are not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 3 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 5.29482 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-16 rho = 0 1 beta_0 = 31.5152 2 beta_1 = -0.0025051 3 4 5 Asymptotic Correlation Matrix of Parameter Estimates 6 7 lalpha rho beta_0 beta_1 8 9 lalpha 1 -0.99 -0.029 0.044 10 11 rho -0.99 1 0.026 -0.04 12 13 beta_0 -0.029 0.026 1 -0.94 14 15 beta_1 0.044 -0.04 -0.94 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 lalpha -2.542 1.65042 -5.77677 0.692762 24 rho 2.40977 0.541752 1.34795 3.47158 25 beta_0 31.2702 4.19399 23.0501 39.4903 26 beta_1 -0.00246009 0.000552567 -0.0035431 -0.00137708 27 28 29 30 Table of Data and Estimated Values of Interest 31 32 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 33

------ --- -------- -------- ----------- ----------- ---------- 34 35 0 10 31.7 31.3 20.6 17.8 0.0717 36 2670 10 24.6 24.7 12 13.4 -0.0253 37 8341 10 10.7 10.8 5.33 4.91 -0.0363 38 39 40 41 Model Descriptions for likelihoods calculated 42 43 44 Model A1: Yij = Mu(i) + e(ij) 45 Var{e(ij)} = Sigma^2 46 47 Model A2: Yij = Mu(i) + e(ij) 48 Var{e(ij)} = Sigma(i)^2 49 50 Model A3: Yij = Mu(i) + e(ij) 51 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 52 Model A3 uses any fixed variance parameters that 53 were specified by the user 54 55 Model R: Yi = Mu + e(i) 56 Var{e(i)} = Sigma^2 57 58 59 Likelihoods of Interest 60 61 Model Log(likelihood) # Param's AIC 62 A1 -92.841935 4 193.683870 63 A2 -85.255316 6 182.510632 64 A3 -85.429148 5 180.858295 65 fitted -85.605740 4 179.211479 66 R -98.136607 2 200.273213 67 68 69 Explanation of Tests 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-17 1 Test 1: Do responses and/or variances differ among Dose levels? 2 (A2 vs. R) 3 Test 2: Are Variances Homogeneous? (A1 vs A2) 4 Test 3: Are variances adequately modeled? (A2 vs. A3) 5 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 6 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 7 8 Tests of Interest 9 10 Test -2*log(Likelihood Ratio) Test df p-value 11 12 Test 1 25.7626 4 <.0001 13 Test 2 15.1732 2 0.0005072 14 Test 3 0.347663 1 0.5554 15 Test 4 0.353184 1 0.5523 16 17 The p-value for Test 1 is less than .05. There appears to be a 18 difference between response and/or variances among the dose levels 19 It seems appropriate to model the data 20 21 The p-value for Test 2 is less than .1. A non-homogeneous variance 22 model appears to be appropriate 23 24 The p-value for Test 3 is greater than .1. The modeled variance appears 25 to be appropriate here 26 27 The p-value for Test 4 is greater than .1. The model chosen seems 28 to adequately describe the data 29 30 31 Benchmark Dose Computation 32 33 Specified effect = 1 34 35 Risk Type = Estimated standard deviations from the control mean 36 37 Confidence level = 0.95 38 39 BMD = 7219.69 40 41 42 BMDL = 4809.97 43 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-18 E.2.1.4. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

5 10 15 20 25 30 35 40 45 50

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

13:42 11/16 2009 BMD BMDL Power

2 3 4 

## E.2.1.5. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_25_s_c.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_25_s_c.plt 12 Mon Nov 16 13:42:20 2009 13

==================================================================== 14 15 Rel Male Thymus wt, Tbl 2 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 3 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-19 Default Initial Parameter Values 1 lalpha = 5.29482 2 rho = 0 3 control = 31.6727 4 slope = -0.00381519 5 power = 0.953851 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho control slope power 11 12 lalpha 1 -0.99 0.34 -0.095 -0.061 13 14 rho -0.99 1 -0.42 0.11 0.068 15 16 control 0.34 -0.42 1 -0.61 -0.56 17 18 slope -0.095 0.11 -0.61 1 1 19 20 power -0.061 0.068 -0.56 1 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha -2.48291 2.08669 -6.57274 1.60692 29 rho 2.38455 0.692047 1.02817 3.74094 30 control 32.99 5.40753 22.3915 43.5886 31 slope -0.0286289 0.0946744 -0.214187 0.156929 32 power 0.736753 0.351085 0.0486403 1.42487 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 10 31.7 33 20.6 18.7 -0.223 42 2670 10 24.6 23.4 12 12.4 0.302 43 8341 10 10.7 10.8 5.33 4.94 -0.08 44 45 Warning: Likelihood for fitted model larger than the Likelihood for model A3. 46 47 48 49 Model Descriptions for likelihoods calculated 50 51 52 Model A1: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma^2 54 55 Model A2: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma(i)^2 57 58 Model A3: Yij = Mu(i) + e(ij) 59 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 60 Model A3 uses any fixed variance parameters that 61 were specified by the user 62 63 Model R: Yi = Mu + e(i) 64 Var{e(i)} = Sigma^2 65 66 67 Likelihoods of Interest 68 69 Model Log(likelihood) # Param's AIC 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-20 A1 -92.841935 4 193.683870 1 A2 -85.255316 6 182.510632 2 A3 -85.429148 5 180.858295 3 fitted -85.429148 5 180.858295 4 R -98.136607 2 200.273213 5 6 7 Explanation of Tests 8 9 Test 1: Do responses and/or variances differ among Dose levels? 10 (A2 vs. R) 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 15 16 Tests of Interest 17 18 Test -2*log(Likelihood Ratio) Test df p-value 19 20 Test 1 25.7626 4 <.0001 21 Test 2 15.1732 2 0.0005072 22 Test 3 0.347663 1 0.5554 23 Test 4 -8.2423e-013 0 NA 24 25 The p-value for Test 1 is less than .05. There appears to be a 26 difference between response and/or variances among the dose levels 27 It seems appropriate to model the data 28 29 The p-value for Test 2 is less than .1. A non-homogeneous variance 30 model appears to be appropriate 31 32 The p-value for Test 3 is greater than .1. The modeled variance appears 33 to be appropriate here 34 35 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 36 test for fit is not valid 37 38 39 Benchmark Dose Computation 40 41 Specified effect = 1 42 43 Risk Type = Estimated standard deviations from the control mean 44 45 Confidence level = 0.95 46 47 BMD = 6606.37 48 49 50 BMDL = 2702.55 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-21 E.2.2. Amin et al. (2000): Sacchari n Consumed, Female (0.50%) 1 

## E.2.2.1. Summary Table of BMDS Modeling Results 2



## Model Degrees of Freedom Variance p -Value a 

## χ 2 

## Test Statistic χ 2 

## p Value b 

## AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 

## 1 <.0001 3.52 0.06 158.58 8.0E+03 5.2E+03 nonconstant variance polynomial 1 <.0001 3.52 0.06 158.58 8.0E+03 5.2E+03 nonconstant variance

power 1 <.0001 3.52 0.06 158.58 8.0E+03 5.2E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 

## 0 <.0001 0.00 NA 157.06 5.2E+03 9.1E+02 nonconstant variance, power unrestricted

3

a 

## Values <0.1 means nonconstant variance model should be selected; values ≥ 0.1 means a 4 

## constant variance model should be selected 5 b 

## Values <0.1 fail to meet BMDS goodness-of-fit criteria 6

c 

## Best-fitting model as assessed by lowest-AIC cri terion, bolded, presented in this appendix 7 d 

## Alternate model also presented in this appendix 8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-22 E.2.2.2. Figure for Selected Model: Linear, Nonconstant Variance 1

0 5 10 15 20 25 30 35

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Linear Model with 0.95 Confidence Level

13:41 11/16 2009 BMD BMDL Linear

2 3 4 

## E.2.2.3. Output File for Selected Mode l: L inear, Nonconstant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_50_s_c.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_50_s_c.plt 11 Mon Nov 16 13:41:55 2009 12

==================================================================== 13 14 Rel Male Thymus wt, Tbl 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Signs of the polynomial coefficients are not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 3 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 4.68512 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-23 rho = 0 1 beta_0 = 20.0674 2 beta_1 = -0.00199124 3 4 5 Asymptotic Correlation Matrix of Parameter Estimates 6 7 lalpha rho beta_0 beta_1 8 9 lalpha 1 -0.96 0.019 -0.0016 10 11 rho -0.96 1 -0.031 0.015 12 13 beta_0 0.019 -0.031 1 -0.96 14 15 beta_1 -0.0016 0.015 -0.96 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 lalpha -0.981979 0.982197 -2.90705 0.943092 24 rho 2.11795 0.401142 1.33173 2.90417 25 beta_0 18.6205 3.17872 12.3903 24.8507 26 beta_1 -0.00168815 0.000408035 -0.00248788 -0.000888416 27 28 29 30 Table of Data and Estimated Values of Interest 31 32 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 33

------ --- -------- -------- ----------- ----------- ---------- 34 35 0 10 22.4 18.6 16 13.5 0.872 36 2670 10 11.4 14.1 7.66 10.1 -0.855 37 8341 10 4.54 4.54 3.33 3.04 -0.00339 38 39 40 41 Model Descriptions for likelihoods calculated 42 43 44 Model A1: Yij = Mu(i) + e(ij) 45 Var{e(ij)} = Sigma^2 46 47 Model A2: Yij = Mu(i) + e(ij) 48 Var{e(ij)} = Sigma(i)^2 49 50 Model A3: Yij = Mu(i) + e(ij) 51 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 52 Model A3 uses any fixed variance parameters that 53 were specified by the user 54 55 Model R: Yi = Mu + e(i) 56 Var{e(i)} = Sigma^2 57 58 59 Likelihoods of Interest 60 61 Model Log(likelihood) # Param's AIC 62 A1 -83.696404 4 175.392808 63 A2 -73.511830 6 159.023660 64 A3 -73.530233 5 157.060467 65 fitted -75.291848 4 158.583695 66 R -90.294746 2 184.589492 67 68 69 Explanation of Tests 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-24 1 Test 1: Do responses and/or variances differ among Dose levels? 2 (A2 vs. R) 3 Test 2: Are Variances Homogeneous? (A1 vs A2) 4 Test 3: Are variances adequately modeled? (A2 vs. A3) 5 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 6 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 7 8 Tests of Interest 9 10 Test -2*log(Likelihood Ratio) Test df p-value 11 12 Test 1 33.5658 4 <.0001 13 Test 2 20.3691 2 <.0001 14 Test 3 0.0368066 1 0.8479 15 Test 4 3.52323 1 0.06051 16 17 The p-value for Test 1 is less than .05. There appears to be a 18 difference between response and/or variances among the dose levels 19 It seems appropriate to model the data 20 21 The p-value for Test 2 is less than .1. A non-homogeneous variance 22 model appears to be appropriate 23 24 The p-value for Test 3 is greater than .1. The modeled variance appears 25 to be appropriate here 26 27 The p-value for Test 4 is less than .1. You may want to try a different 28 model 29 30 31 Benchmark Dose Computation 32 33 Specified effect = 1 34 35 Risk Type = Estimated standard deviations from the control mean 36 37 Confidence level = 0.95 38 39 BMD = 8021.29 40 41 42 BMDL = 5183.12 43 44 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-25 E.2.2.4. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 5 10 15 20 25 30 35

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

13:41 11/16 2009 BMD BMDL Power

2 3 4 

## E.2.2.5. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_50_s_c.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_50_s_c.plt 12 Mon Nov 16 13:41:56 2009 13

==================================================================== 14 15 Rel Male Thymus wt, Tbl 2 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 3 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-26 Default Initial Parameter Values 1 lalpha = 4.68512 2 rho = 0 3 control = 22.3564 4 slope = -0.381559 5 power = 0.42572 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho control slope power 11 12 lalpha 1 -0.96 0.34 -0.2 -0.15 13 14 rho -0.96 1 -0.47 0.23 0.15 15 16 control 0.34 -0.47 1 -0.63 -0.52 17 18 slope -0.2 0.23 -0.63 1 0.99 19 20 power -0.15 0.15 -0.52 0.99 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha -0.708629 1.298 -3.25267 1.83541 29 rho 1.96142 0.529653 0.923323 2.99953 30 control 22.6293 4.48415 13.8405 31.4181 31 slope -0.50513 0.841243 -2.15394 1.14368 32 power 0.396043 0.168878 0.0650481 0.727037 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 10 22.4 22.6 16 15 -0.0577 42 2670 10 11.4 11.1 7.66 7.46 0.105 43 8341 10 4.54 4.58 3.33 3.12 -0.0475 44 45 Degrees of freedom for Test A3 vs fitted <= 0 46 47 48 49 Model Descriptions for likelihoods calculated 50 51 52 Model A1: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma^2 54 55 Model A2: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma(i)^2 57 58 Model A3: Yij = Mu(i) + e(ij) 59 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 60 Model A3 uses any fixed variance parameters that 61 were specified by the user 62 63 Model R: Yi = Mu + e(i) 64 Var{e(i)} = Sigma^2 65 66 67 Likelihoods of Interest 68 69 Model Log(likelihood) # Param's AIC 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-27 A1 -83.696404 4 175.392808 1 A2 -73.511830 6 159.023660 2 A3 -73.530233 5 157.060467 3 fitted -73.530233 5 157.060467 4 R -90.294746 2 184.589492 5 6 7 Explanation of Tests 8 9 Test 1: Do responses and/or variances differ among Dose levels? 10 (A2 vs. R) 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 15 16 Tests of Interest 17 18 Test -2*log(Likelihood Ratio) Test df p-value 19 20 Test 1 33.5658 4 <.0001 21 Test 2 20.3691 2 <.0001 22 Test 3 0.0368066 1 0.8479 23 Test 4 0 0 NA 24 25 The p-value for Test 1 is less than .05. There appears to be a 26 difference between response and/or variances among the dose levels 27 It seems appropriate to model the data 28 29 The p-value for Test 2 is less than .1. A non-homogeneous variance 30 model appears to be appropriate 31 32 The p-value for Test 3 is greater than .1. The modeled variance appears 33 to be appropriate here 34 35 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 36 test for fit is not valid 37 38 39 Benchmark Dose Computation 40 41 Specified effect = 1 42 43 Risk Type = Estimated standard deviations from the control mean 44 45 Confidence level = 0.95 46 47 BMD = 5186.92 48 49 50 BMDL = 913.947 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-28 E.2.3. Amin et al. (2000): Saccharin Preference Ratio, Female (0.25% ) 1 

## E.2.3.1. Summary Table of BMDS Modeling Results 2



## Model Degrees of Freedom Variance p -Value a 

## χ 2 

## Test Statistic χ 2 

## p Value b 

## AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 

## 1 0.01 9.51 0.00 227.81 9.2E+03 4.4E+03 nonconstant variance polynomial 1 0.01 9.51 0.00 227.81 9.2E+03 4.4E+03 nonconstant variance

power 1 0.01 9.51 0.00 227.81 9.2E+03 4.4E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 

## 1 0.01 1.22 0.27 219.52 8.3E+05 error nonconstant variance, power unrestricted

a 

## Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b 

## Values <0.1 fail to meet BMDS goodness-of-fit criteria

c 

## Best-fitting model as assessed by lowest-AIC criterion, bolded , presented in this appendix

d 

## Alternate model also pres ented in this appendix

3 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-29 E.2.3.2. Figure for Selected Model: Linear, Nonconstant Variance 1

30 40 50 60 70 80 90

0 2000 4000 6000 8000Mean Response

dose Linear Model with 0.95 Confidence Level

13:41 11/16 2009 BMD BMDL Linear

2 3 4 

## E.2.3.3. Output File for Selected Mode l: L inear, Nonconstant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_25_s_p_f.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_25_s_p_f.plt 11 Mon Nov 16 13:41:29 2009 12

==================================================================== 13 14 Rel Male Thymus wt Tbl 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Signs of the polynomial coefficients are not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 3 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 6.34368 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-30 rho = 0 1 beta_0 = 75.4969 2 beta_1 = -0.00284822 3 4 5 Asymptotic Correlation Matrix of Parameter Estimates 6 7 lalpha rho beta_0 beta_1 8 9 lalpha 1 -1 0.22 -0.31 10 11 rho -1 1 -0.22 0.31 12 13 beta_0 0.22 -0.22 1 -0.77 14 15 beta_1 -0.31 0.31 -0.77 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 lalpha 3.02282 9.21151 -15.0314 21.077 24 rho 0.793523 2.21122 -3.54039 5.12744 25 beta_0 75.1183 6.74307 61.9021 88.3345 26 beta_1 -0.00274398 0.00127757 -0.00524797 -0.000239995 27 28 29 30 Table of Data and Estimated Values of Interest 31 32 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 33

------ --- -------- -------- ----------- ----------- ---------- 34 35 0 10 82.1 75.1 13.3 25.2 0.883 36 2670 10 58.1 67.8 33.9 24.2 -1.27 37 8341 10 54.9 52.2 19.5 21.8 0.383 38 39 40 41 Model Descriptions for likelihoods calculated 42 43 44 Model A1: Yij = Mu(i) + e(ij) 45 Var{e(ij)} = Sigma^2 46 47 Model A2: Yij = Mu(i) + e(ij) 48 Var{e(ij)} = Sigma(i)^2 49 50 Model A3: Yij = Mu(i) + e(ij) 51 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 52 Model A3 uses any fixed variance parameters that 53 were specified by the user 54 55 Model R: Yi = Mu + e(i) 56 Var{e(i)} = Sigma^2 57 58 59 Likelihoods of Interest 60 61 Model Log(likelihood) # Param's AIC 62 A1 -108.574798 4 225.149597 63 A2 -104.269377 6 220.538754 64 A3 -105.147952 5 220.295903 65 fitted -109.902600 4 227.805201 66 R -112.382522 2 228.765045 67 68 69 Explanation of Tests 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-31 1 Test 1: Do responses and/or variances differ among Dose levels? 2 (A2 vs. R) 3 Test 2: Are Variances Homogeneous? (A1 vs A2) 4 Test 3: Are variances adequately modeled? (A2 vs. A3) 5 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 6 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 7 8 Tests of Interest 9 10 Test -2*log(Likelihood Ratio) Test df p-value 11 12 Test 1 16.2263 4 0.00273 13 Test 2 8.61084 2 0.0135 14 Test 3 1.75715 1 0.185 15 Test 4 9.5093 1 0.002044 16 17 The p-value for Test 1 is less than .05. There appears to be a 18 difference between response and/or variances among the dose levels 19 It seems appropriate to model the data 20 21 The p-value for Test 2 is less than .1. A non-homogeneous variance 22 model appears to be appropriate 23 24 The p-value for Test 3 is greater than .1. The modeled variance appears 25 to be appropriate here 26 27 The p-value for Test 4 is less than .1. You may want to try a different 28 model 29 30 31 Benchmark Dose Computation 32 33 Specified effect = 1 34 35 Risk Type = Estimated standard deviations from the control mean 36 37 Confidence level = 0.95 38 39 BMD = 9167.26 40 41 42 BMDL = 4394.21 43 44 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-32 E.2.3.4. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

30 40 50 60 70 80 90

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model

13:41 11/16 2009 Power

2 3 4 

## E.2.3.5. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_25_s_p_f.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_25_s_p_f.plt 12 Mon Nov 16 13:41:30 2009 13

==================================================================== 14 15 Rel Male Thymus wt Tbl 2 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 3 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-33 Default Initial Parameter Values 1 lalpha = 6.34368 2 rho = 0 3 control = 82.1429 4 slope = -9.98589 5 power = 0.111278 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 ( *** The model parameter(s) -power 11 have been estimated at a boundary point, or have been specified by the user, 12 and do not appear in the correlation matrix ) 13 14 lalpha rho control slope 15 16 lalpha 1 -1 -0.26 0.64 17 18 rho -1 1 0.27 -0.63 19 20 control -0.26 0.27 1 -0.56 21 22 slope 0.64 -0.63 -0.56 1 23 24 25 26 Parameter Estimates 27 28 95.0% Wald Confidence Interval 29 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 30 lalpha 22.273 8.00764 6.57832 37.9677 31 rho -3.90063 1.89036 -7.60567 -0.195596 32 control 82.1429 4.00411 74.295 89.9908 33 slope -25.6494 7.11029 -39.5853 -11.7135 34 power 0 NA 35 36 NA - Indicates that this parameter has hit a bound 37 implied by some inequality constraint and thus 38 has no standard error. 39 40 41 42 Table of Data and Estimated Values of Interest 43 44 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 45

------ --- -------- -------- ----------- ----------- ---------- 46 47 0 10 82.1 56.5 13.3 26.3 3.09 48 2670 10 58.1 56.5 33.9 26.3 0.195 49 8341 10 54.9 56.5 19.5 26.3 -0.195 50 51 52 53 Model Descriptions for likelihoods calculated 54 55 56 Model A1: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 59 Model A2: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma(i)^2 61 62 Model A3: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 64 Model A3 uses any fixed variance parameters that 65 were specified by the user 66 67 Model R: Yi = Mu + e(i) 68 Var{e(i)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-34 1 Likelihoods of Interest 2 3 Model Log(likelihood) # Param's AIC 4 A1 -108.574798 4 225.149597 5 A2 -104.269377 6 220.538754 6 A3 -105.147952 5 220.295903 7 fitted -105.759821 4 219.519641 8 R -112.382522 2 228.765045 9 10 11 Explanation of Tests 12 13 Test 1: Do responses and/or variances differ among Dose levels? 14 (A2 vs. R) 15 Test 2: Are Variances Homogeneous? (A1 vs A2) 16 Test 3: Are variances adequately modeled? (A2 vs. A3) 17 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 18 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 19 20 Tests of Interest 21 22 Test -2*log(Likelihood Ratio) Test df p-value 23 24 Test 1 16.2263 4 0.00273 25 Test 2 8.61084 2 0.0135 26 Test 3 1.75715 1 0.185 27 Test 4 1.22374 1 0.2686 28 29 The p-value for Test 1 is less than .05. There appears to be a 30 difference between response and/or variances among the dose levels 31 It seems appropriate to model the data 32 33 The p-value for Test 2 is less than .1. A non-homogeneous variance 34 model appears to be appropriate 35 36 The p-value for Test 3 is greater than .1. The modeled variance appears 37 to be appropriate here 38 39 The p-value for Test 4 is greater than .1. The model chosen seems 40 to adequately describe the data 41 42 Since the power was estimated to be 0, the BMD is infinite. 43 Setting BMD = 100*(maximum dose). 44 45 Benchmark Dose Computation 46 47 Specified effect = 1 48 49 Risk Type = Estimated standard deviations from the control mean 50 51 Confidence level = 0.95 52 53 BMD = 834064 54 55 Warning: optimum may not have been found. Bad completion code in Optimization routine. 56 57 BMDL computation failed. 58

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-35 E.2.4. Amin et al. (2000): Saccharin Preference Ratio, Female (0.50% ) 1 

## E.2.4.1. Summary Table of BMDS Modeling Results 2



## Saccharin preference ratio, female (0.50%) (Amin et al., 2000)

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 1 0.56 2.23 0.14 234.25 6.4E+03 4.0E+03 constant variance

polynomial 1 0.56 2.23 0.14 234.25 6.4E+03 4.0E+03 constant variance

power 1 0.56 2.23 0.14 234.25 6.4E+03 4.0E+03 constant variance, power restricted ≥ 1, bound hit

power d 0 0.56 0.00 NA 234.02 2.1E+03 1.3E-05 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 3 4 5 

## E.2.4.2. Figure for Selected Model: Linear, Constant Variance 6

10 20 30 40 50 60 70 80 90

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Linear Model with 0.95 Confidence Level

13:41 11/16 2009 BMD BMDL Linear

7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-36 E.2.4.3. Output File for Selected Mode l: L inear, Constant Variance 1
2 3

==================================================================== 4 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\Blood\LinearCV_BMR1_50_s_p_f.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\LinearCV_BMR1_50_s_p_f.plt 7 Mon Nov 16 13:41:03 2009 8

==================================================================== 9 10 Rel Male Thymus wt, Tbl 2 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the response function is: 14 15 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 16 17 18 Dependent variable = Mean 19 Independent variable = Dose 20 rho is set to 0 21 Signs of the polynomial coefficients are not restricted 22 A constant variance model is fit 23 24 Total number of dose groups = 3 25 Total number of records with missing values = 0 26 Maximum number of iterations = 250 27 Relative Function Convergence has been set to: 1e-008 28 Parameter Convergence has been set to: 1e-008 29 30 31 32 Default Initial Parameter Values 33 alpha = 764.602 34 rho = 0 Specified 35 beta_0 = 65.8731 36 beta_1 = -0.00423638 37 38 39 Asymptotic Correlation Matrix of Parameter Estimates 40 41 ( *** The model parameter(s) -rho 42 have been estimated at a boundary point, or have been specified by the user, 43 and do not appear in the correlation matrix ) 44 45 alpha beta_0 beta_1 46 47 alpha 1 -4.3e-009 -3.4e-010 48 49 beta_0 -4.3e-009 1 -0.73 50 51 beta_1 -3.4e-010 -0.73 1 52 53 54 55 Parameter Estimates 56 57 95.0% Wald Confidence Interval 58 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 59 alpha 741.152 191.365 366.084 1116.22 60 beta_0 65.8731 7.22637 51.7096 80.0365 61 beta_1 -0.00423638 0.00142921 -0.00703759 -0.00143517 62 63 64 65 Table of Data and Estimated Values of Interest 66 67 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 68

------ --- -------- -------- ----------- ----------- ---------- 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-37 1 0 10 72.7 65.9 24.6 27.2 0.796 2 2670 10 44.5 54.6 32.9 27.2 -1.17 3 8341 10 33.8 30.5 24.6 27.2 0.375 4 5 6 7 Model Descriptions for likelihoods calculated 8 9 10 Model A1: Yij = Mu(i) + e(ij) 11 Var{e(ij)} = Sigma^2 12 13 Model A2: Yij = Mu(i) + e(ij) 14 Var{e(ij)} = Sigma(i)^2 15 16 Model A3: Yij = Mu(i) + e(ij) 17 Var{e(ij)} = Sigma^2 18 Model A3 uses any fixed variance parameters that 19 were specified by the user 20 21 Model R: Yi = Mu + e(i) 22 Var{e(i)} = Sigma^2 23 24 25 Likelihoods of Interest 26 27 Model Log(likelihood) # Param's AIC 28 A1 -113.009921 4 234.019841 29 A2 -112.428886 6 236.857773 30 A3 -113.009921 4 234.019841 31 fitted -114.123097 3 234.246193 32 R -117.976057 2 239.952114 33 34 35 Explanation of Tests 36 37 Test 1: Do responses and/or variances differ among Dose levels? 38 (A2 vs. R) 39 Test 2: Are Variances Homogeneous? (A1 vs A2) 40 Test 3: Are variances adequately modeled? (A2 vs. A3) 41 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 42 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 43 44 Tests of Interest 45 46 Test -2*log(Likelihood Ratio) Test df p-value 47 48 Test 1 11.0943 4 0.02552 49 Test 2 1.16207 2 0.5593 50 Test 3 1.16207 2 0.5593 51 Test 4 2.22635 1 0.1357 52 53 The p-value for Test 1 is less than .05. There appears to be a 54 difference between response and/or variances among the dose levels 55 It seems appropriate to model the data 56 57 The p-value for Test 2 is greater than .1. A homogeneous variance 58 model appears to be appropriate here 59 60 61 The p-value for Test 3 is greater than .1. The modeled variance appears 62 to be appropriate here 63 64 The p-value for Test 4 is greater than .1. The model chosen seems 65 to adequately describe the data 66 67 68 Benchmark Dose Computation 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-38 Specified effect = 1 1 2 Risk Type = Estimated standard deviations from the control mean 3 4 Confidence level = 0.95 5 6 BMD = 6426.26 7 8 9 BMDL = 4028.71 10 11 12 13 

## E.2.4.4. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 14

10 20 30 40 50 60 70 80 90 100

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

13:41 11/16 2009 BMD BMDL Power

15 16 17 

## E.2.4.5. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 18
19 20

==================================================================== 21 Power Model. (Version: 2.15; Date: 04/07/2008) 22 Input Data File: C:\USEPA\BMDS21\AD\Blood\PwrCV_Unrest_BMR1_50_s_p_f.(d) 23 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\PwrCV_Unrest_BMR1_50_s_p_f.plt 24 Mon Nov 16 13:41:04 2009 25

==================================================================== 26 27 Rel Male Thymus wt, Tbl 2 28

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 30 The form of the response function is: 31 32 Y[dose] = control + slope * dose^power 33 34 35 Dependent variable = Mean 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-39 Independent variable = Dose 1 rho is set to 0 2 The power is not restricted 3 A constant variance model is fit 4 5 Total number of dose groups = 3 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 12 13 Default Initial Parameter Values 14 alpha = 764.602 15 rho = 0 Specified 16 control = 72.7273 17 slope = -3.04504 18 power = 0.282321 19 20 21 Asymptotic Correlation Matrix of Parameter Estimates 22 23 ( *** The model parameter(s) -rho 24 have been estimated at a boundary point, or have been specified by the user, 25 and do not appear in the correlation matrix ) 26 27 alpha control slope power 28 29 alpha 1 -2.2e-008 3.9e-009 1.5e-009 30 31 control -2.2e-008 1 -0.3 -0.22 32 33 slope 3.9e-009 -0.3 1 0.99 34 35 power 1.5e-009 -0.22 0.99 1 36 37 38 39 Parameter Estimates 40 41 95.0% Wald Confidence Interval 42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 43 alpha 688.142 177.677 339.9 1036.38 44 control 72.7273 8.29543 56.4686 88.986 45 slope -3.04504 8.78405 -20.2615 14.1714 46 power 0.282321 0.326249 -0.357114 0.921757 47 48 49 50 Table of Data and Estimated Values of Interest 51 52 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 53

------ --- -------- -------- ----------- ----------- ---------- 54 55 0 10 72.7 72.7 24.6 26.2 8.48e-008 56 2670 10 44.5 44.5 32.9 26.2 -1.25e-008 57 8341 10 33.8 33.8 24.6 26.2 -3.93e-008 58 59 Degrees of freedom for Test A3 vs fitted <= 0 60 61 62 63 Model Descriptions for likelihoods calculated 64 65 66 Model A1: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma^2 68 69 Model A2: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-40 Var{e(ij)} = Sigma(i)^2 1 2 Model A3: Yij = Mu(i) + e(ij) 3 Var{e(ij)} = Sigma^2 4 Model A3 uses any fixed variance parameters that 5 were specified by the user 6 7 Model R: Yi = Mu + e(i) 8 Var{e(i)} = Sigma^2 9 10 11 Likelihoods of Interest 12 13 Model Log(likelihood) # Param's AIC 14 A1 -113.009921 4 234.019841 15 A2 -112.428886 6 236.857773 16 A3 -113.009921 4 234.019841 17 fitted -113.009921 4 234.019841 18 R -117.976057 2 239.952114 19 20 21 Explanation of Tests 22 23 Test 1: Do responses and/or variances differ among Dose levels? 24 (A2 vs. R) 25 Test 2: Are Variances Homogeneous? (A1 vs A2) 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 27 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 28 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 29 30 Tests of Interest 31 32 Test -2*log(Likelihood Ratio) Test df p-value 33 34 Test 1 11.0943 4 0.02552 35 Test 2 1.16207 2 0.5593 36 Test 3 1.16207 2 0.5593 37 Test 4 0 0 NA 38 39 The p-value for Test 1 is less than .05. There appears to be a 40 difference between response and/or variances among the dose levels 41 It seems appropriate to model the data 42 43 The p-value for Test 2 is greater than .1. A homogeneous variance 44 model appears to be appropriate here 45 46 47 The p-value for Test 3 is greater than .1. The modeled variance appears 48 to be appropriate here 49 50 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 51 test for fit is not valid 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 1 57 58 Risk Type = Estimated standard deviations from the control mean 59 60 Confidence level = 0.95 61 62 BMD = 2054.47 63 64 65 BMDL = 1.26421e-005 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-41 1 

## E.2.5. Bell et al. (2007): Balano-Preputial Separa tion in Male Pu ps (10% extra risk) 2 

## E.2.5.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 p-Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 2 0.69 0.71 112.07 2.5E+03 1.7E+03 power restricted ≥ 1, bound hit
logistic 2 2.10 0.35 113.86 5.3E+03 4.1E+03

log-logistic b 2 0.47 0.79 111.88 2.0E+03 1.2E+03 slope restricted ≥ 1, bound hit
log-logistic c 1 0.44 0.51 113.86 1806 264.4 slope unrestricted

log-probit 1 0.54 0.46 113.96 1.8E+03 3.1E+02 slope restricted ≥ 1
multistage, 1- degree 2 0.69 0.71 112.07 2.5E+03 1.7E+03 betas restricted ≥ 0, bound hit
probit 2 1.96 0.38 113.65 5.0E+03 3.8E+03

Weibull 2 0.69 0.71 112.07 2.5E+03 1.7E+03 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix
4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-42 E.2.5.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:35 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.5.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_BMR2_BPS_d49.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_BMR2_BPS_d49.plt 11 Sun Nov 29 11:35:46 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is restricted as slope >= 1 25 26 Total number of observations = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-43 Default Initial Parameter Values 1 background = 0.0333333 2 intercept = -9.77382 3 slope = 1 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -slope 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 background intercept 13 14 background 1 -0.48 15 16 intercept -0.48 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 background 0.0371259 * * * 25 intercept -9.77952 * * * 26 slope 1 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -53.7077 4 36 Fitted model -53.9377 2 0.460052 2 0.7945 37 Reduced model -63.9797 1 20.544 3 0.0001309 38 39 AIC: 111.875 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0371 1.114 1.000 30 -0.110 47 1997.8780 0.1349 4.048 5.000 30 0.509 48 4539.2839 0.2339 7.018 6.000 30 -0.439 49 15952.0000 0.4940 14.820 15.000 30 0.066 50 51 Chi^2 = 0.47 d.f. = 2 P-value = 0.7914 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.1 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 1963.13 63 64 BMDL = 1223.41 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-44 E.2.5.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:35 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.5.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_Unrest_BMR2_BPS_d49.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_Unrest_BMR2_BPS_d49.plt 11 Sun Nov 29 11:35:48 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is not restricted 25 26 Total number of observations = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-45 Default Initial Parameter Values 1 background = 0.0333333 2 intercept = -8.67441 3 slope = 0.877628 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 background intercept slope 9 10 background 1 -0.38 0.34 11 12 intercept -0.38 1 -1 13 14 slope 0.34 -1 1 15 16 17 18 Parameter Estimates 19 20 95.0% Wald Confidence Interval 21 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22 background 0.0352883 * * * 23 intercept -9.31114 * * * 24 slope 0.948644 * * * 25 26 * - Indicates that this value is not calculated. 27 28 29 30 Analysis of Deviance Table 31 32 Model Log(likelihood) # Param's Deviance Test d.f. P-value 33 Full model -53.7077 4 34 Fitted model -53.928 3 0.440703 1 0.5068 35 Reduced model -63.9797 1 20.544 3 0.0001309 36 37 AIC: 113.856 38 39 40 Goodness of Fit 41 Scaled 42 Dose Est._Prob. Expected Observed Size Residual 43

------------------------------------------------------------------------ 44 0.0000 0.0353 1.059 1.000 30 -0.058 45 1997.8780 0.1404 4.212 5.000 30 0.414 46 4539.2839 0.2382 7.145 6.000 30 -0.491 47 15952.0000 0.4861 14.584 15.000 30 0.152 48 49 Chi^2 = 0.44 d.f. = 1 P-value = 0.5076 50 51 52 Benchmark Dose Computation 53 54 Specified effect = 0.1 55 56 Risk Type = Extra risk 57 58 Confidence level = 0.95 59 60 BMD = 1806.29 61 62 BMDL = 264.35 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-46 E.2.6. Bell et al. (2007): Balano-Preputial Separa tion in Male Pu ps (5% extra risk) 1 

## E.2.6.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 pValue a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 2 0.69 0.71 112.07 1.2E+03 8.2E+02 power restricted ≥ 1, bound hit
logistic 2 2.10 0.35 113.86 3.0E+03 2.3E+03

log-logistic b 2 0.47 0.79 111.88 9.3E+02 5.8E+02 slope restricted ≥ 1, bound hit
log-logistic c 1 0.44 0.51 113.86 8.2E+02 4.5E+01 slope unrestricted

log-probit 1 0.54 0.46 113.96 9.5E+02 7.2E+01 slope restricted ≥ 1
multistage, 1- degree 2 0.69 0.71 112.07 1.2E+03 8.2E+02 betas restricted ≥ 0, bound hit
probit 2 1.96 0.38 113.65 2.8E+03 2.1E+03

Weibull 2 0.69 0.71 112.07 1.2E+03 8.2E+02 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-47 E.2.6.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:35 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.6.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_BMR1_BPS_d49.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_BMR1_BPS_d49.plt 11 Sun Nov 29 11:35:45 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is restricted as slope >= 1 25 26 Total number of observations = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-48 Default Initial Parameter Values 1 background = 0.0333333 2 intercept = -9.77382 3 slope = 1 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -slope 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 background intercept 13 14 background 1 -0.48 15 16 intercept -0.48 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 background 0.0371259 * * * 25 intercept -9.77952 * * * 26 slope 1 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -53.7077 4 36 Fitted model -53.9377 2 0.460052 2 0.7945 37 Reduced model -63.9797 1 20.544 3 0.0001309 38 39 AIC: 111.875 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0371 1.114 1.000 30 -0.110 47 1997.8780 0.1349 4.048 5.000 30 0.509 48 4539.2839 0.2339 7.018 6.000 30 -0.439 49 15952.0000 0.4940 14.820 15.000 30 0.066 50 51 Chi^2 = 0.47 d.f. = 2 P-value = 0.7914 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.05 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 929.901 63 64 BMDL = 579.512 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-49 E.2.6.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:35 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.6.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_Unrest_BMR1_BPS_d49.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_Unrest_BMR1_BPS_d49.plt 11 Sun Nov 29 11:35:47 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is not restricted 25 26 Total number of observations = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-50 Default Initial Parameter Values 1 background = 0.0333333 2 intercept = -8.67441 3 slope = 0.877628 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 background intercept slope 9 10 background 1 -0.38 0.34 11 12 intercept -0.38 1 -1 13 14 slope 0.34 -1 1 15 16 17 18 Parameter Estimates 19 20 95.0% Wald Confidence Interval 21 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22 background 0.0352883 * * * 23 intercept -9.31114 * * * 24 slope 0.948644 * * * 25 26 * - Indicates that this value is not calculated. 27 28 29 30 Analysis of Deviance Table 31 32 Model Log(likelihood) # Param's Deviance Test d.f. P-value 33 Full model -53.7077 4 34 Fitted model -53.928 3 0.440703 1 0.5068 35 Reduced model -63.9797 1 20.544 3 0.0001309 36 37 AIC: 113.856 38 39 40 Goodness of Fit 41 Scaled 42 Dose Est._Prob. Expected Observed Size Residual 43

------------------------------------------------------------------------ 44 0.0000 0.0353 1.059 1.000 30 -0.058 45 1997.8780 0.1404 4.212 5.000 30 0.414 46 4539.2839 0.2382 7.145 6.000 30 -0.491 47 15952.0000 0.4861 14.584 15.000 30 0.152 48 49 Chi^2 = 0.44 d.f. = 1 P-value = 0.5076 50 51 52 Benchmark Dose Computation 53 54 Specified effect = 0.05 55 56 Risk Type = Extra risk 57 58 Confidence level = 0.95 59 60 BMD = 821.69 61 62 BMDL = 45.4953 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-51 E.2.7. Cantoni et al. (1981): Urinary Copro-Porhyrins 1 

## E.2.7.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.00 11.91 0.00 32.88 1.8E+04 8.6E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.00 11.91 0.00 32.88 1.8E+04 8.6E+03 nonconstant variance, power restricted ≥ 1
exponential (M4)

c 1 0.00 0.48 0.49 23.46 2.9E+02 9.9E+01 nonconstant variance, power restricted ≥ 1 exponential (M5) 1 0.00 0.48 0.49 23.46 2.9E+02 9.9E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) d 1 0.00 0.48 0.49 23.46 2.9E+02 9.9E+01 nonconstant variance, power unrestricted

Hill 1 0.00 0.07 0.79 23.05 2.4E+02 error nonconstant variance, n restricted >1, bound hit

Hill d 0 0.00 0.00 NA 24.97 1.4E+02 error nonconstant variance, n unrestricted

linear 2 0.00 10.62 0.00 31.59 8.1E+03 1.5E+03 nonconstant variance

polynomial 2 0.00 10.62 0.00 31.59 8.1E+03 1.5E+03 nonconstant variance

power 2 0.00 10.62 0.00 31.59 8.1E+03 1.5E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 1 0.00 0.26 0.61 23.23 1.5E+01 2.3E-06 nonconstant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 3 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-52 E.2.7.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

-1 0 1 2 3 4 5 6 7

0 5000 10000 15000 20000 25000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:43 11/16 2009 BMD BMDL Exponential

3 4 5 

## E.2.7.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_BMR1_urin_copropor.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 13:43:37 2009 14

==================================================================== 15 16 Figure1-UrinaryCoproporphyrin_3months 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-53 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 4 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 4 16

-------- -------- 17 lnalpha -1.50063 18 rho 2.60979 19 a 0.704303 20 b 0.000109864 21 c 4.47268 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 4 29

-------- ------- 30 lnalpha -1.75303 31 rho 2.63218 32 a 0.76122 33 b 0.000438426 34 c 4.15614 35 d 1 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 4 0.7414 0.3475 43 1018 4 1.807 0.8341 44 4868 4 2.734 1.506 45 2.756e+004 4 3 2.6 46 47 48 Estimated Values of Interest 49 50 Dose Est Mean Est Std Scaled Residual 51

------ ---------- --------- ---------------- 52 0 0.7612 0.2907 -0.1366 53 1018 1.626 0.7892 0.4589 54 4868 2.879 1.674 -0.1742 55 2.756e+004 3.164 1.895 -0.1727 56 57 58 59 Other models for which likelihoods are calculated: 60 61 Model A1: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = Sigma^2 63 64 Model A2: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma(i)^2 66 67 Model A3: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-54 Model R: Yij = Mu + e(i) 1 Var{e(ij)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) DF AIC 7

------- ----------------- ---- ------------ 8 A1 -12.90166 5 35.80333 9 A2 -6.203643 8 28.40729 10 A3 -6.487204 6 24.97441 11 R -15.73713 2 35.47427 12 4 -6.729565 5 23.45913 13 14 15 Additive constant for all log-likelihoods = -14.7. This constant added to the 16 above values gives the log-likelihood including the term that does not 17 depend on the model parameters. 18 19 20 Explanation of Tests 21 22 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 23 Test 2: Are Variances Homogeneous? (A2 vs. A1) 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 25 26 Test 6a: Does Model 4 fit the data? (A3 vs 4) 27 28 29 Tests of Interest 30 31 Test -2*log(Likelihood Ratio) D. F. p-value 32

-------- ------------------------ ------ -------------- 33 Test 1 19.07 6 0.004052 34 Test 2 13.4 3 0.003854 35 Test 3 0.5671 2 0.7531 36 Test 6a 0.4847 1 0.4863 37 38 39 The p-value for Test 1 is less than .05. There appears to be a 40 difference between response and/or variances among the dose 41 levels, it seems appropriate to model the data. 42 43 The p-value for Test 2 is less than .1. A non-homogeneous 44 variance model appears to be appropriate. 45 46 The p-value for Test 3 is greater than .1. The modeled 47 variance appears to be appropriate here. 48 49 The p-value for Test 6a is greater than .1. Model 4 seems 50 to adequately describe the data. 51 52 53 Benchmark Dose Computations: 54 55 Specified Effect = 1.000000 56 57 Risk Type = Estimated standard deviations from control 58 59 Confidence Level = 0.950000 60 61 BMD = 294.122 62 63 BMDL = 99.3366 64 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-55 E.2.7.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 1 

## Unrestricted 2

-1 0 1 2 3 4 5 6 7

0 5000 10000 15000 20000 25000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:43 11/16 2009 BMD BMDL Exponential

3 4 5 

## E.2.7.5. Output file for Unrestricted Model: Exponential (M5), Nonconstant Variance, 6 

## Power Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_Unrest_BMR1_urin_copropor.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 13:43:39 2009 14

==================================================================== 15 16 Figure1-UrinaryCoproporphyrin_3months 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-56 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 4 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 5 16

-------- -------- 17 lnalpha -1.50063 18 rho 2.60979 19 a 0.704303 20 b 0.000109864 21 c 4.47268 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 5 29

-------- ------- 30 lnalpha -1.75303 31 rho 2.63218 32 a 0.76122 33 b 0.000438426 34 c 4.15614 35 d 1 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 4 0.7414 0.3475 43 1018 4 1.807 0.8341 44 4868 4 2.734 1.506 45 2.756e+004 4 3 2.6 46 47 48 Estimated Values of Interest 49 50 Dose Est Mean Est Std Scaled Residual 51

------ ---------- --------- ---------------- 52 0 0.7612 0.2907 -0.1366 53 1018 1.626 0.7892 0.4589 54 4868 2.879 1.674 -0.1742 55 2.756e+004 3.164 1.895 -0.1727 56 57 58 59 Other models for which likelihoods are calculated: 60 61 Model A1: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = Sigma^2 63 64 Model A2: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma(i)^2 66 67 Model A3: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-57 Model R: Yij = Mu + e(i) 1 Var{e(ij)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) DF AIC 7

------- ----------------- ---- ------------ 8 A1 -12.90166 5 35.80333 9 A2 -6.203643 8 28.40729 10 A3 -6.487204 6 24.97441 11 R -15.73713 2 35.47427 12 5 -6.729565 5 23.45913 13 14 15 Additive constant for all log-likelihoods = -14.7. This constant added to the 16 above values gives the log-likelihood including the term that does not 17 depend on the model parameters. 18 19 20 Explanation of Tests 21 22 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 23 Test 2: Are Variances Homogeneous? (A2 vs. A1) 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 25 26 Test 7a: Does Model 5 fit the data? (A3 vs 5) 27 28 29 Tests of Interest 30 31 Test -2*log(Likelihood Ratio) D. F. p-value 32

-------- ------------------------ ------ -------------- 33 Test 1 19.07 6 0.004052 34 Test 2 13.4 3 0.003854 35 Test 3 0.5671 2 0.7531 36 Test 7a 0.4847 1 0.4863 37 38 39 The p-value for Test 1 is less than .05. There appears to be a 40 difference between response and/or variances among the dose 41 levels, it seems appropriate to model the data. 42 43 The p-value for Test 2 is less than .1. A non-homogeneous 44 variance model appears to be appropriate. 45 46 The p-value for Test 3 is greater than .1. The modeled 47 variance appears to be appropriate here. 48 49 The p-value for Test 7a is greater than .1. Model 5 seems 50 to adequately describe the data. 51 52 53 Benchmark Dose Computations: 54 55 Specified Effect = 1.000000 56 57 Risk Type = Estimated standard deviations from control 58 59 Confidence Level = 0.950000 60 61 BMD = 294.122 62 63 BMDL = 99.3366 64 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-58 E.2.7.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 1

-1 0 1 2 3 4 5 6 7

0 5000 10000 15000 20000 25000Mean Response

dose Hill Model

13:43 11/16 2009 BMD Hill

2 3 4 

## E.2.7.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_urin_copropor.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_urin_copropor.plt 11 Mon Nov 16 13:43:40 2009 12

==================================================================== 13 14 Figure1-UrinaryCoproporphyrin_3months 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Power parameter is not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 26 27 Total number of dose groups = 4 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 0.90039 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-59 rho = 0 1 intercept = 0.741372 2 v = 2.25875 3 n = 0.0266478 4 k = 8454.34 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 lalpha rho intercept v n k 10 11 lalpha 1 -0.62 -0.53 -0.013 0.027 -0.0092 12 13 rho -0.62 1 0.43 -0.2 -0.017 -0.051 14 15 intercept -0.53 0.43 1 -0.081 0.032 0.011 16 17 v -0.013 -0.2 -0.081 1 -0.88 0.96 18 19 n 0.027 -0.017 0.032 -0.88 1 -0.92 20 21 k -0.0092 -0.051 0.011 0.96 -0.92 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 lalpha -1.78758 0.616312 -2.99553 -0.579633 30 rho 2.64296 0.750855 1.17131 4.11461 31 intercept 0.759014 0.14058 0.483483 1.03455 32 v 3.18202 2.82949 -2.36368 8.72772 33 n 0.739248 0.896737 -1.01832 2.49682 34 k 3317.45 9482.63 -15268.2 21903.1 35 36 37 38 Table of Data and Estimated Values of Interest 39 40 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 41

------ --- -------- -------- ----------- ----------- ---------- 42 43 0 4 0.741 0.759 0.348 0.284 -0.124 44 1018 4 1.81 1.7 0.834 0.822 0.27 45 4868 4 2.73 2.57 1.51 1.43 0.224 46 2.756e+004 4 3 3.39 2.6 2.05 -0.38 47 48 Warning: Likelihood for fitted model larger than the Likelihood for model A3. 49 50 51 52 Model Descriptions for likelihoods calculated 53 54 55 Model A1: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma^2 57 58 Model A2: Yij = Mu(i) + e(ij) 59 Var{e(ij)} = Sigma(i)^2 60 61 Model A3: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 63 Model A3 uses any fixed variance parameters that 64 were specified by the user 65 66 Model R: Yi = Mu + e(i) 67 Var{e(i)} = Sigma^2 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-60 Likelihoods of Interest 1 2 Model Log(likelihood) # Param's AIC 3 A1 -12.901663 5 35.803325 4 A2 -6.203643 8 28.407287 5 A3 -6.487204 6 24.974409 6 fitted -6.487204 6 24.974409 7 R -15.737135 2 35.474269 8 9 10 Explanation of Tests 11 12 Test 1: Do responses and/or variances differ among Dose levels? 13 (A2 vs. R) 14 Test 2: Are Variances Homogeneous? (A1 vs A2) 15 Test 3: Are variances adequately modeled? (A2 vs. A3) 16 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 17 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 18 19 Tests of Interest 20 21 Test -2*log(Likelihood Ratio) Test df p-value 22 23 Test 1 19.067 6 0.004052 24 Test 2 13.396 3 0.003854 25 Test 3 0.567122 2 0.7531 26 Test 4 -1.9007e-013 0 NA 27 28 The p-value for Test 1 is less than .05. There appears to be a 29 difference between response and/or variances among the dose levels 30 It seems appropriate to model the data 31 32 The p-value for Test 2 is less than .1. A non-homogeneous variance 33 model appears to be appropriate 34 35 The p-value for Test 3 is greater than .1. The modeled variance appears 36 to be appropriate here 37 38 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 39 test for fit is not valid 40 41 42 Benchmark Dose Computation 43 44 Specified effect = 1 45 46 Risk Type = Estimated standard deviations from the control mean 47 48 Confidence level = 0.95 49 50 BMD = 143.414 51 52 53 BMDL computation failed. 54 55 56

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-61 E.2.7.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

-1 0 1 2 3 4 5 6 7

0 5000 10000 15000 20000 25000Mean Response

dose Power Model with 0.95 Confidence Level

13:43 11/16 2009 BMD BMDL Power

2 3 4 

## E.2.7.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_urin_copropor.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Pwr_Unrest_BMR1_urin_copropor.plt 12 Mon Nov 16 13:43:39 2009 13

==================================================================== 14 15 Figure1-UrinaryCoproporphyrin_3months 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 4 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-62 Default Initial Parameter Values 1 lalpha = 0.90039 2 rho = 0 3 control = 0.741372 4 slope = 0.226515 5 power = 0.224935 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho control slope power 11 12 lalpha 1 -0.62 -0.53 -0.03 0.024 13 14 rho -0.62 1 0.43 0.052 -0.16 15 16 control -0.53 0.43 1 -0.15 0.086 17 18 slope -0.03 0.052 -0.15 1 -0.98 19 20 power 0.024 -0.16 0.086 -0.98 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha -1.78125 0.617808 -2.99213 -0.570369 29 rho 2.64332 0.744947 1.18325 4.10339 30 control 0.75678 0.139979 0.482426 1.03113 31 slope 0.123953 0.145639 -0.161493 0.4094 32 power 0.304254 0.135074 0.0395142 0.568993 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 4 0.741 0.757 0.348 0.284 -0.109 42 1018 4 1.81 1.78 0.834 0.877 0.0705 43 4868 4 2.73 2.4 1.51 1.3 0.515 44 2.756e+004 4 3 3.54 2.6 2.18 -0.493 45 46 47 48 Model Descriptions for likelihoods calculated 49 50 51 Model A1: Yij = Mu(i) + e(ij) 52 Var{e(ij)} = Sigma^2 53 54 Model A2: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma(i)^2 56 57 Model A3: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 59 Model A3 uses any fixed variance parameters that 60 were specified by the user 61 62 Model R: Yi = Mu + e(i) 63 Var{e(i)} = Sigma^2 64 65 66 Likelihoods of Interest 67 68 Model Log(likelihood) # Param's AIC 69 A1 -12.901663 5 35.803325 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-63 A2 -6.203643 8 28.407287 1 A3 -6.487204 6 24.974409 2 fitted -6.617381 5 23.234762 3 R -15.737135 2 35.474269 4 5 6 Explanation of Tests 7 8 Test 1: Do responses and/or variances differ among Dose levels? 9 (A2 vs. R) 10 Test 2: Are Variances Homogeneous? (A1 vs A2) 11 Test 3: Are variances adequately modeled? (A2 vs. A3) 12 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 13 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 14 15 Tests of Interest 16 17 Test -2*log(Likelihood Ratio) Test df p-value 18 19 Test 1 19.067 6 0.004052 20 Test 2 13.396 3 0.003854 21 Test 3 0.567122 2 0.7531 22 Test 4 0.260353 1 0.6099 23 24 The p-value for Test 1 is less than .05. There appears to be a 25 difference between response and/or variances among the dose levels 26 It seems appropriate to model the data 27 28 The p-value for Test 2 is less than .1. A non-homogeneous variance 29 model appears to be appropriate 30 31 The p-value for Test 3 is greater than .1. The modeled variance appears 32 to be appropriate here 33 34 The p-value for Test 4 is greater than .1. The model chosen seems 35 to adequately describe the data 36 37 38 Benchmark Dose Computation 39 40 Specified effect = 1 41 42 Risk Type = Estimated standard deviations from the control mean 43 44 Confidence level = 0.95 45 46 BMD = 15.247 47 48 49 BMDL = 2.31222e-006 50 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-64 1 

## E.2.8. Cantoni et al. (1981): Urinary Porphyrins 2 

## E.2.8.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2)

c 2 <0.0001 16.12 0.00 55.46 2.1E+03 1.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 <0.0001 16.12 0.00 55.46 2.1E+03 1.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 <0.0001 17.85 <0.0001 59.19 1.4E+02 8.0E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 <0.0001 17.74 N/A 61.08 1.6E+02 8.0E+01 nonconstant variance, power restricted ≥ 1

Hill 0 <.0001 18.86 NA 62.20 3.4E+03 1.8E+03 nonconstant variance, n restricted >1

linear 2 <.0001 17.85 0.00 57.19 1.4E+02 8.0E+01 nonconstant variance

polynomial 1 <.0001 16.63 <.0001 57.97 1.9E+02 8.9E+01 nonconstant variance

power 1 <.0001 17.74 <.0001 59.08 1.6E+02 8.0E+01 nonconstant variance, power restricted ≥ 1

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 4 5 6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-65 E.2.8.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

0 50 100 150 200 250 300 350

0 5000 10000 15000 20000 25000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

13:28 11/16 2009 BMD BMDL Exponential

3 4 5 

## E.2.8.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_BMR1_Urinary_porphyrins.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 13:28:56 2009 14

==================================================================== 15 16 Table 1, dose converted to ng per kg per day 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-66 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 4 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 2 16

-------- -------- 17 lnalpha -3.57509 18 rho 2.23456 19 a 2.1565 20 b 3.49686e-008 21 c 91300.7 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 2 29

-------- ------- 30 lnalpha -4.64559 31 rho 3.18357 32 a 2.32146 33 b 2.51372e-009 34 c 838302 35 d 1.04944 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 4 2.27 0.49 43 1018 4 5.55 0.85 44 4868 3 7.62 1.79 45 2.756e+004 3 196.9 63.14 46 47 48 Estimated Values of Interest 49 50 Dose Est Mean Est Std Scaled Residual 51

------ ---------- --------- ---------------- 52 0 3.579 1.262 -2.074 53 1018 4.152 1.445 1.936 54 4868 7.281 2.411 0.2437 55 2.756e+004 199.5 49.25 -0.09069 56 57 58 59 Other models for which likelihoods are calculated: 60 61 Model A1: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = Sigma^2 63 64 Model A2: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma(i)^2 66 67 Model A3: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-67 Model R: Yij = Mu + e(i) 1 Var{e(ij)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) DF AIC 7

------- ----------------- ---- ------------ 8 A1 -51.42175 5 112.8435 9 A2 -15.31211 8 46.62422 10 A3 -15.66963 6 43.33925 11 R -68.75058 2 141.5012 12 2 -23.73172 4 55.46344 13 14 15 Additive constant for all log-likelihoods = -12.87. This constant added to the 16 above values gives the log-likelihood including the term that does not 17 depend on the model parameters. 18 19 20 Explanation of Tests 21 22 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 23 Test 2: Are Variances Homogeneous? (A2 vs. A1) 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 25 Test 4: Does Model 2 fit the data? (A3 vs. 2) 26 27 28 Tests of Interest 29 30 Test -2*log(Likelihood Ratio) D. F. p-value 31

-------- ------------------------ ------ -------------- 32 Test 1 106.9 6 < 0.0001 33 Test 2 72.22 3 < 0.0001 34 Test 3 0.715 2 0.6994 35 Test 4 16.12 2 0.0003153 36 37 38 The p-value for Test 1 is less than .05. There appears to be a 39 difference between response and/or variances among the dose 40 levels, it seems appropriate to model the data. 41 42 The p-value for Test 2 is less than .1. A non-homogeneous 43 variance model appears to be appropriate. 44 45 The p-value for Test 3 is greater than .1. The modeled 46 variance appears to be appropriate here. 47 48 The p-value for Test 4 is less than .1. Model 2 may not adequately 49 describe the data; you may want to consider another model. 50 51 52 Benchmark Dose Computations: 53 54 Specified Effect = 1.000000 55 56 Risk Type = Estimated standard deviations from control 57 58 Confidence Level = 0.950000 59 60 BMD = 2070.13 61 62 BMDL = 1521.05 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-68 E.2.9. Crofton et al. (2005): Serum T4 1 

## E.2.9.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 8 0.76 44.20 <0.0001 516.36 6.3E+04 3.4E+04 constant variance, power restricted ≥ 1
exponential (M3) 8 0.76 44.20 <0.0001 516.36 6.3E+04 3.4E+04 constant variance, power restricted ≥ 1 exponential (M4)

c 7 0.76 2.29 0.94 476.45 2.9E+03 1.7E+03 constant variance, power restricted ≥ 1
exponential (M5) 6 0.76 2.08 0.91 478.23 3.2E+03 1.7E+03 constant variance, power restricted ≥ 1
exponential (M5) d 6 0.76 2.08 0.91 478.23 3.2E+03 1.7E+03 constant variance, power unrestricted

Hill 6 0.76 1.29 0.97 477.45 3.2E+03 1.7E+03 constant variance, n restricted >1

Hill d 6 0.76 1.29 0.97 477.45 3.2E+03 1.7E+03 constant variance, n unrestricted

linear 8 0.76 50.31 <.0001 522.46 1.3E+05 9.7E+04 constant variance

polynomial 8 0.76 50.31 <.0001 522.46 1.3E+05 9.7E+04 constant variance

power 8 0.76 50.31 <.0001 522.46 1.3E+05 9.7E+04 constant variance, power restricted ≥ 1, bound hit

power d 7 0.76 16.95 0.02 491.10 1.4E+03 1.8E+02 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 3 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-69 E.2.9.2. Figure for Selected Model: Exponential (M 4), C onstant Variance, Power Restricted 1 

## ≥ 1 2

20 40 60 80 100 120

0 50000 100000 150000 200000 250000 300000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

15:13 11/16 2009 BMD BMDL Exponential

3 4 5 

## E.2.9.3. Output File for Selected Model: Expo nential (M4), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\ExpConstVar_BMR1_SerumT4.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 15:13:33 2009 14

==================================================================== 15 16 0 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-70 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 rho is set to 0. 3 A constant variance model is fit. 4 5 Total number of dose groups = 10 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 4 17

-------- -------- 18 lnalpha 5.47437 19 rho(S) 0 20 a 104.999 21 b 1.16502e-005 22 c 0.445764 23 d 1 24 25 (S) = Specified 26 27 28 29 Parameter Estimates 30 31 Variable Model 4 32

-------- ------- 33 lnalpha 5.50322 34 rho 0 35 a 99.7846 36 b 0.000149614 37 c 0.533127 38 d 1.19797 39 40 41 Table of Stats From Input Data 42 43 Dose N Obs Mean Obs Std Dev 44

----- --- ---------- ------------- 45 0 14 100 15.44 46 11.15 6 96.27 14.98 47 269.2 12 98.57 18.11 48 763 6 99.76 19.04 49 1905 6 93.32 12.11 50 5104 6 70.94 12.74 51 1.271e+004 6 62.52 14.75 52 3.617e+004 6 52.68 22.73 53 9.965e+004 6 54.66 19.71 54 3.215e+005 4 49.15 11.15 55 56 57 Estimated Values of Interest 58 59 Dose Est Mean Est Std Scaled Residual 60

------ ---------- --------- ---------------- 61 0 100.3 15.69 -0.07977 62 11.15 100.3 15.69 -0.6232 63 269.2 98.58 15.69 -0.0008246 64 763 95.52 15.69 0.6615 65 1905 89.21 15.69 0.6428 66 5104 76.04 15.69 -0.7955 67 1.271e+004 60.7 15.69 0.2839 68 3.617e+004 52.85 15.69 -0.02601 69 9.965e+004 52.53 15.69 0.3323 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-71 3.215e+005 52.53 15.69 -0.432 1 2 3 4 Other models for which likelihoods are calculated: 5 6 Model A1: Yij = Mu(i) + e(ij) 7 Var{e(ij)} = Sigma^2 8 9 Model A2: Yij = Mu(i) + e(ij) 10 Var{e(ij)} = Sigma(i)^2 11 12 Model A3: Yij = Mu(i) + e(ij) 13 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 14 15 Model R: Yij = Mu + e(i) 16 Var{e(ij)} = Sigma^2 17 18 19 Likelihoods of Interest 20 21 Model Log(likelihood) DF AIC 22

------- ----------------- ---- ------------ 23 A1 -233.0774 11 488.1549 24 A2 -230.2028 20 500.4056 25 A3 -233.0774 11 488.1549 26 R -268.4038 2 540.8076 27 4 -234.2238 4 476.4476 28 29 30 Additive constant for all log-likelihoods = -66.16. This constant added to the 31 above values gives the log-likelihood including the term that does not 32 depend on the model parameters. 33 34 35 Explanation of Tests 36 37 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 38 Test 2: Are Variances Homogeneous? (A2 vs. A1) 39 Test 3: Are variances adequately modeled? (A2 vs. A3) 40 41 Test 6a: Does Model 4 fit the data? (A3 vs 4) 42 43 44 Tests of Interest 45 46 Test -2*log(Likelihood Ratio) D. F. p-value 47

-------- ------------------------ ------ -------------- 48 Test 1 76.4 18 < 0.0001 49 Test 2 5.749 9 0.7647 50 Test 3 5.749 9 0.7647 51 Test 6a 2.293 7 0.9419 52 53 54 The p-value for Test 1 is less than .05. There appears to be a 55 difference between response and/or variances among the dose 56 levels, it seems appropriate to model the data. 57 58 The p-value for Test 2 is greater than .1. A homogeneous 59 variance model appears to be appropriate here. 60 61 The p-value for Test 3 is greater than .1. The modeled 62 variance appears to be appropriate here. 63 64 The p-value for Test 6a is greater than .1. Model 4 seems 65 to adequately describe the data. 66 67 68 Benchmark Dose Computations: 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-72 Specified Effect = 1.000000 1 2 Risk Type = Estimated standard deviations from control 3 4 Confidence Level = 0.950000 5 6 BMD = 2860.82 7 8 BMDL = 1670.13 9 10 11 

## E.2.9.4. Figure for Unrestricted Model: Expone ntial (M5), Constant Variance, Power 12 

## Unrestricted 13

20 40 60 80 100 120

0 50000 100000 150000 200000 250000 300000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

15:13 11/16 2009 BMD BMDL Exponential

14 15 16

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-73 E.2.9.5. Output File for Unrestricted Model: E xponential (M5), Constant Varian ce, Power 1 

## Unrestricted 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\AD\Blood\ExpConstVar_Unrest_BMR1_SerumT4.(d) 7 Gnuplot Plotting File: 8 Mon Nov 16 15:13:40 2009 9

==================================================================== 10 11 0 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 rho is set to 0. 34 A constant variance model is fit. 35 36 Total number of dose groups = 10 37 Total number of records with missing values = 0 38 Maximum number of iterations = 250 39 Relative Function Convergence has been set to: 1e-008 40 Parameter Convergence has been set to: 1e-008 41 42 MLE solution provided: Exact 43 44 45 Initial Parameter Values 46 47 Variable Model 5 48

-------- -------- 49 lnalpha 5.47437 50 rho(S) 0 51 a 104.999 52 b 1.16502e-005 53 c 0.445764 54 d 1 55 56 (S) = Specified 57 58 59 60 Parameter Estimates 61 62 Variable Model 5 63

-------- ------- 64 lnalpha 5.50322 65 rho 0 66 a 99.7846 67 b 0.000149614 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-74 c 0.533127 1 d 1.19797 2 3 4 Table of Stats From Input Data 5 6 Dose N Obs Mean Obs Std Dev 7

----- --- ---------- ------------- 8 0 14 100 15.44 9 11.15 6 96.27 14.98 10 269.2 12 98.57 18.11 11 763 6 99.76 19.04 12 1905 6 93.32 12.11 13 5104 6 70.94 12.74 14 1.271e+004 6 62.52 14.75 15 3.617e+004 6 52.68 22.73 16 9.965e+004 6 54.66 19.71 17 3.215e+005 4 49.15 11.15 18 19 20 Estimated Values of Interest 21 22 Dose Est Mean Est Std Scaled Residual 23

------ ---------- --------- ---------------- 24 0 99.78 15.67 0.0512 25 11.15 99.76 15.67 -0.5465 26 269.2 98.8 15.67 -0.05054 27 763 96.45 15.67 0.5173 28 1905 90.5 15.67 0.4419 29 5104 75.78 15.67 -0.7573 30 1.271e+004 58.58 15.67 0.616 31 3.617e+004 53.22 15.67 -0.08476 32 9.965e+004 53.2 15.67 0.2291 33 3.215e+005 53.2 15.67 -0.5174 34 35 36 37 Other models for which likelihoods are calculated: 38 39 Model A1: Yij = Mu(i) + e(ij) 40 Var{e(ij)} = Sigma^2 41 42 Model A2: Yij = Mu(i) + e(ij) 43 Var{e(ij)} = Sigma(i)^2 44 45 Model A3: Yij = Mu(i) + e(ij) 46 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 47 48 Model R: Yij = Mu + e(i) 49 Var{e(ij)} = Sigma^2 50 51 52 Likelihoods of Interest 53 54 Model Log(likelihood) DF AIC 55

------- ----------------- ---- ------------ 56 A1 -233.0774 11 488.1549 57 A2 -230.2028 20 500.4056 58 A3 -233.0774 11 488.1549 59 R -268.4038 2 540.8076 60 5 -234.1158 5 478.2316 61 62 63 Additive constant for all log-likelihoods = -66.16. This constant added to the 64 above values gives the log-likelihood including the term that does not 65 depend on the model parameters. 66 67 68 Explanation of Tests 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-75 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 1 Test 2: Are Variances Homogeneous? (A2 vs. A1) 2 Test 3: Are variances adequately modeled? (A2 vs. A3) 3 4 Test 7a: Does Model 5 fit the data? (A3 vs 5) 5 6 7 Tests of Interest 8 9 Test -2*log(Likelihood Ratio) D. F. p-value 10

-------- ------------------------ ------ -------------- 11 Test 1 76.4 18 < 0.0001 12 Test 2 5.749 9 0.7647 13 Test 3 5.749 9 0.7647 14 Test 7a 2.077 6 0.9125 15 16 17 The p-value for Test 1 is less than .05. There appears to be a 18 difference between response and/or variances among the dose 19 levels, it seems appropriate to model the data. 20 21 The p-value for Test 2 is greater than .1. A homogeneous 22 variance model appears to be appropriate here. 23 24 The p-value for Test 3 is greater than .1. The modeled 25 variance appears to be appropriate here. 26 27 The p-value for Test 7a is greater than .1. Model 5 seems 28 to adequately describe the data. 29 30 31 Benchmark Dose Computations: 32 33 Specified Effect = 1.000000 34 35 Risk Type = Estimated standard deviations from control 36 37 Confidence Level = 0.950000 38 39 BMD = 3175.08 40 41 BMDL = 1706.36 42 43 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-76 E.2.9.6. Figure for Unrestricted Model: Hill , Constant Variance, n Unrestricted 1

20 40 60 80 100 120

0 50000 100000 150000 200000 250000 300000Mean Response

dose Hill Model with 0.95 Confidence Level

15:13 11/16 2009 BMD BMDL Hill

2 3 4 

## E.2.9.7. Output File for Unrestricted Model: Hil l, Consta nt Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\HillConstVar_Unrest_BMR1_SerumT4.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\HillConstVar_Unrest_BMR1_SerumT4.plt 11 Mon Nov 16 15:13:42 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 rho is set to 0 25 Power parameter is not restricted 26 A constant variance model is fit 27 28 Total number of dose groups = 10 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-77 alpha = 276.969 1 rho = 0 Specified 2 intercept = 99.999 3 v = -50.854 4 n = 1.5549 5 k = 4585.23 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 ( *** The model parameter(s) -rho 11 have been estimated at a boundary point, or have been specified by the user, 12 and do not appear in the correlation matrix ) 13 14 alpha intercept v n k 15 16 alpha 1 1.9e-009 -2e-008 -1.1e-008 1.1e-008 17 18 intercept 1.9e-009 1 -0.58 -0.3 -0.2 19 20 v -2e-008 -0.58 1 0.6 -0.36 21 22 n -1.1e-008 -0.3 0.6 1 -0.34 23 24 k 1.1e-008 -0.2 -0.36 -0.34 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 alpha 242.825 40.4708 163.504 322.146 33 intercept 99.3375 2.66145 94.1212 104.554 34 v -46.4797 5.51009 -57.2793 -35.6801 35 n 1.85655 0.927361 0.0389606 3.67415 36 k 4564.01 1406.15 1808 7320.02 37 38 39 40 Table of Data and Estimated Values of Interest 41 42 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 43

------ --- -------- -------- ----------- ----------- ---------- 44 45 0 14 100 99.3 15.4 15.6 0.159 46 11.15 6 96.3 99.3 15 15.6 -0.483 47 269.2 12 98.6 99.1 18.1 15.6 -0.116 48 763 6 99.8 97.7 19 15.6 0.321 49 1905 6 93.3 91.7 12.1 15.6 0.26 50 5104 6 70.9 73.7 12.7 15.6 -0.433 51 1.271e+004 6 62.5 58.9 14.8 15.6 0.568 52 3.617e+004 6 52.7 53.8 22.7 15.6 -0.181 53 9.965e+004 6 54.7 53 19.7 15.6 0.26 54 3.215e+005 4 49.1 52.9 11.1 15.6 -0.479 55 56 57 58 Model Descriptions for likelihoods calculated 59 60 61 Model A1: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = Sigma^2 63 64 Model A2: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma(i)^2 66 67 Model A3: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma^2 69 Model A3 uses any fixed variance parameters that 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-78 were specified by the user 1 2 Model R: Yi = Mu + e(i) 3 Var{e(i)} = Sigma^2 4 5 6 Likelihoods of Interest 7 8 Model Log(likelihood) # Param's AIC 9 A1 -233.077445 11 488.154889 10 A2 -230.202783 20 500.405566 11 A3 -233.077445 11 488.154889 12 fitted -233.724271 5 477.448543 13 R -268.403817 2 540.807634 14 15 16 Explanation of Tests 17 18 Test 1: Do responses and/or variances differ among Dose levels? 19 (A2 vs. R) 20 Test 2: Are Variances Homogeneous? (A1 vs A2) 21 Test 3: Are variances adequately modeled? (A2 vs. A3) 22 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 23 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 24 25 Tests of Interest 26 27 Test -2*log(Likelihood Ratio) Test df p-value 28 29 Test 1 76.4021 18 <.0001 30 Test 2 5.74932 9 0.7647 31 Test 3 5.74932 9 0.7647 32 Test 4 1.29365 6 0.972 33 34 The p-value for Test 1 is less than .05. There appears to be a 35 difference between response and/or variances among the dose levels 36 It seems appropriate to model the data 37 38 The p-value for Test 2 is greater than .1. A homogeneous variance 39 model appears to be appropriate here 40 41 42 The p-value for Test 3 is greater than .1. The modeled variance appears 43 to be appropriate here 44 45 The p-value for Test 4 is greater than .1. The model chosen seems 46 to adequately describe the data 47 48 49 Benchmark Dose Computation 50 51 Specified effect = 1 52 53 Risk Type = Estimated standard deviations from the control mean 54 55 Confidence level = 0.95 56 57 BMD = 3156.67 58 59 BMDL = 1668.07 60 61 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-79 E.2.9.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

20 40 60 80 100 120

0 50000 100000 150000 200000 250000 300000Mean Response

dose Power Model with 0.95 Confidence Level

15:13 11/16 2009 BMD BMDL Power

2 3 4 

## E.2.9.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5
6 7

==================================================================== 8 Power Model. (Version: 2.15; Date: 04/07/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\PowerConstVar_Unrest_BMR1_SerumT4.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\PowerConstVar_Unrest_BMR1_SerumT4.plt 11 Mon Nov 16 15:13:43 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = control + slope * dose^power 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 rho is set to 0 25 The power is not restricted 26 A constant variance model is fit 27 28 Total number of dose groups = 10 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-80 alpha = 276.969 1 rho = 0 Specified 2 control = 99.999 3 slope = -0.28302 4 power = 0.42875 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha control slope power 14 15 alpha 1 3e-010 -1.9e-010 -1.9e-010 16 17 control 3e-010 1 -0.73 -0.62 18 19 slope -1.9e-010 -0.73 1 0.98 20 21 power -1.9e-010 -0.62 0.98 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 301.804 50.3007 203.217 400.392 30 control 103.499 3.94867 95.76 111.239 31 slope -3.01678 1.68354 -6.31645 0.282886 32 power 0.242881 0.0442912 0.156071 0.32969 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 14 100 103 15.4 17.4 -0.754 42 11.15 6 96.3 98.1 15 17.4 -0.256 43 269.2 12 98.6 91.8 18.1 17.4 1.36 44 763 6 99.8 88.4 19 17.4 1.6 45 1905 6 93.3 84.6 12.1 17.4 1.23 46 5104 6 70.9 79.5 12.7 17.4 -1.21 47 1.271e+004 6 62.5 73.6 14.8 17.4 -1.56 48 3.617e+004 6 52.7 64.9 22.7 17.4 -1.72 49 9.965e+004 6 54.7 54.1 19.7 17.4 0.077 50 3.215e+005 4 49.1 37.9 11.1 17.4 1.3 51 52 53 54 Model Descriptions for likelihoods calculated 55 56 57 Model A1: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma^2 59 60 Model A2: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma(i)^2 62 63 Model A3: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma^2 65 Model A3 uses any fixed variance parameters that 66 were specified by the user 67 68 Model R: Yi = Mu + e(i) 69 Var{e(i)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-81 1 2 Likelihoods of Interest 3 4 Model Log(likelihood) # Param's AIC 5 A1 -233.077445 11 488.154889 6 A2 -230.202783 20 500.405566 7 A3 -233.077445 11 488.154889 8 fitted -241.552045 4 491.104090 9 R -268.403817 2 540.807634 10 11 12 Explanation of Tests 13 14 Test 1: Do responses and/or variances differ among Dose levels? 15 (A2 vs. R) 16 Test 2: Are Variances Homogeneous? (A1 vs A2) 17 Test 3: Are variances adequately modeled? (A2 vs. A3) 18 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 19 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 20 21 Tests of Interest 22 23 Test -2*log(Likelihood Ratio) Test df p-value 24 25 Test 1 76.4021 18 <.0001 26 Test 2 5.74932 9 0.7647 27 Test 3 5.74932 9 0.7647 28 Test 4 16.9492 7 0.01773 29 30 The p-value for Test 1 is less than .05. There appears to be a 31 difference between response and/or variances among the dose levels 32 It seems appropriate to model the data 33 34 The p-value for Test 2 is greater than .1. A homogeneous variance 35 model appears to be appropriate here 36 37 38 The p-value for Test 3 is greater than .1. The modeled variance appears 39 to be appropriate here 40 41 The p-value for Test 4 is less than .1. You may want to try a different 42 model 43 44 45 Benchmark Dose Computation 46 47 Specified effect = 1 48 49 Risk Type = Estimated standard deviations from the control mean 50 51 Confidence level = 0.95 52 53 BMD = 1350.28 54 55 56 BMDL = 182.329 57 58 59

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-82 1 

## E.2.10. Hojo et al. (2002): DRL Reinforce Per Min 2 

## E.2.10.1. Summary Table of BMDS Modeling Results 3

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

Hill 0 NA 6.465 1.320E+03 4.017E-04

linear 2 0.009 9.126 1.070E+04 4.762E+03

polynomial 2 0.009 9.126 1.070E+04 4.762E+03

power 2 0.009 9.126 1.070E+04 4.762E+03 power bound hit

exponential (M2) 2 0.007 9.614 1.284E+04 6.859E+03

exponential (M3) 1 0.001 12.870 2.720E+08 1.522E+05

exponential (M4) c 1 0.054 5.490 1.041E+03 4.944E+00

exponential (M5) 0 N/A 6.465 1.367E+03 1.245E+01

a Constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix 4 5 6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-83 E.2.10.2. Figure for Selected Model: Exponental (M4) 1

2

-0.5 0 0.5

1 1.5

2

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

10:23 01/12 2010 BMD BMDL Exponential

3 

## Hojo et al., 2002: DRL reinforce per min 4 5 6 

## E.2.10.3. Output File for Selected Model: Exponential (M4) 7 

## Hojo et al., 2002: DRL reinforce per min 8

==================================================================== 9 Exponential Model. (Version: 1.61; Date: 7/24/2009) 10 Input Data File: C:\1\Blood\21_Hojo_2002_DRL_rein_min_exp_ExpCV_1.(d) 11 Gnuplot Plotting File: 12 Tue Jan 12 10:23:58 2010 13

==================================================================== 14 15 Table 5, values adjusted by a constant to allow exponential model 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function by Model: 19 Model 2: Y[dose] = a * exp{sign * b * dose} 20 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 21 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 22 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 23 24 Note: Y[dose] is the median response for exposure = dose; 25 sign = +1 for increasing trend in data; 26 sign = -1 for decreasing trend. 27 28 Model 2 is nested within Models 3 and 4. 29 Model 3 is nested within Model 5. 30 Model 4 is nested within Model 5. 31 32 33 Dependent variable = Mean 34 Independent variable = Dose 35 Data are assumed to be distributed: normally 36 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 37 rho is set to 0. 38 A constant variance model is fit. 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-84 1 Total number of dose groups = 4 2 Total number of records with missing values = 0 3 Maximum number of iterations = 250 4 Relative Function Convergence has been set to: 1e-008 5 Parameter Convergence has been set to: 1e-008 6 7 MLE solution provided: Exact 8 9 10 Initial Parameter Values 11 12 Variable Model 4 13

-------- -------- 14 lnalpha -1.29672 15 rho(S) 0 16 a 0.0817 17 b 0.000197777 18 c 16.3733 19 d 1 20 21 (S) = Specified 22 23 24 25 Parameter Estimates 26 27 Variable Model 4 28

-------- ------- 29 lnalpha -1.11954 30 rho 0 31 a 0.054752 32 b 0.000895762 33 c 18.2107 34 d 1 35 36 37 Table of Stats From Input Data 38 39 Dose N Obs Mean Obs Std Dev 40

----- --- ---------- ------------- 41 0 5 0.086 0.448 42 1285 5 0.536 0.821 43 3295 6 1.274 0.54 44 8465 5 0.737 0.443 45 46 47 Estimated Values of Interest 48 49 Dose Est Mean Est Std Scaled Residual 50

------ ---------- --------- ---------------- 51 0 0.05475 0.5713 0.1223 52 1285 0.6991 0.5713 -0.6381 53 3295 0.9478 0.5713 1.398 54 8465 0.9966 0.5713 -1.016 55 56 57 58 Other models for which likelihoods are calculated: 59 60 Model A1: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 63 Model A2: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma(i)^2 65 66 Model A3: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 68 69 Model R: Yij = Mu + e(i) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-85 Var{e(ij)} = Sigma^2 1 2 3 Likelihoods of Interest 4 5 Model Log(likelihood) DF AIC 6

------- ----------------- ---- ------------ 7 A1 3.11555 5 3.7689 8 A2 4.489557 8 7.020886 9 A3 3.11555 5 3.7689 10 R -2.435087 2 8.870174 11 4 1.255168 4 5.489665 12 13 14 Additive constant for all log-likelihoods = -19.3. This constant added to the 15 above values gives the log-likelihood including the term that does not 16 depend on the model parameters. 17 18 19 Explanation of Tests 20 21 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 22 Test 2: Are Variances Homogeneous? (A2 vs. A1) 23 Test 3: Are variances adequately modeled? (A2 vs. A3) 24 25 Test 6a: Does Model 4 fit the data? (A3 vs 4) 26 27 28 Tests of Interest 29 30 Test -2*log(Likelihood Ratio) D. F. p-value 31

-------- ------------------------ ------ -------------- 32 Test 1 13.85 6 0.03137 33 Test 2 2.748 3 0.4321 34 Test 3 2.748 3 0.4321 35 Test 6a 3.721 1 0.05374 36 37 38 The p-value for Test 1 is less than .05. There appears to be a 39 difference between response and/or variances among the dose 40 levels, it seems appropriate to model the data. 41 42 The p-value for Test 2 is greater than .1. A homogeneous 43 variance model appears to be appropriate here. 44 45 The p-value for Test 3 is greater than .1. The modeled 46 variance appears to be appropriate here. 47 48 The p-value for Test 6a is less than .1. Model 4 may not adequately 49 describe the data; you may want to consider another model. 50 51 52 Benchmark Dose Computations: 53 54 Specified Effect = 1.000000 55 56 Risk Type = Estimated standard deviations from control 57 58 Confidence Level = 0.950000 59 60 BMD = 1040.67 61 62 BMDL = 4.94408 63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-86 1 

## E.2.11. Hojo et al. (2002): DRL Response Per Min 2 

## E.2.11.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.30 1.13 0.57 122.98 1.1E+03 error constant variance, power restricted ≥ 1
exponential (M3) 2 0.30 1.13 0.57 122.98 1.1E+03 error constant variance, power restricted ≥ 1 exponential (M4)

c 1 0.30 0.50 0.48 124.36 8.4E+02 5.6E+01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.30 0.50 N/A 126.35 2.0E+03 4.9E+01 constant variance, power restricted ≥ 1

Hill 0 0.30 0.50 NA 126.35 2.9E+03 3.2E-11 constant variance, n restricted >1

linear 2 0.30 11.00 0.00 132.86 3.7E+04 1.7E+04 constant variance

polynomial 2 0.30 11.00 0.00 132.86 3.7E+04 1.7E+04 constant variance

power 2 0.30 11.00 0.00 132.86 3.7E+04 1.7E+04 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presented in this appendix 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-87 E.2.11.2. Figure for Selected Model: Exponential (M4) 1

-10 0 10 20 30

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

10:25 01/12 2010 BMD BMDL Exponential

2 3 

## Hojo et al., 2002: DRL response per min 4 5 6 

## E.2.11.3. Output File for Selected Model: Exponential (M4) 7 

## Hojo et al., 2002: DRL response per min 8 9

==================================================================== 10 Exponential Model. (Version: 1.61; Date: 7/24/2009) 11 Input Data File: C:\1\Blood\23_Hojo_2002_DRL_resp_min_exp_ExpCV_1.(d) 12 Gnuplot Plotting File: 13 Tue Jan 12 10:25:21 2010 14

==================================================================== 15 16 Table 5, values adjusted by a constant to allow exponential model 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36 Data are assumed to be distributed: normally 37 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 38 rho is set to 0. 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-88 A constant variance model is fit. 1 2 Total number of dose groups = 4 3 Total number of records with missing values = 0 4 Maximum number of iterations = 250 5 Relative Function Convergence has been set to: 1e-008 6 Parameter Convergence has been set to: 1e-008 7 8 MLE solution provided: Exact 9 10 11 Initial Parameter Values 12 13 Variable Model 4 14

-------- -------- 15 lnalpha 4.51689 16 rho(S) 0 17 a 24.6362 18 b 0.00047963 19 c 0.0184785 20 d 1 21 22 (S) = Specified 23 24 25 26 Parameter Estimates 27 28 Variable Model 4 29

-------- ------- 30 lnalpha 4.54096 31 rho 0 32 a 23.4674 33 b 0.00203802 34 c 0.101322 35 d 1 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 5 23.46 7.986 43 1285 5 4.013 10.96 44 3295 6 0.478 7.194 45 8465 5 4.594 15.23 46 47 48 Estimated Values of Interest 49 50 Dose Est Mean Est Std Scaled Residual 51

------ ---------- --------- ---------------- 52 0 23.47 9.684 -0.001011 53 1285 3.914 9.684 0.02275 54 3295 2.403 9.684 -0.487 55 8465 2.378 9.684 0.5117 56 57 58 59 Other models for which likelihoods are calculated: 60 61 Model A1: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = Sigma^2 63 64 Model A2: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma(i)^2 66 67 Model A3: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-89 Model R: Yij = Mu + e(i) 1 Var{e(ij)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) DF AIC 7

------- ----------------- ---- ------------ 8 A1 -57.92733 5 125.8547 9 A2 -56.09669 8 128.1934 10 A3 -57.92733 5 125.8547 11 R -64.49611 2 132.9922 12 4 -58.18012 4 124.3602 13 14 15 Additive constant for all log-likelihoods = -19.3. This constant added to the 16 above values gives the log-likelihood including the term that does not 17 depend on the model parameters. 18 19 20 Explanation of Tests 21 22 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 23 Test 2: Are Variances Homogeneous? (A2 vs. A1) 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 25 26 Test 6a: Does Model 4 fit the data? (A3 vs 4) 27 28 29 Tests of Interest 30 31 Test -2*log(Likelihood Ratio) D. F. p-value 32

-------- ------------------------ ------ -------------- 33 Test 1 16.8 6 0.01005 34 Test 2 3.661 3 0.3004 35 Test 3 3.661 3 0.3004 36 Test 6a 0.5056 1 0.4771 37 38 39 The p-value for Test 1 is less than .05. There appears to be a 40 difference between response and/or variances among the dose 41 levels, it seems appropriate to model the data. 42 43 The p-value for Test 2 is greater than .1. A homogeneous 44 variance model appears to be appropriate here. 45 46 The p-value for Test 3 is greater than .1. The modeled 47 variance appears to be appropriate here. 48 49 The p-value for Test 6a is greater than .1. Model 4 seems 50 to adequately describe the data. 51 52 53 Benchmark Dose Computations: 54 55 Specified Effect = 1.000000 56 57 Risk Type = Estimated standard deviations from control 58 59 Confidence Level = 0.950000 60 61 BMD = 301.607 62 63 BMDL = 7.54952 64

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-90 E.2.12. Kattainen et al. (2001): 3 rd 

## Molar Mesio-Distal Length (Molar Development) 1 

## E.2.12.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 <0.0001 38.96 <0.0001 - 122.90 6.4E+04 3.8E+04 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 38.96 <0.0001 - 122.90 6.4E+04 3.8E+04 nonconstant variance, power restricted ≥ 1
exponential (M4) 2 <0.0001 79.12 <0.0001 -80.75 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 13.81 0.00 - 146.06 8.5E+02 5.1E+02 nonconstant variance, power restricted ≥ 1

Hill c 2 <.0001 8.72 0.01 - 151.15 6.3E+02 3.4E+02 nonconstant variance, n restricted >1, bound hit

Hill d 1 <.0001 2.92 0.09 - 154.95 3.0E+00 2.9E-02 nonconstant variance, n unrestricted

linear 3 <.0001 39.59 <.0001 - 122.28 7.4E+04 4.7E+04 nonconstant variance

polynomial 2 <.0001 36.61 <.0001 - 123.26 3.0E+04 1.4E+04 nonconstant variance

power 3 <.0001 39.59 <.0001 - 122.28 7.4E+04 4.7E+04 nonconstant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-91 E.2.12.2. Figure for Selected Model: Hill, Noncon stant Variance, n Restricted >1, Bound Hit 1

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

0 20000 40000 60000 80000 100000 120000 140000 160000Mean Response

dose Hill Model with 0.95 Confidence Level

13:14 11/16 2009 BMD BMDL Hill

2 3 4 

## E.2.12.3. Output File for Selected Model: Hill, No nconstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_BMR1_3rd_molar.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_BMR1_3rd_molar.plt 12 Mon Nov 16 13:14:09 2009 13

==================================================================== 14 15 Figure 3 female only 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter restricted to be greater than 1 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-92 Default Initial Parameter Values 1 lalpha = -2.37155 2 rho = 0 3 intercept = 1.85591 4 v = -0.507874 5 n = 0.825979 6 k = 4284.51 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -n 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 lalpha rho intercept v k 16 17 lalpha 1 -0.98 -0.16 0.84 -0.37 18 19 rho -0.98 1 0.2 -0.79 0.39 20 21 intercept -0.16 0.2 1 -0.31 -0.11 22 23 v 0.84 -0.79 -0.31 1 -0.48 24 25 k -0.37 0.39 -0.11 -0.48 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence Interval 32 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 33 lalpha 3.34591 1.40451 0.593124 6.0987 34 rho -14.3329 2.62142 -19.4708 -9.19505 35 intercept 1.8548 0.0159016 1.82364 1.88597 36 v -0.441028 0.0588146 -0.556302 -0.325753 37 n 1 NA 38 k 3764.75 1228.49 1356.95 6172.54 39 40 NA - Indicates that this parameter has hit a bound 41 implied by some inequality constraint and thus 42 has no standard error. 43 44 45 46 Table of Data and Estimated Values of Interest 47 48 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 49

------ --- -------- -------- ----------- ----------- ---------- 50 51 0 16 1.86 1.85 0.0661 0.0637 0.0692 52 4703 17 1.58 1.61 0.185 0.176 -0.767 53 1.568e+004 15 1.6 1.5 0.265 0.293 1.28 54 4.725e+004 12 1.5 1.45 0.221 0.378 0.527 55 1.585e+005 19 1.35 1.42 0.515 0.423 -0.783 56 57 58 59 Model Descriptions for likelihoods calculated 60 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-93 Model A3 uses any fixed variance parameters that 1 were specified by the user 2 3 Model R: Yi = Mu + e(i) 4 Var{e(i)} = Sigma^2 5 6 7 Likelihoods of Interest 8 9 Model Log(likelihood) # Param's AIC 10 A1 56.758717 6 -101.517434 11 A2 85.856450 10 -151.712901 12 A3 84.934314 7 -155.868628 13 fitted 80.574735 5 -151.149469 14 R 45.373551 2 -86.747101 15 16 17 Explanation of Tests 18 19 Test 1: Do responses and/or variances differ among Dose levels? 20 (A2 vs. R) 21 Test 2: Are Variances Homogeneous? (A1 vs A2) 22 Test 3: Are variances adequately modeled? (A2 vs. A3) 23 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 24 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 25 26 Tests of Interest 27 28 Test -2*log(Likelihood Ratio) Test df p-value 29 30 Test 1 80.9658 8 <.0001 31 Test 2 58.1955 4 <.0001 32 Test 3 1.84427 3 0.6053 33 Test 4 8.71916 2 0.01278 34 35 The p-value for Test 1 is less than .05. There appears to be a 36 difference between response and/or variances among the dose levels 37 It seems appropriate to model the data 38 39 The p-value for Test 2 is less than .1. A non-homogeneous variance 40 model appears to be appropriate 41 42 The p-value for Test 3 is greater than .1. The modeled variance appears 43 to be appropriate here 44 45 The p-value for Test 4 is less than .1. You may want to try a different 46 model 47 48 49 Benchmark Dose Computation 50 51 Specified effect = 1 52 53 Risk Type = Estimated standard deviations from the control mean 54 55 Confidence level = 0.95 56 57 BMD = 634.985 58 59 BMDL = 335.879 60 61 62 63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-94 E.2.12.4. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 1

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

0 20000 40000 60000 80000 100000 120000 140000 160000Mean Response

dose Hill Model with 0.95 Confidence Level

13:14 11/16 2009 BMDBMDL Hill

2 3 4 

## E.2.12.5. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_3rd_molar.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_3rd_molar.plt 11 Mon Nov 16 13:14:09 2009 12

==================================================================== 13 14 Figure 3 female only 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Power parameter is not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 26 27 Total number of dose groups = 5 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = -2.37155 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-95 rho = 0 1 intercept = 1.85591 2 v = -0.507874 3 n = 0.825979 4 k = 4284.51 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 lalpha rho intercept v n k 10 11 lalpha 1 -0.98 -0.18 0.18 -0.28 -0.011 12 13 rho -0.98 1 0.22 -0.18 0.29 0.012 14 15 intercept -0.18 0.22 1 -0.026 -0.058 0.0019 16 17 v 0.18 -0.18 -0.026 1 0.52 -0.96 18 19 n -0.28 0.29 -0.058 0.52 1 -0.71 20 21 k -0.011 0.012 0.0019 -0.96 -0.71 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 lalpha 3.21867 1.42224 0.431136 6.00621 30 rho -14.0858 2.68326 -19.3449 -8.82671 31 intercept 1.85564 0.016023 1.82424 1.88705 32 v -2.44363 2.81206 -7.95516 3.06791 33 n 0.196843 0.0500689 0.0987096 0.294976 34 k 2.75627e+008 2.27948e+009 -4.19207e+009 4.74332e+009 35 36 37 38 Table of Data and Estimated Values of Interest 39 40 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 41

------ --- -------- -------- ----------- ----------- ---------- 42 43 0 16 1.86 1.86 0.0661 0.0643 0.0163 44 4703 17 1.58 1.6 0.185 0.18 -0.597 45 1.568e+004 15 1.6 1.54 0.265 0.234 0.856 46 4.725e+004 12 1.5 1.48 0.221 0.316 0.259 47 1.585e+005 19 1.35 1.4 0.515 0.471 -0.465 48 49 50 51 Model Descriptions for likelihoods calculated 52 53 54 Model A1: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma^2 56 57 Model A2: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma(i)^2 59 60 Model A3: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 62 Model A3 uses any fixed variance parameters that 63 were specified by the user 64 65 Model R: Yi = Mu + e(i) 66 Var{e(i)} = Sigma^2 67 68 69 Likelihoods of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-96 1 Model Log(likelihood) # Param's AIC 2 A1 56.758717 6 -101.517434 3 A2 85.856450 10 -151.712901 4 A3 84.934314 7 -155.868628 5 fitted 83.472636 6 -154.945271 6 R 45.373551 2 -86.747101 7 8 9 Explanation of Tests 10 11 Test 1: Do responses and/or variances differ among Dose levels? 12 (A2 vs. R) 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 17 18 Tests of Interest 19 20 Test -2*log(Likelihood Ratio) Test df p-value 21 22 Test 1 80.9658 8 <.0001 23 Test 2 58.1955 4 <.0001 24 Test 3 1.84427 3 0.6053 25 Test 4 2.92336 1 0.08731 26 27 The p-value for Test 1 is less than .05. There appears to be a 28 difference between response and/or variances among the dose levels 29 It seems appropriate to model the data 30 31 The p-value for Test 2 is less than .1. A non-homogeneous variance 32 model appears to be appropriate 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 The p-value for Test 4 is less than .1. You may want to try a different 38 model 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 2.96451 50 51 BMDL = 0.0287389 52 53 54

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-97 1 

## E.2.13. Kattainen et al. (2001): Females 3 rd 

## Molar Eruption 2 

## E.2.13.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom 

## χ 2 pValue a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

logistic 3 0.360 88.508 7.290E+03 5.273E+03

log-logistic b 3 0.982 85.227 1.896E+03 1.050E+03 slope bound hit
log-probit, unrestricted 2 0.941 87.181 1.641E+03 1.895E+02 slope unrestricted

probit 3 0.379 88.352 6.958E+03 5.177E+03
multistage, 4- degree 3 0.781 86.155 3.195E+03 2.076E+03 final ß=0
log-logistic, unrestricted c 2 0.949 87.162 1.527E+03 1.456E+02 slope unrestricted

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model, BMDS output presented in this appendix

c Alternate model, BMDS output al so presented in this appendix 4 5 6 

## E.2.13.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 7

0 0.2 0.4 0.6 0.8

0 5000 10000 15000 20000 25000 30000 35000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

10:26 01/12 2010 BMDL BMD Log-Logistic

8 9 

## Kattainen et al., 2001: 3r d molar eruption in pups 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-98 E.2.13.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 1 

## Kattainen et al., 2001: 3r d molar eruption in pups 2 3

==================================================================== 4 Logistic Model. (Version: 2.12; Date: 05/16/2008) 5 Input Data File: C:\1\Blood\24_Katt_2001_3molar_erup_LogLogistic_BMR1.(d) 6 Gnuplot Plotting File: C:\1\Blood\24_Katt_2001_3molar_erup_LogLogistic_BMR1.plt 7 Tue Jan 12 10:26:06 2010 8

==================================================================== 9 10 Figure 2 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 16 17 18 Dependent variable = DichEff 19 Independent variable = Dose 20 Slope parameter is restricted as slope >= 1 21 22 Total number of observations = 5 23 Total number of records with missing values = 0 24 Maximum number of iterations = 250 25 Relative Function Convergence has been set to: 1e-008 26 Parameter Convergence has been set to: 1e-008 27 28 29 30 User has chosen the log transformed model 31 32 33 Default Initial Parameter Values 34 background = 0.0625 35 intercept = -9.748 36 slope = 1 37 38 39 Asymptotic Correlation Matrix of Parameter Estimates 40 41 ( *** The model parameter(s) -slope 42 have been estimated at a boundary point, or have been specified by the user, 43 and do not appear in the correlation matrix ) 44 45 background intercept 46 47 background 1 -0.53 48 49 intercept -0.53 1 50 51 52 53 Parameter Estimates 54 55 95.0% Wald Confidence Interval 56 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 57 background 0.0699182 * * * 58 intercept -9.74484 * * * 59 slope 1 * * * 60 61 * - Indicates that this value is not calculated. 62 63 64 65 Analysis of Deviance Table 66 67 Model Log(likelihood) # Param's Deviance Test d.f. P-value 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-99 Full model -40.5286 5 1 Fitted model -40.6136 2 0.170098 3 0.9823 2 Reduced model -50.7341 1 20.411 4 0.0004142 3 4 AIC: 85.2273 5 6 7 Goodness of Fit 8 Scaled 9 Dose Est._Prob. Expected Observed Size Residual 10

------------------------------------------------------------------------ 11 0.0000 0.0699 1.119 1.000 16 -0.116 12 1763.4151 0.1570 2.669 3.000 17 0.220 13 4943.6112 0.2788 4.182 4.000 15 -0.105 14 12712.0000 0.4670 5.604 6.000 12 0.229 15 37039.0000 0.7066 13.426 13.000 19 -0.215 16 17 Chi^2 = 0.17 d.f. = 3 P-value = 0.9820 18 19 20 Benchmark Dose Computation 21 22 Specified effect = 0.1 23 24 Risk Type = Extra risk 25 26 Confidence level = 0.95 27 28 BMD = 1896.22 29 30 BMDL = 1049.96 31 32 33 34 

## E.2.13.4. Figure for Unrestricted Model: Log -Logistic, Unrestricted 35

0 0.2 0.4 0.6 0.8

0 5000 10000 15000 20000 25000 30000 35000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

10:26 01/12 2010 BMDL BMD Log-Logistic

36 37 

## Kattainen et al., 2001: 3r d molar eruption in pups 38 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-100 E.2.13.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 1 

## Kattainen et al., 2001: 3r d molar eruption in pups 2

==================================================================== 3 Logistic Model. (Version: 2.12; Date: 05/16/2008) 4 Input Data File: C:\1\Blood\24_Katt_2001_3molar_erup_LogLogistic_Unrest_BMR1.(d) 5 Gnuplot Plotting File: C:\1\Blood\24_Katt_2001_3molar_erup_LogLogistic_Unrest_BMR1.plt 6 Tue Jan 12 10:26:07 2010 7

==================================================================== 8 9 Figure 2 10

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11 12 The form of the probability function is: 13 14 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 15 16 17 Dependent variable = DichEff 18 Independent variable = Dose 19 Slope parameter is not restricted 20 21 Total number of observations = 5 22 Total number of records with missing values = 0 23 Maximum number of iterations = 250 24 Relative Function Convergence has been set to: 1e-008 25 Parameter Convergence has been set to: 1e-008 26 27 28 29 User has chosen the log transformed model 30 31 32 Default Initial Parameter Values 33 background = 0.0625 34 intercept = -8.7855 35 slope = 0.902051 36 37 38 Asymptotic Correlation Matrix of Parameter Estimates 39 40 background intercept slope 41 42 background 1 -0.43 0.38 43 44 intercept -0.43 1 -0.99 45 46 slope 0.38 -0.99 1 47 48 49 50 Parameter Estimates 51 52 95.0% Wald Confidence Interval 53 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 54 background 0.0630017 * * * 55 intercept -8.87185 * * * 56 slope 0.910471 * * * 57 58 * - Indicates that this value is not calculated. 59 60 61 62 Analysis of Deviance Table 63 64 Model Log(likelihood) # Param's Deviance Test d.f. P-value 65 Full model -40.5286 5 66 Fitted model -40.5812 3 0.105153 2 0.9488 67 Reduced model -50.7341 1 20.411 4 0.0004142 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-101 1 AIC: 87.1623 2 3 Goodness of Fit 4 Scaled 5 Dose Est._Prob. Expected Observed Size Residual 6

------------------------------------------------------------------------ 7 0.0000 0.0630 1.008 1.000 16 -0.008 8 1763.4151 0.1684 2.862 3.000 17 0.089 9 4943.6112 0.2922 4.383 4.000 15 -0.218 10 12712.0000 0.4692 5.630 6.000 12 0.214 11 37039.0000 0.6903 13.117 13.000 19 -0.058 12 13 Chi^2 = 0.10 d.f. = 2 P-value = 0.9491 14 15 Benchmark Dose Computation 16 17 Specified effect = 0.1 18 Risk Type = Extra risk 19 Confidence level = 0.95 20 BMD = 1526.84 21 BMDL = 145.591 22 23 24 

## E.2.14. Kattainen et al., 2001: 3rd molar length in pups 25 

## E.2.14.1. Summary Table of BMDS modeling results 26

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

exponential (M2) 3 <0.0001 - 124.869 1.319E+04 7.850E+03

exponential (M3) 3 <0.0001 - 124.869 1.319E+04 7.850E+03 power bound hit

exponential (M4) 2 0.002 - 147.122 3.351E+02 2.001E+02

exponential (M5) 2 0.002 - 147.122 3.351E+02 2.001E+02 power bound hit

Hill c 2 0.022 - 152.241 2.477E+02 1.328E+02 n lower bound hit

linear 3 <.0001 - 124.026 1.567E+04 1.009E+04

polynomial 4 <.0001 -84.747 error error

power 3 <.0001 - 124.026 1.567E+04 1.009E+04 power bound hit

Hill, unrestricted d 1 <.0001 -78.747 2.007E+05 error n unrestricted

a Non-constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix

d Alternate model, BM DS output also presented in this appendix 27

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-102 E.2.14.2. Figure for selected model: Hill 1

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

0 5000 10000 15000 20000 25000 30000 35000Mean Response

dose Hill Model with 0.95 Confidence Level

10:26 01/12 2010 BMD BMDL Hill

2 3 

## Kattainen et al., 2001: 3rd molar length in pups 4 5 6 

## E.2.14.3. Output for selected model: Hill 7 

## Kattainen et al., 2001: 3rd molar length in pups 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\1\Blood\25_Katt_2001_3molar_length_Hill_1.(d) 11 Gnuplot Plotting File: C:\1\Blood\25_Katt_2001_3molar_length_Hill_1.plt 12 Tue Jan 12 10:26:49 2010 13

==================================================================== 14 15 Figure 3 female only 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter restricted to be greater than 1 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37 lalpha = -2.37155 38 rho = 0 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-103 intercept = 1.85591 1 v = -0.507874 2 n = 0.845971 3 k = 1606.5 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -n 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 lalpha rho intercept v k 13 14 lalpha 1 -0.98 -0.16 0.84 -0.38 15 16 rho -0.98 1 0.2 -0.79 0.4 17 18 intercept -0.16 0.2 1 -0.3 -0.11 19 20 v 0.84 -0.79 -0.3 1 -0.52 21 22 k -0.38 0.4 -0.11 -0.52 1 23 24 25 26 Parameter Estimates 27 28 95.0% Wald Confidence Interval 29 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 30 lalpha 3.31075 1.40399 0.558982 6.06253 31 rho -14.2656 2.6274 -19.4152 -9.11596 32 intercept 1.85483 0.0159478 1.82357 1.88609 33 v -0.45369 0.0620284 -0.575263 -0.332116 34 n 1 NA 35 k 1512.49 494.187 543.903 2481.08 36 37 NA - Indicates that this parameter has hit a bound 38 implied by some inequality constraint and thus 39 has no standard error. 40 41 42 43 Table of Data and Estimated Values of Interest 44 45 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 46

------ --- -------- -------- ----------- ----------- ---------- 47 48 0 16 1.86 1.85 0.0661 0.0639 0.0674 49 1763 17 1.58 1.61 0.185 0.175 -0.789 50 4944 15 1.6 1.51 0.265 0.28 1.22 51 1.271e+004 12 1.5 1.45 0.221 0.371 0.51 52 3.704e+004 19 1.35 1.42 0.515 0.432 -0.716 53 54 55 56 Model Descriptions for likelihoods calculated 57 58 59 Model A1: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 62 Model A2: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma(i)^2 64 65 Model A3: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 67 Model A3 uses any fixed variance parameters that 68 were specified by the user 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-104 Model R: Yi = Mu + e(i) 1 Var{e(i)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) # Param's AIC 7 A1 56.758717 6 -101.517434 8 A2 85.856450 10 -151.712901 9 A3 84.934314 7 -155.868628 10 fitted 81.120729 5 -152.241459 11 R 45.373551 2 -86.747101 12 13 14 Explanation of Tests 15 16 Test 1: Do responses and/or variances differ among Dose levels? 17 (A2 vs. R) 18 Test 2: Are Variances Homogeneous? (A1 vs A2) 19 Test 3: Are variances adequately modeled? (A2 vs. A3) 20 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 21 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 22 23 Tests of Interest 24 25 Test -2*log(Likelihood Ratio) Test df p-value 26 27 Test 1 80.9658 8 <.0001 28 Test 2 58.1955 4 <.0001 29 Test 3 1.84427 3 0.6053 30 Test 4 7.62717 2 0.02207 31 32 The p-value for Test 1 is less than .05. There appears to be a 33 difference between response and/or variances among the dose levels 34 It seems appropriate to model the data 35 36 The p-value for Test 2 is less than .1. A non-homogeneous variance 37 model appears to be appropriate 38 39 The p-value for Test 3 is greater than .1. The modeled variance appears 40 to be appropriate here 41 42 The p-value for Test 4 is less than .1. You may want to try a different 43 model 44 45 46 Benchmark Dose Computation 47 48 Specified effect = 1 49 50 Risk Type = Estimated standard deviations from the control mean 51 52 Confidence level = 0.95 53 54 BMD = 247.728 55 56 BMDL = 132.818 57 58

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-105 E.2.14.4. Figure for additional model presented: Hill, unrestricted 1

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

0 5000 10000 15000 20000 25000 30000 35000Mean Response

dose Hill Model

10:26 01/12 2010 Hill

2 3 

## Kattainen et al., 2001: 3rd molar length in pups 4 5 6 

## E.2.14.5. Output for additional model presented: Hill, unrestricted 7 

## Kattainen et al., 2001: 3rd molar length in pups 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\1\Blood\25_Katt_2001_3molar_length_Hill_Unrest_1.(d) 11 Gnuplot Plotting File: C:\1\Blood\25_Katt_2001_3molar_length_Hill_Unrest_1.plt 12 Tue Jan 12 10:26:49 2010 13

==================================================================== 14 15 Figure 3 female only 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37 lalpha = -2.37155 38 rho = 0 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-106 intercept = 1.85591 1 v = -0.507874 2 n = 0.845971 3 k = 1606.5 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 lalpha rho intercept v n k 9 10 lalpha NA NA NA NA NA NA 11 12 rho NA NA NA NA NA NA 13 14 intercept NA NA 1 NA 0.00038 0.00013 15 16
v NA NA NA NA NA NA 17 18 n NA NA 0.00038 NA 1 -1.1 19 20 k NA NA 0.00013 NA -1.1 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha 7.01946 NA NA NA 29 rho -20.2971 NA NA NA 30 intercept 1.57098 NA NA NA 31 v 4.02956 NA NA NA 32 n 13.2039 NA NA NA 33 k 240356 NA NA NA 34 35 At least some variance estimates are negative. 36 THIS USUALLY MEANS THE MODEL HAS NOT CONVERGED! 37 Try again from another starting point. 38 39 40 41 Table of Data and Estimated Values of Interest 42 43 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 44

------ --- -------- -------- ----------- ----------- ---------- 45 46 0 16 1.86 1.57 0.0661 0.342 3.34 47 1763 17 1.58 1.57 0.185 0.342 0.0747 48 4944 15 1.6 1.57 0.265 0.342 0.284 49 1.271e+004 12 1.5 1.57 0.221 0.342 -0.68 50 3.704e+004 19 1.35 1.57 0.515 0.342 -2.85 51 52 53 54 Model Descriptions for likelihoods calculated 55 56 57 Model A1: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma^2 59 60 Model A2: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma(i)^2 62 63 Model A3: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 65 Model A3 uses any fixed variance parameters that 66 were specified by the user 67 68 Model R: Yi = Mu + e(i) 69 Var{e(i)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-107 1 2 Likelihoods of Interest 3 4 Model Log(likelihood) # Param's AIC 5 A1 56.758717 6 -101.517434 6 A2 85.856450 10 -151.712901 7 A3 84.934314 7 -155.868628 8 fitted 45.373551 6 -78.747101 9 R 45.373551 2 -86.747101 10 11 12 Explanation of Tests 13 14 Test 1: Do responses and/or variances differ among Dose levels? 15 (A2 vs. R) 16 Test 2: Are Variances Homogeneous? (A1 vs A2) 17 Test 3: Are variances adequately modeled? (A2 vs. A3) 18 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 19 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 20 21 Tests of Interest 22 23 Test -2*log(Likelihood Ratio) Test df p-value 24 25 Test 1 80.9658 8 <.0001 26 Test 2 58.1955 4 <.0001 27 Test 3 1.84427 3 0.6053 28 Test 4 79.1215 1 <.0001 29 30 The p-value for Test 1 is less than .05. There appears to be a 31 difference between response and/or variances among the dose levels 32 It seems appropriate to model the data 33 34 The p-value for Test 2 is less than .1. A non-homogeneous variance 35 model appears to be appropriate 36 37 The p-value for Test 3 is greater than .1. The modeled variance appears 38 to be appropriate here 39 40 The p-value for Test 4 is less than .1. You may want to try a different 41 model 42 43 44 Benchmark Dose Computation 45 46 Specified effect = 1 47 48 Risk Type = Estimated standard deviations from the control mean 49 50 Confidence level = 0.95 51 52 BMD = 200720 53 54 55 BMDL computation failed. 56 57 58

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-108 E.2.15. Keller et al. (2006): Missing Mandibular Molars in CBA J Mice 1 

## E.2.15.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 pValue a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

gamma 1 0.105 52.510 1.844E+03 4.959E+02

logistic 2 0.334 49.984 1.692E+03 1.220E+03

log-logistic 1 0.105 52.524 2.210E+03 1.330E+03
log-probit, unrestricted 1 0.105 52.524 2.119E+03 1.336E+03 slope unrestricted
multistage, 1- degree b 3 0.255 50.434 6.014E+02 4.203E+02
multistage, 2- degree 1 0.122 51.394 1.057E+03 5.324E+02
multistage, 3- degree 1 0.150 50.855 9.452E+02 5.285E+02

probit 2 0.342 49.905 1.614E+03 1.132E+03

Weibull 1 0.108 52.221 1.514E+03 5.160E+02

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model, BMDS output presented in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-109 1 

## E.2.15.2. Figure for Selected Model: Multistage, 1-Degree 2

0 0.2 0.4 0.6 0.8

1

0 5000 10000 15000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

10:27 01/12 2010 BMD BMDL Multistage

3 4 

## Keller et al., 2007: Missing molars 5 6 7 

## E.2.15.3. Output File for Selected Model: Multistage, 1-Degree 8 

## Keller et al., 2007: Missing molars 9

==================================================================== 10 Multistage Model. (Version: 3.0; Date: 05/16/2008) 11 Input Data File: C:\1\Blood\26_Keller_2007_mand_molars_Multi1_1.(d) 12 Gnuplot Plotting File: C:\1\Blood\26_Keller_2007_mand_molars_Multi1_1.plt 13 Tue Jan 12 10:27:33 2010 14

==================================================================== 15 16 Table 1 using mandibular molars only 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the probability function is: 20 21 P[response] = background + (1-background)*[1-EXP( 22 -beta1*dose^1)] 23 24 The parameter betas are restricted to be positive 25 26 27 Dependent variable = DichEff 28 Independent variable = Dose 29 30 Total number of observations = 4 31 Total number of records with missing values = 0 32 Total number of parameters in model = 2 33 Total number of specified parameters = 0 34 Degree of polynomial = 1 35 36 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-110 Parameter Convergence has been set to: 1e-008 1 2 3 4 Default Initial Parameter Values 5 Background = 0 6 Beta(1) = 5.51735e+015 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -Background 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 Beta(1) 16 17 Beta(1) 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0 * * * 26 Beta(1) 0.000175192 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -21.5798 4 36 Fitted model -24.2169 1 5.27424 3 0.1528 37 Reduced model -71.326 1 99.4926 3 <.0001 38 39 AIC: 50.4338 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0000 0.000 0.000 29 0.000 47 296.0903 0.0506 1.163 2.000 23 0.797 48 2364.8010 0.3392 9.837 6.000 29 -1.505 49 18764.0000 0.9626 28.879 30.000 30 1.079 50 51 Chi^2 = 4.06 d.f. = 3 P-value = 0.2547 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.1 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 601.401 63 64 BMDL = 420.296 65 66 BMDU = 862.599 67 68 Taken together, (420.296, 862.599) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-111 1 

## E.2.16. Kociba et al. (1978): Urinary Copr oporphyrins, Females (Table 2) 2 

## E.2.16.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.03 18.65 <0.0001 82.98 1.3E+04 7.4E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.03 18.65 <0.0001 82.98 1.3E+04 7.4E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.03 7.49 0.01 73.82 8.6E+02 4.0E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.03 0.72 N/A 69.05 3.4E+03 8.7E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.03 0.72 N/A 69.05 3.4E+03 8.7E+02 nonconstant variance, power unrestricted

Hill 0 0.03 0.72 NA 69.05 3.0E+03 error nonconstant variance, n restricted >1

Hill 0 0.03 0.72 NA 69.05 3.0E+03 error nonconstant variance, n unrestricted

linear 2 0.03 17.90 0.00 82.23 9.9E+03 2.1E+03 nonconstant variance

polynomial 2 0.03 17.90 0.00 82.23 9.9E+03 2.1E+03 nonconstant variance

power 2 0.03 17.90 0.00 82.23 9.9E+03 2.1E+03 nonconstant variance, power restricted ≥ 1, bound hit

power 1 0.03 12.36 0.00 78.69 6.3E+02 5.6E-06 nonconstant variance, power unrestricted
exponential (M2) 2 0.03 11.60 0.00 81.00 1.4E+04 9.5E+03 constant variance, power restricted ≥ 1
exponential (M3) 2 0.03 11.60 0.00 81.00 1.4E+04 9.5E+03 constant variance, power restricted ≥ 1
exponential (M4) c 1 0.03 4.05 0.04 75.44 1.4E+03 6.5E+02 constant variance, power restricted ≥ 1
exponential (M5) 0 0.03 0.41 N/A 73.80 3.5E+03 8.8E+02 constant variance, power restricted ≥ 1
exponential (M5) d 0 0.03 0.41 N/A 73.80 3.5E+03 8.8E+02 constant variance, power unrestricted

Hill 0 0.03 0.41 NA 73.80 3.3E+03 error constant variance, n restricted >1

Hill d 0 0.03 0.41 NA 73.80 3.3E+03 error constant variance, n unrestricted

linear 2 0.03 11.02 0.00 80.41 1.1E+04 7.3E+03 constant variance

polynomial 2 0.03 11.02 0.00 80.41 1.1E+04 7.3E+03 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-112 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

power 2 0.03 11.02 0.00 80.41 1.1E+04 7.3E+03 constant variance, power restricted ≥ 1, bound hit

power d 1 0.03 7.99 0.00 79.38 2.5E+03 1.9E+02 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-113 E.2.17. Kociba et al. (1978): Uroporphyrin per Creatinine, Females 1 

## E.2.17.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.49 1.09 0.58 -93.46 7.6E+03 5.3E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.49 1.09 0.58 -93.46 7.6E+03 5.3E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.49 0.97 0.32 -91.57 5.7E+03 1.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.49 0.51 N/A -90.03 4.0E+03 2.0E+03 nonconstant variance, power restricted ≥ 1

Hill 0 0.49 0.51 NA -90.03 4.1E+03 2.0E+03 nonconstant variance, n restricted >1

linear 2 0.49 0.98 0.61 -93.57 5.9E+03 3.7E+03 nonconstant variance

polynomial 2 0.49 0.98 0.61 -93.57 5.9E+03 3.7E+03 nonconstant variance

power 1 0.49 0.97 0.33 -91.58 6.3E+03 3.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M2) 2 0.49 0.56 0.75 -93.83 9.0E+03 6.9E+03 constant variance, power restricted ≥ 1
exponential (M3) 2 0.49 0.56 0.75 -93.83 9.0E+03 6.9E+03 constant variance, power restricted ≥ 1
exponential (M4) 1 0.49 0.46 0.50 -91.93 6.7E+03 2.2E+03 constant variance, power restricted ≥ 1
exponential (M5) 0 0.49 0.20 N/A -90.19 4.2E+03 2.3E+03 constant variance, power restricted ≥ 1

linear c 2 0.49 0.46 0.79 -93.93 7.2E+03 5.1E+03 constant variance

polynomial 2 0.49 0.46 0.79 -93.93 7.2E+03 5.1E+03 constant variance

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-114 E.2.17.2. Figure for Selected Model: Linear, Constant Variance 1

0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 5000 10000 15000 20000Mean Response

dose Linear Model with 0.95 Confidence Level

13:40 11/16 2009 BMD BMDL Linear

2 3 4 

## E.2.17.3. Output File for Selected Mode l: L inear, Constant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: 10 C:\USEPA\BMDS21\AD\Blood\LinearConstVar_BMR1_Females_uroporphyrin_per_creatinine.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AD\Blood\LinearConstVar_BMR1_Females_uroporphyrin_per_creatinine.plt 13 Mon Nov 16 13:40:10 2009 14

==================================================================== 15 16 Table 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 rho is set to 0 27 Signs of the polynomial coefficients are not restricted 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-115 1 Default Initial Parameter Values 2 alpha = 0.0030385 3 rho = 0 Specified 4 beta_0 = 0.149139 5 beta_1 = 6.92935e-006 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 ( *** The model parameter(s) -rho 11 have been estimated at a boundary point, or have been specified by the user, 12 and do not appear in the correlation matrix ) 13 14 alpha beta_0 beta_1 15 16 alpha 1 -5.8e-012 2.2e-011 17 18 beta_0 -5.8e-012 1 -0.6 19 20 beta_1 2.2e-011 -0.6 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 alpha 0.00248773 0.000786688 0.000945846 0.00402961 29 beta_0 0.149139 0.0139684 0.121762 0.176517 30 beta_1 6.92935e-006 1.29185e-006 4.39737e-006 9.46132e-006 31 32 33 34 Table of Data and Estimated Values of Interest 35 36 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 37

------ --- -------- -------- ----------- ----------- ---------- 38 39 0 5 0.157 0.149 0.05 0.0499 0.352 40 852.5 5 0.143 0.155 0.037 0.0499 -0.54 41 3942 5 0.181 0.176 0.053 0.0499 0.204 42 2.125e+004 5 0.296 0.296 0.074 0.0499 -0.0161 43 44 45 46 Model Descriptions for likelihoods calculated 47 48 49 Model A1: Yij = Mu(i) + e(ij) 50 Var{e(ij)} = Sigma^2 51 52 Model A2: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma(i)^2 54 55 Model A3: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma^2 57 Model A3 uses any fixed variance parameters that 58 were specified by the user 59 60 Model R: Yi = Mu + e(i) 61 Var{e(i)} = Sigma^2 62 63 64 Likelihoods of Interest 65 66 Model Log(likelihood) # Param's AIC 67 A1 50.195349 5 -90.390697 68 A2 51.400051 8 -86.800103 69 A3 50.195349 5 -90.390697 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-116 fitted 49.963861 3 -93.927722 1 R 41.049755 2 -78.099510 2 3 4 Explanation of Tests 5 6 Test 1: Do responses and/or variances differ among Dose levels? 7 (A2 vs. R) 8 Test 2: Are Variances Homogeneous? (A1 vs A2) 9 Test 3: Are variances adequately modeled? (A2 vs. A3) 10 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 11 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 12 13 Tests of Interest 14 15 Test -2*log(Likelihood Ratio) Test df p-value 16 17 Test 1 20.7006 6 0.002076 18 Test 2 2.40941 3 0.4919 19 Test 3 2.40941 3 0.4919 20 Test 4 0.462975 2 0.7934 21 22 The p-value for Test 1 is less than .05. There appears to be a 23 difference between response and/or variances among the dose levels 24 It seems appropriate to model the data 25 26 The p-value for Test 2 is greater than .1. A homogeneous variance 27 model appears to be appropriate here 28 29 30 The p-value for Test 3 is greater than .1. The modeled variance appears 31 to be appropriate here 32 33 The p-value for Test 4 is greater than .1. The model chosen seems 34 to adequately describe the data 35 36 37 Benchmark Dose Computation 38 39 Specified effect = 1 40 41 Risk Type = Estimated standard deviations from the control mean 42 43 Confidence level = 0.95 44 45 BMD = 7197.95 46 47 48 BMDL = 5116.98 49 50 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-117 E.2.18. Latchoumycandane and Mathur (2002): Daily Sperm Production 1 

## E.2.18.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD (ng/kg-d) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.85 19.80 <0.0001 94.90 1.2E+04 5.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.85 19.80 <0.0001 94.90 1.2E+04 5.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.85 0.16 0.69 77.26 1.0E+02 3.9E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.85 0.16 0.69 77.26 1.0E+02 3.9E+01 nonconstant variance, power restricted ≥ 1

Hill 1 0.85 0.00 0.95 77.10 6.3E+01 6.2E+00 nonconstant variance, n restricted >1, bound hit

Hill 0 0.85 0.00 NA 79.10 5.1E+01 1.7E-05 nonconstant variance, n unrestricted

linear 2 0.85 20.13 <.0001 95.23 1.3E+04 7.3E+03 nonconstant variance

polynomial 1 0.85 9.62 0.00 86.72 1.4E+03 7.9E+02 nonconstant variance

power 2 0.85 20.13 <.0001 95.23 1.3E+04 7.3E+03 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.85 20.71 <0.0001 93.82 9.6E+03 5.2E+03 constant variance, power restricted ≥ 1
exponential (M3) 2 0.85 20.71 <0.0001 93.82 9.6E+03 5.2E+03 constant variance, power restricted ≥ 1
exponential (M4) d 1 0.85 0.15 0.70 75.26 1.1E+02 4.4E+01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.85 0.15 N/A 77.26 1.6E+02 4.4E+01 constant variance, power restricted ≥ 1

Hill, rextricted c 1 0.85 0.00 0.98 118.11 3.40E+02 1.51E-02 constant variance, n restricted >1, bound hit
Hill, unrestricted d 0 0.85 0.00 NA 120.11 3.32E+02 8.77E-03 constant variance, n unrestricted

linear 2 0.85 21.13 <.0001 94.24 1.1E+04 6.7E+03 constant variance

polynomial 1 0.85 11.01 0.00 86.13 1.1E+03 7.1E+02 constant variance

power 2 0.85 21.13 <.0001 94.24 1.1E+04 6.7E+03 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-118 1 

## E.2.18.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 2

5 10 15 20 25 30

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Hill Model with 0.95 Confidence Level

10:15 11/27 2009 BMD BMDL Hill

3 4 5 

## E.2.18.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 6 

## Hit 7
8 9

==================================================================== 10 Hill Model. (Version: 2.14; Date: 06/26/2008) 11 Input Data File: C:\Usepa\Bmds2\Data\HilTCDSet.(d) 12 Gnuplot Plotting File: C:\Usepa\Bmds2\Data\HilTCDSet.plt 13 Fri Nov 27 10:15:04 2009 14

==================================================================== 15 16 BMDS Model Run 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 22 23 24 Dependent variable = m_sperm 25 Independent variable = DOSE 26 rho is set to 0 27 Power parameter restricted to be greater than 1 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-119 1 Default Initial Parameter Values 2 alpha = 43.3822 3 rho = 0 Specified 4 intercept = 22.19 5 v = -9.09 6 n = 1.93174 7 k = 304.417 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -rho -n 13 have been estimated at a boundary point, or have been specified by 14 the user, 15 and do not appear in the correlation matrix ) 16 17 alpha intercept v k 18 19 alpha 1 6.6e-010 -7.3e-008 6.3e-008 20 21 intercept 6.6e-010 1 -0.75 -0.23 22 23 v -7.3e-008 -0.75 1 -0.24 24 25 k 6.3e-008 -0.23 -0.24 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence 32 Interval 33 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. 34 Limit 35 alpha 36.1524 10.4363 15.6976 36 56.6072 37 intercept 22.1894 2.45468 17.3783 38 27.0005 39 v -9.16864 3.2083 -15.4568 - 40 2.88049 41 n 1 NA 42 k 178.32 300.643 -410.929 43 767.569 44 45 NA - Indicates that this parameter has hit a bound 46 implied by some inequality constraint and thus 47 has no standard error. 48 49 50 51 Table of Data and Estimated Values of Interest 52 53 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 54

------ --- -------- -------- ----------- ----------- ---------- 55 56 0 6 22.2 22.2 6.54 6.01 0.000252 57 436.7 6 15.7 15.7 6.49 6.01 -0.00371 58 2579 6 13.7 13.6 5.36 6.01 0.0148 59 1.509e+004 6 13.1 13.1 7.74 6.01 -0.0113 60 61 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-120 1 Model Descriptions for likelihoods calculated 2 3 4 Model A1: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = Sigma^2 6 7 Model A2: Yij = Mu(i) + e(ij) 8 Var{e(ij)} = Sigma(i)^2 9 10 Model A3: Yij = Mu(i) + e(ij) 11 Var{e(ij)} = Sigma^2 12 Model A3 uses any fixed variance parameters that 13 were specified by the user 14 15 Model R: Yi = Mu + e(i) 16 Var{e(i)} = Sigma^2 17 18 19 Likelihoods of Interest 20 21 Model Log(likelihood) # Param's AIC 22 A1 -55.052739 5 120.105478 23 A2 -54.653533 8 125.307067 24 A3 -55.052739 5 120.105478 25 fitted -55.052919 4 118.105839 26 R -58.755106 2 121.510213 27 28 29 Explanation of Tests 30 31 Test 1: Do responses and/or variances differ among Dose levels? 32 (A2 vs. R) 33 Test 2: Are Variances Homogeneous? (A1 vs A2) 34 Test 3: Are variances adequately modeled? (A2 vs. A3) 35 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 36 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 37 38 Tests of Interest 39 40 Test -2*log(Likelihood Ratio) Test df p-value 41 42 Test 1 8.20315 6 0.2236 43 Test 2 0.798411 3 0.8498 44 Test 3 0.798411 3 0.8498 45 Test 4 0.000361116 1 0.9848 46 47 The p-value for Test 1 is greater than .05. There may not be a 48 diffence between responses and/or variances among the dose levels 49 Modelling the data with a dose/response curve may not be appropriate 50 51 The p-value for Test 2 is greater than .1. A homogeneous variance 52 model appears to be appropriate here 53 54 55 The p-value for Test 3 is greater than .1. The modeled variance appears 56 to be appropriate here 57 58 The p-value for Test 4 is greater than .1. The model chosen seems 59 to adequately describe the data 60 61 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-121 Benchmark Dose Computation 1 2 Specified effect = 1 3 4 Risk Type = Estimated standard deviations from the control mean 5 6 Confidence level = 0.95 7 8 BMD = 339.732 9 10 BMDL = 0.015111 11 12 13 

## E.2.18.4. Figure for Unrestricted Model: Hill , Constant Variance, n Unrestricted 14

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10000 20000 30000 40000 50000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

07:51 11/27 2009 BMDL BMD Log-Logistic

15 16 17 

## E.2.18.5. Output File for Unrestricted Model: Hil l, Consta nt Variance, n Unrestricted 18
19 20

==================================================================== 21 Logistic Model. (Version: 2.12; Date: 05/16/2008) 22 Input Data File: C:\Usepa\Bmds2\Data\LogTcdSet.(d) 23 Gnuplot Plotting File: C:\Usepa\Bmds2\Data\LogTcdSet.plt 24 Fri Nov 27 07:51:12 2009 25

==================================================================== 26 27 BMDS Model Run 28

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 30 The form of the probability function is: 31 32 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 33 34 35 Dependent variable = r_skin 36 Independent variable = DOSE 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-122 Slope parameter is not restricted 1 2 Total number of observations = 4 3 Total number of records with missing values = 0 4 Maximum number of iterations = 250 5 Relative Function Convergence has been set to: 1e-008 6 Parameter Convergence has been set to: 1e-008 7 8 9 10 User has chosen the log transformed model 11 12 13 Default Initial Parameter Values 14 background = 0 15 intercept = -4.78342 16 slope = 0.469549 17 18 19 Asymptotic Correlation Matrix of Parameter Estimates 20 21 ( *** The model parameter(s) -background 22 have been estimated at a boundary point, or have been specified by 23 the user, 24 and do not appear in the correlation matrix ) 25 26 intercept slope 27 28 intercept 1 -0.98 29 30 slope -0.98 1 31 32 33 34 Parameter Estimates 35 36 95.0% Wald Confidence 37 Interval 38 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. 39 Limit 40 background 0 * * * 41 intercept -4.84059 * * * 42 slope 0.475472 * * * 43 44 * - Indicates that this value is not calculated. 45 46 47 48 Analysis of Deviance Table 49 50 Model Log(likelihood) # Param's Deviance Test d.f. P-value 51 Full model -71.5177 4 52 Fitted model -71.5376 2 0.0398444 2 0.9803 53 Reduced model -95.8498 1 48.6642 3 <.0001 54 55 AIC: 147.075 56 57 58 Goodness of Fit 59 Scaled 60 Dose Est._Prob. Expected Observed Size Residual 61

------------------------------------------------------------------------ 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-123 0.0000 0.0000 0.000 0.000 38 0.000 1 316.0000 0.1087 4.784 5.000 44 0.105 2 4714.0000 0.3060 13.464 13.000 44 -0.152 3 50105.0000 0.5756 24.753 25.000 43 0.076 4 5 Chi^2 = 0.04 d.f. = 2 P-value = 0.9803 6 7 8 Benchmark Dose Computation 9 10 Specified effect = 0.1 11 12 Risk Type = Extra risk 13 14 Confidence level = 0.95 15 16 BMD = 259.682 17 18 BMDL = 31.788 19 20 21 

## E.2.19. Li et al. (1997): Follicle-Stimulating Hormone 22 

## E.2.19.1. Summary Table of BMDS Modeling Results 23

24

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

exponential (M2) 8 <0.0001 1095.433 2.898E+05 2.286E+05

exponential (M3) 8 <0.0001 1095.433 2.898E+05 2.286E+05 power bound hit

exponential (M4) 7 <0.0001 1059.480 1.891E+04 5.471E+03

exponential (M5) 6 <0.0001 1066.195 6.118E+04 4.729E+02

Hill 7 <.0001 1056.455 2.993E+03 1.081E+03 n lower bound hit

linear 8 <.0001 1077.819 1.109E+05 7.503E+04

polynomial 9 <.0001 1155.670 error error

power c 8 <.0001 1077.819 1.109E+05 7.503E+04 power bound hit

Hill, unrestricted 6 0.001 1039.476 1.206E+02 error n unrestricted
power, unrestricted d 7 0.002 1037.471 1.078E+02 1.353E+01 power unrestricted

a Non-constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix

d Alternate model, BM DS output also presented in this appendix

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-124 E.2.19.2. Figure for Selected Model: Power 1

0 100 200 300 400 500 600 700

0 100000 200000 300000 400000 500000 600000Mean Response

dose Power Model with 0.95 Confidence Level

10:32 01/12 2010 BMD BMDL Power

2 3 

## Li et al., 1997: FSH 4 5 6 

## E.2.19.3. Output for Selected Model: Power 7 

## Li et al., 1997: FSH 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\1\Blood\72_Li_1997_FSH_Power_BMR1.(d) 11 Gnuplot Plotting File: C:\1\Blood\72_Li_1997_FSH_Power_BMR1.plt 12 Tue Jan 12 10:32:04 2010 13

==================================================================== 14 15 Figure 3: FSH in female S-D rats 24hr after dosing, 22 day old rats 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is restricted to be greater than or equal to 1 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 10 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37 lalpha = 9.8191 38 rho = 0 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-125 control = 22.1591 1 slope = 8.17907 2 power = 0.293959 3 4 5 Asymptotic Correlation Matrix of Parameter Estimates 6 7 ( *** The model parameter(s) -power 8 have been estimated at a boundary point, or have been specified by the user, 9 and do not appear in the correlation matrix ) 10 11 lalpha rho control slope 12 13 lalpha 1 -0.99 -0.29 -0.035 14 15 rho -0.99 1 0.2 0.035 16 17 control -0.29 0.2 1 -0.36 18 19 slope -0.035 0.035 -0.36 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 lalpha 3.49167 1.22596 1.08884 5.89451 28 rho 1.27289 0.242042 0.798492 1.74728 29 control 87.5089 12.9454 62.1364 112.881 30 slope 0.000889717 0.000166742 0.000562908 0.00121653 31 power 1 NA 32 33 NA - Indicates that this parameter has hit a bound 34 implied by some inequality constraint and thus 35 has no standard error. 36 37 38 39 Table of Data and Estimated Values of Interest 40 41 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 42

------ --- -------- -------- ----------- ----------- ---------- 43 44 0 10 23.9 87.5 29.6 98.7 -2.04 45 146.5 10 22.2 87.6 48.5 98.8 -2.1 46 440.1 10 85.2 87.9 94.3 99 -0.0854 47 1156 10 73.3 88.5 48.5 99.4 -0.485 48 3232 10 126 90.4 159 101 1.12 49 8266 10 132 94.9 116 104 1.13 50 2.388e+004 10 117 109 51.2 113 0.224 51 6.608e+004 10 304 146 154 137 3.65 52 2.127e+005 10 347 277 151 205 1.08 53 6.497e+005 10 455 666 286 359 -1.85 54 55 56 57 Model Descriptions for likelihoods calculated 58 59 60 Model A1: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 63 Model A2: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma(i)^2 65 66 Model A3: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 68 Model A3 uses any fixed variance parameters that 69 were specified by the user 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-126 1 Model R: Yi = Mu + e(i) 2 Var{e(i)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) # Param's AIC 8 A1 -535.687163 11 1093.374327 9 A2 -496.367061 20 1032.734122 10 A3 -502.709623 12 1029.419246 11 fitted -534.909723 4 1077.819445 12 R -574.835246 2 1153.670492 13 14 15 Explanation of Tests 16 17 Test 1: Do responses and/or variances differ among Dose levels? 18 (A2 vs. R) 19 Test 2: Are Variances Homogeneous? (A1 vs A2) 20 Test 3: Are variances adequately modeled? (A2 vs. A3) 21 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 22 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 23 24 Tests of Interest 25 26 Test -2*log(Likelihood Ratio) Test df p-value 27 28 Test 1 156.936 18 <.0001 29 Test 2 78.6402 9 <.0001 30 Test 3 12.6851 8 0.1232 31 Test 4 64.4002 8 <.0001 32 33 The p-value for Test 1 is less than .05. There appears to be a 34 difference between response and/or variances among the dose levels 35 It seems appropriate to model the data 36 37 The p-value for Test 2 is less than .1. A non-homogeneous variance 38 model appears to be appropriate 39 40 The p-value for Test 3 is greater than .1. The modeled variance appears 41 to be appropriate here 42 43 The p-value for Test 4 is less than .1. You may want to try a different 44 model 45 46 47 Benchmark Dose Computation 48 49 Specified effect = 1 50 51 Risk Type = Estimated standard deviations from the control mean 52 53 Confidence level = 0.95 54 55 BMD = 110907 56 57 58 BMDL = 75025.9 59 60

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-127 E.2.19.4. Figure for Unrestricted M odel: Po wer, Unrestricted 1

0 100 200 300 400 500 600 700

0 100000 200000 300000 400000 500000 600000Mean Response

dose Power Model with 0.95 Confidence Level

10:32 01/12 2010 BMDBMDL Power

2 3 

## Li et al., 1997: FSH 4 5 6 

## E.2.19.5. Output for Unrestricted Model: Power, Unrestricted 7 

## Li et al., 1997: FSH 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\1\Blood\72_Li_1997_FSH_Power_Unrest_BMR1.(d) 11 Gnuplot Plotting File: C:\1\Blood\72_Li_1997_FSH_Power_Unrest_BMR1.plt 12 Tue Jan 12 10:32:11 2010 13

==================================================================== 14 15 Figure 3: FSH in female S-D rats 24hr after dosing, 22 day old rats 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 10 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37 lalpha = 9.8191 38 rho = 0 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-128 control = 22.1591 1 slope = 8.17907 2 power = 0.293959 3 4 5 Asymptotic Correlation Matrix of Parameter Estimates 6 7 lalpha rho control slope power 8 9 lalpha 1 -0.99 -0.69 -0.17 0.26 10 11 rho -0.99 1 0.65 0.13 -0.23 12 13 control -0.69 0.65 1 -0.12 0.029 14 15 slope -0.17 0.13 -0.12 1 -0.97 16 17 power 0.26 -0.23 0.029 -0.97 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 lalpha 3.6735 1.12114 1.4761 5.8709 26 rho 1.17908 0.221492 0.744961 1.61319 27 control 15.8235 6.8753 2.34812 29.2988 28 slope 7.68345 2.90499 1.98976 13.3771 29 power 0.30464 0.0336473 0.238692 0.370587 30 31 32 33 Table of Data and Estimated Values of Interest 34 35 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 36

------ --- -------- -------- ----------- ----------- ---------- 37 38 0 10 23.9 15.8 29.6 32 0.795 39 146.5 10 22.2 50.9 48.5 63.7 -1.43 40 440.1 10 85.2 64.9 94.3 73.5 0.875 41 1156 10 73.3 81.7 48.5 84.1 -0.315 42 3232 10 126 106 159 98.1 0.652 43 8266 10 132 136 116 114 -0.102 44 2.388e+004 10 117 181 51.2 135 -1.52 45 6.608e+004 10 304 242 154 160 1.24 46 2.127e+005 10 347 338 151 194 0.139 47 6.497e+005 10 455 469 286 236 -0.187 48 49 50 51 Model Descriptions for likelihoods calculated 52 53 54 Model A1: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma^2 56 57 Model A2: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma(i)^2 59 60 Model A3: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 62 Model A3 uses any fixed variance parameters that 63 were specified by the user 64 65 Model R: Yi = Mu + e(i) 66 Var{e(i)} = Sigma^2 67 68 69 Likelihoods of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-129 1 Model Log(likelihood) # Param's AIC 2 A1 -535.687163 11 1093.374327 3 A2 -496.367061 20 1032.734122 4 A3 -502.709623 12 1029.419246 5 fitted -513.735602 5 1037.471204 6 R -574.835246 2 1153.670492 7 8 9 Explanation of Tests 10 11 Test 1: Do responses and/or variances differ among Dose levels? 12 (A2 vs. R) 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 17 18 Tests of Interest 19 20 Test -2*log(Likelihood Ratio) Test df p-value 21 22 Test 1 156.936 18 <.0001 23 Test 2 78.6402 9 <.0001 24 Test 3 12.6851 8 0.1232 25 Test 4 22.052 7 0.002489 26 27 The p-value for Test 1 is less than .05. There appears to be a 28 difference between response and/or variances among the dose levels 29 It seems appropriate to model the data 30 31 The p-value for Test 2 is less than .1. A non-homogeneous variance 32 model appears to be appropriate 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 The p-value for Test 4 is less than .1. You may want to try a different 38 model 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 107.761 50 51 52 BMDL = 13.5336 53 54

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-130 1 

## E.2.20. Li et al. (2006): Hormone Levels (Estradiol) 2 

## E.2.20.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.44 4.95 0.08 271.02 7.7E+03 2.8E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.44 4.95 0.08 271.02 7.7E+03 2.8E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.44 0.34 0.56 268.41 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.44 0.34 N/A 270.41 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.44 0.34 N/A 270.41 error error nonconstant variance, power unrestricted

Hill 1 0.44 0.34 0.56 268.41 error error nonconstant variance, n restricted >1

linear 2 0.44 4.87 0.09 270.95 8.7E+03 2.7E+03 nonconstant variance

polynomial 2 0.44 4.87 0.09 270.95 8.7E+03 2.7E+03 nonconstant variance

power 2 0.44 4.87 0.09 270.95 8.7E+03 2.7E+03 nonconstant variance, power restricted ≥ 1, bound hit

power 2 0.44 0.34 0.84 266.41 2.8E+05 error nonconstant variance, power unrestricted
exponential (M2) 2 0.44 3.72 0.16 269.03 7.8E+03 3.1E+03 constant variance, power restricted ≥ 1
exponential (M3) 2 0.44 3.72 0.16 269.03 7.8E+03 3.1E+03 constant variance, power restricted ≥ 1
exponential (M4) 1 0.44 0.91 0.34 268.21 error error constant variance, power restricted ≥ 1
exponential (M5) 0 0.44 0.91 N/A 270.21 error error constant variance, power restricted ≥ 1
exponential (M5) d 0 0.44 0.91 N/A 270.21 error error constant variance, power unrestricted

Hill 0 0.44 0.91 NA 270.21 error error constant variance, n restricted >1

Hill d 0 0.44 0.96 NA 270.26 5.1E+15 5.1E+15 constant variance, n unrestricted

linear c 2 0.44 3.65 0.16 268.95 8.8E+03 3.0E+03 constant variance

polynomial 2 0.44 3.65 0.16 268.95 8.8E+03 3.0E+03 constant variance

power 2 0.44 3.65 0.16 268.95 8.8E+03 3.0E+03 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-131 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

power d 1 0.44 0.96 0.33 268.27 5.2E+13 error constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.2.20.2. Figure for Selected Model: Linear, Constant Variance 3

0 5 10 15 20 25 30 35

0 1000 2000 3000 4000 5000 6000 7000 8000 9000Mean Response

dose Linear Model with 0.95 Confidence Level

13:50 11/16 2009 BMD BMDL Linear

4 5 6 

## E.2.20.3. Output File for Unrestricted M odel: Linear, Constant Variance 7
8 9

==================================================================== 10 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\LinearConst_BMR1_Li_Estradiol_3d.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\LinearConst_BMR1_Li_Estradiol_3d.plt 13 Mon Nov 16 13:50:03 2009 14

==================================================================== 15 16 Figure 3, 3-day estradiol 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-132 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 1 2 3 Dependent variable = Mean 4 Independent variable = Dose 5 rho is set to 0 6 Signs of the polynomial coefficients are not restricted 7 A constant variance model is fit 8 9 Total number of dose groups = 4 10 Total number of records with missing values = 0 11 Maximum number of iterations = 250 12 Relative Function Convergence has been set to: 1e-008 13 Parameter Convergence has been set to: 1e-008 14 15 16 17 Default Initial Parameter Values 18 alpha = 267.211 19 rho = 0 Specified 20 beta_0 = 16.1706 21 beta_1 = 0.00183421 22 23 24 Asymptotic Correlation Matrix of Parameter Estimates 25 26 ( *** The model parameter(s) -rho 27 have been estimated at a boundary point, or have been specified by the user, 28 and do not appear in the correlation matrix ) 29 30 alpha beta_0 beta_1 31 32 alpha 1 2.7e-011 6.4e-013 33 34 beta_0 2.7e-011 1 -0.69 35 36 beta_1 6.4e-013 -0.69 1 37 38 39 40 Parameter Estimates 41 42 95.0% Wald Confidence Interval 43 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 44 alpha 263.435 58.9058 147.981 378.888 45 beta_0 16.1706 3.55948 9.19411 23.147 46 beta_1 0.00183421 0.00220486 -0.00248724 0.00615566 47 48 49 50 Table of Data and Estimated Values of Interest 51 52 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 53

------ --- -------- -------- ----------- ----------- ---------- 54 55 0 10 10.2 16.2 12.2 16.2 -1.17 56 87.49 10 19.9 16.3 20 16.2 0.697 57 1564 10 24.7 19 14.6 16.2 1.11 58 2823 10 18.1 21.3 17.6 16.2 -0.635 59 60 61 62 Model Descriptions for likelihoods calculated 63 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-133 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = Sigma^2 3 Model A3 uses any fixed variance parameters that 4 were specified by the user 5 6 Model R: Yi = Mu + e(i) 7 Var{e(i)} = Sigma^2 8 9 10 Likelihoods of Interest 11 12 Model Log(likelihood) # Param's AIC 13 A1 -129.653527 5 269.307054 14 A2 -128.294657 8 272.589314 15 A3 -129.653527 5 269.307054 16 fitted -131.476105 3 268.952210 17 R -131.819169 2 267.638338 18 19 20 Explanation of Tests 21 22 Test 1: Do responses and/or variances differ among Dose levels? 23 (A2 vs. R) 24 Test 2: Are Variances Homogeneous? (A1 vs A2) 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 26 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 27 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 28 29 Tests of Interest 30 31 Test -2*log(Likelihood Ratio) Test df p-value 32 33 Test 1 7.04902 6 0.3163 34 Test 2 2.71774 3 0.4372 35 Test 3 2.71774 3 0.4372 36 Test 4 3.64516 2 0.1616 37 38 The p-value for Test 1 is greater than .05. There may not be a 39 diffence between responses and/or variances among the dose levels 40 Modelling the data with a dose/response curve may not be appropriate 41 42 The p-value for Test 2 is greater than .1. A homogeneous variance 43 model appears to be appropriate here 44 45 46 The p-value for Test 3 is greater than .1. The modeled variance appears 47 to be appropriate here 48 49 The p-value for Test 4 is greater than .1. The model chosen seems 50 to adequately describe the data 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 1 56 57 Risk Type = Estimated standard deviations from the control mean 58 59 Confidence level = 0.95 60 61 BMD = 8848.86 62 63 64 BMDL = 2963.62 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-134 E.2.20.4. Figure for Unrestricted Model: Expone ntial (M5), Constant Variance, Power 1 

## Unrestricted 2

0 5 10 15 20 25 30 35

0 500 1000 1500 2000 2500Mean Response

dose Exponential_beta Model 5

13:50 11/16 2009 BMD Exponential

3 4 5 

## E.2.20.5. Output File for Unrestricted Model: E xponential (M5), Constant Varian ce, Power 6 

## Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\ExpConst_Unrest_BMR1_Li_Estradiol_3d.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 13:50:07 2009 14

==================================================================== 15 16 Figure 3, 3-day estradiol 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-135 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 rho is set to 0. 3 A constant variance model is fit. 4 5 Total number of dose groups = 4 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 5 17

-------- -------- 18 lnalpha 5.48268 19 rho(S) 0 20 a 9.65979 21 b 0.000592388 22 c 2.68754 23 d 1 24 25 (S) = Specified 26 27 28 29 Parameter Estimates 30 31 Variable Model 5 32

-------- ------- 33 lnalpha 5.50531 34 rho 0 35 a 10.1682 36 b 0.0192802 37 c 2.10526 38 d 1.3399 39 40 NC = No Convergence 41 42 43 Table of Stats From Input Data 44 45 Dose N Obs Mean Obs Std Dev 46

----- --- ---------- ------------- 47 0 10 10.17 12.18 48 87.49 10 19.91 19.97 49 1564 10 24.72 14.55 50 2823 10 18.09 17.6 51 52 53 Estimated Values of Interest 54 55 Dose Est Mean Est Std Scaled Residual 56

------ ---------- --------- ---------------- 57 0 10.17 15.68 2.254e-007 58 87.49 19.91 15.68 -2.355e-007 59 1564 21.41 15.68 0.669 60 2823 21.41 15.68 -0.669 61 62 63 64 Other models for which likelihoods are calculated: 65 66 Model A1: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma^2 68 69 Model A2: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-136 Var{e(ij)} = Sigma(i)^2 1 2 Model A3: Yij = Mu(i) + e(ij) 3 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 4 5 Model R: Yij = Mu + e(i) 6 Var{e(ij)} = Sigma^2 7 8 9 Likelihoods of Interest 10 11 Model Log(likelihood) DF AIC 12

------- ----------------- ---- ------------ 13 A1 -129.6535 5 269.3071 14 A2 -128.2947 8 272.5893 15 A3 -129.6535 5 269.3071 16 R -131.8192 2 267.6383 17 5 -130.1062 5 270.2123 18 19 20 Additive constant for all log-likelihoods = -36.76. This constant added to the 21 above values gives the log-likelihood including the term that does not 22 depend on the model parameters. 23 24 25 Explanation of Tests 26 27 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 28 Test 2: Are Variances Homogeneous? (A2 vs. A1) 29 Test 3: Are variances adequately modeled? (A2 vs. A3) 30 31 Test 7a: Does Model 5 fit the data? (A3 vs 5) 32 33 34 Tests of Interest 35 36 Test -2*log(Likelihood Ratio) D. F. p-value 37

-------- ------------------------ ------ -------------- 38 Test 1 7.049 6 0.3163 39 Test 2 2.718 3 0.4372 40 Test 3 2.718 3 0.4372 41 Test 7a 0.9053 0 N/A 42 43 44 The p-value for Test 1 is greater than .05. There may not be a 45 diffence between responses and/or variances among the dose levels 46 Modelling the data with a dose/response curve may not be appropriate. 47 48 The p-value for Test 2 is greater than .1. A homogeneous 49 variance model appears to be appropriate here. 50 51 The p-value for Test 3 is greater than .1. The modeled 52 variance appears to be appropriate here. 53 54 Degrees of freedom for Test 7a are less than or equal to 0. 55 The Chi-Square test for fit is not valid. 56 57 58 Benchmark Dose Computations: 59 60 Specified Effect = 1.000000 61 62 Risk Type = Estimated standard deviations from control 63 64 Confidence Level = 0.950000 65 66 BMD = Not_Computed 67 68 BMDL = 0 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-137 1 

## E.2.20.6. Figure for Unrestricted Model: Hill , Constant Variance, n Unrestricted 2

0 5 10 15 20 25 30 35

0 1e+015 2e+015 3e+015 4e+015 5e+015Mean Response

dose Hill Model with 0.95 Confidence Level

13:50 11/16 2009 BMDBMDL Hill

3 4 5 

## E.2.20.7. Output File for Unrestricted Model: Hil l, Consta nt Variance, n Unrestricted 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\HillConst_Unrest_BMR1_Li_Estradiol_3d.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AD\Blood\HillConst_Unrest_BMR1_Li_Estradiol_3d.plt 13 Mon Nov 16 13:50:08 2009 14

==================================================================== 15 16 Figure 3, 3-day estradiol 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 rho is set to 0 27 Power parameter is not restricted 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-138 1 2 Default Initial Parameter Values 3 alpha = 267.211 4 rho = 0 Specified 5 intercept = 10.1682 6 v = 14.5566 7 n = 0.0272301 8 k = 109.605 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -rho 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 alpha intercept v n k 18 19 alpha 1 9.3e-007 NA 0.00038 NA 20 21 intercept 9.3e-007 1 NA 0.047 NA 22 23
v NA NA NA NA NA 24 25 n 0.00038 0.047 NA 1 NA 26 27 k NA NA NA NA NA 28 29 30 NA - This parameter's variance has been estimated as zero or less. 31 THE MODEL HAS PROBABLY NOT CONVERGED!!! 32 33 34 35 Parameter Estimates 36 37 95.0% Wald Confidence Interval 38 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 39 alpha 246.316 NA NA NA 40 intercept 10.168 NA NA NA 41 v 23.0562 NA NA NA 42 n 0.030228 NA NA NA 43 k 68005.7 NA NA NA 44 45 At least some variance estimates are negative. 46 THIS USUALLY MEANS THE MODEL HAS NOT CONVERGED! 47 Try again from another starting point. 48 49 50 51 Table of Data and Estimated Values of Interest 52 53 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 54

------ --- -------- -------- ----------- ----------- ---------- 55 56 0 10 10.2 10.2 12.2 15.7 4.22e-005 57 87.49 10 19.9 20.5 20 15.7 -0.127 58 1564 10 24.7 21 14.6 15.7 0.743 59 2823 10 18.1 21.1 17.6 15.7 -0.615 60 61 Degrees of freedom for Test A3 vs fitted <= 0 62 63 64 65 Model Descriptions for likelihoods calculated 66 67 68 Model A1: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-139 1 Model A2: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = Sigma(i)^2 3 4 Model A3: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = Sigma^2 6 Model A3 uses any fixed variance parameters that 7 were specified by the user 8 9 Model R: Yi = Mu + e(i) 10 Var{e(i)} = Sigma^2 11 12 13 Likelihoods of Interest 14 15 Model Log(likelihood) # Param's AIC 16 A1 -129.653527 5 269.307054 17 A2 -128.294657 8 272.589314 18 A3 -129.653527 5 269.307054 19 fitted -130.132269 5 270.264537 20 R -131.819169 2 267.638338 21 22 23 Explanation of Tests 24 25 Test 1: Do responses and/or variances differ among Dose levels? 26 (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A1 vs A2) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 30 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 31 32 Tests of Interest 33 34 Test -2*log(Likelihood Ratio) Test df p-value 35 36 Test 1 7.04902 6 0.3163 37 Test 2 2.71774 3 0.4372 38 Test 3 2.71774 3 0.4372 39 Test 4 0.957483 0 NA 40 41 The p-value for Test 1 is greater than .05. There may not be a 42 diffence between responses and/or variances among the dose levels 43 Modelling the data with a dose/response curve may not be appropriate 44 45 The p-value for Test 2 is greater than .1. A homogeneous variance 46 model appears to be appropriate here 47 48 49 The p-value for Test 3 is greater than .1. The modeled variance appears 50 to be appropriate here 51 52 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 53 test for fit is not valid 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 1 59 60 Risk Type = Estimated standard deviations from the control mean 61 62 Confidence level = 0.95 63 64 BMD = 5.11313e+015 65 66 BMDL = 5.11313e+015 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-140 1 

## E.2.20.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 2

-5 0 5 10 15 20 25 30 35 40

0 500 1000 1500 2000 2500Mean Response

dose Power Model

13:50 11/16 2009 Power

3 4 5 

## E.2.20.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\PowerConst_Unrest_BMR1_Li_Estradiol_3d.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AD\Blood\PowerConst_Unrest_BMR1_Li_Estradiol_3d.plt 13 Mon Nov 16 13:50:08 2009 14

==================================================================== 15 16 Figure 3, 3-day estradiol 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = control + slope * dose^power 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 rho is set to 0 27 The power is not restricted 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-141 1 2 Default Initial Parameter Values 3 alpha = 267.211 4 rho = 0 Specified 5 control = 10.1682 6 slope = 10.1311 7 power = 0.00388985 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -rho 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 alpha control slope power 17 18 alpha 1 3.9e-009 -6.4e-009 1.1e-008 19 20 control 3.9e-009 1 -0.4 0.038 21 22 slope -6.4e-009 -0.4 1 -0.91 23 24 power 1.1e-008 0.038 -0.91 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 alpha 246.319 55.0786 138.367 354.271 33 control 10.1675 4.96274 0.440676 19.8943 34 slope 9.71449 12.3808 -14.5514 33.9803 35 power 0.0151875 0.171197 -0.320352 0.350727 36 37 38 39 Table of Data and Estimated Values of Interest 40 41 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 42

------ --- -------- -------- ----------- ----------- ---------- 43 44 0 10 10.2 10.2 12.2 15.7 0.000148 45 87.49 10 19.9 20.6 20 15.7 -0.132 46 1564 10 24.7 21 14.6 15.7 0.744 47 2823 10 18.1 21.1 17.6 15.7 -0.612 48 49 50 51 Model Descriptions for likelihoods calculated 52 53 54 Model A1: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma^2 56 57 Model A2: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma(i)^2 59 60 Model A3: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 Model A3 uses any fixed variance parameters that 63 were specified by the user 64 65 Model R: Yi = Mu + e(i) 66 Var{e(i)} = Sigma^2 67 68 69 Likelihoods of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-142 1 Model Log(likelihood) # Param's AIC 2 A1 -129.653527 5 269.307054 3 A2 -128.294657 8 272.589314 4 A3 -129.653527 5 269.307054 5 fitted -130.132565 4 268.265130 6 R -131.819169 2 267.638338 7 8 9 Explanation of Tests 10 11 Test 1: Do responses and/or variances differ among Dose levels? 12 (A2 vs. R) 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 17 18 Tests of Interest 19 20 Test -2*log(Likelihood Ratio) Test df p-value 21 22 Test 1 7.04902 6 0.3163 23 Test 2 2.71774 3 0.4372 24 Test 3 2.71774 3 0.4372 25 Test 4 0.958076 1 0.3277 26 27 The p-value for Test 1 is greater than .05. There may not be a 28 diffence between responses and/or variances among the dose levels 29 Modelling the data with a dose/response curve may not be appropriate 30 31 The p-value for Test 2 is greater than .1. A homogeneous variance 32 model appears to be appropriate here 33 34 35 The p-value for Test 3 is greater than .1. The modeled variance appears 36 to be appropriate here 37 38 The p-value for Test 4 is greater than .1. The model chosen seems 39 to adequately describe the data 40 41 42 Benchmark Dose Computation 43 44 Specified effect = 1 45 46 Risk Type = Estimated standard deviations from the control mean 47 48 Confidence level = 0.95 49 50 BMD = 5.21395e+013 51 52 53 BMDL computation failed. 54 55 56

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-143 E.2.21. Li et al. (2006): Hormone Levels (Progesterone) 1 

## E.2.21.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2)

c 2 0.00 14.72 0.00 327.86 2.0E+03 7.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.00 14.72 0.00 327.86 2.0E+03 7.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.00 0.60 0.44 315.74 8.3E+00 1.4E-02 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.00 0.60 N/A 317.74 2.0E+01 3.5E-02 nonconstant variance, power restricted ≥ 1
exponential (M5) d 0 0.00 0.60 N/A 317.74 2.0E+01 3.5E-02 nonconstant variance, power unrestricted

Hill 1 0.00 0.60 0.44 315.73 9.0E-01 6.3E-03 nonconstant variance, n restricted >1, bound hit

Hill d 0 0.00 0.62 NA 317.75 1.9E-01 error nonconstant variance, n unrestricted

linear 2 0.00 15.21 0.00 328.35 2.4E+03 1.3E+03 nonconstant variance

polynomial 2 0.00 15.21 0.00 328.35 2.4E+03 1.3E+03 nonconstant variance

power 2 0.00 15.21 0.00 328.35 2.4E+03 1.4E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 1 0.00 0.55 0.46 315.69 1.4E-39 1.4E-39 nonconstant variance, power unrestricted
exponential (M2) 2 0.00 2.22 0.33 327.49 2.8E+03 1.1E+03 constant variance, power restricted ≥ 1
exponential (M3) 2 0.00 2.22 0.33 327.49 2.8E+03 1.1E+03 constant variance, power restricted ≥ 1
exponential (M4) 1 0.00 0.02 0.88 327.29 2.0E+02 8.3E-01 constant variance, power restricted ≥ 1
exponential (M5) 1 0.00 0.02 0.88 327.29 2.0E+02 7.8E-01 constant variance, power restricted ≥ 1
exponential (M5) 1 0.00 0.02 0.88 327.29 2.0E+02 7.8E-01 constant variance, power unrestricted

Hill 0 0.00 0.02 NA 329.29 1.3E+02 1.6E-09 constant variance, n restricted >1

Hill 0 0.00 0.00 NA 329.27 5.5E+02 1.0E-03 constant variance, n unrestricted

linear 2 0.00 2.72 0.26 327.99 2.9E+03 1.7E+03 constant variance

polynomial 2 0.00 2.72 0.26 327.99 2.9E+03 1.7E+03 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-144 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

power 2 0.00 2.72 0.26 327.99 2.9E+03 1.7E+03 constant variance, power restricted ≥ 1, bound hit

power 1 0.00 0.02 0.90 327.28 8.1E+02 2.8E-12 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.2.21.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 3 

## Restricted ≥ 1 4

-10 0 10 20 30 40 50 60 70 80

0 500 1000 1500 2000 2500Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

13:48 11/16 2009 BMD BMDL Exponential

5 6 7 

## E.2.21.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 8 

## Restricted ≥ 1 9
10 11

==================================================================== 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 13 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_BMR1_Li_Progesterone_3d.(d) 14 Gnuplot Plotting File: 15 Mon Nov 16 13:48:35 2009 16

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-145 ==================================================================== 1 2 Figure 4, 3-day progesterone 3

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4 5 The form of the response function by Model: 6 Model 2: Y[dose] = a * exp{sign * b * dose} 7 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 8 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 9 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 10 11 Note: Y[dose] is the median response for exposure = dose; 12 sign = +1 for increasing trend in data; 13 sign = -1 for decreasing trend. 14 15 Model 2 is nested within Models 3 and 4. 16 Model 3 is nested within Model 5. 17 Model 4 is nested within Model 5. 18 19 20 Dependent variable = Mean 21 Independent variable = Dose 22 Data are assumed to be distributed: normally 23 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 24 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 25 26 Total number of dose groups = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 MLE solution provided: Exact 33 34 35 Initial Parameter Values 36 37 Variable Model 2 38

-------- -------- 39 lnalpha 15.2703 40 rho -2.36741 41 a 68.5132 42 b 0.00136853 43 c 0.350182 44 d 1 45 46 47 48 Parameter Estimates 49 50 Variable Model 2 51

-------- ------- 52 lnalpha 19.9572 53 rho -3.64854 54 a 65.2616 55 b 0.0274418 56 c 0.490738 57 d 1.59344 58 59 60 Table of Stats From Input Data 61 62 Dose N Obs Mean Obs Std Dev 63

----- --- ---------- ------------- 64 0 10 65.25 11.1 65 87.49 10 43.36 40.48 66 1564 10 27.46 33.3 67 2823 10 25.19 43.75 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-146 Estimated Values of Interest 1 2 Dose Est Mean Est Std Scaled Residual 3

------ ---------- --------- ---------------- 4 0 55.31 28.9 1.088 5 87.49 53.54 29.21 -1.102 6 1564 30.93 34.87 -0.314 7 2823 19.36 40.57 0.4542 8 9 10 11 Other models for which likelihoods are calculated: 12 13 Model A1: Yij = Mu(i) + e(ij) 14 Var{e(ij)} = Sigma^2 15 16 Model A2: Yij = Mu(i) + e(ij) 17 Var{e(ij)} = Sigma(i)^2 18 19 Model A3: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 21 22 Model R: Yij = Mu + e(i) 23 Var{e(ij)} = Sigma^2 24 25 26 Likelihoods of Interest 27 28 Model Log(likelihood) DF AIC 29

------- ----------------- ---- ------------ 30 A1 -159.6327 5 329.2653 31 A2 -151.8128 8 319.6255 32 A3 -152.5679 6 317.1358 33 R -163.9025 2 331.805 34 2 -159.928 4 327.856 35 36 37 Additive constant for all log-likelihoods = -36.76. This constant added to the 38 above values gives the log-likelihood including the term that does not 39 depend on the model parameters. 40 41 42 Explanation of Tests 43 44 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 45 Test 2: Are Variances Homogeneous? (A2 vs. A1) 46 Test 3: Are variances adequately modeled? (A2 vs. A3) 47 Test 4: Does Model 2 fit the data? (A3 vs. 2) 48 49 50 Tests of Interest 51 52 Test -2*log(Likelihood Ratio) D. F. p-value 53

-------- ------------------------ ------ -------------- 54 Test 1 24.18 6 0.000484 55 Test 2 15.64 3 0.001344 56 Test 3 1.51 2 0.4699 57 Test 4 14.72 2 0.0006361 58 59 60 The p-value for Test 1 is less than .05. There appears to be a 61 difference between response and/or variances among the dose 62 levels, it seems appropriate to model the data. 63 64 The p-value for Test 2 is less than .1. A non-homogeneous 65 variance model appears to be appropriate. 66 67 The p-value for Test 3 is greater than .1. The modeled 68 variance appears to be appropriate here. 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-147 The p-value for Test 4 is less than .1. Model 2 may not adequately 1 describe the data; you may want to consider another model. 2 3 4 Benchmark Dose Computations: 5 6 Specified Effect = 1.000000 7 8 Risk Type = Estimated standard deviations from control 9 10 Confidence Level = 0.950000 11 12 BMD = 1988.62 13 14 BMDL = 712.505 15 16 17 

## E.2.21.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 18 

## Unrestricted 19

-10 0 10 20 30 40 50 60 70 80

0 500 1000 1500 2000 2500Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:48 11/16 2009 BMD BMDL Exponential

20 21 22 

## E.2.21.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 23 

## Power Unrestricted 24
25 26

==================================================================== 27 Exponential Model. (Version: 1.5; Date: 4/23/2009) 28 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_Unrest_BMR1_Li_Progesterone_3d.(d) 29 Gnuplot Plotting File: 30 Mon Nov 16 13:48:36 2009 31

==================================================================== 32 33 Figure 4, 3-day progesterone 34

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-148 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1 2 The form of the response function by Model: 3 Model 2: Y[dose] = a * exp{sign * b * dose} 4 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 5 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 6 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 7 8 Note: Y[dose] is the median response for exposure = dose; 9 sign = +1 for increasing trend in data; 10 sign = -1 for decreasing trend. 11 12 Model 2 is nested within Models 3 and 4. 13 Model 3 is nested within Model 5. 14 Model 4 is nested within Model 5. 15 16 17 Dependent variable = Mean 18 Independent variable = Dose 19 Data are assumed to be distributed: normally 20 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 21 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 22 23 Total number of dose groups = 4 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 MLE solution provided: Exact 30 31 32 Initial Parameter Values 33 34 Variable Model 5 35

-------- -------- 36 lnalpha 15.2703 37 rho -2.36741 38 a 68.5132 39 b 0.00136853 40 c 0.350182 41 d 1 42 43 44 45 Parameter Estimates 46 47 Variable Model 5 48

-------- ------- 49 lnalpha 19.9572 50 rho -3.64854 51 a 65.2616 52 b 0.0274418 53 c 0.490738 54 d 1.59344 55 56 57 Table of Stats From Input Data 58 59 Dose N Obs Mean Obs Std Dev 60

----- --- ---------- ------------- 61 0 10 65.25 11.1 62 87.49 10 43.36 40.48 63 1564 10 27.46 33.3 64 2823 10 25.19 43.75 65 66 67 Estimated Values of Interest 68 69 Dose Est Mean Est Std Scaled Residual 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-149 ------ ---------- --------- ---------------- 1 0 65.26 10.55 -0.003266 2 87.49 32.61 37.4 0.909 3 1564 32.03 38.65 -0.3733 4 2823 32.03 38.65 -0.5591 5 6 7 8 Other models for which likelihoods are calculated: 9 10 Model A1: Yij = Mu(i) + e(ij) 11 Var{e(ij)} = Sigma^2 12 13 Model A2: Yij = Mu(i) + e(ij) 14 Var{e(ij)} = Sigma(i)^2 15 16 Model A3: Yij = Mu(i) + e(ij) 17 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 18 19 Model R: Yij = Mu + e(i) 20 Var{e(ij)} = Sigma^2 21 22 23 Likelihoods of Interest 24 25 Model Log(likelihood) DF AIC 26

------- ----------------- ---- ------------ 27 A1 -159.6327 5 329.2653 28 A2 -151.8128 8 319.6255 29 A3 -152.5679 6 317.1358 30 R -163.9025 2 331.805 31 5 -152.8697 6 317.7393 32 33 34 Additive constant for all log-likelihoods = -36.76. This constant added to the 35 above values gives the log-likelihood including the term that does not 36 depend on the model parameters. 37 38 39 Explanation of Tests 40 41 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 42 Test 2: Are Variances Homogeneous? (A2 vs. A1) 43 Test 3: Are variances adequately modeled? (A2 vs. A3) 44 45 Test 7a: Does Model 5 fit the data? (A3 vs 5) 46 47 48 Tests of Interest 49 50 Test -2*log(Likelihood Ratio) D. F. p-value 51

-------- ------------------------ ------ -------------- 52 Test 1 24.18 6 0.000484 53 Test 2 15.64 3 0.001344 54 Test 3 1.51 2 0.4699 55 Test 7a 0.6035 0 N/A 56 57 58 The p-value for Test 1 is less than .05. There appears to be a 59 difference between response and/or variances among the dose 60 levels, it seems appropriate to model the data. 61 62 The p-value for Test 2 is less than .1. A non-homogeneous 63 variance model appears to be appropriate. 64 65 The p-value for Test 3 is greater than .1. The modeled 66 variance appears to be appropriate here. 67 68 Degrees of freedom for Test 7a are less than or equal to 0. 69 The Chi-Square test for fit is not valid. 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-150 1 2 Benchmark Dose Computations: 3 4 Specified Effect = 1.000000 5 6 Risk Type = Estimated standard deviations from control 7 8 Confidence Level = 0.950000 9 10 BMD = 19.9163 11 12 BMDL = 0.03489 13 14 15 

## E.2.21.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 16

-10 0 10 20 30 40 50 60 70 80

0 500 1000 1500 2000 2500Mean Response

dose Hill Model

13:48 11/16 2009 BMD Hill

17 18 19 

## E.2.21.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 20
21 22

==================================================================== 23 Hill Model. (Version: 2.14; Date: 06/26/2008) 24 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_Li_Progesterone_3d.(d) 25 Gnuplot Plotting File: 26 C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_Li_Progesterone_3d.plt 27 Mon Nov 16 13:48:37 2009 28

==================================================================== 29 30 Figure 4, 3-day progesterone 31

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 32 33 The form of the response function is: 34 35 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-151 1 2 Dependent variable = Mean 3 Independent variable = Dose 4 Power parameter is not restricted 5 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 6 7 Total number of dose groups = 4 8 Total number of records with missing values = 0 9 Maximum number of iterations = 250 10 Relative Function Convergence has been set to: 1e-008 11 Parameter Convergence has been set to: 1e-008 12 13 14 15 Default Initial Parameter Values 16 lalpha = 7.08699 17 rho = 0 18 intercept = 65.2507 19 v = -40.059 20 n = 4.4725 21 k = 80.0627 22 23 24 Asymptotic Correlation Matrix of Parameter Estimates 25 26 lalpha rho intercept v n k 27 28 lalpha 1 -1 -0.17 0.84 6e-008 1.1e-008 29 30 rho -1 1 0.19 -0.82 -5.6e-008 -1e-008 31 32 intercept -0.17 0.19 1 -0.43 1e-008 1.9e-009 33 34 v 0.84 -0.82 -0.43 1 1.4e-009 2.6e-010 35 36 n 6e-008 -5.6e-008 1e-008 1.4e-009 1 1.1 37 38 k 1.1e-008 -1e-008 1.9e-009 2.6e-010 1.1 1 39 40 41 42 Parameter Estimates 43 44 95.0% Wald Confidence Interval 45 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 46 lalpha 19.8437 5.41703 9.22649 30.4609 47 rho -3.62235 1.35086 -6.27 -0.974711 48 intercept 65.2507 3.33016 58.7237 71.7777 49 v -33.2448 7.73875 -48.4125 -18.0772 50 n 5.43075 5.32553e+006 -1.04378e+007 1.04378e+007 51 k 0.22398 1.45115e+006 -2.84421e+006 2.84421e+006 52 53 54 55 Table of Data and Estimated Values of Interest 56 57 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 58

------ --- -------- -------- ----------- ----------- ---------- 59 60 0 10 65.3 65.3 11.1 10.5 -7.47e-007 61 87.49 10 43.4 32 40.5 38.3 0.939 62 1564 10 27.5 32 33.3 38.3 -0.375 63 2823 10 25.2 32 43.7 38.3 -0.563 64 65 Degrees of freedom for Test A3 vs fitted <= 0 66 67 68 69 Model Descriptions for likelihoods calculated 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-152 1 2 Model A1: Yij = Mu(i) + e(ij) 3 Var{e(ij)} = Sigma^2 4 5 Model A2: Yij = Mu(i) + e(ij) 6 Var{e(ij)} = Sigma(i)^2 7 8 Model A3: Yij = Mu(i) + e(ij) 9 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 10 Model A3 uses any fixed variance parameters that 11 were specified by the user 12 13 Model R: Yi = Mu + e(i) 14 Var{e(i)} = Sigma^2 15 16 17 Likelihoods of Interest 18 19 Model Log(likelihood) # Param's AIC 20 A1 -159.632675 5 329.265349 21 A2 -151.812765 8 319.625529 22 A3 -152.567898 6 317.135795 23 fitted -152.876553 6 317.753105 24 R -163.902499 2 331.804998 25 26 27 Explanation of Tests 28 29 Test 1: Do responses and/or variances differ among Dose levels? 30 (A2 vs. R) 31 Test 2: Are Variances Homogeneous? (A1 vs A2) 32 Test 3: Are variances adequately modeled? (A2 vs. A3) 33 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 34 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 35 36 Tests of Interest 37 38 Test -2*log(Likelihood Ratio) Test df p-value 39 40 Test 1 24.1795 6 0.000484 41 Test 2 15.6398 3 0.001344 42 Test 3 1.51027 2 0.4699 43 Test 4 0.61731 0 NA 44 45 The p-value for Test 1 is less than .05. There appears to be a 46 difference between response and/or variances among the dose levels 47 It seems appropriate to model the data 48 49 The p-value for Test 2 is less than .1. A non-homogeneous variance 50 model appears to be appropriate 51 52 The p-value for Test 3 is greater than .1. The modeled variance appears 53 to be appropriate here 54 55 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 56 test for fit is not valid 57 58 59 Benchmark Dose Computation 60 61 Specified effect = 1 62 63 Risk Type = Estimated standard deviations from the control mean 64 65 Confidence level = 0.95 66 67 BMD = 0.19442 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-153 BMDL computation failed. 1 2 3 

## E.2.21.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 4

-10 0 10 20 30 40 50 60 70 80

0 500 1000 1500 2000 2500Mean Response

dose Power Model with 0.95 Confidence Level

13:48 11/16 2009 BMDBMDL Power

5 6 7 

## E.2.21.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 8 

## Unrestricted 9
10 11

==================================================================== 12 Power Model. (Version: 2.15; Date: 04/07/2008) 13 Input Data File: C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_Li_Progesterone_3d.(d) 14 Gnuplot Plotting File: 15 C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_Li_Progesterone_3d.plt 16 Mon Nov 16 13:48:37 2009 17

==================================================================== 18 19 Figure 4, 3-day progesterone 20

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 21 22 The form of the response function is: 23 24 Y[dose] = control + slope * dose^power 25 26 27 Dependent variable = Mean 28 Independent variable = Dose 29 The power is not restricted 30 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 31 32 Total number of dose groups = 4 33 Total number of records with missing values = 0 34 Maximum number of iterations = 250 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-154 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 lalpha = 7.08699 7 rho = 0 8 control = 65.2507 9 slope = -9.66956 10 power = 0.178886 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 lalpha rho control slope power 16 17 lalpha 1 -1 -0.17 0.57 0.15 18 19 rho -1 1 0.19 -0.55 -0.13 20 21 control -0.17 0.19 1 -0.22 0.02 22 23 slope 0.57 -0.55 -0.22 1 0.84 24 25 power 0.15 -0.13 0.02 0.84 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence Interval 32 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 33 lalpha 20.0647 5.5864 9.11557 31.0139 34 rho -3.67315 1.39112 -6.39969 -0.946614 35 control 65.2739 3.34327 58.7212 71.8266 36 slope -30.3669 13.1525 -56.1453 -4.58852 37 power 0.0117985 0.0472043 -0.0807202 0.104317 38 39 40 41 Table of Data and Estimated Values of Interest 42 43 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 44

------ --- -------- -------- ----------- ----------- ---------- 45 46 0 10 65.3 65.3 11.1 10.6 -0.00695 47 87.49 10 43.4 33.3 40.5 36.5 0.876 48 1564 10 27.5 32.2 33.3 38.8 -0.382 49 2823 10 25.2 31.9 43.7 39.3 -0.541 50 51 52 53 Model Descriptions for likelihoods calculated 54 55 56 Model A1: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 59 Model A2: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma(i)^2 61 62 Model A3: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 64 Model A3 uses any fixed variance parameters that 65 were specified by the user 66 67 Model R: Yi = Mu + e(i) 68 Var{e(i)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-155 1 Likelihoods of Interest 2 3 Model Log(likelihood) # Param's AIC 4 A1 -159.632675 5 329.265349 5 A2 -151.812765 8 319.625529 6 A3 -152.567898 6 317.135795 7 fitted -152.844599 5 315.689197 8 R -163.902499 2 331.804998 9 10 11 Explanation of Tests 12 13 Test 1: Do responses and/or variances differ among Dose levels? 14 (A2 vs. R) 15 Test 2: Are Variances Homogeneous? (A1 vs A2) 16 Test 3: Are variances adequately modeled? (A2 vs. A3) 17 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 18 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 19 20 Tests of Interest 21 22 Test -2*log(Likelihood Ratio) Test df p-value 23 24 Test 1 24.1795 6 0.000484 25 Test 2 15.6398 3 0.001344 26 Test 3 1.51027 2 0.4699 27 Test 4 0.553402 1 0.4569 28 29 The p-value for Test 1 is less than .05. There appears to be a 30 difference between response and/or variances among the dose levels 31 It seems appropriate to model the data 32 33 The p-value for Test 2 is less than .1. A non-homogeneous variance 34 model appears to be appropriate 35 36 The p-value for Test 3 is greater than .1. The modeled variance appears 37 to be appropriate here 38 39 The p-value for Test 4 is greater than .1. The model chosen seems 40 to adequately describe the data 41 42 43 Benchmark Dose Computation 44 45 Specified effect = 1 46 47 Risk Type = Estimated standard deviations from the control mean 48 49 Confidence level = 0.95 50 51 BMD = 1.42955e-039 52 53 54 BMDL = 1.42955e-039 55 56 57 58

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-156 E.2.22. Markowski et al. (2001): FR10 Run Opportunities 1 

## E.2.22.1. Summary Table of BMDS Modeling Results 2

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

exponential (M2) c 2 0.304 117.151 6.769E+03 2.281E+03

exponential (M3) 2 0.304 117.151 6.769E+03 2.281E+03 power bound hit

exponential (M4) 1 0.370 117.574 2.732E+03 1.151E+01

exponential (M5) 0 N/A 118.918 1.834E+03 9.541E-03

Hill 0 NA 118.918 1.428E+03 1.932E-04

linear 2 0.226 117.744 8.734E+03 4.535E+03

polynomial 2 0.226 117.744 8.734E+03 4.535E+03

power 2 0.226 117.744 8.734E+03 4.535E+03 power bound hit

a Non-constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix 3 

## E.2.22.2. Figure for Selected Model: Exponential (M2) 4

0 5 10 15 20

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

10:28 01/12 2010 BMD BMDL Exponential

5 

## Markowski et al., 2001 : FR10 run opportunities 6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-157 E.2.22.3. Output File for Selected Model: Exponential (M2) 1 

## Markowski et al., 2001 : FR10 run opportunities 2

==================================================================== 3 Exponential Model. (Version: 1.61; Date: 7/24/2009) 4 Input Data File: C:\1\Blood\33_Markowski_2001_FR10_run_opp_ExpCV_BMR1.(d) 5 Gnuplot Plotting File: 6 Tue Jan 12 10:28:14 2010 7

==================================================================== 8 9 Table 3 10

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11 12 The form of the response function by Model: 13 Model 2: Y[dose] = a * exp{sign * b * dose} 14 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 15 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 16 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 17 18 Note: Y[dose] is the median response for exposure = dose; 19 sign = +1 for increasing trend in data; 20 sign = -1 for decreasing trend. 21 22 Model 2 is nested within Models 3 and 4. 23 Model 3 is nested within Model 5. 24 Model 4 is nested within Model 5. 25 26 27 Dependent variable = Mean 28 Independent variable = Dose 29 Data are assumed to be distributed: normally 30 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 31 rho is set to 0. 32 A constant variance model is fit. 33 34 Total number of dose groups = 4 35 Total number of records with missing values = 0 36 Maximum number of iterations = 250 37 Relative Function Convergence has been set to: 1e-008 38 Parameter Convergence has been set to: 1e-008 39 40 MLE solution provided: Exact 41 42 43 Initial Parameter Values 44 45 Variable Model 2 46

-------- -------- 47 lnalpha 3.5321 48 rho(S) 0 49 a 6.7793 50 b 7.36629e-005 51 c 0 52 d 1 53 54 (S) = Specified 55 56 57 58 Parameter Estimates 59 60 Variable Model 2 61

-------- ------- 62 lnalpha 3.63129 63 rho 0 64 a 12.2912 65 b 0.00010238 66 c 0 67 d 1 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-158 1 2 Table of Stats From Input Data 3 4 Dose N Obs Mean Obs Std Dev 5

----- --- ---------- ------------- 6 0 7 13.29 8.65 7 1234 4 11.25 5.56 8 3184 6 5.75 3.53 9 8152 7 7 6.01 10 11 12 Estimated Values of Interest 13 14 Dose Est Mean Est Std Scaled Residual 15

------ ---------- --------- ---------------- 16 0 12.29 6.145 0.43 17 1234 10.83 6.145 0.1359 18 3184 8.872 6.145 -1.245 19 8152 5.335 6.145 0.7168 20 21 22 23 Other models for which likelihoods are calculated: 24 25 Model A1: Yij = Mu(i) + e(ij) 26 Var{e(ij)} = Sigma^2 27 28 Model A2: Yij = Mu(i) + e(ij) 29 Var{e(ij)} = Sigma(i)^2 30 31 Model A3: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 33 34 Model R: Yij = Mu + e(i) 35 Var{e(ij)} = Sigma^2 36 37 38 Likelihoods of Interest 39 40 Model Log(likelihood) DF AIC 41

------- ----------------- ---- ------------ 42 A1 -54.38526 5 118.7705 43 A2 -51.88568 8 119.7714 44 A3 -54.38526 5 118.7705 45 R -57.45429 2 118.9086 46 2 -55.57543 3 117.1509 47 48 49 Additive constant for all log-likelihoods = -22.05. This constant added to the 50 above values gives the log-likelihood including the term that does not 51 depend on the model parameters. 52 53 54 Explanation of Tests 55 56 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 57 Test 2: Are Variances Homogeneous? (A2 vs. A1) 58 Test 3: Are variances adequately modeled? (A2 vs. A3) 59 Test 4: Does Model 2 fit the data? (A3 vs. 2) 60 61 62 Tests of Interest 63 64 Test -2*log(Likelihood Ratio) D. F. p-value 65

-------- ------------------------ ------ -------------- 66 Test 1 11.14 6 0.08423 67 Test 2 4.999 3 0.1719 68 Test 3 4.999 3 0.1719 69 Test 4 2.38 2 0.3042 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-159 1 2 The p-value for Test 1 is greater than .05. There may not be a 3 diffence between responses and/or variances among the dose levels 4 Modelling the data with a dose/response curve may not be appropriate. 5 6 The p-value for Test 2 is greater than .1. A homogeneous 7 variance model appears to be appropriate here. 8 9 The p-value for Test 3 is greater than .1. The modeled 10 variance appears to be appropriate here. 11 12 The p-value for Test 4 is greater than .1. Model 2 seems 13 to adequately describe the data. 14 15 16 Benchmark Dose Computations: 17 18 Specified Effect = 1.000000 19 20 Risk Type = Estimated standard deviations from control 21 22 Confidence Level = 0.950000 23 24 BMD = 6769.45 25 26 BMDL = 2280.85 27 28 29

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-160 E.2.23. Markowski et al. (2001): FR2 Revolutions 1 

## E.2.23.1. Summary Table of BMDS Modeling Results 2

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

power, unrestricted 1 0.053 216.124 1.570E+04 3.350E+02 power unrestricted

exponential (M2) 2 0.236 217.220 6.704E+03 2.553E+03

exponential (M3) 2 0.236 217.220 6.704E+03 2.553E+03 power bound hit

exponential (M4) 1 0.262 217.588 2.702E+03 1.655E+01

exponential (M5) c 0 N/A 218.532 1.922E+03 7.384E+02

Hill 1 0.654 216.532 1.458E+03 4.757E+02 n lower bound hit

linear 2 0.180 217.765 8.361E+03 4.426E+03

polynomial 2 0.180 217.765 8.361E+03 4.426E+03

Hill, unrestricted 1 0.654 216.532 1.458E+03 error n unrestricted
power, unrestricted d 1 0.161 218.297 4.538E+03 8.152E-12 power unrestricted

a Constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix

d Alternate model, BM DS output also presented in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-161 E.2.23.2. Figure for Selected Model: Exponential (M5) 1

0 50 100 150 200

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:52 01/13 2010 BMD BMDL Exponential

2 3 

## Markowski et al., 2001: FR2 revolutions 4 5 6 

## E.2.23.3. Output File for Selected Model: Exponential (M5) 7 

## Markowski et al., 2001: FR2 revolutions 8

==================================================================== 9 Exponential Model. (Version: 1.61; Date: 7/24/2009) 10 Input Data File: C:\1\Blood\34_Markowski_2001_FR2_rev_ExpCV_1.(d) 11 Gnuplot Plotting File: 12 Wed Jan 13 14:52:52 2010 13

==================================================================== 14 15 Table 3 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function by Model: 19 Model 2: Y[dose] = a * exp{sign * b * dose} 20 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 21 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 22 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 23 24 Note: Y[dose] is the median response for exposure = dose; 25 sign = +1 for increasing trend in data; 26 sign = -1 for decreasing trend. 27 28 Model 2 is nested within Models 3 and 4. 29 Model 3 is nested within Model 5. 30 Model 4 is nested within Model 5. 31 32 33 Dependent variable = Mean 34 Independent variable = Dose 35 Data are assumed to be distributed: normally 36 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 37 rho is set to 0. 38 A constant variance model is fit. 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-162 1 Total number of dose groups = 4 2 Total number of records with missing values = 0 3 Maximum number of iterations = 250 4 Relative Function Convergence has been set to: 1e-008 5 Parameter Convergence has been set to: 1e-008 6 7 MLE solution provided: Exact 8 9 10 Initial Parameter Values 11 12 Variable Model 5 13

-------- -------- 14 lnalpha 7.68046 15 rho(S) 0 16 a 125.255 17 b 0.000305547 18 c 0.429602 19 d 1 20 21 (S) = Specified 22 23 24 25 Parameter Estimates 26 27 Variable Model 5 28

-------- ------- 29 lnalpha 7.68885 30 rho 0 31 a 119.29 32 b 0.000585299 33 c 0.526177 34 d 4.76993 35 36 37 Table of Stats From Input Data 38 39 Dose N Obs Mean Obs Std Dev 40

----- --- ---------- ------------- 41 0 7 119.3 69.9 42 1234 4 108.5 61 43 3184 6 56.5 31.21 44 8152 7 68.14 33.23 45 46 47 Estimated Values of Interest 48 49 Dose Est Mean Est Std Scaled Residual 50

------ ---------- --------- ---------------- 51 0 119.3 46.73 -1.267e-006 52 1234 108.5 46.73 2.704e-006 53 3184 62.77 46.73 -0.3285 54 8152 62.77 46.73 0.3042 55 56 57 58 Other models for which likelihoods are calculated: 59 60 Model A1: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 63 Model A2: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma(i)^2 65 66 Model A3: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 68 69 Model R: Yij = Mu + e(i) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-163 Var{e(ij)} = Sigma^2 1 2 3 Likelihoods of Interest 4 5 Model Log(likelihood) DF AIC 6

------- ----------------- ---- ------------ 7 A1 -104.1655 5 218.331 8 A2 -101.1402 8 218.2803 9 A3 -104.1655 5 218.331 10 R -107.5993 2 219.1985 11 5 -104.2662 5 218.5323 12 13 14 Additive constant for all log-likelihoods = -22.05. This constant added to the 15 above values gives the log-likelihood including the term that does not 16 depend on the model parameters. 17 18 19 Explanation of Tests 20 21 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 22 Test 2: Are Variances Homogeneous? (A2 vs. A1) 23 Test 3: Are variances adequately modeled? (A2 vs. A3) 24 25 Test 7a: Does Model 5 fit the data? (A3 vs 5) 26 27 28 Tests of Interest 29 30 Test -2*log(Likelihood Ratio) D. F. p-value 31

-------- ------------------------ ------ -------------- 32 Test 1 12.92 6 0.04435 33 Test 2 6.051 3 0.1092 34 Test 3 6.051 3 0.1092 35 Test 7a 0.2013 0 N/A 36 37 38 The p-value for Test 1 is less than .05. There appears to be a 39 difference between response and/or variances among the dose 40 levels, it seems appropriate to model the data. 41 42 The p-value for Test 2 is greater than .1. A homogeneous 43 variance model appears to be appropriate here. 44 45 The p-value for Test 3 is greater than .1. The modeled 46 variance appears to be appropriate here. 47 48 Degrees of freedom for Test 7a are less than or equal to 0. 49 The Chi-Square test for fit is not valid. 50 51 52 Benchmark Dose Computations: 53 54 Specified Effect = 1.000000 55 56 Risk Type = Estimated standard deviations from control 57 58 Confidence Level = 0.950000 59 60 BMD = 1921.95 61 62 BMDL = 738.412 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-164 E.2.23.4. Figure for Unrestricted M odel: Po wer, Unrestricted 1

0 50 100 150 200

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

14:52 01/13 2010 BMD BMDL Power

2 3 

## Markowski et al., 2001: FR2 revolutions 4 5 6 

## E.2.23.5. Output for Unrestricted Model: Power, Unrestricted 7 

## Markowski et al., 2001: FR2 revolutions 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\1\Blood\34_Markowski_2001_FR2_rev_PowerCV_Unrest_1.(d) 11 Gnuplot Plotting File: C:\1\Blood\34_Markowski_2001_FR2_rev_PowerCV_Unrest_1.plt 12 Wed Jan 13 14:52:55 2010 13

==================================================================== 14 15 Table 3 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 The power is not restricted 27 A constant variance model is fit 28 29 Total number of dose groups = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 alpha = 2598.74 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-165 rho = 0 Specified 1 control = 119.29 2 slope = -0.0418736 3 power = 0.825655 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -rho 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 alpha control slope power 13 14 alpha 1 3.2e-009 -4.2e-009 -2.8e-009 15 16 control 3.2e-009 1 -0.39 -0.28 17 18 slope -4.2e-009 -0.39 1 0.99 19 20 power -2.8e-009 -0.28 0.99 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 alpha 2350.46 678.52 1020.59 3680.33 29 control 120.079 18.0799 84.6433 155.515 30 slope -3.33162 10.4368 -23.7875 17.1242 31 power 0.318007 0.351246 -0.370423 1.00644 32 33 34 35 Table of Data and Estimated Values of Interest 36 37 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 38

------ --- -------- -------- ----------- ----------- ---------- 39 40 0 7 119 120 69.9 48.5 -0.0431 41 1234 4 109 88 61 48.5 0.844 42 3184 6 56.5 76.8 31.2 48.5 -1.02 43 8152 7 68.1 61.7 33.2 48.5 0.353 44 45 46 47 Model Descriptions for likelihoods calculated 48 49 50 Model A1: Yij = Mu(i) + e(ij) 51 Var{e(ij)} = Sigma^2 52 53 Model A2: Yij = Mu(i) + e(ij) 54 Var{e(ij)} = Sigma(i)^2 55 56 Model A3: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 Model A3 uses any fixed variance parameters that 59 were specified by the user 60 61 Model R: Yi = Mu + e(i) 62 Var{e(i)} = Sigma^2 63 64 65 Likelihoods of Interest 66 67 Model Log(likelihood) # Param's AIC 68 A1 -104.165520 5 218.331040 69 A2 -101.140174 8 218.280349 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-166 A3 -104.165520 5 218.331040 1 fitted -105.148400 4 218.296799 2 R -107.599268 2 219.198536 3 4 5 Explanation of Tests 6 7 Test 1: Do responses and/or variances differ among Dose levels? 8 (A2 vs. R) 9 Test 2: Are Variances Homogeneous? (A1 vs A2) 10 Test 3: Are variances adequately modeled? (A2 vs. A3) 11 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 12 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 13 14 Tests of Interest 15 16 Test -2*log(Likelihood Ratio) Test df p-value 17 18 Test 1 12.9182 6 0.04435 19 Test 2 6.05069 3 0.1092 20 Test 3 6.05069 3 0.1092 21 Test 4 1.96576 1 0.1609 22 23 The p-value for Test 1 is less than .05. There appears to be a 24 difference between response and/or variances among the dose levels 25 It seems appropriate to model the data 26 27 The p-value for Test 2 is greater than .1. A homogeneous variance 28 model appears to be appropriate here 29 30 31 The p-value for Test 3 is greater than .1. The modeled variance appears 32 to be appropriate here 33 34 The p-value for Test 4 is greater than .1. The model chosen seems 35 to adequately describe the data 36 37 38 Benchmark Dose Computation 39 40 Specified effect = 1 41 42 Risk Type = Estimated standard deviations from the control mean 43 44 Confidence level = 0.95 45 46 BMD = 4538.4 47 48 49 BMDL = 8.15173e-012 50

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-167 E.2.24. Markowski et al. (2001): FR5 Run Opp 1 

## E.2.24.1. Summary Table of BMDS Modeling Results 2

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

exponential (M2) 2 0.205 133.194 4.012E+03 1.927E+03

exponential (M3) 2 0.205 133.194 4.012E+03 1.927E+03 power bound hit

exponential (M4) 1 0.253 133.335 1.710E+03 5.425E+02

exponential (M5) 1 0.212 133.587 1.757E+03 5.030E+02 power bound hit

Hill c 1 0.939 132.032 1.366E+03 7.212E+02 n lower bound hit

linear 2 0.122 134.230 5.715E+03 3.500E+03

polynomial 2 0.122 134.230 5.715E+03 3.500E+03

power 2 0.122 134.230 5.715E+03 3.500E+03 power bound hit

Hill, unrestricted 1 0.939 132.032 1.366E+03 6.598E+02 n unrestricted
power, unrestricted d 1 0.134 134.272 2.109E+03 8.152E-12 power unrestricted

a Constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix

d Alternate model, BM DS output also presented in this appendix 3 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-168 E.2.24.2. Figure for Selected Model: Hill 1

5 10 15 20 25 30 35 40

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Hill Model with 0.95 Confidence Level

10:29 01/12 2010 BMD BMDL

Hill

2 3 

## Markowski et al., 2001: FR5 run opportunities 4 5 6 

## E.2.24.3. Output File for Selected Model: Hill 7 

## Markowski et al., 2001: FR5 run opportunities 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\1\Blood\35_Markowski_2001_FR5_run_opp_HillCV_BMR1.(d) 11 Gnuplot Plotting File: C:\1\Blood\35_Markowski_2001_FR5_run_opp_HillCV_BMR1.plt 12 Tue Jan 12 10:29:45 2010 13

==================================================================== 14 15 Table 3 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter restricted to be greater than 1 27 A constant variance model is fit 28 29 Total number of dose groups = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 alpha = 77.4849 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-169 rho = 0 Specified 1 intercept = 26.14 2 v = -13.34 3 n = 2.78062 4 k = 1968.39 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho -n 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha intercept v k 14 15 alpha 1 -1.9e-010 1.7e-008 1.8e-008 16 17 intercept -1.9e-010 1 -0.81 -0.51 18 19 v 1.7e-008 -0.81 1 0.36 20 21 k 1.8e-008 -0.51 0.36 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 64.5863 18.6445 28.0438 101.129 30 intercept 26.14 3.03753 20.1865 32.0935 31 v -13.1569 3.7676 -20.5413 -5.77257 32 n 18 NA 33 k 1332.5 165.441 1008.24 1656.76 34 35 NA - Indicates that this parameter has hit a bound 36 implied by some inequality constraint and thus 37 has no standard error. 38 39 40 41 Table of Data and Estimated Values of Interest 42 43 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 44

------ --- -------- -------- ----------- ----------- ---------- 45 46 0 7 26.1 26.1 12.3 8.04 -3.13e-008 47 1234 4 23.5 23.5 7.04 8.04 -1.71e-008 48 3184 6 12.8 13 6.17 8.04 -0.0558 49 8152 7 13.1 13 7.14 8.04 0.0517 50 51 52 53 Model Descriptions for likelihoods calculated 54 55 56 Model A1: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 59 Model A2: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma(i)^2 61 62 Model A3: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 Model A3 uses any fixed variance parameters that 65 were specified by the user 66 67 Model R: Yi = Mu + e(i) 68 Var{e(i)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-170 1 Likelihoods of Interest 2 3 Model Log(likelihood) # Param's AIC 4 A1 -62.013133 5 134.026266 5 A2 -59.839035 8 135.678070 6 A3 -62.013133 5 134.026266 7 fitted -62.016025 4 132.032049 8 R -67.530040 2 139.060081 9 10 11 Explanation of Tests 12 13 Test 1: Do responses and/or variances differ among Dose levels? 14 (A2 vs. R) 15 Test 2: Are Variances Homogeneous? (A1 vs A2) 16 Test 3: Are variances adequately modeled? (A2 vs. A3) 17 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 18 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 19 20 Tests of Interest 21 22 Test -2*log(Likelihood Ratio) Test df p-value 23 24 Test 1 15.382 6 0.01748 25 Test 2 4.3482 3 0.2262 26 Test 3 4.3482 3 0.2262 27 Test 4 0.00578335 1 0.9394 28 29 The p-value for Test 1 is less than .05. There appears to be a 30 difference between response and/or variances among the dose levels 31 It seems appropriate to model the data 32 33 The p-value for Test 2 is greater than .1. A homogeneous variance 34 model appears to be appropriate here 35 36 37 The p-value for Test 3 is greater than .1. The modeled variance appears 38 to be appropriate here 39 40 The p-value for Test 4 is greater than .1. The model chosen seems 41 to adequately describe the data 42 43 44 Benchmark Dose Computation 45 46 Specified effect = 1 47 48 Risk Type = Estimated standard deviations from the control mean 49 50 Confidence level = 0.95 51 52 BMD = 1366.29 53 54 BMDL = 721.238 55 56 57 58 59

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-171 E.2.24.4. Figure for Unrestricted M odel: Po wer, Unrestricted 1

5 10 15 20 25 30 35 40

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

10:29 01/12 2010 BMD BMDL Power

2 3 

## Markowski et al., 2001: FR5 run opportunities 4 5 6 

## E.2.24.5. Output File for Unrestricted Model: Power, Unrestricted 7 

## Markowski et al., 2001: FR5 run opportunities 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\1\Blood\35_Markowski_2001_FR5_run_opp_PowerCV_Unrest_BMR1.(d) 11 Gnuplot Plotting File: 12 C:\1\Blood\35_Markowski_2001_FR5_run_opp_PowerCV_Unrest_BMR1.plt 13 Tue Jan 12 10:29:46 2010 14

==================================================================== 15 16 Table 3 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = control + slope * dose^power 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 rho is set to 0 27 The power is not restricted 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36 37 38 Default Initial Parameter Values 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-172 alpha = 77.4849 1 rho = 0 Specified 2 control = 26.14 3 slope = -0.00843066 4 power = 0.845567 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha control slope power 14 15 alpha 1 -2e-008 -1e-008 -1.3e-008 16 17 control -2e-008 1 -0.43 -0.34 18 19 slope -1e-008 -0.43 1 0.99 20 21 power -1.3e-008 -0.34 0.99 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 70.905 20.4685 30.7875 111.023 30 control 26.3577 3.12942 20.2242 32.4913 31 slope -0.41863 1.06088 -2.49792 1.66066 32 power 0.392134 0.282163 -0.160895 0.945164 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 7 26.1 26.4 12.3 8.42 -0.0684 42 1234 4 23.5 19.5 7.04 8.42 0.942 43 3184 6 12.8 16.5 6.17 8.42 -1.07 44 8152 7 13.1 12.1 7.14 8.42 0.342 45 46 47 48 Model Descriptions for likelihoods calculated 49 50 51 Model A1: Yij = Mu(i) + e(ij) 52 Var{e(ij)} = Sigma^2 53 54 Model A2: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma(i)^2 56 57 Model A3: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma^2 59 Model A3 uses any fixed variance parameters that 60 were specified by the user 61 62 Model R: Yi = Mu + e(i) 63 Var{e(i)} = Sigma^2 64 65 66 Likelihoods of Interest 67 68 Model Log(likelihood) # Param's AIC 69 A1 -62.013133 5 134.026266 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-173 A2 -59.839035 8 135.678070 1 A3 -62.013133 5 134.026266 2 fitted -63.136095 4 134.272189 3 R -67.530040 2 139.060081 4 5 6 Explanation of Tests 7 8 Test 1: Do responses and/or variances differ among Dose levels? 9 (A2 vs. R) 10 Test 2: Are Variances Homogeneous? (A1 vs A2) 11 Test 3: Are variances adequately modeled? (A2 vs. A3) 12 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 13 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 14 15 Tests of Interest 16 17 Test -2*log(Likelihood Ratio) Test df p-value 18 19 Test 1 15.382 6 0.01748 20 Test 2 4.3482 3 0.2262 21 Test 3 4.3482 3 0.2262 22 Test 4 2.24592 1 0.134 23 24 The p-value for Test 1 is less than .05. There appears to be a 25 difference between response and/or variances among the dose levels 26 It seems appropriate to model the data 27 28 The p-value for Test 2 is greater than .1. A homogeneous variance 29 model appears to be appropriate here 30 31 32 The p-value for Test 3 is greater than .1. The modeled variance appears 33 to be appropriate here 34 35 The p-value for Test 4 is greater than .1. The model chosen seems 36 to adequately describe the data 37 38 39 Benchmark Dose Computation 40 41 Specified effect = 1 42 43 Risk Type = Estimated standard deviations from the control mean 44 45 Confidence level = 0.95 46 47 BMD = 2109.29 48 49 50 BMDL = 8.15175e-012 51

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-174 E.2.25. Mietinnin et al. (2006): Ca riogenic Lesions in Pups 1 

## E.2.25.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 pValue a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

gamma 3 0.410 162.281 2.689E+03 1.494E+03 power bound hit

logistic 3 0.371 162.518 3.248E+03 1.937E+03

log-logistic b 3 0.603 161.291 1.129E+03 4.091E+02 slope bound hit
log-probit, unrestricted 2 0.732 161.972 5.141E+01 error slope unrestricted
multistage, 4- degree 3 0.410 162.281 2.689E+03 1.494E+03 final ß=0

probit 3 0.350 162.656 3.596E+03 2.284E+03

Weibull 3 0.410 162.281 2.689E+03 1.494E+03 power bound hit
log-logistic, unrestricted c 2 0.728 161.983 3.912E+01 error slope unrestricted

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model, BMDS output presented in this appendix

c Alternate model, BMDS output al so presented in this appendix 3 

## E.2.25.2. Figure for Selected Model: Log-Logistic 4

0.4 0.5 0.6 0.7 0.8 0.9

1

0 5000 10000 15000 20000 25000 30000 35000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

10:30 01/12 2010 BMDL BMD Log-Logistic

5 

## Mietinnen et al., 2006: Cariogenic lesions in pups 6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-175 E.2.25.3. Output File for Selected Model: Log-Logistic 1 

## Mietinnen et al., 2006: Cariogenic lesions in pups 2

==================================================================== 3 Logistic Model. (Version: 2.12; Date: 05/16/2008) 4 Input Data File: C:\1\Blood\36_Miet_06_carc_lesions_LogLogistic_1.(d) 5 Gnuplot Plotting File: C:\1\Blood\36_Miet_06_carc_lesions_LogLogistic_1.plt 6 Tue Jan 12 10:30:32 2010 7

==================================================================== 8 9 Table 2 converting the percentage into the number of animals, and control is Control II from the 10 study. Dose is in ng per kg and is from Table 1 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 16 17 18 Dependent variable = DichEff 19 Independent variable = Dose 20 Slope parameter is restricted as slope >= 1 21 22 Total number of observations = 5 23 Total number of records with missing values = 0 24 Maximum number of iterations = 250 25 Relative Function Convergence has been set to: 1e-008 26 Parameter Convergence has been set to: 1e-008 27 28 29 30 User has chosen the log transformed model 31 32 33 Default Initial Parameter Values 34 background = 0.595238 35 intercept = -9.1668 36 slope = 1 37 38 39 Asymptotic Correlation Matrix of Parameter Estimates 40 41 ( *** The model parameter(s) -slope 42 have been estimated at a boundary point, or have been specified by the user, 43 and do not appear in the correlation matrix ) 44 45 background intercept 46 47 background 1 -0.66 48 49 intercept -0.66 1 50 51 52 53 Parameter Estimates 54 55 95.0% Wald Confidence Interval 56 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 57 background 0.644146 * * * 58 intercept -9.22611 * * * 59 slope 1 * * * 60 61 * - Indicates that this value is not calculated. 62 63 64 65 Analysis of Deviance Table 66 67 Model Log(likelihood) # Param's Deviance Test d.f. P-value 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-176 Full model -77.6769 5 1 Fitted model -78.6457 2 1.93773 3 0.5854 2 Reduced model -83.2067 1 11.0597 4 0.0259 3 4 AIC: 161.291 5 6 7 Goodness of Fit 8 Scaled 9 Dose Est._Prob. Expected Observed Size Residual 10

------------------------------------------------------------------------ 11 0.0000 0.6441 27.054 25.000 42 -0.662 12 1755.6399 0.6966 20.201 23.000 29 1.131 13 4922.4989 0.7603 19.007 19.000 25 -0.003 14 12657.0000 0.8416 20.197 20.000 24 -0.110 15 36874.0000 0.9231 29.540 29.000 32 -0.359 16 17 Chi^2 = 1.86 d.f. = 3 P-value = 0.6025 18 19 20 Benchmark Dose Computation 21 22 Specified effect = 0.1 23 24 Risk Type = Extra risk 25 26 Confidence level = 0.95 27 28 BMD = 1128.77 29 30 BMDL = 409.065 31 32 33 34 35 

## E.2.25.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 36

0.4 0.5 0.6 0.7 0.8 0.9

1

0 5000 10000 15000 20000 25000 30000 35000Fraction Affected

dose Log-Logistic Model

10:30 01/12 2010 Log-Logistic

37 38 

## Mietinnen et al., 2006: Cariogenic lesions in pups 39 40

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-177 1 

## E.2.25.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 2 

## Mietinnen et al., 2006: Cariogenic lesions in pups 3

==================================================================== 4 Logistic Model. (Version: 2.12; Date: 05/16/2008) 5 Input Data File: C:\1\Blood\36_Miet_06_carc_lesions_LogLogistic_Unrest_1.(d) 6 Gnuplot Plotting File: C:\1\Blood\36_Miet_06_carc_lesions_LogLogistic_Unrest_1.plt 7 Tue Jan 12 10:30:33 2010 8

==================================================================== 9 10 Table 2 converting the percentage into the number of animals, and control is Control II from the 11 study. Dose is in ng per kg and is from Table 1 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the probability function is: 15 16 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 17 18 19 Dependent variable = DichEff 20 Independent variable = Dose 21 Slope parameter is not restricted 22 23 Total number of observations = 5 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 30 31 User has chosen the log transformed model 32 33 34 Default Initial Parameter Values 35 background = 0.595238 36 intercept = -3.69546 37 slope = 0.442957 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 41 42 background intercept slope 43 44 background 1 -0.34 0.24 45 46 intercept -0.34 1 -0.99 47 48 slope 0.24 -0.99 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 background 0.597745 * * * 57 intercept -3.90353 * * * 58 slope 0.465358 * * * 59 60 * - Indicates that this value is not calculated. 61 62 63 64 Analysis of Deviance Table 65 66 Model Log(likelihood) # Param's Deviance Test d.f. P-value 67 Full model -77.6769 5 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-178 Fitted model -77.9913 3 0.62887 2 0.7302 1 Reduced model -83.2067 1 11.0597 4 0.0259 2 3 AIC: 161.983 4 5 6 Goodness of Fit 7 Scaled 8 Dose Est._Prob. Expected Observed Size Residual 9

------------------------------------------------------------------------ 10 0.0000 0.5977 25.105 25.000 42 -0.033 11 1755.6399 0.7566 21.941 23.000 29 0.458 12 4922.4989 0.8042 20.104 19.000 25 -0.557 13 12657.0000 0.8474 20.338 20.000 24 -0.192 14 36874.0000 0.8910 28.512 29.000 32 0.277 15 16 Chi^2 = 0.63 d.f. = 2 P-value = 0.7282 17 18 19 Benchmark Dose Computation 20 21 Specified effect = 0.1 22 23 Risk Type = Extra risk 24 25 Confidence level = 0.95 26 27 BMD = 39.1207 28 29 Benchmark dose computation failed. Lower limit includes zero. 30 31 32 

## E.2.26. National Toxicology Program (198 2): Male Mice, Toxic Hepatitis 33 

## E.2.26.1. Summary Table of BMDS Modeling Results 34

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 p-Value a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

gamma 1 4.92 0.03 113.10 2.1E+03 1.1E+03 power restricted ≥ 1
logistic b 2 4.77 0.09 110.35 1.7E+03 1.3E+03

log-logistic 1 4.93 0.03 113.09 2.1E+03 1.2E+03 slope restricted ≥ 1
log-probit 1 4.89 0.03 113.11 1.9E+03 1.3E+03 slope restricted ≥ 1 multistage 2- degree 1 6.04 0.01 113.71 1.3E+03 7.0E+02 betas restricted ≥ 0 probit 2 4.99 0.08 110.51 1.5E+03 1.2E+03

Weibull 1 5.00 0.03 113.04 2.2E+03 9.3E+02 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-179 1 

## E.2.26.2. Figure for Selected Model: Multistage, 2 nd 

## Degree 2

0 0.2 0.4 0.6 0.8

1

0 1000 2000 3000 4000 5000 6000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

13:20 11/16 2009 BMD BMDL Multistage

3 4 5 

## E.2.26.3. Output File for Selected Model: Multistage, 2 nd 

## Degree 6
7 8

==================================================================== 9 Multistage Model. (Version: 3.0; Date: 05/16/2008) 10 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\Multistage_BMR2_Toxic_hepatitis.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\Multistage_BMR2_Toxic_hepatitis.plt 12 Sun Nov 29 13:16:19 2009 13

==================================================================== 14 15 0 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background + (1-background)*[1-EXP( 21 -beta1*dose^1-beta2*dose^2)] 22 23 The parameter betas are restricted to be positive 24 25 26 Dependent variable = DichEff 27 Independent variable = Dose 28 29 Total number of observations = 4 30 Total number of records with missing values = 0 31 Total number of parameters in model = 3 32 Total number of specified parameters = 0 33 Degree of polynomial = 2 34 35 36 Maximum number of iterations = 250 37 Relative Function Convergence has been set to: 1e-008 38 Parameter Convergence has been set to: 1e-008 39 40

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-180 1 2 Default Initial Parameter Values 3 Background = 0.0298369 4 Beta(1) = 0 5 Beta(2) = 5.57954e-008 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 Background Beta(1) Beta(2) 11 12 Background 1 -0.8 0.74 13 14 Beta(1) -0.8 1 -0.97 15 16 Beta(2) 0.74 -0.97 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 Background 0.0286224 * * * 25 Beta(1) 1.97711e-005 * * * 26 Beta(2) 5.00241e-008 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -51.0633 4 36 Fitted model -53.8523 3 5.57784 1 0.01819 37 Reduced model -121.743 1 141.358 3 <.0001 38 39 AIC: 113.705 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0286 2.089 1.000 73 -0.765 47 420.0366 0.0451 2.211 5.000 49 1.920 48 1239.6134 0.1223 5.991 3.000 49 -1.304 49 6117.5662 0.8676 43.381 44.000 50 0.258 50 51 Chi^2 = 6.04 d.f. = 1 P-value = 0.0140 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.1 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 1267.05 63 64 BMDL = 698.659 65 66 BMDU = 1628.68 67 68 Taken together, (698.659, 1628.68) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-181 1 

## E.2.27. National Toxicology Program (2006): Alveolar Metaplasia 2 

## E.2.27.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 13.37 0.01 320.09 2.7E+02 2.3E+02 power restricted ≥ 1, bound hit

gamma 4 13.37 0.01 320.09 5.4E+02 4.6E+02 power restricted ≥ 1, bound hit
logistic 4 33.08 0.00 343.28 6.8E+02 5.8E+02

logistic 4 33.08 0.00 343.28 1.3E+03 1.1E+03

log-logistic 3 1.32 0.72 312.56 1.8E+02 9.8E+01 slope restricted ≥ 1

log-logistic b 3 1.32 0.72 312.56 3.6E+02 2.1E+02 slope restricted ≥ 1

log-probit 3 1.44 0.70 312.68 2.2E+02 7.4E+01 slope restricted ≥ 1

log-probit 3 1.44 0.70 312.68 3.8E+02 1.5E+02 slope restricted ≥ 1
multistage, 2- degree 4 13.37 0.01 320.09 2.7E+02 2.3E+02 betas restricted ≥ 0, bound hit multistage, 2- degree 4 13.37 0.01 320.09 5.4E+02 4.6E+02 betas restricted ≥ 0, bound hit
probit 4 35.22 0.00 347.07 7.2E+02 6.2E+02

probit 4 35.22 0.00 347.07 1.4E+03 1.2E+03

Weibull 4 13.37 0.01 320.09 2.7E+02 2.3E+02 power restricted ≥ 1, bound hit

Weibull 4 13.37 0.01 320.09 5.4E+02 4.6E+02 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-182 E.2.27.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1 1

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

13:20 11/16 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.27.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR2_Alveolar_metaplasia.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR2_Alveolar_metaplasia.plt 12 Mon Nov 16 13:20:58 2009 13

==================================================================== 14 15 0 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 21 22 23 Dependent variable = DichEff 24 Independent variable = Dose 25 Slope parameter is restricted as slope >= 1 26 27 Total number of observations = 6 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 User has chosen the log transformed model 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-183 1 Default Initial Parameter Values 2 background = 0.0377358 3 intercept = -8.78161 4 slope = 1.1228 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 background intercept slope 10 11 background 1 -0.13 0.1 12 13 intercept -0.13 1 -1 14 15 slope 0.1 -1 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 background 0.0373474 * * * 24 intercept -8.85134 * * * 25 slope 1.13159 * * * 26 27 * - Indicates that this value is not calculated. 28 29 30 31 Analysis of Deviance Table 32 33 Model Log(likelihood) # Param's Deviance Test d.f. P-value 34 Full model -152.615 6 35 Fitted model -153.279 3 1.32714 3 0.7227 36 Reduced model -216.802 1 128.374 5 <.0001 37 38 AIC: 312.558 39 40 41 Goodness of Fit 42 Scaled 43 Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45 0.0000 0.0373 1.979 2.000 53 0.015 46 1408.4504 0.3682 19.881 19.000 54 -0.249 47 3137.0446 0.5807 30.777 33.000 53 0.619 48 5392.9593 0.7162 37.244 35.000 52 -0.690 49 9128.8027 0.8197 43.445 45.000 53 0.556 50 16361.0000 0.8976 46.674 46.000 52 -0.308 51 52 Chi^2 = 1.32 d.f. = 3 P-value = 0.7232 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.1 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 357.926 64 65 BMDL = 206.635 66 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-184 E.2.28. National Toxicology Program (2006): Gi ngival Hyperplasia Squamous, 2 Years 1 

## E.2.28.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 p-Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 10.30 0.04 314.99 4.3E+03 2.8E+03 power restricted ≥ 1, bound hit
logistic 4 12.16 0.02 318.60 7.7E+03 5.8E+03

log-logistic b 4 9.26 0.06 313.35 3.2E+03 2.1E+03 slope restricted ≥ 1, bound hit
log-logistic c 3 1.62 0.66 307.51 3.9E+02 6.9E-03 slope unrestricted

log-probit 3 1.56 0.67 307.44 4.6E+02 2.6E-02 slope restricted ≥ 1
multistage, 1- degree 4 10.30 0.04 314.99 4.3E+03 2.8E+03 betas restricted ≥ 0, bound hit
probit 4 11.97 0.02 318.24 7.3E+03 5.5E+03

Weibull 4 10.30 0.04 314.99 4.3E+03 2.8E+03 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-185 E.2.28.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.1 0.2 0.3 0.4

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:36 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.28.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_BMR2_Ging_Hyp_2yr.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_BMR2_Ging_Hyp_2yr.plt 11 Sun Nov 29 11:36:25 2009 12

==================================================================== 13 14 [insert study notes] 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is restricted as slope >= 1 25 26 Total number of observations = 6 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-186 Default Initial Parameter Values 1 background = 0.0188679 2 intercept = -10.0647 3 slope = 1 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -slope 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 background intercept 13 14 background 1 -0.79 15 16 intercept -0.79 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 background 0.0671889 * * * 25 intercept -10.2754 * * * 26 slope 1 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -149.95 6 36 Fitted model -154.675 2 9.45083 4 0.05077 37 Reduced model -162.631 1 25.3627 5 0.0001186 38 39 AIC: 313.351 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0672 3.561 1.000 53 -1.405 47 1408.4504 0.1104 5.961 7.000 54 0.451 48 3137.0446 0.1582 8.386 14.000 53 2.113 49 5392.9593 0.2134 11.311 13.000 53 0.566 50 9128.8027 0.2905 15.395 15.000 53 -0.119 51 16361.0000 0.4036 21.389 16.000 53 -1.509 52 53 Chi^2 = 9.26 d.f. = 4 P-value = 0.0550 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.1 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 3223.25 65 66 BMDL = 2054.88 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-187 E.2.28.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 1

0 0.1 0.2 0.3 0.4

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:36 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.28.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_Unrest_BMR2_Ging_Hyp_2yr.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\Nov29\Blood\LogLogistic_Unrest_BMR2_Ging_Hyp_2yr.plt 12 Sun Nov 29 11:36:27 2009 13

==================================================================== 14 15 [insert study notes] 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 21 22 23 Dependent variable = DichEff 24 Independent variable = Dose 25 Slope parameter is not restricted 26 27 Total number of observations = 6 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 User has chosen the log transformed model 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-188 1 Default Initial Parameter Values 2 background = 0.0188679 3 intercept = -4.87817 4 slope = 0.424322 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 background intercept slope 10 11 background 1 -0.16 0.11 12 13 intercept -0.16 1 -0.99 14 15 slope 0.11 -0.99 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 background 0.0185138 * * * 24 intercept -4.42531 * * * 25 slope 0.373718 * * * 26 27 * - Indicates that this value is not calculated. 28 29 30 31 Analysis of Deviance Table 32 33 Model Log(likelihood) # Param's Deviance Test d.f. P-value 34 Full model -149.95 6 35 Fitted model -150.753 3 1.60686 3 0.6578 36 Reduced model -162.631 1 25.3627 5 0.0001186 37 38 AIC: 307.507 39 40 41 Goodness of Fit 42 Scaled 43 Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45 0.0000 0.0185 0.981 1.000 53 0.019 46 1408.4504 0.1681 9.078 7.000 54 -0.756 47 3137.0446 0.2101 11.136 14.000 53 0.966 48 5392.9593 0.2433 12.893 13.000 53 0.034 49 9128.8027 0.2792 14.795 15.000 53 0.063 50 16361.0000 0.3230 17.117 16.000 53 -0.328 51 52 Chi^2 = 1.62 d.f. = 3 P-value = 0.6555 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.1 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 388.363 64 65 BMDL = 0.00694785 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-189 E.2.29. National Toxicology Program ( 2006): Heart, Cardiomyopathy 1 

## E.2.29.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 2.65 0.62 394.49 1.5E+03 1.2E+03 power restricted ≥ 1, bound hit
logistic 4 6.73 0.15 398.64 2.7E+03 2.2E+03

log-logistic 3 1.32 0.72 395.20 1.2E+03 7.3E+02 slope restricted ≥ 1

log-probit 3 1.11 0.78 394.98 1.3E+03 4.9E+02 slope restricted ≥ 1
multistage, 2- degree b 4 2.65 0.62 394.49 1.5E+03 1.2E+03 betas restricted ≥ 0, bound hit
probit 4 6.71 0.15 398.61 2.6E+03 2.2E+03

Weibull 4 2.65 0.62 394.49 1.5E+03 1.2E+03 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.2.29.2. Figure for Selected Model: Multis tage, 2-Degree, Betas Restricted ≥ 0, Bound Hit 5

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

13:37 11/16 2009 BMD BMDL Multistage

6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-190 1 

## E.2.29.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound 2 

## Hit 3
4 5

==================================================================== 6 Multistage Model. (Version: 3.0; Date: 05/16/2008) 7 Input Data File: C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Cardiomyopathy.(d) 8 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Cardiomyopathy.plt 9 Mon Nov 16 13:37:37 2009 10

==================================================================== 11 12 0 13

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 14 15 The form of the probability function is: 16 17 P[response] = background + (1-background)*[1-EXP( 18 -beta1*dose^1-beta2*dose^2)] 19 20 The parameter betas are restricted to be positive 21 22 23 Dependent variable = DichEff 24 Independent variable = Dose 25 26 Total number of observations = 6 27 Total number of records with missing values = 0 28 Total number of parameters in model = 3 29 Total number of specified parameters = 0 30 Degree of polynomial = 2 31 32 33 Maximum number of iterations = 250 34 Relative Function Convergence has been set to: 1e-008 35 Parameter Convergence has been set to: 1e-008 36 37 38 39 Default Initial Parameter Values 40 Background = 0.234028 41 Beta(1) = 6.08803e-005 42 Beta(2) = 0 43 44 45 Asymptotic Correlation Matrix of Parameter Estimates 46 47 ( *** The model parameter(s) -Beta(2) 48 have been estimated at a boundary point, or have been specified by the user, 49 and do not appear in the correlation matrix ) 50 51 Background Beta(1) 52 53 Background 1 -0.69 54 55 Beta(1) -0.69 1 56 57 58 59 Parameter Estimates 60 61 95.0% Wald Confidence Interval 62 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 63 Background 0.196221 * * * 64 Beta(1) 6.98634e-005 * * * 65 Beta(2) 0 * * * 66 67 * - Indicates that this value is not calculated. 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-191 1 2 3 Analysis of Deviance Table 4 5 Model Log(likelihood) # Param's Deviance Test d.f. P-value 6 Full model -193.93 6 7 Fitted model -195.247 2 2.63378 4 0.6209 8 Reduced model -216.802 1 45.7449 5 <.0001 9 10 AIC: 394.493 11 12 13 Goodness of Fit 14 Scaled 15 Dose Est._Prob. Expected Observed Size Residual 16

------------------------------------------------------------------------ 17 0.0000 0.1962 10.400 10.000 53 -0.138 18 1408.4504 0.2715 14.663 12.000 54 -0.815 19 3137.0446 0.3544 18.784 22.000 53 0.924 20 5392.9593 0.4485 23.325 25.000 52 0.467 21 9128.8027 0.5752 30.487 32.000 53 0.420 22 16361.0000 0.7437 38.673 36.000 52 -0.849 23 24 Chi^2 = 2.65 d.f. = 4 P-value = 0.6176 25 26 27 Benchmark Dose Computation 28 29 Specified effect = 0.1 30 31 Risk Type = Extra risk 32 33 Confidence level = 0.95 34 35 BMD = 1508.09 36 37 BMDL = 1170.08 38 39 BMDU = 2325.84 40 41 Taken together, (1170.08, 2325.84) is a 90 % two-sided confidence 42 interval for the BMD 43 44 45 46 

## E.2.30. National Toxicology Program (2006 ): Hepatocyte Hypertrophy, 2 Years 47 

## E.2.30.1. Summary Table of BMDS Modeling Results 48

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 5 12.03 0.03 273.88 2.4E+02 2.1E+02 power restricted ≥ 1, bound hit

gamma 5 12.03 0.03 273.88 5.0E+02 4.3E+02 power restricted ≥ 1, bound hit
logistic 4 26.14 0.00 297.90 7.4E+02 6.2E+02

logistic 4 26.14 0.00 297.90 1.4E+03 1.2E+03

log-logistic 4 14.32 0.01 279.21 3.7E+02 1.8E+02 slope restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-192 log-logistic 4 14.32 0.01 279.21 6.3E+02 3.6E+02 slope restricted ≥ 1

log-probit 4 13.74 0.01 278.36 4.3E+02 2.3E+02 slope restricted ≥ 1

log-probit 4 13.74 0.01 278.36 6.6E+02 3.9E+02 slope restricted ≥ 1
multistage, 2- degree 5 12.03 0.03 273.88 2.4E+02 2.1E+02 betas restricted ≥ 0, bound hit multistage, 2- degree b 5 12.03 0.03 273.88 5.0E+02 4.3E+02 betas restricted ≥ 0, bound hit
probit 4 28.00 0.00 299.73 7.2E+02 6.2E+02

probit 4 28.00 0.00 299.73 1.4E+03 1.2E+03

Weibull 5 12.03 0.03 273.88 2.4E+02 2.1E+02 power restricted ≥ 1, bound hit

Weibull 5 12.03 0.03 273.88 5.0E+02 4.3E+02 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 1 2 

## E.2.30.2. Figure for Selected Model: Multis tage, 2-Degree, Betas Restricted ≥ 0, Bound Hit 3

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

13:27 11/16 2009 BMD BMDL Multistage

4 5 6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-193 E.2.30.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound 1 

## Hit 2
3 4

==================================================================== 5 Multistage Model. (Version: 3.0; Date: 05/16/2008) 6 Input Data File: 7 C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Hepatocyte_hypertrophy_2years.(d) 8 Gnuplot Plotting File: 9 C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Hepatocyte_hypertrophy_2years.plt 10 Mon Nov 16 13:27:47 2009 11

==================================================================== 12 13 [insert study notes] 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the probability function is: 17 18 P[response] = background + (1-background)*[1-EXP( 19 -beta1*dose^1-beta2*dose^2)] 20 21 The parameter betas are restricted to be positive 22 23 24 Dependent variable = DichEff 25 Independent variable = Dose 26 27 Total number of observations = 6 28 Total number of records with missing values = 0 29 Total number of parameters in model = 3 30 Total number of specified parameters = 0 31 Degree of polynomial = 2 32 33 34 Maximum number of iterations = 250 35 Relative Function Convergence has been set to: 1e-008 36 Parameter Convergence has been set to: 1e-008 37 38 39 40 Default Initial Parameter Values 41 Background = 0.117028 42 Beta(1) = 0.000142077 43 Beta(2) = 5.42278e-009 44 45 46 Asymptotic Correlation Matrix of Parameter Estimates 47 48 ( *** The model parameter(s) -Background -Beta(2) 49 have been estimated at a boundary point, or have been specified by the user, 50 and do not appear in the correlation matrix ) 51 52 Beta(1) 53 54 Beta(1) 1 55 56 57 58 Parameter Estimates 59 60 95.0% Wald Confidence Interval 61 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 62 Background 0 * * * 63 Beta(1) 0.00021035 * * * 64 Beta(2) 0 * * * 65 66 * - Indicates that this value is not calculated. 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-194 1 2 Analysis of Deviance Table 3 4 Model Log(likelihood) # Param's Deviance Test d.f. P-value 5 Full model -129.986 6 6 Fitted model -135.938 1 11.9043 5 0.03612 7 Reduced model -219.97 1 179.968 5 <.0001 8 9 AIC: 273.876 10 11 12 Goodness of Fit 13 Scaled 14 Dose Est._Prob. Expected Observed Size Residual 15

------------------------------------------------------------------------ 16 0.0000 0.0000 0.000 0.000 53 0.000 17 1408.4504 0.2564 13.846 19.000 54 1.606 18 3137.0446 0.4831 25.604 19.000 53 -1.815 19 5392.9593 0.6784 35.955 42.000 53 1.778 20 9128.8027 0.8534 45.232 41.000 53 -1.643 21 16361.0000 0.9680 51.303 52.000 53 0.544 22 23 Chi^2 = 12.03 d.f. = 5 P-value = 0.0344 24 25 26 Benchmark Dose Computation 27 28 Specified effect = 0.1 29 30 Risk Type = Extra risk 31 32 Confidence level = 0.95 33 34 BMD = 500.882 35 36 BMDL = 433.488 37 38 BMDU = 637.074 39 40 Taken together, (433.488, 637.074) is a 90 % two-sided confidence 41 interval for the BMD 42 43 44 45 

## E.2.31. National Toxicology Program (2006): Li ver, E osinophilic Focus, Multiple 46 

## E.2.31.1. Summary Table of BMDS Modeling Results 47

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p Value a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

gamma 3 3.72 0.29 331.90 2.0E+03 1.2E+03 power restricted ≥ 1

logistic 4 4.01 0.40 330.40 3.3E+03 2.8E+03

log-logistic 3 5.29 0.15 333.52 2.3E+03 1.1E+03 slope restricted ≥ 1

log-probit 3 5.90 0.12 334.15 2.3E+03 1.2E+03 slope restricted ≥ 1

multistage, 2-degree 3 2.69 0.44 330.82 2.0E+03 1.3E+03 betas restricted ≥ 0

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-195 probit b 4 3.62 0.46 329.94 3.1E+03 2.7E+03

Weibull 3 3.47 0.32 331.63 2.1E+03 1.2E+03 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

1 2 

## E.2.31.2. Figure for Selected Model: Probit 3

0 0.2 0.4 0.6 0.8

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Probit Model with 0.95 Confidence Level

13:31 11/16 2009 BMDL BMD Probit

4 5 6 

## E.2.31.3. Output File for Selected Model: Probit 7
8 9

==================================================================== 10 Probit Model. (Version: 3.1; Date: 05/16/2008) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Probit_BMR2_liver_eosin_focus.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Probit_BMR2_liver_eosin_focus.plt 13 Mon Nov 16 13:31:29 2009 14

==================================================================== 15 16 0 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the probability function is: 20 21 P[response] = CumNorm(Intercept+Slope*Dose), 22 23 where CumNorm(.) is the cumulative normal distribution function 24 25 26

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-196 Dependent variable = DichEff 1 Independent variable = Dose 2 Slope parameter is not restricted 3 4 Total number of observations = 6 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 11 12 Default Initial (and Specified) Parameter Values 13 background = 0 Specified 14 intercept = -1.28017 15 slope = 0.000129308 16 17 18 Asymptotic Correlation Matrix of Parameter Estimates 19 20 ( *** The model parameter(s) -background 21 have been estimated at a boundary point, or have been specified by the user, 22 and do not appear in the correlation matrix ) 23 24 intercept slope 25 26 intercept 1 -0.77 27 28 slope -0.77 1 29 30 31 32 Parameter Estimates 33 34 95.0% Wald Confidence Interval 35 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 36 intercept -1.23453 0.125131 -1.47978 -0.98928 37 slope 0.000124995 1.49436e-005 9.57063e-005 0.000154284 38 39 40 41 Analysis of Deviance Table 42 43 Model Log(likelihood) # Param's Deviance Test d.f. P-value 44 Full model -161.07 6 45 Fitted model -162.972 2 3.80457 4 0.4331 46 Reduced model -202.816 1 83.4925 5 <.0001 47 48 AIC: 329.944 49 50 51 Goodness of Fit 52 Scaled 53 Dose Est._Prob. Expected Observed Size Residual 54

------------------------------------------------------------------------ 55 0.0000 0.1085 5.751 3.000 53 -1.215 56 1408.4504 0.1449 7.826 8.000 54 0.067 57 3137.0446 0.1998 10.588 14.000 53 1.172 58 5392.9593 0.2876 15.242 17.000 53 0.533 59 9128.8027 0.4628 24.526 22.000 53 -0.696 60 16361.0000 0.7912 41.932 42.000 53 0.023 61 62 Chi^2 = 3.62 d.f. = 4 P-value = 0.4593 63 64 65 Benchmark Dose Computation 66 67 Specified effect = 0.1 68 69 Risk Type = Extra risk 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-197 1 Confidence level = 0.95 2 3 BMD = 3076.08 4 5 BMDL = 2679.85 6 7 8 9 

## E.2.32. National Toxicology Program (2006): Liver, Fatty Change, Diffuse 10 

## E.2.32.1. Summary Table of BMDS Modeling Results 11

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p Value a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

gamma 4 2.42 0.66 252.35 2.2E+03 1.6E+03 power restricted ≥ 1

logistic 4 9.22 0.06 262.13 3.2E+03 2.8E+03

log-logistic 4 4.36 0.36 254.41 2.3E+03 1.8E+03 slope restricted ≥ 1

log-probit 4 4.30 0.37 254.43 2.3E+03 1.8E+03 slope restricted ≥ 1

multistage, 2-degree 4 2.03 0.73 252.07 2.0E+03 1.4E+03 betas restricted ≥ 0

probit 4 8.50 0.07 260.92 3.1E+03 2.6E+03

Weibull b 4 2.06 0.72 251.99 2.2E+03 1.6E+03 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-198 1 

## E.2.32.2. Figure for Selected Model: Weibull, Power Restricted ≥ 1 2

3

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Weibull Model with 0.95 Confidence Level

13:31 11/16 2009 BMDL BMD Weibull

4 5 6 

## E.2.32.3. Output File for Selected Model: Weibull, Power Restricted ≥ 1 7
8 9

==================================================================== 10 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Weibull_BMR2_liver_fatty_change_diff.(d) 12 Gnuplot Plotting File: 13 C:\USEPA\BMDS21\AD\Blood\Weibull_BMR2_liver_fatty_change_diff.plt 14 Mon Nov 16 13:31:55 2009 15

==================================================================== 16 17 NTP_liver_fatty_change_diffuse 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 19 20 The form of the probability function is: 21 22 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 Power parameter is restricted as power >=1 28 29 Total number of observations = 6 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-199 1 Default Initial (and Specified) Parameter Values 2 Background = 0.00925926 3 Slope = 1.61086e-007 4 Power = 1.69678 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -Background 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 Slope Power 14 15 Slope 1 -1 16 17 Power -1 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0 NA 26 Slope 1.01566e-006 1.55672e-006 -2.03545e-006 4.06678e-006 27 Power 1.50443 0.168998 1.1732 1.83566 28 29 NA - Indicates that this parameter has hit a bound 30 implied by some inequality constraint and thus 31 has no standard error. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -122.992 6 39 Fitted model -123.994 2 2.00421 4 0.735 40 Reduced model -204.846 1 163.708 5 <.0001 41 42 AIC: 251.989 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0000 0.000 0.000 53 0.000 50 1408.4504 0.0539 2.912 2.000 54 -0.550 51 3137.0446 0.1688 8.949 12.000 53 1.119 52 5392.9593 0.3415 18.102 17.000 53 -0.319 53 9128.8027 0.6024 31.929 30.000 53 -0.542 54 16361.0000 0.8913 47.238 48.000 53 0.336 55 56 Chi^2 = 2.06 d.f. = 4 P-value = 0.7243 57 58 59 Benchmark Dose Computation 60 61 Specified effect = 0.1 62 63 Risk Type = Extra risk 64 65 Confidence level = 0.95 66 67 BMD = 2158.24 68 69 BMDL = 1573.34 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-200 1 2 

## E.2.33. National Toxicology Program (2006): Liver Necrosis 3 

## E.2.33.1. Summary Table of BMDS Modeling Results 4

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 pValue a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 0.80 0.94 234.40 4.8E+03 3.5E+03 power restricted ≥ 1, bound hit
logistic 4 2.75 0.60 236.74 8.2E+03 6.8E+03

log-logistic 4 0.77 0.94 234.38 4.4E+03 3.1E+03 slope restricted ≥ 1, bound hit
log-logistic 3 0.75 0.86 236.38 4.3E+03 1.9E+03 slope unrestricted

log-probit b 3 0.99 0.80 236.60 4.1E+03 1.9E+03 slope unrestricted
multistage, 2- degree 4 0.80 0.94 234.40 4.8E+03 3.5E+03 betas restricted ≥ 0, bound hit
probit 4 2.38 0.67 236.29 7.7E+03 6.4E+03

Weibull 4 0.80 0.94 234.40 4.8E+03 3.5E+03 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 5 6 

## E.2.33.2. Figure for Selected Model: Log-Probit 7

0 0.1 0.2 0.3 0.4 0.5

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

12:27 11/29 2009 BMDL BMD LogProbit

8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-201 1 

## E.2.33.3. Output File for Selected Model: Log-Probit 2
3

==================================================================== 4 Probit Model. (Version: 3.1; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov29\Blood\LogProbit_BMR2_liver_necrosis.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\Blood\LogProbit_BMR2_liver_necrosis.plt 7 Sun Nov 29 12:27:13 2009 8

==================================================================== 9 10 NTP_liver_necrosis 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = Background 16 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 17 18 where CumNorm(.) is the cumulative normal distribution function 19 20 21 Dependent variable = DichEff 22 Independent variable = Dose 23 Slope parameter is not restricted 24 25 Total number of observations = 6 26 Total number of records with missing values = 0 27 Maximum number of iterations = 250 28 Relative Function Convergence has been set to: 1e-008 29 Parameter Convergence has been set to: 1e-008 30 31 32 33 User has chosen the log transformed model 34 35 36 Default Initial (and Specified) Parameter Values 37 background = 0.0188679 38 intercept = -5.04893 39 slope = 0.457364 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 background intercept slope 45 46 background 1 -0.59 0.55 47 48 intercept -0.59 1 -1 49 50 slope 0.55 -1 1 51 52 53 54 Parameter Estimates 55 56 95.0% Wald Confidence Interval 57 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 58 background 0.0221159 0.0221444 -0.0212863 0.0655182 59 intercept -5.58721 1.71363 -8.94586 -2.22855 60 slope 0.517092 0.185108 0.154287 0.879898 61 62 63 64 Analysis of Deviance Table 65 66 Model Log(likelihood) # Param's Deviance Test d.f. P-value 67 Full model -114.813 6 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-202 Fitted model -115.299 3 0.972296 3 0.808 1 Reduced model -127.98 1 26.3331 5 <.0001 2 3 AIC: 236.598 4 5 6 Goodness of Fit 7 Scaled 8 Dose Est._Prob. Expected Observed Size Residual 9

------------------------------------------------------------------------ 10 0.0000 0.0221 1.172 1.000 53 -0.161 11 1408.4504 0.0544 2.938 4.000 54 0.637 12 3137.0446 0.0976 5.174 4.000 53 -0.543 13 5392.9593 0.1457 7.720 8.000 53 0.109 14 9128.8027 0.2096 11.106 10.000 53 -0.373 15 16361.0000 0.3002 15.908 17.000 53 0.327 16 17 Chi^2 = 0.99 d.f. = 3 P-value = 0.8048 18 19 20 Benchmark Dose Computation 21 22 Specified effect = 0.1 23 24 Risk Type = Extra risk 25 26 Confidence level = 0.95 27 28 BMD = 4132.6 29 30 BMDL = 1930.47 31 32 33 34 

## E.2.34. National Toxicology Program ( 2006): Liver, P igmentation 35 

## E.2.34.1. Summary Table of BMDS Modeling Results 36

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 3 2.10 0.55 196.97 1.2E+03 8.2E+02 power restricted ≥ 1

logistic 4 5.42 0.25 197.07 1.0E+03 8.4E+02

log-logistic 3 0.16 0.98 195.53 1.4E+03 1.1E+03 slope restricted ≥ 1

log-probit b 3 0.29 0.96 195.53 1.4E+03 1.0E+03 slope restricted ≥ 1
multistage, 2- degree 3 7.47 0.06 199.96 1.0E+03 5.5E+02 betas restricted ≥ 0

probit 4 15.44 0.00 200.50 9.4E+02 7.9E+02

Weibull 3 4.42 0.22 199.01 9.7E+02 6.6E+02 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 37 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-203 E.2.34.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1 1

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

13:38 11/16 2009 BMDL BMD LogProbit

2 3 4 

## E.2.34.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Probit Model. (Version: 3.1; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\LogProbit_BMR2_Pigmentation.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\LogProbit_BMR2_Pigmentation.plt 11 Mon Nov 16 13:38:02 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = Background 20 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 21 22 where CumNorm(.) is the cumulative normal distribution function 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 Slope parameter is not restricted 28 29 Total number of observations = 6 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-204 User has chosen the log transformed model 1 2 3 Default Initial (and Specified) Parameter Values 4 background = 0.0754717 5 intercept = -12.1574 6 slope = 1.53218 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 background intercept slope 12 13 background 1 -0.35 0.33 14 15 intercept -0.35 1 -1 16 17 slope 0.33 -1 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 background 0.0725493 0.0338874 0.00613127 0.138967 26 intercept -14.4941 2.03052 -18.4738 -10.5144 27 slope 1.83177 0.246866 1.34792 2.31562 28 29 30 31 Analysis of Deviance Table 32 33 Model Log(likelihood) # Param's Deviance Test d.f. P-value 34 Full model -94.6177 6 35 Fitted model -94.7632 3 0.290885 3 0.9617 36 Reduced model -210.717 1 232.198 5 <.0001 37 38 AIC: 195.526 39 40 41 Goodness of Fit 42 Scaled 43 Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45 0.0000 0.0725 3.845 4.000 53 0.082 46 1408.4504 0.1769 9.552 9.000 54 -0.197 47 3137.0446 0.6291 33.342 34.000 53 0.187 48 5392.9593 0.9013 47.771 48.000 53 0.105 49 9128.8027 0.9874 52.334 52.000 53 -0.412 50 16361.0000 0.9995 52.974 53.000 53 0.160 51 52 Chi^2 = 0.29 d.f. = 3 P-value = 0.9624 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.1 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 1356.93 64 65 BMDL = 1041.17 66 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-205 E.2.35. National Toxicology Program (200 6): Liver, T oxic Hepatopathy 1 

## E.2.35.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 1.90 0.75 185.76 2.4E+03 1.9E+03 power restricted ≥ 1

logistic 4 6.59 0.16 191.14 2.7E+03 2.2E+03

log-logistic 3 3.01 0.39 189.58 2.6E+03 2.1E+03 slope restricted ≥ 1

log-probit 3 2.99 0.39 189.58 2.7E+03 2.1E+03 slope restricted ≥ 1
multistage, 2- degree b 5 2.28 0.81 184.08 2.1E+03 1.7E+03 betas restricted ≥ 0, bound hit
probit 4 5.60 0.23 189.82 2.5E+03 2.1E+03

Weibull 4 2.11 0.72 185.79 2.3E+03 1.8E+03 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 3 4 

## E.2.35.2. Figure for Selected Model: Multis tage, 2-Degree, Betas Restricted ≥ 0, Bound Hit 5

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:44 11/19 2009 BMD BMDL Multistage

6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-206 1 2 

## E.2.35.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound 3 

## Hit 4
5 6

==================================================================== 7 Multistage Model. (Version: 3.0; Date: 05/16/2008) 8 Input Data File: C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Toxic_hepatopathy.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Toxic_hepatopathy.plt 10 Thu Nov 19 11:44:22 2009 11

==================================================================== 12 13 0 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the probability function is: 17 18 P[response] = background + (1-background)*[1-EXP( 19 -beta1*dose^1-beta2*dose^2)] 20 21 The parameter betas are restricted to be positive 22 23 24 Dependent variable = DichEff 25 Independent variable = Dose 26 27 Total number of observations = 6 28 Total number of records with missing values = 0 29 Total number of parameters in model = 3 30 Total number of specified parameters = 0 31 Degree of polynomial = 2 32 33 34 Maximum number of iterations = 250 35 Relative Function Convergence has been set to: 1e-008 36 Parameter Convergence has been set to: 1e-008 37 38 39 40 Default Initial Parameter Values 41 Background = 0 42 Beta(1) = 0 43 Beta(2) = 3.75131e+011 44 45 46 Asymptotic Correlation Matrix of Parameter Estimates 47 48 ( *** The model parameter(s) -Background -Beta(1) 49 have been estimated at a boundary point, or have been specified by the user, 50 and do not appear in the correlation matrix ) 51 52 Beta(2) 53 54 Beta(2) 1 55 56 57 58 Parameter Estimates 59 60 95.0% Wald Confidence Interval 61 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 62 Background 0 * * * 63 Beta(1) 0 * * * 64 Beta(2) 2.3767e-008 * * * 65 66 * - Indicates that this value is not calculated. 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-207 1 2 3 Analysis of Deviance Table 4 5 Model Log(likelihood) # Param's Deviance Test d.f. P-value 6 Full model -89.8076 6 7 Fitted model -91.0417 1 2.46809 5 0.7813 8 Reduced model -218.207 1 256.799 5 <.0001 9 10 AIC: 184.083 11 12 13 Goodness of Fit 14 Scaled 15 Dose Est._Prob. Expected Observed Size Residual 16

------------------------------------------------------------------------ 17 0.0000 0.0000 0.000 0.000 53 0.000 18 1408.4504 0.0461 2.487 2.000 54 -0.316 19 3137.0446 0.2086 11.053 8.000 53 -1.032 20 5392.9593 0.4990 26.449 30.000 53 0.975 21 9128.8027 0.8620 45.687 45.000 53 -0.274 22 16361.0000 0.9983 52.909 53.000 53 0.303 23 24 Chi^2 = 2.28 d.f. = 5 P-value = 0.8087 25 26 27 Benchmark Dose Computation 28 29 Specified effect = 0.1 30 31 Risk Type = Extra risk 32 33 Confidence level = 0.95 34 35 BMD = 2105.48 36 37 BMDL = 1698.91 38 39 BMDU = 2318.05 40 41 Taken together, (1698.91, 2318.05) is a 90 % two-sided confidence 42 interval for the BMD 43 44 45 46

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-208 E.2.35.4. Figure for Unrestricted Model: Multistage, 2-Degree, Betas Unrestricted 1

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:22 11/19 2009 BMD BMDL Multistage

2 3 4 

## E.2.35.5. Output File for Unrestricted Model: Multis tage, 2-Degree, Betas Unrestricted 5
6 7

==================================================================== 8 Multistage Model. (Version: 3.0; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Multistage_Unrest_BMR2_Toxic_hepatopathy.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\AD\Blood\Multistage_Unrest_BMR2_Toxic_hepatopathy.plt 12 Thu Nov 19 11:22:30 2009 13

==================================================================== 14 15 0 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background + (1-background)*[1-EXP( 21 -beta1*dose^1-beta2*dose^2)] 22 23 The parameter betas are not restricted 24 25 26 Dependent variable = DichEff 27 Independent variable = Dose 28 29 Total number of observations = 6 30 Total number of records with missing values = 0 31 Total number of parameters in model = 3 32 Total number of specified parameters = 0 33 Degree of polynomial = 2 34 35 36 Maximum number of iterations = 250 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-209 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 Background = 1 7 Beta(1) = -6.1241e+015 8 Beta(2) = 7.17596e+011 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) Beta(2) 18 19 Beta(1) 1 -0.92 20 21 Beta(2) -0.92 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 Background 0 * * * 30 Beta(1) -1.36642e-005 * * * 31 Beta(2) 2.62877e-008 * * * 32 33 * - Indicates that this value is not calculated. 34 35 36 37 Analysis of Deviance Table 38 39 Model Log(likelihood) # Param's Deviance Test d.f. P-value 40 Full model -89.8076 6 41 Fitted model -90.8336 2 2.05202 4 0.7262 42 Reduced model -218.207 1 256.799 5 <.0001 43 44 AIC: 185.667 45 46 47 Goodness of Fit 48 Scaled 49 Dose Est._Prob. Expected Observed Size Residual 50

------------------------------------------------------------------------ 51 0.0000 0.0000 0.000 0.000 53 0.000 52 1408.4504 0.0324 1.748 2.000 54 0.194 53 3137.0446 0.1941 10.289 8.000 53 -0.795 54 5392.9593 0.4989 26.439 30.000 53 0.978 55 9128.8027 0.8733 46.285 45.000 53 -0.531 56 16361.0000 0.9989 52.942 53.000 53 0.241 57 58 Chi^2 = 1.97 d.f. = 4 P-value = 0.7420 59 60 61 Benchmark Dose Computation 62 63 Specified effect = 0.1 64 65 Risk Type = Extra risk 66 67 Confidence level = 0.95 68 69 BMD = 2278.69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-210 1 BMDL = 1743.86 2 3 BMDU = 2713.68 4 5 Taken together, (1743.86, 2713.68) is a 90 % two-sided confidence 6 interval for the BMD 7 8 9 10 

## E.2.36. National Toxicology Program (2006): Lun g, Alveolar to Bronchiolar Epithelial 11 

## Metaplasia (Alveolar Epithelium, Metaplasia, Bronchiolar) 12 

## E.2.36.1. Summary Table of BMDS Modeling Results 13

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 13.37 0.01 320.09 5.4E+02 4.6E+02 power restricted ≥ 1, bound hit
logistic 4 33.08 0.00 343.28 1.3E+03 1.1E+03

log-logistic b 3 1.32 0.72 312.56 3.6E+02 2.1E+02 slope restricted ≥ 1

log-probit 3 1.44 0.70 312.68 3.8E+02 1.5E+02 slope restricted ≥ 1
multistage, 2- degree 4 13.37 0.01 320.09 5.4E+02 4.6E+02 betas restricted ≥ 0, bound hit
probit 4 35.22 0.00 347.07 1.4E+03 1.2E+03

Weibull 4 13.37 0.01 320.09 5.4E+02 4.6E+02 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 14 15

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-211 E.2.36.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1 1

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

13:38 11/16 2009 BMDL BMD Log-Logistic

2 3 4 

## E.2.36.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR2_Alv_bronch_epith_metapl.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR2_Alv_bronch_epith_metapl.plt 12 Mon Nov 16 13:38:53 2009 13

==================================================================== 14 15 0 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 21 22 23 Dependent variable = DichEff 24 Independent variable = Dose 25 Slope parameter is restricted as slope <= 1 26 27 Total number of observations = 6 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 User has chosen the log transformed model 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-212 1 Default Initial Parameter Values 2 background = 0.0377358 3 intercept = -8.78161 4 slope = 1.1228 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 background intercept slope 10 11 background 1 -0.13 0.1 12 13 intercept -0.13 1 -1 14 15 slope 0.1 -1 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 background 0.0373474 * * * 24 intercept -8.85134 * * * 25 slope 1.13159 * * * 26 27 * - Indicates that this value is not calculated. 28 29 30 31 Analysis of Deviance Table 32 33 Model Log(likelihood) # Param's Deviance Test d.f. P-value 34 Full model -152.615 6 35 Fitted model -153.279 3 1.32714 3 0.7227 36 Reduced model -216.802 1 128.374 5 <.0001 37 38 AIC: 312.558 39 40 41 Goodness of Fit 42 Scaled 43 Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45 0.0000 0.0373 1.979 2.000 53 0.015 46 1408.4504 0.3682 19.881 19.000 54 -0.249 47 3137.0446 0.5807 30.777 33.000 53 0.619 48 5392.9593 0.7162 37.244 35.000 52 -0.690 49 9128.8027 0.8197 43.445 45.000 53 0.556 50 16361.0000 0.8976 46.674 46.000 52 -0.308 51 52 Chi^2 = 1.32 d.f. = 3 P-value = 0.7232 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.1 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 357.926 64 65 BMDL = 206.635 66 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-213 E.2.37. National Toxicology Program (2006 ): Oval Cell Hyperp lasia, 2 Years 1 

## E.2.37.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 3 6.94 0.07 199.47 3.7E+03 2.8E+03 power restricted ≥ 1

logistic 4 6.40 0.17 196.80 3.3E+03 2.8E+03

log-logistic 3 8.21 0.04 201.66 3.8E+03 3.1E+03 slope restricted ≥ 1

log-probit 3 7.00 0.07 200.12 3.9E+03 3.3E+03 slope restricted ≥ 1
multistage, 2- degree 4 7.05 0.13 197.13 2.5E+03 2.0E+03 betas restricted ≥ 0

probit b 4 5.64 0.23 195.45 3.1E+03 2.6E+03

Weibull 3 6.85 0.08 198.38 3.2E+03 2.3E+03 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.2.37.2. Figure for Selected Model: Probit 5

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Probit Model with 0.95 Confidence Level

13:21 11/16 2009 BMDL BMD Probit

6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-214 1 

## E.2.37.3. Output File for Selected Model: Probit 2
3 4

==================================================================== 5 Probit Model. (Version: 3.1; Date: 05/16/2008) 6 Input Data File: C:\USEPA\BMDS21\AD\Blood\Probit_BMR2_Oval_cell_hyperplasia.(d) 7 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Probit_BMR2_Oval_cell_hyperplasia.plt 8 Mon Nov 16 13:21:57 2009 9

==================================================================== 10 11 0 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the probability function is: 15 16 P[response] = CumNorm(Intercept+Slope*Dose), 17 18 where CumNorm(.) is the cumulative normal distribution function 19 20 21 Dependent variable = DichEff 22 Independent variable = Dose 23 Slope parameter is not restricted 24 25 Total number of observations = 6 26 Total number of records with missing values = 0 27 Maximum number of iterations = 250 28 Relative Function Convergence has been set to: 1e-008 29 Parameter Convergence has been set to: 1e-008 30 31 32 33 Default Initial (and Specified) Parameter Values 34 background = 0 Specified 35 intercept = -2.29925 36 slope = 0.000307725 37 38 39 Asymptotic Correlation Matrix of Parameter Estimates 40 41 ( *** The model parameter(s) -background 42 have been estimated at a boundary point, or have been specified by the user, 43 and do not appear in the correlation matrix ) 44 45 intercept slope 46 47 intercept 1 -0.87 48 49 slope -0.87 1 50 51 52 53 Parameter Estimates 54 55 95.0% Wald Confidence Interval 56 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 57 intercept -2.18988 0.208022 -2.59759 -1.78216 58 slope 0.000313001 3.3114e-005 0.000248098 0.000377903 59 60 61 62 Analysis of Deviance Table 63 64 Model Log(likelihood) # Param's Deviance Test d.f. P-value 65 Full model -92.4898 6 66 Fitted model -95.7243 2 6.46898 4 0.1668 67 Reduced model -210.191 1 235.402 5 <.0001 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-215 1 AIC: 195.449 2 3 4 Goodness of Fit 5 Scaled 6 Dose Est._Prob. Expected Observed Size Residual 7

------------------------------------------------------------------------ 8 0.0000 0.0143 0.756 0.000 53 -0.876 9 1408.4504 0.0401 2.168 4.000 54 1.270 10 3137.0446 0.1135 6.017 3.000 53 -1.306 11 5392.9593 0.3079 16.317 20.000 53 1.096 12 9128.8027 0.7478 39.631 38.000 53 -0.516 13 16361.0000 0.9983 52.911 53.000 53 0.299 14 15 Chi^2 = 5.64 d.f. = 4 P-value = 0.2274 16 17 18 Benchmark Dose Computation 19 20 Specified effect = 0.1 21 22 Risk Type = Extra risk 23 24 Confidence level = 0.95 25 26 BMD = 3125.6 27 28 BMDL = 2640.99 29 30 31 32 

## E.2.38. National Toxicology Program (2006): Toxic Hepatopathy 33 

## E.2.38.1. Summary Table of BMDS Modeling Results 34

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 1.90 0.75 185.76 2.4E+03 1.9E+03 power restricted ≥ 1

logistic 4 6.59 0.16 191.14 2.7E+03 2.2E+03

log-logistic 3 3.01 0.39 189.58 2.6E+03 2.1E+03 slope restricted ≥ 1

log-probit 3 2.99 0.39 189.58 2.7E+03 2.1E+03 slope restricted ≥ 1
multistage, 2- degree b 5 2.28 0.81 184.08 2.1E+03 1.7E+03 betas restricted ≥ 0, bound hit
probit 4 5.60 0.23 189.82 2.5E+03 2.1E+03

Weibull 4 2.11 0.72 185.79 2.3E+03 1.8E+03 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-216 E.2.38.2. Figure for Selected Model: Multis tage, 2-Degree, Betas Restricted ≥ 0, Bound Hit 1

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:44 11/19 2009 BMD BMDL Multistage

2 3 4 

## E.2.38.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0, Bound 5 

## Hit 6
7 8

==================================================================== 9 Multistage Model. (Version: 3.0; Date: 05/16/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Toxic_hepatopathy.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Multistage_BMR2_Toxic_hepatopathy.plt 12 Thu Nov 19 11:44:22 2009 13

==================================================================== 14 15 0 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background + (1-background)*[1-EXP( 21 -beta1*dose^1-beta2*dose^2)] 22 23 The parameter betas are restricted to be positive 24 25 26 Dependent variable = DichEff 27 Independent variable = Dose 28 29 Total number of observations = 6 30 Total number of records with missing values = 0 31 Total number of parameters in model = 3 32 Total number of specified parameters = 0 33 Degree of polynomial = 2 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-217 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0 9 Beta(2) = 3.75131e+011 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background -Beta(1) 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(2) 19 20 Beta(2) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 0 * * * 30 Beta(2) 2.3767e-008 * * * 31 32 * - Indicates that this value is not calculated. 33 34 35 36 Analysis of Deviance Table 37 38 Model Log(likelihood) # Param's Deviance Test d.f. P-value 39 Full model -89.8076 6 40 Fitted model -91.0417 1 2.46809 5 0.7813 41 Reduced model -218.207 1 256.799 5 <.0001 42 43 AIC: 184.083 44 45 46 Goodness of Fit 47 Scaled 48 Dose Est._Prob. Expected Observed Size Residual 49

------------------------------------------------------------------------ 50 0.0000 0.0000 0.000 0.000 53 0.000 51 1408.4504 0.0461 2.487 2.000 54 -0.316 52 3137.0446 0.2086 11.053 8.000 53 -1.032 53 5392.9593 0.4990 26.449 30.000 53 0.975 54 9128.8027 0.8620 45.687 45.000 53 -0.274 55 16361.0000 0.9983 52.909 53.000 53 0.303 56 57 Chi^2 = 2.28 d.f. = 5 P-value = 0.8087 58 59 60 Benchmark Dose Computation 61 62 Specified effect = 0.1 63 64 Risk Type = Extra risk 65 66 Confidence level = 0.95 67 68 BMD = 2105.48 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-218 BMDL = 1698.91 1 2 BMDU = 2318.05 3 4 Taken together, (1698.91, 2318.05) is a 90 % two-sided confidence 5 interval for the BMD 6 7 8 9 

## E.2.38.4. Figure for Unrestricted Model: Multistage, 2-Degree, Betas Unrestricted 10

0 0.2 0.4 0.6 0.8

1

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:44 11/19 2009 BMD BMDL Multistage

11 12 13 

## E.2.38.5. Output File for Unrestricted Model: Multis tage, 2-Degree, Betas Unrestricted 14
15 16

==================================================================== 17 Multistage Model. (Version: 3.0; Date: 05/16/2008) 18 Input Data File: 19 C:\USEPA\BMDS21\AD\Blood\Multistage_Unrest_BMR2_2nd_Toxic_hepatopathy.(d) 20 Gnuplot Plotting File: 21 C:\USEPA\BMDS21\AD\Blood\Multistage_Unrest_BMR2_2nd_Toxic_hepatopathy.plt 22 Thu Nov 19 11:44:23 2009 23

==================================================================== 24 25 0 26

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 27 28 The form of the probability function is: 29 30 P[response] = background + (1-background)*[1-EXP( 31 -beta1*dose^1-beta2*dose^2)] 32 33 The parameter betas are not restricted 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-219 Dependent variable = DichEff 1 Independent variable = Dose 2 3 Total number of observations = 6 4 Total number of records with missing values = 0 5 Total number of parameters in model = 3 6 Total number of specified parameters = 0 7 Degree of polynomial = 2 8 9 10 Maximum number of iterations = 250 11 Relative Function Convergence has been set to: 1e-008 12 Parameter Convergence has been set to: 1e-008 13 14 15 16 Default Initial Parameter Values 17 Background = 1 18 Beta(1) = -6.1241e+015 19 Beta(2) = 7.17596e+011 20 21 22 Asymptotic Correlation Matrix of Parameter Estimates 23 24 ( *** The model parameter(s) -Background 25 have been estimated at a boundary point, or have been specified by the user, 26 and do not appear in the correlation matrix ) 27 28 Beta(1) Beta(2) 29 30 Beta(1) 1 -0.92 31 32 Beta(2) -0.92 1 33 34 35 36 Parameter Estimates 37 38 95.0% Wald Confidence Interval 39 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 40 Background 0 * * * 41 Beta(1) -1.36642e-005 * * * 42 Beta(2) 2.62877e-008 * * * 43 44 * - Indicates that this value is not calculated. 45 46 47 48 Analysis of Deviance Table 49 50 Model Log(likelihood) # Param's Deviance Test d.f. P-value 51 Full model -89.8076 6 52 Fitted model -90.8336 2 2.05202 4 0.7262 53 Reduced model -218.207 1 256.799 5 <.0001 54 55 AIC: 185.667 56 57 58 Goodness of Fit 59 Scaled 60 Dose Est._Prob. Expected Observed Size Residual 61

------------------------------------------------------------------------ 62 0.0000 0.0000 0.000 0.000 53 0.000 63 1408.4504 0.0324 1.748 2.000 54 0.194 64 3137.0446 0.1941 10.289 8.000 53 -0.795 65 5392.9593 0.4989 26.439 30.000 53 0.978 66 9128.8027 0.8733 46.285 45.000 53 -0.531 67 16361.0000 0.9989 52.942 53.000 53 0.241 68 69 Chi^2 = 1.97 d.f. = 4 P-value = 0.7420 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-220 1 2 Benchmark Dose Computation 3 4 Specified effect = 0.1 5 6 Risk Type = Extra risk 7 8 Confidence level = 0.95 9 10 BMD = 2278.69 11 12 BMDL = 1743.86 13 14 BMDU = 2713.68 15 16 Taken together, (1743.86, 2713.68) is a 90 % two-sided confidence 17 interval for the BMD 18 19 20 21 

## E.2.39. Ohsako et al. (2001): Anogenital Distance in Male Pups 22 

## E.2.39.1. Summary Table of BMDS Modeling Results 23

Model a Degrees of Freedom 

## χ 2 pValue b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

exponential (M2) 3 0.092 185.349 2.358E+04 1.529E+04

exponential (M3) 3 0.092 185.349 2.358E+04 1.529E+04 power bound hit

exponential (M4) 2 0.190 184.217 2.617E+03 8.029E+02

exponential (M5) 1 0.092 185.741 2.204E+03 8.487E+02

Hill c 2 0.261 183.587 3.628E+03 8.053E+02 n lower bound hit

linear 3 0.086 185.490 2.436E+04 1.638E+04

polynomial 3 0.086 185.490 2.436E+04 1.638E+04

power 3 0.086 185.490 2.436E+04 1.638E+04 power bound hit

Hill, unrestricted d 1 0.106 185.515 4.741E+03 4.517E+02 n unrestricted

a Constant variance model selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model, BMDS output presented in this appendix

d Alternate model, BM DS output also presented in this appendix 24 25 26

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-221 E.2.39.2. Figure for Selected Model: Hill 1

22 24 26 28 30 32

0 5000 10000 15000 20000 25000 30000Mean Response

dose Hill Model with 0.95 Confidence Level

10:31 01/12 2010 BMD BMDL Hill

2 3 

## Ohsako et al., 2001: Ano-genital distance in male pups 4 5 6 

## E.2.39.3. Output File for Selected Model: Hill 7 

## Ohsako et al., 2001: Ano-genital distance in male pups 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\1\Blood\56_Ohsako_2001_anogenital_HillCV_1.(d) 11 Gnuplot Plotting File: C:\1\Blood\56_Ohsako_2001_anogenital_HillCV_1.plt 12 Tue Jan 12 10:31:18 2010 13

==================================================================== 14 15 Figure 7 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter restricted to be greater than 1 27 A constant variance model is fit 28 29 Total number of dose groups = 5 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 alpha = 9.96434 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-222 rho = 0 Specified 1 intercept = 28.9146 2 v = -5.04512 3 n = 1.64399 4 k = 2013.5 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho -n 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha intercept v k 14 15 alpha 1 4.1e-008 7.2e-008 -1e-007 16 17 intercept 4.1e-008 1 -0.53 -0.53 18 19 v 7.2e-008 -0.53 1 -0.27 20 21 k -1e-007 -0.53 -0.27 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 9.50299 1.82885 5.91851 13.0875 30 intercept 28.988 0.868025 27.2867 30.6893 31 v -5.03805 1.23954 -7.4675 -2.6086 32 n 1 NA 33 k 2301.52 2261.96 -2131.83 6734.88 34 35 NA - Indicates that this parameter has hit a bound 36 implied by some inequality constraint and thus 37 has no standard error. 38 39 40 41 Table of Data and Estimated Values of Interest 42 43 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 44

------ --- -------- -------- ----------- ----------- ---------- 45 46 0 12 28.9 29 3.54 3.08 -0.0824 47 845.3 10 28.1 27.6 2.52 3.08 0.455 48 2763 10 25.3 26.2 3.59 3.08 -0.953 49 9022 10 26.1 25 3.59 3.08 1.12 50 3.05e+004 12 23.9 24.3 2.36 3.08 -0.488 51 52 53 54 Model Descriptions for likelihoods calculated 55 56 57 Model A1: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma^2 59 60 Model A2: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma(i)^2 62 63 Model A3: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma^2 65 Model A3 uses any fixed variance parameters that 66 were specified by the user 67 68 Model R: Yi = Mu + e(i) 69 Var{e(i)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-223 1 2 Likelihoods of Interest 3 4 Model Log(likelihood) # Param's AIC 5 A1 -86.449919 6 184.899838 6 A2 -84.654549 10 189.309098 7 A3 -86.449919 6 184.899838 8 fitted -87.793369 4 183.586738 9 R -95.473923 2 194.947846 10 11 12 Explanation of Tests 13 14 Test 1: Do responses and/or variances differ among Dose levels? 15 (A2 vs. R) 16 Test 2: Are Variances Homogeneous? (A1 vs A2) 17 Test 3: Are variances adequately modeled? (A2 vs. A3) 18 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 19 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 20 21 Tests of Interest 22 23 Test -2*log(Likelihood Ratio) Test df p-value 24 25 Test 1 21.6387 8 0.005631 26 Test 2 3.59074 4 0.4642 27 Test 3 3.59074 4 0.4642 28 Test 4 2.6869 2 0.2609 29 30 The p-value for Test 1 is less than .05. There appears to be a 31 difference between response and/or variances among the dose levels 32 It seems appropriate to model the data 33 34 The p-value for Test 2 is greater than .1. A homogeneous variance 35 model appears to be appropriate here 36 37 38 The p-value for Test 3 is greater than .1. The modeled variance appears 39 to be appropriate here 40 41 The p-value for Test 4 is greater than .1. The model chosen seems 42 to adequately describe the data 43 44 45 Benchmark Dose Computation 46 47 Specified effect = 1 48 49 Risk Type = Estimated standard deviations from the control mean 50 51 Confidence level = 0.95 52 53 BMD = 3628.44 54 55 BMDL = 805.33 56 57 58 59

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-224 E.2.39.4. Figure for Unrestricted M odel: Hill, Unrestric ted 1

22 24 26 28 30 32

0 5000 10000 15000 20000 25000 30000Mean Response

dose Hill Model with 0.95 Confidence Level

10:31 01/12 2010 BMD BMDL Hill

2 3 

## Ohsako et al., 2001: Ano-genital distance in male pups 4 5 6 

## E.2.39.5. Output File for Unrestricted Mode l: Hill, Unrestricted 7 

## Ohsako et al., 2001: Ano-genital distance in male pups 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\1\Blood\56_Ohsako_2001_anogenital_HillCV_Unrest_1.(d) 11 Gnuplot Plotting File: C:\1\Blood\56_Ohsako_2001_anogenital_HillCV_Unrest_1.plt 12 Tue Jan 12 10:31:19 2010 13

==================================================================== 14 15 Figure 7 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter is not restricted 27 A constant variance model is fit 28 29 Total number of dose groups = 5 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 alpha = 9.96434 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-225 rho = 0 Specified 1 intercept = 28.9146 2 v = -5.04512 3 n = 1.64399 4 k = 2013.5 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha intercept v n k 14 15 alpha 1 1.7e-008 7.5e-008 7.3e-008 -7.2e-008 16 17 intercept 1.7e-008 1 -0.0053 -0.0089 -0.14 18 19 v 7.5e-008 -0.0053 1 0.98 -0.99 20 21 n 7.3e-008 -0.0089 0.98 1 -0.96 22 23 k -7.2e-008 -0.14 -0.99 -0.96 1 24 25 26 27 Parameter Estimates 28 29 95.0% Wald Confidence Interval 30 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 31 alpha 9.49042 1.82643 5.91068 13.0702 32 intercept 28.9785 0.871908 27.2696 30.6874 33 v -6.77236 12.034 -30.3585 16.8138 34 n 0.615459 1.15558 -1.64943 2.88035 35 k 6361.67 43105.4 -78123.4 90846.7 36 37 38 39 Table of Data and Estimated Values of Interest 40 41 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 42

------ --- -------- -------- ----------- ----------- ---------- 43 44 0 12 28.9 29 3.54 3.08 -0.0718 45 845.3 10 28.1 27.5 2.52 3.08 0.633 46 2763 10 25.3 26.4 3.59 3.08 -1.16 47 9022 10 26.1 25.2 3.59 3.08 0.861 48 3.05e+004 12 23.9 24.1 2.36 3.08 -0.231 49 50 51 52 Model Descriptions for likelihoods calculated 53 54 55 Model A1: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma^2 57 58 Model A2: Yij = Mu(i) + e(ij) 59 Var{e(ij)} = Sigma(i)^2 60 61 Model A3: Yij = Mu(i) + e(ij) 62 Var{e(ij)} = Sigma^2 63 Model A3 uses any fixed variance parameters that 64 were specified by the user 65 66 Model R: Yi = Mu + e(i) 67 Var{e(i)} = Sigma^2 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-226 Likelihoods of Interest 1 2 Model Log(likelihood) # Param's AIC 3 A1 -86.449919 6 184.899838 4 A2 -84.654549 10 189.309098 5 A3 -86.449919 6 184.899838 6 fitted -87.757640 5 185.515280 7 R -95.473923 2 194.947846 8 9 10 Explanation of Tests 11 12 Test 1: Do responses and/or variances differ among Dose levels? 13 (A2 vs. R) 14 Test 2: Are Variances Homogeneous? (A1 vs A2) 15 Test 3: Are variances adequately modeled? (A2 vs. A3) 16 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 17 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 18 19 Tests of Interest 20 21 Test -2*log(Likelihood Ratio) Test df p-value 22 23 Test 1 21.6387 8 0.005631 24 Test 2 3.59074 4 0.4642 25 Test 3 3.59074 4 0.4642 26 Test 4 2.61544 1 0.1058 27 28 The p-value for Test 1 is less than .05. There appears to be a 29 difference between response and/or variances among the dose levels 30 It seems appropriate to model the data 31 32 The p-value for Test 2 is greater than .1. A homogeneous variance 33 model appears to be appropriate here 34 35 36 The p-value for Test 3 is greater than .1. The modeled variance appears 37 to be appropriate here 38 39 The p-value for Test 4 is greater than .1. The model chosen seems 40 to adequately describe the data 41 42 43 Benchmark Dose Computation 44 45 Specified effect = 1 46 47 Risk Type = Estimated standard deviations from the control mean 48 49 Confidence level = 0.95 50 51 BMD = 4741.19 52 53 BMDL = 451.715 54 55 56

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-227 1 

## E.2.40. Schantz et al. (1996): Maze Errors Per Block, Female 2 

## E.2.40.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear 1 0.71 2.38 0.12 19.76 5.1E+03 2.9E+03 nonconstant variance

polynomial 1 0.71 2.38 0.12 19.76 5.1E+03 2.9E+03 nonconstant variance

power 1 0.71 2.38 0.12 19.76 5.1E+03 2.9E+03 nonconstant variance, power restricted ≥ 1, bound hit

power 0 0.71 0.00 NA 19.38 1.2E+03 5.4E-08 nonconstant variance, power unrestricted

linear c 1 0.71 1.99 0.16 17.95 5.5E+03 3.6E+03 constant variance

polynomial 1 0.71 1.99 0.16 17.95 5.5E+03 3.6E+03 constant variance

power 1 0.71 1.99 0.16 17.95 5.5E+03 3.6E+03 constant variance, power restricted ≥ 1, bound hit

power d 0 0.71 0.00 NA 17.95 2.0E+03 8.1E-06 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-228 E.2.40.2. Figure for Selected Model: Linear, Constant Variance 1

2 2.5

3 3.5

4

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Linear Model with 0.95 Confidence Level

13:42 11/16 2009 BMD BMDL Linear

2 3 4 

## E.2.40.3. Output File for Selected Mode l: L inear, Constant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\LinearConstVar_BMR4_maze_errors.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\LinearConstVar_BMR4_maze_errors.plt 11 Mon Nov 16 13:42:46 2009 12

==================================================================== 13 14 Rel Male Thymus wt, Tbl 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 rho is set to 0 25 Signs of the polynomial coefficients are not restricted 26 A constant variance model is fit 27 28 Total number of dose groups = 3 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-229 alpha = 0.569565 1 rho = 0 Specified 2 beta_0 = 3.37789 3 beta_1 = -0.000133906 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -rho 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 alpha beta_0 beta_1 13 14 alpha 1 1.5e-010 7.3e-012 15 16 beta_0 1.5e-010 1 -0.73 17 18 beta_1 7.3e-012 -0.73 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 alpha 0.547839 0.141451 0.270599 0.825079 27 beta_0 3.37789 0.196469 2.99282 3.76296 28 beta_1 -0.000133906 3.88571e-005 -0.000210064 -5.77472e-005 29 30 31 32 Table of Data and Estimated Values of Interest 33 34 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 35

------ --- -------- -------- ----------- ----------- ---------- 36 37 0 10 3.55 3.38 0.639 0.74 0.755 38 2670 10 2.76 3.02 0.806 0.74 -1.11 39 8341 10 2.34 2.26 0.806 0.74 0.355 40 41 42 43 Model Descriptions for likelihoods calculated 44 45 46 Model A1: Yij = Mu(i) + e(ij) 47 Var{e(ij)} = Sigma^2 48 49 Model A2: Yij = Mu(i) + e(ij) 50 Var{e(ij)} = Sigma(i)^2 51 52 Model A3: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma^2 54 Model A3 uses any fixed variance parameters that 55 were specified by the user 56 57 Model R: Yi = Mu + e(i) 58 Var{e(i)} = Sigma^2 59 60 61 Likelihoods of Interest 62 63 Model Log(likelihood) # Param's AIC 64 A1 -4.976366 4 17.952732 65 A2 -4.638353 6 21.276707 66 A3 -4.976366 4 17.952732 67 fitted -5.973388 3 17.946777 68 R -10.975997 2 25.951993 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-230 1 Explanation of Tests 2 3 Test 1: Do responses and/or variances differ among Dose levels? 4 (A2 vs. R) 5 Test 2: Are Variances Homogeneous? (A1 vs A2) 6 Test 3: Are variances adequately modeled? (A2 vs. A3) 7 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 8 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 9 10 Tests of Interest 11 12 Test -2*log(Likelihood Ratio) Test df p-value 13 14 Test 1 12.6753 4 0.01298 15 Test 2 0.676025 2 0.7132 16 Test 3 0.676025 2 0.7132 17 Test 4 1.99405 1 0.1579 18 19 The p-value for Test 1 is less than .05. There appears to be a 20 difference between response and/or variances among the dose levels 21 It seems appropriate to model the data 22 23 The p-value for Test 2 is greater than .1. A homogeneous variance 24 model appears to be appropriate here 25 26 27 The p-value for Test 3 is greater than .1. The modeled variance appears 28 to be appropriate here 29 30 The p-value for Test 4 is greater than .1. The model chosen seems 31 to adequately describe the data 32 33 34 Benchmark Dose Computation 35 36 Specified effect = 1 37 38 Risk Type = Estimated standard deviations from the control mean 39 40 Confidence level = 0.95 41 42 BMD = 5527.48 43 44 45 BMDL = 3627.8 46 47 48 49

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-231 E.2.40.4. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

2 2.5

3 3.5

4

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

13:42 11/16 2009 BMD BMDL Power

2 3 4 

## E.2.40.5. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5
6 7

==================================================================== 8 Power Model. (Version: 2.15; Date: 04/07/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\PwrConstVar_Unrest_BMR6_maze_errors.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\AD\Blood\PwrConstVar_Unrest_BMR6_maze_errors.plt 12 Mon Nov 16 13:42:47 2009 13

==================================================================== 14 15 Rel Male Thymus wt, Tbl 2 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 The power is not restricted 27 A constant variance model is fit 28 29 Total number of dose groups = 3 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-232 Default Initial Parameter Values 1 alpha = 0.569565 2 rho = 0 Specified 3 control = 3.55459 4 slope = -0.0428676 5 power = 0.369985 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 ( *** The model parameter(s) -rho 11 have been estimated at a boundary point, or have been specified by the user, 12 and do not appear in the correlation matrix ) 13 14 alpha control slope power 15 16 alpha 1 -6.8e-011 -1.4e-012 -1.6e-013 17 18 control -6.8e-011 1 -0.35 -0.28 19 20 slope -1.4e-012 -0.35 1 1 21 22 power -1.6e-013 -0.28 1 1 23 24 25 26 Parameter Estimates 27 28 95.0% Wald Confidence Interval 29 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 30 alpha 0.512609 0.132355 0.253198 0.77202 31 control 3.55459 0.226409 3.11084 3.99834 32 slope -0.0428676 0.119074 -0.276249 0.190514 33 power 0.369985 0.311491 -0.240526 0.980496 34 35 36 37 Table of Data and Estimated Values of Interest 38 39 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 40

------ --- -------- -------- ----------- ----------- ---------- 41 42 0 10 3.55 3.55 0.639 0.716 2.62e-010 43 2670 10 2.76 2.76 0.806 0.716 3.09e-010 44 8341 10 2.34 2.34 0.806 0.716 3.32e-010 45 46 Degrees of freedom for Test A3 vs fitted <= 0 47 48 49 50 Model Descriptions for likelihoods calculated 51 52 53 Model A1: Yij = Mu(i) + e(ij) 54 Var{e(ij)} = Sigma^2 55 56 Model A2: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma(i)^2 58 59 Model A3: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 Model A3 uses any fixed variance parameters that 62 were specified by the user 63 64 Model R: Yi = Mu + e(i) 65 Var{e(i)} = Sigma^2 66 67 68 Likelihoods of Interest 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-233 Model Log(likelihood) # Param's AIC 1 A1 -4.976366 4 17.952732 2 A2 -4.638353 6 21.276707 3 A3 -4.976366 4 17.952732 4 fitted -4.976366 4 17.952732 5 R -10.975997 2 25.951993 6 7 8 Explanation of Tests 9 10 Test 1: Do responses and/or variances differ among Dose levels? 11 (A2 vs. R) 12 Test 2: Are Variances Homogeneous? (A1 vs A2) 13 Test 3: Are variances adequately modeled? (A2 vs. A3) 14 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 15 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 16 17 Tests of Interest 18 19 Test -2*log(Likelihood Ratio) Test df p-value 20 21 Test 1 12.6753 4 0.01298 22 Test 2 0.676025 2 0.7132 23 Test 3 0.676025 2 0.7132 24 Test 4 1.77636e-015 0 NA 25 26 The p-value for Test 1 is less than .05. There appears to be a 27 difference between response and/or variances among the dose levels 28 It seems appropriate to model the data 29 30 The p-value for Test 2 is greater than .1. A homogeneous variance 31 model appears to be appropriate here 32 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 NA - Degrees of freedom for Test 4 are less than or equal to 0. The Chi-Square 38 test for fit is not valid 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 2017.9 50 51 52 BMDL = 8.10578e-006 53 54 55 56

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-234 E.2.41. Shi et al. (2007): Estradiol 1 

## E.2.41.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 0.05 11.41 0.01 391.64 3.8E+03 2.1E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.05 11.41 0.01 391.64 3.8E+03 2.1E+03 nonconstant variance, power restricted ≥ 1 exponential (M4)

c 2 0.05 0.74 0.69 382.97 4.4E+02 2.0E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.05 0.74 0.69 382.97 4.4E+02 2.0E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) d 2 0.05 0.74 0.69 382.97 4.4E+02 2.0E+02 nonconstant variance, power unrestricted

Hill 2 0.05 0.05 0.97 382.28 4.0E+02 error nonconstant variance, n restricted >1, bound hit

Hill d 1 0.05 0.02 0.90 384.24 3.9E+02 error nonconstant variance, n unrestricted

linear 3 0.05 14.08 0.00 394.31 5.4E+03 3.7E+03 nonconstant variance

polynomial 2 0.05 5.06 0.08 387.29 1.8E+03 1.2E+03 nonconstant variance

power 3 0.05 14.08 0.00 394.31 5.4E+03 3.7E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 2 0.05 1.36 0.51 383.59 3.5E+02 1.8E+01 nonconstant variance, power unrestricted
exponential (M2) 3 0.05 9.37 0.02 392.09 2.8E+03 1.6E+03 constant variance, power restricted ≥ 1
exponential (M3) 3 0.05 9.37 0.02 392.09 2.8E+03 1.6E+03 constant variance, power restricted ≥ 1
exponential (M4) 2 0.05 0.61 0.74 385.34 3.3E+02 1.5E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 0.05 0.61 0.74 385.34 3.3E+02 1.5E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 0.05 0.61 0.74 385.34 3.3E+02 1.5E+02 constant variance, power unrestricted

Hill 1 0.05 0.26 0.61 386.98 3.1E+02 1.2E+02 constant variance, n restricted >1

Hill 1 0.05 0.26 0.61 386.98 3.1E+02 4.0E+01 constant variance, n unrestricted

linear 3 0.05 12.21 0.01 394.93 4.4E+03 3.2E+03 constant variance

polynomial 2 0.05 5.39 0.07 390.12 1.4E+03 9.3E+02 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-235 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

power 3 0.05 12.21 0.01 394.93 4.4E+03 3.2E+03 constant variance, power restricted ≥ 1, bound hit

power 2 0.05 1.66 0.44 386.38 2.3E+02 1.2E+01 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.2.41.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 3 

## Restricted ≥ 1 4

20 40 60 80 100 120 140

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:45 11/16 2009 BMD BMDL Exponential

5 6 7 

## E.2.41.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 8 

## Restricted ≥ 1 9
10 11

==================================================================== 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 13 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_BMR1_Shi_estradiol_17B_conc_PE9.(d) 14 Gnuplot Plotting File: 15 Mon Nov 16 13:45:19 2009 16

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-236 ==================================================================== 1 2 Figure 4 PE9 only 3

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4 5 The form of the response function by Model: 6 Model 2: Y[dose] = a * exp{sign * b * dose} 7 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 8 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 9 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 10 11 Note: Y[dose] is the median response for exposure = dose; 12 sign = +1 for increasing trend in data; 13 sign = -1 for decreasing trend. 14 15 Model 2 is nested within Models 3 and 4. 16 Model 3 is nested within Model 5. 17 Model 4 is nested within Model 5. 18 19 20 Dependent variable = Mean 21 Independent variable = Dose 22 Data are assumed to be distributed: normally 23 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 24 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 25 26 Total number of dose groups = 5 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 MLE solution provided: Exact 33 34 35 Initial Parameter Values 36 37 Variable Model 4 38

-------- -------- 39 lnalpha 2.65881 40 rho 0.913414 41 a 108 42 b 0.000503911 43 c 0.340136 44 d 1 45 46 47 48 Parameter Estimates 49 50 Variable Model 4 51

-------- ------- 52 lnalpha 1.66777 53 rho 1.15313 54 a 103.145 55 b 0.00182735 56 c 0.418744 57 d 1 58 59 60 Table of Stats From Input Data 61 62 Dose N Obs Mean Obs Std Dev 63

----- --- ---------- ------------- 64 0 10 102.9 41.41 65 188.3 10 86.19 19.58 66 592.1 10 63.33 29.36 67 2882 10 48.1 18.82 68 7665 10 38.57 22.59 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-237 1 Estimated Values of Interest 2 3 Dose Est Mean Est Std Scaled Residual 4

------ ---------- --------- ---------------- 5 0 103.1 33.35 -0.02732 6 188.3 85.69 29.96 0.05287 7 592.1 63.51 25.21 -0.02235 8 2882 43.5 20.27 0.7167 9 7665 43.19 20.19 -0.7237 10 11 12 13 Other models for which likelihoods are calculated: 14 15 Model A1: Yij = Mu(i) + e(ij) 16 Var{e(ij)} = Sigma^2 17 18 Model A2: Yij = Mu(i) + e(ij) 19 Var{e(ij)} = Sigma(i)^2 20 21 Model A3: Yij = Mu(i) + e(ij) 22 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 23 24 Model R: Yij = Mu + e(i) 25 Var{e(ij)} = Sigma^2 26 27 28 Likelihoods of Interest 29 30 Model Log(likelihood) DF AIC 31

------- ----------------- ---- ------------ 32 A1 -188.3615 6 388.7231 33 A2 -183.667 10 387.3339 34 A3 -186.1132 7 386.2263 35 R -203.3606 2 410.7211 36 4 -186.4844 5 382.9688 37 38 39 Additive constant for all log-likelihoods = -45.95. This constant added to the 40 above values gives the log-likelihood including the term that does not 41 depend on the model parameters. 42 43 44 Explanation of Tests 45 46 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 47 Test 2: Are Variances Homogeneous? (A2 vs. A1) 48 Test 3: Are variances adequately modeled? (A2 vs. A3) 49 50 Test 6a: Does Model 4 fit the data? (A3 vs 4) 51 52 53 Tests of Interest 54 55 Test -2*log(Likelihood Ratio) D. F. p-value 56

-------- ------------------------ ------ -------------- 57 Test 1 39.39 8 < 0.0001 58 Test 2 9.389 4 0.05208 59 Test 3 4.892 3 0.1798 60 Test 6a 0.7425 2 0.6899 61 62 63 The p-value for Test 1 is less than .05. There appears to be a 64 difference between response and/or variances among the dose 65 levels, it seems appropriate to model the data. 66 67 The p-value for Test 2 is less than .1. A non-homogeneous 68 variance model appears to be appropriate. 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-238 The p-value for Test 3 is greater than .1. The modeled 1 variance appears to be appropriate here. 2 3 The p-value for Test 6a is greater than .1. Model 4 seems 4 to adequately describe the data. 5 6 7 Benchmark Dose Computations: 8 9 Specified Effect = 1.000000 10 11 Risk Type = Estimated standard deviations from control 12 13 Confidence Level = 0.950000 14 15 BMD = 444.551 16 17 BMDL = 195.249 18 19 20 

## E.2.41.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 21 

## Unrestricted 22

20 40 60 80 100 120 140

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:45 11/16 2009 BMD BMDL Exponential

23 24 25 

## E.2.41.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 26 

## Power Unrestricted 27
28 29

==================================================================== 30 Exponential Model. (Version: 1.5; Date: 4/23/2009) 31 Input Data File: 32 C:\USEPA\BMDS21\AD\Blood\Exp_Unrest_BMR1_Shi_estradiol_17B_conc_PE9.(d) 33 Gnuplot Plotting File: 34

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-239 Mon Nov 16 13:45:21 2009 1

==================================================================== 2 3 Figure 4 PE9 only 4

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 5 6 The form of the response function by Model: 7 Model 2: Y[dose] = a * exp{sign * b * dose} 8 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 9 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 10 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 11 12 Note: Y[dose] is the median response for exposure = dose; 13 sign = +1 for increasing trend in data; 14 sign = -1 for decreasing trend. 15 16 Model 2 is nested within Models 3 and 4. 17 Model 3 is nested within Model 5. 18 Model 4 is nested within Model 5. 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 Data are assumed to be distributed: normally 24 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 5 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 MLE solution provided: Exact 34 35 36 Initial Parameter Values 37 38 Variable Model 5 39

-------- -------- 40 lnalpha 2.65881 41 rho 0.913414 42 a 108 43 b 0.000503911 44 c 0.340136 45 d 1 46 47 48 49 Parameter Estimates 50 51 Variable Model 5 52

-------- ------- 53 lnalpha 1.66777 54 rho 1.15313 55 a 103.145 56 b 0.00182735 57 c 0.418744 58 d 1 59 60 61 Table of Stats From Input Data 62 63 Dose N Obs Mean Obs Std Dev 64

----- --- ---------- ------------- 65 0 10 102.9 41.41 66 188.3 10 86.19 19.58 67 592.1 10 63.33 29.36 68 2882 10 48.1 18.82 69 7665 10 38.57 22.59 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-240 1 2 Estimated Values of Interest 3 4 Dose Est Mean Est Std Scaled Residual 5

------ ---------- --------- ---------------- 6 0 103.1 33.35 -0.02732 7 188.3 85.69 29.96 0.05287 8 592.1 63.51 25.21 -0.02235 9 2882 43.5 20.27 0.7167 10 7665 43.19 20.19 -0.7237 11 12 13 14 Other models for which likelihoods are calculated: 15 16 Model A1: Yij = Mu(i) + e(ij) 17 Var{e(ij)} = Sigma^2 18 19 Model A2: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = Sigma(i)^2 21 22 Model A3: Yij = Mu(i) + e(ij) 23 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 24 25 Model R: Yij = Mu + e(i) 26 Var{e(ij)} = Sigma^2 27 28 29 Likelihoods of Interest 30 31 Model Log(likelihood) DF AIC 32

------- ----------------- ---- ------------ 33 A1 -188.3615 6 388.7231 34 A2 -183.667 10 387.3339 35 A3 -186.1132 7 386.2263 36 R -203.3606 2 410.7211 37 5 -186.4844 5 382.9688 38 39 40 Additive constant for all log-likelihoods = -45.95. This constant added to the 41 above values gives the log-likelihood including the term that does not 42 depend on the model parameters. 43 44 45 Explanation of Tests 46 47 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 48 Test 2: Are Variances Homogeneous? (A2 vs. A1) 49 Test 3: Are variances adequately modeled? (A2 vs. A3) 50 51 Test 7a: Does Model 5 fit the data? (A3 vs 5) 52 53 54 Tests of Interest 55 56 Test -2*log(Likelihood Ratio) D. F. p-value 57

-------- ------------------------ ------ -------------- 58 Test 1 39.39 8 < 0.0001 59 Test 2 9.389 4 0.05208 60 Test 3 4.892 3 0.1798 61 Test 7a 0.7425 2 0.6899 62 63 64 The p-value for Test 1 is less than .05. There appears to be a 65 difference between response and/or variances among the dose 66 levels, it seems appropriate to model the data. 67 68 The p-value for Test 2 is less than .1. A non-homogeneous 69 variance model appears to be appropriate. 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-241 1 The p-value for Test 3 is greater than .1. The modeled 2 variance appears to be appropriate here. 3 4 The p-value for Test 7a is greater than .1. Model 5 seems 5 to adequately describe the data. 6 7 8 Benchmark Dose Computations: 9 10 Specified Effect = 1.000000 11 12 Risk Type = Estimated standard deviations from control 13 14 Confidence Level = 0.950000 15 16 BMD = 444.551 17 18 BMDL = 195.249 19 20 21 

## E.2.41.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 22

20 40 60 80 100 120 140

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Hill Model

13:45 11/16 2009 BMD Hill

23 24 25 

## E.2.41.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 26
27 28

==================================================================== 29 Hill Model. (Version: 2.14; Date: 06/26/2008) 30 Input Data File: 31 C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_Shi_estradiol_17B_conc_PE9.(d) 32 Gnuplot Plotting File: 33 C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_Shi_estradiol_17B_conc_PE9.plt 34 Mon Nov 16 13:45:22 2009 35

==================================================================== 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-242 1 Figure 4 PE9 only 2

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3 4 The form of the response function is: 5 6 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 7 8 9 Dependent variable = Mean 10 Independent variable = Dose 11 Power parameter is not restricted 12 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 13 14 Total number of dose groups = 5 15 Total number of records with missing values = 0 16 Maximum number of iterations = 250 17 Relative Function Convergence has been set to: 1e-008 18 Parameter Convergence has been set to: 1e-008 19 20 21 22 Default Initial Parameter Values 23 lalpha = 6.63982 24 rho = 0 25 intercept = 102.857 26 v = -64.2856 27 n = 1.33525 28 k = 461.707 29 30 31 Asymptotic Correlation Matrix of Parameter Estimates 32 33 lalpha rho intercept v n k 34 35 lalpha 1 -1 0.064 -0.095 0.073 0.085 36 37 rho -1 1 -0.075 0.096 -0.074 -0.085 38 39 intercept 0.064 -0.075 1 -0.61 -0.22 -0.37 40 41 v -0.095 0.096 -0.61 1 0.83 -0.4 42 43 n 0.073 -0.074 -0.22 0.83 1 -0.52 44 45 k 0.085 -0.085 -0.37 -0.4 -0.52 1 46 47 48 49 Parameter Estimates 50 51 95.0% Wald Confidence Interval 52 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 53 lalpha 1.54702 2.36086 -3.08017 6.17422 54 rho 1.17907 0.564621 0.0724289 2.2857 55 intercept 105.265 10.3805 84.9191 125.61 56 v -70.2058 20.1009 -109.603 -30.8086 57 n 0.875252 0.64467 -0.388278 2.13878 58 k 426.676 337.186 -234.197 1087.55 59 60 61 62 Table of Data and Estimated Values of Interest 63 64 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 65

------ --- -------- -------- ----------- ----------- ---------- 66 67 0 10 103 105 41.4 33.7 -0.226 68 188.3 10 86.2 82.2 19.6 29.2 0.431 69 592.1 10 63.3 65.2 29.4 25.4 -0.227 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-243 2882 10 48.1 46.2 18.8 20.8 0.294 1 7665 10 38.6 40.2 22.6 19.1 -0.277 2 3 4 5 Model Descriptions for likelihoods calculated 6 7 8 Model A1: Yij = Mu(i) + e(ij) 9 Var{e(ij)} = Sigma^2 10 11 Model A2: Yij = Mu(i) + e(ij) 12 Var{e(ij)} = Sigma(i)^2 13 14 Model A3: Yij = Mu(i) + e(ij) 15 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 16 Model A3 uses any fixed variance parameters that 17 were specified by the user 18 19 Model R: Yi = Mu + e(i) 20 Var{e(i)} = Sigma^2 21 22 23 Likelihoods of Interest 24 25 Model Log(likelihood) # Param's AIC 26 A1 -188.361545 6 388.723090 27 A2 -183.666974 10 387.333947 28 A3 -186.113162 7 386.226325 29 fitted -186.121461 6 384.242922 30 R -203.360558 2 410.721116 31 32 33 Explanation of Tests 34 35 Test 1: Do responses and/or variances differ among Dose levels? 36 (A2 vs. R) 37 Test 2: Are Variances Homogeneous? (A1 vs A2) 38 Test 3: Are variances adequately modeled? (A2 vs. A3) 39 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 40 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 41 42 Tests of Interest 43 44 Test -2*log(Likelihood Ratio) Test df p-value 45 46 Test 1 39.3872 8 <.0001 47 Test 2 9.38914 4 0.05208 48 Test 3 4.89238 3 0.1798 49 Test 4 0.0165976 1 0.8975 50 51 The p-value for Test 1 is less than .05. There appears to be a 52 difference between response and/or variances among the dose levels 53 It seems appropriate to model the data 54 55 The p-value for Test 2 is less than .1. A non-homogeneous variance 56 model appears to be appropriate 57 58 The p-value for Test 3 is greater than .1. The modeled variance appears 59 to be appropriate here 60 61 The p-value for Test 4 is greater than .1. The model chosen seems 62 to adequately describe the data 63 64 65 Benchmark Dose Computation 66 67 Specified effect = 1 68 69 Risk Type = Estimated standard deviations from the control mean 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-244 1 Confidence level = 0.95 2 3 BMD = 390.413 4 5 6 BMDL computation failed. 7 8 9 

## E.2.41.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 10

20 40 60 80 100 120 140

0 1000 2000 3000 4000 5000 6000 7000 8000Mean Response

dose Power Model with 0.95 Confidence Level

13:45 11/16 2009 BMD BMDL Power

11 12 13 

## E.2.41.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 14 

## Unrestricted 15
16 17

==================================================================== 18 Power Model. (Version: 2.15; Date: 04/07/2008) 19 Input Data File: 20 C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_Shi_estradiol_17B_conc_PE9.(d) 21 Gnuplot Plotting File: 22 C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_Shi_estradiol_17B_conc_PE9.plt 23 Mon Nov 16 13:45:22 2009 24

==================================================================== 25 26 Figure 4 PE9 only 27

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 28 29 The form of the response function is: 30 31 Y[dose] = control + slope * dose^power 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-245 Independent variable = Dose 1 The power is not restricted 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 5 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 11 12 Default Initial Parameter Values 13 lalpha = 6.63982 14 rho = 0 15 control = 102.857 16 slope = -2.986 17 power = 0.343163 18 19 20 Asymptotic Correlation Matrix of Parameter Estimates 21 22 lalpha rho control slope power 23 24 lalpha 1 -1 0.048 0.17 0.25 25 26 rho -1 1 -0.059 -0.17 -0.25 27 28 control 0.048 -0.059 1 -0.74 -0.59 29 30 slope 0.17 -0.17 -0.74 1 0.98 31 32 power 0.25 -0.25 -0.59 0.98 1 33 34 35 36 Parameter Estimates 37 38 95.0% Wald Confidence Interval 39 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 40 lalpha 1.5482 2.39188 -3.13979 6.23619 41 rho 1.1846 0.571778 0.0639365 2.30526 42 control 106.216 10.4574 85.7201 126.712 43 slope -9.40933 6.9801 -23.0901 4.27142 44 power 0.221631 0.0746081 0.0754014 0.36786 45 46 47 48 Table of Data and Estimated Values of Interest 49 50 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 51

------ --- -------- -------- ----------- ----------- ---------- 52 53 0 10 103 106 41.4 34.4 -0.309 54 188.3 10 86.2 76.2 19.6 28.2 1.12 55 592.1 10 63.3 67.5 29.4 26.3 -0.5 56 2882 10 48.1 51.2 18.8 22.3 -0.443 57 7665 10 38.6 37.9 22.6 18.7 0.113 58 59 60 61 Model Descriptions for likelihoods calculated 62 63 64 Model A1: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma^2 66 67 Model A2: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma(i)^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-246 Model A3: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 2 Model A3 uses any fixed variance parameters that 3 were specified by the user 4 5 Model R: Yi = Mu + e(i) 6 Var{e(i)} = Sigma^2 7 8 9 Likelihoods of Interest 10 11 Model Log(likelihood) # Param's AIC 12 A1 -188.361545 6 388.723090 13 A2 -183.666974 10 387.333947 14 A3 -186.113162 7 386.226325 15 fitted -186.795167 5 383.590334 16 R -203.360558 2 410.721116 17 18 19 Explanation of Tests 20 21 Test 1: Do responses and/or variances differ among Dose levels? 22 (A2 vs. R) 23 Test 2: Are Variances Homogeneous? (A1 vs A2) 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 25 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 26 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 27 28 Tests of Interest 29 30 Test -2*log(Likelihood Ratio) Test df p-value 31 32 Test 1 39.3872 8 <.0001 33 Test 2 9.38914 4 0.05208 34 Test 3 4.89238 3 0.1798 35 Test 4 1.36401 2 0.5056 36 37 The p-value for Test 1 is less than .05. There appears to be a 38 difference between response and/or variances among the dose levels 39 It seems appropriate to model the data 40 41 The p-value for Test 2 is less than .1. A non-homogeneous variance 42 model appears to be appropriate 43 44 The p-value for Test 3 is greater than .1. The modeled variance appears 45 to be appropriate here 46 47 The p-value for Test 4 is greater than .1. The model chosen seems 48 to adequately describe the data 49 50 51 Benchmark Dose Computation 52 53 Specified effect = 1 54 55 Risk Type = Estimated standard deviations from the control mean 56 57 Confidence level = 0.95 58 59 BMD = 346.016 60 61 62 BMDL = 18.2028 63 64 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-247 E.2.42. Smialowicz et al. (2008): PFC per 10^6 Cells 1 

## E.2.42.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 <0.0001 13.24 0.00 892.22 5.8E+03 3.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 639.80 <0.0001 1518.75 6.4E+03 error nonconstant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 13.24 0.00 892.22 5.8E+03 3.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 10.69 0.00 891.67 8.4E+03 5.1E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) d 2 <0.0001 10.69 0.00 891.67 8.4E+03 5.1E+03 nonconstant variance, power unrestricted

Hill 2 <.0001 9.23 0.01 890.21 8.2E+03 error nonconstant variance, n restricted >1, bound hit

Hill d 1 <.0001 8.09 0.00 891.07 6.0E+03 error nonconstant variance, n unrestricted

linear c 3 <.0001 9.68 0.02 888.66 9.7E+03 7.8E+03 nonconstant variance

polynomial 2 <.0001 9.28 0.01 890.26 8.4E+03 5.4E+03 nonconstant variance

power 3 <.0001 9.68 0.02 888.66 9.7E+03 7.8E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 2 <.0001 7.86 0.02 888.84 5.9E+03 1.6E+03 nonconstant variance, power unrestricted
exponential (M2) 3 <0.0001 6.23 0.10 901.90 4.6E+03 2.8E+03 constant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 6.23 0.10 901.90 4.6E+03 2.8E+03 constant variance, power restricted ≥ 1
exponential (M4) 2 <0.0001 6.23 0.04 903.90 4.6E+03 8.1E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 6.23 0.04 903.90 4.6E+03 8.1E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 6.23 0.04 903.90 4.6E+03 8.1E+02 constant variance, power unrestricted

Hill 2 <.0001 5.53 0.06 903.19 2.0E+03 3.8E+02 constant variance, n restricted >1, bound hit

Hill 1 <.0001 1.55 0.21 901.22 1.1E+03 1.2E+02 constant variance, n unrestricted

linear 3 <.0001 7.92 0.05 903.59 7.6E+03 5.8E+03 constant variance

polynomial 2 <.0001 6.55 0.04 904.22 5.3E+03 3.3E+03 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-248 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

power 3 <.0001 7.92 0.05 903.59 7.6E+03 5.8E+03 constant variance, power restricted ≥ 1, bound hit

power 2 <.0001 1.46 0.48 899.13 1.0E+03 1.2E+02 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.2.42.2. Figure for Selected Model: Linear, Nonconstant Variance 3

0 500 1000 1500 2000

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Linear Model with 0.95 Confidence Level

13:47 11/16 2009 BMD BMDL Linear

4 5 6 

## E.2.42.3. Output File for Selected Mode l: L inear, Nonconstant Variance 7
8 9

==================================================================== 10 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_PFC_per_cells.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_PFC_per_cells.plt 13 Mon Nov 16 13:47:58 2009 14

==================================================================== 15 16 Anti Response to SRBCs, PFC per 10^6 cells, Table 4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-249 1 The form of the response function is: 2 3 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 4 5 6 Dependent variable = Mean 7 Independent variable = Dose 8 Signs of the polynomial coefficients are not restricted 9 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 10 11 Total number of dose groups = 5 12 Total number of records with missing values = 0 13 Maximum number of iterations = 250 14 Relative Function Convergence has been set to: 1e-008 15 Parameter Convergence has been set to: 1e-008 16 17 18 19 Default Initial Parameter Values 20 lalpha = 12.3562 21 rho = 0 22 beta_0 = 1213.22 23 beta_1 = -0.0629452 24 25 26 Asymptotic Correlation Matrix of Parameter Estimates 27 28 lalpha rho beta_0 beta_1 29 30 lalpha 1 -1 0.081 -0.15 31 32 rho -1 1 -0.08 0.15 33 34 beta_0 0.081 -0.08 1 -0.9 35 36 beta_1 -0.15 0.15 -0.9 1 37 38 39 40 Parameter Estimates 41 42 95.0% Wald Confidence Interval 43 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 44 lalpha 1.72142 1.91282 -2.02764 5.47047 45 rho 1.55211 0.2835 0.99646 2.10776 46 beta_0 1192.68 79.6002 1036.66 1348.69 47 beta_1 -0.0597519 0.00532318 -0.0701851 -0.0493186 48 49 50 51 Table of Data and Estimated Values of Interest 52 53 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 54

------ --- -------- -------- ----------- ----------- ---------- 55 56 0 15 1.49e+003 1.19e+003 716 577 2 57 241.3 14 1.13e+003 1.18e+003 171 572 -0.322 58 1358 15 945 1.11e+003 516 547 -1.18 59 7385 15 677 751 465 403 -0.715 60 1.744e+004 8 161 151 117 116 0.251 61 62 63 64 Model Descriptions for likelihoods calculated 65 66 67 Model A1: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-250 Model A2: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = Sigma(i)^2 2 3 Model A3: Yij = Mu(i) + e(ij) 4 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 5 Model A3 uses any fixed variance parameters that 6 were specified by the user 7 8 Model R: Yi = Mu + e(i) 9 Var{e(i)} = Sigma^2 10 11 12 Likelihoods of Interest 13 14 Model Log(likelihood) # Param's AIC 15 A1 -444.832859 6 901.665718 16 A2 -425.402825 10 870.805651 17 A3 -435.489363 7 884.978727 18 fitted -440.330158 4 888.660316 19 R -463.753685 2 931.507371 20 21 22 Explanation of Tests 23 24 Test 1: Do responses and/or variances differ among Dose levels? 25 (A2 vs. R) 26 Test 2: Are Variances Homogeneous? (A1 vs A2) 27 Test 3: Are variances adequately modeled? (A2 vs. A3) 28 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 29 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 30 31 Tests of Interest 32 33 Test -2*log(Likelihood Ratio) Test df p-value 34 35 Test 1 76.7017 8 <.0001 36 Test 2 38.8601 4 <.0001 37 Test 3 20.1731 3 0.0001563 38 Test 4 9.68159 3 0.02148 39 40 The p-value for Test 1 is less than .05. There appears to be a 41 difference between response and/or variances among the dose levels 42 It seems appropriate to model the data 43 44 The p-value for Test 2 is less than .1. A non-homogeneous variance 45 model appears to be appropriate 46 47 The p-value for Test 3 is less than .1. You may want to consider a 48 different variance model 49 50 The p-value for Test 4 is less than .1. You may want to try a different 51 model 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 1 57 58 Risk Type = Estimated standard deviations from the control mean 59 60 Confidence level = 0.95 61 62 BMD = 9660.48 63 64 65 BMDL = 7755.63 66 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-251 E.2.42.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 1 

## Unrestricted 2

0 500 1000 1500 2000

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:48 11/16 2009 BMD BMDL Exponential

3 4 5 

## E.2.42.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 6 

## Power Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_Unrest_BMR1_PFC_per_cells.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 13:48:00 2009 14

==================================================================== 15 16 Anti Response to SRBCs, PFC per 10^6 cells, Table 4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-252 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 5 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 5 16

-------- -------- 17 lnalpha 3.29848 18 rho 1.2578 19 a 1565.55 20 b 0.000129358 21 c 0.000102839 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 5 29

-------- ------- 30 lnalpha 1.88041 31 rho 1.53102 32 a 1200.9 33 b 9.15015e-005 34 c 0 35 d 1.53838 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 15 1491 716 43 241.3 14 1129 171 44 1358 15 945 516 45 7385 15 677 465 46 1.744e+004 8 161 117 47 48 49 Estimated Values of Interest 50 51 Dose Est Mean Est Std Scaled Residual 52

------ ---------- --------- ---------------- 53 0 1201 583.1 1.927 54 241.3 1198 581.8 -0.4405 55 1358 1153 565.3 -1.427 56 7385 694.8 383.5 -0.1801 57 1.744e+004 154.3 121.2 0.1566 58 59 60 61 Other models for which likelihoods are calculated: 62 63 Model A1: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma^2 65 66 Model A2: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma(i)^2 68 69 Model A3: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-253 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 1 2 Model R: Yij = Mu + e(i) 3 Var{e(ij)} = Sigma^2 4 5 6 Likelihoods of Interest 7 8 Model Log(likelihood) DF AIC 9

------- ----------------- ---- ------------ 10 A1 -444.8329 6 901.6657 11 A2 -425.4028 10 870.8057 12 A3 -435.4894 7 884.9787 13 R -463.7537 2 931.5074 14 5 -440.8331 5 891.6662 15 16 17 Additive constant for all log-likelihoods = -61.57. This constant added to the 18 above values gives the log-likelihood including the term that does not 19 depend on the model parameters. 20 21 22 Explanation of Tests 23 24 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 25 Test 2: Are Variances Homogeneous? (A2 vs. A1) 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 27 28 Test 7a: Does Model 5 fit the data? (A3 vs 5) 29 30 31 Tests of Interest 32 33 Test -2*log(Likelihood Ratio) D. F. p-value 34

-------- ------------------------ ------ -------------- 35 Test 1 76.7 8 < 0.0001 36 Test 2 38.86 4 < 0.0001 37 Test 3 20.17 3 0.0001563 38 Test 7a 10.69 2 0.004778 39 40 41 The p-value for Test 1 is less than .05. There appears to be a 42 difference between response and/or variances among the dose 43 levels, it seems appropriate to model the data. 44 45 The p-value for Test 2 is less than .1. A non-homogeneous 46 variance model appears to be appropriate. 47 48 The p-value for Test 3 is less than .1. You may want to 49 consider a different variance model. 50 51 The p-value for Test 7a is less than .1. Model 5 may not adequately 52 describe the data; you may want to consider another model. 53 54 55 Benchmark Dose Computations: 56 57 Specified Effect = 1.000000 58 59 Risk Type = Estimated standard deviations from control 60 61 Confidence Level = 0.950000 62 63 BMD = 8379.86 64 65 BMDL = 5143.92 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-254 E.2.42.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 1

0 500 1000 1500 2000

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Hill Model

13:48 11/16 2009 BMD Hill

2 3 4 

## E.2.42.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_PFC_per_cells.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_PFC_per_cells.plt 11 Mon Nov 16 13:48:01 2009 12

==================================================================== 13 14 Anti Response to SRBCs, PFC per 10^6 cells, Table 4 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Power parameter is not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 26 27 Total number of dose groups = 5 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 12.3562 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-255 rho = 0 1 intercept = 1491 2 v = -1330 3 n = 0.478435 4 k = 4033.79 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 lalpha rho intercept v n k 10 11 lalpha 1 -1 0.4 -0.047 -0.39 0.16 12 13 rho -1 1 -0.41 0.05 0.39 -0.16 14 15 intercept 0.4 -0.41 1 -0.15 -0.77 0.36 16 17 v -0.047 0.05 -0.15 1 0.37 -0.95 18 19 n -0.39 0.39 -0.77 0.37 1 -0.65 20 21 k 0.16 -0.16 0.36 -0.95 -0.65 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 lalpha 2.8564 2.65961 -2.35633 8.06913 30 rho 1.38249 0.391339 0.615484 2.1495 31 intercept 1309.76 139.641 1036.07 1583.45 32 v -18748.9 37661.1 -92563.2 55065.4 33 n 0.659862 0.240194 0.189091 1.13063 34 k 1.07302e+006 4.27003e+006 -7.29608e+006 9.44213e+006 35 36 37 38 Table of Data and Estimated Values of Interest 39 40 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 41

------ --- -------- -------- ----------- ----------- ---------- 42 43 0 15 1.49e+003 1.31e+003 716 596 1.18 44 241.3 14 1.13e+003 1.24e+003 171 572 -0.703 45 1358 15 945 1.08e+003 516 522 -1.02 46 7385 15 677 633 465 360 0.469 47 1.744e+004 8 161 149 117 133 0.251 48 49 50 51 Model Descriptions for likelihoods calculated 52 53 54 Model A1: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma^2 56 57 Model A2: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma(i)^2 59 60 Model A3: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 62 Model A3 uses any fixed variance parameters that 63 were specified by the user 64 65 Model R: Yi = Mu + e(i) 66 Var{e(i)} = Sigma^2 67 68 69 Likelihoods of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-256 1 Model Log(likelihood) # Param's AIC 2 A1 -444.832859 6 901.665718 3 A2 -425.402825 10 870.805651 4 A3 -435.489363 7 884.978727 5 fitted -439.536553 6 891.073107 6 R -463.753685 2 931.507371 7 8 9 Explanation of Tests 10 11 Test 1: Do responses and/or variances differ among Dose levels? 12 (A2 vs. R) 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 17 18 Tests of Interest 19 20 Test -2*log(Likelihood Ratio) Test df p-value 21 22 Test 1 76.7017 8 <.0001 23 Test 2 38.8601 4 <.0001 24 Test 3 20.1731 3 0.0001563 25 Test 4 8.09438 1 0.00444 26 27 The p-value for Test 1 is less than .05. There appears to be a 28 difference between response and/or variances among the dose levels 29 It seems appropriate to model the data 30 31 The p-value for Test 2 is less than .1. A non-homogeneous variance 32 model appears to be appropriate 33 34 The p-value for Test 3 is less than .1. You may want to consider a 35 different variance model 36 37 The p-value for Test 4 is less than .1. You may want to try a different 38 model 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 6049.74 50 51 52 BMDL computation failed. 53 54 55

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-257 E.2.42.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 500 1000 1500 2000

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Power Model with 0.95 Confidence Level

13:48 11/16 2009 BMD BMDL

Power

2 3 4 

## E.2.42.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_PFC_per_cells.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_PFC_per_cells.plt 12 Mon Nov 16 13:48:05 2009 13

==================================================================== 14 15 Anti Response to SRBCs, PFC per 10^6 cells, Table 4 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-258 Default Initial Parameter Values 1 lalpha = 12.3562 2 rho = 0 3 control = 1491 4 slope = -79.8343 5 power = 0.288026 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho control slope power 11 12 lalpha 1 -1 0.39 -0.42 -0.4 13 14 rho -1 1 -0.41 0.42 0.4 15 16 control 0.39 -0.41 1 -0.81 -0.79 17 18 slope -0.42 0.42 -0.81 1 1 19 20 power -0.4 0.4 -0.79 1 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha 2.91272 2.64894 -2.2791 8.10454 29 rho 1.37364 0.389689 0.60986 2.13741 30 control 1319.7 140.669 1043.99 1595.41 31 slope -2.80443 6.05405 -14.6701 9.06128 32 power 0.617853 0.211323 0.203668 1.03204 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 15 1.49e+003 1.32e+003 716 597 1.11 42 241.3 14 1.13e+003 1.24e+003 171 571 -0.705 43 1358 15 945 1.08e+003 516 519 -0.992 44 7385 15 677 631 465 359 0.494 45 1.744e+004 8 161 149 117 133 0.256 46 47 48 49 Model Descriptions for likelihoods calculated 50 51 52 Model A1: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma^2 54 55 Model A2: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma(i)^2 57 58 Model A3: Yij = Mu(i) + e(ij) 59 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 60 Model A3 uses any fixed variance parameters that 61 were specified by the user 62 63 Model R: Yi = Mu + e(i) 64 Var{e(i)} = Sigma^2 65 66 67 Likelihoods of Interest 68 69 Model Log(likelihood) # Param's AIC 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-259 A1 -444.832859 6 901.665718 1 A2 -425.402825 10 870.805651 2 A3 -435.489363 7 884.978727 3 fitted -439.417961 5 888.835922 4 R -463.753685 2 931.507371 5 6 7 Explanation of Tests 8 9 Test 1: Do responses and/or variances differ among Dose levels? 10 (A2 vs. R) 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 15 16 Tests of Interest 17 18 Test -2*log(Likelihood Ratio) Test df p-value 19 20 Test 1 76.7017 8 <.0001 21 Test 2 38.8601 4 <.0001 22 Test 3 20.1731 3 0.0001563 23 Test 4 7.85719 2 0.01967 24 25 The p-value for Test 1 is less than .05. There appears to be a 26 difference between response and/or variances among the dose levels 27 It seems appropriate to model the data 28 29 The p-value for Test 2 is less than .1. A non-homogeneous variance 30 model appears to be appropriate 31 32 The p-value for Test 3 is less than .1. You may want to consider a 33 different variance model 34 35 The p-value for Test 4 is less than .1. You may want to try a different 36 model 37 38 39 Benchmark Dose Computation 40 41 Specified effect = 1 42 43 Risk Type = Estimated standard deviations from the control mean 44 45 Confidence level = 0.95 46 47 BMD = 5856.4 48 49 50 BMDL = 1632.55 51 52 53 54

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-260 E.2.43. Smialowicz et al. (2008): PFC per Spleen 1 

## E.2.43.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 0.00 5.76 0.12 377.56 7.4E+03 4.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.00 5.34 0.07 379.14 8.5E+03 4.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.00 5.76 0.12 377.56 7.4E+03 4.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.00 5.34 0.02 381.14 8.5E+03 4.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) d 1 0.00 5.34 0.02 381.14 8.5E+03 4.9E+03 nonconstant variance, power unrestricted

Hill 2 0.00 4.31 0.12 378.11 8.6E+03 error nonconstant variance, n restricted >1, bound hit

Hill d 1 0.00 2.66 0.10 378.46 6.6E+03 error nonconstant variance, n unrestricted

linear c 3 0.00 5.72 0.13 377.52 1.1E+04 8.9E+03 nonconstant variance
polynomial 2 0.00 4.49 0.11 378.29 8.9E+03 5.7E+03 nonconstant variance

power 3 0.00 5.72 0.13 377.52 1.1E+04 8.9E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 2 0.00 2.62 0.27 376.42 6.5E+03 2.1E+03 nonconstant variance, power unrestricted
exponential (M2) 3 0.00 4.38 0.22 391.51 5.8E+03 3.2E+03 constant variance, power restricted ≥ 1
exponential (M3) 3 0.00 4.38 0.22 391.51 5.8E+03 3.2E+03 constant variance, power restricted ≥ 1
exponential (M4) 2 0.00 4.38 0.11 393.51 5.8E+03 8.0E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 0.00 4.38 0.11 393.51 5.8E+03 8.0E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 0.00 4.38 0.11 393.51 5.8E+03 8.0E+02 constant variance, power unrestricted

Hill 2 0.00 3.87 0.14 393.00 2.7E+03 4.0E+02 constant variance, n restricted >1, bound hit

Hill 1 0.00 1.06 0.30 392.19 1.8E+03 1.8E+02 constant variance, n unrestricted

linear 3 0.00 5.59 0.13 392.72 9.0E+03 6.7E+03 constant variance

polynomial 2 0.00 4.61 0.10 393.74 6.5E+03 3.8E+03 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-261 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

power 3 0.00 5.59 0.13 392.72 9.0E+03 6.7E+03 constant variance, power restricted ≥ 1, bound hit

power 2 0.00 1.01 0.60 390.14 1.8E+03 1.8E+02 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.2.43.2. Figure for Selected Model: Linear, Nonconstant Variance 3

0 5 10 15 20 25 30 35

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Linear Model with 0.95 Confidence Level

13:45 11/16 2009 BMD BMDL Linear

4 5 

## E.2.43.3. Output File for Selected Mode l: L inear, Nonconstant Variance 6
7 8

==================================================================== 9 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_PFC_per_spleen.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Linear_BMR1_PFC_per_spleen.plt 12 Mon Nov 16 13:45:55 2009 13

==================================================================== 14 15 Anti Response to SRBCs - PFC x 10 to the 4 per spleen, Table 4 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-262 The form of the response function is: 1 2 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 3 4 5 Dependent variable = Mean 6 Independent variable = Dose 7 Signs of the polynomial coefficients are not restricted 8 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 9 10 Total number of dose groups = 5 11 Total number of records with missing values = 0 12 Maximum number of iterations = 250 13 Relative Function Convergence has been set to: 1e-008 14 Parameter Convergence has been set to: 1e-008 15 16 17 18 Default Initial Parameter Values 19 lalpha = 4.76607 20 rho = 0 21 beta_0 = 22.5956 22 beta_1 = -0.00117245 23 24 25 Asymptotic Correlation Matrix of Parameter Estimates 26 27 lalpha rho beta_0 beta_1 28 29 lalpha 1 -0.97 0.031 -0.021 30 31 rho -0.97 1 -0.034 0.026 32 33 beta_0 0.031 -0.034 1 -0.88 34 35 beta_1 -0.021 0.026 -0.88 1 36 37 38 39 Parameter Estimates 40 41 95.0% Wald Confidence Interval 42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 43 lalpha 0.491077 0.742891 -0.964962 1.94712 44 rho 1.47094 0.264097 0.953314 1.98856 45 beta_0 22.151 1.72621 18.7677 25.5343 46 beta_1 -0.00110204 0.000118826 -0.00133493 -0.000869145 47 48 49 50 Table of Data and Estimated Values of Interest 51 52 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 53

------ --- -------- -------- ----------- ----------- ---------- 54 55 0 15 27.8 22.2 13.4 12.5 1.75 56 241.3 14 21 21.9 13.6 12.4 -0.268 57 1358 15 17.6 20.7 9.4 11.9 -0.998 58 7385 15 12.6 14 8.7 8.91 -0.614 59 1.744e+004 8 3 2.93 3.1 2.82 0.0665 60 61 62 63 Model Descriptions for likelihoods calculated 64 65 66 Model A1: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma^2 68 69 Model A2: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-263 Var{e(ij)} = Sigma(i)^2 1 2 Model A3: Yij = Mu(i) + e(ij) 3 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 4 Model A3 uses any fixed variance parameters that 5 were specified by the user 6 7 Model R: Yi = Mu + e(i) 8 Var{e(i)} = Sigma^2 9 10 11 Likelihoods of Interest 12 13 Model Log(likelihood) # Param's AIC 14 A1 -190.565019 6 393.130038 15 A2 -181.476284 10 382.952569 16 A3 -181.900030 7 377.800059 17 fitted -184.760998 4 377.521996 18 R -204.636496 2 413.272993 19 20 21 Explanation of Tests 22 23 Test 1: Do responses and/or variances differ among Dose levels? 24 (A2 vs. R) 25 Test 2: Are Variances Homogeneous? (A1 vs A2) 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 27 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 28 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 29 30 Tests of Interest 31 32 Test -2*log(Likelihood Ratio) Test df p-value 33 34 Test 1 46.3204 8 <.0001 35 Test 2 18.1775 4 0.001139 36 Test 3 0.84749 3 0.8381 37 Test 4 5.72194 3 0.126 38 39 The p-value for Test 1 is less than .05. There appears to be a 40 difference between response and/or variances among the dose levels 41 It seems appropriate to model the data 42 43 The p-value for Test 2 is less than .1. A non-homogeneous variance 44 model appears to be appropriate 45 46 The p-value for Test 3 is greater than .1. The modeled variance appears 47 to be appropriate here 48 49 The p-value for Test 4 is greater than .1. The model chosen seems 50 to adequately describe the data 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 1 56 57 Risk Type = Estimated standard deviations from the control mean 58 59 Confidence level = 0.95 60 61 BMD = 11322.2 62 63 64 BMDL = 8948.34 65 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-264 E.2.43.4. Figure for UnrestrictedModel: Exponen tial (M5), Nonconstant Varian ce, Power 1 

## Unrestricted 2

0 5 10 15 20 25 30 35

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:45 11/16 2009 BMD BMDL Exponential

3 4 5 

## E.2.43.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 6 

## Power Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_Unrest_BMR1_PFC_per_spleen.(d) 12 Gnuplot Plotting File: 13 Mon Nov 16 13:45:56 2009 14

==================================================================== 15 16 Anti Response to SRBCs - PFC x 10 to the 4 per spleen, Table 4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-265 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 5 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 5 16

-------- -------- 17 lnalpha 0.786146 18 rho 1.36372 19 a 29.19 20 b 0.000129431 21 c 0.000102775 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 5 29

-------- ------- 30 lnalpha 0.52811 31 rho 1.45744 32 a 23.1604 33 b 9.96651e-005 34 c 6.92509e-030 35 d 1.23518 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 15 27.8 13.4 43 241.3 14 21 13.6 44 1358 15 17.6 9.4 45 7385 15 12.6 8.7 46 1.744e+004 8 3 3.1 47 48 49 Estimated Values of Interest 50 51 Dose Est Mean Est Std Scaled Residual 52

------ ---------- --------- ---------------- 53 0 23.16 12.86 1.397 54 241.3 22.93 12.77 -0.5656 55 1358 21.28 12.09 -1.18 56 7385 11.68 7.807 0.4578 57 1.744e+004 3.2 3.04 -0.1864 58 59 60 61 Other models for which likelihoods are calculated: 62 63 Model A1: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma^2 65 66 Model A2: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma(i)^2 68 69 Model A3: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-266 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 1 2 Model R: Yij = Mu + e(i) 3 Var{e(ij)} = Sigma^2 4 5 6 Likelihoods of Interest 7 8 Model Log(likelihood) DF AIC 9

------- ----------------- ---- ------------ 10 A1 -190.565 6 393.13 11 A2 -181.4763 10 382.9526 12 A3 -181.9 7 377.8001 13 R -204.6365 2 413.273 14 5 -184.5689 6 381.1378 15 16 17 Additive constant for all log-likelihoods = -61.57. This constant added to the 18 above values gives the log-likelihood including the term that does not 19 depend on the model parameters. 20 21 22 Explanation of Tests 23 24 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 25 Test 2: Are Variances Homogeneous? (A2 vs. A1) 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 27 28 Test 7a: Does Model 5 fit the data? (A3 vs 5) 29 30 31 Tests of Interest 32 33 Test -2*log(Likelihood Ratio) D. F. p-value 34

-------- ------------------------ ------ -------------- 35 Test 1 46.32 8 < 0.0001 36 Test 2 18.18 4 0.001139 37 Test 3 0.8475 3 0.8381 38 Test 7a 5.338 1 0.02087 39 40 41 The p-value for Test 1 is less than .05. There appears to be a 42 difference between response and/or variances among the dose 43 levels, it seems appropriate to model the data. 44 45 The p-value for Test 2 is less than .1. A non-homogeneous 46 variance model appears to be appropriate. 47 48 The p-value for Test 3 is greater than .1. The modeled 49 variance appears to be appropriate here. 50 51 The p-value for Test 7a is less than .1. Model 5 may not adequately 52 describe the data; you may want to consider another model. 53 54 55 Benchmark Dose Computations: 56 57 Specified Effect = 1.000000 58 59 Risk Type = Estimated standard deviations from control 60 61 Confidence Level = 0.950000 62 63 BMD = 8460.94 64 65 BMDL = 4901.02 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-267 E.2.43.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 1

0 5 10 15 20 25 30 35

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Hill Model

13:45 11/16 2009 BMD Hill

2 3 4 

## E.2.43.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_PFC_per_spleen.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_PFC_per_spleen.plt 11 Mon Nov 16 13:45:57 2009 12

==================================================================== 13 14 Anti Response to SRBCs - PFC x 10 to the 4 per spleen, Table 4 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Power parameter is not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 26 27 Total number of dose groups = 5 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 4.76607 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-268 rho = 0 1 intercept = 27.8 2 v = -24.8 3 n = 0.476652 4 k = 4009.51 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 lalpha rho intercept v n k 10 11 lalpha 1 -0.98 0.24 0.03 -0.21 0.019 12 13 rho -0.98 1 -0.3 -0.026 0.21 -0.021 14 15 intercept 0.24 -0.3 1 0.079 -0.73 0.1 16 17 v 0.03 -0.026 0.079 1 0.019 -0.96 18 19 n -0.21 0.21 -0.73 0.019 1 -0.28 20 21 k 0.019 -0.021 0.1 -0.96 -0.28 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 lalpha 0.742099 1.02085 -1.25872 2.74292 30 rho 1.37015 0.355955 0.67249 2.06781 31 intercept 25.3072 2.92734 19.5697 31.0447 32 v -1195.09 4993.33 -10981.8 8591.65 33 n 0.543247 0.174917 0.200417 0.886078 34 k 2.57198e+007 2.10767e+008 -3.87375e+008 4.38815e+008 35 36 37 38 Table of Data and Estimated Values of Interest 39 40 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 41

------ --- -------- -------- ----------- ----------- ---------- 42 43 0 15 27.8 25.3 13.4 13.3 0.728 44 241.3 14 21 23.1 13.6 12.5 -0.629 45 1358 15 17.6 19.7 9.4 11.2 -0.716 46 7385 15 12.6 11.2 8.7 7.6 0.691 47 1.744e+004 8 3 3.03 3.1 3.1 -0.03 48 49 50 51 Model Descriptions for likelihoods calculated 52 53 54 Model A1: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma^2 56 57 Model A2: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma(i)^2 59 60 Model A3: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 62 Model A3 uses any fixed variance parameters that 63 were specified by the user 64 65 Model R: Yi = Mu + e(i) 66 Var{e(i)} = Sigma^2 67 68 69 Likelihoods of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-269 1 Model Log(likelihood) # Param's AIC 2 A1 -190.565019 6 393.130038 3 A2 -181.476284 10 382.952569 4 A3 -181.900030 7 377.800059 5 fitted -183.230840 6 378.461681 6 R -204.636496 2 413.272993 7 8 9 Explanation of Tests 10 11 Test 1: Do responses and/or variances differ among Dose levels? 12 (A2 vs. R) 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 17 18 Tests of Interest 19 20 Test -2*log(Likelihood Ratio) Test df p-value 21 22 Test 1 46.3204 8 <.0001 23 Test 2 18.1775 4 0.001139 24 Test 3 0.84749 3 0.8381 25 Test 4 2.66162 1 0.1028 26 27 The p-value for Test 1 is less than .05. There appears to be a 28 difference between response and/or variances among the dose levels 29 It seems appropriate to model the data 30 31 The p-value for Test 2 is less than .1. A non-homogeneous variance 32 model appears to be appropriate 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 The p-value for Test 4 is greater than .1. The model chosen seems 38 to adequately describe the data 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 6615.87 50 51 52 BMDL computation failed. 53 54 55

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-270 E.2.43.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 5 10 15 20 25 30 35

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Mean Response

dose Power Model with 0.95 Confidence Level

13:45 11/16 2009 BMD BMDL Power

2 3 4 

## E.2.43.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_PFC_per_spleen.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Power_Unrest_BMR1_PFC_per_spleen.plt 12 Mon Nov 16 13:45:57 2009 13

==================================================================== 14 15 Anti Response to SRBCs - PFC x 10 to the 4 per spleen, Table 4 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-271 Default Initial Parameter Values 1 lalpha = 4.76607 2 rho = 0 3 control = 27.8 4 slope = -1.51177 5 power = 0.286447 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho control slope power 11 12 lalpha 1 -0.98 0.25 -0.24 -0.22 13 14 rho -0.98 1 -0.3 0.25 0.22 15 16 control 0.25 -0.3 1 -0.78 -0.74 17 18 slope -0.24 0.25 -0.78 1 1 19 20 power -0.22 0.22 -0.74 1 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha 0.746924 1.02058 -1.25337 2.74721 29 rho 1.36826 0.355827 0.670849 2.06566 30 control 25.3818 2.96695 19.5666 31.1969 31 slope -0.124774 0.226126 -0.567972 0.318425 32 power 0.531205 0.175723 0.186794 0.875617 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 15 27.8 25.4 13.4 13.3 0.705 42 241.3 14 21 23.1 13.6 12.4 -0.626 43 1358 15 17.6 19.6 9.4 11.1 -0.704 44 7385 15 12.6 11.2 8.7 7.6 0.702 45 1.744e+004 8 3 3.03 3.1 3.1 -0.0313 46 47 48 49 Model Descriptions for likelihoods calculated 50 51 52 Model A1: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma^2 54 55 Model A2: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma(i)^2 57 58 Model A3: Yij = Mu(i) + e(ij) 59 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 60 Model A3 uses any fixed variance parameters that 61 were specified by the user 62 63 Model R: Yi = Mu + e(i) 64 Var{e(i)} = Sigma^2 65 66 67 Likelihoods of Interest 68 69 Model Log(likelihood) # Param's AIC 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-272 A1 -190.565019 6 393.130038 1 A2 -181.476284 10 382.952569 2 A3 -181.900030 7 377.800059 3 fitted -183.210067 5 376.420134 4 R -204.636496 2 413.272993 5 6 7 Explanation of Tests 8 9 Test 1: Do responses and/or variances differ among Dose levels? 10 (A2 vs. R) 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 15 16 Tests of Interest 17 18 Test -2*log(Likelihood Ratio) Test df p-value 19 20 Test 1 46.3204 8 <.0001 21 Test 2 18.1775 4 0.001139 22 Test 3 0.84749 3 0.8381 23 Test 4 2.62008 2 0.2698 24 25 The p-value for Test 1 is less than .05. There appears to be a 26 difference between response and/or variances among the dose levels 27 It seems appropriate to model the data 28 29 The p-value for Test 2 is less than .1. A non-homogeneous variance 30 model appears to be appropriate 31 32 The p-value for Test 3 is greater than .1. The modeled variance appears 33 to be appropriate here 34 35 The p-value for Test 4 is greater than .1. The model chosen seems 36 to adequately describe the data 37 38 39 Benchmark Dose Computation 40 41 Specified effect = 1 42 43 Risk Type = Estimated standard deviations from the control mean 44 45 Confidence level = 0.95 46 47 BMD = 6542.48 48 49 50 BMDL = 2072.46 51 52 53 54

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-273 E.2.44. Toth et al. (1978): Amyloidosis 1 

## E.2.44.1. Summary Table of BMDS Modeling Results 2



## Amyloidosis (Toth et al. (1978))

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 p-Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 2 6.45 0.04 149.12 1.1E+04 7.0E+03 power restricted ≥ 1, bound hit
logistic 2 7.91 0.02 151.34 2.0E+04 1.6E+04

log-logistic b 2 5.86 0.05 148.27 8.3E+03 4.8E+03 slope restricted ≥ 1, bound hit
log-logistic c 2 0.20 0.90 140.24 2.7E+02 2.9E+00 slope unrestricted

log-probit 2 9.94 0.007 153.52 2.2E+04 1.5E+4 slope restricted ≥ 1, bound hit
log-probit 2 0.28 0.87 140.32 2.7E+02 4.0E+00 slope unrestricted

multistage 2 6.45 0.04 149.12 1.1E+04 7.0E+03 betas restricted ≥ 0

probit 2 7.75 0.02 151.11 1.9E+04 1.5E+04

Weibull 2 6.45 0.04 149.12 1.1E+04 7.0E+03 power restricted ≥ 1, bound hit

Weibull 3 0.00 1.00 140.03 2.0E+02 1.9E+00 power unrestricted

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-274 1 

## E.2.44.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1 2

3

0 0.1 0.2 0.3 0.4 0.5 0.6

0 10000 20000 30000 40000 50000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

13:39 11/16 2009 BMDL BMD Log-Logistic

4 5 6 

## E.2.44.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1 7
8

==================================================================== 9 Logistic Model. (Version: 2.12; Date: 05/16/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR1_Amyloidosis.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR1_Amyloidosis.plt 13 Mon Nov 16 13:39:45 2009 14

==================================================================== 15 16 Table 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the probability function is: 20 21 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 22 23 24 Dependent variable = DichEff 25 Independent variable = Dose 26 Slope parameter is restricted as slope >= 1 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-275 1 User has chosen the log transformed model 2 3 4 Default Initial Parameter Values 5 background = 0 6 intercept = -10.8548 7 slope = 1 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -slope 13 have been estimated at a boundary point, or have been specified by 14 the user, 15 and do not appear in the correlation matrix ) 16 17 background intercept 18 19 background 1 -0.49 20 21 intercept -0.49 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence 28 Interval 29 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. 30 Limit 31 background 0.0699641 * * * 32 intercept -11.2157 * * * 33 slope 1 * * * 34 35 * - Indicates that this value is not calculated. 36 37 38 39 Analysis of Deviance Table 40 41 Model Log(likelihood) # Param's Deviance Test d.f. P-value 42 Full model -68.017 4 43 Fitted model -72.1329 2 8.23187 2 0.01631 44 Reduced model -82.0119 1 27.99 3 <.0001 45 46 AIC: 148.266 47 48 49 Goodness of Fit 50 Scaled 51 Dose Est._Prob. Expected Observed Size Residual 52

------------------------------------------------------------------------ 53 0.0000 0.0700 2.659 0.000 38 -1.691 54 315.4949 0.0739 3.251 5.000 44 1.008 55 7814.0188 0.1585 6.973 10.000 44 1.250 56 50105.0000 0.4446 19.117 17.000 43 -0.650 57 58 Chi^2 = 5.86 d.f. = 2 P-value = 0.0535 59 60 61 Benchmark Dose Computation 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-276 1 Specified effect = 0.1 2 3 Risk Type = Extra risk 4 5 Confidence level = 0.95 6 7 BMD = 8254.29 8 9 BMDL = 4805.18 10 11 12 13 

## E.2.44.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 14

0 0.1 0.2 0.3 0.4 0.5 0.6

0 10000 20000 30000 40000 50000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

13:39 11/16 2009 BMDL BMD Log-Logistic

15 16 17 

## E.2.44.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 18
19 20

==================================================================== 21 Logistic Model. (Version: 2.12; Date: 05/16/2008) 22 Input Data File: C:\USEPA\BMDS21\AD\Blood\LogLogistic_Unrest_BMR1_Amyloidosis.(d) 23 Gnuplot Plotting File: 24 C:\USEPA\BMDS21\AD\Blood\LogLogistic_Unrest_BMR1_Amyloidosis.plt 25 Mon Nov 16 13:39:45 2009 26

==================================================================== 27 28 Table 2 29

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 31 The form of the probability function is: 32 33 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 34

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-277 1 2 Dependent variable = DichEff 3 Independent variable = Dose 4 Slope parameter is not restricted 5 6 Total number of observations = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 13 14 User has chosen the log transformed model 15 16 17 Default Initial Parameter Values 18 background = 0 19 intercept = -3.91243 20 slope = 0.314588 21 22 23 Asymptotic Correlation Matrix of Parameter Estimates 24 25 ( *** The model parameter(s) -background 26 have been estimated at a boundary point, or have been specified by the user, 27 and do not appear in the correlation matrix ) 28 29 intercept slope 30 31 intercept 1 -0.98 32 33 slope -0.98 1 34 35 36 37 Parameter Estimates 38 39 95.0% Wald Confidence Interval 40 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 41 background 0 * * * 42 intercept -4.01968 * * * 43 slope 0.326277 * * * 44 45 * - Indicates that this value is not calculated. 46 47 48 49 Analysis of Deviance Table 50 51 Model Log(likelihood) # Param's Deviance Test d.f. P-value 52 Full model -68.017 4 53 Fitted model -68.1202 2 0.206421 2 0.9019 54 Reduced model -82.0119 1 27.99 3 <.0001 55 56 AIC: 140.24 57 58 59 Goodness of Fit 60 Scaled 61 Dose Est._Prob. Expected Observed Size Residual 62

------------------------------------------------------------------------ 63 0.0000 0.0000 0.000 0.000 38 0.000 64 315.4949 0.1051 4.623 5.000 44 0.186 65 7814.0188 0.2507 11.029 10.000 44 -0.358 66 50105.0000 0.3802 16.348 17.000 43 0.205 67 68 Chi^2 = 0.20 d.f. = 2 P-value = 0.9028 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-278 1 Benchmark Dose Computation 2 3 Specified effect = 0.1 4 5 Risk Type = Extra risk 6 7 Confidence level = 0.95 8 9 BMD = 266.567 10 11 BMDL = 2.92895 12 13 14 15 

## E.2.44.6. Figure for Unrestricted Model: Log-Probit, S lope Restricted ≥ 1 16

0 0.1 0.2 0.3 0.4 0.5 0.6

0 10000 20000 30000 40000 50000Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

13:39 11/16 2009 BMDL BMD LogProbit

17 18 19 

## E.2.44.7. Output File for Unrestricted Mode l: Log-Probit, Slope Restricted ≥ 1 20
21 22

==================================================================== 23 Probit Model. (Version: 3.1; Date: 05/16/2008) 24 Input Data File: C:\USEPA\BMDS21\AD\Blood\LogProbit_BMR1_Amyloidosis.(d) 25 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\LogProbit_BMR1_Amyloidosis.plt 26 Mon Nov 16 13:39:45 2009 27

==================================================================== 28 29 Table 2 30

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 31 32 The form of the probability function is: 33 34 P[response] = Background 35 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-279 1 where CumNorm(.) is the cumulative normal distribution function 2 3 4 Dependent variable = DichEff 5 Independent variable = Dose 6 Slope parameter is not restricted 7 8 Total number of observations = 4 9 Total number of records with missing values = 0 10 Maximum number of iterations = 250 11 Relative Function Convergence has been set to: 1e-008 12 Parameter Convergence has been set to: 1e-008 13 14 15 16 User has chosen the log transformed model 17 18 19 Default Initial (and Specified) Parameter Values 20 background = 0 21 intercept = -2.2812 22 slope = 0.180958 23 24 25 Asymptotic Correlation Matrix of Parameter Estimates 26 27 ( *** The model parameter(s) -background 28 have been estimated at a boundary point, or have been specified by the user, 29 and do not appear in the correlation matrix ) 30 31 intercept slope 32 33 intercept 1 -0.98 34 35 slope -0.98 1 36 37 38 39 Parameter Estimates 40 41 95.0% Wald Confidence Interval 42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 43 background 0 NA 44 intercept -2.3225 0.57595 -3.45134 -1.19365 45 slope 0.185565 0.0628719 0.0623389 0.308792 46 47 NA - Indicates that this parameter has hit a bound 48 implied by some inequality constraint and thus 49 has no standard error. 50 51 52 53 Analysis of Deviance Table 54 55 Model Log(likelihood) # Param's Deviance Test d.f. P-value 56 Full model -68.017 4 57 Fitted model -68.1574 2 0.280896 2 0.869 58 Reduced model -82.0119 1 27.99 3 <.0001 59 60 AIC: 140.315 61 62 63 Goodness of Fit 64 Scaled 65 Dose Est._Prob. Expected Observed Size Residual 66

------------------------------------------------------------------------ 67 0.0000 0.0000 0.000 0.000 38 0.000 68 315.4949 0.1048 4.611 5.000 44 0.192 69 7814.0188 0.2549 11.216 10.000 44 -0.421 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-280 50105.0000 0.3766 16.195 17.000 43 0.253 1 2 Chi^2 = 0.28 d.f. = 2 P-value = 0.8704 3 4 5 Benchmark Dose Computation 6 7 Specified effect = 0.1 8 9 Risk Type = Extra risk 10 11 Confidence level = 0.95 12 13 BMD = 273.029 14 15 BMDL = 4.02007 16 17 18 19 

## E.2.45. Toth et al. (1978): Skin Lesions 20 

## E.2.45.1. Summary Table of BMDS Modeling Results 21

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 p-Value a AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

gamma 2 6.89 0.03 156.34 5.7E+03 4.1E+03 power restricted ≥ 1, bound hit
logistic 2 10.70 0.00 161.42 1.4E+04 1.1E+04

log-logistic b 2 5.09 0.08 153.96 3.5E+03 2.2E+03 slope restricted ≥ 1, bound hit
log-logistic c 2 0.04 0.95 147.08 2.60E+02 3.18E+01 slope urestricted

log-probit 2 14.29 <0.001 164.79 1.24E+04 8.31E+03 slope restricted ≥ 1, bound hit
log-probit 2 0.80 0.67 147.84 3.3E+02 4.5E+01 slope unrestricted ≥ 1

multistage 2 6.89 0.03 156.34 5.7E+03 4.1E+03 betas restricted ≥ 0

probit 2 10.39 0.01 160.99 1.3E+04 1.0E+04

Weibull 2 6.89 0.03 156.34 5.7E+03 4.1E+03 power restricted ≥ 1, bound hit

Weibull 2 0.00 1.00 147.04 2.19E+02 2.08E+01 power unrestricted

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 22 23

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-281 E.2.45.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10000 20000 30000 40000 50000Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

13:30 11/16 2009 BMDL BMD LogProbit

2 3 4 

## E.2.45.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\A\Blood\LogLogistic_BMR2_Skin_lesion_1yr.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\AD\Blood\LogLogistic_BMR2_Skin_lesion_1yr.plt 12 Mon Nov 16 13:30:07 2009 13

==================================================================== 14 15 Table 2 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 21 22 23 Dependent variable = DichEff 24 Independent variable = Dose 25 Slope parameter is restricted as slope >= 1 26 27 Total number of observations = 4 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-282 1 2 User has chosen the log transformed model 3 4 5 Default Initial Parameter Values 6 background = 0 7 intercept = -10.252 8 slope = 1 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -slope 14 have been estimated at a boundary point, or have been specified by 15 the user, 16 and do not appear in the correlation matrix ) 17 18 background intercept 19 20 background 1 -0.43 21 22 intercept -0.43 1 23 24 25 26 Parameter Estimates 27 28 95.0% Wald Confidence 29 Interval 30 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. 31 Limit 32 background 0.0564295 * * * 33 intercept -10.3645 * * * 34 slope 1 * * * 35 36 * - Indicates that this value is not calculated. 37 38 39 40 Analysis of Deviance Table 41 42 Model Log(likelihood) # Param's Deviance Test d.f. P-value 43 Full model -71.5177 4 44 Fitted model -74.9791 2 6.92292 2 0.03138 45 Reduced model -95.8498 1 48.6642 3 <.0001 46 47 AIC: 153.958 48 49 50 Goodness of Fit 51 Scaled 52 Dose Est._Prob. Expected Observed Size Residual 53

------------------------------------------------------------------------ 54 0.0000 0.0564 2.144 0.000 38 -1.508 55 315.4949 0.0657 2.892 5.000 44 1.283 56 7814.0188 0.2430 10.690 13.000 44 0.812 57 50105.0000 0.6343 27.273 25.000 43 -0.720 58 59 Chi^2 = 5.09 d.f. = 2 P-value = 0.0783 60 61 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-283 Benchmark Dose Computation 1 2 Specified effect = 0.1 3 4 Risk Type = Extra risk 5 6 Confidence level = 0.95 7 8 BMD = 3523.85 9 10 BMDL = 2211.53 11 12 13 14 

## E.2.45.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 15

16

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10000 20000 30000 40000 50000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

07:51 11/27 2009 BMDLBMD Log-Logistic

17 18 19 

## E.2.45.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 20

21

==================================================================== 22 Logistic Model. (Version: 2.12; Date: 05/16/2008) 23 Input Data File: C:\Usepa\Bmds2\Data\LogTcdSet.(d) 24 Gnuplot Plotting File: C:\Usepa\Bmds2\Data\LogTcdSet.plt 25 Fri Nov 27 07:51:12 2009 26

==================================================================== 27 28 BMDS Model Run 29

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 31 The form of the probability function is: 32 33 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-284 1 Dependent variable = r_skin 2 Independent variable = DOSE 3 Slope parameter is not restricted 4 5 Total number of observations = 4 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 12 13 User has chosen the log transformed model 14 15 16 Default Initial Parameter Values 17 background = 0 18 intercept = -4.78342 19 slope = 0.469549 20 21 22 Asymptotic Correlation Matrix of Parameter Estimates 23 24 ( *** The model parameter(s) -background 25 have been estimated at a boundary point, or have been specified by 26 the user, 27 and do not appear in the correlation matrix ) 28 29 intercept slope 30 31 intercept 1 -0.98 32 33 slope -0.98 1 34 35 36 37 Parameter Estimates 38 39 95.0% Wald Confidence 40 Interval 41 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. 42 Limit 43 background 0 * * * 44 intercept -4.84059 * * * 45 slope 0.475472 * * * 46 47 * - Indicates that this value is not calculated. 48 49 50 51 Analysis of Deviance Table 52 53 Model Log(likelihood) # Param's Deviance Test d.f. P-value 54 Full model -71.5177 4 55 Fitted model -71.5376 2 0.0398444 2 0.9803 56 Reduced model -95.8498 1 48.6642 3 <.0001 57 58 AIC: 147.075 59 60 61 Goodness of Fit 62

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-285 Scaled 1 Dose Est._Prob. Expected Observed Size Residual 2

------------------------------------------------------------------------ 3 0.0000 0.0000 0.000 0.000 38 0.000 4 316.0000 0.1087 4.784 5.000 44 0.105 5 4714.0000 0.3060 13.464 13.000 44 -0.152 6 50105.0000 0.5756 24.753 25.000 43 0.076 7 8 Chi^2 = 0.04 d.f. = 2 P-value = 0.9803 9 10 11 Benchmark Dose Computation 12 13 Specified effect = 0.1 14 15 Risk Type = Extra risk 16 17 Confidence level = 0.95 18 19 BMD = 259.682 20 21 BMDL = 31.788 22 23 24 25 

## E.2.46. Van Birgelen et al. (1995a): Hepatic Retinol 26 

## E.2.46.1. Summary Table of BMDS Modeling Results 27

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 4 <0.0001 41.09 <0.0001 159.73 4.3E+03 2.3E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 40.44 <0.0001 159.09 3.4E+04 2.4E+03 nonconstant variance, power restricted ≥ 1 exponential (M4)

c 3 <0.0001 20.80 0.00 141.45 1.4E+04 1.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 20.80 0.00 141.45 1.4E+04 1.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 <0.0001 20.80 0.00 141.45 1.4E+04 1.9E+03 nonconstant variance, power unrestricted

Hill 3 <.0001 4.22 0.24 124.86 2.9E+03 error nonconstant variance, n restricted >1, bound hit

Hill d 2 <.0001 2.85 0.24 125.50 2.0E+03 error nonconstant variance, n unrestricted

linear 4 <.0001 58.18 <.0001 176.83 1.0E+05 7.9E+04 nonconstant variance

polynomial 4 <.0001 58.18 <.0001 176.83 1.0E+05 7.9E+04 nonconstant variance

power 4 <.0001 58.18 <.0001 176.83 1.0E+05 7.9E+04 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 11.12 0.01 131.77 2.1E+02 7.7E+00 nonconstant variance, power unrestricted

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-286 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 4 <0.0001 3.87 0.42 184.19 3.0E+03 1.9E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 3.87 0.42 184.19 3.0E+03 1.9E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 1.84 0.61 184.15 2.7E+03 1.7E+03 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 1.84 0.61 184.15 2.7E+03 1.7E+03 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 1.84 0.61 184.15 2.7E+03 1.7E+03 constant variance, power unrestricted

Hill 3 <.0001 1.04 0.79 183.36 2.1E+03 1.1E+03 constant variance, n restricted >1, bound hit

Hill 2 <.0001 0.98 0.61 185.29 1.7E+03 4.0E+01 constant variance, n unrestricted

linear 4 <.0001 25.63 <.0001 205.94 6.8E+04 5.0E+04 constant variance

polynomial 4 <.0001 25.63 <.0001 205.94 6.8E+04 5.0E+04 constant variance

power 4 <.0001 25.63 <.0001 205.94 6.8E+04 5.0E+04 constant variance, power restricted ≥ 1, bound hit

power 3 <.0001 2.28 0.52 184.60 2.1E+02 6.2E+00 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-287 E.2.46.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

0 5 10 15 20

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:28 11/20 2009 BMD BMDL Exponential

3 4 5 

## E.2.46.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_hepatic_retinol.(d) 12 Gnuplot Plotting File: 13 Fri Nov 20 12:28:01 2009 14

==================================================================== 15 16 Tbl3, hepatic retinol 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-288 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 6 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 4 16

-------- -------- 17 lnalpha -1.16065 18 rho 1.53688 19 a 15.645 20 b 4.61687e-005 21 c 0.0365247 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 4 29

-------- ------- 30 lnalpha -0.926841 31 rho 1.77261 32 a 11.5052 33 b 5.20223e-005 34 c 0.0653036 35 d 1 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 8 14.9 8.768 43 3969 8 8.4 3.394 44 6479 8 8.2 2.263 45 9968 8 5.1 0.8485 46 4.761e+004 8 2.2 0.8485 47 1.378e+005 8 0.6 0.5657 48 49 50 Estimated Values of Interest 51 52 Dose Est Mean Est Std Scaled Residual 53

------ ---------- --------- ---------------- 54 0 11.51 5.483 1.751 55 3969 9.499 4.627 -0.6719 56 6479 8.428 4.161 -0.1551 57 9968 7.154 3.599 -1.614 58 4.761e+004 1.655 0.9832 1.568 59 1.378e+005 0.7596 0.4931 -0.9156 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-289 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 -87.1567 7 188.3134 13 A2 -47.28742 12 118.5748 14 A3 -55.32422 8 126.6484 15 R -109.967 2 223.934 16 4 -65.72639 5 141.4528 17 18 19 Additive constant for all log-likelihoods = -44.11. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 30 Test 6a: Does Model 4 fit the data? (A3 vs 4) 31 32 33 Tests of Interest 34 35 Test -2*log(Likelihood Ratio) D. F. p-value 36

-------- ------------------------ ------ -------------- 37 Test 1 125.4 10 < 0.0001 38 Test 2 79.74 5 < 0.0001 39 Test 3 16.07 4 0.002922 40 Test 6a 20.8 3 0.0001156 41 42 43 The p-value for Test 1 is less than .05. There appears to be a 44 difference between response and/or variances among the dose 45 levels, it seems appropriate to model the data. 46 47 The p-value for Test 2 is less than .1. A non-homogeneous 48 variance model appears to be appropriate. 49 50 The p-value for Test 3 is less than .1. You may want to 51 consider a different variance model. 52 53 The p-value for Test 6a is less than .1. Model 4 may not adequately 54 describe the data; you may want to consider another model. 55 56 57 Benchmark Dose Computations: 58 59 Specified Effect = 1.000000 60 61 Risk Type = Estimated standard deviations from control 62 63 Confidence Level = 0.950000 64 65 BMD = 13706.9 66 67 BMDL = 1852.89 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-290 E.2.46.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 1 

## Unrestricted 2

0 5 10 15 20

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:28 11/20 2009 BMD BMDL Exponential

3 4 5 

## E.2.46.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 6 

## Power Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_hepatic_retinol.(d) 12 Gnuplot Plotting File: 13 Fri Nov 20 12:28:10 2009 14

==================================================================== 15 16 Tbl3, hepatic retinol 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-291 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 3 4 Total number of dose groups = 6 5 Total number of records with missing values = 0 6 Maximum number of iterations = 250 7 Relative Function Convergence has been set to: 1e-008 8 Parameter Convergence has been set to: 1e-008 9 10 MLE solution provided: Exact 11 12 13 Initial Parameter Values 14 15 Variable Model 5 16

-------- -------- 17 lnalpha -1.16065 18 rho 1.53688 19 a 15.645 20 b 4.61687e-005 21 c 0.0365247 22 d 1 23 24 25 26 Parameter Estimates 27 28 Variable Model 5 29

-------- ------- 30 lnalpha -0.926841 31 rho 1.77261 32 a 11.5052 33 b 5.20223e-005 34 c 0.0653036 35 d 1 36 37 38 Table of Stats From Input Data 39 40 Dose N Obs Mean Obs Std Dev 41

----- --- ---------- ------------- 42 0 8 14.9 8.768 43 3969 8 8.4 3.394 44 6479 8 8.2 2.263 45 9968 8 5.1 0.8485 46 4.761e+004 8 2.2 0.8485 47 1.378e+005 8 0.6 0.5657 48 49 50 Estimated Values of Interest 51 52 Dose Est Mean Est Std Scaled Residual 53

------ ---------- --------- ---------------- 54 0 11.51 5.483 1.751 55 3969 9.499 4.627 -0.6719 56 6479 8.428 4.161 -0.1551 57 9968 7.154 3.599 -1.614 58 4.761e+004 1.655 0.9832 1.568 59 1.378e+005 0.7596 0.4931 -0.9156 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-292 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 -87.1567 7 188.3134 13 A2 -47.28742 12 118.5748 14 A3 -55.32422 8 126.6484 15 R -109.967 2 223.934 16 5 -65.72639 5 141.4528 17 18 19 Additive constant for all log-likelihoods = -44.11. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 30 Test 7a: Does Model 5 fit the data? (A3 vs 5) 31 32 33 Tests of Interest 34 35 Test -2*log(Likelihood Ratio) D. F. p-value 36

-------- ------------------------ ------ -------------- 37 Test 1 125.4 10 < 0.0001 38 Test 2 79.74 5 < 0.0001 39 Test 3 16.07 4 0.002922 40 Test 7a 20.8 3 0.0001156 41 42 43 The p-value for Test 1 is less than .05. There appears to be a 44 difference between response and/or variances among the dose 45 levels, it seems appropriate to model the data. 46 47 The p-value for Test 2 is less than .1. A non-homogeneous 48 variance model appears to be appropriate. 49 50 The p-value for Test 3 is less than .1. You may want to 51 consider a different variance model. 52 53 The p-value for Test 7a is less than .1. Model 5 may not adequately 54 describe the data; you may want to consider another model. 55 56 57 Benchmark Dose Computations: 58 59 Specified Effect = 1.000000 60 61 Risk Type = Estimated standard deviations from control 62 63 Confidence Level = 0.950000 64 65 BMD = 13706.9 66 67 BMDL = 1852.89 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-293 E.2.46.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 1

0 5 10 15 20

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Hill Model

12:28 11/20 2009 BMD Hill

2 3 4 

## E.2.46.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_hepatic_retinol.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_hepatic_retinol.plt 12 Fri Nov 20 12:28:12 2009 13

==================================================================== 14 15 Tbl3, hepatic retinol 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 6 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-294 lalpha = 2.76506 1 rho = 0 2 intercept = 14.9 3 v = -14.3 4 n = 3.62162 5 k = 6985.28 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho intercept v n k 11 12 lalpha 1 -0.78 -0.04 0.012 0.036 0.033 13 14 rho -0.78 1 -0.099 0.12 -0.046 -0.052 15 16 intercept -0.04 -0.099 1 -0.94 -0.25 -0.81 17 18 v 0.012 0.12 -0.94 1 0.54 0.75 19 20 n 0.036 -0.046 -0.25 0.54 1 0.31 21 22 k 0.033 -0.052 -0.81 0.75 0.31 1 23 24 25 26 Parameter Estimates 27 28 95.0% Wald Confidence Interval 29 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 30 lalpha -1.16164 0.374355 -1.89536 -0.427913 31 rho 1.69911 0.18585 1.33485 2.06337 32 intercept 16.6709 2.08161 12.591 20.7508 33 v -17.0495 2.32002 -21.5967 -12.5023 34 n 0.763329 0.19632 0.378549 1.14811 35 k 4251.89 1440.45 1428.66 7075.13 36 37 38 39 Table of Data and Estimated Values of Interest 40 41 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 42

------ --- -------- -------- ----------- ----------- ---------- 43 44 0 8 14.9 16.7 8.77 6.11 -0.82 45 3969 8 8.4 8.37 3.39 3.4 0.0248 46 6479 8 8.2 6.79 2.26 2.85 1.4 47 9968 8 5.1 5.47 0.849 2.37 -0.439 48 4.761e+004 8 2.2 1.95 0.849 0.987 0.716 49 1.378e+005 8 0.6 0.741 0.566 0.434 -0.919 50 51 52 53 Model Descriptions for likelihoods calculated 54 55 56 Model A1: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 59 Model A2: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma(i)^2 61 62 Model A3: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 64 Model A3 uses any fixed variance parameters that 65 were specified by the user 66 67 Model R: Yi = Mu + e(i) 68 Var{e(i)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-295 1 Likelihoods of Interest 2 3 Model Log(likelihood) # Param's AIC 4 A1 -87.156698 7 188.313395 5 A2 -47.287416 12 118.574833 6 A3 -55.324218 8 126.648436 7 fitted -56.747514 6 125.495027 8 R -109.967018 2 223.934036 9 10 11 Explanation of Tests 12 13 Test 1: Do responses and/or variances differ among Dose levels? 14 (A2 vs. R) 15 Test 2: Are Variances Homogeneous? (A1 vs A2) 16 Test 3: Are variances adequately modeled? (A2 vs. A3) 17 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 18 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 19 20 Tests of Interest 21 22 Test -2*log(Likelihood Ratio) Test df p-value 23 24 Test 1 125.359 10 <.0001 25 Test 2 79.7386 5 <.0001 26 Test 3 16.0736 4 0.002922 27 Test 4 2.84659 2 0.2409 28 29 The p-value for Test 1 is less than .05. There appears to be a 30 difference between response and/or variances among the dose levels 31 It seems appropriate to model the data 32 33 The p-value for Test 2 is less than .1. A non-homogeneous variance 34 model appears to be appropriate 35 36 The p-value for Test 3 is less than .1. You may want to consider a 37 different variance model 38 39 The p-value for Test 4 is greater than .1. The model chosen seems 40 to adequately describe the data 41 42 43 Benchmark Dose Computation 44 45 Specified effect = 1 46 47 Risk Type = Estimated standard deviations from the control mean 48 49 Confidence level = 0.95 50 51 BMD = 1980.88 52 53 54 BMDL computation failed. 55 56 57

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-296 E.2.46.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 5 10 15 20

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Power Model with 0.95 Confidence Level

12:28 11/20 2009 BMD BMDL Power

2 3 4 

## E.2.46.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_hepatic_retinol.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_hepatic_retinol.plt 12 Fri Nov 20 12:28:14 2009 13

==================================================================== 14 15 Tbl3, hepatic retinol 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = control + slope * dose^power 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 The power is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 27 28 Total number of dose groups = 6 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-297 Default Initial Parameter Values 1 lalpha = 2.76506 2 rho = 0 3 control = 14.9 4 slope = -0.92667 5 power = 0.231239 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 lalpha rho control slope power 11 12 lalpha 1 -0.8 -0.042 0.048 0.063 13 14 rho -0.8 1 -0.089 -0.038 -0.1 15 16 control -0.042 -0.089 1 -0.91 -0.81 17 18 slope 0.048 -0.038 -0.91 1 0.98 19 20 power 0.063 -0.1 -0.81 0.98 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 lalpha -0.986245 0.394723 -1.75989 -0.212602 29 rho 1.67858 0.202896 1.28091 2.07625 30 control 16.9266 2.23237 12.5513 21.302 31 slope -3.10665 1.35883 -5.76991 -0.443384 32 power 0.139874 0.0269583 0.0870372 0.192712 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 8 14.9 16.9 8.77 6.56 -0.874 42 3969 8 8.4 7.03 3.39 3.14 1.24 43 6479 8 8.2 6.32 2.26 2.87 1.85 44 9968 8 5.1 5.67 0.849 2.62 -0.611 45 4.761e+004 8 2.2 2.91 0.849 1.5 -1.34 46 1.378e+005 8 0.6 0.666 0.566 0.434 -0.427 47 48 49 50 Model Descriptions for likelihoods calculated 51 52 53 Model A1: Yij = Mu(i) + e(ij) 54 Var{e(ij)} = Sigma^2 55 56 Model A2: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma(i)^2 58 59 Model A3: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 61 Model A3 uses any fixed variance parameters that 62 were specified by the user 63 64 Model R: Yi = Mu + e(i) 65 Var{e(i)} = Sigma^2 66 67 68 Likelihoods of Interest 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-298 Model Log(likelihood) # Param's AIC 1 A1 -87.156698 7 188.313395 2 A2 -47.287416 12 118.574833 3 A3 -55.324218 8 126.648436 4 fitted -60.885852 5 131.771704 5 R -109.967018 2 223.934036 6 7 8 Explanation of Tests 9 10 Test 1: Do responses and/or variances differ among Dose levels? 11 (A2 vs. R) 12 Test 2: Are Variances Homogeneous? (A1 vs A2) 13 Test 3: Are variances adequately modeled? (A2 vs. A3) 14 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 15 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 16 17 Tests of Interest 18 19 Test -2*log(Likelihood Ratio) Test df p-value 20 21 Test 1 125.359 10 <.0001 22 Test 2 79.7386 5 <.0001 23 Test 3 16.0736 4 0.002922 24 Test 4 11.1233 3 0.01108 25 26 The p-value for Test 1 is less than .05. There appears to be a 27 difference between response and/or variances among the dose levels 28 It seems appropriate to model the data 29 30 The p-value for Test 2 is less than .1. A non-homogeneous variance 31 model appears to be appropriate 32 33 The p-value for Test 3 is less than .1. You may want to consider a 34 different variance model 35 36 The p-value for Test 4 is less than .1. You may want to try a different 37 model 38 39 40 Benchmark Dose Computation 41 42 Specified effect = 1 43 44 Risk Type = Estimated standard deviations from the control mean 45 46 Confidence level = 0.95 47 48 BMD = 209.498 49 50 51 BMDL = 7.67456 52 53 54 55

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-299 E.2.47. Van Birgelen et al. (1995a): Hepatic Retinol Palmitate 1 

## E.2.47.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value a 

## χ 2 Test Statistic 

## χ 2 

## p Value b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes
exponential (M2) 4 <0.0001 57.51 <0.0001 460.28 error error nonconstant variance, power restricted ≥ 1 exponential (M3) 4 <0.0001 57.51 <0.0001 460.28 error error nonconstant variance, power restricted ≥ 1 exponential (M4) c 3 <0.0001 42.23 <0.0001 446.99 7.8E+04 2.0E+04 nonconstant variance, power restricted ≥ 1 exponential (M5) 3 <0.0001 42.23 <0.0001 446.99 7.8E+04 2.0E+04 nonconstant variance, power restricted ≥ 1 exponential (M5) d 3 <0.0001 42.23 <0.0001 446.99 7.8E+04 2.0E+04 nonconstant variance, power unrestricted
Hill 3 <.0001 11.47 0.01 416.23 2.0E+03 error nonconstant variance, n restricted >1, bound hit
Hill d 3 <.0001 120.59 <.0001 525.36 5.0E-11 5.0E-11 nonconstant variance, n unrestricted
linear 4 <.0001 83.61 <.0001 486.37 1.9E+05 1.3E+05 nonconstant variance

polynomial 4 <.0001 128.71 <.0001 531.47 6.2E+04 5.0E+04 nonconstant variance

power 4 <.0001 83.61 <.0001 486.37 1.9E+05 1.3E+05 nonconstant variance, power restricted ≥ 1, bound hit power d 3 <.0001 4.22 0.24 408.98 2.9E+01 3.2E-02 nonconstant variance, power unrestricted exponential (M2) 4 <0.0001 142.00 <0.0001 649.06 error error constant variance, power restricted ≥ 1 exponential (M3) 4 <0.0001 142.00 <0.0001 649.06 error error constant variance, power restricted ≥ 1 exponential (M4) 3 <0.0001 2.84 0.42 511.95 7.9E+02 2.9E+00 constant variance, power restricted ≥ 1 exponential (M5) 3 <0.0001 2.84 0.42 511.95 7.9E+02 2.0E+00 constant variance, power restricted ≥ 1 exponential (M5) 3 <0.0001 2.84 0.42 511.95 7.9E+02 2.0E+00 constant variance, power unrestricted
Hill 3 <.0001 0.93 0.82 510.04 3.9E+02 9.5E+01 constant variance, n restricted >1, bound hit
Hill 2 <.0001 0.31 0.86 511.42 2.8E-01 2.8E-01 constant variance, n unrestricted
linear 4 <.0001 43.71 <.0001 550.82 1.1E+05 7.0E+04 constant variance

polynomial 4 <.0001 43.71 <.0001 550.82 1.1E+05 7.0E+04 constant variance

power 4 <.0001 43.71 <.0001 550.82 1.1E+05 7.0E+04 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-300 Model Degrees of Freedom Variance 

## p -Value a 

## χ 2 Test Statistic 

## χ 2 

## p Value b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes

power 3 <.0001 0.33 0.95 509.44 2.0E-04 2.0E-04 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to m eet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix

1 2 

## E.2.47.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 3 

## Restricted ≥ 1 4

0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:29 11/20 2009 BMD BMDL Exponential

5 6 7 

## E.2.47.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 8 

## Restricted ≥ 1 9
10 11

==================================================================== 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 13 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_hepatic_retinol_palmitate.(d) 14 Gnuplot Plotting File: 15 Fri Nov 20 12:29:00 2009 16

==================================================================== 17 18 Tbl3, hepatic retinol palmitate 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 20 21

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-301 The form of the response function by Model: 1 Model 2: Y[dose] = a * exp{sign * b * dose} 2 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 3 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 4 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 5 6 Note: Y[dose] is the median response for exposure = dose; 7 sign = +1 for increasing trend in data; 8 sign = -1 for decreasing trend. 9 10 Model 2 is nested within Models 3 and 4. 11 Model 3 is nested within Model 5. 12 Model 4 is nested within Model 5. 13 14 15 Dependent variable = Mean 16 Independent variable = Dose 17 Data are assumed to be distributed: normally 18 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 19 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 20 21 Total number of dose groups = 6 22 Total number of records with missing values = 0 23 Maximum number of iterations = 250 24 Relative Function Convergence has been set to: 1e-008 25 Parameter Convergence has been set to: 1e-008 26 27 MLE solution provided: Exact 28 29 30 Initial Parameter Values 31 32 Variable Model 4 33

-------- -------- 34 lnalpha 0.284674 35 rho 1.77158 36 a 495.6 37 b 6.13207e-005 38 c 0.00576502 39 d 1 40 41 42 43 Parameter Estimates 44 45 Variable Model 4 46

-------- ------- 47 lnalpha -0.241584 48 rho 2.03456 49 a 223.851 50 b 5.45885e-005 51 c 0.012925 52 d 1 53 54 NC = No Convergence 55 56 57 Table of Stats From Input Data 58 59 Dose N Obs Mean Obs Std Dev 60

----- --- ---------- ------------- 61 0 8 472 271.5 62 3969 8 94 67.88 63 6479 8 107 76.37 64 9968 8 74 39.6 65 4.761e+004 8 22 22.63 66 1.378e+005 8 3 2.828 67 68 69 Estimated Values of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-302 1 Dose Est Mean Est Std Scaled Residual 2

------ ---------- --------- ---------------- 3 0 223.9 217.8 3.222 4 3969 180.8 175.3 -1.401 5 6479 158 152.9 -0.9443 6 9968 131.1 126.4 -1.278 7 4.761e+004 19.33 18.03 0.4197 8 1.378e+005 3.013 2.721 -0.01317 9 10 11 12 Other models for which likelihoods are calculated: 13 14 Model A1: Yij = Mu(i) + e(ij) 15 Var{e(ij)} = Sigma^2 16 17 Model A2: Yij = Mu(i) + e(ij) 18 Var{e(ij)} = Sigma(i)^2 19 20 Model A3: Yij = Mu(i) + e(ij) 21 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 22 23 Model R: Yij = Mu + e(i) 24 Var{e(ij)} = Sigma^2 25 26 27 Likelihoods of Interest 28 29 Model Log(likelihood) DF AIC 30

------- ----------------- ---- ------------ 31 A1 -250.5548 7 515.1096 32 A2 -196.7557 12 417.5115 33 A3 -197.3832 8 410.7663 34 R -276.7896 2 557.5793 35 4 -218.4969 5 446.9938 36 37 38 Additive constant for all log-likelihoods = -44.11. This constant added to the 39 above values gives the log-likelihood including the term that does not 40 depend on the model parameters. 41 42 43 Explanation of Tests 44 45 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 46 Test 2: Are Variances Homogeneous? (A2 vs. A1) 47 Test 3: Are variances adequately modeled? (A2 vs. A3) 48 49 Test 6a: Does Model 4 fit the data? (A3 vs 4) 50 51 52 Tests of Interest 53 54 Test -2*log(Likelihood Ratio) D. F. p-value 55

-------- ------------------------ ------ -------------- 56 Test 1 160.1 10 < 0.0001 57 Test 2 107.6 5 < 0.0001 58 Test 3 1.255 4 0.869 59 Test 6a 42.23 3 < 0.0001 60 61 62 The p-value for Test 1 is less than .05. There appears to be a 63 difference between response and/or variances among the dose 64 levels, it seems appropriate to model the data. 65 66 The p-value for Test 2 is less than .1. A non-homogeneous 67 variance model appears to be appropriate. 68 69 The p-value for Test 3 is greater than .1. The modeled 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-303 variance appears to be appropriate here. 1 2 The p-value for Test 6a is less than .1. Model 4 may not adequately 3 describe the data; you may want to consider another model. 4 5 6 Benchmark Dose Computations: 7 8 Specified Effect = 1.000000 9 10 Risk Type = Estimated standard deviations from control 11 12 Confidence Level = 0.950000 13 14 BMD = 77948.7 15 16 BMDL = 20092.3 17 18 19 

## E.2.47.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 20 

## Unrestricted 21

0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:29 11/20 2009 BMD BMDL Exponential

22 23 24 

## E.2.47.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 25 

## Power Unrestricted 26
27 28

==================================================================== 29 Exponential Model. (Version: 1.5; Date: 4/23/2009) 30 Input Data File: 31 C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_hepatic_retinol_palmitate.(d) 32 Gnuplot Plotting File: 33 Fri Nov 20 12:29:18 2009 34

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-304 ==================================================================== 1 2 Tbl3, hepatic retinol palmitate 3

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4 5 The form of the response function by Model: 6 Model 2: Y[dose] = a * exp{sign * b * dose} 7 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 8 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 9 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 10 11 Note: Y[dose] is the median response for exposure = dose; 12 sign = +1 for increasing trend in data; 13 sign = -1 for decreasing trend. 14 15 Model 2 is nested within Models 3 and 4. 16 Model 3 is nested within Model 5. 17 Model 4 is nested within Model 5. 18 19 20 Dependent variable = Mean 21 Independent variable = Dose 22 Data are assumed to be distributed: normally 23 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 24 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 25 26 Total number of dose groups = 6 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 MLE solution provided: Exact 33 34 35 Initial Parameter Values 36 37 Variable Model 5 38

-------- -------- 39 lnalpha 0.284674 40 rho 1.77158 41 a 495.6 42 b 6.13207e-005 43 c 0.00576502 44 d 1 45 46 47 48 Parameter Estimates 49 50 Variable Model 5 51

-------- ------- 52 lnalpha -0.241584 53 rho 2.03456 54 a 223.851 55 b 5.45885e-005 56 c 0.012925 57 d 1 58 59 NC = No Convergence 60 61 62 Table of Stats From Input Data 63 64 Dose N Obs Mean Obs Std Dev 65

----- --- ---------- ------------- 66 0 8 472 271.5 67 3969 8 94 67.88 68 6479 8 107 76.37 69 9968 8 74 39.6 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-305 4.761e+004 8 22 22.63 1 1.378e+005 8 3 2.828 2 3 4 Estimated Values of Interest 5 6 Dose Est Mean Est Std Scaled Residual 7

------ ---------- --------- ---------------- 8 0 223.9 217.8 3.222 9 3969 180.8 175.3 -1.401 10 6479 158 152.9 -0.9443 11 9968 131.1 126.4 -1.278 12 4.761e+004 19.33 18.03 0.4197 13 1.378e+005 3.013 2.721 -0.01317 14 15 16 17 Other models for which likelihoods are calculated: 18 19 Model A1: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = Sigma^2 21 22 Model A2: Yij = Mu(i) + e(ij) 23 Var{e(ij)} = Sigma(i)^2 24 25 Model A3: Yij = Mu(i) + e(ij) 26 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 27 28 Model R: Yij = Mu + e(i) 29 Var{e(ij)} = Sigma^2 30 31 32 Likelihoods of Interest 33 34 Model Log(likelihood) DF AIC 35

------- ----------------- ---- ------------ 36 A1 -250.5548 7 515.1096 37 A2 -196.7557 12 417.5115 38 A3 -197.3832 8 410.7663 39 R -276.7896 2 557.5793 40 5 -218.4969 5 446.9938 41 42 43 Additive constant for all log-likelihoods = -44.11. This constant added to the 44 above values gives the log-likelihood including the term that does not 45 depend on the model parameters. 46 47 48 Explanation of Tests 49 50 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 51 Test 2: Are Variances Homogeneous? (A2 vs. A1) 52 Test 3: Are variances adequately modeled? (A2 vs. A3) 53 54 Test 7a: Does Model 5 fit the data? (A3 vs 5) 55 56 57 Tests of Interest 58 59 Test -2*log(Likelihood Ratio) D. F. p-value 60

-------- ------------------------ ------ -------------- 61 Test 1 160.1 10 < 0.0001 62 Test 2 107.6 5 < 0.0001 63 Test 3 1.255 4 0.869 64 Test 7a 42.23 3 < 0.0001 65 66 67 The p-value for Test 1 is less than .05. There appears to be a 68 difference between response and/or variances among the dose 69 levels, it seems appropriate to model the data. 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-306 1 The p-value for Test 2 is less than .1. A non-homogeneous 2 variance model appears to be appropriate. 3 4 The p-value for Test 3 is greater than .1. The modeled 5 variance appears to be appropriate here. 6 7 The p-value for Test 7a is less than .1. Model 5 may not adequately 8 describe the data; you may want to consider another model. 9 10 11 Benchmark Dose Computations: 12 13 Specified Effect = 1.000000 14 15 Risk Type = Estimated standard deviations from control 16 17 Confidence Level = 0.950000 18 19 BMD = 77952.3 20 21 BMDL = 20092.3 22 23 24 

## E.2.47.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 25

0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Hill Model with 0.95 Confidence Level

12:29 11/20 2009 BMDBMDL Hill

26 27 28 

## E.2.47.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 29
30 31

==================================================================== 32 Hill Model. (Version: 2.14; Date: 06/26/2008) 33 Input Data File: 34 C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_hepatic_retinol_palmitate.(d) 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-307 Gnuplot Plotting File: 1 C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_hepatic_retinol_palmitate.plt 2 Fri Nov 20 12:29:21 2009 3

==================================================================== 4 5 Tbl3, hepatic retinol palmitate 6

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 7 8 The form of the response function is: 9 10 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 11 12 13 Dependent variable = Mean 14 Independent variable = Dose 15 Power parameter is not restricted 16 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 17 18 Total number of dose groups = 6 19 Total number of records with missing values = 0 20 Maximum number of iterations = 250 21 Relative Function Convergence has been set to: 1e-008 22 Parameter Convergence has been set to: 1e-008 23 24 25 26 Default Initial Parameter Values 27 lalpha = 9.57332 28 rho = 0 29 intercept = 472 30 v = -469 31 n = 1.6454 32 k = 2462.18 33 34 35 Asymptotic Correlation Matrix of Parameter Estimates 36 37 ( *** The model parameter(s) -k 38 have been estimated at a boundary point, or have been specified by the user, 39 and do not appear in the correlation matrix ) 40 41 lalpha rho intercept v n 42 43 lalpha 1 -0.9 -0.0084 -0.05 0.00043 44 45 rho -0.9 1 0.33 -0.25 6.2e-005 46 47 intercept -0.0084 0.33 1 -1 0.00089 48 49 v -0.05 -0.25 -1 1 -0.00081 50 51 n 0.00043 6.2e-005 0.00089 -0.00081 1 52 53 54 55 Parameter Estimates 56 57 95.0% Wald Confidence Interval 58 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 59 lalpha 9.05753 0.813787 7.46254 10.6525 60 rho 0.296518 0.132793 0.0362478 0.556789 61 intercept 733.34 146.204 446.785 1019.89 62 v -707.607 132.71 -967.713 -447.5 63 n 0.620012 31.4549 -61.0305 62.2705 64 k 1.3782e-010 NA 65 66 NA - Indicates that this parameter has hit a bound 67 implied by some inequality constraint and thus 68 has no standard error. 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-308 1 2 Table of Data and Estimated Values of Interest 3 4 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 5

------ --- -------- -------- ----------- ----------- ---------- 6 7 0 8 472 733 272 246 -3 8 3969 8 94 25.7 67.9 150 1.29 9 6479 8 107 25.7 76.4 150 1.53 10 9968 8 74 25.7 39.6 150 0.91 11 4.761e+004 8 22 25.7 22.6 150 -0.0704 12 1.378e+005 8 3 25.7 2.83 150 -0.429 13 14 15 16 Model Descriptions for likelihoods calculated 17 18 19 Model A1: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = Sigma^2 21 22 Model A2: Yij = Mu(i) + e(ij) 23 Var{e(ij)} = Sigma(i)^2 24 25 Model A3: Yij = Mu(i) + e(ij) 26 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 27 Model A3 uses any fixed variance parameters that 28 were specified by the user 29 30 Model R: Yi = Mu + e(i) 31 Var{e(i)} = Sigma^2 32 33 34 Likelihoods of Interest 35 36 Model Log(likelihood) # Param's AIC 37 A1 -250.554817 7 515.109634 38 A2 -196.755746 12 417.511491 39 A3 -197.383174 8 410.766347 40 fitted -257.680271 5 525.360542 41 R -276.789644 2 557.579287 42 43 44 Explanation of Tests 45 46 Test 1: Do responses and/or variances differ among Dose levels? 47 (A2 vs. R) 48 Test 2: Are Variances Homogeneous? (A1 vs A2) 49 Test 3: Are variances adequately modeled? (A2 vs. A3) 50 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 51 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 52 53 Tests of Interest 54 55 Test -2*log(Likelihood Ratio) Test df p-value 56 57 Test 1 160.068 10 <.0001 58 Test 2 107.598 5 <.0001 59 Test 3 1.25486 4 0.869 60 Test 4 120.594 3 <.0001 61 62 The p-value for Test 1 is less than .05. There appears to be a 63 difference between response and/or variances among the dose levels 64 It seems appropriate to model the data 65 66 The p-value for Test 2 is less than .1. A non-homogeneous variance 67 model appears to be appropriate 68 69 The p-value for Test 3 is greater than .1. The modeled variance appears 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-309 to be appropriate here 1 2 The p-value for Test 4 is less than .1. You may want to try a different 3 model 4 5 6 Benchmark Dose Computation 7 8 Specified effect = 1 9 10 Risk Type = Estimated standard deviations from the control mean 11 12 Confidence level = 0.95 13 14 BMD = 5.01376e-011 15 16 BMDL = 5.01376e-011 17 18 19 20 

## E.2.47.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 21

0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Power Model with 0.95 Confidence Level

12:29 11/20 2009 BMDBMDL Power

22 23 24 

## E.2.47.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 25 

## Unrestricted 26
27 28

==================================================================== 29 Power Model. (Version: 2.15; Date: 04/07/2008) 30 Input Data File: 31 C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_hepatic_retinol_palmitate.(d) 32 Gnuplot Plotting File: 33 C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_hepatic_retinol_palmitate.plt 34 Fri Nov 20 12:29:22 2009 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-310 ==================================================================== 1 2 Tbl3, hepatic retinol palmitate 3

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4 5 The form of the response function is: 6 7 Y[dose] = control + slope * dose^power 8 9 10 Dependent variable = Mean 11 Independent variable = Dose 12 The power is not restricted 13 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 14 15 Total number of dose groups = 6 16 Total number of records with missing values = 0 17 Maximum number of iterations = 250 18 Relative Function Convergence has been set to: 1e-008 19 Parameter Convergence has been set to: 1e-008 20 21 22 23 Default Initial Parameter Values 24 lalpha = 9.57332 25 rho = 0 26 control = 472 27 slope = -204.597 28 power = 0.0711193 29 30 31 Asymptotic Correlation Matrix of Parameter Estimates 32 33 lalpha rho control slope power 34 35 lalpha 1 -0.95 0.3 -0.32 -0.3 36 37 rho -0.95 1 -0.41 0.37 0.29 38 39 control 0.3 -0.41 1 -0.96 -0.82 40 41 slope -0.32 0.37 -0.96 1 0.95 42 43 power -0.3 0.29 -0.82 0.95 1 44 45 46 47 Parameter Estimates 48 49 95.0% Wald Confidence Interval 50 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 51 lalpha 0.064014 0.859473 -1.62052 1.74855 52 rho 1.81132 0.197468 1.42429 2.19835 53 control 464.289 87.5706 292.654 635.925 54 slope -216.594 73.4027 -360.461 -72.7275 55 power 0.0639105 0.0139781 0.0365139 0.0913071 56 57 58 59 Table of Data and Estimated Values of Interest 60 61 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 62

------ --- -------- -------- ----------- ----------- ---------- 63 64 0 8 472 464 272 269 0.0812 65 3969 8 94 96.5 67.9 64.7 -0.108 66 6479 8 107 84.8 76.4 57.6 1.09 67 9968 8 74 74.2 39.6 51 -0.00938 68 4.761e+004 8 22 33.2 22.6 24.6 -1.28 69 1.378e+005 8 3 2.86 2.83 2.68 0.145 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-311 1 2 3 Model Descriptions for likelihoods calculated 4 5 6 Model A1: Yij = Mu(i) + e(ij) 7 Var{e(ij)} = Sigma^2 8 9 Model A2: Yij = Mu(i) + e(ij) 10 Var{e(ij)} = Sigma(i)^2 11 12 Model A3: Yij = Mu(i) + e(ij) 13 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 14 Model A3 uses any fixed variance parameters that 15 were specified by the user 16 17 Model R: Yi = Mu + e(i) 18 Var{e(i)} = Sigma^2 19 20 21 Likelihoods of Interest 22 23 Model Log(likelihood) # Param's AIC 24 A1 -250.554817 7 515.109634 25 A2 -196.755746 12 417.511491 26 A3 -197.383174 8 410.766347 27 fitted -199.490894 5 408.981788 28 R -276.789644 2 557.579287 29 30 31 Explanation of Tests 32 33 Test 1: Do responses and/or variances differ among Dose levels? 34 (A2 vs. R) 35 Test 2: Are Variances Homogeneous? (A1 vs A2) 36 Test 3: Are variances adequately modeled? (A2 vs. A3) 37 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 38 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 39 40 Tests of Interest 41 42 Test -2*log(Likelihood Ratio) Test df p-value 43 44 Test 1 160.068 10 <.0001 45 Test 2 107.598 5 <.0001 46 Test 3 1.25486 4 0.869 47 Test 4 4.21544 3 0.2391 48 49 The p-value for Test 1 is less than .05. There appears to be a 50 difference between response and/or variances among the dose levels 51 It seems appropriate to model the data 52 53 The p-value for Test 2 is less than .1. A non-homogeneous variance 54 model appears to be appropriate 55 56 The p-value for Test 3 is greater than .1. The modeled variance appears 57 to be appropriate here 58 59 The p-value for Test 4 is greater than .1. The model chosen seems 60 to adequately describe the data 61 62 63 Benchmark Dose Computation 64 65 Specified effect = 1 66 67 Risk Type = Estimated standard deviations from the control mean 68 69 Confidence level = 0.95 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-312 1 BMD = 28.9991 2 3 4 BMDL = 0.0324608 5 6 7 8 

## E.2.48. Van Birgelen et al. (1995a): Plasma FT4 9 

## E.2.48.1. Summary Table of BMDS Modeling Results 10

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) c 4 0.01 2.70 0.61 214.98 4.4E+04 2.8E+04 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.01 2.70 0.61 214.98 4.4E+04 2.8E+04 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.01 1.96 0.58 216.24 3.0E+04 1.2E+04 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.01 1.96 0.58 216.24 3.0E+04 1.2E+04 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 0.01 1.96 0.58 216.24 3.0E+04 1.2E+04 nonconstant variance, power unrestricted

Hill 3 0.01 1.90 0.59 216.19 2.8E+04 8.8E+03 nonconstant variance, n restricted >1, bound hit

Hill d 2 0.01 1.90 0.39 218.19 2.8E+04 7.9E+03 nonconstant variance, n unrestricted

linear 4 0.01 3.98 0.41 216.27 6.0E+04 4.4E+04 nonconstant variance

polynomial 4 0.01 3.98 0.41 216.27 6.0E+04 4.4E+04 nonconstant variance

power 4 0.01 3.98 0.41 216.27 6.0E+04 4.4E+04 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 0.01 2.30 0.51 216.59 3.0E+04 7.2E+03 nonconstant variance, power unrestricted
exponential (M2) 4 0.01 3.21 0.52 213.50 4.1E+04 2.7E+04 constant variance, power restricted ≥ 1
exponential (M3) 4 0.01 3.21 0.52 213.50 4.1E+04 2.7E+04 constant variance, power restricted ≥ 1
exponential (M4) 3 0.01 2.47 0.48 214.76 2.7E+04 1.1E+04 constant variance, power restricted ≥ 1
exponential (M5) 3 0.01 2.47 0.48 214.76 2.7E+04 1.1E+04 constant variance, power restricted ≥ 1
exponential (M5) 3 0.01 2.47 0.48 214.76 2.7E+04 1.1E+04 constant variance, power unrestricted

Hill 3 0.01 2.35 0.50 214.64 2.4E+04 8.1E+03 constant variance, n restricted >1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-313 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

Hill 2 0.01 2.33 0.31 216.62 2.4E+04 7.0E+03 constant variance, n unrestricted

linear 4 0.01 4.50 0.34 214.79 5.7E+04 4.3E+04 constant variance

polynomial 4 0.01 4.50 0.34 214.79 5.7E+04 4.3E+04 constant variance

power 4 0.01 4.50 0.34 214.79 5.7E+04 4.3E+04 constant variance, power restricted ≥ 1, bound hit

power 3 0.01 2.66 0.45 214.95 2.6E+04 6.4E+03 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.2.48.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 3 

## Restricted ≥ 1 4

5 10 15 20 25 30

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

12:30 11/20 2009 BMD BMDL

Exponential

5 6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-314 E.2.48.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 1 

## Restricted ≥ 1 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_plasma_FT4.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 12:30:05 2009 9

==================================================================== 10 11 Tbl3, plasma FT4 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 34 35 Total number of dose groups = 6 36 Total number of records with missing values = 0 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39 Parameter Convergence has been set to: 1e-008 40 41 MLE solution provided: Exact 42 43 44 Initial Parameter Values 45 46 Variable Model 2 47

-------- -------- 48 lnalpha 4.29134 49 rho -0.423761 50 a 25.725 51 b 2.47112e-005 52 c 0.381323 53 d 1 54 55 56 57 Parameter Estimates 58 59 Variable Model 2 60

-------- ------- 61 lnalpha 1.7323 62 rho 0.534787 63 a 23.5975 64 b 1.50877e-005 65 c 0.358997 66 d 1 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-315 1 Table of Stats From Input Data 2 3 Dose N Obs Mean Obs Std Dev 4

----- --- ---------- ------------- 5 0 8 23.4 3.111 6 3969 8 24.5 5.657 7 6479 8 22.4 2.828 8 9968 8 19.3 9.334 9 4.761e+004 8 16.3 4.243 10 1.378e+005 8 10.3 4.808 11 12 13 Estimated Values of Interest 14 15 Dose Est Mean Est Std Scaled Residual 16

------ ---------- --------- ---------------- 17 0 23.03 5.531 0.1896 18 3969 22.47 5.496 1.046 19 6479 22.12 5.474 0.1445 20 9968 21.65 5.444 -1.219 21 4.761e+004 17.13 5.13 -0.4583 22 1.378e+005 9.779 4.447 0.3314 23 24 25 26 Other models for which likelihoods are calculated: 27 28 Model A1: Yij = Mu(i) + e(ij) 29 Var{e(ij)} = Sigma^2 30 31 Model A2: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = Sigma(i)^2 33 34 Model A3: Yij = Mu(i) + e(ij) 35 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 36 37 Model R: Yij = Mu + e(i) 38 Var{e(ij)} = Sigma^2 39 40 41 Likelihoods of Interest 42 43 Model Log(likelihood) DF AIC 44

------- ----------------- ---- ------------ 45 A1 -102.145 7 218.2901 46 A2 -94.04963 12 212.0993 47 A3 -102.143 8 220.286 48 R -117.8175 2 239.635 49 2 -103.491 4 214.9821 50 51 52 Additive constant for all log-likelihoods = -44.11. This constant added to the 53 above values gives the log-likelihood including the term that does not 54 depend on the model parameters. 55 56 57 Explanation of Tests 58 59 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 60 Test 2: Are Variances Homogeneous? (A2 vs. A1) 61 Test 3: Are variances adequately modeled? (A2 vs. A3) 62 Test 4: Does Model 2 fit the data? (A3 vs. 2) 63 64 65 Tests of Interest 66 67 Test -2*log(Likelihood Ratio) D. F. p-value 68

-------- ------------------------ ------ -------------- 69 Test 1 47.54 10 < 0.0001 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-316 Test 2 16.19 5 0.00632 1 Test 3 16.19 4 0.002778 2 Test 4 2.696 4 0.6099 3 4 5 The p-value for Test 1 is less than .05. There appears to be a 6 difference between response and/or variances among the dose 7 levels, it seems appropriate to model the data. 8 9 The p-value for Test 2 is less than .1. A non-homogeneous 10 variance model appears to be appropriate. 11 12 The p-value for Test 3 is less than .1. You may want to 13 consider a different variance model. 14 15 The p-value for Test 4 is greater than .1. Model 2 seems 16 to adequately describe the data. 17 18 19 Benchmark Dose Computations: 20 21 Specified Effect = 1.000000 22 23 Risk Type = Estimated standard deviations from control 24 25 Confidence Level = 0.950000 26 27 BMD = 44193.5 28 29 BMDL = 28156.1 30 31 32 

## E.2.48.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 33 

## Unrestricted 34

5 10 15 20 25 30

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:30 11/20 2009 BMD BMDL Exponential

35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-317 E.2.48.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 1 

## Power Unrestricted 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_plasma_FT4.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 12:30:11 2009 9

==================================================================== 10 11 Tbl3, plasma FT4 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 34 35 Total number of dose groups = 6 36 Total number of records with missing values = 0 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39 Parameter Convergence has been set to: 1e-008 40 41 MLE solution provided: Exact 42 43 44 Initial Parameter Values 45 46 Variable Model 5 47

-------- -------- 48 lnalpha 4.29134 49 rho -0.423761 50 a 25.725 51 b 2.47112e-005 52 c 0.381323 53 d 1 54 55 56 57 Parameter Estimates 58 59 Variable Model 5 60

-------- ------- 61 lnalpha 1.7323 62 rho 0.534787 63 a 23.5975 64 b 1.50877e-005 65 c 0.358997 66 d 1 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-318 1 Table of Stats From Input Data 2 3 Dose N Obs Mean Obs Std Dev 4

----- --- ---------- ------------- 5 0 8 23.4 3.111 6 3969 8 24.5 5.657 7 6479 8 22.4 2.828 8 9968 8 19.3 9.334 9 4.761e+004 8 16.3 4.243 10 1.378e+005 8 10.3 4.808 11 12 13 Estimated Values of Interest 14 15 Dose Est Mean Est Std Scaled Residual 16

------ ---------- --------- ---------------- 17 0 23.6 5.537 -0.1009 18 3969 22.72 5.481 0.9194 19 6479 22.19 5.446 0.1096 20 9968 21.49 5.4 -1.145 21 4.761e+004 15.85 4.978 0.2575 22 1.378e+005 10.36 4.443 -0.03965 23 24 25 26 Other models for which likelihoods are calculated: 27 28 Model A1: Yij = Mu(i) + e(ij) 29 Var{e(ij)} = Sigma^2 30 31 Model A2: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = Sigma(i)^2 33 34 Model A3: Yij = Mu(i) + e(ij) 35 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 36 37 Model R: Yij = Mu + e(i) 38 Var{e(ij)} = Sigma^2 39 40 41 Likelihoods of Interest 42 43 Model Log(likelihood) DF AIC 44

------- ----------------- ---- ------------ 45 A1 -102.145 7 218.2901 46 A2 -94.04963 12 212.0993 47 A3 -102.143 8 220.286 48 R -117.8175 2 239.635 49 5 -103.1224 5 216.2449 50 51 52 Additive constant for all log-likelihoods = -44.11. This constant added to the 53 above values gives the log-likelihood including the term that does not 54 depend on the model parameters. 55 56 57 Explanation of Tests 58 59 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 60 Test 2: Are Variances Homogeneous? (A2 vs. A1) 61 Test 3: Are variances adequately modeled? (A2 vs. A3) 62 63 Test 7a: Does Model 5 fit the data? (A3 vs 5) 64 65 66 Tests of Interest 67 68 Test -2*log(Likelihood Ratio) D. F. p-value 69

-------- ------------------------ ------ -------------- 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-319 Test 1 47.54 10 < 0.0001 1 Test 2 16.19 5 0.00632 2 Test 3 16.19 4 0.002778 3 Test 7a 1.959 3 0.581 4 5 6 The p-value for Test 1 is less than .05. There appears to be a 7 difference between response and/or variances among the dose 8 levels, it seems appropriate to model the data. 9 10 The p-value for Test 2 is less than .1. A non-homogeneous 11 variance model appears to be appropriate. 12 13 The p-value for Test 3 is less than .1. You may want to 14 consider a different variance model. 15 16 The p-value for Test 7a is greater than .1. Model 5 seems 17 to adequately describe the data. 18 19 20 Benchmark Dose Computations: 21 22 Specified Effect = 1.000000 23 24 Risk Type = Estimated standard deviations from control 25 26 Confidence Level = 0.950000 27 28 BMD = 30208.5 29 30 BMDL = 12273.2 31 32 33 

## E.2.48.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 34

5 10 15 20 25 30

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Hill Model with 0.95 Confidence Level

12:30 11/20 2009 BMD BMDL Hill

35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-320 E.2.48.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 1
2 3

==================================================================== 4 Hill Model. (Version: 2.14; Date: 06/26/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_plasma_FT4.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_plasma_FT4.plt 7 Fri Nov 20 12:30:12 2009 8

==================================================================== 9 10 Tbl3, plasma FT4 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the response function is: 14 15 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 16 17 18 Dependent variable = Mean 19 Independent variable = Dose 20 Power parameter is not restricted 21 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 22 23 Total number of dose groups = 6 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 30 31 Default Initial Parameter Values 32 lalpha = 3.38957 33 rho = 0 34 intercept = 23.4 35 v = -13.1 36 n = 0.996796 37 k = 40705.6 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 41 42 lalpha rho intercept v n k 43 44 lalpha 1 -1 0.2 -0.16 -0.19 0.12 45 46 rho -1 1 -0.2 0.16 0.19 -0.12 47 48 intercept 0.2 -0.2 1 -0.39 -0.59 0.22 49 50 v -0.16 0.16 -0.39 1 0.9 -0.98 51 52 n -0.19 0.19 -0.59 0.9 1 -0.85 53 54 k 0.12 -0.12 0.22 -0.98 -0.85 1 55 56 57 58 Parameter Estimates 59 60 95.0% Wald Confidence Interval 61 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 62 lalpha 1.81761 2.18889 -2.47254 6.10776 63 rho 0.505217 0.744572 -0.954117 1.96455 64 intercept 23.7748 1.72532 20.3933 27.1564 65 v -21.6283 20.8713 -62.5352 19.2786 66 n 0.975863 0.6937 -0.383764 2.33549 67 k 83458.4 171511 -252696 419613 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-321 1 2 Table of Data and Estimated Values of Interest 3 4 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 5

------ --- -------- -------- ----------- ----------- ---------- 6 7 0 8 23.4 23.8 3.11 5.52 -0.192 8 3969 8 24.5 22.7 5.66 5.46 0.921 9 6479 8 22.4 22.1 2.83 5.43 0.143 10 9968 8 19.3 21.4 9.33 5.38 -1.08 11 4.761e+004 8 16.3 15.9 4.24 4.99 0.255 12 1.378e+005 8 10.3 10.4 4.81 4.48 -0.0414 13 14 15 16 Model Descriptions for likelihoods calculated 17 18 19 Model A1: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = Sigma^2 21 22 Model A2: Yij = Mu(i) + e(ij) 23 Var{e(ij)} = Sigma(i)^2 24 25 Model A3: Yij = Mu(i) + e(ij) 26 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 27 Model A3 uses any fixed variance parameters that 28 were specified by the user 29 30 Model R: Yi = Mu + e(i) 31 Var{e(i)} = Sigma^2 32 33 34 Likelihoods of Interest 35 36 Model Log(likelihood) # Param's AIC 37 A1 -102.145036 7 218.290071 38 A2 -94.049629 12 212.099258 39 A3 -102.143023 8 220.286046 40 fitted -103.092664 6 218.185329 41 R -117.817514 2 239.635028 42 43 44 Explanation of Tests 45 46 Test 1: Do responses and/or variances differ among Dose levels? 47 (A2 vs. R) 48 Test 2: Are Variances Homogeneous? (A1 vs A2) 49 Test 3: Are variances adequately modeled? (A2 vs. A3) 50 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 51 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 52 53 Tests of Interest 54 55 Test -2*log(Likelihood Ratio) Test df p-value 56 57 Test 1 47.5358 10 <.0001 58 Test 2 16.1908 5 0.00632 59 Test 3 16.1868 4 0.002778 60 Test 4 1.89928 2 0.3869 61 62 The p-value for Test 1 is less than .05. There appears to be a 63 difference between response and/or variances among the dose levels 64 It seems appropriate to model the data 65 66 The p-value for Test 2 is less than .1. A non-homogeneous variance 67 model appears to be appropriate 68 69 The p-value for Test 3 is less than .1. You may want to consider a 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-322 different variance model 1 2 The p-value for Test 4 is greater than .1. The model chosen seems 3 to adequately describe the data 4 5 6 Benchmark Dose Computation 7 8 Specified effect = 1 9 10 Risk Type = Estimated standard deviations from the control mean 11 12 Confidence level = 0.95 13 14 BMD = 27884.5 15 16 BMDL = 7907.26 17 18 19 20 

## E.2.48.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 21

5 10 15 20 25 30

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Power Model with 0.95 Confidence Level

12:30 11/20 2009 BMD BMDL Power

22 23 24 

## E.2.48.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 25 

## Unrestricted 26
27 28

==================================================================== 29 Power Model. (Version: 2.15; Date: 04/07/2008) 30 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_plasma_FT4.(d) 31 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_plasma_FT4.plt 32 Fri Nov 20 12:30:13 2009 33

==================================================================== 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-323 Tbl3, plasma FT4 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2 3 The form of the response function is: 4 5 Y[dose] = control + slope * dose^power 6 7 8 Dependent variable = Mean 9 Independent variable = Dose 10 The power is not restricted 11 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 12 13 Total number of dose groups = 6 14 Total number of records with missing values = 0 15 Maximum number of iterations = 250 16 Relative Function Convergence has been set to: 1e-008 17 Parameter Convergence has been set to: 1e-008 18 19 20 21 Default Initial Parameter Values 22 lalpha = 3.38957 23 rho = 0 24 control = 24.5 25 slope = -0.0256219 26 power = 0.537235 27 28 29 Asymptotic Correlation Matrix of Parameter Estimates 30 31 lalpha rho control slope power 32 33 lalpha 1 -1 0.099 -0.069 -0.06 34 35 rho -1 1 -0.1 0.069 0.06 36 37 control 0.099 -0.1 1 -0.78 -0.75 38 39 slope -0.069 0.069 -0.78 1 1 40 41 power -0.06 0.06 -0.75 1 1 42 43 44 45 Parameter Estimates 46 47 95.0% Wald Confidence Interval 48 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 49 lalpha 1.99957 2.14696 -2.20839 6.20753 50 rho 0.44594 0.730207 -0.98524 1.87712 51 control 24.0444 1.65932 20.7922 27.2966 52 slope -0.0113184 0.0287697 -0.0677059 0.0450692 53 power 0.601415 0.209424 0.190952 1.01188 54 55 56 57 Table of Data and Estimated Values of Interest 58 59 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 60

------ --- -------- -------- ----------- ----------- ---------- 61 62 0 8 23.4 24 3.11 5.52 -0.33 63 3969 8 24.5 22.4 5.66 5.44 1.1 64 6479 8 22.4 21.8 2.83 5.4 0.3 65 9968 8 19.3 21.2 9.33 5.37 -0.985 66 4.761e+004 8 16.3 16.7 4.24 5.09 -0.212 67 1.378e+005 8 10.3 10.1 4.81 4.55 0.129 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-324 1 Model Descriptions for likelihoods calculated 2 3 4 Model A1: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = Sigma^2 6 7 Model A2: Yij = Mu(i) + e(ij) 8 Var{e(ij)} = Sigma(i)^2 9 10 Model A3: Yij = Mu(i) + e(ij) 11 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 12 Model A3 uses any fixed variance parameters that 13 were specified by the user 14 15 Model R: Yi = Mu + e(i) 16 Var{e(i)} = Sigma^2 17 18 19 Likelihoods of Interest 20 21 Model Log(likelihood) # Param's AIC 22 A1 -102.145036 7 218.290071 23 A2 -94.049629 12 212.099258 24 A3 -102.143023 8 220.286046 25 fitted -103.295375 5 216.590750 26 R -117.817514 2 239.635028 27 28 29 Explanation of Tests 30 31 Test 1: Do responses and/or variances differ among Dose levels? 32 (A2 vs. R) 33 Test 2: Are Variances Homogeneous? (A1 vs A2) 34 Test 3: Are variances adequately modeled? (A2 vs. A3) 35 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 36 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 37 38 Tests of Interest 39 40 Test -2*log(Likelihood Ratio) Test df p-value 41 42 Test 1 47.5358 10 <.0001 43 Test 2 16.1908 5 0.00632 44 Test 3 16.1868 4 0.002778 45 Test 4 2.3047 3 0.5116 46 47 The p-value for Test 1 is less than .05. There appears to be a 48 difference between response and/or variances among the dose levels 49 It seems appropriate to model the data 50 51 The p-value for Test 2 is less than .1. A non-homogeneous variance 52 model appears to be appropriate 53 54 The p-value for Test 3 is less than .1. You may want to consider a 55 different variance model 56 57 The p-value for Test 4 is greater than .1. The model chosen seems 58 to adequately describe the data 59 60 61 Benchmark Dose Computation 62 63 Specified effect = 1 64 65 Risk Type = Estimated standard deviations from the control mean 66 67 Confidence level = 0.95 68 69 BMD = 29513.9 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-325 1 2 BMDL = 7158.08 3 4 5 6 

## E.2.49. Van Birgelen et al. (1995a): Plasma TT4 7 

## E.2.49.1. Summary Table of BMDS Modeling Results 8

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 4 0.94 9.91 0.04 241.35 5.6E+04 3.6E+04 nonconstant variance, power restricted ≥ 1
exponential (M2) 4 0.94 9.91 0.04 241.35 5.6E+04 3.6E+04 nonconstant variance, power unrestricted
exponential (M3) 4 0.94 9.91 0.04 241.35 5.6E+04 3.6E+04 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.94 9.91 0.04 241.35 5.6E+04 3.6E+04 nonconstant variance, power unrestricted
exponential (M4) 3 0.94 9.33 0.03 242.77 3.6E+04 6.8E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.94 9.33 0.03 242.77 3.6E+04 6.8E+03 nonconstant variance, power unrestricted
exponential (M5) 3 0.94 9.33 0.03 242.77 3.6E+04 5.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.94 9.33 0.03 242.77 3.6E+04 5.5E+03 nonconstant variance, power unrestricted

Hill 3 0.94 5.45 0.14 238.89 9.4E+03 error nonconstant variance, n restricted >1, bound hit

Hill 3 0.94 5.45 0.14 238.89 9.4E+03 error nonconstant variance, n unrestricted

linear 4 0.94 10.33 0.04 241.77 6.6E+04 4.5E+04 nonconstant variance

polynomial 4 0.94 10.33 0.04 241.77 6.6E+04 4.5E+04 nonconstant variance

power 4 0.94 10.33 0.04 241.77 6.6E+04 4.5E+04 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.94 8.78 0.03 242.22 2.9E+04 5.4E+03 nonconstant variance, power unrestricted exponential (M2)

c 4 0.94 9.33 0.05 239.35 5.7E+04 3.9E+04 constant variance, power restricted ≥ 1
exponential (M3) 4 0.94 9.33 0.05 239.35 5.7E+04 3.9E+04 constant variance, power restricted ≥ 1
exponential (M4) 3 0.94 8.75 0.03 240.78 3.7E+04 9.1E+03 constant variance, power restricted ≥ 1
exponential (M5) 3 0.94 8.75 0.03 240.78 3.7E+04 9.1E+03 constant variance, power restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-326 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M5) d 3 0.94 8.75 0.03 240.78 3.7E+04 9.1E+03 constant variance, power unrestricted

Hill 3 0.94 6.31 0.10 238.33 9.5E+03 error constant variance, n restricted >1, bound hit

Hill d 3 0.94 6.31 0.10 238.33 9.5E+03 error constant variance, n unrestricted

linear 4 0.94 9.75 0.04 239.77 6.6E+04 4.8E+04 constant variance

polynomial 4 0.94 9.75 0.04 239.77 6.6E+04 4.8E+04 constant variance

power 4 0.94 9.75 0.04 239.77 6.6E+04 4.8E+04 constant variance, power restricted ≥ 1, bound hit

power d 3 0.94 8.21 0.04 240.24 3.0E+04 5.8E+03 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-327 E.2.49.2. Figure for Selected Model: Exponential (M 2), C onstant Variance, Power Restricted 1 

## ≥ 1 2

20 25 30 35 40 45

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

12:31 11/20 2009 BMD BMDL Exponential

3 4 5 

## E.2.49.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_CV_BMR1_plasma_TT4.(d) 12 Gnuplot Plotting File: 13 Fri Nov 20 12:31:00 2009 14

==================================================================== 15 16 Tbl3, plasma TT4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-328 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 rho is set to 0. 3 A constant variance model is fit. 4 5 Total number of dose groups = 6 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 2 17

-------- -------- 18 lnalpha 3.66719 19 rho(S) 0 20 a 43.47 21 b 1.98277e-005 22 c 0.558678 23 d 1 24 25 (S) = Specified 26 27 28 29 Parameter Estimates 30 31 Variable Model 2 32

-------- ------- 33 lnalpha 3.84955 34 rho 0 35 a 40.4479 36 b 1.38876e-005 37 c 0.575097 38 d 1 39 40 41 Table of Stats From Input Data 42 43 Dose N Obs Mean Obs Std Dev 44

----- --- ---------- ------------- 45 0 8 40.9 6.788 46 3969 8 41.4 5.374 47 6479 8 41.4 6.505 48 9968 8 32.3 7.354 49 4.761e+004 8 33.6 6.223 50 1.378e+005 8 25.5 7.637 51 52 53 Estimated Values of Interest 54 55 Dose Est Mean Est Std Scaled Residual 56

------ ---------- --------- ---------------- 57 0 39.73 6.895 0.4797 58 3969 39.2 6.895 0.901 59 6479 38.87 6.895 1.036 60 9968 38.42 6.895 -2.511 61 4.761e+004 33.85 6.895 -0.1024 62 1.378e+005 24.99 6.895 0.2106 63 64 65 66 Other models for which likelihoods are calculated: 67 68 Model A1: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-329 1 Model A2: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = Sigma(i)^2 3 4 Model A3: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 6 7 Model R: Yij = Mu + e(i) 8 Var{e(ij)} = Sigma^2 9 10 11 Likelihoods of Interest 12 13 Model Log(likelihood) DF AIC 14

------- ----------------- ---- ------------ 15 A1 -112.0125 7 238.025 16 A2 -111.4015 12 246.8029 17 A3 -112.0125 7 238.025 18 R -127.4455 2 258.891 19 2 -116.6748 3 239.3495 20 21 22 Additive constant for all log-likelihoods = -44.11. This constant added to the 23 above values gives the log-likelihood including the term that does not 24 depend on the model parameters. 25 26 27 Explanation of Tests 28 29 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 30 Test 2: Are Variances Homogeneous? (A2 vs. A1) 31 Test 3: Are variances adequately modeled? (A2 vs. A3) 32 Test 4: Does Model 2 fit the data? (A3 vs. 2) 33 34 35 Tests of Interest 36 37 Test -2*log(Likelihood Ratio) D. F. p-value 38

-------- ------------------------ ------ -------------- 39 Test 1 32.09 10 0.0003871 40 Test 2 1.222 5 0.9427 41 Test 3 1.222 5 0.9427 42 Test 4 9.325 4 0.05348 43 44 45 The p-value for Test 1 is less than .05. There appears to be a 46 difference between response and/or variances among the dose 47 levels, it seems appropriate to model the data. 48 49 The p-value for Test 2 is greater than .1. A homogeneous 50 variance model appears to be appropriate here. 51 52 The p-value for Test 3 is greater than .1. The modeled 53 variance appears to be appropriate here. 54 55 The p-value for Test 4 is less than .1. Model 2 may not adequately 56 describe the data; you may want to consider another model. 57 58 59 Benchmark Dose Computations: 60 61 Specified Effect = 1.000000 62 63 Risk Type = Estimated standard deviations from control 64 65 Confidence Level = 0.950000 66 67 BMD = 56637.1 68 69 BMDL = 38643.8 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-330 E.2.49.4. Figure for Unrestricted Model: Expone ntial (M5), Constant Variance, Power 1 

## Unrestricted 2

20 25 30 35 40 45

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:31 11/20 2009 BMD BMDL Exponential

3 4 5 

## E.2.49.5. Output File for Unrestricted Model: E xponential (M5), Constant Varian ce, Power 6 

## Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_CV_Unrest_BMR1_plasma_TT4.(d) 12 Gnuplot Plotting File: 13 Fri Nov 20 12:31:08 2009 14

==================================================================== 15 16 Tbl3, plasma TT4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35 Independent variable = Dose 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-331 Data are assumed to be distributed: normally 1 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 2 rho is set to 0. 3 A constant variance model is fit. 4 5 Total number of dose groups = 6 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 5 17

-------- -------- 18 lnalpha 3.66719 19 rho(S) 0 20 a 43.47 21 b 1.98277e-005 22 c 0.558678 23 d 1 24 25 (S) = Specified 26 27 28 29 Parameter Estimates 30 31 Variable Model 5 32

-------- ------- 33 lnalpha 3.84955 34 rho 0 35 a 40.4479 36 b 1.38876e-005 37 c 0.575097 38 d 1 39 40 41 Table of Stats From Input Data 42 43 Dose N Obs Mean Obs Std Dev 44

----- --- ---------- ------------- 45 0 8 40.9 6.788 46 3969 8 41.4 5.374 47 6479 8 41.4 6.505 48 9968 8 32.3 7.354 49 4.761e+004 8 33.6 6.223 50 1.378e+005 8 25.5 7.637 51 52 53 Estimated Values of Interest 54 55 Dose Est Mean Est Std Scaled Residual 56

------ ---------- --------- ---------------- 57 0 40.45 6.854 0.1866 58 3969 39.53 6.854 0.7733 59 6479 38.97 6.854 1.003 60 9968 38.23 6.854 -2.446 61 4.761e+004 32.13 6.854 0.6049 62 1.378e+005 25.8 6.854 -0.1223 63 64 65 66 Other models for which likelihoods are calculated: 67 68 Model A1: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-332 1 Model A2: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = Sigma(i)^2 3 4 Model A3: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 6 7 Model R: Yij = Mu + e(i) 8 Var{e(ij)} = Sigma^2 9 10 11 Likelihoods of Interest 12 13 Model Log(likelihood) DF AIC 14

------- ----------------- ---- ------------ 15 A1 -112.0125 7 238.025 16 A2 -111.4015 12 246.8029 17 A3 -112.0125 7 238.025 18 R -127.4455 2 258.891 19 5 -116.3891 4 240.7782 20 21 22 Additive constant for all log-likelihoods = -44.11. This constant added to the 23 above values gives the log-likelihood including the term that does not 24 depend on the model parameters. 25 26 27 Explanation of Tests 28 29 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 30 Test 2: Are Variances Homogeneous? (A2 vs. A1) 31 Test 3: Are variances adequately modeled? (A2 vs. A3) 32 33 Test 7a: Does Model 5 fit the data? (A3 vs 5) 34 35 36 Tests of Interest 37 38 Test -2*log(Likelihood Ratio) D. F. p-value 39

-------- ------------------------ ------ -------------- 40 Test 1 32.09 10 0.0003871 41 Test 2 1.222 5 0.9427 42 Test 3 1.222 5 0.9427 43 Test 7a 8.753 3 0.03276 44 45 46 The p-value for Test 1 is less than .05. There appears to be a 47 difference between response and/or variances among the dose 48 levels, it seems appropriate to model the data. 49 50 The p-value for Test 2 is greater than .1. A homogeneous 51 variance model appears to be appropriate here. 52 53 The p-value for Test 3 is greater than .1. The modeled 54 variance appears to be appropriate here. 55 56 The p-value for Test 7a is less than .1. Model 5 may not adequately 57 describe the data; you may want to consider another model. 58 59 60 Benchmark Dose Computations: 61 62 Specified Effect = 1.000000 63 64 Risk Type = Estimated standard deviations from control 65 66 Confidence Level = 0.950000 67 68 BMD = 36636.4 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-333 BMDL = 9124.3 1 2 3 

## E.2.49.6. Figure for Unrestricted Model: Hill , Constant Variance, n Unrestricted 4

20 25 30 35 40 45

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Hill Model

12:31 11/20 2009 BMD Hill

5 6 7 

## E.2.49.7. Output File for Unrestricted Model: Hil l, Consta nt Variance, n Unrestricted 8
9 10

==================================================================== 11 Hill Model. (Version: 2.14; Date: 06/26/2008) 12 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_CV_Unrest_BMR1_plasma_TT4.(d) 13 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_CV_Unrest_BMR1_plasma_TT4.plt 14 Fri Nov 20 12:31:10 2009 15

==================================================================== 16 17 Tbl3, plasma TT4 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 19 20 The form of the response function is: 21 22 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 rho is set to 0 28 Power parameter is not restricted 29 A constant variance model is fit 30 31 Total number of dose groups = 6 32 Total number of records with missing values = 0 33 Maximum number of iterations = 250 34 Relative Function Convergence has been set to: 1e-008 35 Parameter Convergence has been set to: 1e-008 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-334 1 2 3 Default Initial Parameter Values 4 alpha = 44.7333 5 rho = 0 Specified 6 intercept = 40.9 7 v = -15.4 8 n = 3.33301 9 k = 9622.52 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -rho -n 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 alpha intercept v k 19 20 alpha 1 -6.6e-008 7.9e-008 -1.5e-007 21 22 intercept -6.6e-008 1 -0.63 -0.12 23 24 v 7.9e-008 -0.63 1 -0.29 25 26 k -1.5e-007 -0.12 -0.29 1 27 28 29 30 Parameter Estimates 31 32 95.0% Wald Confidence Interval 33 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 34 alpha 44.6379 9.11167 26.7793 62.4964 35 intercept 41.2386 1.36525 38.5627 43.9144 36 v -11.689 2.1552 -15.9131 -7.46484 37 n 18 NA 38 k 9336.14 666.631 8029.56 10642.7 39 40 NA - Indicates that this parameter has hit a bound 41 implied by some inequality constraint and thus 42 has no standard error. 43 44 45 46 Table of Data and Estimated Values of Interest 47 48 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 49

------ --- -------- -------- ----------- ----------- ---------- 50 51 0 8 40.9 41.2 6.79 6.68 -0.143 52 3969 8 41.4 41.2 5.37 6.68 0.0683 53 6479 8 41.4 41.2 6.51 6.68 0.0752 54 9968 8 32.3 32.3 7.35 6.68 -0.00058 55 4.761e+004 8 33.6 29.5 6.22 6.68 1.71 56 1.378e+005 8 25.5 29.5 7.64 6.68 -1.71 57 58 59 60 Model Descriptions for likelihoods calculated 61 62 63 Model A1: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma^2 65 66 Model A2: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma(i)^2 68 69 Model A3: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-335 Var{e(ij)} = Sigma^2 1 Model A3 uses any fixed variance parameters that 2 were specified by the user 3 4 Model R: Yi = Mu + e(i) 5 Var{e(i)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) # Param's AIC 11 A1 -112.012501 7 238.025002 12 A2 -111.401462 12 246.802924 13 A3 -112.012501 7 238.025002 14 fitted -115.165987 4 238.331973 15 R -127.445484 2 258.890968 16 17 18 Explanation of Tests 19 20 Test 1: Do responses and/or variances differ among Dose levels? 21 (A2 vs. R) 22 Test 2: Are Variances Homogeneous? (A1 vs A2) 23 Test 3: Are variances adequately modeled? (A2 vs. A3) 24 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 25 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 26 27 Tests of Interest 28 29 Test -2*log(Likelihood Ratio) Test df p-value 30 31 Test 1 32.088 10 0.0003871 32 Test 2 1.22208 5 0.9427 33 Test 3 1.22208 5 0.9427 34 Test 4 6.30697 3 0.09759 35 36 The p-value for Test 1 is less than .05. There appears to be a 37 difference between response and/or variances among the dose levels 38 It seems appropriate to model the data 39 40 The p-value for Test 2 is greater than .1. A homogeneous variance 41 model appears to be appropriate here 42 43 44 The p-value for Test 3 is greater than .1. The modeled variance appears 45 to be appropriate here 46 47 The p-value for Test 4 is less than .1. You may want to try a different 48 model 49 50 51 Benchmark Dose Computation 52 53 Specified effect = 1 54 55 Risk Type = Estimated standard deviations from the control mean 56 57 Confidence level = 0.95 58 59 BMD = 9486.87 60 61 62 BMDL computation failed. 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-336 E.2.49.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

20 25 30 35 40 45

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Power Model with 0.95 Confidence Level

12:31 11/20 2009 BMD BMDL Power

2 3 4 

## E.2.49.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5
6 7

==================================================================== 8 Power Model. (Version: 2.15; Date: 04/07/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_CV_Unrest_BMR1_plasma_TT4.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_CV_Unrest_BMR1_plasma_TT4.plt 11 Fri Nov 20 12:31:11 2009 12

==================================================================== 13 14 Tbl3, plasma TT4 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = control + slope * dose^power 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 rho is set to 0 25 The power is not restricted 26 A constant variance model is fit 27 28 Total number of dose groups = 6 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 Default Initial Parameter Values 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-337 alpha = 44.7333 1 rho = 0 Specified 2 control = 41.4 3 slope = -1.4001 4 power = 0.189211 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha control slope power 14 15 alpha 1 -5.9e-009 -5e-011 -3.8e-010 16 17 control -5.9e-009 1 -0.78 -0.75 18 19 slope -5e-011 -0.78 1 1 20 21 power -3.8e-010 -0.75 1 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 46.4461 9.48077 27.8641 65.028 30 control 41.4607 2.18095 37.1861 45.7352 31 slope -0.0241896 0.0653588 -0.15229 0.103911 32 power 0.547925 0.223428 0.110013 0.985836 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 8 40.9 41.5 6.79 6.82 -0.233 42 3969 8 41.4 39.2 5.37 6.82 0.916 43 6479 8 41.4 38.5 6.51 6.82 1.21 44 9968 8 32.3 37.7 7.35 6.82 -2.24 45 4.761e+004 8 33.6 32.6 6.22 6.82 0.408 46 1.378e+005 8 25.5 25.6 7.64 6.82 -0.0527 47 48 49 50 Model Descriptions for likelihoods calculated 51 52 53 Model A1: Yij = Mu(i) + e(ij) 54 Var{e(ij)} = Sigma^2 55 56 Model A2: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma(i)^2 58 59 Model A3: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 Model A3 uses any fixed variance parameters that 62 were specified by the user 63 64 Model R: Yi = Mu + e(i) 65 Var{e(i)} = Sigma^2 66 67 68 Likelihoods of Interest 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-338 Model Log(likelihood) # Param's AIC 1 A1 -112.012501 7 238.025002 2 A2 -111.401462 12 246.802924 3 A3 -112.012501 7 238.025002 4 fitted -116.119011 4 240.238023 5 R -127.445484 2 258.890968 6 7 8 Explanation of Tests 9 10 Test 1: Do responses and/or variances differ among Dose levels? 11 (A2 vs. R) 12 Test 2: Are Variances Homogeneous? (A1 vs A2) 13 Test 3: Are variances adequately modeled? (A2 vs. A3) 14 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 15 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 16 17 Tests of Interest 18 19 Test -2*log(Likelihood Ratio) Test df p-value 20 21 Test 1 32.088 10 0.0003871 22 Test 2 1.22208 5 0.9427 23 Test 3 1.22208 5 0.9427 24 Test 4 8.21302 3 0.04181 25 26 The p-value for Test 1 is less than .05. There appears to be a 27 difference between response and/or variances among the dose levels 28 It seems appropriate to model the data 29 30 The p-value for Test 2 is greater than .1. A homogeneous variance 31 model appears to be appropriate here 32 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 The p-value for Test 4 is less than .1. You may want to try a different 38 model 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 29589.5 50 51 52 BMDL = 5826.38 53 54 55 

## E.2.50. White et al. (1986): CH50 56 

## E.2.50.1. Summary Table of BMDS Modeling Results 57

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 5 0.09 19.19 0.00 389.66 1.1E+04 6.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 5 0.09 19.19 0.00 389.66 1.1E+04 6.9E+03 nonconstant variance, power restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-339 exponential (M4) 4 0.09 18.15 0.00 390.63 7.8E+03 2.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 4 0.09 18.15 0.00 390.63 7.8E+03 2.9E+03 nonconstant variance, power restricted ≥ 1

Hill c 4 0.09 17.12 0.00 389.60 4.8E+03 8.3E+02 nonconstant variance, n restricted >1, bound hit

Hill d 3 0.09 7.05 0.07 381.53 8.2E+01 7.6E+01 nonconstant variance, n unrestricted

linear 5 0.09 23.97 0.00 394.45 1.9E+04 1.4E+04 nonconstant variance

polynomial 5 0.09 23.97 0.00 394.45 1.9E+04 1.4E+04 nonconstant variance

power 5 0.09 23.97 0.00 394.45 1.9E+04 1.4E+04 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 5 0.09 19.89 0.00 388.58 9.6E+03 6.5E+03 constant variance, power restricted ≥ 1
exponential (M3) 5 0.09 19.89 0.00 388.58 9.6E+03 6.5E+03 constant variance, power restricted ≥ 1
exponential (M4) 4 0.09 18.80 0.00 389.48 6.5E+03 2.2E+03 constant variance, power restricted ≥ 1
exponential (M5) 4 0.09 18.80 0.00 389.48 6.5E+03 2.2E+03 constant variance, power restricted ≥ 1

Hill 4 0.09 17.39 0.00 388.07 3.3E+03 8.4E+02 constant variance, n restricted >1, bound hit

Hill 3 0.09 7.07 0.07 379.75 1.5E+02 6.3E+00 constant variance, n unrestricted

linear 5 0.09 24.48 0.00 393.16 1.8E+04 1.4E+04 constant variance

polynomial 5 0.09 24.48 0.00 393.16 1.8E+04 1.4E+04 constant variance

power 5 0.09 24.48 0.00 393.16 1.8E+04 1.4E+04 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-340 E.2.50.2. Figure for Selected Model: Hill, Noncon stant Variance, n Restricted >1, Bound Hit 1

0 20 40 60 80 100

0 10000 20000 30000 40000 50000Mean Response

dose Hill Model with 0.95 Confidence Level

13:28 11/16 2009 BMD BMDL Hill

2 3 4 

## E.2.50.3. Output File for Selected Model: Hill, No nconstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_BMR1_CH50.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_BMR1_CH50.plt 12 Mon Nov 16 13:28:23 2009 13

==================================================================== 14 15 [insert study notes] 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter restricted to be greater than 1 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 7 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-341 Default Initial Parameter Values 1 lalpha = 5.60999 2 rho = 0 3 intercept = 91 4 v = -74 5 n = 0.118036 6 k = 602.74 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -n 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 lalpha rho intercept v k 16 17 lalpha 1 -0.99 0.27 0.23 -0.32 18 19 rho -0.99 1 -0.28 -0.24 0.33 20 21 intercept 0.27 -0.28 1 0.39 -0.78 22 23 v 0.23 -0.24 0.39 1 -0.85 24 25 k -0.32 0.33 -0.78 -0.85 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence Interval 32 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 33 lalpha 4.581 1.66271 1.32215 7.83986 34 rho 0.312931 0.431612 -0.533012 1.15887 35 intercept 74.6365 6.33658 62.217 87.056 36 v -66.2095 14.7868 -95.1911 -37.2278 37 n 1 NA 38 k 11475.6 11747.8 -11549.6 34500.8 39 40 NA - Indicates that this parameter has hit a bound 41 implied by some inequality constraint and thus 42 has no standard error. 43 44 45 46 Table of Data and Estimated Values of Interest 47 48 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 49

------ --- -------- -------- ----------- ----------- ---------- 50 51 0 8 91 74.6 14.1 19.4 2.39 52 602.7 8 54 71.3 8.49 19.3 -2.54 53 2250 8 63 63.8 11.3 18.9 -0.117 54 3934 8 56 57.7 25.5 18.6 -0.263 55 1.477e+004 8 41 37.4 17 17.4 0.589 56 2.684e+004 8 32 28.3 17 16.7 0.636 57 4.99e+004 8 17 20.8 17 15.9 -0.678 58 59 60 61 Model Descriptions for likelihoods calculated 62 63 64 Model A1: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma^2 66 67 Model A2: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma(i)^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-342 Model A3: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 2 Model A3 uses any fixed variance parameters that 3 were specified by the user 4 5 Model R: Yi = Mu + e(i) 6 Var{e(i)} = Sigma^2 7 8 9 Likelihoods of Interest 10 11 Model Log(likelihood) # Param's AIC 12 A1 -181.340979 8 378.681959 13 A2 -175.820265 14 379.640529 14 A3 -181.238690 9 380.477380 15 fitted -189.800260 5 389.600520 16 R -212.367055 2 428.734109 17 18 19 Explanation of Tests 20 21 Test 1: Do responses and/or variances differ among Dose levels? 22 (A2 vs. R) 23 Test 2: Are Variances Homogeneous? (A1 vs A2) 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 25 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 26 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 27 28 Tests of Interest 29 30 Test -2*log(Likelihood Ratio) Test df p-value 31 32 Test 1 73.0936 12 <.0001 33 Test 2 11.0414 6 0.0871 34 Test 3 10.8369 5 0.05471 35 Test 4 17.1231 4 0.001829 36 37 The p-value for Test 1 is less than .05. There appears to be a 38 difference between response and/or variances among the dose levels 39 It seems appropriate to model the data 40 41 The p-value for Test 2 is less than .1. A non-homogeneous variance 42 model appears to be appropriate 43 44 The p-value for Test 3 is less than .1. You may want to consider a 45 different variance model 46 47 The p-value for Test 4 is less than .1. You may want to try a different 48 model 49 50 51 Benchmark Dose Computation 52 53 Specified effect = 1 54 55 Risk Type = Estimated standard deviations from the control mean 56 57 Confidence level = 0.95 58 59 BMD = 4756.06 60 61 BMDL = 825.553 62 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-343 E.2.50.4. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 1

0 20 40 60 80 100

0 10000 20000 30000 40000 50000Mean Response

dose Hill Model with 0.95 Confidence Level

13:28 11/16 2009 BMDBMDL Hill

2 3 4 

## E.2.50.5. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_CH50.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_CH50.plt 11 Mon Nov 16 13:28:23 2009 12

==================================================================== 13 14 [insert study notes] 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Power parameter is not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 26 27 Total number of dose groups = 7 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 lalpha = 5.60999 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-344 rho = 0 1 intercept = 91 2 v = -74 3 n = 0.118036 4 k = 602.74 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 lalpha rho intercept v n k 10 11 lalpha 1 -1 0.16 0.19 -0.4 -0.013 12 13 rho -1 1 -0.16 -0.19 0.4 0.011 14 15 intercept 0.16 -0.16 1 0.15 -0.58 0.015 16 17 v 0.19 -0.19 0.15 1 -0.011 -0.93 18 19 n -0.4 0.4 -0.58 -0.011 1 -0.36 20 21 k -0.013 0.011 0.015 -0.93 -0.36 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 lalpha 6.54258 2.08981 2.44663 10.6385 30 rho -0.246247 0.541898 -1.30835 0.815854 31 intercept 89.6313 5.59369 78.6679 100.595 32 v -615.173 706.037 -1998.98 768.633 33 n 0.246754 0.0587686 0.13157 0.361938 34 k 2.44083e+008 1.35075e+009 -2.40334e+009 2.89151e+009 35 36 37 38 Table of Data and Estimated Values of Interest 39 40 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 41

------ --- -------- -------- ----------- ----------- ---------- 42 43 0 8 91 89.6 14.1 15.1 0.256 44 602.7 8 54 65.2 8.49 15.8 -2.01 45 2250 8 63 56.3 11.3 16 1.17 46 3934 8 56 51.7 25.5 16.2 0.747 47 1.477e+004 8 41 38.3 17 16.8 0.453 48 2.684e+004 8 32 30.9 17 17.3 0.175 49 4.99e+004 8 17 22.3 17 18 -0.833 50 51 52 53 Model Descriptions for likelihoods calculated 54 55 56 Model A1: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 59 Model A2: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma(i)^2 61 62 Model A3: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 64 Model A3 uses any fixed variance parameters that 65 were specified by the user 66 67 Model R: Yi = Mu + e(i) 68 Var{e(i)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-345 1 Likelihoods of Interest 2 3 Model Log(likelihood) # Param's AIC 4 A1 -181.340979 8 378.681959 5 A2 -175.820265 14 379.640529 6 A3 -181.238690 9 380.477380 7 fitted -184.762700 6 381.525401 8 R -212.367055 2 428.734109 9 10 11 Explanation of Tests 12 13 Test 1: Do responses and/or variances differ among Dose levels? 14 (A2 vs. R) 15 Test 2: Are Variances Homogeneous? (A1 vs A2) 16 Test 3: Are variances adequately modeled? (A2 vs. A3) 17 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 18 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 19 20 Tests of Interest 21 22 Test -2*log(Likelihood Ratio) Test df p-value 23 24 Test 1 73.0936 12 <.0001 25 Test 2 11.0414 6 0.0871 26 Test 3 10.8369 5 0.05471 27 Test 4 7.04802 3 0.07038 28 29 The p-value for Test 1 is less than .05. There appears to be a 30 difference between response and/or variances among the dose levels 31 It seems appropriate to model the data 32 33 The p-value for Test 2 is less than .1. A non-homogeneous variance 34 model appears to be appropriate 35 36 The p-value for Test 3 is less than .1. You may want to consider a 37 different variance model 38 39 The p-value for Test 4 is less than .1. You may want to try a different 40 model 41 42 43 Benchmark Dose Computation 44 45 Specified effect = 1 46 47 Risk Type = Estimated standard deviations from the control mean 48 49 Confidence level = 0.95 50 51 BMD = 81.6596 52 53 BMDL = 75.5039 54 55 56 57

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-346 E.3. ADMINISTERED DOSE BMDS RESULTS 1 

## E.3.1. Amin et al. (2000): Sacchari n Consumed, Female (0.25%) 2 

## E.3.1.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 1 0.00 0.84 0.36 179.70 8.8E+01 5.9E+01 nonconstant variance

polynomial 1 0.00 0.84 0.36 179.70 8.8E+01 5.9E+01 nonconstant variance

power 1 0.00 0.84 0.36 179.70 8.8E+01 5.9E+01 nonconstant variance, power restricted ≥ 1, bound hit

linear 1 0.00 0.12 0.73 191.80 6.6E+01 4.3E+01 constant variance

polynomial 1 0.00 0.12 0.73 191.80 6.6E+01 4.3E+01 constant variance

power 1 0.00 0.12 0.73 191.80 6.6E+01 4.3E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-347 E.3.1.2. Figure for Selected Model: Linear, Nonconstant Variance 1

5 10 15 20 25 30 35 40 45 50

0 20 40 60 80 100Mean Response

dose Linear Model with 0.95 Confidence Level

13:41 11/11 2009 BMD BMDL Linear

2 3 4 

## E.3.1.3. Output file for Selected Mode l: L inear, Nonconstant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Linear_BMR1_25_s_c.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Linear_BMR1_25_s_c.plt 11 Wed Nov 11 13:41:21 2009 12

==================================================================== 13 14 Rel Male Thymus wt, Tbl 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Signs of the polynomial coefficients are not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 3 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-348 lalpha = 5.29482 1 rho = 0 2 beta_0 = 30.8266 3 beta_1 = -0.204134 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 lalpha rho beta_0 beta_1 9 10 lalpha 1 -0.99 -0.016 0.03 11 12 rho -0.99 1 0.013 -0.026 13 14 beta_0 -0.016 0.013 1 -0.94 15 16 beta_1 0.03 -0.026 -0.94 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 lalpha -2.55843 1.66185 -5.8156 0.698746 25 rho 2.42056 0.545617 1.35117 3.48995 26 beta_0 30.3968 4.03582 22.4868 38.3069 27 beta_1 -0.196699 0.0443352 -0.283594 -0.109803 28 29 30 31 Table of Data and Estimated Values of Interest 32 33 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 34

------ --- -------- -------- ----------- ----------- ---------- 35 36 0 10 31.7 30.4 20.6 17.3 0.233 37 25 10 24.6 25.5 12 14 -0.2 38 100 10 10.7 10.7 5.33 4.92 -0.0204 39 40 41 42 Model Descriptions for likelihoods calculated 43 44 45 Model A1: Yij = Mu(i) + e(ij) 46 Var{e(ij)} = Sigma^2 47 48 Model A2: Yij = Mu(i) + e(ij) 49 Var{e(ij)} = Sigma(i)^2 50 51 Model A3: Yij = Mu(i) + e(ij) 52 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 53 Model A3 uses any fixed variance parameters that 54 were specified by the user 55 56 Model R: Yi = Mu + e(i) 57 Var{e(i)} = Sigma^2 58 59 60 Likelihoods of Interest 61 62 Model Log(likelihood) # Param's AIC 63 A1 -92.841935 4 193.683870 64 A2 -85.255316 6 182.510632 65 A3 -85.429148 5 180.858295 66 fitted -85.851107 4 179.702213 67 R -98.136607 2 200.273213 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-349 Explanation of Tests 1 2 Test 1: Do responses and/or variances differ among Dose levels? 3 (A2 vs. R) 4 Test 2: Are Variances Homogeneous? (A1 vs A2) 5 Test 3: Are variances adequately modeled? (A2 vs. A3) 6 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 7 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 8 9 Tests of Interest 10 11 Test -2*log(Likelihood Ratio) Test df p-value 12 13 Test 1 25.7626 4 <.0001 14 Test 2 15.1732 2 0.0005072 15 Test 3 0.347663 1 0.5554 16 Test 4 0.843918 1 0.3583 17 18 The p-value for Test 1 is less than .05. There appears to be a 19 difference between response and/or variances among the dose levels 20 It seems appropriate to model the data 21 22 The p-value for Test 2 is less than .1. A non-homogeneous variance 23 model appears to be appropriate 24 25 The p-value for Test 3 is greater than .1. The modeled variance appears 26 to be appropriate here 27 28 The p-value for Test 4 is greater than .1. The model chosen seems 29 to adequately describe the data 30 31 32 Benchmark Dose Computation 33 34 Specified effect = 1 35 36 Risk Type = Estimated standard deviations from the control mean 37 38 Confidence level = 0.95 39 40 BMD = 88.1623 41 42 43 BMDL = 58.9029 44 45 46 47 

## E.3.2. Amin et al. (2000): Sacchari n Consumed, Female (0.50%) 48 

## E.3.2.1. Summary Table of BMDS Modeling Results 49

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 1 <.0001 4.68 0.03 159.74 9.9E+01 6.4E+01 nonconstant variance
polynomial 1 <.0001 4.68 0.03 159.74 9.9E+01 6.4E+01 nonconstant variance

power 1 <.0001 4.68 0.03 159.74 9.9E+01 6.4E+01 nonconstant variance, power restricted ≥ 1, bound hit

linear 1 <.0001 2.57 0.11 175.96 6.5E+01 4.3E+01 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-350 polynomial 1 <.0001 2.57 0.11 175.96 6.5E+01 4.3E+01 constant variance

power 1 <.0001 2.57 0.11 175.96 6.5E+01 4.3E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 1 2 

## E.3.2.2. Figure for Selected Model: Linear, Nonconstant Variance 3

0 5 10 15 20 25 30 35

0 20 40 60 80 100Mean Response

dose Linear Model with 0.95 Confidence Level

13:41 11/11 2009 BMD BMDL Linear

4 5 6 

## E.3.2.3. Output File for Selected Mode l: L inear, Nonconstant Variance 7
8 9

==================================================================== 10 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 11 Input Data File: C:\USEPA\BMDS21\AD\Linear_BMR1_50_s_c.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Linear_BMR1_50_s_c.plt 13 Wed Nov 11 13:41:42 2009 14

==================================================================== 15 16 Rel Male Thymus wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 22 23

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-351 1 Dependent variable = Mean 2 Independent variable = Dose 3 Signs of the polynomial coefficients are not restricted 4 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 5 6 Total number of dose groups = 3 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 13 14 Default Initial Parameter Values 15 lalpha = 4.68512 16 rho = 0 17 beta_0 = 19.3484 18 beta_1 = -0.158141 19 20 21 Asymptotic Correlation Matrix of Parameter Estimates 22 23 lalpha rho beta_0 beta_1 24 25 lalpha 1 -0.97 0.018 -0.0021 26 27 rho -0.97 1 -0.027 0.014 28 29 beta_0 0.018 -0.027 1 -0.95 30 31 beta_1 -0.0021 0.014 -0.95 1 32 33 34 35 Parameter Estimates 36 37 95.0% Wald Confidence Interval 38 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 39 lalpha -0.997428 0.992786 -2.94325 0.948397 40 rho 2.13634 0.404989 1.34257 2.9301 41 beta_0 18.1144 3.10302 12.0326 24.1962 42 beta_1 -0.135736 0.0331501 -0.200709 -0.0707631 43 44 45 46 Table of Data and Estimated Values of Interest 47 48 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 49

------ --- -------- -------- ----------- ----------- ---------- 50 51 0 10 22.4 18.1 16 13.4 1 52 25 10 11.4 14.7 7.66 10.7 -0.983 53 100 10 4.54 4.54 3.33 3.06 -0.00393 54 55 56 57 Model Descriptions for likelihoods calculated 58 59 60 Model A1: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 63 Model A2: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma(i)^2 65 66 Model A3: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 68 Model A3 uses any fixed variance parameters that 69 were specified by the user 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-352 1 Model R: Yi = Mu + e(i) 2 Var{e(i)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) # Param's AIC 8 A1 -83.696404 4 175.392808 9 A2 -73.511830 6 159.023660 10 A3 -73.530233 5 157.060467 11 fitted -75.868688 4 159.737377 12 R -90.294746 2 184.589492 13 14 15 Explanation of Tests 16 17 Test 1: Do responses and/or variances differ among Dose levels? 18 (A2 vs. R) 19 Test 2: Are Variances Homogeneous? (A1 vs A2) 20 Test 3: Are variances adequately modeled? (A2 vs. A3) 21 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 22 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 23 24 Tests of Interest 25 26 Test -2*log(Likelihood Ratio) Test df p-value 27 28 Test 1 33.5658 4 <.0001 29 Test 2 20.3691 2 <.0001 30 Test 3 0.0368066 1 0.8479 31 Test 4 4.67691 1 0.03057 32 33 The p-value for Test 1 is less than .05. There appears to be a 34 difference between response and/or variances among the dose levels 35 It seems appropriate to model the data 36 37 The p-value for Test 2 is less than .1. A non-homogeneous variance 38 model appears to be appropriate 39 40 The p-value for Test 3 is greater than .1. The modeled variance appears 41 to be appropriate here 42 43 The p-value for Test 4 is less than .1. You may want to try a different 44 model 45 46 47 Benchmark Dose Computation 48 49 Specified effect = 1 50 51 Risk Type = Estimated standard deviations from the control mean 52 53 Confidence level = 0.95 54 55 BMD = 98.7409 56 57 58 BMDL = 64.169 59 60 61 62 63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-353 E.3.3. Amin et al. (2000): Saccharin Preference Ratio, Female (0.25% ) 1 

## E.3.3.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 1 0.01 9.80 0.00 228.09 1.3E+02 6.1E+01 nonconstant variance

polynomial 1 0.01 9.80 0.00 228.09 1.3E+02 6.1E+01 nonconstant variance

power 1 0.01 9.80 0.00 228.09 1.3E+02 6.1E+01 nonconstant variance, power restricted ≥ 1, bound hit

linear 1 0.01 3.36 0.07 226.51 1.1E+02 6.1E+01 constant variance

polynomial 1 0.01 3.36 0.07 226.51 1.1E+02 6.1E+01 constant variance

power 1 0.01 3.36 0.07 226.51 1.1E+02 6.1E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4 

## E.3.3.2. Figure for Selected Model: Linear, Nonconstant Variance 5

30 40 50 60 70 80 90

0 20 40 60 80 100 120Mean Response

dose Linear Model with 0.95 Confidence Level

13:42 11/11 2009 BMD BMDL Linear

6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-354 E.3.3.3. Output File for Selected Mode l: L inear, Nonconstant Variance 1
2 3

==================================================================== 4 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\Linear_BMR1_25_s_p_f.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Linear_BMR1_25_s_p_f.plt 7 Wed Nov 11 13:42:05 2009 8

==================================================================== 9 10 Rel Male Thymus wt Tbl 2 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the response function is: 14 15 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 16 17 18 Dependent variable = Mean 19 Independent variable = Dose 20 Signs of the polynomial coefficients are not restricted 21 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 22 23 Total number of dose groups = 3 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 30 31 Default Initial Parameter Values 32 lalpha = 6.34368 33 rho = 0 34 beta_0 = 74.2008 35 beta_1 = -0.219781 36 37 38 Asymptotic Correlation Matrix of Parameter Estimates 39 40 lalpha rho beta_0 beta_1 41 42 lalpha 1 -1 0.2 -0.28 43 44 rho -1 1 -0.19 0.28 45 46 beta_0 0.2 -0.19 1 -0.76 47 48 beta_1 -0.28 0.28 -0.76 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 lalpha 0.338774 9.23768 -17.7667 18.4443 57 rho 1.43998 2.21674 -2.90476 5.78472 58 beta_0 73.6633 6.6623 60.6054 86.7211 59 beta_1 -0.207175 0.101074 -0.405276 -0.00907442 60 61 62 63 Table of Data and Estimated Values of Interest 64 65 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 66

------ --- -------- -------- ----------- ----------- ---------- 67 68 0 10 82.1 73.7 13.3 26.2 1.02 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-355 25 10 58.1 68.5 33.9 24.8 -1.32 1 100 10 54.9 52.9 19.5 20.6 0.295 2 3 4 5 Model Descriptions for likelihoods calculated 6 7 8 Model A1: Yij = Mu(i) + e(ij) 9 Var{e(ij)} = Sigma^2 10 11 Model A2: Yij = Mu(i) + e(ij) 12 Var{e(ij)} = Sigma(i)^2 13 14 Model A3: Yij = Mu(i) + e(ij) 15 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 16 Model A3 uses any fixed variance parameters that 17 were specified by the user 18 19 Model R: Yi = Mu + e(i) 20 Var{e(i)} = Sigma^2 21 22 23 Likelihoods of Interest 24 25 Model Log(likelihood) # Param's AIC 26 A1 -108.574798 4 225.149597 27 A2 -104.269377 6 220.538754 28 A3 -105.147952 5 220.295903 29 fitted -110.046917 4 228.093834 30 R -112.382522 2 228.765045 31 32 33 Explanation of Tests 34 35 Test 1: Do responses and/or variances differ among Dose levels? 36 (A2 vs. R) 37 Test 2: Are Variances Homogeneous? (A1 vs A2) 38 Test 3: Are variances adequately modeled? (A2 vs. A3) 39 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 40 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 41 42 Tests of Interest 43 44 Test -2*log(Likelihood Ratio) Test df p-value 45 46 Test 1 16.2263 4 0.00273 47 Test 2 8.61084 2 0.0135 48 Test 3 1.75715 1 0.185 49 Test 4 9.79793 1 0.001747 50 51 The p-value for Test 1 is less than .05. There appears to be a 52 difference between response and/or variances among the dose levels 53 It seems appropriate to model the data 54 55 The p-value for Test 2 is less than .1. A non-homogeneous variance 56 model appears to be appropriate 57 58 The p-value for Test 3 is greater than .1. The modeled variance appears 59 to be appropriate here 60 61 The p-value for Test 4 is less than .1. You may want to try a different 62 model 63 64 65 Benchmark Dose Computation 66 67 Specified effect = 1 68 69 Risk Type = Estimated standard deviations from the control mean 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-356 1 Confidence level = 0.95 2 3 BMD = 126.365 4 5 6 BMDL = 61.2812 7 8 9 10 

## E.3.4. Amin et al. (2000): Saccharin Preference Ratio, Female (0.50% ) 11 

## E.3.4.1. Summary Table of BMDS Modeling Results 12

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear c 1 0.56 2.60 0.11 236.57 9.2E+01 5.2E+01 nonconstant variance

polynomial 1 0.56 2.60 0.11 236.57 9.2E+01 5.2E+01 nonconstant variance

power 1 0.56 2.60 0.11 236.57 9.2E+01 5.2E+01 nonconstant variance, power restricted ≥ 1, bound hit

linear 1 0.56 2.92 0.09 234.94 8.3E+01 5.1E+01 constant variance

polynomial 1 0.56 2.92 0.09 234.94 8.3E+01 5.1E+01 constant variance

power 1 0.56 2.92 0.09 234.94 8.3E+01 5.1E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 13 14

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-357 E.3.4.2. Figure for Selected Model: Linear, Nonconstant Variance 1

10 20 30 40 50 60 70 80 90

0 20 40 60 80 100Mean Response

dose Linear Model with 0.95 Confidence Level

13:42 11/11 2009 BMD BMDL Linear

2 3 4 

## E.3.4.3. Output File for Selected Mode l: L inear, Nonconstant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Linear_BMR1_50_s_p_f.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Linear_BMR1_50_s_p_f.plt 11 Wed Nov 11 13:42:27 2009 12

==================================================================== 13 14 Rel Male Thymus wt, Tbl 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Signs of the polynomial coefficients are not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 3 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-358 lalpha = 6.63936 1 rho = 0 2 beta_0 = 64.1858 3 beta_1 = -0.332668 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 lalpha rho beta_0 beta_1 9 10 lalpha 1 -1 0.11 -0.18 11 12 rho -1 1 -0.11 0.18 13 14 beta_0 0.11 -0.11 1 -0.75 15 16 beta_1 -0.18 0.18 -0.75 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 lalpha 4.43902 3.53662 -2.49263 11.3707 25 rho 0.562378 0.909867 -1.22093 2.34569 26 beta_0 63.7204 7.49597 49.0286 78.4122 27 beta_1 -0.320869 0.114882 -0.546034 -0.0957048 28 29 30 31 Table of Data and Estimated Values of Interest 32 33 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 34

------ --- -------- -------- ----------- ----------- ---------- 35 36 0 10 72.7 63.7 24.6 29.6 0.962 37 25 10 44.5 55.7 32.9 28.5 -1.24 38 100 10 33.8 31.6 24.6 24.3 0.277 39 40 41 42 Model Descriptions for likelihoods calculated 43 44 45 Model A1: Yij = Mu(i) + e(ij) 46 Var{e(ij)} = Sigma^2 47 48 Model A2: Yij = Mu(i) + e(ij) 49 Var{e(ij)} = Sigma(i)^2 50 51 Model A3: Yij = Mu(i) + e(ij) 52 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 53 Model A3 uses any fixed variance parameters that 54 were specified by the user 55 56 Model R: Yi = Mu + e(i) 57 Var{e(i)} = Sigma^2 58 59 60 Likelihoods of Interest 61 62 Model Log(likelihood) # Param's AIC 63 A1 -113.009921 4 234.019841 64 A2 -112.428886 6 236.857773 65 A3 -112.984528 5 235.969055 66 fitted -114.283840 4 236.567679 67 R -117.976057 2 239.952114 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-359 Explanation of Tests 1 2 Test 1: Do responses and/or variances differ among Dose levels? 3 (A2 vs. R) 4 Test 2: Are Variances Homogeneous? (A1 vs A2) 5 Test 3: Are variances adequately modeled? (A2 vs. A3) 6 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 7 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 8 9 Tests of Interest 10 11 Test -2*log(Likelihood Ratio) Test df p-value 12 13 Test 1 11.0943 4 0.02552 14 Test 2 1.16207 2 0.5593 15 Test 3 1.11128 1 0.2918 16 Test 4 2.59862 1 0.107 17 18 The p-value for Test 1 is less than .05. There appears to be a 19 difference between response and/or variances among the dose levels 20 It seems appropriate to model the data 21 22 The p-value for Test 2 is greater than .1. Consider running a 23 homogeneous model 24 25 The p-value for Test 3 is greater than .1. The modeled variance appears 26 to be appropriate here 27 28 The p-value for Test 4 is greater than .1. The model chosen seems 29 to adequately describe the data 30 31 32 Benchmark Dose Computation 33 34 Specified effect = 1 35 36 Risk Type = Estimated standard deviations from the control mean 37 38 Confidence level = 0.95 39 40 BMD = 92.2435 41 42 43 BMDL = 51.5208 44 45 46 47 

## E.3.5. Bell et al. (2007): Balano-Preputial Separa tion in Male Pu ps (10% Extra Risk) 48 

## E.3.5.1. Summary Table of BMDS modeling results 49

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 pValue a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 2 1.99 0.37 113.51 7.3E+00 4.7E+00 power restricted ≥ 1, bound hit
logistic 2 2.88 0.24 114.85 1.5E+01 1.1E+01

log-logistic b 2 1.57 0.46 112.95 5.2E+00 2.9E+00 slope restricted ≥ 1, bound hit
log-logistic c 1 0.49 0.48 113.91 2.1E+00 1.4E-01 slope unrestricted

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-360 log-probit 1 0.60 0.44 114.02 2.2E+00 1.7E-01 slope restricted ≥ 1
multistage, 1- degree 2 1.99 0.37 113.51 7.3E+00 4.7E+00 betas restricted ≥ 0, bound hit
probit 2 2.79 0.25 114.72 1.4E+01 1.1E+01

Weibull 2 1.99 0.37 113.51 7.3E+00 4.7E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 1 2 

## E.3.5.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 3

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10 20 30 40Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:43 11/29 2009 BMDL BMD Log-Logistic

4 5 6 

## E.3.5.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 7
8 9

==================================================================== 10 Logistic Model. (Version: 2.12; Date: 05/16/2008) 11 Input Data File: C:\USEPA\BMDS21\Nov29\LogLogistic_BMR2_BPS_d49.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogLogistic_BMR2_BPS_d49.plt 13 Sun Nov 29 11:43:52 2009 14

==================================================================== 15 16 0 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-361 The form of the probability function is: 1 2 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 3 4 5 Dependent variable = DichEff 6 Independent variable = Dose 7 Slope parameter is restricted as slope >= 1 8 9 Total number of observations = 4 10 Total number of records with missing values = 0 11 Maximum number of iterations = 250 12 Relative Function Convergence has been set to: 1e-008 13 Parameter Convergence has been set to: 1e-008 14 15 16 17 User has chosen the log transformed model 18 19 20 Default Initial Parameter Values 21 background = 0.0333333 22 intercept = -3.75371 23 slope = 1 24 25 26 Asymptotic Correlation Matrix of Parameter Estimates 27 28 ( *** The model parameter(s) -slope 29 have been estimated at a boundary point, or have been specified by the user, 30 and do not appear in the correlation matrix ) 31 32 background intercept 33 34 background 1 -0.58 35 36 intercept -0.58 1 37 38 39 40 Parameter Estimates 41 42 95.0% Wald Confidence Interval 43 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 44 background 0.0635251 * * * 45 intercept -3.84765 * * * 46 slope 1 * * * 47 48 * - Indicates that this value is not calculated. 49 50 51 52 Analysis of Deviance Table 53 54 Model Log(likelihood) # Param's Deviance Test d.f. P-value 55 Full model -53.7077 4 56 Fitted model -54.476 2 1.53661 2 0.4638 57 Reduced model -63.9797 1 20.544 3 0.0001309 58 59 AIC: 112.952 60 61 62 Goodness of Fit 63 Scaled 64 Dose Est._Prob. Expected Observed Size Residual 65

------------------------------------------------------------------------ 66 0.0000 0.0635 1.906 1.000 30 -0.678 67 2.4000 0.1091 3.274 5.000 30 1.011 68 8.0000 0.2000 6.001 6.000 30 -0.000 69 46.0000 0.5273 15.819 15.000 30 -0.300 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-362 1 Chi^2 = 1.57 d.f. = 2 P-value = 0.4559 2 3 4 Benchmark Dose Computation 5 6 Specified effect = 0.1 7 8 Risk Type = Extra risk 9 10 Confidence level = 0.95 11 12 BMD = 5.20918 13 14 BMDL = 2.86991 15 16 17

18 

## E.3.5.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 19

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10 20 30 40Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:43 11/29 2009 BMDL BMD Log-Logistic

20 21 22 

## E.3.5.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 23
24 25

==================================================================== 26 Logistic Model. (Version: 2.12; Date: 05/16/2008) 27 Input Data File: C:\USEPA\BMDS21\Nov29\LogLogistic_Unrest_BMR2_BPS_d49.(d) 28 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogLogistic_Unrest_BMR2_BPS_d49.plt 29 Sun Nov 29 11:43:54 2009 30

==================================================================== 31 32 0 33

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-363 The form of the probability function is: 1 2 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 3 4 5 Dependent variable = DichEff 6 Independent variable = Dose 7 Slope parameter is not restricted 8 9 Total number of observations = 4 10 Total number of records with missing values = 0 11 Maximum number of iterations = 250 12 Relative Function Convergence has been set to: 1e-008 13 Parameter Convergence has been set to: 1e-008 14 15 16 17 User has chosen the log transformed model 18 19 20 Default Initial Parameter Values 21 background = 0.0333333 22 intercept = -2.54947 23 slope = 0.615936 24 25 26 Asymptotic Correlation Matrix of Parameter Estimates 27 28 background intercept slope 29 30 background 1 -0.49 0.35 31 32 intercept -0.49 1 -0.93 33 34 slope 0.35 -0.93 1 35 36 37 38 Parameter Estimates 39 40 95.0% Wald Confidence Interval 41 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 42 background 0.0354714 * * * 43 intercept -2.70296 * * * 44 slope 0.670238 * * * 45 46 * - Indicates that this value is not calculated. 47 48 49 50 Analysis of Deviance Table 51 52 Model Log(likelihood) # Param's Deviance Test d.f. P-value 53 Full model -53.7077 4 54 Fitted model -53.9541 3 0.492844 1 0.4827 55 Reduced model -63.9797 1 20.544 3 0.0001309 56 57 AIC: 113.908 58 59 60 Goodness of Fit 61 Scaled 62 Dose Est._Prob. Expected Observed Size Residual 63

------------------------------------------------------------------------ 64 0.0000 0.0355 1.064 1.000 30 -0.063 65 2.4000 0.1392 4.176 5.000 30 0.435 66 8.0000 0.2405 7.216 6.000 30 -0.520 67 46.0000 0.4848 14.544 15.000 30 0.167 68 69 Chi^2 = 0.49 d.f. = 1 P-value = 0.4836 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-364 1 2 Benchmark Dose Computation 3 4 Specified effect = 0.1 5 6 Risk Type = Extra risk 7 8 Confidence level = 0.95 9 10 BMD = 2.12667 11 12 BMDL = 0.13633 13 14 15 

## E.3.6. Bell et al. (2007): Balano-Preputial Separa tion in Male Pu ps (5% Extra Risk) 16 

## E.3.6.1. Summary Table of BMDS Modeling Results 17

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 pValue a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 2 1.99 0.37 113.51 3.6E+00 2.3E+00 power restricted ≥ 1, bound hit
logistic 2 2.88 0.24 114.85 8.4E+00 6.2E+00

log-logistic b 2 1.57 0.46 112.95 2.5E+00 1.4E+00 slope restricted ≥ 1, bound hit
log-logistic c 1 0.49 0.48 113.91 7.0E-01 1.1E-02 slope unrestricted

log-probit 1 0.60 0.44 114.02 8.6E-01 2.1E-02 slope restricted ≥ 1
multistage, 1- degree 2 1.99 0.37 113.51 3.6E+00 2.3E+00 betas restricted ≥ 0, bound hit
probit 2 2.79 0.25 114.72 7.7E+00 5.7E+00

Weibull 2 1.99 0.37 113.51 3.6E+00 2.3E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 18

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-365 E.3.6.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10 20 30 40Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:43 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.3.6.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\LogLogistic_BMR1_BPS_d49.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogLogistic_BMR1_BPS_d49.plt 11 Sun Nov 29 11:43:49 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is restricted as slope >= 1 25 26 Total number of observations = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-366 Default Initial Parameter Values 1 background = 0.0333333 2 intercept = -3.75371 3 slope = 1 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -slope 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 background intercept 13 14 background 1 -0.58 15 16 intercept -0.58 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 background 0.0635251 * * * 25 intercept -3.84765 * * * 26 slope 1 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -53.7077 4 36 Fitted model -54.476 2 1.53661 2 0.4638 37 Reduced model -63.9797 1 20.544 3 0.0001309 38 39 AIC: 112.952 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0635 1.906 1.000 30 -0.678 47 2.4000 0.1091 3.274 5.000 30 1.011 48 8.0000 0.2000 6.001 6.000 30 -0.000 49 46.0000 0.5273 15.819 15.000 30 -0.300 50 51 Chi^2 = 1.57 d.f. = 2 P-value = 0.4559 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.05 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 2.46751 63 64 BMDL = 1.35943 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-367 E.3.6.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10 20 30 40Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:43 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.3.6.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\LogLogistic_Unrest_BMR1_BPS_d49.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogLogistic_Unrest_BMR1_BPS_d49.plt 11 Sun Nov 29 11:43:53 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is not restricted 25 26 Total number of observations = 4 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-368 Default Initial Parameter Values 1 background = 0.0333333 2 intercept = -2.54947 3 slope = 0.615936 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 background intercept slope 9 10 background 1 -0.49 0.35 11 12 intercept -0.49 1 -0.93 13 14 slope 0.35 -0.93 1 15 16 17 18 Parameter Estimates 19 20 95.0% Wald Confidence Interval 21 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22 background 0.0354714 * * * 23 intercept -2.70296 * * * 24 slope 0.670238 * * * 25 26 * - Indicates that this value is not calculated. 27 28 29 30 Analysis of Deviance Table 31 32 Model Log(likelihood) # Param's Deviance Test d.f. P-value 33 Full model -53.7077 4 34 Fitted model -53.9541 3 0.492844 1 0.4827 35 Reduced model -63.9797 1 20.544 3 0.0001309 36 37 AIC: 113.908 38 39 40 Goodness of Fit 41 Scaled 42 Dose Est._Prob. Expected Observed Size Residual 43

------------------------------------------------------------------------ 44 0.0000 0.0355 1.064 1.000 30 -0.063 45 2.4000 0.1392 4.176 5.000 30 0.435 46 8.0000 0.2405 7.216 6.000 30 -0.520 47 46.0000 0.4848 14.544 15.000 30 0.167 48 49 Chi^2 = 0.49 d.f. = 1 P-value = 0.4836 50 51 52 Benchmark Dose Computation 53 54 Specified effect = 0.05 55 56 Risk Type = Extra risk 57 58 Confidence level = 0.95 59 60 BMD = 0.697474 61 62 BMDL = 0.0111259 63 64 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-369 E.3.7. Cantoni et al. (1981): Urinary Copro-Porhyrins 1 

## E.3.7.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

logistic 2 20.02 0.00 131.96 4.6E+03 3.8E+01

log-logistic 2 20.02 0.00 131.96 8.0E+07 3.8E+01 slope restricted ≥ 1, bound hit
log-probit 2 20.02 0.00 131.96 4.6E+03 error slope restricted ≥ 1
multistage, 2- degree 3 20.02 0.00 129.96 error error betas restricted ≥ 0, bound hit
probit b 2 20.02 0.00 131.96 4.6E+03 3.8E+01

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.3.7.2. Figure for Selected Model: Probit 5

0.3 0.4 0.5 0.6 0.7 0.8 0.9

1

0 1000 2000 3000 4000Fraction Affected

dose Probit Model with 0.95 Confidence Level

13:34 11/11 2009 BMDL BMD Probit

6 7 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-370 E.3.7.3. Output File for Selected Model: Probit 1
2 3

==================================================================== 4 Probit Model. (Version: 3.1; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\Probit_BMR2_BPS_pnd49.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Probit_BMR2_BPS_pnd49.plt 7 Wed Nov 11 13:34:24 2009 8

==================================================================== 9 10 0 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = CumNorm(Intercept+Slope*Dose), 16 17 where CumNorm(.) is the cumulative normal distribution function 18 19 20 Dependent variable = DichEff 21 Independent variable = Dose 22 Slope parameter is not restricted 23 24 Total number of observations = 4 25 Total number of records with missing values = 0 26 Maximum number of iterations = 250 27 Relative Function Convergence has been set to: 1e-008 28 Parameter Convergence has been set to: 1e-008 29 30 31 32 Default Initial (and Specified) Parameter Values 33 background = 0 Specified 34 intercept = 1.29116 35 slope = -0.0292594 36 37 38 Asymptotic Correlation Matrix of Parameter Estimates 39 40 ( *** The model parameter(s) -background 41 have been estimated at a boundary point, or have been specified by the user, 42 and do not appear in the correlation matrix ) 43 44 intercept slope 45 46 intercept 1 -0.64 47 48 slope -0.64 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 intercept 0.755415 0.164576 0.432851 1.07798 57 slope 0 0.00651162 -0.0127625 0.0127625 58 59 60 61 Analysis of Deviance Table 62 63 Model Log(likelihood) # Param's Deviance Test d.f. P-value 64 Full model -53.7077 4 65 Fitted model -63.9797 2 20.544 2 3.4588333e-005 66 Reduced model -63.9797 1 20.544 3 0.0001309 67 68 AIC: 131.959 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-371 1 2 Goodness of Fit 3 Scaled 4 Dose Est._Prob. Expected Observed Size Residual 5

------------------------------------------------------------------------ 6 0.0000 0.7750 23.250 29.000 30 2.514 7 2.4000 0.7750 23.250 25.000 30 0.765 8 8.0000 0.7750 23.250 24.000 30 0.328 9 46.0000 0.7750 23.250 15.000 30 -3.607 10 11 Chi^2 = 20.02 d.f. = 2 P-value = 0.0000 12 13 Slope parameter essentially zero. BMD set to 100 * max(Dose). 14 15 16 Benchmark Dose Computation 17 18 Specified effect = 0.1 19 20 Risk Type = Extra risk 21 22 Confidence level = 0.95 23 24 BMD = 4600 25 26 BMDL = 38.2394 27 28 29 30 

## E.3.8. Cantoni et al. (1981): Urinary Porphyrins 31 

## E.3.8.1. Summary Table of BMDS Modeling Results 32

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 <0.0001 19.41 <0.0001 58.75 1.2E+01 9.0E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 <0.0001 19.41 <0.0001 58.75 1.2E+01 9.0E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 <0.0001 21.80 <0.0001 63.14 2.2E-01 1.1E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 <0.0001 21.80 <0.0001 63.14 2.2E-01 1.1E-01 nonconstant variance, power restricted ≥ 1

Hill 0 <.0001 19.02 NA 62.36 9.4E+00 4.7E+00 nonconstant variance, n restricted >1

linear c 2 <.0001 23.15 <.0001 62.49 7.7E-01 2.8E-01 nonconstant variance
polynomial 1 <.0001 18.19 <.0001 59.53 6.3E+00 2.0E+00 nonconstant variance

power 2 <.0001 23.15 <.0001 62.49 7.7E-01 2.8E-01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 <0.0001 0.05 0.98 108.89 7.0E+01 5.0E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 <0.0001 0.05 0.98 108.89 7.0E+01 5.0E+01 constant variance, power restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-372 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M4) 1 <0.0001 0.86 0.35 111.70 1.8E+01 1.0E+01 constant variance, power restricted ≥ 1
exponential (M5) 0 <0.0001 0.04 N/A 112.88 4.2E+01 1.4E+01 constant variance, power restricted ≥ 1

Hill 0 <.0001 0.04 NA 112.88 4.2E+01 1.0E+01 constant variance, n restricted >1

linear 2 <.0001 0.85 0.66 109.69 1.8E+01 1.3E+01 constant variance

polynomial 1 <.0001 0.03 0.86 110.88 4.4E+01 1.1E+01 constant variance

power 1 <.0001 0.04 0.85 110.88 4.2E+01 1.4E+01 constant variance, power restricted ≥ 1

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 1 2 

## E.3.8.2. Figure for Selected Model: Linear, Nonconstant Variance 3

0 50 100 150 200 250 300 350

0 20 40 60 80 100 120 140Mean Response

dose Linear Model with 0.95 Confidence Level

14:06 10/06 2009 BMD BMDL Linear

4 5 6

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-373 E.3.8.3. Output File for Selected Mode l: L inear, Nonconstant Variance 1
2 3

==================================================================== 4 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 5 Input Data File: C:\USEPA\BMDS21\AniDose\Linear_BMR1_Urinary_porphyrins.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\Linear_BMR1_Urinary_porphyrins.plt 7 Tue Oct 06 14:06:04 2009 8

==================================================================== 9 10 Table 1, dose converted to ng per kg per day 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the response function is: 14 15 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 16 17 18 Dependent variable = Mean 19 Independent variable = Dose 20 Signs of the polynomial coefficients are not restricted 21 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 22 23 Total number of dose groups = 4 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 30 31 Default Initial Parameter Values 32 lalpha = 6.68244 33 rho = 0 34 beta_0 = -1.7736 35 beta_1 = 1.38238 36 37 38 Asymptotic Correlation Matrix of Parameter Estimates 39 40 lalpha rho beta_0 beta_1 41 42 lalpha 1 -0.89 -0.27 0.2 43 44 rho -0.89 1 0.18 -0.082 45 46 beta_0 -0.27 0.18 1 -0.31 47 48 beta_1 0.2 -0.082 -0.31 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 lalpha -2.51366 0.863504 -4.2061 -0.821228 57 rho 2.27539 0.314031 1.6599 2.89088 58 beta_0 2.57041 0.376521 1.83244 3.30838 59 beta_1 1.07729 0.234062 0.618541 1.53605 60 61 62 63 Table of Data and Estimated Values of Interest 64 65 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 66

------ --- -------- -------- ----------- ----------- ---------- 67 68 0 4 2.27 2.57 0.49 0.833 -0.721 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-374 1.43 4 5.55 4.11 0.85 1.42 2.03 1 14.3 3 7.62 18 1.79 7.61 -2.36 2 143 3 197 157 63.1 89.4 0.78 3 4 5 6 Model Descriptions for likelihoods calculated 7 8 9 Model A1: Yij = Mu(i) + e(ij) 10 Var{e(ij)} = Sigma^2 11 12 Model A2: Yij = Mu(i) + e(ij) 13 Var{e(ij)} = Sigma(i)^2 14 15 Model A3: Yij = Mu(i) + e(ij) 16 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 17 Model A3 uses any fixed variance parameters that 18 were specified by the user 19 20 Model R: Yi = Mu + e(i) 21 Var{e(i)} = Sigma^2 22 23 24 Likelihoods of Interest 25 26 Model Log(likelihood) # Param's AIC 27 A1 -51.421748 5 112.843496 28 A2 -15.312111 8 46.624223 29 A3 -15.669627 6 43.339255 30 fitted -27.243469 4 62.486938 31 R -68.750584 2 141.501167 32 33 34 Explanation of Tests 35 36 Test 1: Do responses and/or variances differ among Dose levels? 37 (A2 vs. R) 38 Test 2: Are Variances Homogeneous? (A1 vs A2) 39 Test 3: Are variances adequately modeled? (A2 vs. A3) 40 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 41 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 42 43 Tests of Interest 44 45 Test -2*log(Likelihood Ratio) Test df p-value 46 47 Test 1 106.877 6 <.0001 48 Test 2 72.2193 3 <.0001 49 Test 3 0.715032 2 0.6994 50 Test 4 23.1477 2 <.0001 51 52 The p-value for Test 1 is less than .05. There appears to be a 53 difference between response and/or variances among the dose levels 54 It seems appropriate to model the data 55 56 The p-value for Test 2 is less than .1. A non-homogeneous variance 57 model appears to be appropriate 58 59 The p-value for Test 3 is greater than .1. The modeled variance appears 60 to be appropriate here 61 62 The p-value for Test 4 is less than .1. You may want to try a different 63 model 64 65 66 Benchmark Dose Computation 67 68 Specified effect = 1 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-375 Risk Type = Estimated standard deviations from the control mean 1 Confidence level = 0.95 2 BMD = 0.773193 3 BMDL = 0.281589 4 5 6 7 

## E.3.9. Crofton et al. (2005): Serum T4 8 

## E.3.9.1. Summary Table of BMDS Modeling Results 9

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 8 0.76 46.09 <0.0001 518.24 2.1E+03 1.2E+03 constant variance, power restricted ≥ 1
exponential (M3) 8 0.76 46.09 <0.0001 518.24 2.1E+03 1.2E+03 constant variance, power restricted ≥ 1 exponential (M4)

c 7 0.76 2.05 0.96 476.20 5.6E+01 3.0E+01 constant variance, power restricted ≥ 1
exponential (M5) 7 0.76 2.05 0.96 476.20 5.6E+01 3.0E+01 constant variance, power restricted ≥ 1

Hill 6 0.76 1.28 0.97 477.43 5.6E+01 2.6E+01 constant variance, n restricted >1

linear 8 0.76 51.36 <.0001 523.52 4.2E+03 3.1E+03 constant variance

polynomial 8 0.76 51.36 <.0001 523.52 4.2E+03 3.1E+03 constant variance

power 8 0.76 51.36 <.0001 523.52 4.2E+03 3.1E+03 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-376 E.3.9.2. Figure for Selected Model: Exponential (M 4), C onstant Variance, Power Restricted 1 

## ≥ 1 2

20 40 60 80 100 120

0 2000 4000 6000 8000 10000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:00 11/11 2009 BMD BMDL Exponential

3 4 5 

## E.3.9.3. Output File for selected Model: Expo nential (M4), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\ExpConstVar_BMR1_SerumT4.(d) 12 Gnuplot Plotting File: 13 Wed Nov 11 12:00:47 2009 14

==================================================================== 15 16 0 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-377 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 10 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 4 18

-------- -------- 19 lnalpha 5.47437 20 rho(S) 0 21 a 104.999 22 b 0.000371694 23 c 0.445764 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 4 33

-------- ------- 34 lnalpha 5.50283 35 rho 0 36 a 99.776 37 b 0.00728387 38 c 0.533516 39 d 1 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 14 100 15.44 47 0.1 6 96.27 14.98 48 3 12 98.57 18.11 49 10 6 99.76 19.04 50 30 6 93.32 12.11 51 100 6 70.94 12.74 52 300 6 62.52 14.75 53 1000 6 52.68 22.73 54 3000 6 54.66 19.71 55 1e+004 4 49.15 11.15 56 57 58 Estimated Values of Interest 59 60 Dose Est Mean Est Std Scaled Residual 61

------ ---------- --------- ---------------- 62 0 99.78 15.66 0.05325 63 0.1 99.74 15.66 -0.5434 64 3 98.77 15.66 -0.04357 65 10 96.51 15.66 0.5085 66 30 90.64 15.66 0.4195 67 100 75.7 15.66 -0.744 68 300 58.47 15.66 0.6334 69 1000 53.26 15.66 -0.09133 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-378 3000 53.23 15.66 0.2237 1 1e+004 53.23 15.66 -0.5218 2 3 4 5 Other models for which likelihoods are calculated: 6 7 Model A1: Yij = Mu(i) + e(ij) 8 Var{e(ij)} = Sigma^2 9 10 Model A2: Yij = Mu(i) + e(ij) 11 Var{e(ij)} = Sigma(i)^2 12 13 Model A3: Yij = Mu(i) + e(ij) 14 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 15 16 Model R: Yij = Mu + e(i) 17 Var{e(ij)} = Sigma^2 18 19 20 Likelihoods of Interest 21 22 Model Log(likelihood) DF AIC 23

------- ----------------- ---- ------------ 24 A1 -233.0774 11 488.1549 25 A2 -230.2028 20 500.4056 26 A3 -233.0774 11 488.1549 27 R -268.4038 2 540.8076 28 4 -234.1019 4 476.2038 29 30 31 Additive constant for all log-likelihoods = -66.16. This constant added to the 32 above values gives the log-likelihood including the term that does not 33 depend on the model parameters. 34 35 36 Explanation of Tests 37 38 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 39 Test 2: Are Variances Homogeneous? (A2 vs. A1) 40 Test 3: Are variances adequately modeled? (A2 vs. A3) 41 42 Test 6a: Does Model 4 fit the data? (A3 vs 4) 43 44 45 Tests of Interest 46 47 Test -2*log(Likelihood Ratio) D. F. p-value 48

-------- ------------------------ ------ -------------- 49 Test 1 76.4 18 < 0.0001 50 Test 2 5.749 9 0.7647 51 Test 3 5.749 9 0.7647 52 Test 6a 2.049 7 0.9571 53 54 55 The p-value for Test 1 is less than .05. There appears to be a 56 difference between response and/or variances among the dose 57 levels, it seems appropriate to model the data. 58 59 The p-value for Test 2 is greater than .1. A homogeneous 60 variance model appears to be appropriate here. 61 62 The p-value for Test 3 is greater than .1. The modeled 63 variance appears to be appropriate here. 64 65 The p-value for Test 6a is greater than .1. Model 4 seems 66 to adequately describe the data. 67 68 69 Benchmark Dose Computations: 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-379 1 Specified Effect = 1.000000 2 Risk Type = Estimated standard deviations from control 3 Confidence Level = 0.950000 4 BMD = 56.3321 5 BMDL = 30.0635 6 7 

## E.3.10. DeCaprio et al. (1986): Absolute Kidney Weight, Males 8 

## E.3.10.1. Summary Table of BMDS Modeling Results 9

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.67 10.85 0.00 -9.87 2.6E+00 1.7E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.67 10.85 0.00 -9.87 2.6E+00 1.7E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.67 0.54 0.46 -18.18 2.7E-01 1.2E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.67 0.54 0.46 -18.18 2.7E-01 1.2E-01 nonconstant variance, power restricted ≥ 1

Hill 1 0.67 0.08 0.78 -18.64 1.9E-01 7.3E-02 nonconstant variance, n restricted >1, bound hit

linear 2 0.67 11.14 0.00 -9.58 2.8E+00 1.9E+00 nonconstant variance

polynomial 1 0.67 1.10 0.29 -17.62 3.6E-01 2.3E-01 nonconstant variance

power 2 0.67 11.14 0.00 -9.58 2.8E+00 1.9E+00 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.67 10.90 0.00 -11.71 2.5E+00 1.7E+00 constant variance, power restricted ≥ 1
exponential (M3) 2 0.67 10.90 0.00 -11.71 2.5E+00 1.7E+00 constant variance, power restricted ≥ 1
exponential (M4) 1 0.67 0.52 0.47 -20.10 2.6E-01 1.2E-01 constant variance, power restricted ≥ 1
exponential (M5) 1 0.67 0.52 0.47 -20.10 2.6E-01 1.2E-01 constant variance, power restricted ≥ 1

Hill c 1 0.67 0.07 0.79 -20.54 1.9E-01 7.1E-02 constant variance, n restricted >1, bound hit

linear 2 0.67 11.21 0.00 -11.40 2.6E+00 1.9E+00 constant variance

polynomial 1 0.67 1.08 0.30 -19.53 3.5E-01 2.4E-01 constant variance

power 2 0.67 11.21 0.00 -11.40 2.6E+00 1.9E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-380 E.3.10.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 1

4 4.5

5 5.5

6

0 1 2 3 4 5Mean Response

dose Hill Model with 0.95 Confidence Level

14:07 10/06 2009 BMD BMDL Hill

2 3 4 

## E.3.10.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_abs_male_kidney_wt.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_abs_male_kidney_wt.plt 13 Tue Oct 06 14:07:06 2009 14

==================================================================== 15 16 Abs Male Kidney wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 rho is set to 0 27 Power parameter restricted to be greater than 1 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-381 1 2 Default Initial Parameter Values 3 alpha = 0.202865 4 rho = 0 Specified 5 intercept = 5.49 6 v = -1.19 7 n = 1.12255 8 k = 0.399186 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -rho -n 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 alpha intercept v k 18 19 alpha 1 -1.7e-009 4.6e-009 -2e-009 20 21 intercept -1.7e-009 1 -0.49 -0.54 22 23 v 4.6e-009 -0.49 1 -0.27 24 25 k -2e-009 -0.54 -0.27 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence Interval 32 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 33 alpha 0.183391 0.0405044 0.104004 0.262778 34 intercept 5.47882 0.130251 5.22353 5.7341 35 v -1.25656 0.197258 -1.64318 -0.869946 36 n 1 NA 37 k 0.361009 0.220645 -0.0714485 0.793466 38 39 NA - Indicates that this parameter has hit a bound 40 implied by some inequality constraint and thus 41 has no standard error. 42 43 44 45 Table of Data and Estimated Values of Interest 46 47 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 48

------ --- -------- -------- ----------- ----------- ---------- 49 50 0 10 5.49 5.48 0.538 0.428 0.0826 51 0.12 10 5.14 5.17 0.379 0.428 -0.187 52 0.61 11 4.71 4.69 0.398 0.428 0.159 53 4.9 10 4.3 4.31 0.474 0.428 -0.0626 54 55 56 57 Model Descriptions for likelihoods calculated 58 59 60 Model A1: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 63 Model A2: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma(i)^2 65 66 Model A3: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma^2 68 Model A3 uses any fixed variance parameters that 69 were specified by the user 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-382 1 Model R: Yi = Mu + e(i) 2 Var{e(i)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) # Param's AIC 8 A1 14.306322 5 -18.612644 9 A2 15.093716 8 -14.187432 10 A3 14.306322 5 -18.612644 11 fitted 14.270730 4 -20.541459 12 R -0.636909 2 5.273819 13 14 15 Explanation of Tests 16 17 Test 1: Do responses and/or variances differ among Dose levels? 18 (A2 vs. R) 19 Test 2: Are Variances Homogeneous? (A1 vs A2) 20 Test 3: Are variances adequately modeled? (A2 vs. A3) 21 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 22 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 23 24 Tests of Interest 25 26 Test -2*log(Likelihood Ratio) Test df p-value 27 28 Test 1 31.4613 6 <.0001 29 Test 2 1.57479 3 0.6651 30 Test 3 1.57479 3 0.6651 31 Test 4 0.0711848 1 0.7896 32 33 The p-value for Test 1 is less than .05. There appears to be a 34 difference between response and/or variances among the dose levels 35 It seems appropriate to model the data 36 37 The p-value for Test 2 is greater than .1. A homogeneous variance 38 model appears to be appropriate here 39 40 41 The p-value for Test 3 is greater than .1. The modeled variance appears 42 to be appropriate here 43 44 The p-value for Test 4 is greater than .1. The model chosen seems 45 to adequately describe the data 46 47 48 Benchmark Dose Computation 49 50 Specified effect = 1 51 52 Risk Type = Estimated standard deviations from the control mean 53 54 Confidence level = 0.95 55 56 BMD = 0.186641 57 58 BMDL = 0.0714793 59 60 61 62 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-383 E.3.11. DeCaprio et al. (1986): Absolute Thymus Weight, Males 1 

## E.3.11.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 <0.0001 0.74 0.69 -93.74 1.8E+00 4.8E-01 nonconstant variance, power restricted ≥ 1
exponential (M3) 1 <0.0001 0.70 0.40 -91.78 2.4E+00 4.8E-01 nonconstant variance, power restricted ≥ 1
exponential (M4) 2 <0.0001 0.74 0.69 -93.74 1.8E+00 4.4E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 <0.0001 0.70 N/A -89.78 2.4E+00 4.8E-01 nonconstant variance, power restricted ≥ 1

Hill 0 <.0001 0.70 NA -89.78 8.4E-01 error nonconstant variance, n restricted >1

linear 2 <.0001 0.69 0.71 -93.79 2.4E+00 error nonconstant variance

polynomial 1 <.0001 0.69 0.41 -91.79 2.4E+00 error nonconstant variance

power c 2 <.0001 0.69 0.71 -93.79 2.4E+00 1.0E+00 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 <0.0001 1.01 0.60 -60.51 1.1E+01 3.7E+00 constant variance, power restricted ≥ 1
exponential (M3) 2 <0.0001 1.01 0.60 -60.51 1.1E+01 3.7E+00 constant variance, power restricted ≥ 1
exponential (M4) 1 <0.0001 0.60 0.44 -58.92 error error constant variance, power restricted ≥ 1
exponential (M5) 1 <0.0001 0.60 0.44 -58.92 error error constant variance, power restricted ≥ 1

Hill 1 <.0001 0.40 0.53 -59.12 error error constant variance, n restricted >1, bound hit

linear 2 <.0001 1.04 0.59 -60.48 9.0E+00 4.2E+00 constant variance

polynomial 1 <.0001 0.67 0.41 -58.85 error 5.8E+00 constant variance

power 2 <.0001 1.04 0.59 -60.48 9.0E+00 4.2E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-384 E.3.11.2. Figure for Selected Model: Power, No nconstant Variance, Power Restricted ≥ 1, 1 

## Bound Hit 2

-0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 1 2 3 4 5Mean Response

dose Power Model with 0.95 Confidence Level

14:07 10/06 2009 BMD BMDL Power

3 4 5 

## E.3.11.3. Output File for Selected Model: Power, Nonconstant Varian ce, Power Restricted ≥ 1, 6 

## Bound Hit 7
8 9

==================================================================== 10 Power Model. (Version: 2.15; Date: 04/07/2008) 11 Input Data File: C:\USEPA\BMDS21\AniDose\Pwr_BMR1_abs_thymus_wt.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\Pwr_BMR1_abs_thymus_wt.plt 13 Tue Oct 06 14:07:51 2009 14

==================================================================== 15 16 Abs Thymus wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = control + slope * dose^power 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 The power is restricted to be greater than or equal to 1 27 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 28 29 Total number of dose groups = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-385 1 2 Default Initial Parameter Values 3 lalpha = -2.54423 4 rho = 0 5 control = 0.562 6 slope = -0.216619 7 power = -0.019526 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -power 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 lalpha rho control slope 17 18 lalpha 1 0.99 0.39 -0.97 19 20 rho 0.99 1 0.33 -0.98 21 22 control 0.39 0.33 1 -0.4 23 24 slope -0.97 -0.98 -0.4 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 lalpha -7.29904 2.85129 -12.8875 -1.71062 33 rho -4.37824 3.97762 -12.1742 3.41775 34 control 0.500643 0.0242054 0.453202 0.548085 35 slope -0.0492183 0.0335618 -0.114998 0.0165617 36 power 1 NA 37 38 NA - Indicates that this parameter has hit a bound 39 implied by some inequality constraint and thus 40 has no standard error. 41 42 43 44 Table of Data and Estimated Values of Interest 45 46 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 47

------ --- -------- -------- ----------- ----------- ---------- 48 49 0 10 0.562 0.501 0.158 0.118 1.64 50 0.12 10 0.448 0.495 0.0696 0.121 -1.22 51 0.61 11 0.445 0.471 0.113 0.135 -0.628 52 4.9 10 0.352 0.259 0.528 0.498 0.587 53 54 55 56 Model Descriptions for likelihoods calculated 57 58 59 Model A1: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 62 Model A2: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma(i)^2 64 65 Model A3: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 67 Model A3 uses any fixed variance parameters that 68 were specified by the user 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-386 Model R: Yi = Mu + e(i) 1 Var{e(i)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) # Param's AIC 7 A1 33.761192 5 -57.522384 8 A2 57.094821 8 -98.189643 9 A3 51.239109 6 -90.478218 10 fitted 50.896393 4 -93.792785 11 R 32.253943 2 -60.507885 12 13 14 Explanation of Tests 15 16 Test 1: Do responses and/or variances differ among Dose levels? 17 (A2 vs. R) 18 Test 2: Are Variances Homogeneous? (A1 vs A2) 19 Test 3: Are variances adequately modeled? (A2 vs. A3) 20 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 21 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 22 23 Tests of Interest 24 25 Test -2*log(Likelihood Ratio) Test df p-value 26 27 Test 1 49.6818 6 <.0001 28 Test 2 46.6673 3 <.0001 29 Test 3 11.7114 2 0.002863 30 Test 4 0.685433 2 0.7098 31 32 The p-value for Test 1 is less than .05. There appears to be a 33 difference between response and/or variances among the dose levels 34 It seems appropriate to model the data 35 36 The p-value for Test 2 is less than .1. A non-homogeneous variance 37 model appears to be appropriate 38 39 The p-value for Test 3 is less than .1. You may want to consider a 40 different variance model 41 42 The p-value for Test 4 is greater than .1. The model chosen seems 43 to adequately describe the data 44 45 46 Benchmark Dose Computation 47 48 Specified effect = 1 49 50 Risk Type = Estimated standard deviations from the control mean 51 52 Confidence level = 0.95 53 54 BMD = 2.40256 55 56 57 BMDL = 1.00746 58 59 60 61

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-387 E.3.12. DeCaprio et al. (1986): Body Weight, Females 1 

## E.3.12.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 0.10 1.49 0.68 380.09 5.5E+00 3.6E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.10 1.49 0.68 380.09 5.5E+00 3.6E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 2 0.10 1.27 0.53 381.87 4.5E+00 2.4E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.10 1.27 0.53 381.87 4.5E+00 2.4E+00 nonconstant variance, power restricted ≥ 1

Hill 2 0.10 1.26 0.53 381.86 4.5E+00 error nonconstant variance, n restricted >1, bound hit

linear 3 0.10 2.06 0.56 380.66 6.9E+00 4.7E+00 nonconstant variance

polynomial 2 0.10 1.28 0.53 381.88 4.6E+00 2.6E+00 nonconstant variance

power 3 0.10 2.06 0.56 380.66 6.9E+00 4.7E+00 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2)

c 3 0.10 1.11 0.78 379.55 6.1E+00 4.5E+00 constant variance, power restricted ≥ 1
exponential (M3) 3 0.10 1.11 0.78 379.55 6.1E+00 4.5E+00 constant variance, power restricted ≥ 1
exponential (M4) 2 0.10 0.75 0.69 381.19 4.7E+00 2.6E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.10 0.75 0.69 381.19 4.7E+00 2.6E+00 constant variance, power restricted ≥ 1

Hill 2 0.10 0.74 0.69 381.18 4.7E+00 2.4E+00 constant variance, n restricted >1, bound hit

linear 3 0.10 1.73 0.63 380.17 7.6E+00 5.9E+00 constant variance

polynomial 2 0.10 0.76 0.68 381.20 4.7E+00 2.7E+00 constant variance

power 3 0.10 1.73 0.63 380.17 7.6E+00 5.9E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-388 E.3.12.2. Figure for Selected Model: Exponential (M 2), C onstant Variance, Power Restricted 1 

## ≥ 1 2

200 300 400 500 600

0 5 10 15 20 25 30Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

14:08 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.12.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\ExpConstVar_BMR1_fem_BW.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 14:08:53 2009 14

==================================================================== 15 16 Female BW Tbl 1 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-389 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 5 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 2 18

-------- -------- 19 lnalpha 8.08396 20 rho(S) 0 21 a 632.1 22 b 0.0928666 23 c 0.528849 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 2 33

-------- ------- 34 lnalpha 8.10223 35 rho 0 36 a 588.488 37 b 0.0403005 38 c 0.434663 39 d 1 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 8 602 33.94 47 0.12 10 583 69.57 48 0.68 9 570 66 49 4.86 10 531 44.27 50 31 4 351 98 51 52 53 Estimated Values of Interest 54 55 Dose Est Mean Est Std Scaled Residual 56

------ ---------- --------- ---------------- 57 0 584.9 57.71 0.839 58 0.12 583.7 57.71 -0.0379 59 0.68 578.2 57.71 -0.4248 60 4.86 538.6 57.71 -0.4161 61 31 345.7 57.71 0.1845 62 63 64 65 Other models for which likelihoods are calculated: 66 67 Model A1: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-390 Model A2: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = Sigma(i)^2 2 3 Model A3: Yij = Mu(i) + e(ij) 4 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 5 6 Model R: Yij = Mu + e(i) 7 Var{e(ij)} = Sigma^2 8 9 10 Likelihoods of Interest 11 12 Model Log(likelihood) DF AIC 13

------- ----------------- ---- ------------ 14 A1 -186.2212 6 384.4424 15 A2 -182.3775 10 384.755 16 A3 -186.2212 6 384.4424 17 R -204.9225 2 413.8449 18 2 -186.7751 3 379.5501 19 20 21 Additive constant for all log-likelihoods = -37.68. This constant added to the 22 above values gives the log-likelihood including the term that does not 23 depend on the model parameters. 24 25 26 Explanation of Tests 27 28 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 29 Test 2: Are Variances Homogeneous? (A2 vs. A1) 30 Test 3: Are variances adequately modeled? (A2 vs. A3) 31 Test 4: Does Model 2 fit the data? (A3 vs. 2) 32 33 34 Tests of Interest 35 36 Test -2*log(Likelihood Ratio) D. F. p-value 37

-------- ------------------------ ------ -------------- 38 Test 1 45.09 8 < 0.0001 39 Test 2 7.687 4 0.1037 40 Test 3 7.687 4 0.1037 41 Test 4 1.108 3 0.7752 42 43 44 The p-value for Test 1 is less than .05. There appears to be a 45 difference between response and/or variances among the dose 46 levels, it seems appropriate to model the data. 47 48 The p-value for Test 2 is greater than .1. A homogeneous 49 variance model appears to be appropriate here. 50 51 The p-value for Test 3 is greater than .1. The modeled 52 variance appears to be appropriate here. 53 54 The p-value for Test 4 is greater than .1. Model 2 seems 55 to adequately describe the data. 56 57 58 Benchmark Dose Computations: 59 60 Specified Effect = 1.000000 61 62 Risk Type = Estimated standard deviations from control 63 64 Confidence Level = 0.950000 65 66 BMD = 6.12391 67 68 BMDL = 4.52632 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-391 E.3.13. DeCaprio et al. (1986): Body Weight, Males 1 

## E.3.13.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 0.79 6.75 0.08 419.55 4.5E+00 2.9E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.79 6.75 0.08 419.55 4.5E+00 2.9E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 2 0.79 4.68 0.10 419.49 2.8E+00 1.5E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.79 4.68 0.10 419.49 2.8E+00 1.5E+00 nonconstant variance, power restricted ≥ 1

Hill 2 0.79 4.56 0.10 419.36 2.6E+00 error nonconstant variance, n restricted >1, bound hit

linear 3 0.79 8.23 0.04 421.04 5.8E+00 3.9E+00 nonconstant variance

polynomial 2 0.79 4.82 0.09 419.63 2.9E+00 1.8E+00 nonconstant variance

power 3 0.79 8.23 0.04 421.04 5.8E+00 3.9E+00 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 3 0.79 6.14 0.11 417.87 4.8E+00 3.7E+00 constant variance, power restricted ≥ 1
exponential (M3) 3 0.79 6.14 0.11 417.87 4.8E+00 3.7E+00 constant variance, power restricted ≥ 1
exponential (M4) 2 0.79 4.08 0.13 417.81 2.9E+00 1.8E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.79 4.08 0.13 417.81 2.9E+00 1.8E+00 constant variance, power restricted ≥ 1

Hill c 2 0.79 3.98 0.14 417.70 2.8E+00 1.6E+00 constant variance, n restricted >1, bound hit

linear 3 0.79 7.56 0.06 419.29 6.1E+00 4.8E+00 constant variance

polynomial 2 0.79 4.20 0.12 417.93 3.1E+00 2.0E+00 constant variance

power 3 0.79 7.56 0.06 419.29 6.1E+00 4.8E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-392 E.3.13.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 1

300 400 500 600 700

0 5 10 15 20 25Mean Response

dose Hill Model with 0.95 Confidence Level

14:09 10/06 2009 BMD BMDL Hill

2 3 4 

## E.3.13.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_male_BW.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_male_BW.plt 12 Tue Oct 06 14:09:41 2009 13

==================================================================== 14 15 Male BW Tbl 1 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter restricted to be greater than 1 27 A constant variance model is fit 28 29 Total number of dose groups = 5 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-393 1 Default Initial Parameter Values 2 alpha = 3408.2 3 rho = 0 Specified 4 intercept = 713 5 v = -280 6 n = 0.5774 7 k = 8.62353 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -rho -n 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 alpha intercept v k 17 18 alpha 1 1.1e-008 5.5e-008 -5.8e-008 19 20 intercept 1.1e-008 1 0.27 -0.46 21 22 v 5.5e-008 0.27 1 -0.94 23 24 k -5.8e-008 -0.46 -0.94 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 alpha 3309.29 697.66 1941.9 4676.68 33 intercept 688.613 11.4849 666.103 711.123 34 v -430.869 146.654 -718.305 -143.432 35 n 1 NA 36 k 18.1326 12.6279 -6.61762 42.8828 37 38 NA - Indicates that this parameter has hit a bound 39 implied by some inequality constraint and thus 40 has no standard error. 41 42 43 44 Table of Data and Estimated Values of Interest 45 46 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 47

------ --- -------- -------- ----------- ----------- ---------- 48 49 0 10 713 689 47.4 57.5 1.34 50 0.12 10 682 686 50.6 57.5 -0.208 51 0.61 11 651 675 63 57.5 -1.36 52 4.9 10 603 597 63.2 57.5 0.333 53 26 4 433 435 76 57.5 -0.0617 54 55 56 57 Model Descriptions for likelihoods calculated 58 59 60 Model A1: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = Sigma^2 62 63 Model A2: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma(i)^2 65 66 Model A3: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma^2 68 Model A3 uses any fixed variance parameters that 69 were specified by the user 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-394 1 Model R: Yi = Mu + e(i) 2 Var{e(i)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) # Param's AIC 8 A1 -202.863522 6 417.727044 9 A2 -202.022697 10 424.045393 10 A3 -202.863522 6 417.727044 11 fitted -204.851020 4 417.702041 12 R -226.717147 2 457.434293 13 14 15 Explanation of Tests 16 17 Test 1: Do responses and/or variances differ among Dose levels? 18 (A2 vs. R) 19 Test 2: Are Variances Homogeneous? (A1 vs A2) 20 Test 3: Are variances adequately modeled? (A2 vs. A3) 21 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 22 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 23 24 Tests of Interest 25 26 Test -2*log(Likelihood Ratio) Test df p-value 27 28 Test 1 49.3889 8 <.0001 29 Test 2 1.68165 4 0.794 30 Test 3 1.68165 4 0.794 31 Test 4 3.975 2 0.137 32 33 The p-value for Test 1 is less than .05. There appears to be a 34 difference between response and/or variances among the dose levels 35 It seems appropriate to model the data 36 37 The p-value for Test 2 is greater than .1. A homogeneous variance 38 model appears to be appropriate here 39 40 41 The p-value for Test 3 is greater than .1. The modeled variance appears 42 to be appropriate here 43 44 The p-value for Test 4 is greater than .1. The model chosen seems 45 to adequately describe the data 46 47 48 Benchmark Dose Computation 49 50 Specified effect = 1 51 52 Risk Type = Estimated standard deviations from the control mean 53 54 Confidence level = 0.95 55 56 BMD = 2.79396 57 58 BMDL = 1.55261 59 60 61 62 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-395 E.3.14. DeCaprio et al. (1986): Rela tive Brain Weight, Males 1 

## E.3.14.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.99 5.25 0.07 -194.78 2.9E+00 2.0E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.99 5.25 0.07 -194.78 2.9E+00 2.0E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.99 0.02 0.89 -198.01 4.4E-01 1.8E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.99 0.02 0.89 -198.01 4.4E-01 1.8E-01 nonconstant variance, power restricted ≥ 1

Hill 0 0.99 0.00 NA -196.03 4.1E-01 1.3E-01 nonconstant variance, n restricted >1

linear 2 0.99 5.09 0.08 -194.93 2.8E+00 1.9E+00 nonconstant variance

polynomial 1 0.99 0.08 0.78 -197.95 4.9E-01 2.7E-01 nonconstant variance

power 2 0.99 5.09 0.08 -194.93 2.8E+00 1.9E+00 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.99 5.27 0.07 -196.72 2.8E+00 2.1E+00 constant variance, power restricted ≥ 1
exponential (M3) 2 0.99 5.27 0.07 -196.72 2.8E+00 2.1E+00 constant variance, power restricted ≥ 1 exponential (M4)

c 1 0.99 0.02 0.89 -199.97 4.6E-01 2.1E-01 constant variance, power restricted ≥ 1
exponential (M5) 1 0.99 0.02 0.89 -199.97 4.6E-01 2.1E-01 constant variance, power restricted ≥ 1

Hill 0 0.99 0.00 NA -197.99 4.3E-01 1.5E-01 constant variance, n restricted >1

linear 2 0.99 5.10 0.08 -196.88 2.7E+00 1.9E+00 constant variance

polynomial 1 0.99 0.08 0.78 -199.91 5.0E-01 3.0E-01 constant variance

power 2 0.99 5.10 0.08 -196.88 2.7E+00 1.9E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-396 E.3.14.2. Figure for Selected Model: Exponential (M 4), C onstant Variance, Power Restricted 1 

## ≥ 1 2

0.5 0.55 0.6 0.65 0.7

0 1 2 3 4 5Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:11 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.14.3. Output File for Selected Model: Expo nential (M4), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\ExpConstVar_BMR1_rel_male_brain_wt.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 14:11:05 2009 14

==================================================================== 15 16 Rel Male Brain wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-397 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 4 18

-------- -------- 19 lnalpha -6.07283 20 rho(S) 0 21 a 0.5111 22 b 0.351325 23 c 1.33125 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 4 33

-------- ------- 34 lnalpha -6.07239 35 rho 0 36 a 0.53911 37 b 1.25838 38 c 1.20224 39 d 1 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 10 0.538 0.04743 47 0.12 10 0.556 0.0506 48 0.61 11 0.597 0.05307 49 4.9 10 0.648 0.0506 50 51 52 Estimated Values of Interest 53 54 Dose Est Mean Est Std Scaled Residual 55

------ ---------- --------- ---------------- 56 0 0.5391 0.04802 -0.0731 57 0.12 0.5544 0.04802 0.106 58 0.61 0.5975 0.04802 -0.03703 59 4.9 0.6479 0.04802 0.005972 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-398 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 103.9931 5 -197.9862 13 A2 104.0646 8 -192.1293 14 A3 103.9931 5 -197.9862 15 R 92.4089 2 -180.8178 16 4 103.9841 4 -199.9682 17 18 19 Additive constant for all log-likelihoods = -37.68. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 30 Test 6a: Does Model 4 fit the data? (A3 vs 4) 31 32 33 Tests of Interest 34 35 Test -2*log(Likelihood Ratio) D. F. p-value 36

-------- ------------------------ ------ -------------- 37 Test 1 23.31 6 0.0006986 38 Test 2 0.1431 3 0.9862 39 Test 3 0.1431 3 0.9862 40 Test 6a 0.01798 1 0.8933 41 42 43 The p-value for Test 1 is less than .05. There appears to be a 44 difference between response and/or variances among the dose 45 levels, it seems appropriate to model the data. 46 47 The p-value for Test 2 is greater than .1. A homogeneous 48 variance model appears to be appropriate here. 49 50 The p-value for Test 3 is greater than .1. The modeled 51 variance appears to be appropriate here. 52 53 The p-value for Test 6a is greater than .1. Model 4 seems 54 to adequately describe the data. 55 56 57 Benchmark Dose Computations: 58 59 Specified Effect = 1.000000 60 61 Risk Type = Estimated standard deviations from control 62 63 Confidence Level = 0.950000 64 65 BMD = 0.461347 66 67 BMDL = 0.209454 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-399 1 

## E.3.15. DeCaprio et al. (1986): Relative Liver Weight, Females 2 

## E.3.15.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2)

c 2 0.02 5.20 0.07 38.53 3.4E+00 2.1E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 1 0.02 4.15 0.04 39.48 4.7E+00 2.3E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.02 5.33 0.02 40.66 3.3E+00 1.9E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.02 4.15 N/A 41.48 4.6E+00 7.3E-01 nonconstant variance, power restricted ≥ 1

Hill 0 0.02 4.15 NA 41.48 4.6E+00 7.5E-01 nonconstant variance, n restricted >1

linear 2 0.02 5.33 0.07 38.66 3.3E+00 1.9E+00 nonconstant variance

polynomial 1 0.02 2.86 0.09 38.20 4.9E+00 2.7E+00 nonconstant variance

power 1 0.02 4.15 0.04 39.48 4.7E+00 2.2E+00 nonconstant variance, power restricted ≥ 1
exponential (M2) 2 0.02 0.63 0.73 39.73 3.9E+00 2.7E+00 constant variance, power restricted ≥ 1
exponential (M3) 1 0.02 0.30 0.58 41.40 4.7E+00 2.7E+00 constant variance, power restricted ≥ 1
exponential (M4) 1 0.02 0.69 0.41 41.78 3.8E+00 1.2E+00 constant variance, power restricted ≥ 1
exponential (M5) 0 0.02 0.30 N/A 43.40 4.7E+00 7.2E-01 constant variance, power restricted ≥ 1

Hill 0 0.02 0.30 NA 43.40 4.7E+00 7.3E-01 constant variance, n restricted >1

linear 2 0.02 0.68 0.71 39.78 3.8E+00 2.5E+00 constant variance

polynomial 1 0.02 0.24 0.62 41.34 4.6E+00 1.2E+00 constant variance

power 1 0.02 0.30 0.58 41.40 4.7E+00 2.5E+00 constant variance, power restricted ≥ 1

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 4 5

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-400 E.3.15.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

3.5 4 4.5

5 5.5

6 6.5

0 1 2 3 4 5Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

14:10 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.15.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\Exp_BMR1_rel_fem_liver_wt.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 14:10:17 2009 14

==================================================================== 15 16 Relative Female Liver wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-401 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 4 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 2 17

-------- -------- 18 lnalpha -9.34924 19 rho 5.89997 20 a 4.0565 21 b 0.378048 22 c 1.43399 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 2 30

-------- ------- 31 lnalpha -6.47175 32 rho 4.07772 33 a 4.36037 34 b 0.196303 35 c 1.57543 36 d 9.64518 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 8 4.3 0.7354 44 0.12 10 4.49 1.107 45 0.68 9 4.27 0.48 46 4.86 10 5.54 1.36 47 48 49 Estimated Values of Interest 50 51 Dose Est Mean Est Std Scaled Residual 52

------ ---------- --------- ---------------- 53 0 4.312 0.7964 -0.04371 54 0.12 4.338 0.8054 0.5953 55 0.68 4.462 0.8483 -0.6795 56 4.86 5.505 1.25 0.08976 57 58 59 60 Other models for which likelihoods are calculated: 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-402 1 Model R: Yij = Mu + e(i) 2 Var{e(ij)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) DF AIC 8

------- ----------------- ---- ------------ 9 A1 -16.54794 5 43.09588 10 A2 -11.40563 8 38.81126 11 A3 -12.66678 6 37.33356 12 R -21.58737 2 47.17474 13 2 -15.2671 4 38.53419 14 15 16 Additive constant for all log-likelihoods = -34. This constant added to the 17 above values gives the log-likelihood including the term that does not 18 depend on the model parameters. 19 20 21 Explanation of Tests 22 23 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 24 Test 2: Are Variances Homogeneous? (A2 vs. A1) 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 26 Test 4: Does Model 2 fit the data? (A3 vs. 2) 27 28 29 Tests of Interest 30 31 Test -2*log(Likelihood Ratio) D. F. p-value 32

-------- ------------------------ ------ -------------- 33 Test 1 20.36 6 0.002385 34 Test 2 10.28 3 0.0163 35 Test 3 2.522 2 0.2833 36 Test 4 5.201 2 0.07425 37 38 39 The p-value for Test 1 is less than .05. There appears to be a 40 difference between response and/or variances among the dose 41 levels, it seems appropriate to model the data. 42 43 The p-value for Test 2 is less than .1. A non-homogeneous 44 variance model appears to be appropriate. 45 46 The p-value for Test 3 is greater than .1. The modeled 47 variance appears to be appropriate here. 48 49 The p-value for Test 4 is less than .1. Model 2 may not adequately 50 describe the data; you may want to consider another model. 51 52 53 Benchmark Dose Computations: 54 55 Specified Effect = 1.000000 56 57 Risk Type = Estimated standard deviations from control 58 59 Confidence Level = 0.950000 60 61 BMD = 3.37444 62 63 BMDL = 2.10781 64 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-403 E.3.16. DeCaprio et al. (1986): Relative Liver Weight, Males 1 

## E.3.16.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 <0.0001 25.86 <0.0001 65.17 6.2E+00 3.7E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 1 <0.0001 25.30 <0.0001 66.60 5.1E+00 3.9E+00 nonconstant variance, power restricted ≥ 1 exponential (M4)

c 1 <0.0001 16.82 <0.0001 58.12 3.8E-01 1.4E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 <0.0001 7.80 N/A 51.11 3.5E-01 1.3E-01 nonconstant variance, power restricted ≥ 1

Hill 1 <.0001 7.80 0.01 49.11 2.8E-01 error nonconstant variance, n restricted >1, bound hit

linear 2 <.0001 25.90 <.0001 65.20 6.3E+00 3.4E+00 nonconstant variance

polynomial 2 <.0001 25.39 <.0001 64.69 5.8E+00 4.4E+00 nonconstant variance

power 1 <.0001 25.30 <.0001 66.60 5.1E+00 3.7E+00 nonconstant variance, power restricted ≥ 1
exponential (M2) 2 <0.0001 5.09 0.08 64.15 5.6E+00 3.4E+00 constant variance, power restricted ≥ 1
exponential (M3) 2 <0.0001 5.09 0.08 64.15 5.6E+00 3.4E+00 constant variance, power restricted ≥ 1
exponential (M4) 1 <0.0001 2.15 0.14 63.21 1.1E+00 2.7E-01 constant variance, power restricted ≥ 1
exponential (M5) 0 <0.0001 0.72 N/A 63.78 6.3E-01 1.3E-01 constant variance, power restricted ≥ 1

Hill 0 <.0001 0.72 NA 63.78 6.5E-01 error constant variance, n restricted >1

linear 2 <.0001 5.00 0.08 64.06 5.5E+00 3.2E+00 constant variance

polynomial 2 <.0001 5.00 0.08 64.06 5.5E+00 3.2E+00 constant variance

power 2 <.0001 5.00 0.08 64.06 5.5E+00 3.2E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-404 E.3.16.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

3.5 4 4.5

5 5.5

6 6.5

7

0 1 2 3 4 5Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:11 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.16.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\Exp_BMR1_rel_male_liver_wt.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 14:11:44 2009 14

==================================================================== 15 16 Rel Male Liver wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-405 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 4 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 4 17

-------- -------- 18 lnalpha -10.8833 19 rho 6.71347 20 a 3.895 21 b 0.428412 22 c 1.51772 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 4 30

-------- ------- 31 lnalpha -12.146 32 rho 7.6297 33 a 4.32 34 b 2.79927 35 c 1.2705 36 d 18 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 10 4.54 0.7273 44 0.12 10 4.1 0.4427 45 0.61 11 5.36 2.023 46 4.9 10 5.63 0.9171 47 48 49 Estimated Values of Interest 50 51 Dose Est Mean Est Std Scaled Residual 52

------ ---------- --------- ---------------- 53 0 4.333 0.6741 0.9699 54 0.12 4.633 0.8928 -1.889 55 0.61 5.172 1.417 0.4393 56 4.9 5.338 1.617 0.5712 57 58 59 60 Other models for which likelihoods are calculated: 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-406 1 Model R: Yij = Mu + e(i) 2 Var{e(ij)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) DF AIC 8

------- ----------------- ---- ------------ 9 A1 -26.53142 5 63.06284 10 A2 -13.9487 8 43.89739 11 A3 -15.65277 6 43.30554 12 R -31.57211 2 67.14421 13 4 -24.06213 5 58.12426 14 15 16 Additive constant for all log-likelihoods = -37.68. This constant added to the 17 above values gives the log-likelihood including the term that does not 18 depend on the model parameters. 19 20 21 Explanation of Tests 22 23 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 24 Test 2: Are Variances Homogeneous? (A2 vs. A1) 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 26 27 Test 6a: Does Model 4 fit the data? (A3 vs 4) 28 29 30 Tests of Interest 31 32 Test -2*log(Likelihood Ratio) D. F. p-value 33

-------- ------------------------ ------ -------------- 34 Test 1 35.25 6 < 0.0001 35 Test 2 25.17 3 < 0.0001 36 Test 3 3.408 2 0.1819 37 Test 6a 16.82 1 < 0.0001 38 39 40 The p-value for Test 1 is less than .05. There appears to be a 41 difference between response and/or variances among the dose 42 levels, it seems appropriate to model the data. 43 44 The p-value for Test 2 is less than .1. A non-homogeneous 45 variance model appears to be appropriate. 46 47 The p-value for Test 3 is greater than .1. The modeled 48 variance appears to be appropriate here. 49 50 The p-value for Test 6a is less than .1. Model 4 may not adequately 51 describe the data; you may want to consider another model. 52 53 54 Benchmark Dose Computations: 55 56 Specified Effect = 1.000000 57 58 Risk Type = Estimated standard deviations from control 59 60 Confidence Level = 0.950000 61 62 BMD = 0.376095 63 64 BMDL = 0.137425 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-407 E.3.17. DeCaprio et al. (1986): Rela tive Th ymus Weight, Males 1 

## E.3.17.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.07 7.12 0.03 -308.01 6.0E+00 3.4E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.07 7.12 0.03 -308.01 6.0E+00 3.4E+00 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.07 5.77 0.02 -307.36 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.07 5.77 0.02 -307.36 error error nonconstant variance, power restricted ≥ 1

Hill 1 0.07 4.71 0.03 -308.42 error error nonconstant variance, n restricted >1, bound hit

linear 2 0.07 7.19 0.03 -307.94 5.9E+00 3.6E+00 nonconstant variance

polynomial 1 0.07 5.98 0.01 -307.16 2.0E+00 6.8E-01 nonconstant variance

power 2 0.07 7351250 <0.0001 7350937 error error nonconstant variance, power restricted ≥ 1, bound hit exponential (M2)

c 2 0.07 4.25 0.12 -306.73 5.1E+00 2.8E+00 constant variance, power restricted ≥ 1
exponential (M3) 2 0.07 4.25 0.12 -306.73 5.1E+00 2.8E+00 constant variance, power restricted ≥ 1
exponential (M4) 1 0.07 3.29 0.07 -305.69 1.8E+00 7.6E-03 constant variance, power restricted ≥ 1
exponential (M5) 1 0.07 3.29 0.07 -305.69 1.8E+00 7.1E-03 constant variance, power restricted ≥ 1

Hill 1 0.07 2.10 0.15 -306.88 3.2E-01 5.1E-07 constant variance, n restricted >1, bound hit

linear 2 0.07 4.30 0.12 -306.68 5.2E+00 3.1E+00 constant variance

polynomial 1 0.07 3.48 0.06 -305.50 1.4E+00 5.1E-01 constant variance

power 2 0.07 4.30 0.12 -306.68 5.2E+00 3.1E+00 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-408 E.3.17.2. Figure for selected Model: Exponential (M 2), C onstant Variance, Power Restricted 1 

## ≥ 1 2

0.05 0.055 0.06 0.065 0.07 0.075 0.08 0.085 0.09 0.095

0 1 2 3 4 5Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

14:12 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.17.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\ExpConstVar_BMR1_rel_male_thymus_wt.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 14:12:33 2009 14

==================================================================== 15 16 Rel Male Thymus wt, Tbl 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-409 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 2 18

-------- -------- 19 lnalpha -8.73123 20 rho(S) 0 21 a 0.0819 22 b 0.468839 23 c 0.686086 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 2 33

-------- ------- 34 lnalpha -8.65107 35 rho 0 36 a 0.0739582 37 b 1.27978 38 c 0.80201 39 d 1 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 10 0.078 0.01897 47 0.12 10 0.066 0.009487 48 0.61 11 0.068 0.01327 49 4.9 10 0.059 0.009487 50 51 52 Estimated Values of Interest 53 54 Dose Est Mean Est Std Scaled Residual 55

------ ---------- --------- ---------------- 56 0 0.07145 0.01338 1.548 57 0.12 0.0711 0.01338 -1.205 58 0.61 0.0697 0.01338 -0.4219 59 4.9 0.05857 0.01338 0.1014 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-410 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 158.4903 5 -306.9805 13 A2 161.9563 8 -307.9126 14 A3 158.4903 5 -306.9805 15 R 153.4442 2 -302.8885 16 2 156.3648 3 -306.7296 17 18 19 Additive constant for all log-likelihoods = -37.68. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 Test 4: Does Model 2 fit the data? (A3 vs. 2) 30 31 32 Tests of Interest 33 34 Test -2*log(Likelihood Ratio) D. F. p-value 35

-------- ------------------------ ------ -------------- 36 Test 1 17.02 6 0.009195 37 Test 2 6.932 3 0.07409 38 Test 3 6.932 3 0.07409 39 Test 4 4.251 2 0.1194 40 41 42 The p-value for Test 1 is less than .05. There appears to be a 43 difference between response and/or variances among the dose 44 levels, it seems appropriate to model the data. 45 46 The p-value for Test 2 is less than .1. Consider running 47 a non-homogeneous variance model. 48 49 The p-value for Test 3 is less than .1. You may want to 50 consider a different variance model. 51 52 The p-value for Test 4 is greater than .1. Model 2 seems 53 to adequately describe the data. 54 55 56 Benchmark Dose Computations: 57 58 Specified Effect = 1.000000 59 60 Risk Type = Estimated standard deviations from control 61 62 Confidence Level = 0.950000 63 64 BMD = 5.11373 65 66 BMDL = 2.82487 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-411 E.3.18. Hojo et al. (2002): DRL Reinforce per Min 1 

## E.3.18.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.43 9.01 0.01 10.48 6.9E+02 1.7E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 1 0.43 8.95 0.00 12.43 3.9E+02 1.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.43 2.92 0.09 6.39 1.0E+01 1.5E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.43 2.31 N/A 7.78 2.0E+01 error nonconstant variance, power restricted ≥ 1

Hill 1 0.43 1.#QNAN <.0001 7.60 error error nonconstant variance, n restricted >1

linear 2 0.43 9.21 0.01 11.02 error error nonconstant variance

polynomial 2 0.43 8.79 0.01 10.60 error 4.4E+02 nonconstant variance

power 2 0.43 8.28 0.02 9.98 error error nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.43 10.12 0.01 9.89 3.0E+02 1.5E+02 constant variance, power restricted ≥ 1
exponential (M3) 2 0.43 10.12 0.01 9.89 3.0E+02 1.5E+02 constant variance, power restricted ≥ 1
exponential (M4) 1 0.43 3.47 0.06 5.24 1.7E+01 3.8E-02 constant variance, power restricted ≥ 1
exponential (M5) 0 0.43 2.70 N/A 6.46 2.1E+01 1.2E-05 constant variance, power restricted ≥ 1

Hill 0 0.43 2.70 NA 6.46 2.1E+01 1.7E-05 constant variance, n restricted >1

linear c 2 0.43 9.78 0.01 9.55 2.7E+02 1.1E+02 constant variance

polynomial 2 0.43 9.78 0.01 9.55 2.7E+02 1.1E+02 constant variance

power 2 0.43 9.78 0.01 9.55 2.7E+02 1.1E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-412 E.3.18.2. Figure for Selected Model: Linear, Constant Variance 1

-1.5 -1 -0.5

0 0.5

1

0 50 100 150 200 250Mean Response

dose Linear Model with 0.95 Confidence Level

14:33 10/06 2009 BMD BMDL Linear

2 3 4 

## E.3.18.3. Output File for Selected Mode l: L inear, Constant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\AniDose\LinearConstVar_BMR1_DRL_reinforce_per_min.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\AniDose\LinearConstVar_BMR1_DRL_reinforce_per_min.plt 12 Tue Oct 06 14:33:14 2009 13

==================================================================== 14 15 Table 5 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Signs of the polynomial coefficients are not restricted 27 A constant variance model is fit 28 29 Total number of dose groups = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-413 1 Default Initial Parameter Values 2 alpha = 0.337763 3 rho = 0 Specified 4 beta_0 = -0.404 5 beta_1 = 0.00249615 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 ( *** The model parameter(s) -rho 11 have been estimated at a boundary point, or have been specified by the user, 12 and do not appear in the correlation matrix ) 13 14 alpha beta_0 beta_1 15 16 alpha 1 -1.4e-008 2.2e-008 17 18 beta_0 -1.4e-008 1 -0.69 19 20 beta_1 2.2e-008 -0.69 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 alpha 0.435671 0.134451 0.172152 0.69919 29 beta_0 -0.372098 0.198702 -0.761547 0.017352 30 beta_1 0.00246548 0.00211361 -0.00167711 0.00660807 31 32 33 34 Table of Data and Estimated Values of Interest 35 36 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 37

------ --- -------- -------- ----------- ----------- ---------- 38 39 0 5 -0.814 -0.372 0.448 0.66 -1.5 40 20 5 -0.364 -0.323 0.821 0.66 -0.14 41 60 6 0.374 -0.224 0.54 0.66 2.22 42 180 5 -0.163 0.0717 0.443 0.66 -0.795 43 44 45 46 Model Descriptions for likelihoods calculated 47 48 49 Model A1: Yij = Mu(i) + e(ij) 50 Var{e(ij)} = Sigma^2 51 52 Model A2: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma(i)^2 54 55 Model A3: Yij = Mu(i) + e(ij) 56 Var{e(ij)} = Sigma^2 57 Model A3 uses any fixed variance parameters that 58 were specified by the user 59 60 Model R: Yi = Mu + e(i) 61 Var{e(i)} = Sigma^2 62 63 64 Likelihoods of Interest 65 66 Model Log(likelihood) # Param's AIC 67 A1 3.115550 5 3.768900 68 A2 4.489557 8 7.020886 69 A3 3.115550 5 3.768900 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-414 fitted -1.775882 3 9.551763 1 R -2.435087 2 8.870174 2 3 4 Explanation of Tests 5 6 Test 1: Do responses and/or variances differ among Dose levels? 7 (A2 vs. R) 8 Test 2: Are Variances Homogeneous? (A1 vs A2) 9 Test 3: Are variances adequately modeled? (A2 vs. A3) 10 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 11 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 12 13 Tests of Interest 14 15 Test -2*log(Likelihood Ratio) Test df p-value 16 17 Test 1 13.8493 6 0.03137 18 Test 2 2.74801 3 0.4321 19 Test 3 2.74801 3 0.4321 20 Test 4 9.78286 2 0.007511 21 22 The p-value for Test 1 is less than .05. There appears to be a 23 difference between response and/or variances among the dose levels 24 It seems appropriate to model the data 25 26 The p-value for Test 2 is greater than .1. A homogeneous variance 27 model appears to be appropriate here 28 29 30 The p-value for Test 3 is greater than .1. The modeled variance appears 31 to be appropriate here 32 33 The p-value for Test 4 is less than .1. You may want to try a different 34 model 35 36 37 Benchmark Dose Computation 38 39 Specified effect = 1 40 41 Risk Type = Estimated standard deviations from the control mean 42 43 Confidence level = 0.95 44 45 BMD = 267.718 46 47 48 BMDL = 110.032 49 50 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-415 E.3.19. Hojo et al. (2002): DRL Response per Min 1 

## E.3.19.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.30 -0.14 N/A 122.33 4.3E+00 error nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.30 25.76 <0.0001 148.23 error error nonconstant variance, power restricted ≥ 1
exponential (M4) 2 0.30 -0.12 N/A 122.35 4.7E+00 3.2E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.30 0.16 0.69 124.63 6.4E+00 4.1E-01 nonconstant variance, power restricted ≥ 1

Hill 0 0.30 1.#QNAN NA 127.53 1.3E+01 1.8E-13 nonconstant variance, n restricted >1

linear 2 0.30 11.09 0.00 133.30 2.1E+02 9.9E+01 nonconstant variance

polynomial 2 0.30 11.09 0.00 133.30 2.1E+02 error nonconstant variance

power 2 0.30 12.33 0.00 133.30 2.2E+02 9.6E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.30 1.13 0.57 122.98 6.2E+00 error constant variance, power restricted ≥ 1
exponential (M3) 2 0.30 1.13 0.57 122.98 6.2E+00 error constant variance, power restricted ≥ 1 exponential (M4)

c 1 0.30 0.50 0.48 124.36 4.8E+00 2.7E-01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.30 0.50 N/A 126.35 1.1E+01 2.1E-01 constant variance, power restricted ≥ 1

Hill 0 0.30 0.50 NA 126.35 1.6E+01 1.8E-13 constant variance, n restricted >1

linear 2 0.30 10.97 0.00 132.83 2.1E+02 9.8E+01 constant variance

polynomial 2 0.30 10.97 0.00 132.83 2.1E+02 9.8E+01 constant variance

power 2 0.30 10.97 0.00 132.83 2.1E+02 9.8E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-416 E.3.19.2. Figure for Selected Model: Exponential (M 4), C onstant Variance, Power Restricted 1 

## ≥ 1 2

-10 0 10 20 30

0 20 40 60 80 100 120 140 160 180Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:34 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.19.3. Output File for Selected Model: Expo nential (M4), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\ExpConstVar_BMR1_DRL_response_per_min.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 14:34:01 2009 14

==================================================================== 15 16 Table 5, values adjusted by a constant to allow exponential model 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-417 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 4 18

-------- -------- 19 lnalpha 4.51689 20 rho(S) 0 21 a 24.6362 22 b 0.0212679 23 c 0.0184785 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 4 33

-------- ------- 34 lnalpha 4.54064 35 rho 0 36 a 23.463 37 b 0.073228 38 c 0.100111 39 d 2.44375 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 5 23.46 7.986 47 20 5 4.013 10.96 48 60 6 0.478 7.194 49 180 5 4.594 15.23 50 51 52 Estimated Values of Interest 53 54 Dose Est Mean Est Std Scaled Residual 55

------ ---------- --------- ---------------- 56 0 23.47 9.683 -0.0004677 57 20 3.973 9.683 0.009182 58 60 2.37 9.683 -0.4787 59 180 2.361 9.683 0.5157 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-418 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 -57.92733 5 125.8547 13 A2 -56.09669 8 128.1934 14 A3 -57.92733 5 125.8547 15 R -64.49611 2 132.9922 16 4 -58.17787 4 124.3557 17 18 19 Additive constant for all log-likelihoods = -19.3. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 30 Test 6a: Does Model 4 fit the data? (A3 vs 4) 31 32 33 Tests of Interest 34 35 Test -2*log(Likelihood Ratio) D. F. p-value 36

-------- ------------------------ ------ -------------- 37 Test 1 16.8 6 0.01005 38 Test 2 3.661 3 0.3004 39 Test 3 3.661 3 0.3004 40 Test 6a 0.5011 1 0.479 41 42 43 The p-value for Test 1 is less than .05. There appears to be a 44 difference between response and/or variances among the dose 45 levels, it seems appropriate to model the data. 46 47 The p-value for Test 2 is greater than .1. A homogeneous 48 variance model appears to be appropriate here. 49 50 The p-value for Test 3 is greater than .1. The modeled 51 variance appears to be appropriate here. 52 53 The p-value for Test 6a is greater than .1. Model 4 seems 54 to adequately describe the data. 55 56 57 Benchmark Dose Computations: 58 59 Specified Effect = 1.000000 60 61 Risk Type = Estimated standard deviations from control 62 63 Confidence Level = 0.950000 64 65 BMD = 4.77493 66 67 BMDL = 0.270447 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-419 E.3.20. Kattainen et al. (2001): 3 rd 

## Molar Mesio-Distal Length (Molar Development) 1 

## E.3.20.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 <0.0001 38.91 <0.0001 -122.95 4.0E+02 2.4E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 38.91 <0.0001 -122.95 4.0E+02 2.4E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 2 <0.0001 79.12 <0.0001 -80.75 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 1 <0.0001 79.12 <0.0001 -78.75 error error nonconstant variance, power restricted ≥ 1

Hill c 2 <.0001 8.72 0.01 -151.15 4.1E+00 2.1E+00 nonconstant variance, n restricted >1, bound hit

linear 3 <.0001 39.54 <.0001 -122.33 4.7E+02 3.0E+02 nonconstant variance

polynomial 2 <.0001 36.57 <.0001 -123.30 1.9E+02 9.0E+01 nonconstant variance

power 3 <.0001 39.54 <.0001 -122.33 4.7E+02 3.0E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 3 <0.0001 7.81 0.05 -99.70 8.5E+02 5.6E+02 constant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 7.81 0.05 -99.70 8.5E+02 5.6E+02 constant variance, power restricted ≥ 1
exponential (M4) 2 <0.0001 5.05 0.08 -100.47 2.3E+02 1.0E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 5.05 0.08 -100.47 2.3E+02 8.1E-01 constant variance, power restricted ≥ 1

Hill 2 <.0001 3.23 0.20 -102.29 8.1E+01 1.1E+01 constant variance, n restricted >1, bound hit

linear 3 <.0001 8.07 0.04 -99.45 8.8E+02 6.2E+02 constant variance

polynomial 2 <.0001 5.88 0.05 -99.64 3.7E+02 1.8E+02 constant variance

power 3 <.0001 8.07 0.04 -99.45 8.8E+02 6.2E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-420 E.3.20.2. Figure for Selected Model: Hill, Noncon stant Variance, n Restricted >1, Bound Hit 1

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

0 200 400 600 800 1000Mean Response

dose Hill Model with 0.95 Confidence Level

14:36 10/06 2009 BMD BMDL Hill

2 3 4 

## E.3.20.3. Output File for Selected Model: Hill, No nconstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AniDose\Hill_BMR1_3rd_molar.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\Hill_BMR1_3rd_molar.plt 12 Tue Oct 06 14:36:22 2009 13

==================================================================== 14 15 Figure 3 female only 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter restricted to be greater than 1 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-421 Default Initial Parameter Values 1 lalpha = -2.37155 2 rho = 0 3 intercept = 1.85591 4 v = -0.507874 5 n = 0.826204 6 k = 27.3305 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -n 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 lalpha rho intercept v k 16 17 lalpha 1 -0.98 -0.16 0.84 -0.37 18 19 rho -0.98 1 0.2 -0.79 0.39 20 21 intercept -0.16 0.2 1 -0.31 -0.11 22 23 v 0.84 -0.79 -0.31 1 -0.48 24 25 k -0.37 0.39 -0.11 -0.48 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence Interval 32 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 33 lalpha 3.34561 1.40443 0.592981 6.09824 34 rho -14.3325 2.62129 -19.4701 -9.19484 35 intercept 1.8548 0.0159017 1.82364 1.88597 36 v -0.441166 0.058852 -0.556513 -0.325818 37 n 1 NA 38 k 24.0343 7.84495 8.65852 39.4101 39 40 NA - Indicates that this parameter has hit a bound 41 implied by some inequality constraint and thus 42 has no standard error. 43 44 45 46 Table of Data and Estimated Values of Interest 47 48 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 49

------ --- -------- -------- ----------- ----------- ---------- 50 51 0 16 1.86 1.85 0.0661 0.0637 0.0692 52 30 17 1.58 1.61 0.185 0.176 -0.768 53 100 15 1.6 1.5 0.265 0.293 1.28 54 300 12 1.5 1.45 0.221 0.378 0.527 55 1000 19 1.35 1.42 0.515 0.423 -0.783 56 57 58 59 Model Descriptions for likelihoods calculated 60 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-422 Model A3 uses any fixed variance parameters that 1 were specified by the user 2 3 Model R: Yi = Mu + e(i) 4 Var{e(i)} = Sigma^2 5 6 7 Likelihoods of Interest 8 9 Model Log(likelihood) # Param's AIC 10 A1 56.758717 6 -101.517434 11 A2 85.856450 10 -151.712901 12 A3 84.934314 7 -155.868628 13 fitted 80.575940 5 -151.151880 14 R 45.373551 2 -86.747101 15 16 17 Explanation of Tests 18 19 Test 1: Do responses and/or variances differ among Dose levels? 20 (A2 vs. R) 21 Test 2: Are Variances Homogeneous? (A1 vs A2) 22 Test 3: Are variances adequately modeled? (A2 vs. A3) 23 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 24 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 25 26 Tests of Interest 27 28 Test -2*log(Likelihood Ratio) Test df p-value 29 30 Test 1 80.9658 8 <.0001 31 Test 2 58.1955 4 <.0001 32 Test 3 1.84427 3 0.6053 33 Test 4 8.71675 2 0.0128 34 35 The p-value for Test 1 is less than .05. There appears to be a 36 difference between response and/or variances among the dose levels 37 It seems appropriate to model the data 38 39 The p-value for Test 2 is less than .1. A non-homogeneous variance 40 model appears to be appropriate 41 42 The p-value for Test 3 is greater than .1. The modeled variance appears 43 to be appropriate here 44 45 The p-value for Test 4 is less than .1. You may want to try a different 46 model 47 48 49 Benchmark Dose Computation 50 51 Specified effect = 1 52 53 Risk Type = Estimated standard deviations from the control mean 54 55 Confidence level = 0.95 56 57 BMD = 4.05231 58 59 BMDL = 2.14357 60 61 62 63 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-423 E.3.21. Kattainen et al. (2001): Females 3 rd 

## Molar Eruption 1 

## E.3.21.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

logistic 3 3.73 0.29 89.06 1.0E+02 7.3E+01

logistic 3 3.73 0.29 89.06 1.9E+02 1.4E+02

log-logistic b 3 0.48 0.92 85.53 2.3E+01 1.2E+01 slope restricted ≥ 1, bound hit
log-logistic 3 0.48 0.92 85.53 4.8E+01 2.5E+01 slope restricted ≥ 1, bound hit
log-probit 2 0.12 0.94 87.18 1.3E+01 5.2E-01 slope restricted ≥ 1

log-probit 2 0.12 0.94 87.18 2.8E+01 2.3E+00 slope restricted ≥ 1
multistage, 1- degree 3 1.68 0.64 86.80 4.2E+01 2.7E+01 betas restricted ≥ 0
multistage, 1- degree 3 1.68 0.64 86.80 8.7E+01 5.5E+01 betas restricted ≥ 0

probit 3 3.62 0.31 88.92 9.8E+01 7.1E+01

probit 3 3.62 0.31 88.92 1.9E+02 1.4E+02

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-424 E.3.21.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.2 0.4 0.6 0.8

0 200 400 600 800 1000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:05 10/15 2009 BMDL BMD Log-Logistic

2 3 4 

## E.3.21.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: 10 C:\USEPA\BMDS21\AniDose2\LogLogistic_BMR1_Female_3rd_molar_eruption.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AniDose2\LogLogistic_BMR1_Female_3rd_molar_eruption.plt 13 Thu Oct 15 11:05:20 2009 14

==================================================================== 15 16 Figure 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the probability function is: 20 21 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 22 23 24 Dependent variable = DichEff 25 Independent variable = Dose 26 Slope parameter is restricted as slope <= 1 27 28 Total number of observations = 5 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-425 User has chosen the log transformed model 1 2 3 Default Initial Parameter Values 4 background = 0.0625 5 intercept = -6.063 6 slope = 1 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -slope 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 background intercept 16 17 background 1 -0.56 18 19 intercept -0.56 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 background 0.0846785 * * * 28 intercept -6.06063 * * * 29 slope 1 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -40.5286 5 39 Fitted model -40.7674 2 0.477533 3 0.9238 40 Reduced model -50.7341 1 20.411 4 0.0004142 41 42 AIC: 85.5347 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0847 1.355 1.000 16 -0.319 50 30.0000 0.1445 2.457 3.000 17 0.374 51 100.0000 0.2578 3.867 4.000 15 0.078 52 300.0000 0.4615 5.538 6.000 12 0.267 53 1000.0000 0.7254 13.782 13.000 19 -0.402 54 55 Chi^2 = 0.48 d.f. = 3 P-value = 0.9231 56 57 58 Benchmark Dose Computation 59 60 Specified effect = 0.05 61 62 Risk Type = Extra risk 63 64 Confidence level = 0.95 65 66 BMD = 22.5603 67 68 BMDL = 11.7531 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-426 E.3.22. Keller et al. (2006): Missing Mandibular Molars in CBA J Mice 1 

## E.3.22.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 1 2.63 0.10 52.49 5.2E+01 9.9E+00 power restricted ≥ 1

gamma 1 2.63 0.10 52.49 7.3E+01 2.0E+01 power restricted ≥ 1

logistic 2 2.28 0.32 50.10 4.6E+01 3.1E+01

logistic 2 2.28 0.32 50.10 7.2E+01 5.1E+01

log-logistic 1 2.62 0.11 52.52 8.5E+01 3.6E+01 slope restricted ≥ 1

log-logistic 1 2.62 0.11 52.52 9.3E+01 5.3E+01 slope restricted ≥ 1

log-probit 1 2.62 0.11 52.52 7.8E+01 3.9E+01 slope restricted ≥ 1

log-probit 1 2.62 0.11 52.52 8.9E+01 5.3E+01 slope restricted ≥ 1
multistage, 2- degree 1 2.34 0.13 51.52 2.4E+01 1.1E+01 betas restricted ≥ 0
multistage, 1- degree b 3 3.87 0.28 49.41 1.4E+01 9.2E+00 betas restricted ≥ 0
multistage, 2- degree 1 2.34 0.13 51.52 4.6E+01 2.2E+01 betas restricted ≥ 0
multistage, 1- degree 3 3.87 0.28 49.41 2.8E+01 1.9E+01 betas restricted ≥ 0

probit 2 2.25 0.32 50.03 4.3E+01 2.8E+01

probit 2 2.25 0.32 50.03 6.8E+01 4.8E+01

Weibull 1 2.58 0.11 52.22 3.7E+01 1.0E+01 power restricted ≥ 1

Weibull 1 2.58 0.11 52.22 6.1E+01 2.1E+01 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-427 E.3.22.2. Figure for Selected Model: Multis tage, 1-Degree, Betas Restricted ≥ 0 1

0 0.2 0.4 0.6 0.8

1

0 200 400 600 800 1000Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:04 10/15 2009 BMD BMDL Multistage

2 3 4 

## E.3.22.3. Output File for Selected Model: Multistage, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Model. (Version: 3.0; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AniDose2\Multi1st_BMR1_CBA_J_mandibular.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose2\Multi1st_BMR1_CBA_J_mandibular.plt 11 Thu Oct 15 11:04:49 2009 12

==================================================================== 13 14 Table 1 using mandibular molars only 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 Maximum number of iterations = 250 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-428 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 Background = 0 7 Beta(1) = 1.02909e+017 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -Background 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 Beta(1) 17 18 Beta(1) 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0 * * * 27 Beta(1) 0.00379264 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -21.5798 4 37 Fitted model -23.7044 1 4.24924 3 0.2358 38 Reduced model -71.326 1 99.4926 3 <.0001 39 40 AIC: 49.4088 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0000 0.000 0.000 29 0.000 48 10.0000 0.0372 0.856 2.000 23 1.260 49 100.0000 0.3156 9.153 6.000 29 -1.260 50 1000.0000 0.9775 29.324 30.000 30 0.832 51 52 Chi^2 = 3.87 d.f. = 3 P-value = 0.2762 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.05 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 13.5244 64 65 BMDL = 9.17426 66 67 BMDU = 20.3135 68 69 Taken together, (9.17426, 20.3135) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-429 interval for the BMD 1 2 3 4 

## E.3.23. Kociba et al. (1978): Urinary Copr oporphyrins, Females (Table 2) 5 

## E.3.23.1. Summary Table of BMDS Modeling Results 6

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.03 19.68 <0.0001 84.01 7.1E+01 4.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.03 19.68 <0.0001 84.01 7.1E+01 4.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M4)

c 1 0.03 4.23 0.04 70.56 1.6E+00 7.3E-01 nonconstant variance, power restricted ≥ 1 exponential (M5) 0 0.03 0.76 N/A 69.09 3.1E+00 1.0E+00 nonconstant variance, power restricted ≥ 1

linear 2 0.03 19.38 <.0001 83.71 6.2E+01 3.1E+01 nonconstant variance

polynomial 2 0.03 19.38 <.0001 83.71 6.2E+01 3.1E+01 nonconstant variance

power 2 0.03 19.38 <.0001 83.71 6.2E+01 3.1E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.03 12.65 0.00 82.04 6.9E+01 4.7E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 0.03 12.65 0.00 82.04 6.9E+01 4.7E+01 constant variance, power restricted ≥ 1
exponential (M4) 1 0.03 1.96 0.16 73.36 2.7E+00 1.1E+00 constant variance, power restricted ≥ 1
exponential (M5) 0 0.03 0.41 N/A 73.80 8.3E+00 1.0E+00 constant variance, power restricted ≥ 1

Hill 0 0.03 0.41 NA 73.80 7.6E+00 error constant variance, n restricted >1

linear 2 0.03 12.32 0.00 81.72 6.1E+01 3.8E+01 constant variance

polynomial 2 0.03 12.32 0.00 81.72 6.1E+01 3.8E+01 constant variance

power 2 0.03 12.32 0.00 81.72 6.1E+01 3.8E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 7 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-430 E.3.23.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

6 8 10 12 14 16 18 20 22 24

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:21 11/11 2009 BMD BMDL Exponential

3 4 5 

## E.3.23.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Exp_BMR1_urin_copropor_f.(d) 12 Gnuplot Plotting File: 13 Wed Nov 11 13:21:02 2009 14

==================================================================== 15 16 Table2-UrinaryCoproporphyrin 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-431 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 4 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 4 17

-------- -------- 18 lnalpha -5.58269 19 rho 2.98472 20 a 8.17 21 b 0.0259469 22 c 2.23623 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 4 30

-------- ------- 31 lnalpha -5.49254 32 rho 2.91176 33 a 9.2 34 b 0.295128 35 c 1.83696 36 d 18 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 5 9.8 1.3 44 1 5 8.6 2 45 10 5 16.4 4.7 46 100 5 17.4 4 47 48 49 Estimated Values of Interest 50 51 Dose Est Mean Est Std Scaled Residual 52

------ ---------- --------- ---------------- 53 0 8.93 1.733 1.122 54 1 10.04 2.038 -1.582 55 10 15.42 3.683 0.5967 56 100 17.64 4.436 -0.1211 57 58 59 60 Other models for which likelihoods are calculated: 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-432 1 Model R: Yij = Mu + e(i) 2 Var{e(ij)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) DF AIC 8

------- ----------------- ---- ------------ 9 A1 -31.69739 5 73.39478 10 A2 -27.21541 8 70.43081 11 A3 -28.16434 6 68.32868 12 R -41.73188 2 87.46376 13 4 -30.27804 5 70.55608 14 15 16 Additive constant for all log-likelihoods = -18.38. This constant added to the 17 above values gives the log-likelihood including the term that does not 18 depend on the model parameters. 19 20 21 Explanation of Tests 22 23 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 24 Test 2: Are Variances Homogeneous? (A2 vs. A1) 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 26 27 Test 6a: Does Model 4 fit the data? (A3 vs 4) 28 29 30 Tests of Interest 31 32 Test -2*log(Likelihood Ratio) D. F. p-value 33

-------- ------------------------ ------ -------------- 34 Test 1 29.03 6 < 0.0001 35 Test 2 8.964 3 0.02977 36 Test 3 1.898 2 0.3872 37 Test 6a 4.227 1 0.03978 38 39 40 The p-value for Test 1 is less than .05. There appears to be a 41 difference between response and/or variances among the dose 42 levels, it seems appropriate to model the data. 43 44 The p-value for Test 2 is less than .1. A non-homogeneous 45 variance model appears to be appropriate. 46 47 The p-value for Test 3 is greater than .1. The modeled 48 variance appears to be appropriate here. 49 50 The p-value for Test 6a is less than .1. Model 4 may not adequately 51 describe the data; you may want to consider another model. 52 53 54 Benchmark Dose Computations: 55 56 Specified Effect = 1.000000 57 58 Risk Type = Estimated standard deviations from control 59 60 Confidence Level = 0.950000 61 62 BMD = 1.62505 63 64 BMDL = 0.729987 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-433 E.3.24. Kociba et al. (1978): Uroporphyrin per Creatinine, Females 1 

## E.3.24.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.49 1.45 0.48 -93.10 3.8E+01 2.6E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.49 1.45 0.48 -93.10 3.8E+01 2.6E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.49 0.73 0.39 -91.82 1.4E+01 4.4E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.49 0.51 N/A -90.03 1.0E+01 4.5E+00 nonconstant variance, power restricted ≥ 1

Hill 0 0.49 0.51 NA -90.03 1.0E+01 7.7E+00 nonconstant variance, n restricted >1

linear 2 0.49 1.20 0.55 -93.35 2.9E+01 1.8E+01 nonconstant variance

polynomial 1 0.49 0.72 0.40 -91.83 1.3E+01 4.8E+00 nonconstant variance

power 2 0.49 1.20 0.55 -93.35 2.9E+01 1.8E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.49 0.83 0.66 -93.56 4.4E+01 3.3E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 0.49 0.83 0.66 -93.56 4.4E+01 3.3E+01 constant variance, power restricted ≥ 1
exponential (M4) 1 0.49 0.31 0.58 -92.08 1.7E+01 5.5E+00 constant variance, power restricted ≥ 1
exponential (M5) 0 0.49 0.20 N/A -90.19 1.1E+01 5.6E+00 constant variance, power restricted ≥ 1

linear c 2 0.49 0.66 0.72 -93.73 3.5E+01 2.5E+01 constant variance

polynomial 1 0.49 0.31 0.58 -92.08 1.7E+01 6.1E+00 constant variance

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-434 E.3.24.2. Figure for Selected Model: Linear, Constant Variance 1

0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 20 40 60 80 100Mean Response

dose Linear Model with 0.95 Confidence Level

15:00 10/06 2009 BMD BMDL Linear

2 3 4 

## E.3.24.3. Output File for Selected Mode l: L inear, Constant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: 10 C:\USEPA\BMDS21\AniDose\LinearConstVar_BMR1_Females_uroporphyrin_per_creatinine.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AniDose\LinearConstVar_BMR1_Females_uroporphyrin_per_creatinine.plt 13 Tue Oct 06 15:00:16 2009 14

==================================================================== 15 16 Table 2 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 rho is set to 0 27 Signs of the polynomial coefficients are not restricted 28 A constant variance model is fit 29 30 Total number of dose groups = 4 31 Total number of records with missing values = 0 32 Maximum number of iterations = 250 33 Relative Function Convergence has been set to: 1e-008 34 Parameter Convergence has been set to: 1e-008 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-435 1 2 Default Initial Parameter Values 3 alpha = 0.0030385 4 rho = 0 Specified 5 beta_0 = 0.154759 6 beta_1 = 0.0014231 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -rho 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 alpha beta_0 beta_1 16 17 alpha 1 -2.2e-009 3.5e-009 18 19 beta_0 -2.2e-009 1 -0.55 20 21 beta_1 3.5e-009 -0.55 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 0.00251184 0.000794315 0.000955015 0.00406867 30 beta_0 0.154759 0.0134422 0.128413 0.181105 31 beta_1 0.0014231 0.000267497 0.000898818 0.00194739 32 33 34 35 Table of Data and Estimated Values of Interest 36 37 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 38

------ --- -------- -------- ----------- ----------- ---------- 39 40 0 5 0.157 0.155 0.05 0.0501 0.1 41 1 5 0.143 0.156 0.037 0.0501 -0.588 42 10 5 0.181 0.169 0.053 0.0501 0.536 43 100 5 0.296 0.297 0.074 0.0501 -0.0477 44 45 46 47 Model Descriptions for likelihoods calculated 48 49 50 Model A1: Yij = Mu(i) + e(ij) 51 Var{e(ij)} = Sigma^2 52 53 Model A2: Yij = Mu(i) + e(ij) 54 Var{e(ij)} = Sigma(i)^2 55 56 Model A3: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma^2 58 Model A3 uses any fixed variance parameters that 59 were specified by the user 60 61 Model R: Yi = Mu + e(i) 62 Var{e(i)} = Sigma^2 63 64 65 Likelihoods of Interest 66 67 Model Log(likelihood) # Param's AIC 68 A1 50.195349 5 -90.390697 69 A2 51.400051 8 -86.800103 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-436 A3 50.195349 5 -90.390697 1 fitted 49.867385 3 -93.734769 2 R 41.049755 2 -78.099510 3 4 5 Explanation of Tests 6 7 Test 1: Do responses and/or variances differ among Dose levels? 8 (A2 vs. R) 9 Test 2: Are Variances Homogeneous? (A1 vs A2) 10 Test 3: Are variances adequately modeled? (A2 vs. A3) 11 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 12 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 13 14 Tests of Interest 15 16 Test -2*log(Likelihood Ratio) Test df p-value 17 18 Test 1 20.7006 6 0.002076 19 Test 2 2.40941 3 0.4919 20 Test 3 2.40941 3 0.4919 21 Test 4 0.655928 2 0.7204 22 23 The p-value for Test 1 is less than .05. There appears to be a 24 difference between response and/or variances among the dose levels 25 It seems appropriate to model the data 26 27 The p-value for Test 2 is greater than .1. A homogeneous variance 28 model appears to be appropriate here 29 30 31 The p-value for Test 3 is greater than .1. The modeled variance appears 32 to be appropriate here 33 34 The p-value for Test 4 is greater than .1. The model chosen seems 35 to adequately describe the data 36 37 38 Benchmark Dose Computation 39 40 Specified effect = 1 41 42 Risk Type = Estimated standard deviations from the control mean 43 44 Confidence level = 0.95 45 46 BMD = 35.2176 47 48 49 BMDL = 25.0024 50 51 52 53

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-437 E.3.25. Latchoumycandane and Mathur (2002): Daily sperm Production 1 

## E.3.25.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.85 20.91 <0.0001 96.01 9.2E+01 4.5E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.85 20.91 <0.0001 96.01 9.2E+01 4.5E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.85 0.16 0.69 77.26 2.4E-01 8.8E-02 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.85 0.16 N/A 79.26 2.9E-01 8.8E-02 nonconstant variance, power restricted ≥ 1

Hill 1 0.85 0.04 0.85 77.14 1.4E-01 1.3E-02 nonconstant variance, n restricted >1, bound hit

linear 2 0.85 21.07 <.0001 96.18 9.5E+01 5.4E+01 nonconstant variance

polynomial 1 0.85 10.98 0.00 88.08 6.2E+00 3.7E+00 nonconstant variance

power 2 0.85 21.07 <.0001 96.18 9.5E+01 5.4E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.85 21.99 <0.0001 95.11 7.6E+01 4.0E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 0.85 21.99 <0.0001 95.11 7.6E+01 4.0E+01 constant variance, power restricted ≥ 1
exponential (M4) 1 0.85 0.15 0.70 75.26 2.4E-01 1.0E-01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.85 0.15 N/A 77.26 3.7E-01 1.0E-01 constant variance, power restricted ≥ 1

Hill c 1 0.85 0.03 0.86 75.14 1.4E-01 1.6E-02 constant variance, n restricted >1, bound hit

linear 2 0.85 22.20 <.0001 95.31 8.3E+01 4.9E+01 constant variance

polynomial 1 0.85 12.98 0.00 88.09 5.0E+00 3.2E+00 constant variance

power 2 0.85 22.20 <.0001 95.31 8.3E+01 4.9E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-438 E.3.25.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 1

10 12 14 16 18 20 22 24 26

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

15:09 10/06 2009 BMD BMDL Hill

2 3 4 

## E.3.25.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_sperm_prod.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_sperm_prod.plt 12 Tue Oct 06 15:09:27 2009 13

==================================================================== 14 15 (x10^6) Table 1 without Vitamin E 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter restricted to be greater than 1 27 A constant variance model is fit 28 29 Total number of dose groups = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-439 1 Default Initial Parameter Values 2 alpha = 7.23328 3 rho = 0 Specified 4 intercept = 22.19 5 v = -9.09 6 n = 1.80484 7 k = 0.697086 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -rho -n 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 alpha intercept v k 17 18 alpha 1 6.3e-010 3e-008 8.3e-009 19 20 intercept 6.3e-010 1 -0.78 -0.23 21 22 v 3e-008 -0.78 1 -0.17 23 24 k 8.3e-009 -0.23 -0.17 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 alpha 6.03567 1.74235 2.62073 9.45061 33 intercept 22.1885 1.00316 20.2223 24.1547 34 v -9.00869 1.26801 -11.4939 -6.52343 35 n 1 NA 36 k 0.386669 0.265663 -0.134021 0.907359 37 38 NA - Indicates that this parameter has hit a bound 39 implied by some inequality constraint and thus 40 has no standard error. 41 42 43 44 Table of Data and Estimated Values of Interest 45 46 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 47

------ --- -------- -------- ----------- ----------- ---------- 48 49 0 6 22.2 22.2 2.67 2.46 0.00151 50 1 6 15.7 15.7 2.65 2.46 -0.0218 51 10 6 13.7 13.5 2.19 2.46 0.134 52 100 6 13.1 13.2 3.16 2.46 -0.114 53 54 55 56 Model Descriptions for likelihoods calculated 57 58 59 Model A1: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 62 Model A2: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma(i)^2 64 65 Model A3: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 Model A3 uses any fixed variance parameters that 68 were specified by the user 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-440 Model R: Yi = Mu + e(i) 1 Var{e(i)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) # Param's AIC 7 A1 -33.556444 5 77.112888 8 A2 -33.158811 8 82.317623 9 A3 -33.556444 5 77.112888 10 fitted -33.572245 4 75.144490 11 R -47.392394 2 98.784788 12 13 14 Explanation of Tests 15 16 Test 1: Do responses and/or variances differ among Dose levels? 17 (A2 vs. R) 18 Test 2: Are Variances Homogeneous? (A1 vs A2) 19 Test 3: Are variances adequately modeled? (A2 vs. A3) 20 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 21 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 22 23 Tests of Interest 24 25 Test -2*log(Likelihood Ratio) Test df p-value 26 27 Test 1 28.4672 6 <.0001 28 Test 2 0.795266 3 0.8506 29 Test 3 0.795266 3 0.8506 30 Test 4 0.031602 1 0.8589 31 32 The p-value for Test 1 is less than .05. There appears to be a 33 difference between response and/or variances among the dose levels 34 It seems appropriate to model the data 35 36 The p-value for Test 2 is greater than .1. A homogeneous variance 37 model appears to be appropriate here 38 39 40 The p-value for Test 3 is greater than .1. The modeled variance appears 41 to be appropriate here 42 43 The p-value for Test 4 is greater than .1. The model chosen seems 44 to adequately describe the data 45 46 47 Benchmark Dose Computation 48 49 Specified effect = 1 50 51 Risk Type = Estimated standard deviations from the control mean 52 53 Confidence level = 0.95 54 55 BMD = 0.144988 56 57 BMDL = 0.0155926 58 59 60 61

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-441 E.3.26. Li et al. (2006): Hormone Levels (Estradiol) 1 

## E.3.26.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.47 4.98 0.08 272.78 3.0E+02 1.0E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.47 4.98 0.08 272.78 3.0E+02 1.0E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.47 0.32 0.57 270.12 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.47 0.32 N/A 272.12 error error nonconstant variance, power restricted ≥ 1

Hill 1 0.47 0.32 0.57 270.12 error error nonconstant variance, n restricted >1, bound hit

linear 2 0.47 4.92 0.09 272.72 3.4E+02 9.7E+01 nonconstant variance

polynomial 2 0.47 4.92 0.09 272.72 3.4E+02 9.7E+01 nonconstant variance

power 2 0.47 4.92 0.09 272.72 3.4E+02 9.7E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2)

c 2 0.47 3.84 0.15 270.81 3.2E+02 1.1E+02 constant variance, power restricted ≥ 1
exponential (M3) 2 0.47 3.84 0.15 270.81 3.2E+02 1.1E+02 constant variance, power restricted ≥ 1
exponential (M4) 1 0.47 0.92 0.34 269.90 error error constant variance, power restricted ≥ 1
exponential (M5) 0 0.47 0.92 N/A 271.90 error error constant variance, power restricted ≥ 1

Hill 0 0.47 0.92 NA 271.90 error error constant variance, n restricted >1

linear 2 0.47 3.78 0.15 270.75 3.6E+02 1.1E+02 constant variance

polynomial 2 0.47 3.78 0.15 270.75 3.6E+02 1.1E+02 constant variance

power 2 0.47 3.78 0.15 270.75 3.6E+02 1.1E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-442 E.3.26.2. Figure for Selected Model: Exponential (M 2), C onstant Variance, Power Restricted 1 

## ≥ 1 2

0 5 10 15 20 25 30 35

0 50 100 150 200 250 300Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

13:21 11/11 2009 BMD BMDL Exponential

3 4 5 

## E.3.26.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\ExpConst_BMR1_Li_Estradiol.(d) 12 Gnuplot Plotting File: 13 Wed Nov 11 13:21:55 2009 14

==================================================================== 15 16 Figure 3 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-443 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 2 18

-------- -------- 19 lnalpha 5.52431 20 rho(S) 0 21 a 9.5 22 b 0.0162139 23 c 2.73407 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 2 33

-------- ------- 34 lnalpha 5.54738 35 rho 0 36 a 10 37 b 0.842953 38 c 2.13158 39 d 1.46715 40 41 NC = No Convergence 42 43 44 Table of Stats From Input Data 45 46 Dose N Obs Mean Obs Std Dev 47

----- --- ---------- ------------- 48 0 10 10 12.48 49 2 10 20 19.97 50 50 10 24.74 14.98 51 100 10 17.89 18.31 52 53 54 Estimated Values of Interest 55 56 Dose Est Mean Est Std Scaled Residual 57

------ ---------- --------- ---------------- 58 0 16.66 16.61 -1.267 59 2 16.73 16.61 0.6227 60 50 18.57 16.61 1.173 61 100 20.71 16.61 -0.5362 62 63 64 65 Other models for which likelihoods are calculated: 66 67 Model A1: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-444 Model A2: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = Sigma(i)^2 2 3 Model A3: Yij = Mu(i) + e(ij) 4 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 5 6 Model R: Yij = Mu + e(i) 7 Var{e(ij)} = Sigma^2 8 9 10 Likelihoods of Interest 11 12 Model Log(likelihood) DF AIC 13

------- ----------------- ---- ------------ 14 A1 -130.4861 5 270.9723 15 A2 -129.2199 8 274.4398 16 A3 -130.4861 5 270.9723 17 R -132.6269 2 269.2537 18 2 -132.404 3 270.8079 19 20 21 Additive constant for all log-likelihoods = -36.76. This constant added to the 22 above values gives the log-likelihood including the term that does not 23 depend on the model parameters. 24 25 26 Explanation of Tests 27 28 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 29 Test 2: Are Variances Homogeneous? (A2 vs. A1) 30 Test 3: Are variances adequately modeled? (A2 vs. A3) 31 Test 4: Does Model 2 fit the data? (A3 vs. 2) 32 33 34 Tests of Interest 35 36 Test -2*log(Likelihood Ratio) D. F. p-value 37

-------- ------------------------ ------ -------------- 38 Test 1 6.814 6 0.3384 39 Test 2 2.533 3 0.4694 40 Test 3 2.533 3 0.4694 41 Test 4 3.836 2 0.1469 42 43 44 The p-value for Test 1 is greater than .05. There may not be a 45 diffence between responses and/or variances among the dose levels 46 Modelling the data with a dose/response curve may not be appropriate. 47 48 The p-value for Test 2 is greater than .1. A homogeneous 49 variance model appears to be appropriate here. 50 51 The p-value for Test 3 is greater than .1. The modeled 52 variance appears to be appropriate here. 53 54 The p-value for Test 4 is greater than .1. Model 2 seems 55 to adequately describe the data. 56 57 58 Benchmark Dose Computations: 59 60 Specified Effect = 1.000000 61 62 Risk Type = Estimated standard deviations from control 63 64 Confidence Level = 0.950000 65 66 BMD = 317.497 67 68 BMDL = 111.954 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-445 E.3.27. Li et al. (2006): Hormone Levels (Progesterone) 1 

## E.3.27.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.00 16.99 0.00 330.20 4.9E+01 error nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.00 16.99 0.00 330.20 4.9E+01 error nonconstant variance, power restricted ≥ 1 exponential (M4)

c 1 0.00 0.82 0.37 316.03 1.6E-01 1.0E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.00 0.82 N/A 318.03 4.9E-01 7.9E-02 nonconstant variance, power restricted ≥ 1

Hill 1 0.00 0.81 0.37 316.02 2.2E-02 6.4E-05 nonconstant variance, n restricted >1, bound hit

linear 2 0.00 17.93 0.00 331.13 7.5E+01 5.2E+01 nonconstant variance

polynomial 2 0.00 17.93 0.00 331.13 7.5E+01 5.2E+01 nonconstant variance

power 2 0.00 17.93 0.00 331.13 7.5E+01 4.5E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.00 3.97 0.14 329.50 6.8E+01 error constant variance, power restricted ≥ 1
exponential (M3) 2 0.00 3.97 0.14 329.50 6.8E+01 error constant variance, power restricted ≥ 1
exponential (M4) 1 0.00 0.14 0.71 327.66 2.2E+00 1.3E-01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.00 0.14 N/A 329.66 2.2E+00 2.8E-01 constant variance, power restricted ≥ 1

Hill 1 0.00 0.12 0.73 327.64 2.4E+00 3.5E-05 constant variance, n restricted >1, bound hit

linear 2 0.00 4.97 0.08 330.49 9.2E+01 5.7E+01 constant variance

polynomial 2 0.00 4.97 0.08 330.49 9.2E+01 5.7E+01 constant variance

power 2 0.00 4.97 0.08 330.49 9.2E+01 5.7E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-446 E.3.27.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

-20 0 20 40 60

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:22 11/11 2009 BMD BMDL Exponential

3 4 5 

## E.3.27.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AD\Exp_BMR1_Li_Progesterone.(d) 12 Gnuplot Plotting File: 13 Wed Nov 11 13:22:19 2009 14

==================================================================== 15 16 Figure 4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-447 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 4 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 4 17

-------- -------- 18 lnalpha 11.2757 19 rho -1.43319 20 a 65.0395 21 b 0.0460242 22 c 0.162232 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 4 30

-------- ------- 31 lnalpha 14.0852 32 rho -2.26856 33 a 61.9568 34 b 1.02041 35 c 0.315961 36 d 1.78188 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 10 61.94 11.15 44 2 10 30.72 39.81 45 50 10 16.62 33.44 46 100 10 11.08 44.59 47 48 49 Estimated Values of Interest 50 51 Dose Est Mean Est Std Scaled Residual 52

------ ---------- --------- ---------------- 53 0 61.96 10.61 -0.0043 54 2 20.78 36.65 0.858 55 50 19.58 39.21 -0.2385 56 100 19.58 39.21 -0.6853 57 58 59 60 Other models for which likelihoods are calculated: 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-448 1 Model R: Yij = Mu + e(i) 2 Var{e(ij)} = Sigma^2 3 4 5 Likelihoods of Interest 6 7 Model Log(likelihood) DF AIC 8

------- ----------------- ---- ------------ 9 A1 -159.7613 5 329.5225 10 A2 -151.9206 8 319.8412 11 A3 -152.6038 6 317.2077 12 R -165.9023 2 335.8046 13 4 -153.0132 5 316.0265 14 15 16 Additive constant for all log-likelihoods = -36.76. This constant added to the 17 above values gives the log-likelihood including the term that does not 18 depend on the model parameters. 19 20 21 Explanation of Tests 22 23 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 24 Test 2: Are Variances Homogeneous? (A2 vs. A1) 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 26 27 Test 6a: Does Model 4 fit the data? (A3 vs 4) 28 29 30 Tests of Interest 31 32 Test -2*log(Likelihood Ratio) D. F. p-value 33

-------- ------------------------ ------ -------------- 34 Test 1 27.96 6 < 0.0001 35 Test 2 15.68 3 0.001318 36 Test 3 1.366 2 0.505 37 Test 6a 0.8188 1 0.3655 38 39 40 The p-value for Test 1 is less than .05. There appears to be a 41 difference between response and/or variances among the dose 42 levels, it seems appropriate to model the data. 43 44 The p-value for Test 2 is less than .1. A non-homogeneous 45 variance model appears to be appropriate. 46 47 The p-value for Test 3 is greater than .1. The modeled 48 variance appears to be appropriate here. 49 50 The p-value for Test 6a is greater than .1. Model 4 seems 51 to adequately describe the data. 52 53 54 Benchmark Dose Computations: 55 56 Specified Effect = 1.000000 57 58 Risk Type = Estimated standard deviations from control 59 60 Confidence Level = 0.950000 61 62 BMD = 0.161712 63 64 BMDL = 0.100383 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-449 E.3.28. Markowski et al. (2001): FR10 Run Opp 1 

## E.3.28.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.17 6.17 0.05 119.08 2.3E+02 5.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 1 0.17 10.00 0.00 124.91 1.6E+05 1.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.17 2.09 0.15 117.00 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.17 1.52 N/A 118.43 error error nonconstant variance, power restricted ≥ 1

Hill 0 0.17 1.51 NA 118.43 error error nonconstant variance, n restricted >1

linear 2 0.17 6.66 0.04 119.57 2.5E+02 1.1E+02 nonconstant variance

polynomial 1 0.17 0.00 1.00 114.91 6.2E+01 2.7E+01 nonconstant variance

power 2 0.17 6.66 0.04 119.57 2.5E+02 1.1E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2)

c 2 0.17 2.79 0.25 117.56 1.7E+02 5.0E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 0.17 2.79 0.25 117.56 1.7E+02 5.0E+01 constant variance, power restricted ≥ 1
exponential (M4) 1 0.17 0.67 0.41 117.44 4.7E+01 1.7E-01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.17 0.15 N/A 118.92 3.2E+01 4.0E-05 constant variance, power restricted ≥ 1

Hill 0 0.17 0.15 NA 118.92 2.3E+01 6.7E-06 constant variance, n restricted >1

linear 2 0.17 3.32 0.19 118.09 2.1E+02 1.1E+02 constant variance

polynomial 2 0.17 3.32 0.19 118.09 2.1E+02 1.1E+02 constant variance

power 2 0.17 3.32 0.19 118.09 2.1E+02 1.1E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-450 E.3.28.2. Figure for Selected Model: Exponential (M 2), C onstant Variance, Power Restricted 1 

## ≥ 1 2

0 5 10 15 20

0 20 40 60 80 100 120 140 160 180Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

15:18 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.28.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\ExpConstVar_BMR1_FR10_run_opp.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 15:18:28 2009 14

==================================================================== 15 16 Table 3 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-451 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 2 18

-------- -------- 19 lnalpha 3.5321 20 rho(S) 0 21 a 13.9545 22 b 0.0143568 23 c 0.392432 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 2 33

-------- ------- 34 lnalpha 3.53824 35 rho 0 36 a 13.29 37 b 0.0376253 38 c 0.483301 39 d 3.66691 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 7 13.29 8.65 47 20 4 11.25 5.56 48 60 6 5.75 3.53 49 180 7 7 6.01 50 51 52 Estimated Values of Interest 53 54 Dose Est Mean Est Std Scaled Residual 55

------ ---------- --------- ---------------- 56 0 11.94 6.197 0.5745 57 20 10.93 6.197 0.1025 58 60 9.158 6.197 -1.347 59 180 5.385 6.197 0.6897 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-452 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 -54.38526 5 118.7705 13 A2 -51.88568 8 119.7714 14 A3 -54.38526 5 118.7705 15 R -57.45429 2 118.9086 16 2 -55.77871 3 117.5574 17 18 19 Additive constant for all log-likelihoods = -22.05. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 Test 4: Does Model 2 fit the data? (A3 vs. 2) 30 31 32 Tests of Interest 33 34 Test -2*log(Likelihood Ratio) D. F. p-value 35

-------- ------------------------ ------ -------------- 36 Test 1 11.14 6 0.08423 37 Test 2 4.999 3 0.1719 38 Test 3 4.999 3 0.1719 39 Test 4 2.787 2 0.2482 40 41 42 The p-value for Test 1 is greater than .05. There may not be a 43 diffence between responses and/or variances among the dose levels 44 Modelling the data with a dose/response curve may not be appropriate. 45 46 The p-value for Test 2 is greater than .1. A homogeneous 47 variance model appears to be appropriate here. 48 49 The p-value for Test 3 is greater than .1. The modeled 50 variance appears to be appropriate here. 51 52 The p-value for Test 4 is greater than .1. Model 2 seems 53 to adequately describe the data. 54 55 56 Benchmark Dose Computations: 57 58 Specified Effect = 1.000000 59 60 Risk Type = Estimated standard deviations from control 61 62 Confidence Level = 0.950000 63 64 BMD = 165.284 65 66 BMDL = 50.2488 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-453 E.3.29. Markowski et al. (2001): FR2 Revolutions 1 

## E.3.29.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.11 5.71 0.06 216.09 3.6E+02 1.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.11 5.71 0.06 216.09 3.6E+02 1.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.11 1.94 0.16 214.33 error error nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.11 0.45 N/A 214.83 error error nonconstant variance, power restricted ≥ 1

Hill 1 0.11 0.45 0.50 212.83 error error nonconstant variance, n restricted >1, bound hit

linear 2 0.11 6.08 0.05 216.46 3.3E+02 1.4E+02 nonconstant variance

polynomial 2 0.11 6.08 0.05 216.46 3.3E+02 1.4E+02 nonconstant variance

power 2 0.11 6.08 0.05 216.46 3.3E+02 1.4E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2)

c 2 0.11 3.31 0.19 217.64 1.6E+02 5.8E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 0.11 3.31 0.19 217.64 1.6E+02 5.8E+01 constant variance, power restricted ≥ 1
exponential (M4) 1 0.11 1.08 0.30 217.41 4.7E+01 2.0E-01 constant variance, power restricted ≥ 1
exponential (M5) 0 0.11 0.20 N/A 218.53 3.3E+01 1.2E+01 constant variance, power restricted ≥ 1

Hill 0 0.11 0.20 NA 218.53 2.4E+01 7.3E+00 constant variance, n restricted >1, bound hit

linear 2 0.11 3.80 0.15 218.13 2.0E+02 1.0E+02 constant variance

polynomial 2 0.11 3.80 0.15 218.13 2.0E+02 1.0E+02 constant variance

power 2 0.11 3.80 0.15 218.13 2.0E+02 1.0E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-454 E.3.29.2. Figure for Selected Model: Exponential (M 2), C onstant Variance, Power Restricted 1 

## ≥ 1 2

0 50 100 150 200

0 20 40 60 80 100 120 140 160 180Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

15:18 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.29.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\ExpConstVar_BMR1_FR2_revolutions.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 15:18:54 2009 14

==================================================================== 15 16 Table 3 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-455 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 4 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 2 18

-------- -------- 19 lnalpha 7.68046 20 rho(S) 0 21 a 125.255 22 b 0.0134965 23 c 0.429602 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 2 33

-------- ------- 34 lnalpha 7.68885 35 rho 0 36 a 119.29 37 b 0.0345516 38 c 0.526177 39 d 4.19941 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 7 119.3 69.9 47 20 4 108.5 61 48 60 6 56.5 31.21 49 180 7 68.14 33.23 50 51 52 Estimated Values of Interest 53 54 Dose Est Mean Est Std Scaled Residual 55

------ ---------- --------- ---------------- 56 0 108.9 49.85 0.5497 57 20 101 49.85 0.2994 58 60 86.93 49.85 -1.495 59 180 55.35 49.85 0.6786 60 61 62 63 Other models for which likelihoods are calculated: 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-456 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 3 4 Model R: Yij = Mu + e(i) 5 Var{e(ij)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) DF AIC 11

------- ----------------- ---- ------------ 12 A1 -104.1655 5 218.331 13 A2 -101.1402 8 218.2803 14 A3 -104.1655 5 218.331 15 R -107.5993 2 219.1985 16 2 -105.8179 3 217.6357 17 18 19 Additive constant for all log-likelihoods = -22.05. This constant added to the 20 above values gives the log-likelihood including the term that does not 21 depend on the model parameters. 22 23 24 Explanation of Tests 25 26 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 27 Test 2: Are Variances Homogeneous? (A2 vs. A1) 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 29 Test 4: Does Model 2 fit the data? (A3 vs. 2) 30 31 32 Tests of Interest 33 34 Test -2*log(Likelihood Ratio) D. F. p-value 35

-------- ------------------------ ------ -------------- 36 Test 1 12.92 6 0.04435 37 Test 2 6.051 3 0.1092 38 Test 3 6.051 3 0.1092 39 Test 4 3.305 2 0.1916 40 41 42 The p-value for Test 1 is less than .05. There appears to be a 43 difference between response and/or variances among the dose 44 levels, it seems appropriate to model the data. 45 46 The p-value for Test 2 is greater than .1. A homogeneous 47 variance model appears to be appropriate here. 48 49 The p-value for Test 3 is greater than .1. The modeled 50 variance appears to be appropriate here. 51 52 The p-value for Test 4 is greater than .1. Model 2 seems 53 to adequately describe the data. 54 55 56 Benchmark Dose Computations: 57 58 Specified Effect = 1.000000 59 60 Risk Type = Estimated standard deviations from control 61 62 Confidence Level = 0.950000 63 64 BMD = 162.682 65 66 BMDL = 58.0677 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-457 E.3.30. Markowski et al. (2001): FR5 Run Opp 1 

## E.3.30.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 2 0.23 5.55 0.06 134.53 1.4E+02 5.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 0.23 5.55 0.06 134.53 1.4E+02 5.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 1 0.23 1.05 0.31 132.03 3.6E+01 1.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 0 0.23 0.08 N/A 133.06 2.8E+01 1.4E+01 nonconstant variance, power restricted ≥ 1

Hill 0 0.23 0.08 NA 133.06 2.2E+01 error nonconstant variance, n restricted >1

linear 2 0.23 6.35 0.04 135.33 1.8E+02 9.3E+01 nonconstant variance

polynomial 1 0.23 0.06 0.81 131.04 4.0E+01 2.2E+01 nonconstant variance

power 2 0.23 6.35 0.04 135.33 1.8E+02 9.3E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 2 0.23 3.80 0.15 133.83 9.5E+01 4.3E+01 constant variance, power restricted ≥ 1
exponential (M3) 2 0.23 3.80 0.15 133.83 9.5E+01 4.3E+01 constant variance, power restricted ≥ 1
exponential (M4) 1 0.23 1.06 0.30 133.09 3.0E+01 9.4E+00 constant variance, power restricted ≥ 1
exponential (M5) 0 0.23 0.01 N/A 134.03 2.9E+01 1.2E+01 constant variance, power restricted ≥ 1

Hill c 1 0.23 0.01 0.94 132.03 2.2E+01 1.1E+01 constant variance, n restricted >1, bound hit

linear 2 0.23 4.80 0.09 134.82 1.3E+02 8.1E+01 constant variance

polynomial 1 0.23 0.36 0.55 132.39 3.1E+01 1.8E+01 constant variance

power 2 0.23 4.80 0.09 134.82 1.3E+02 8.1E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-458 E.3.30.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 1

5 10 15 20 25 30 35 40

0 20 40 60 80 100 120 140 160 180Mean Response

dose Hill Model with 0.95 Confidence Level

15:22 10/06 2009 BMD BMDL Hill

2 3 4 

## E.3.30.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_FR5_run_opp.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_FR5_run_opp.plt 12 Tue Oct 06 15:22:42 2009 13

==================================================================== 14 15 Table 3 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter restricted to be greater than 1 27 A constant variance model is fit 28 29 Total number of dose groups = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-459 1 Default Initial Parameter Values 2 alpha = 77.4849 3 rho = 0 Specified 4 intercept = 26.14 5 v = -13.34 6 n = 2.36002 7 k = 35.0654 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -rho -n 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 alpha intercept v k 17 18 alpha 1 -3.6e-009 9.8e-009 3.6e-008 19 20 intercept -3.6e-009 1 -0.81 -0.51 21 22 v 9.8e-009 -0.81 1 0.36 23 24 k 3.6e-008 -0.51 0.36 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 alpha 64.5863 18.6445 28.0438 101.129 33 intercept 26.14 3.03753 20.1865 32.0935 34 v -13.1569 3.7676 -20.5413 -5.77257 35 n 18 NA 36 k 21.5963 2.68136 16.3409 26.8517 37 38 NA - Indicates that this parameter has hit a bound 39 implied by some inequality constraint and thus 40 has no standard error. 41 42 43 44 Table of Data and Estimated Values of Interest 45 46 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 47

------ --- -------- -------- ----------- ----------- ---------- 48 49 0 7 26.1 26.1 12.3 8.04 1.02e-008 50 20 4 23.5 23.5 7.04 8.04 -1.39e-007 51 60 6 12.8 13 6.17 8.04 -0.0558 52 180 7 13.1 13 7.14 8.04 0.0517 53 54 55 56 Model Descriptions for likelihoods calculated 57 58 59 Model A1: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 62 Model A2: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma(i)^2 64 65 Model A3: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 Model A3 uses any fixed variance parameters that 68 were specified by the user 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-460 Model R: Yi = Mu + e(i) 1 Var{e(i)} = Sigma^2 2 3 4 Likelihoods of Interest 5 6 Model Log(likelihood) # Param's AIC 7 A1 -62.013133 5 134.026266 8 A2 -59.839035 8 135.678070 9 A3 -62.013133 5 134.026266 10 fitted -62.016024 4 132.032049 11 R -67.530040 2 139.060081 12 13 14 Explanation of Tests 15 16 Test 1: Do responses and/or variances differ among Dose levels? 17 (A2 vs. R) 18 Test 2: Are Variances Homogeneous? (A1 vs A2) 19 Test 3: Are variances adequately modeled? (A2 vs. A3) 20 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 21 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 22 23 Tests of Interest 24 25 Test -2*log(Likelihood Ratio) Test df p-value 26 27 Test 1 15.382 6 0.01748 28 Test 2 4.3482 3 0.2262 29 Test 3 4.3482 3 0.2262 30 Test 4 0.0057833 1 0.9394 31 32 The p-value for Test 1 is less than .05. There appears to be a 33 difference between response and/or variances among the dose levels 34 It seems appropriate to model the data 35 36 The p-value for Test 2 is greater than .1. A homogeneous variance 37 model appears to be appropriate here 38 39 40 The p-value for Test 3 is greater than .1. The modeled variance appears 41 to be appropriate here 42 43 The p-value for Test 4 is greater than .1. The model chosen seems 44 to adequately describe the data 45 46 47 Benchmark Dose Computation 48 49 Specified effect = 1 50 51 Risk Type = Estimated standard deviations from the control mean 52 53 Confidence level = 0.95 54 55 BMD = 22.144 56 57 BMDL = 11.165 58 59 60 61

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-461 E.3.31. Mietinnin et al. (2006): Caries 1 

## E.3.31.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 3 3.32 0.34 162.70 3.7E+01 2.0E+01 power restricted ≥ 1, bound hit

gamma 3 3.32 0.34 162.70 7.5E+01 4.1E+01 power restricted ≥ 1, bound hit
logistic 3 3.54 0.32 162.91 4.4E+01 2.6E+01

logistic 3 3.54 0.32 162.91 9.0E+01 5.2E+01

log-logistic b 3 2.33 0.51 161.77 1.5E+01 5.0E+00 slope restricted ≥ 1, bound hit
log-logistic 3 2.33 0.51 161.77 3.1E+01 1.1E+01 slope restricted ≥ 1, bound hit
log-probit 2 0.64 0.73 161.99 1.2E-01 error slope restricted ≥ 1

log-probit 2 0.64 0.73 161.99 5.1E-01 error slope restricted ≥ 1
multistage, 2- degree 3 3.32 0.34 162.70 3.7E+01 2.0E+01 betas restricted ≥ 0, bound hit multistage, 2- degree 3 3.32 0.34 162.70 7.5E+01 4.1E+01 betas restricted ≥ 0, bound hit
probit 3 3.67 0.30 163.03 4.9E+01 3.1E+01

probit 3 3.67 0.30 163.03 9.9E+01 6.2E+01

Weibull 3 3.32 0.34 162.70 3.7E+01 2.0E+01 power restricted ≥ 1, bound hit

Weibull 3 3.32 0.34 162.70 7.5E+01 4.1E+01 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-462 E.3.31.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0.4 0.5 0.6 0.7 0.8 0.9

1

0 200 400 600 800 1000Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

15:23 10/06 2009 BMDL BMD Log-Logistic

2 3 4 

## E.3.31.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AniDose\LogLogistic_BMR1_Caries.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\LogLogistic_BMR1_Caries.plt 11 Tue Oct 06 15:23:23 2009 12

==================================================================== 13 14 Table 2 converting the percentage into the number of animals, and control is Control II from the 15 study. Dose is in ng per kg and is from Table 1 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 21 22 23 Dependent variable = DichEff 24 Independent variable = Dose 25 Slope parameter is restricted as slope <= 1 26 27 Total number of observations = 5 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 User has chosen the log transformed model 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-463 1 2 Default Initial Parameter Values 3 background = 0.595238 4 intercept = -5.52519 5 slope = 1 6 7 8 Asymptotic Correlation Matrix of Parameter Estimates 9 10 ( *** The model parameter(s) -slope 11 have been estimated at a boundary point, or have been specified by the user, 12 and do not appear in the correlation matrix ) 13 14 background intercept 15 16 background 1 -0.64 17 18 intercept -0.64 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 background 0.658158 * * * 27 intercept -5.64068 * * * 28 slope 1 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -77.6769 5 38 Fitted model -78.8837 2 2.41374 3 0.4911 39 Reduced model -83.2067 1 11.0597 4 0.0259 40 41 AIC: 161.767 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.6582 27.643 25.000 42 -0.860 49 30.0000 0.6911 20.041 23.000 29 1.189 50 100.0000 0.7477 18.693 19.000 25 0.141 51 300.0000 0.8345 20.027 20.000 24 -0.015 52 1000.0000 0.9249 29.596 29.000 32 -0.400 53 54 Chi^2 = 2.33 d.f. = 3 P-value = 0.5062 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.05 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 14.824 66 67 BMDL = 4.99044 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-464 1 

## E.3.32. National Toxicology Program (198 2): Male Mice, Toxic Hepatitis 2 

## E.3.32.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 1 4.93 0.03 113.10 1.6E+01 5.2E+00 power restricted ≥ 1

logistic b 2 4.76 0.09 110.71 1.8E+01 1.4E+01

log-logistic 1 4.93 0.03 113.09 1.5E+01 6.6E+00 slope restricted ≥ 1

log-probit 1 4.89 0.03 113.11 1.4E+01 7.2E+00 slope restricted ≥ 1
multistage, 2- degree 1 5.18 0.02 112.86 1.2E+01 4.6E+00 betas restricted ≥ 0

probit 2 4.86 0.09 110.70 1.6E+01 1.3E+01

Weibull 1 4.99 0.03 113.06 1.6E+01 4.9E+00 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 4 5 

## E.3.32.2. Figure for Selected Model: Logistic 6

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose Logistic Model with 0.95 Confidence Level

12:25 11/04 2009 BMDL BMD Logistic

7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-465 E.3.32.3. Output file for Selected Model: Logistic 1
2 3

==================================================================== 4 Logistic Model. (Version: 2.12; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\AniDose\Logistic_BMR2_Toxic_hepatitis.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\Logistic_BMR2_Toxic_hepatitis.plt 7 Wed Nov 04 12:25:18 2009 8

==================================================================== 9 10 0 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = 1/[1+EXP(-intercept-slope*dose)] 16 17 18 Dependent variable = DichEff 19 Independent variable = Dose 20 Slope parameter is not restricted 21 22 Total number of observations = 4 23 Total number of records with missing values = 0 24 Maximum number of iterations = 250 25 Relative Function Convergence has been set to: 1e-008 26 Parameter Convergence has been set to: 1e-008 27 28 29 30 Default Initial Parameter Values 31 background = 0 Specified 32 intercept = -3.05581 33 slope = 0.0703319 34 35 36 Asymptotic Correlation Matrix of Parameter Estimates 37 38 ( *** The model parameter(s) -background 39 have been estimated at a boundary point, or have been specified by the user, 40 and do not appear in the correlation matrix ) 41 42 intercept slope 43 44 intercept 1 -0.66 45 46 slope -0.66 1 47 48 49 50 Parameter Estimates 51 52 95.0% Wald Confidence Interval 53 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 54 intercept -3.08708 0.358526 -3.78978 -2.38438 55 slope 0.07156 0.00813416 0.0556174 0.0875027 56 57 58 59 Analysis of Deviance Table 60 61 Model Log(likelihood) # Param's Deviance Test d.f. P-value 62 Full model -51.0633 4 63 Fitted model -53.3562 2 4.58581 2 0.101 64 Reduced model -121.743 1 141.358 3 <.0001 65 66 AIC: 110.712 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-466 Goodness of Fit 1 Scaled 2 Dose Est._Prob. Expected Observed Size Residual 3

------------------------------------------------------------------------ 4 0.0000 0.0436 3.186 1.000 73 -1.252 5 1.4000 0.0480 2.353 5.000 49 1.769 6 7.1000 0.0705 3.455 3.000 49 -0.254 7 71.0000 0.8801 44.007 44.000 50 -0.003 8 9 Chi^2 = 4.76 d.f. = 2 P-value = 0.0925 10 11 12 Benchmark Dose Computation 13 14 Specified effect = 0.1 15 16 Risk Type = Extra risk 17 18 Confidence level = 0.95 19 20 BMD = 17.6885 21 22 BMDL = 13.8272 23 24 25 26 

## E.3.33. National Toxicology Program (2006): Alveolar Metaplasia 27 

## E.3.33.1. Summary Table of BMDS Modeling Results 28

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 34.09 0.00 340.13 2.2E+00 1.8E+00 power restricted ≥ 1, bound hit
logistic 4 45.56 0.00 358.35 5.0E+00 4.1E+00

log-logistic 4 3.98 0.41 312.97 6.6E-01 5.0E-01 slope restricted ≥ 1, bound hit
log-probit b 3 1.31 0.73 312.54 3.3E-01 9.0E-02 slope restricted ≥ 1
multistage, 2- degree 4 34.09 0.00 340.13 2.2E+00 1.8E+00 betas restricted ≥ 0, bound hit
probit 4 46.73 0.00 362.18 5.7E+00 4.8E+00

Weibull 4 34.09 0.00 340.13 2.2E+00 1.8E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 29 30

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-467 E.3.33.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1 1

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

12:26 11/04 2009 BMDLBMD LogProbit

2 3 4 

## E.3.33.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Probit Model. (Version: 3.1; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AniDose\LogProbit_BMR2_Alveolar_metaplasia.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\LogProbit_BMR2_Alveolar_metaplasia.plt 11 Wed Nov 04 12:26:52 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = Background 20 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 21 22 where CumNorm(.) is the cumulative normal distribution function 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 Slope parameter is not restricted 28 29 Total number of observations = 6 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-468 1 User has chosen the log transformed model 2 3 4 Default Initial (and Specified) Parameter Values 5 background = 0.0377358 6 intercept = -0.759264 7 slope = 0.469642 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 background intercept slope 13 14 background 1 -0.24 0.12 15 16 intercept -0.24 1 -0.9 17 18 slope 0.12 -0.9 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 background 0.0374101 0.0259232 -0.0133985 0.0882186 27 intercept -0.761678 0.210613 -1.17447 -0.348885 28 slope 0.471021 0.0755121 0.32302 0.619022 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -152.615 6 36 Fitted model -153.271 3 1.31226 3 0.7262 37 Reduced model -216.802 1 128.374 5 <.0001 38 39 AIC: 312.543 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0374 1.983 2.000 53 0.012 47 2.1400 0.3679 19.868 19.000 54 -0.245 48 7.1400 0.5815 30.819 33.000 53 0.607 49 15.7000 0.7149 37.174 35.000 52 -0.668 50 32.9000 0.8187 43.389 45.000 53 0.574 51 71.4000 0.8981 46.701 46.000 52 -0.321 52 53 Chi^2 = 1.31 d.f. = 3 P-value = 0.7272 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.1 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 0.331636 65 66 BMDL = 0.0896842 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-469 E.3.34. National Toxicology Program (2006): Gi ngival Hyperplasia Squamous, 2 Years 1 

## E.3.34.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 pValue a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 12.82 0.01 318.87 2.3E+01 1.4E+01 power restricted ≥ 1, bound hit
logistic 4 13.78 0.01 320.91 3.6E+01 2.6E+01

log-logistic b 4 12.38 0.01 317.97 1.8E+01 1.0E+01 slope restricted ≥ 1, bound hit
log-logistic c 3 1.53 0.68 307.42 3.7E-01 1.5E-07 slope unrestricted

log-probit 3 1.47 0.69 307.35 4.7E-01 8.9E-07 slope restricted ≥ 1
multistage, 1- degree 4 12.82 0.01 318.87 2.3E+01 1.4E+01 betas restricted ≥ 0, bound hit
probit 4 13.67 0.01 320.69 3.4E+01 2.4E+01

Weibull 4 12.82 0.01 318.87 2.3E+01 1.4E+01 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-470 E.3.34.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.1 0.2 0.3 0.4

0 10 20 30 40 50 60 70Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:44 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.3.34.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\LogLogistic_BMR2_Ging_Hyp_2yr.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogLogistic_BMR2_Ging_Hyp_2yr.plt 11 Sun Nov 29 11:44:28 2009 12

==================================================================== 13 14 [insert study notes] 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is restricted as slope >= 1 25 26 Total number of observations = 6 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-471 Default Initial Parameter Values 1 background = 0.0188679 2 intercept = -4.5509 3 slope = 1 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -slope 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 background intercept 13 14 background 1 -0.71 15 16 intercept -0.71 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 background 0.117717 * * * 25 intercept -5.10866 * * * 26 slope 1 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -149.95 6 36 Fitted model -156.985 2 14.0696 4 0.007076 37 Reduced model -162.631 1 25.3627 5 0.0001186 38 39 AIC: 317.969 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.1177 6.239 1.000 53 -2.233 47 2.1400 0.1290 6.965 7.000 54 0.014 48 7.1400 0.1542 8.174 14.000 53 2.216 49 15.7000 0.1942 10.292 13.000 53 0.940 50 32.9000 0.2641 13.995 15.000 53 0.313 51 71.4000 0.3837 20.335 16.000 53 -1.225 52 53 Chi^2 = 12.38 d.f. = 4 P-value = 0.0147 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.1 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 18.3832 65 66 BMDL = 10.4359 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-472 E.3.34.4. Figure for Unrestricted Model: Log-Logistic, Slope Unrestricted 1

0 0.1 0.2 0.3 0.4

0 10 20 30 40 50 60 70Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:44 11/29 2009 BMDL BMD Log-Logistic

2 3 4 

## E.3.34.5. Output File for Unrestricted Model: Log-Logistic, Slope Unrestricted 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov29\LogLogistic_Unrest_BMR2_Ging_Hyp_2yr.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogLogistic_Unrest_BMR2_Ging_Hyp_2yr.plt 11 Sun Nov 29 11:44:31 2009 12

==================================================================== 13 14 [insert study notes] 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 20 21 22 Dependent variable = DichEff 23 Independent variable = Dose 24 Slope parameter is not restricted 25 26 Total number of observations = 6 27 Total number of records with missing values = 0 28 Maximum number of iterations = 250 29 Relative Function Convergence has been set to: 1e-008 30 Parameter Convergence has been set to: 1e-008 31 32 33 34 User has chosen the log transformed model 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-473 Default Initial Parameter Values 1 background = 0.0188679 2 intercept = -2.04571 3 slope = 0.299277 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 background intercept slope 9 10 background 1 -0.3 0.12 11 12 intercept -0.3 1 -0.91 13 14 slope 0.12 -0.91 1 15 16 17 18 Parameter Estimates 19 20 95.0% Wald Confidence Interval 21 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22 background 0.0185126 * * * 23 intercept -1.93464 * * * 24 slope 0.264795 * * * 25 26 * - Indicates that this value is not calculated. 27 28 29 30 Analysis of Deviance Table 31 32 Model Log(likelihood) # Param's Deviance Test d.f. P-value 33 Full model -149.95 6 34 Fitted model -150.708 3 1.5163 3 0.6785 35 Reduced model -162.631 1 25.3627 5 0.0001186 36 37 AIC: 307.416 38 39 40 Goodness of Fit 41 Scaled 42 Dose Est._Prob. Expected Observed Size Residual 43

------------------------------------------------------------------------ 44 0.0000 0.0185 0.981 1.000 53 0.019 45 2.1400 0.1659 8.959 7.000 54 -0.717 46 7.1400 0.2105 11.155 14.000 53 0.959 47 15.7000 0.2447 12.972 13.000 53 0.009 48 32.9000 0.2806 14.873 15.000 53 0.039 49 71.4000 0.3219 17.059 16.000 53 -0.311 50 51 Chi^2 = 1.53 d.f. = 3 P-value = 0.6750 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.1 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 0.370958 63 64 BMDL = 1.50494e-007 65 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-474 E.3.35. National Toxicology Program ( 2006): Heart, Cardiomyopathy 1 

## E.3.35.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 6.23 0.18 398.01 6.5E+00 4.8E+00 power restricted ≥ 1, bound hit
logistic 4 10.70 0.03 402.78 1.1E+01 9.2E+00

log-logistic b 4 2.42 0.66 394.22 3.7E+00 2.5E+00 slope restricted ≥ 1, bound hit
log-probit 3 0.93 0.82 394.80 2.1E+00 5.1E-01 slope restricted ≥ 1
multistage, 2- degree 4 6.23 0.18 398.01 6.5E+00 4.8E+00 betas restricted ≥ 0, bound hit
probit 4 10.72 0.03 402.80 1.1E+01 9.3E+00

Weibull 4 6.23 0.18 398.01 6.5E+00 4.8E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.3.35.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 5

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 10 20 30 40 50 60 70Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

11:58 11/11 2009 BMDL BMD Log-Logistic

6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-475 E.3.35.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 1
2 3

==================================================================== 4 Logistic Model. (Version: 2.12; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\LogLogistic_BMR2_Cardiomyopathy.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\LogLogistic_BMR2_Cardiomyopathy.plt 7 Wed Nov 11 11:58:41 2009 8

==================================================================== 9 10 0 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 16 17 18 Dependent variable = DichEff 19 Independent variable = Dose 20 Slope parameter is restricted as slope <= 1 21 22 Total number of observations = 6 23 Total number of records with missing values = 0 24 Maximum number of iterations = 250 25 Relative Function Convergence has been set to: 1e-008 26 Parameter Convergence has been set to: 1e-008 27 28 29 30 User has chosen the log transformed model 31 32 33 Default Initial Parameter Values 34 background = 0.188679 35 intercept = -3.47661 36 slope = 1 37 38 39 Asymptotic Correlation Matrix of Parameter Estimates 40 41 ( *** The model parameter(s) -slope 42 have been estimated at a boundary point, or have been specified by the user, 43 and do not appear in the correlation matrix ) 44 45 background intercept 46 47 background 1 -0.65 48 49 intercept -0.65 1 50 51 52 53 Parameter Estimates 54 55 95.0% Wald Confidence Interval 56 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 57 background 0.20346 * * * 58 intercept -3.50681 * * * 59 slope 1 * * * 60 61 * - Indicates that this value is not calculated. 62 63 64 65 Analysis of Deviance Table 66 67 Model Log(likelihood) # Param's Deviance Test d.f. P-value 68 Full model -193.93 6 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-476 Fitted model -195.111 2 2.36161 4 0.6696 1 Reduced model -216.802 1 45.7449 5 <.0001 2 3 AIC: 394.221 4 5 6 Goodness of Fit 7 Scaled 8 Dose Est._Prob. Expected Observed Size Residual 9

------------------------------------------------------------------------ 10 0.0000 0.2035 10.783 10.000 53 -0.267 11 2.1400 0.2515 13.581 12.000 54 -0.496 12 7.1400 0.3440 18.229 22.000 53 1.090 13 15.7000 0.4585 23.840 25.000 52 0.323 14 32.9000 0.5991 31.751 32.000 53 0.070 15 71.4000 0.7464 38.815 36.000 52 -0.897 16 17 Chi^2 = 2.42 d.f. = 4 P-value = 0.6589 18 19 20 Benchmark Dose Computation 21 22 Specified effect = 0.1 23 24 Risk Type = Extra risk 25 26 Confidence level = 0.95 27 28 BMD = 3.70462 29 30 BMDL = 2.50223 31 32 33 34 

## E.3.36. National Toxicology Program (2006 ): Hepatocyte Hypertrophy, 2 Years 35 

## E.3.36.1. Summary Table of BMDS Modeling Results 36

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 26.48 0.00 290.37 1.6E+00 1.3E+00 power restricted ≥ 1, bound hit
logistic 4 35.54 0.00 310.49 4.3E+00 3.6E+00

log-logistic b 5 15.18 0.01 278.08 7.0E-01 5.5E-01 slope restricted ≥ 1, bound hit
log-probit 4 14.46 0.01 279.20 7.2E-01 3.3E-01 slope restricted ≥ 1
multistage, 2- degree 4 26.48 0.00 290.37 1.6E+00 1.3E+00 betas restricted ≥ 0, bound hit
probit 4 41.23 0.00 313.84 4.6E+00 3.9E+00

Weibull 4 26.48 0.00 290.37 1.6E+00 1.3E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 37 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-477 E.3.36.2. Figure for Selected Model: L og-Logistic, Slope Restricted ≥ 1, Bound Hit 1

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

18:49 10/06 2009 BMDLBMD Log-Logistic

2 3 4 

## E.3.36.3. Output File for Selected Model: Log-Logistic, Slope Restricted ≥ 1, Bound Hit 5
6 7

==================================================================== 8 Logistic Model. (Version: 2.12; Date: 05/16/2008) 9 Input Data File: 10 C:\USEPA\BMDS21\AniDose\LogLogistic_BMR2_Hepatocyte_hypertrophy_2years.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\AniDose\LogLogistic_BMR2_Hepatocyte_hypertrophy_2years.plt 13 Tue Oct 06 18:49:36 2009 14

==================================================================== 15 16 [insert study notes] 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the probability function is: 20 21 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 22 23 24 Dependent variable = DichEff 25 Independent variable = Dose 26 Slope parameter is restricted as slope <= 1 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-478 User has chosen the log transformed model 1 2 3 Default Initial Parameter Values 4 background = 0 5 intercept = -2.2119 6 slope = 1.23746 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -background -slope 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 intercept 16 17 intercept 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 background 0 * * * 26 intercept -1.83737 * * * 27 slope 1 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -129.986 6 37 Fitted model -138.041 1 16.1104 5 0.006536 38 Reduced model -219.97 1 179.968 5 <.0001 39 40 AIC: 278.082 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0000 0.000 0.000 53 0.000 48 2.1400 0.2542 13.724 19.000 54 1.649 49 7.1400 0.5320 28.198 19.000 53 -2.532 50 15.7000 0.7143 37.857 42.000 53 1.260 51 32.9000 0.8397 44.505 41.000 53 -1.312 52 71.4000 0.9192 48.715 52.000 53 1.655 53 54 Chi^2 = 15.18 d.f. = 5 P-value = 0.0096 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.1 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 0.697776 66 67 BMDL = 0.545416 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-479 1 

## E.3.37. National Toxicology Program (2006): Li ver, E osinophilic Focus, Multiple 2 

## E.3.37.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 4.30 0.37 330.46 5.7E+00 4.5E+00 power restricted ≥ 1, bound hit
logistic 4 6.46 0.17 333.34 1.3E+01 1.1E+01

log-logistic 3 5.90 0.12 334.15 4.7E+00 2.9E+00 slope restricted ≥ 1

log-probit 3 6.58 0.09 334.85 4.8E+00 1.8E+00 slope restricted ≥ 1
multistage, 2- degree 3 4.18 0.24 332.36 6.2E+00 4.5E+00 betas restricted ≥ 0

probit 4 6.16 0.19 332.96 1.2E+01 1.0E+01

Weibull b 4 4.30 0.37 330.46 5.7E+00 4.5E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 4 5 

## E.3.37.2. Figure for Selected Model: Weibull, Power Restricted ≥ 1, Bound Hit 6

0 0.2 0.4 0.6 0.8

0 10 20 30 40 50 60 70Fraction Affected

dose Weibull Model with 0.95 Confidence Level

11:44 11/11 2009 BMDL BMD Weibull

7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-480 E.3.37.3. Output File for Selected Model: Weibull, Power Restricted ≥ 1, Bound Hit 1
2 3

==================================================================== 4 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\Weibull_BMR2_liver_eosin_focus.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Weibull_BMR2_liver_eosin_focus.plt 7 Wed Nov 11 11:44:27 2009 8

==================================================================== 9 10 0 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 16 17 18 Dependent variable = DichEff 19 Independent variable = Dose 20 Power parameter is restricted as power >=1 21 22 Total number of observations = 6 23 Total number of records with missing values = 0 24 Maximum number of iterations = 250 25 Relative Function Convergence has been set to: 1e-008 26 Parameter Convergence has been set to: 1e-008 27 28 29 30 Default Initial (and Specified) Parameter Values 31 Background = 0.0648148 32 Slope = 0.00246576 33 Power = 1.49873 34 35 36 Asymptotic Correlation Matrix of Parameter Estimates 37 38 ( *** The model parameter(s) -Power 39 have been estimated at a boundary point, or have been specified by the user, 40 and do not appear in the correlation matrix ) 41 42 Background Slope 43 44 Background 1 -0.49 45 46 Slope -0.49 1 47 48 49 50 Parameter Estimates 51 52 95.0% Wald Confidence Interval 53 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 54 Background 0.0893152 0.0297295 0.0310464 0.147584 55 Slope 0.0185641 0.00270697 0.0132586 0.0238697 56 Power 1 NA 57 58 NA - Indicates that this parameter has hit a bound 59 implied by some inequality constraint and thus 60 has no standard error. 61 62 63 64 Analysis of Deviance Table 65 66 Model Log(likelihood) # Param's Deviance Test d.f. P-value 67 Full model -161.07 6 68 Fitted model -163.229 2 4.31726 4 0.3648 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-481 Reduced model -202.816 1 83.4925 5 <.0001 1 2 AIC: 330.457 3 4 5 Goodness of Fit 6 Scaled 7 Dose Est._Prob. Expected Observed Size Residual 8

------------------------------------------------------------------------ 9 0.0000 0.0893 4.734 3.000 53 -0.835 10 2.1400 0.1248 6.738 8.000 54 0.520 11 7.1400 0.2024 10.725 14.000 53 1.120 12 15.7000 0.3196 16.937 17.000 53 0.019 13 32.9000 0.5056 26.794 22.000 53 -1.317 14 71.4000 0.7581 40.177 42.000 53 0.585 15 16 Chi^2 = 4.30 d.f. = 4 P-value = 0.3672 17 18 19 Benchmark Dose Computation 20 21 Specified effect = 0.1 22 23 Risk Type = Extra risk 24 25 Confidence level = 0.95 26 27 BMD = 5.67549 28 29 BMDL = 4.5323 30 31 32 33 

## E.3.38. National Toxicology Program (2006): Liver, Fatty Change, Diffuse 34 

## E.3.38.1. Summary Table of BMDS Modeling Results 35

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 2.37 0.67 252.29 4.2E+00 3.2E+00 power restricted ≥ 1

logistic 4 15.06 0.00 269.83 1.1E+01 9.3E+00

log-logistic 4 4.96 0.29 255.08 4.7E+00 3.2E+00 slope restricted ≥ 1

log-probit 4 5.05 0.28 255.26 4.6E+00 3.2E+00 slope restricted ≥ 1
multistage, 2- degree b 4 2.03 0.73 251.93 4.2E+00 3.2E+00 betas restricted ≥ 0

probit 4 14.92 0.00 269.43 1.1E+01 9.1E+00

Weibull 4 2.31 0.68 252.22 4.3E+00 3.2E+00 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-482 E.3.39. Figure for Selected Model: Multis tage, 2-Degree, Betas Restricted ≥ 0 1

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:44 11/11 2009 BMD BMDL Multistage

2 3 4 

## E.3.40. Output File for Selected Model: Mu ltis tage, 2-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Model. (Version: 3.0; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\Multistage_BMR2_liver_fatty_change_diff.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Multistage_BMR2_liver_fatty_change_diff.plt 11 Wed Nov 11 11:44:50 2009 12

==================================================================== 13 14 NTP_liver_fatty_change_diffuse 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 3 31 Total number of specified parameters = 0 32 Degree of polynomial = 2 33 34 35 Maximum number of iterations = 250 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-483 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 Background = 0.02888 7 Beta(1) = 0.0193083 8 Beta(2) = 0.000185869 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) Beta(2) 18 19 Beta(1) 1 -0.89 20 21 Beta(2) -0.89 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 Background 0 * * * 30 Beta(1) 0.0248561 * * * 31 Beta(2) 9.42857e-005 * * * 32 33 * - Indicates that this value is not calculated. 34 35 36 37 Analysis of Deviance Table 38 39 Model Log(likelihood) # Param's Deviance Test d.f. P-value 40 Full model -122.992 6 41 Fitted model -123.966 2 1.94705 4 0.7455 42 Reduced model -204.846 1 163.708 5 <.0001 43 44 AIC: 251.932 45 46 47 Goodness of Fit 48 Scaled 49 Dose Est._Prob. Expected Observed Size Residual 50

------------------------------------------------------------------------ 51 0.0000 0.0000 0.000 0.000 53 0.000 52 2.1400 0.0522 2.819 2.000 54 -0.501 53 7.1400 0.1666 8.831 12.000 53 1.168 54 15.7000 0.3387 17.949 17.000 53 -0.275 55 32.9000 0.6014 31.875 30.000 53 -0.526 56 71.4000 0.8952 47.444 48.000 53 0.249 57 58 Chi^2 = 2.03 d.f. = 4 P-value = 0.7302 59 60 61 Benchmark Dose Computation 62 63 Specified effect = 0.1 64 65 Risk Type = Extra risk 66 67 Confidence level = 0.95 68 69 BMD = 4.17277 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-484 1 BMDL = 3.20452 2 3 BMDU = 5.73352 4 5 Taken together, (3.20452, 5.73352) is a 90 % two-sided confidence 6 interval for the BMD 7 8 9 

## E.3.41. National Toxicology Program (2006): Liver Necrosis 10 

## E.3.41.1. Summary Table of BMDS Modeling Results 11

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 pValue a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 1.85 0.76 235.58 2.0E+01 1.4E+01 power restricted ≥ 1, bound hit
logistic 4 4.07 0.40 238.31 3.5E+01 2.8E+01

log-logistic 4 1.60 0.81 235.27 1.8E+01 1.2E+01 slope restricted ≥ 1, bound hit
log-probit b 3 1.14 0.77 236.74 1.1E+01 3.5E+00 slope restricted ≥ 1
multistage, 2- degree 4 1.85 0.76 235.58 2.0E+01 1.4E+01 betas restricted ≥ 0, bound hit
probit 4 3.72 0.45 237.89 3.3E+01 2.6E+01

Weibull 4 1.85 0.76 235.58 2.0E+01 1.4E+01 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-485 E.3.41.2. Figure for Selected Model: LogProbit 1

2 3 4 

## E.3.41.3. Output File for Selected Model: Log-Probit 5
6

==================================================================== 7 Probit Model. (Version: 3.1; Date: 05/16/2008) 8 Input Data File: C:\USEPA\BMDS21\Nov29\LogProbit_BMR2_liver_necrosis.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov29\LogProbit_BMR2_liver_necrosis.plt 10 Sun Nov 29 12:24:51 2009 11

==================================================================== 12 13 NTP_liver_necrosis 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the probability function is: 17 18 P[response] = Background 19 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 20 21 where CumNorm(.) is the cumulative normal distribution function 22 23 24 Dependent variable = DichEff 25 Independent variable = Dose 26 Slope parameter is not restricted 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 User has chosen the log transformed model 37 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-486 1 Default Initial (and Specified) Parameter Values 2 background = 0.0188679 3 intercept = -1.98094 4 slope = 0.316942 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 background intercept slope 10 11 background 1 -0.69 0.59 12 13 intercept -0.69 1 -0.97 14 15 slope 0.59 -0.97 1 16 17 18 19 Parameter Estimates 20 21 95.0% Wald Confidence Interval 22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23 background 0.0228339 0.0230818 -0.0224057 0.0680734 24 intercept -2.14844 0.527256 -3.18184 -1.11503 25 slope 0.367034 0.139055 0.0944904 0.639577 26 27 28 29 Analysis of Deviance Table 30 31 Model Log(likelihood) # Param's Deviance Test d.f. P-value 32 Full model -114.813 6 33 Fitted model -115.371 3 1.1157 3 0.7733 34 Reduced model -127.98 1 26.3331 5 <.0001 35 36 AIC: 236.742 37 38 39 Goodness of Fit 40 Scaled 41 Dose Est._Prob. Expected Observed Size Residual 42

------------------------------------------------------------------------ 43 0.0000 0.0228 1.210 1.000 53 -0.193 44 2.1400 0.0529 2.858 4.000 54 0.694 45 7.1400 0.0979 5.187 4.000 53 -0.549 46 15.7000 0.1475 7.819 8.000 53 0.070 47 32.9000 0.2116 11.215 10.000 53 -0.409 48 71.4000 0.2968 15.729 17.000 53 0.382 49 50 Chi^2 = 1.14 d.f. = 3 P-value = 0.7678 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 0.1 56 57 Risk Type = Extra risk 58 59 Confidence level = 0.95 60 61 BMD = 10.6107 62 63 BMDL = 3.49791 64 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-487 E.3.42. National Toxicology Program ( 2006): Liver, P igmentation 1 

## E.3.42.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 3 3.05 0.38 197.66 1.5E+00 8.1E-01 power restricted ≥ 1

logistic 4 29.12 0.00 203.52 2.3E+00 1.9E+00

log-logistic 3 0.19 0.98 195.60 2.2E+00 1.5E+00 slope restricted ≥ 1

log-probit b 3 0.18 0.98 195.45 2.1E+00 1.4E+00 slope restricted ≥ 1
multistage, 2- degree 3 4.53 0.21 199.85 9.4E-01 7.1E-01 betas restricted ≥ 0

probit 4 131.22 0.00 210.31 2.3E+00 1.9E+00

Weibull 3 3.75 0.29 198.49 1.3E+00 7.5E-01 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.3.42.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1 5

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

11:59 11/11 2009 BMDL BMD LogProbit

6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-488 E.3.42.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1 1
2 3

==================================================================== 4 Probit Model. (Version: 3.1; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\LogProbit_BMR2_Pigmentation.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\LogProbit_BMR2_Pigmentation.plt 7 Wed Nov 11 11:59:31 2009 8

==================================================================== 9 10 0 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = Background 16 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 17 18 where CumNorm(.) is the cumulative normal distribution function 19 20 21 Dependent variable = DichEff 22 Independent variable = Dose 23 Slope parameter is not restricted 24 25 Total number of observations = 6 26 Total number of records with missing values = 0 27 Maximum number of iterations = 250 28 Relative Function Convergence has been set to: 1e-008 29 Parameter Convergence has been set to: 1e-008 30 31 32 33 User has chosen the log transformed model 34 35 36 Default Initial (and Specified) Parameter Values 37 background = 0.0754717 38 intercept = -1.91144 39 slope = 1.07385 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 background intercept slope 45 46 background 1 -0.45 0.35 47 48 intercept -0.45 1 -0.94 49 50 slope 0.35 -0.94 1 51 52 53 54 Parameter Estimates 55 56 95.0% Wald Confidence Interval 57 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 58 background 0.0735956 0.0343284 0.00631316 0.140878 59 intercept -2.19294 0.400053 -2.97703 -1.40885 60 slope 1.25068 0.169731 0.918012 1.58335 61 62 63 64 Analysis of Deviance Table 65 66 Model Log(likelihood) # Param's Deviance Test d.f. P-value 67 Full model -94.6177 6 68 Fitted model -94.7248 3 0.214232 3 0.9753 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-489 Reduced model -210.717 1 232.198 5 <.0001 1 2 AIC: 195.45 3 4 5 Goodness of Fit 6 Scaled 7 Dose Est._Prob. Expected Observed Size Residual 8

------------------------------------------------------------------------ 9 0.0000 0.0736 3.901 4.000 53 0.052 10 2.1400 0.1729 9.338 9.000 54 -0.122 11 7.1400 0.6338 33.591 34.000 53 0.117 12 15.7000 0.9023 47.822 48.000 53 0.082 13 32.9000 0.9863 52.275 52.000 53 -0.325 14 71.4000 0.9992 52.959 53.000 53 0.202 15 16 Chi^2 = 0.18 d.f. = 3 P-value = 0.9801 17 18 19 Benchmark Dose Computation 20 21 Specified effect = 0.1 22 23 Risk Type = Extra risk 24 25 Confidence level = 0.95 26 27 BMD = 2.07241 28 29 BMDL = 1.39932 30 31 32 33 

## E.3.43. National Toxicology Program (2006): Lun g, Alveolar to Bronchiolar Epithelial 34 

## Metaplasia (Alveolar Epithelium, Metaplasia, Bronchiolar) 35 

## E.3.43.1. Summary Table of BMDS Modeling Results 36

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 4 34.09 0.00 340.13 2.2E+00 1.8E+00 power restricted ≥ 1, bound hit
logistic 4 45.56 0.00 358.35 5.0E+00 4.1E+00

log-logistic 4 3.98 0.41 312.97 6.6E-01 5.0E-01 slope restricted ≥ 1, bound hit
log-probit b 3 1.31 0.73 312.54 3.3E-01 9.0E-02 slope restricted ≥ 1
multistage, 2- degree 4 34.09 0.00 340.13 2.2E+00 1.8E+00 betas restricted ≥ 0, bound hit
probit 4 46.73 0.00 362.18 5.7E+00 4.8E+00

Weibull 4 34.09 0.00 340.13 2.2E+00 1.8E+00 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-490 E.3.43.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1 1

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

12:00 11/11 2009 BMDLBMD LogProbit

2 3 4 

## E.3.43.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Probit Model. (Version: 3.1; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AD\LogProbit_BMR2_Alv_bronch_epith_metapl.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\LogProbit_BMR2_Alv_bronch_epith_metapl.plt 11 Wed Nov 11 12:00:22 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = Background 20 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 21 22 where CumNorm(.) is the cumulative normal distribution function 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 Slope parameter is not restricted 28 29 Total number of observations = 6 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-491 1 User has chosen the log transformed model 2 3 4 Default Initial (and Specified) Parameter Values 5 background = 0.0377358 6 intercept = -0.759264 7 slope = 0.469642 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 background intercept slope 13 14 background 1 -0.24 0.12 15 16 intercept -0.24 1 -0.9 17 18 slope 0.12 -0.9 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 background 0.0374101 0.0259232 -0.0133985 0.0882186 27 intercept -0.761678 0.210613 -1.17447 -0.348885 28 slope 0.471021 0.0755121 0.32302 0.619022 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -152.615 6 36 Fitted model -153.271 3 1.31226 3 0.7262 37 Reduced model -216.802 1 128.374 5 <.0001 38 39 AIC: 312.543 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0374 1.983 2.000 53 0.012 47 2.1400 0.3679 19.868 19.000 54 -0.245 48 7.1400 0.5815 30.819 33.000 53 0.607 49 15.7000 0.7149 37.174 35.000 52 -0.668 50 32.9000 0.8187 43.389 45.000 53 0.574 51 71.4000 0.8981 46.701 46.000 52 -0.321 52 53 Chi^2 = 1.31 d.f. = 3 P-value = 0.7272 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.1 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 0.331636 65 66 BMDL = 0.0896842 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-492 E.3.44. National Toxicology Program (2006 ): Oval Cell Hyperp lasia, 2 Years 1 

## E.3.44.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 3 7.00 0.07 199.45 9.0E+00 5.5E+00 power restricted ≥ 1

logistic 4 8.72 0.07 199.88 9.8E+00 8.2E+00

log-logistic 3 8.38 0.04 202.01 9.7E+00 7.2E+00 slope restricted ≥ 1

log-probit 3 7.12 0.07 200.42 1.0E+01 7.8E+00 slope restricted ≥ 1
multistage, 2- degree b 4 6.33 0.18 195.33 5.8E+00 4.0E+00 betas restricted ≥ 0

probit 4 7.50 0.11 198.17 9.1E+00 7.7E+00

Weibull 3 6.92 0.07 198.69 7.7E+00 4.7E+00 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.3.44.2. Figure for Selected Model: Multis tage, 2-Degree, Betas Restricted ≥ 0 5

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:59 11/11 2009 BMD BMDL Multistage

6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-493 E.3.44.3. Output File for Selected Model: Multistage, 2-Degree, Betas Restricted ≥ 0 1
2 3

==================================================================== 4 Multistage Model. (Version: 3.0; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\AD\Multistage_BMR2_Oval_cell_hyperplasia.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Multistage_BMR2_Oval_cell_hyperplasia.plt 7 Wed Nov 11 11:59:06 2009 8

==================================================================== 9 10 0 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background + (1-background)*[1-EXP( 16 -beta1*dose^1-beta2*dose^2)] 17 18 The parameter betas are restricted to be positive 19 20 21 Dependent variable = DichEff 22 Independent variable = Dose 23 24 Total number of observations = 6 25 Total number of records with missing values = 0 26 Total number of parameters in model = 3 27 Total number of specified parameters = 0 28 Degree of polynomial = 2 29 30 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 Background = 0 39 Beta(1) = 0 40 Beta(2) = 1.98687e+016 41 42 43 Asymptotic Correlation Matrix of Parameter Estimates 44 45 ( *** The model parameter(s) -Background 46 have been estimated at a boundary point, or have been specified by the user, 47 and do not appear in the correlation matrix ) 48 49 Beta(1) Beta(2) 50 51 Beta(1) 1 -0.89 52 53 Beta(2) -0.89 1 54 55 56 57 Parameter Estimates 58 59 95.0% Wald Confidence Interval 60 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 61 Background 0 * * * 62 Beta(1) 0.0133632 * * * 63 Beta(2) 0.00083535 * * * 64 65 * - Indicates that this value is not calculated. 66 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-494 Analysis of Deviance Table 1 2 Model Log(likelihood) # Param's Deviance Test d.f. P-value 3 Full model -92.4898 6 4 Fitted model -95.6669 2 6.35417 4 0.1742 5 Reduced model -210.191 1 235.402 5 <.0001 6 7 AIC: 195.334 8 9 10 Goodness of Fit 11 Scaled 12 Dose Est._Prob. Expected Observed Size Residual 13

------------------------------------------------------------------------ 14 0.0000 0.0000 0.000 0.000 53 0.000 15 2.1400 0.0319 1.723 4.000 54 1.763 16 7.1400 0.1289 6.832 3.000 53 -1.571 17 15.7000 0.3401 18.027 20.000 53 0.572 18 32.9000 0.7392 39.175 38.000 53 -0.368 19 71.4000 0.9946 52.711 53.000 53 0.539 20 21 Chi^2 = 6.33 d.f. = 4 P-value = 0.1759 22 23 24 Benchmark Dose Computation 25 26 Specified effect = 0.1 27 28 Risk Type = Extra risk 29 30 Confidence level = 0.95 31 32 BMD = 5.78926 33 34 BMDL = 4.04553 35 36 BMDU = 9.63861 37 38 Taken together, (4.04553, 9.63861) is a 90 % two-sided confidence 39 interval for the BMD 40 41 42 

## E.3.45. National Toxicology Program (2006): Toxic Hepatopathy 43 

## E.3.45.1. Summary Table of BMDS Modeling Results 44

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma b 4 1.80 0.77 185.63 4.7E+00 3.3E+00 power restricted ≥ 1

logistic 4 12.79 0.01 198.45 7.1E+00 5.9E+00

log-logistic 3 3.20 0.36 190.06 5.7E+00 4.0E+00 slope restricted ≥ 1

log-probit 3 3.09 0.38 189.86 6.1E+00 4.1E+00 slope restricted ≥ 1
multistage, 2- degree 4 2.89 0.58 186.52 4.2E+00 2.7E+00 betas restricted ≥ 0
multistage, 2- degree 4 2.89 0.58 186.52 4.2E+00 2.7E+00 betas unrestricted

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-495 Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

multistage, 1- degree 5 10.28 0.07 194.94 2.1E+00 1.8E+00 betas unrestricted

probit 4 11.78 0.02 197.16 6.8E+00 5.7E+00

Weibull c 4 1.95 0.75 185.66 4.5E+00 3.2E+00 power restricted ≥ 1

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded

c Alternate model also presented in this appendix 1 2 

## E.3.45.2. Figure for Selected Model: Gamma, Power Restricted ≥ 1 3

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

16:49 11/20 2009 BMDL BMD Gamma Multi-Hit

4 5 6 

## E.3.45.3. Output file for Selected M odel: Gamma, Power Restricted ≥ 1 7
8 9

==================================================================== 10 Gamma Model. (Version: 2.13; Date: 05/16/2008) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Gamma_BMR2_Toxic_hepatopathy.(d) 12 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Gamma_BMR2_Toxic_hepatopathy.plt 13 Fri Nov 20 16:49:26 2009 14

==================================================================== 15 16 0 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-496 1 The form of the probability function is: 2 3 P[response]= background+(1-background)*CumGamma[slope*dose,power], 4 where CumGamma(.) is the cummulative Gamma distribution function 5 6 7 Dependent variable = DichEff 8 Independent variable = Dose 9 Power parameter is restricted as power >=1 10 11 Total number of observations = 6 12 Total number of records with missing values = 0 13 Maximum number of iterations = 250 14 Relative Function Convergence has been set to: 1e-008 15 Parameter Convergence has been set to: 1e-008 16 17 18 19 Default Initial (and Specified) Parameter Values 20 Background = 0.00925926 21 Slope = 0.0683125 22 Power = 1.3 23 24 25 Asymptotic Correlation Matrix of Parameter Estimates 26 27 ( *** The model parameter(s) -Background 28 have been estimated at a boundary point, or have been specified by the user, 29 and do not appear in the correlation matrix ) 30 31 Slope Power 32 33 Slope 1 0.94 34 35 Power 0.94 1 36 37 38 39 Parameter Estimates 40 41 95.0% Wald Confidence Interval 42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 43 Background 0 NA 44 Slope 0.105412 0.0237428 0.0588765 0.151947 45 Power 1.92239 0.361359 1.21414 2.63064 46 47 NA - Indicates that this parameter has hit a bound 48 implied by some inequality constraint and thus 49 has no standard error. 50 51 52 53 Analysis of Deviance Table 54 55 Model Log(likelihood) # Param's Deviance Test d.f. P-value 56 Full model -89.8076 6 57 Fitted model -90.8168 2 2.01832 4 0.7324 58 Reduced model -218.207 1 256.799 5 <.0001 59 60 AIC: 185.634 61 62 63 Goodness of Fit 64 Scaled 65 Dose Est._Prob. Expected Observed Size Residual 66

------------------------------------------------------------------------ 67 0.0000 0.0000 0.000 0.000 53 0.000 68 2.1400 0.0265 1.429 2.000 54 0.484 69 7.1400 0.1926 10.205 8.000 53 -0.768 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-497 15.7000 0.5170 27.403 30.000 53 0.714 1 32.9000 0.8723 46.232 45.000 53 -0.507 2 71.4000 0.9960 52.788 53.000 53 0.462 3 4 Chi^2 = 1.80 d.f. = 4 P-value = 0.7716 5 6 7 Benchmark Dose Computation 8 9 Specified effect = 0.1 10 11 Risk Type = Extra risk 12 13 Confidence level = 0.95 14 15 BMD = 4.66805 16 17 BMDL = 3.31743 18 19 20 21 

## E.3.45.4. Figure for Unrestricted Model: Weibull, Power Restricted ≥ 1 22

0 0.2 0.4 0.6 0.8

1

0 10 20 30 40 50 60 70Fraction Affected

dose Weibull Model with 0.95 Confidence Level

16:49 11/20 2009 BMDL BMD Weibull

23 24 25 

## E.3.45.5. Output File for Unrestricted M odel: Weibull, Po wer Restricted ≥ 1 26
27 28

==================================================================== 29 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 30 Input Data File: C:\USEPA\BMDS21\Nov20\Weibull_BMR2_Toxic_hepatopathy.(d) 31 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Weibull_BMR2_Toxic_hepatopathy.plt 32 Fri Nov 20 16:49:32 2009 33

==================================================================== 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-498 0 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2 3 The form of the probability function is: 4 5 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 6 7 8 Dependent variable = DichEff 9 Independent variable = Dose 10 Power parameter is restricted as power >=1 11 12 Total number of observations = 6 13 Total number of records with missing values = 0 14 Maximum number of iterations = 250 15 Relative Function Convergence has been set to: 1e-008 16 Parameter Convergence has been set to: 1e-008 17 18 19 20 Default Initial (and Specified) Parameter Values 21 Background = 0.00925926 22 Slope = 0.0286401 23 Power = 1.19362 24 25 26 Asymptotic Correlation Matrix of Parameter Estimates 27 28 ( *** The model parameter(s) -Background 29 have been estimated at a boundary point, or have been specified by the user, 30 and do not appear in the correlation matrix ) 31 32 Slope Power 33 34 Slope 1 -0.97 35 36 Power -0.97 1 37 38 39 40 Parameter Estimates 41 42 95.0% Wald Confidence Interval 43 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 44 Background 0 NA 45 Slope 0.0113696 0.00592954 -0.000252127 0.0229912 46 Power 1.4905 0.169532 1.15823 1.82278 47 48 NA - Indicates that this parameter has hit a bound 49 implied by some inequality constraint and thus 50 has no standard error. 51 52 53 54 Analysis of Deviance Table 55 56 Model Log(likelihood) # Param's Deviance Test d.f. P-value 57 Full model -89.8076 6 58 Fitted model -90.8285 2 2.04181 4 0.7281 59 Reduced model -218.207 1 256.799 5 <.0001 60 61 AIC: 185.657 62 63 64 Goodness of Fit 65 Scaled 66 Dose Est._Prob. Expected Observed Size Residual 67

------------------------------------------------------------------------ 68 0.0000 0.0000 0.000 0.000 53 0.000 69 2.1400 0.0347 1.875 2.000 54 0.093 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-499 7.1400 0.1918 10.164 8.000 53 -0.755 1 15.7000 0.4979 26.391 30.000 53 0.992 2 32.9000 0.8745 46.349 45.000 53 -0.559 3 71.4000 0.9986 52.927 53.000 53 0.270 4 5 Chi^2 = 1.95 d.f. = 4 P-value = 0.7454 6 7 8 Benchmark Dose Computation 9 10 Specified effect = 0.1 11 12 Risk Type = Extra risk 13 14 Confidence level = 0.95 15 16 BMD = 4.4538 17 18 BMDL = 3.15886 19 20 21 22 

## E.3.46. Ohsako et al. (2001): Anogenital PND120 23 

## E.3.46.1. Summary Table of BMDS Modeling Results 24

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 0.46 5.02 0.17 185.44 7.5E+02 4.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.46 5.02 0.17 185.44 7.5E+02 4.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 2 0.46 4.29 0.12 186.72 4.8E+02 1.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.46 4.29 0.12 186.72 4.8E+02 1.1E+01 nonconstant variance, power restricted ≥ 1

Hill 2 0.46 3.11 0.21 185.54 7.1E+01 1.3E+01 nonconstant variance, n restricted >1, bound hit

linear 3 0.46 5.09 0.17 185.52 7.6E+02 5.1E+02 nonconstant variance

polynomial 2 0.46 4.45 0.11 186.88 4.8E+02 1.5E+02 nonconstant variance

power 3 0.46 5.09 0.17 185.52 7.6E+02 5.1E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 3 0.46 7.00 0.07 185.90 6.5E+02 4.2E+02 constant variance, power restricted ≥ 1
exponential (M3) 3 0.46 7.00 0.07 185.90 6.5E+02 4.2E+02 constant variance, power restricted ≥ 1
exponential (M4) 2 0.46 3.17 0.20 184.07 4.1E+01 1.2E+01 constant variance, power restricted ≥ 1
exponential (M5) 1 0.46 2.84 0.09 185.74 3.8E+01 1.3E+01 constant variance, power restricted ≥ 1

Hill c 2 0.46 2.74 0.25 183.64 6.0E+01 1.2E+01 constant variance, n restricted >1, bound

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-500 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

hit

linear 3 0.46 7.12 0.07 186.02 6.6E+02 4.4E+02 constant variance

polynomial 2 0.46 5.55 0.06 186.45 2.7E+02 1.3E+02 constant variance

power 3 0.46 7.12 0.07 186.02 6.6E+02 4.4E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 1 2 

## E.3.46.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 3

22 24 26 28 30 32

0 100 200 300 400 500 600 700 800Mean Response

dose Hill Model with 0.95 Confidence Level

18:59 10/06 2009 BMD BMDL Hill

4 5 6 

## E.3.46.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 7 

## Hit 8
9 10

==================================================================== 11 Hill Model. (Version: 2.14; Date: 06/26/2008) 12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-501 Input Data File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_Anogenital_PND120.(d) 1 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_Anogenital_PND120.plt 2 Tue Oct 06 18:59:02 2009 3

==================================================================== 4 5 Figure 7 6

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 7 8 The form of the response function is: 9 10 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 11 12 13 Dependent variable = Mean 14 Independent variable = Dose 15 rho is set to 0 16 Power parameter restricted to be greater than 1 17 A constant variance model is fit 18 19 Total number of dose groups = 5 20 Total number of records with missing values = 0 21 Maximum number of iterations = 250 22 Relative Function Convergence has been set to: 1e-008 23 Parameter Convergence has been set to: 1e-008 24 25 26 27 Default Initial Parameter Values 28 alpha = 9.96434 29 rho = 0 Specified 30 intercept = 28.9146 31 v = -5.04512 32 n = 1.44913 33 k = 35.3408 34 35 36 Asymptotic Correlation Matrix of Parameter Estimates 37 38 ( *** The model parameter(s) -rho -n 39 have been estimated at a boundary point, or have been specified by the user, 40 and do not appear in the correlation matrix ) 41 42 alpha intercept v k 43 44 alpha 1 -4.2e-009 -3.6e-008 2.3e-008 45 46 intercept -4.2e-009 1 -0.63 -0.52 47 48 v -3.6e-008 -0.63 1 -0.13 49 50 k 2.3e-008 -0.52 -0.13 1 51 52 53 54 Parameter Estimates 55 56 95.0% Wald Confidence Interval 57 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 58 alpha 9.51224 1.83063 5.92427 13.1002 59 intercept 28.9963 0.861586 27.3077 30.685 60 v -4.77893 1.14548 -7.02403 -2.53384 61 n 1 NA 62 k 33.2115 32.41 -30.3109 96.7338 63 64 NA - Indicates that this parameter has hit a bound 65 implied by some inequality constraint and thus 66 has no standard error. 67 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-502 Table of Data and Estimated Values of Interest 1 2 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 3

------ --- -------- -------- ----------- ----------- ---------- 4 5 0 12 28.9 29 3.54 3.08 -0.0918 6 12.5 10 28.1 27.7 2.52 3.08 0.399 7 50 10 25.3 26.1 3.59 3.08 -0.836 8 200 10 26.1 24.9 3.59 3.08 1.2 9 800 12 23.9 24.4 2.36 3.08 -0.605 10 11 12 13 Model Descriptions for likelihoods calculated 14 15 16 Model A1: Yij = Mu(i) + e(ij) 17 Var{e(ij)} = Sigma^2 18 19 Model A2: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = Sigma(i)^2 21 22 Model A3: Yij = Mu(i) + e(ij) 23 Var{e(ij)} = Sigma^2 24 Model A3 uses any fixed variance parameters that 25 were specified by the user 26 27 Model R: Yi = Mu + e(i) 28 Var{e(i)} = Sigma^2 29 30 31 Likelihoods of Interest 32 33 Model Log(likelihood) # Param's AIC 34 A1 -86.449919 6 184.899838 35 A2 -84.654549 10 189.309098 36 A3 -86.449919 6 184.899838 37 fitted -87.819648 4 183.639297 38 R -95.473923 2 194.947846 39 40 41 Explanation of Tests 42 43 Test 1: Do responses and/or variances differ among Dose levels? 44 (A2 vs. R) 45 Test 2: Are Variances Homogeneous? (A1 vs A2) 46 Test 3: Are variances adequately modeled? (A2 vs. A3) 47 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 48 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 49 50 Tests of Interest 51 52 Test -2*log(Likelihood Ratio) Test df p-value 53 54 Test 1 21.6387 8 0.005631 55 Test 2 3.59074 4 0.4642 56 Test 3 3.59074 4 0.4642 57 Test 4 2.73946 2 0.2542 58 59 The p-value for Test 1 is less than .05. There appears to be a 60 difference between response and/or variances among the dose levels 61 It seems appropriate to model the data 62 63 The p-value for Test 2 is greater than .1. A homogeneous variance 64 model appears to be appropriate here 65 66 67 The p-value for Test 3 is greater than .1. The modeled variance appears 68 to be appropriate here 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-503 The p-value for Test 4 is greater than .1. The model chosen seems 1 to adequately describe the data 2 3 4 Benchmark Dose Computation 5 6 Specified effect = 1 7 Risk Type = Estimated standard deviations from the control mean 8 Confidence level = 0.95 9 BMD = 60.4402 10 BMDL = 12.1546 11 12 13 14 

## E.3.47. Schantz et al. (1996): Maze Errors Per Block, Female 15 

## E.3.47.1. Summary Table of BMDS Modeling Results 16

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear 1 0.71 3.25 0.07 20.63 6.7E+01 3.8E+01 nonconstant variance

polynomial 1 0.71 3.25 0.07 20.63 6.7E+01 3.8E+01 nonconstant variance

power 1 0.71 3.25 0.07 20.63 6.7E+01 3.8E+01 nonconstant variance, power restricted ≥ 1, bound hit

linear c 1 0.71 2.77 0.10 18.72 7.1E+01 4.6E+01 constant variance

polynomial 1 0.71 2.77 0.10 18.72 7.1E+01 4.6E+01 constant variance

power 1 0.71 2.77 0.10 18.72 7.1E+01 4.6E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 17 18

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-504 E.3.47.2. Figure for Selected Model: Linear, Constant Variance 1

2 2.5

3 3.5

4

0 20 40 60 80 100Mean Response

dose Linear Model with 0.95 Confidence Level

13:40 11/11 2009 BMD BMDL Linear

2 3 4 

## E.3.47.3. Output File for Selected Mode l: L inear, Constant Variance 5
6

==================================================================== 7 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 8 Input Data File: C:\USEPA\BMDS21\AD\LinearConstVar_BMR4_maze_errors.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\LinearConstVar_BMR4_maze_errors.plt 10 Wed Nov 11 13:40:58 2009 11

==================================================================== 12 13 Rel Male Thymus wt, Tbl 2 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the response function is: 17 18 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 rho is set to 0 24 Signs of the polynomial coefficients are not restricted 25 A constant variance model is fit 26 27 Total number of dose groups = 3 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-505 alpha = 0.569565 1 rho = 0 Specified 2 beta_0 = 3.32773 3 beta_1 = -0.0105912 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 ( *** The model parameter(s) -rho 9 have been estimated at a boundary point, or have been specified by the user, 10 and do not appear in the correlation matrix ) 11 12 alpha beta_0 beta_1 13 14 alpha 1 1.3e-010 3.9e-011 15 16 beta_0 1.3e-010 1 -0.7 17 18 beta_1 3.9e-011 -0.7 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 alpha 0.562168 0.145151 0.277677 0.846659 27 beta_0 3.32773 0.191722 2.95196 3.7035 28 beta_1 -0.0105912 0.00322157 -0.0169054 -0.00427705 29 30 31 32 Table of Data and Estimated Values of Interest 33 34 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 35

------ --- -------- -------- ----------- ----------- ---------- 36 37 0 10 3.55 3.33 0.639 0.75 0.957 38 25 10 2.76 3.06 0.806 0.75 -1.28 39 100 10 2.34 2.27 0.806 0.75 0.319 40 41 42 43 Model Descriptions for likelihoods calculated 44 45 46 Model A1: Yij = Mu(i) + e(ij) 47 Var{e(ij)} = Sigma^2 48 49 Model A2: Yij = Mu(i) + e(ij) 50 Var{e(ij)} = Sigma(i)^2 51 52 Model A3: Yij = Mu(i) + e(ij) 53 Var{e(ij)} = Sigma^2 54 Model A3 uses any fixed variance parameters that 55 were specified by the user 56 57 Model R: Yi = Mu + e(i) 58 Var{e(i)} = Sigma^2 59 60 61 Likelihoods of Interest 62 63 Model Log(likelihood) # Param's AIC 64 A1 -4.976366 4 17.952732 65 A2 -4.638353 6 21.276707 66 A3 -4.976366 4 17.952732 67 fitted -6.360686 3 18.721371 68 R -10.975997 2 25.951993 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-506 1 Explanation of Tests 2 3 Test 1: Do responses and/or variances differ among Dose levels? 4 (A2 vs. R) 5 Test 2: Are Variances Homogeneous? (A1 vs A2) 6 Test 3: Are variances adequately modeled? (A2 vs. A3) 7 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 8 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 9 10 Tests of Interest 11 12 Test -2*log(Likelihood Ratio) Test df p-value 13 14 Test 1 12.6753 4 0.01298 15 Test 2 0.676025 2 0.7132 16 Test 3 0.676025 2 0.7132 17 Test 4 2.76864 1 0.09613 18 19 The p-value for Test 1 is less than .05. There appears to be a 20 difference between response and/or variances among the dose levels 21 It seems appropriate to model the data 22 23 The p-value for Test 2 is greater than .1. A homogeneous variance 24 model appears to be appropriate here 25 26 27 The p-value for Test 3 is greater than .1. The modeled variance appears 28 to be appropriate here 29 30 The p-value for Test 4 is less than .1. You may want to try a different 31 model 32 33 34 Benchmark Dose Computation 35 36 Specified effect = 1 37 38 Risk Type = Estimated standard deviations from the control mean 39 40 Confidence level = 0.95 41 42 BMD = 70.7926 43 44 45 BMDL = 45.8305 46 47 48

49 

## E.3.48. Shi et al. (2007): Estradiol 50 

## E.3.48.1. Summary Table of BMDS Modeling Results 51

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 3 0.05 15.48 0.00 395.70 1.7E+01 9.0E+00 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.05 15.48 0.00 395.70 1.7E+01 9.0E+00 nonconstant variance, power restricted ≥ 1 exponential (M4)

c 2 0.05 1.41 0.49 383.64 5.6E-01 2.2E-01 nonconstant variance, power restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-507 exponential (M5) 2 0.05 1.41 0.49 383.64 5.6E-01 2.2E-01 nonconstant variance, power restricted ≥ 1

Hill 2 0.05 0.52 0.77 382.74 4.4E-01 error nonconstant variance, n restricted >1, bound hit

linear 3 0.05 17.26 0.00 397.48 2.2E+01 1.5E+01 nonconstant variance

polynomial 2 0.05 7.34 0.03 389.57 5.4E+00 3.6E+00 nonconstant variance

power 3 0.05 17.26 0.00 397.48 2.2E+01 1.5E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 3 0.05 13.33 0.00 396.06 1.2E+01 6.6E+00 constant variance, power restricted ≥ 1
exponential (M3) 3 0.05 13.33 0.00 396.06 1.2E+01 6.6E+00 constant variance, power restricted ≥ 1
exponential (M4) 2 0.05 0.87 0.65 385.59 3.9E-01 1.5E-01 constant variance, power restricted ≥ 1
exponential (M5) 2 0.05 0.87 0.65 385.59 3.9E-01 1.5E-01 constant variance, power restricted ≥ 1

Hill 2 0.05 0.37 0.83 385.09 3.1E-01 1.0E-01 constant variance, n restricted >1, bound hit

linear 3 0.05 15.40 0.00 398.12 1.9E+01 1.3E+01 constant variance

polynomial 2 0.05 8.10 0.02 392.82 4.5E+00 2.9E+00 constant variance

power 3 0.05 15.40 0.00 398.12 1.9E+01 1.3E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-508 E.3.48.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

20 40 60 80 100 120 140

0 5 10 15 20 25 30Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

19:13 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.48.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\Exp_BMR1_Shi_estradiol_17B_conc_PE9.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 19:13:28 2009 14

==================================================================== 15 16 Figure 4 PE9 only 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-509 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 5 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 4 17

-------- -------- 18 lnalpha 2.65881 19 rho 0.913414 20 a 108 21 b 0.136287 22 c 0.340136 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 4 30

-------- ------- 31 lnalpha 1.81331 32 rho 1.12126 33 a 100.526 34 b 1.53823 35 c 0.431796 36 d 1 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 10 102.9 41.41 44 0.143 10 86.19 19.58 45 0.714 10 63.33 29.36 46 7.14 10 48.1 18.82 47 28.6 10 38.57 22.59 48 49 50 Estimated Values of Interest 51 52 Dose Est Mean Est Std Scaled Residual 53

------ ---------- --------- ---------------- 54 0 100.5 32.83 0.2245 55 0.143 89.25 30.71 -0.3147 56 0.714 62.45 25.14 0.1108 57 7.14 43.41 20.5 0.723 58 28.6 43.41 20.5 -0.7458 59 60 61 62 Other models for which likelihoods are calculated: 63 64 Model A1: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma^2 66 67 Model A2: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma(i)^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-510 Model A3: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 2 3 Model R: Yij = Mu + e(i) 4 Var{e(ij)} = Sigma^2 5 6 7 Likelihoods of Interest 8 9 Model Log(likelihood) DF AIC 10

------- ----------------- ---- ------------ 11 A1 -188.3615 6 388.7231 12 A2 -183.667 10 387.3339 13 A3 -186.1132 7 386.2263 14 R -203.3606 2 410.7211 15 4 -186.8176 5 383.6352 16 17 18 Additive constant for all log-likelihoods = -45.95. This constant added to the 19 above values gives the log-likelihood including the term that does not 20 depend on the model parameters. 21 22 23 Explanation of Tests 24 25 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 26 Test 2: Are Variances Homogeneous? (A2 vs. A1) 27 Test 3: Are variances adequately modeled? (A2 vs. A3) 28 29 Test 6a: Does Model 4 fit the data? (A3 vs 4) 30 31 32 Tests of Interest 33 34 Test -2*log(Likelihood Ratio) D. F. p-value 35

-------- ------------------------ ------ -------------- 36 Test 1 39.39 8 < 0.0001 37 Test 2 9.389 4 0.05208 38 Test 3 4.892 3 0.1798 39 Test 6a 1.409 2 0.4944 40 41 42 The p-value for Test 1 is less than .05. There appears to be a 43 difference between response and/or variances among the dose 44 levels, it seems appropriate to model the data. 45 46 The p-value for Test 2 is less than .1. A non-homogeneous 47 variance model appears to be appropriate. 48 49 The p-value for Test 3 is greater than .1. The modeled 50 variance appears to be appropriate here. 51 52 The p-value for Test 6a is greater than .1. Model 4 seems 53 to adequately describe the data. 54 55 56 Benchmark Dose Computations: 57 58 Specified Effect = 1.000000 59 60 Risk Type = Estimated standard deviations from control 61 62 Confidence Level = 0.950000 63 64 BMD = 0.555948 65 66 BMDL = 0.223612 67 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-511 E.3.49. Smialowicz et al. (2008): PFC per 10^6 Cells 1 

## E.3.49.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) c 3 <0.0001 11.58 0.01 890.56 1.1E+02 7.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 2 <0.0001 10.85 0.00 891.83 1.3E+02 7.6E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 11.58 0.01 890.56 1.1E+02 7.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 10.85 0.00 891.83 1.3E+02 7.6E+01 nonconstant variance, power restricted ≥ 1

Hill 2 <.0001 10.26 0.01 891.23 1.3E+02 error nonconstant variance, n restricted >1, bound hit

linear 3 <.0001 11.79 0.01 890.77 1.8E+02 1.5E+02 nonconstant variance

polynomial 2 <.0001 10.36 0.01 891.34 1.3E+02 8.4E+01 nonconstant variance

power 3 <.0001 11.79 0.01 890.77 1.8E+02 1.5E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 3 <0.0001 7.92 0.05 903.59 8.2E+01 4.8E+01 constant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 7.92 0.05 903.59 8.2E+01 4.8E+01 constant variance, power restricted ≥ 1
exponential (M4) 2 <0.0001 7.91 0.02 905.58 8.0E+01 6.2E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 7.91 0.02 905.58 8.0E+01 6.2E+00 constant variance, power restricted ≥ 1

Hill 2 <.0001 7.31 0.03 904.98 1.6E+01 2.2E+00 constant variance, n restricted >1, bound hit

linear 3 <.0001 10.33 0.02 905.99 1.5E+02 1.1E+02 constant variance

polynomial 2 <.0001 8.14 0.02 905.80 8.8E+01 5.5E+01 constant variance

power 3 <.0001 10.33 0.02 905.99 1.5E+02 1.1E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-512 E.3.49.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

0 500 1000 1500 2000

0 50 100 150 200 250 300Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

19:14 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.49.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\Exp_BMR1_PFC_per_cells.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 19:14:43 2009 14

==================================================================== 15 16 Anti Response to SRBCs, PFC per 10^6 cells, Table 4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-513 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 5 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 2 17

-------- -------- 18 lnalpha 3.29848 19 rho 1.2578 20 a 1565.55 21 b 0.00725727 22 c 0.00205679 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 2 30

-------- ------- 31 lnalpha 1.84544 32 rho 1.53651 33 a 1195.73 34 b 0.00560912 35 c 0 36 d 1.22053 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 15 1491 716 44 1.07 14 1129 171 45 10.7 15 945 516 46 107 15 677 465 47 321 8 161 117 48 49 50 Estimated Values of Interest 51 52 Dose Est Mean Est Std Scaled Residual 53

------ ---------- --------- ---------------- 54 0 1232 593.6 1.688 55 1.07 1224 590.7 -0.6027 56 10.7 1153 565 -1.428 57 107 635.7 362 0.442 58 321 169.2 134.6 -0.1716 59 60 61 62 Other models for which likelihoods are calculated: 63 64 Model A1: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma^2 66 67 Model A2: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma(i)^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-514 Model A3: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 2 3 Model R: Yij = Mu + e(i) 4 Var{e(ij)} = Sigma^2 5 6 7 Likelihoods of Interest 8 9 Model Log(likelihood) DF AIC 10

------- ----------------- ---- ------------ 11 A1 -444.8329 6 901.6657 12 A2 -425.4028 10 870.8057 13 A3 -435.4894 7 884.9787 14 R -463.7537 2 931.5074 15 2 -441.2778 4 890.5555 16 17 18 Additive constant for all log-likelihoods = -61.57. This constant added to the 19 above values gives the log-likelihood including the term that does not 20 depend on the model parameters. 21 22 23 Explanation of Tests 24 25 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 26 Test 2: Are Variances Homogeneous? (A2 vs. A1) 27 Test 3: Are variances adequately modeled? (A2 vs. A3) 28 Test 4: Does Model 2 fit the data? (A3 vs. 2) 29 30 31 Tests of Interest 32 33 Test -2*log(Likelihood Ratio) D. F. p-value 34

-------- ------------------------ ------ -------------- 35 Test 1 76.7 8 < 0.0001 36 Test 2 38.86 4 < 0.0001 37 Test 3 20.17 3 0.0001563 38 Test 4 11.58 3 0.008983 39 40 41 The p-value for Test 1 is less than .05. There appears to be a 42 difference between response and/or variances among the dose 43 levels, it seems appropriate to model the data. 44 45 The p-value for Test 2 is less than .1. A non-homogeneous 46 variance model appears to be appropriate. 47 48 The p-value for Test 3 is less than .1. You may want to 49 consider a different variance model. 50 51 The p-value for Test 4 is less than .1. Model 2 may not adequately 52 describe the data; you may want to consider another model. 53 54 55 Benchmark Dose Computations: 56 57 Specified Effect = 1.000000 58 59 Risk Type = Estimated standard deviations from control 60 61 Confidence Level = 0.950000 62 63 BMD = 106.252 64 65 BMDL = 71.9153 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-515 E.3.50. Smialowicz et al. (2008): PFC per Spleen 1 

## E.3.50.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) c 3 0.00 5.60 0.13 377.40 1.3E+02 8.4E+01 nonconstant variance, power restricted ≥ 1 exponential (M3) 3 0.00 5.60 0.13 377.40 1.3E+02 8.4E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.00 5.60 0.13 377.40 1.3E+02 8.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.00 5.60 0.06 379.40 1.3E+02 8.2E+01 nonconstant variance, power restricted ≥ 1

Hill 2 0.00 5.35 0.07 379.15 1.4E+02 error nonconstant variance, n restricted >1, bound hit

linear 3 0.00 8.09 0.04 379.89 2.2E+02 1.7E+02 nonconstant variance

polynomial 2 0.00 5.58 0.06 379.38 1.4E+02 8.9E+01 nonconstant variance

power 3 0.00 8.09 0.04 379.89 2.2E+02 1.7E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 3 0.00 5.58 0.13 392.71 1.0E+02 5.5E+01 constant variance, power restricted ≥ 1
exponential (M3) 3 0.00 5.58 0.13 392.71 1.0E+02 5.5E+01 constant variance, power restricted ≥ 1
exponential (M4) 2 0.00 5.58 0.06 394.71 1.0E+02 6.5E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.00 5.58 0.06 394.71 1.0E+02 6.5E+00 constant variance, power restricted ≥ 1

Hill 2 0.00 5.36 0.07 394.49 8.4E+01 1.7E+00 constant variance, n restricted >1, bound hit

linear 3 0.00 7.31 0.06 394.44 1.7E+02 1.3E+02 constant variance

polynomial 2 0.00 5.74 0.06 394.87 1.1E+02 6.3E+01 constant variance

power 3 0.00 7.31 0.06 394.44 1.7E+02 1.3E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-516 E.3.50.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 1 

## Restricted ≥ 1 2

0 5 10 15 20 25 30 35

0 50 100 150 200 250 300Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

19:15 10/06 2009 BMD BMDL Exponential

3 4 5 

## E.3.50.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 6 

## Restricted ≥ 1 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\AniDose\Exp_BMR1_PFC_per_spleen.(d) 12 Gnuplot Plotting File: 13 Tue Oct 06 19:15:26 2009 14

==================================================================== 15 16 Anti Response to SRBCs - PFC x 10 to the 4 per spleen, Table 4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-517 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 4 5 Total number of dose groups = 5 6 Total number of records with missing values = 0 7 Maximum number of iterations = 250 8 Relative Function Convergence has been set to: 1e-008 9 Parameter Convergence has been set to: 1e-008 10 11 MLE solution provided: Exact 12 13 14 Initial Parameter Values 15 16 Variable Model 2 17

-------- -------- 18 lnalpha 0.786146 19 rho 1.36372 20 a 29.19 21 b 0.00907371 22 c 0.0513875 23 d 1 24 25 26 27 Parameter Estimates 28 29 Variable Model 2 30

-------- ------- 31 lnalpha 0.525138 32 rho 1.45988 33 a 22.9464 34 b 0.00618274 35 c 0 36 d 1 37 38 39 Table of Stats From Input Data 40 41 Dose N Obs Mean Obs Std Dev 42

----- --- ---------- ------------- 43 0 15 27.8 13.4 44 1.07 14 21 13.6 45 10.7 15 17.6 9.4 46 107 15 12.6 8.7 47 321 8 3 3.1 48 49 50 Estimated Values of Interest 51 52 Dose Est Mean Est Std Scaled Residual 53

------ ---------- --------- ---------------- 54 0 22.95 12.8 1.468 55 1.07 22.8 12.74 -0.5272 56 10.7 21.48 12.2 -1.231 57 107 11.84 7.899 0.3719 58 321 3.153 3.007 -0.1444 59 60 61 62 Other models for which likelihoods are calculated: 63 64 Model A1: Yij = Mu(i) + e(ij) 65 Var{e(ij)} = Sigma^2 66 67 Model A2: Yij = Mu(i) + e(ij) 68 Var{e(ij)} = Sigma(i)^2 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-518 Model A3: Yij = Mu(i) + e(ij) 1 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 2 3 Model R: Yij = Mu + e(i) 4 Var{e(ij)} = Sigma^2 5 6 7 Likelihoods of Interest 8 9 Model Log(likelihood) DF AIC 10

------- ----------------- ---- ------------ 11 A1 -190.565 6 393.13 12 A2 -181.4763 10 382.9526 13 A3 -181.9 7 377.8001 14 R -204.6365 2 413.273 15 2 -184.6977 4 377.3954 16 17 18 Additive constant for all log-likelihoods = -61.57. This constant added to the 19 above values gives the log-likelihood including the term that does not 20 depend on the model parameters. 21 22 23 Explanation of Tests 24 25 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 26 Test 2: Are Variances Homogeneous? (A2 vs. A1) 27 Test 3: Are variances adequately modeled? (A2 vs. A3) 28 Test 4: Does Model 2 fit the data? (A3 vs. 2) 29 30 31 Tests of Interest 32 33 Test -2*log(Likelihood Ratio) D. F. p-value 34

-------- ------------------------ ------ -------------- 35 Test 1 46.32 8 < 0.0001 36 Test 2 18.18 4 0.001139 37 Test 3 0.8475 3 0.8381 38 Test 4 5.595 3 0.133 39 40 41 The p-value for Test 1 is less than .05. There appears to be a 42 difference between response and/or variances among the dose 43 levels, it seems appropriate to model the data. 44 45 The p-value for Test 2 is less than .1. A non-homogeneous 46 variance model appears to be appropriate. 47 48 The p-value for Test 3 is greater than .1. The modeled 49 variance appears to be appropriate here. 50 51 The p-value for Test 4 is greater than .1. Model 2 seems 52 to adequately describe the data. 53 54 55 Benchmark Dose Computations: 56 57 Specified Effect = 1.000000 58 59 Risk Type = Estimated standard deviations from control 60 61 Confidence Level = 0.950000 62 63 BMD = 132.016 64 65 BMDL = 84.3108 66 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-519 E.3.51. Toth et al. (1978): Amyloidosis 1 

## E.3.51.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

multistage, 1- degree b 1 0.00 1.00 33.16 8.7E-01 4.5E-01 betas restricted ≥ 0

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 3 4 

## E.3.51.2. Figure for Selected Model: Multis tage, 1-Degree, Betas Restricted ≥ 0 5

0 0.05 0.1 0.15 0.2 0.25

0 0.2 0.4 0.6 0.8 1Fraction Affected

dose Multistage Model with 0.95 Confidence Level

19:21 10/06 2009 BMD BMDL Multistage

6 7 8 

## E.3.51.3. Output File for Selected Model: Multistage, 1-Degree, Betas Restricted ≥ 0 9
10 11

==================================================================== 12 Multistage Model. (Version: 3.0; Date: 05/16/2008) 13 Input Data File: C:\USEPA\BMDS21\AniDose\mult2_0.1_amyloidosis_1yr.(d) 14 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\mult2_0.1_amyloidosis_1yr.plt 15 Tue Oct 06 19:21:03 2009 16

==================================================================== 17 18 Table 2 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 20 21 The form of the probability function is: 22 23

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-520 P[response] = background + (1-background)*[1-EXP( 1 -beta1*dose^1)] 2 3 The parameter betas are restricted to be positive 4 5 6 Dependent variable = DichEff 7 Independent variable = Dose 8 9 Total number of observations = 2 10 Total number of records with missing values = 0 11 Total number of parameters in model = 2 12 Total number of specified parameters = 0 13 Degree of polynomial = 1 14 15 16 Maximum number of iterations = 250 17 Relative Function Convergence has been set to: 1e-008 18 Parameter Convergence has been set to: 1e-008 19 20 21 22 Default Initial Parameter Values 23 Background = 0 24 Beta(1) = 0.120628 25 26 27 Asymptotic Correlation Matrix of Parameter Estimates 28 29 ( *** The model parameter(s) -Background 30 have been estimated at a boundary point, or have been specified by the user, 31 and do not appear in the correlation matrix ) 32 33 Beta(1) 34 35 Beta(1) 1 36 37 38 39 Parameter Estimates 40 41 95.0% Wald Confidence Interval 42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 43 Background 0 * * * 44 Beta(1) 0.120628 * * * 45 46 * - Indicates that this value is not calculated. 47 48 49 50 Analysis of Deviance Table 51 52 Model Log(likelihood) # Param's Deviance Test d.f. P-value 53 Full model -15.5783 2 54 Fitted model -15.5783 1 1.42109e-014 1 1 55 Reduced model -18.8308 1 6.50504 1 0.01076 56 57 AIC: 33.1565 58 59 60 Goodness of Fit 61 Scaled 62 Dose Est._Prob. Expected Observed Size Residual 63

------------------------------------------------------------------------ 64 0.0000 0.0000 0.000 0.000 38 0.000 65 1.0000 0.1136 5.000 5.000 44 -0.000 66 67 Chi^2 = 0.00 d.f. = 1 P-value = 1.0000 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-521 Benchmark Dose Computation 1 2 Specified effect = 0.1 3 4 Risk Type = Extra risk 5 6 Confidence level = 0.95 7 8 BMD = 0.873433 9 10 BMDL = 0.453242 11 12 BMDU = 2.10749 13 14 Taken together, (0.453242, 2.10749) is a 90 % two-sided confidence 15 interval for the BMD 16 17 18 19 

## E.3.52. Toth et al. (1978): Skin Lesions 20 

## E.3.52.1. Summary Table of BMDS Modeling Results 21

Model Degrees of Freedom 

## χ 2 Test Statistic 

## χ 2 

## p

Value a AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

gamma 2 9.35 0.01 159.22 1.2E+02 8.3E+01 power restricted ≥ 1, bound hit
logistic 2 12.19 0.00 162.97 2.7E+02 2.1E+02

log-logistic 2 7.10 0.03 156.57 6.7E+01 4.1E+01 slope restricted ≥ 1, bound hit
log-probit b 2 1.17 0.56 148.22 1.1E+00 6.8E-02 slope restricted ≥ 1
multistage, 2- degree 2 9.35 0.01 159.22 1.2E+02 8.3E+01 betas restricted ≥ 0, bound hit
probit 2 11.98 0.00 162.68 2.5E+02 2.0E+02

Weibull 2 9.35 0.01 159.22 1.2E+02 8.3E+01 power restricted ≥ 1, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria

b Best-fitting model as assessed by lowest-AIC criterion, bolded 22 23

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-522 E.3.52.2. Figure for Selected Model: Log-Probit, Slope Restricted ≥ 1 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 200 400 600 800 1000Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

19:21 10/06 2009 BMDLBMD LogProbit

2 3 4 

## E.3.52.3. Output File for Selected Model: Log-Probit, Slope Restricted ≥ 1 5
6 7

==================================================================== 8 Probit Model. (Version: 3.1; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\AniDose\LogProbit_BMR2_Skin_lesion_1yr.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\LogProbit_BMR2_Skin_lesion_1yr.plt 11 Tue Oct 06 19:21:47 2009 12

==================================================================== 13 14 Table 2 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = Background 20 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 21 22 where CumNorm(.) is the cumulative normal distribution function 23 24 25 Dependent variable = DichEff 26 Independent variable = Dose 27 Slope parameter is not restricted 28 29 Total number of observations = 4 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-523 1 User has chosen the log transformed model 2 3 4 Default Initial (and Specified) Parameter Values 5 background = 0 6 intercept = -1.26532 7 slope = 0.195762 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -background 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 intercept slope 17 18 intercept 1 -0.87 19 20 slope -0.87 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 background 0 NA 29 intercept -1.30013 0.240943 -1.77237 -0.827887 30 slope 0.202414 0.0463497 0.111571 0.293258 31 32 NA - Indicates that this parameter has hit a bound 33 implied by some inequality constraint and thus 34 has no standard error. 35 36 37 38 Analysis of Deviance Table 39 40 Model Log(likelihood) # Param's Deviance Test d.f. P-value 41 Full model -71.5177 4 42 Fitted model -72.1089 2 1.18249 2 0.5536 43 Reduced model -95.8498 1 48.6642 3 <.0001 44 45 AIC: 148.218 46 47 48 Goodness of Fit 49 Scaled 50 Dose Est._Prob. Expected Observed Size Residual 51

------------------------------------------------------------------------ 52 0.0000 0.0000 0.000 0.000 38 0.000 53 1.0000 0.0968 4.258 5.000 44 0.378 54 100.0000 0.3564 15.684 13.000 44 -0.845 55 1000.0000 0.5391 23.180 25.000 43 0.557 56 57 Chi^2 = 1.17 d.f. = 2 P-value = 0.5581 58 59 60 Benchmark Dose Computation 61 62 Specified effect = 0.1 63 64 Risk Type = Extra risk 65 66 Confidence level = 0.95 67 68 BMD = 1.09611 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-524 BMDL = 0.0684731 1 2 3 

## E.3.53. Van Birgelen et al. (1995a): Hepatic Retinol 4 

## E.3.53.1. Summary Table of BMDS Modeling Results 5

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 4 <0.0001 45.69 <0.0001 164.34 2.9E+02 error nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 45.69 <0.0001 164.34 2.9E+02 error nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 27.40 <0.0001 148.05 1.2E+02 7.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 27.40 <0.0001 148.05 1.2E+02 7.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 <0.0001 27.40 <0.0001 148.05 1.2E+02 7.1E+01 nonconstant variance, power unrestricted

Hill 3 <.0001 8.11 0.04 128.76 1.3E+01 error nonconstant variance, n restricted >1, bound hit

Hill d 2 <.0001 2.62 0.27 125.27 5.6E+00 error nonconstant variance, n unrestricted

linear 4 <.0001 60.09 <.0001 178.73 7.8E+02 6.0E+02 nonconstant variance

polynomial 4 <.0001 60.09 <.0001 178.73 7.8E+02 6.0E+02 nonconstant variance

power 4 <.0001 60.09 <.0001 178.73 7.8E+02 6.0E+02 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 9.34 0.03 129.99 4.2E-01 8.5E-03 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 141.80 <0.0001 322.09 error error constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 141.80 <0.0001 322.09 error error constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 2.71 0.44 185.03 1.2E+01 7.0E+00 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 2.71 0.44 185.03 1.2E+01 7.0E+00 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 2.71 0.44 185.03 1.2E+01 7.0E+00 constant variance, power unrestricted

Hill 3 <.0001 1.37 0.71 183.68 8.3E+00 4.2E+00 constant variance, n restricted >1, bound hit

Hill 2 <.0001 0.89 0.64 185.20 4.5E+00 5.8E-02 constant variance, n unrestricted

linear 4 <.0001 27.00 <.0001 207.31 5.3E+02 3.9E+02 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-525 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

polynomial 4 <.0001 27.00 <.0001 207.31 5.3E+02 3.9E+02 constant variance

power 4 <.0001 27.00 <.0001 207.31 5.3E+02 3.9E+02 constant variance, power restricted ≥ 1, bound hit

power 3 <.0001 1.92 0.59 184.23 4.4E-01 6.6E-03 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.3.53.2. Figure for Selected Model: Exponentia l (M4), N onconstant Variance, Power 3 

## Restricted ≥ 1 4

0 5 10 15 20

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:29 11/20 2009 BMD BMDL Exponential

5 6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-526 E.3.53.3. Output File for Selected Model: Expone ntial (M4), Nonconstant Varian ce, Power 1 

## Restricted ≥ 1 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_hepatic_retinol.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 14:29:52 2009 9

==================================================================== 10 11 Tbl3, hepatic retinol 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 34 35 Total number of dose groups = 6 36 Total number of records with missing values = 0 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39 Parameter Convergence has been set to: 1e-008 40 41 MLE solution provided: Exact 42 43 44 Initial Parameter Values 45 46 Variable Model 4 47

-------- -------- 48 lnalpha -1.16065 49 rho 1.53688 50 a 15.645 51 b 0.00625117 52 c 0.0365247 53 d 1 54 55 56 57 Parameter Estimates 58 59 Variable Model 4 60

-------- ------- 61 lnalpha -0.882224 62 rho 1.82707 63 a 10.5294 64 b 0.00720346 65 c 0.068866 66 d 1 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-527 1 Table of Stats From Input Data 2 3 Dose N Obs Mean Obs Std Dev 4

----- --- ---------- ------------- 5 0 8 14.9 8.768 6 14 8 8.4 3.394 7 26 8 8.2 2.263 8 47 8 5.1 0.8485 9 320 8 2.2 0.8485 10 1024 8 0.6 0.5657 11 12 13 Estimated Values of Interest 14 15 Dose Est Mean Est Std Scaled Residual 16

------ ---------- --------- ---------------- 17 0 10.53 5.526 2.237 18 14 9.589 5.073 -0.6628 19 26 8.855 4.717 -0.3926 20 47 7.714 4.159 -1.778 21 320 1.703 1.046 1.343 22 1024 0.7313 0.4833 -0.7681 23 24 25 26 Other models for which likelihoods are calculated: 27 28 Model A1: Yij = Mu(i) + e(ij) 29 Var{e(ij)} = Sigma^2 30 31 Model A2: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = Sigma(i)^2 33 34 Model A3: Yij = Mu(i) + e(ij) 35 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 36 37 Model R: Yij = Mu + e(i) 38 Var{e(ij)} = Sigma^2 39 40 41 Likelihoods of Interest 42 43 Model Log(likelihood) DF AIC 44

------- ----------------- ---- ------------ 45 A1 -87.1567 7 188.3134 46 A2 -47.28742 12 118.5748 47 A3 -55.32422 8 126.6484 48 R -109.967 2 223.934 49 4 -69.02619 5 148.0524 50 51 52 Additive constant for all log-likelihoods = -44.11. This constant added to the 53 above values gives the log-likelihood including the term that does not 54 depend on the model parameters. 55 56 57 Explanation of Tests 58 59 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 60 Test 2: Are Variances Homogeneous? (A2 vs. A1) 61 Test 3: Are variances adequately modeled? (A2 vs. A3) 62 63 Test 6a: Does Model 4 fit the data? (A3 vs 4) 64 65 66 Tests of Interest 67 68 Test -2*log(Likelihood Ratio) D. F. p-value 69

-------- ------------------------ ------ -------------- 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-528 Test 1 125.4 10 < 0.0001 1 Test 2 79.74 5 < 0.0001 2 Test 3 16.07 4 0.002922 3 Test 6a 27.4 3 < 0.0001 4 5 6 The p-value for Test 1 is less than .05. There appears to be a 7 difference between response and/or variances among the dose 8 levels, it seems appropriate to model the data. 9 10 The p-value for Test 2 is less than .1. A non-homogeneous 11 variance model appears to be appropriate. 12 13 The p-value for Test 3 is less than .1. You may want to 14 consider a different variance model. 15 16 The p-value for Test 6a is less than .1. Model 4 may not adequately 17 describe the data; you may want to consider another model. 18 19 20 Benchmark Dose Computations: 21 22 Specified Effect = 1.000000 23 24 Risk Type = Estimated standard deviations from control 25 26 Confidence Level = 0.950000 27 28 BMD = 115.128 29 30 BMDL = 70.981 31 32 33 

## E.3.53.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 34 

## Unrestricted 35

0 5 10 15 20

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:30 11/20 2009 BMD BMDL Exponential

36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-529 E.3.53.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 1 

## Power Unrestricted 2
3 4

==================================================================== 5 Exponential Model. (V ersion: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\ Nov20\Exp_Unrest_BMR1_he patic_retinol.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 14:30:05 2009 9

==================================================================== 10 11 Tbl3, hepatic retinol 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 The variance is to be modeled as Va r(i) = exp(lalpha + log(mean(i)) * rho) 34 35 Total number of dose groups = 6 36 Total number of records with missing values = 0 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39 Parameter Convergence has been set to: 1e-008 40 41 MLE solution provided: Exact 42 43 44 Initial Parameter Values 45 46 Variable Model 5 47

-------- -------- 48 lnalpha -1.16065 49 rho 1.53688 50 a 15.645 51 b 0.00625117 52 c 0.0365247 53 d 1 54 55 56 57 Parameter Estimates 58 59 Variable Model 5 60

-------- ------- 61 lnalpha -0.882224 62 rho 1.82707 63 a 10.5294 64 b 0.00720346 65 c 0.068866 66 d 1 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-530 1 2 Table of Stats From Input Data 3 4 Dose N Obs Mean Obs Std Dev 5

----- --- ---------- ------------- 6 0 8 14.9 8.768 7 14 8 8.4 3.394 8 26 8 8.2 2.263 9 47 8 5.1 0.8485 10 320 8 2.2 0.8485 11 1024 8 0.6 0.5657 12 13 14 Estimated Values of Interest 15 16 Dose Est Mean Est Std Scaled Residual 17

------ ---------- --------- ---------------- 18 0 10.53 5.526 2.237 19 14 9.589 5.073 -0.6628 20 26 8.855 4.717 -0.3926 21 47 7.714 4.159 -1.778 22 320 1.703 1.046 1.343 23 1024 0.7313 0.4833 -0.7681 24 25 26 27 Other models for which likelihoods are calculated: 28 29 Model A1: Yij = Mu(i) + e(ij) 30 Var{e(ij)} = Sigma^2 31 32 Model A2: Yij = Mu(i) + e(ij) 33 Var{e(ij)} = Sigma(i)^2 34 35 Model A3: Yij = Mu(i) + e(ij) 36 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 37 38 Model R: Yij = Mu + e(i) 39 Var{e(ij)} = Sigma^2 40 41 42 Likelihoods of Interest 43 44 Model Log(likelihood) DF AIC 45

------- ----------------- ---- ------------ 46 A1 -87.1567 7 188.3134 47 A2 -47.28742 12 118.5748 48 A3 -55.32422 8 126.6484 49 R -109.967 2 223.934 50 5 -69.02619 5 148.0524 51 52 53 Additive constant for all log-likelihoods = -44.11. This constant added to the 54 above values gives the log-like lihood including the term that does not 55 depend on the model parameters. 56 57 58 Explanation of Tests 59 60 Test 1: Does response and/or vari ances differ among Dose levels? (A2 vs. R) 61 Test 2: Are Variances Homogeneous? (A2 vs. A1) 62 Test 3: Are variances adequately modeled? (A2 vs. A3) 63 64 Test 7a: Does Model 5 fit the data? (A3 vs 5) 65 66 67 Tests of Interest 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-531 Test -2*log(Likelihood Ratio) D. F. p-value 1

-------- ------------------------ ------ -------------- 2 Test 1 125.4 10 < 0.0001 3 Test 2 79.74 5 < 0.0001 4 Test 3 16.07 4 0.002922 5 Test 7a 27.4 3 < 0.0001 6 7 8 The p-value for Test 1 is le ss than .05. There appears to be a 9 difference between response and/or variances among the dose 10 levels, it seems appropriate to model the data. 11 12 The p-value for Test 2 is less than .1. A non-homogeneous 13 variance model appears to be appropriate. 14 15 The p-value for Test 3 is less than .1. You may want to 16 consider a different variance model. 17 18 The p-value for Test 7a is le ss than .1. Model 5 may not adequately 19 describe the data; you may want to consider another model. 20 21 22 Benchmark Dose Computations: 23 24 Specified Effect = 1.000000 25 26 Risk Type = Esti mated standard devia tions from control 27 28 Confidence Level = 0.950000 29 30 BMD = 115.128 31 32 BMDL = 70.981 33 34 35 

## E.3.53.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 36

0 5 10 15 20

0 200 400 600 800 1000Mean Response

dose Hill Model

14:30 11/20 2009 BMD Hill

37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-532 E.3.53.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 1
2 3

==================================================================== 4 Hill Model. (Versi on: 2.14; Date: 06/26/2008) 5 Input Data File: C:\USEPA\BMDS21\ Nov20\Hill_Unrest_BMR1_he patic_retinol.(d) 6 Gnuplot Plotting File: C:\USEPA\B MDS21\Nov20\Hill_Unrest_B MR1_hepatic_retinol.plt 7 Fri Nov 20 14:30:12 2009 8

==================================================================== 9 10 Tbl3, hepatic retinol 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the response function is: 14 15 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 16 17 18 Dependent variable = Mean 19 Independent variable = Dose 20 Power parameter is not restricted 21 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 22 23 Total number of dose groups = 6 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 30 31 Default Initial Parameter Values 32 lalpha = 2.76506 33 rho = 0 34 intercept = 14.9 35 v = -14.3 36 n = 2.92354 37 k = 29.0484 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 41 42 lalpha rho intercept v n k 43 44 lalpha 1 -0.78 -0.041 0.015 0.037 0.029 45 46 rho -0.78 1 -0.098 0.11 -0.047 -0.046 47 48 intercept -0.041 -0.098 1 -0.9 -0.25 -0.8 49 50 v 0.015 0.11 -0.9 1 0.63 0.63 51 52 n 0.037 -0.047 -0.25 0.63 1 0.15 53 54 k 0.029 -0.046 -0.8 0.63 0.15 1 55 56 57 58 Parameter Estimates 59 60 95.0% Wald Confidence Interval 61 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 62 lalpha -1.16547 0.373814 -1.89813 -0.432809 63 rho 1.69882 0.185479 1.33529 2.06235 64 intercept 16.6759 2.07841 12.6023 20.7495 65 v -17.4464 2.46627 -22.2801 -12.6126 66 n 0.570647 0.161383 0.254343 0.886951 67 k 16.5364 7.36467 2.10191 30.9709 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-533 1 2 3 Table of Data and Estimated Values of Interest 4 5 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 6

------ --- -------- -------- ----------- ----------- ---------- 7 8 0 8 14.9 16.7 8.77 6.1 -0.824 9 14 8 8.4 8.37 3.39 3.39 0.0276 10 26 8 8.2 6.83 2.26 2.86 1.35 11 47 8 5.1 5.43 0.849 2.35 -0.394 12 320 8 2.2 1.95 0.849 0.983 0.732 13 1024 8 0.6 0.742 0.566 0.434 -0.929 14 15 16 17 Model Descriptions for likelihoods calculated 18 19 20 Model A1: Yij = Mu(i) + e(ij) 21 Var{e(ij)} = Sigma^2 22 23 Model A2: Yij = Mu(i) + e(ij) 24 Var{e(ij)} = Sigma(i)^2 25 26 Model A3: Yij = Mu(i) + e(ij) 27 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 28 Model A3 uses any fixed variance parameters that 29 were specified by the user 30 31 Model R: Yi = Mu + e(i) 32 Var{e(i)} = Sigma^2 33 34 35 Likelihoods of Interest 36 37 Model Log(likelihood) # Param's AIC 38 A1 -87.156698 7 188.313395 39 A2 -47.287416 12 118.574833 40 A3 -55.324218 8 126.648436 41 fitted -56.636555 6 125.273110 42 R -109.967018 2 223.934036 43 44 45 Explanation of Tests 46 47 Test 1: Do responses and/or variances differ among Dose levels? 48 (A2 vs. R) 49 Test 2: Are Variances Homogeneous? (A1 vs A2) 50 Test 3: Are variances adequately modeled? (A2 vs. A3) 51 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 52 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 53 54 Tests of Interest 55 56 Test -2*log(Likelihood Ratio) Test df p-value 57 58 Test 1 125.359 10 <.0001 59 Test 2 79.7386 5 <.0001 60 Test 3 16.0736 4 0.002922 61 Test 4 2.62467 2 0.2692 62 63 The p-value for Test 1 is less than .05. There appears to be a 64 difference between response and/or variances among the dose levels 65 It seems appropriate to model the data 66 67 The p-value for Test 2 is less than .1. A non-homogeneous variance 68 model appears to be appropriate 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-534 1 The p-value for Test 3 is less than .1. You may want to consider a 2 different variance model 3 4 The p-value for Test 4 is greater th an .1. The model chosen seems 5 to adequately describe the data 6 7 8 Benchmark Dose Computation 9 10 Specified effect = 1 11 12 Risk Type = Estimated st andard deviations from the control mean 13 14 Confidence level = 0.95 15 16 BMD = 5.56122 17 18 19 BMDL computation failed. 20 21 22 

## E.3.53.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 23

0 5 10 15 20

0 200 400 600 800 1000Mean Response

dose Power Model with 0.95 Confidence Level

14:30 11/20 2009 BMD BMDL Power

24 25 26

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-535 E.3.53.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 1 

## Unrestricted 2
3 4

==================================================================== 5 Power Model. (Versi on: 2.15; Date: 04/07/2008) 6 Input Data File: C:\USEPA\BMDS21\ Nov20\Pwr_Unrest_BMR1_hepatic_retinol.(d) 7 Gnuplot Plotting File: C:\USEPA\BMD S21\Nov20\Pwr_Unrest_BMR1_hepatic_retinol.plt 8 Fri Nov 20 14:30:13 2009 9

==================================================================== 10 11 Tbl3, hepatic retinol 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function is: 15 16 Y[dose] = control + slope * dose^power 17 18 19 Dependent variable = Mean 20 Independent variable = Dose 21 The power is not restricted 22 The variance is to be modeled as Va r(i) = exp(lalpha + log(mean(i)) * rho) 23 24 Total number of dose groups = 6 25 Total number of records with missing values = 0 26 Maximum number of iterations = 250 27 Relative Function Convergence has been set to: 1e-008 28 Parameter Convergence has been set to: 1e-008 29 30 31 32 Default Initial Parameter Values 33 lalpha = 2.76506 34 rho = 0 35 control = 14.9 36 slope = -3.78637 37 power = 0.191713 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 41 42 lalpha rho control slope power 43 44 lalpha 1 -0.8 -0.047 0.042 0.065 45 46 rho -0.8 1 -0.085 -0.0029 -0.11 47 48 control -0.047 -0.085 1 -0.95 -0.81 49 50 slope 0.042 -0.0029 -0.95 1 0.96 51 52 power 0.065 -0.11 -0.81 0.96 1 53 54 55 56 Parameter Estimates 57 58 95.0% Wald Confidence Interval 59 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 60 lalpha -1.02622 0.389164 -1.78897 -0.263475 61 rho 1.68421 0.199212 1.29376 2.07466 62 control 16.9577 2.21133 12.6235 21.2918 63 slope -7.19097 1.99708 -11.1052 -3.27676 64 power 0.117935 0.0225396 0.0737578 0.162111 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-536 1 Table of Data and Estimated Values of Interest 2 3 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 4

------ --- -------- -------- ----------- ----------- ---------- 5 6 0 8 14.9 17 8.77 6.49 -0.896 7 14 8 8.4 7.14 3.39 3.13 1.14 8 26 8 8.2 6.4 2.26 2.86 1.78 9 47 8 5.1 5.63 0.849 2.57 -0.588 10 320 8 2.2 2.76 0.849 1.41 -1.12 11 1024 8 0.6 0.672 0.566 0.428 -0.475 12 13 14 15 Model Descriptions for likelihoods calculated 16 17 18 Model A1: Yij = Mu(i) + e(ij) 19 Var{e(ij)} = Sigma^2 20 21 Model A2: Yij = Mu(i) + e(ij) 22 Var{e(ij)} = Sigma(i)^2 23 24 Model A3: Yij = Mu(i) + e(ij) 25 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 26 Model A3 uses any fixed variance parameters that 27 were specified by the user 28 29 Model R: Yi = Mu + e(i) 30 Var{e(i)} = Sigma^2 31 32 33 Likelihoods of Interest 34 35 Model Log(likelihood) # Param's AIC 36 A1 -87.156698 7 188.313395 37 A2 -47.287416 12 118.574833 38 A3 -55.324218 8 126.648436 39 fitted -59.994980 5 129.989960 40 R -109.967018 2 223.934036 41 42 43 Explanation of Tests 44 45 Test 1: Do responses and/or variances differ among Dose levels? 46 (A2 vs. R) 47 Test 2: Are Variances Homogeneous? (A1 vs A2) 48 Test 3: Are variances adequately modeled? (A2 vs. A3) 49 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 50 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 51 52 Tests of Interest 53 54 Test -2*log(Likelihood Ratio) Test df p-value 55 56 Test 1 125.359 10 <.0001 57 Test 2 79.7386 5 <.0001 58 Test 3 16.0736 4 0.002922 59 Test 4 9.34152 3 0.02508 60 61 The p-value for Test 1 is less than .05. There appears to be a 62 difference between response and/or variances among the dose levels 63 It seems appropriate to model the data 64 65 The p-value for Test 2 is less than .1. A non-homogeneous variance 66 model appears to be appropriate 67 68 The p-value for Test 3 is less than .1. You may want to consider a 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-537 different variance model 1 2 The p-value for Test 4 is less than .1. You may want to try a different 3 model 4 5 6 Benchmark Dose Computation 7 8 Specified effect = 1 9 10 Risk Type = Estimated st andard deviations from the control mean 11 12 Confidence level = 0.95 13 14 BMD = 0.420475 15 16 17 BMDL = 0.00850422 18 19 20 21 

## E.3.54. Van Birgelen et al. (1995a): Hepatic Retinol Palmitate 22 

## E.3.54.1. Summary Table of BMDS Modeling Results 23

Model Degrees of Freedom Variance 

## p -Value a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes
exponential (M2) 4 <0.0001 64.68 <0.0001 467.45 error error nonconstant variance, power restricted ≥ 1 exponential (M3) 4 <0.0001 64.68 <0.0001 467.45 error error nonconstant variance, power restricted ≥ 1 exponential (M4) 3 <0.0001 49.32 <0.0001 454.09 error error nonconstant variance, power restricted ≥ 1 exponential (M5) 3 <0.0001 49.32 <0.0001 454.09 error error nonconstant variance, power restricted ≥ 1 exponential (M5) 3 <0.0001 49.32 <0.0001 454.09 error error nonconstant variance, power unrestricted
Hill 3 <.0001 158.81 <.0001 563.58 error error nonconstant variance, n restricted >1
Hill d 3 <.0001 117.56 <.0001 522.32 2.4E-12 2.4E-12 nonconstant variance, n unrestricted
linear c 4 <.0001 85.68 <.0001 488.45 1.4E+03 9.9E+02 nonconstant variance

polynomial 4 <.0001 85.68 <.0001 488.45 1.4E+03 9.9E+02 nonconstant variance

power 4 <.0001 85.68 <.0001 488.45 1.4E+03 9.9E+02 nonconstant variance, power restricted ≥ 1, bound hit power d 3 <.0001 3.30 0.35 408.06 3.8E-02 1.2E-05 nonconstant variance, power unrestricted exponential (M2) 4 <0.0001 140.00 <0.0001 647.15 error error constant variance, power restricted ≥ 1 exponential (M3) 4 <0.0001 140.00 <0.0001 647.15 error error constant variance, power restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-538 Model Degrees of Freedom Variance 

## p -Value a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD (ng/kg-d) BMDL (ng/kg-d) Model Notes
exponential (M4) 3 <0.0001 3.50 0.32 512.61 2.5E+00 9.0E-03 constant variance, power restricted ≥ 1 exponential (M5) 3 <0.0001 3.50 0.32 512.61 2.5E+00 9.0E-03 constant variance, power restricted ≥ 1 exponential (M5) d 3 <0.0001 3.50 0.32 512.61 2.5E+00 9.0E-03 constant variance, power unrestricted
Hill 3 <.0001 1.33 0.72 510.44 1.3E+00 2.5E-01 constant variance, n restricted >1, bound hit
Hill 2 <.0001 0.29 0.86 511.40 7.9E-06 7.9E-06 constant variance, n unrestricted
linear 4 <.0001 44.59 <.0001 551.70 8.7E+02 5.5E+02 constant variance

polynomial 4 <.0001 44.59 <.0001 551.70 8.7E+02 5.5E+02 constant variance

power 4 <.0001 44.59 <.0001 551.70 8.7E+02 5.5E+02 constant variance, power restricted ≥ 1, bound hit

power 3 <.0001 0.29 0.96 509.40 2.2E-08 2.2E-08 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix

1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-539 E.3.54.2. Figure for Selected Model: Hill, No nconstant Variance, n Unrestricted 1

0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Hill Model with 0.95 Confidence Level

14:31 11/20 2009 BMDBMDL Hill

2 3 4 

## E.3.54.3. Output File for Selected Model: Hill, Nonconstant Variance, n Unrestricted 5
6 7

==================================================================== 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_hepatic_retinol_palmitate.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_hepatic_retinol_palmitate.plt 12 Fri Nov 20 14:31:05 2009 13

==================================================================== 14 15 Tbl3, hepatic retinol palmitate 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 Power parameter is not restricted 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 27 28 Total number of dose groups = 6 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-540 Default Initial Parameter Values 1 lalpha = 9.57332 2 rho = 0 3 intercept = 472 4 v = -469 5 n = 1.50651 6 k = 8.68519 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -k 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 lalpha rho intercept v n 16 17 lalpha 1 -1 -0.43 0.39 -0.014 18 19 rho -1 1 0.44 -0.41 0.015 20 21 intercept -0.43 0.44 1 -1 0.027 22 23 v 0.39 -0.41 -1 1 -0.026 24 25 n -0.014 0.015 0.027 -0.026 1 26 27 28 29 Parameter Estimates 30 31 95.0% Wald Confidence Interval 32 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 33 lalpha 2.09439 1.99191 -1.80969 5.99847 34 rho 1.43616 0.388229 0.675242 2.19707 35 intercept 640.986 167.573 312.548 969.423 36 v -495.665 166.074 -821.163 -170.167 37 n 0.451934 0.597514 -0.719171 1.62304 38 k 1.024e-012 NA 39 40 NA - Indicates that this parameter has hit a bound 41 implied by some inequality constraint and thus 42 has no standard error. 43 44 45 46 Table of Data and Estimated Values of Interest 47 48 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 49

------ --- -------- -------- ----------- ----------- ---------- 50 51 0 8 472 641 272 295 -1.62 52 14 8 94 145 67.9 102 -1.43 53 26 8 107 145 76.4 102 -1.07 54 47 8 74 145 39.6 102 -1.98 55 320 8 22 145 22.6 102 -3.43 56 1024 8 3 145 2.83 102 -3.96 57 58 59 60 Model Descriptions for likelihoods calculated 61 62 63 Model A1: Yij = Mu(i) + e(ij) 64 Var{e(ij)} = Sigma^2 65 66 Model A2: Yij = Mu(i) + e(ij) 67 Var{e(ij)} = Sigma(i)^2 68 69 Model A3: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-541 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 1 Model A3 uses any fixed variance parameters that 2 were specified by the user 3 4 Model R: Yi = Mu + e(i) 5 Var{e(i)} = Sigma^2 6 7 8 Likelihoods of Interest 9 10 Model Log(likelihood) # Param's AIC 11 A1 -250.554817 7 515.109634 12 A2 -196.755746 12 417.511491 13 A3 -197.383174 8 410.766347 14 fitted -256.161039 5 522.322077 15 R -276.789644 2 557.579287 16 17 18 Explanation of Tests 19 20 Test 1: Do responses and/or variances differ among Dose levels? 21 (A2 vs. R) 22 Test 2: Are Variances Homogeneous? (A1 vs A2) 23 Test 3: Are variances adequately modeled? (A2 vs. A3) 24 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 25 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 26 27 Tests of Interest 28 29 Test -2*log(Likelihood Ratio) Test df p-value 30 31 Test 1 160.068 10 <.0001 32 Test 2 107.598 5 <.0001 33 Test 3 1.25486 4 0.869 34 Test 4 117.556 3 <.0001 35 36 The p-value for Test 1 is less than .05. There appears to be a 37 difference between response and/or variances among the dose levels 38 It seems appropriate to model the data 39 40 The p-value for Test 2 is less than .1. A non-homogeneous variance 41 model appears to be appropriate 42 43 The p-value for Test 3 is greater than .1. The modeled variance appears 44 to be appropriate here 45 46 The p-value for Test 4 is less than .1. You may want to try a different 47 model 48 49 50 Benchmark Dose Computation 51 52 Specified effect = 1 53 54 Risk Type = Estimated standard deviations from the control mean 55 56 Confidence level = 0.95 57 58 BMD = 2.41754e-012 59 60 BMDL = 2.41754e-012 61 62 63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-542 E.3.54.4. Figure for Unrestricted Model: L inear, Nonconstant Variance 1

-100 0 100 200 300 400 500 600 700

0 200 400 600 800 1000 1200 1400Mean Response

dose Linear Model with 0.95 Confidence Level

14:30 11/20 2009 BMD BMDL Linear

2 3 4 

## E.3.54.5. Output File for Unrestricted M odel: Linear, Nonconstant Variance 5
6 7

==================================================================== 8 Polynomial Model. (Version: 2.13; Date: 04/08/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov20\Linear_BMR1_hepatic_retinol_palmitate.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Linear_BMR1_hepatic_retinol_palmitate.plt 11 Fri Nov 20 14:30:57 2009 12

==================================================================== 13 14 Tbl3, hepatic retinol palmitate 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the response function is: 18 19 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ... 20 21 22 Dependent variable = Mean 23 Independent variable = Dose 24 Signs of the polynomial coefficients are not restricted 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 26 27 Total number of dose groups = 6 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-543 lalpha = 9.57332 1 rho = 0 2 beta_0 = 177.506 3 beta_1 = -0.204775 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 7 8 lalpha rho beta_0 beta_1 9 10 lalpha 1 -0.95 -0.017 0.022 11 12 rho -0.95 1 0.00019 -0.0048 13 14 beta_0 -0.017 0.00019 1 -1 15 16 beta_1 0.022 -0.0048 -1 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 lalpha -0.723216 0.638291 -1.97424 0.527811 25 rho 2.26615 0.140196 1.99137 2.54093 26 beta_0 150.535 31.5457 88.7064 212.363 27 beta_1 -0.143931 0.0308317 -0.20436 -0.0835018 28 29 30 31 Table of Data and Estimated Values of Interest 32 33 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 34

------ --- -------- -------- ----------- ----------- ---------- 35 36 0 8 472 151 272 204 4.45 37 14 8 94 149 67.9 201 -0.766 38 26 8 107 147 76.4 199 -0.567 39 47 8 74 144 39.6 194 -1.02 40 320 8 22 104 22.6 135 -1.73 41 1024 8 3 3.15 2.83 2.56 -0.166 42 43 44 45 Model Descriptions for likelihoods calculated 46 47 48 Model A1: Yij = Mu(i) + e(ij) 49 Var{e(ij)} = Sigma^2 50 51 Model A2: Yij = Mu(i) + e(ij) 52 Var{e(ij)} = Sigma(i)^2 53 54 Model A3: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 56 Model A3 uses any fixed variance parameters that 57 were specified by the user 58 59 Model R: Yi = Mu + e(i) 60 Var{e(i)} = Sigma^2 61 62 63 Likelihoods of Interest 64 65 Model Log(likelihood) # Param's AIC 66 A1 -250.554817 7 515.109634 67 A2 -196.755746 12 417.511491 68 A3 -197.383174 8 410.766347 69 fitted -240.223107 4 488.446215 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-544 R -276.789644 2 557.579287 1 2 3 Explanation of Tests 4 5 Test 1: Do responses and/or variances differ among Dose levels? 6 (A2 vs. R) 7 Test 2: Are Variances Homogeneous? (A1 vs A2) 8 Test 3: Are variances adequately modeled? (A2 vs. A3) 9 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 10 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 11 12 Tests of Interest 13 14 Test -2*log(Likelihood Ratio) Test df p-value 15 16 Test 1 160.068 10 <.0001 17 Test 2 107.598 5 <.0001 18 Test 3 1.25486 4 0.869 19 Test 4 85.6799 4 <.0001 20 21 The p-value for Test 1 is less than .05. There appears to be a 22 difference between response and/or variances among the dose levels 23 It seems appropriate to model the data 24 25 The p-value for Test 2 is less than .1. A non-homogeneous variance 26 model appears to be appropriate 27 28 The p-value for Test 3 is greater than .1. The modeled variance appears 29 to be appropriate here 30 31 The p-value for Test 4 is less than .1. You may want to try a different 32 model 33 34 35 Benchmark Dose Computation 36 37 Specified effect = 1 38 39 Risk Type = Estimated standard deviations from the control mean 40 41 Confidence level = 0.95 42 43 BMD = 1419.81 44 45 46 BMDL = 988.945 47 48 49

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-545 E.3.54.6. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Power Model with 0.95 Confidence Level

14:31 11/20 2009 BMDBMDL Power

2 3 4 

## E.3.54.7. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 

## Unrestricted 6
7 8

==================================================================== 9 Power Model. (Version: 2.15; Date: 04/07/2008) 10 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_hepatic_retinol_palmitate.(d) 11 Gnuplot Plotting File: 12 C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_hepatic_retinol_palmitate.plt 13 Fri Nov 20 14:31:06 2009 14

==================================================================== 15 16 Tbl3, hepatic retinol palmitate 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function is: 20 21 Y[dose] = control + slope * dose^power 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 The power is not restricted 27 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 28 29 Total number of dose groups = 6 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-546 1 Default Initial Parameter Values 2 lalpha = 9.57332 3 rho = 0 4 control = 472 5 slope = -315.054 6 power = 0.0586881 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 lalpha rho control slope power 12 13 lalpha 1 -0.95 0.29 -0.31 -0.3 14 15 rho -0.95 1 -0.4 0.39 0.29 16 17 control 0.29 -0.4 1 -0.98 -0.82 18 19 slope -0.31 0.39 -0.98 1 0.91 20 21 power -0.3 0.29 -0.82 0.91 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 lalpha 0.0734958 0.849559 -1.59161 1.7386 30 rho 1.80632 0.194602 1.42491 2.18774 31 control 465.497 86.914 295.149 635.845 32 slope -318.06 82.4127 -479.586 -156.534 33 power 0.0540573 0.0117709 0.0309869 0.0771278 34 35 36 37 Table of Data and Estimated Values of Interest 38 39 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 40

------ --- -------- -------- ----------- ----------- ---------- 41 42 0 8 472 465 272 266 0.069 43 14 8 94 98.7 67.9 65.6 -0.201 44 26 8 107 86.2 76.4 58.1 1.01 45 47 8 74 73.8 39.6 50.5 0.0086 46 320 8 22 31.1 22.6 23.1 -1.11 47 1024 8 3 2.86 2.83 2.68 0.145 48 49 50 51 Model Descriptions for likelihoods calculated 52 53 54 Model A1: Yij = Mu(i) + e(ij) 55 Var{e(ij)} = Sigma^2 56 57 Model A2: Yij = Mu(i) + e(ij) 58 Var{e(ij)} = Sigma(i)^2 59 60 Model A3: Yij = Mu(i) + e(ij) 61 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 62 Model A3 uses any fixed variance parameters that 63 were specified by the user 64 65 Model R: Yi = Mu + e(i) 66 Var{e(i)} = Sigma^2 67 68 69 Likelihoods of Interest 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-547 1 Model Log(likelihood) # Param's AIC 2 A1 -250.554817 7 515.109634 3 A2 -196.755746 12 417.511491 4 A3 -197.383174 8 410.766347 5 fitted -199.031154 5 408.062307 6 R -276.789644 2 557.579287 7 8 9 Explanation of Tests 10 11 Test 1: Do responses and/or variances differ among Dose levels? 12 (A2 vs. R) 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 17 18 Tests of Interest 19 20 Test -2*log(Likelihood Ratio) Test df p-value 21 22 Test 1 160.068 10 <.0001 23 Test 2 107.598 5 <.0001 24 Test 3 1.25486 4 0.869 25 Test 4 3.29596 3 0.3482 26 27 The p-value for Test 1 is less than .05. There appears to be a 28 difference between response and/or variances among the dose levels 29 It seems appropriate to model the data 30 31 The p-value for Test 2 is less than .1. A non-homogeneous variance 32 model appears to be appropriate 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 The p-value for Test 4 is greater than .1. The model chosen seems 38 to adequately describe the data 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 0.0376489 50 51 52 BMDL = 1.20769e-005 53 54 55

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-548 E.3.54.8. Figure for Unrestricted Model: Expone ntial (M5), Constant Variance, Power 1 

## Unrestricted 2

0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:31 11/20 2009 BMD BMDL Exponential

3 4 5 

## E.3.54.9. Output File for Unrestricted Model: E xponential (M5), Constant Varian ce, Power 6 

## Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_CV_Unrest_BMR1_hepatic_retinol_palmitate.(d) 12 Gnuplot Plotting File: 13 Fri Nov 20 14:31:06 2009 14

==================================================================== 15 16 Tbl3, hepatic retinol palmitate 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-549 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 6 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 5 18

-------- -------- 19 lnalpha 9.43978 20 rho(S) 0 21 a 495.6 22 b 0.00826283 23 c 0.00576502 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 5 33

-------- ------- 34 lnalpha 9.51279 35 rho 0 36 a 470.237 37 b 0.126105 38 c 0.0898547 39 d 1 40 41 NC = No Convergence 42 43 44 Table of Stats From Input Data 45 46 Dose N Obs Mean Obs Std Dev 47

----- --- ---------- ------------- 48 0 8 472 271.5 49 14 8 94 67.88 50 26 8 107 76.37 51 47 8 74 39.6 52 320 8 22 22.63 53 1024 8 3 2.828 54 55 56 Estimated Values of Interest 57 58 Dose Est Mean Est Std Scaled Residual 59

------ ---------- --------- ---------------- 60 0 470.2 116.3 0.04286 61 14 115.5 116.3 -0.5224 62 26 58.38 116.3 1.182 63 47 43.39 116.3 0.7442 64 320 42.25 116.3 -0.4924 65 1024 42.25 116.3 -0.9544 66 67 68 69 Other models for which likelihoods are calculated: 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-550 1 Model A1: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = Sigma^2 3 4 Model A2: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = Sigma(i)^2 6 7 Model A3: Yij = Mu(i) + e(ij) 8 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 9 10 Model R: Yij = Mu + e(i) 11 Var{e(ij)} = Sigma^2 12 13 14 Likelihoods of Interest 15 16 Model Log(likelihood) DF AIC 17

------- ----------------- ---- ------------ 18 A1 -250.5548 7 515.1096 19 A2 -196.7557 12 417.5115 20 A3 -250.5548 7 515.1096 21 R -276.7896 2 557.5793 22 5 -252.3071 4 512.6141 23 24 25 Additive constant for all log-likelihoods = -44.11. This constant added to the 26 above values gives the log-likelihood including the term that does not 27 depend on the model parameters. 28 29 30 Explanation of Tests 31 32 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 33 Test 2: Are Variances Homogeneous? (A2 vs. A1) 34 Test 3: Are variances adequately modeled? (A2 vs. A3) 35 36 Test 7a: Does Model 5 fit the data? (A3 vs 5) 37 38 39 Tests of Interest 40 41 Test -2*log(Likelihood Ratio) D. F. p-value 42

-------- ------------------------ ------ -------------- 43 Test 1 160.1 10 < 0.0001 44 Test 2 107.6 5 < 0.0001 45 Test 3 107.6 5 < 0.0001 46 Test 7a 3.504 3 0.3202 47 48 49 The p-value for Test 1 is less than .05. There appears to be a 50 difference between response and/or variances among the dose 51 levels, it seems appropriate to model the data. 52 53 The p-value for Test 2 is less than .1. Consider running 54 a non-homogeneous variance model. 55 56 The p-value for Test 3 is less than .1. You may want to 57 consider a different variance model. 58 59 The p-value for Test 7a is greater than .1. Model 5 seems 60 to adequately describe the data. 61 62 63 Benchmark Dose Computations: 64 65 Specified Effect = 1.000000 66 67 Risk Type = Estimated standard deviations from control 68 69 Confidence Level = 0.950000 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-551 1 BMD = 2.5152 2 3 BMDL = 0.00902578 4 5 6 

## E.3.55. Van Birgelen et al. (1995a): Plasma FT4 7 

## E.3.55.1. Summary Table of BMDS Modeling Results 8

Model Degrees of Freedom Variance p-Value a 

## χ 2 Test Statistic 

## χ 2 pValue b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) c 4 0.01 3.18 0.53 215.46 3.4E+02 2.2E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.01 3.18 0.53 215.46 3.4E+02 2.2E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.01 2.13 0.55 216.42 2.2E+02 8.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.01 2.13 0.55 216.42 2.2E+02 8.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 0.01 2.13 0.55 216.42 2.2E+02 8.3E+01 nonconstant variance, power unrestricted

Hill 3 0.01 2.02 0.57 216.30 1.9E+02 4.2E+01 nonconstant variance, n restricted >1, bound hit

Hill d 2 0.01 1.87 0.39 218.16 1.7E+02 3.5E+01 nonconstant variance, n unrestricted

linear 4 0.01 4.52 0.34 216.81 4.6E+02 3.3E+02 nonconstant variance

polynomial 4 0.01 4.52 0.34 216.81 4.6E+02 3.3E+02 nonconstant variance

power 4 0.01 4.52 0.34 216.81 4.6E+02 3.3E+02 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 0.01 2.09 0.55 216.38 1.8E+02 3.2E+01 nonconstant variance, power unrestricted
exponential (M2) 4 0.01 3.77 0.44 214.06 3.1E+02 2.1E+02 constant variance, power restricted ≥ 1
exponential (M3) 4 0.01 3.77 0.44 214.06 3.1E+02 2.1E+02 constant variance, power restricted ≥ 1
exponential (M4) 3 0.01 2.79 0.43 215.08 1.9E+02 6.7E+01 constant variance, power restricted ≥ 1
exponential (M5) 3 0.01 2.79 0.43 215.08 1.9E+02 6.7E+01 constant variance, power restricted ≥ 1
exponential (M5) 3 0.01 2.79 0.43 215.08 1.9E+02 6.7E+01 constant variance, power unrestricted

Hill 3 0.01 2.58 0.46 214.87 1.6E+02 3.7E+01 constant variance, n restricted >1, bound hit

Hill 2 0.01 2.29 0.32 216.58 1.4E+02 3.0E+01 constant variance, n unrestricted

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-552 linear 4 0.01 5.11 0.28 215.40 4.3E+02 3.3E+02 constant variance

polynomial 4 0.01 5.11 0.28 215.40 4.3E+02 3.3E+02 constant variance

power 4 0.01 5.11 0.28 215.40 4.3E+02 3.3E+02 constant variance, power restricted ≥ 1, bound hit

power 3 0.01 2.46 0.48 214.75 1.5E+02 2.8E+01 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.3.55.2. Figure for Selected Model: Exponentia l (M2), N onconstant Variance, Power 3 

## Restricted ≥ 1 4

5 10 15 20 25 30

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

14:31 11/20 2009 BMD BMDL Exponential

5 6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-553 E.3.55.3. Output File for Selected Model: Expone ntial (M2), Nonconstant Varian ce, Power 1 

## Restricted ≥ 1 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_plasma_FT4.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 14:31:57 2009 9

==================================================================== 10 11 Tbl3, plasma FT4 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 34 35 Total number of dose groups = 6 36 Total number of records with missing values = 0 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39 Parameter Convergence has been set to: 1e-008 40 41 MLE solution provided: Exact 42 43 44 Initial Parameter Values 45 46 Variable Model 2 47

-------- -------- 48 lnalpha 4.29134 49 rho -0.423761 50 a 25.725 51 b 0.00336354 52 c 0.381323 53 d 1 54 55 56 57 Parameter Estimates 58 59 Variable Model 2 60

-------- ------- 61 lnalpha 1.55298 62 rho 0.59724 63 a 23.1888 64 b 0.00232277 65 c 0.391713 66 d 1 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-554 1 Table of Stats From Input Data 2 3 Dose N Obs Mean Obs Std Dev 4

----- --- ---------- ------------- 5 0 8 23.4 3.111 6 14 8 24.5 5.657 7 26 8 22.4 2.828 8 47 8 19.3 9.334 9 320 8 16.3 4.243 10 1024 8 10.3 4.808 11 12 13 Estimated Values of Interest 14 15 Dose Est Mean Est Std Scaled Residual 16

------ ---------- --------- ---------------- 17 0 22.66 5.554 0.3768 18 14 22.4 5.536 1.073 19 26 22.18 5.521 0.1131 20 47 21.8 5.495 -1.286 21 320 17.4 5.17 -0.6029 22 1024 9.735 4.417 0.3618 23 24 25 26 Other models for which likelihoods are calculated: 27 28 Model A1: Yij = Mu(i) + e(ij) 29 Var{e(ij)} = Sigma^2 30 31 Model A2: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = Sigma(i)^2 33 34 Model A3: Yij = Mu(i) + e(ij) 35 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 36 37 Model R: Yij = Mu + e(i) 38 Var{e(ij)} = Sigma^2 39 40 41 Likelihoods of Interest 42 43 Model Log(likelihood) DF AIC 44

------- ----------------- ---- ------------ 45 A1 -102.145 7 218.2901 46 A2 -94.04963 12 212.0993 47 A3 -102.143 8 220.286 48 R -117.8175 2 239.635 49 2 -103.7322 4 215.4645 50 51 52 Additive constant for all log-likelihoods = -44.11. This constant added to the 53 above values gives the log-likelihood including the term that does not 54 depend on the model parameters. 55 56 57 Explanation of Tests 58 59 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 60 Test 2: Are Variances Homogeneous? (A2 vs. A1) 61 Test 3: Are variances adequately modeled? (A2 vs. A3) 62 Test 4: Does Model 2 fit the data? (A3 vs. 2) 63 64 65 Tests of Interest 66 67 Test -2*log(Likelihood Ratio) D. F. p-value 68

-------- ------------------------ ------ -------------- 69 Test 1 47.54 10 < 0.0001 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-555 Test 2 16.19 5 0.00632 1 Test 3 16.19 4 0.002778 2 Test 4 3.178 4 0.5284 3 4 5 The p-value for Test 1 is less than .05. There appears to be a 6 difference between response and/or variances among the dose 7 levels, it seems appropriate to model the data. 8 9 The p-value for Test 2 is less than .1. A non-homogeneous 10 variance model appears to be appropriate. 11 12 The p-value for Test 3 is less than .1. You may want to 13 consider a different variance model. 14 15 The p-value for Test 4 is greater than .1. Model 2 seems 16 to adequately describe the data. 17 18 19 Benchmark Dose Computations: 20 21 Specified Effect = 1.000000 22 23 Risk Type = Estimated standard deviations from control 24 25 Confidence Level = 0.950000 26 27 BMD = 340.749 28 29 BMDL = 217.397 30 31 32 

## E.3.55.4. Figure for Unrestricted Model: Expone ntial (M5), Nonconstant Varian ce, Power 33 

## Unrestricted 34

5 10 15 20 25 30

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:32 11/20 2009 BMD BMDL Exponential

35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-556 E.3.55.5. Output File for Unrestricted Model: Exponential (M5), Nonconstant Variance, 1 

## Power Unrestricted 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_Unrest_BMR1_plasma_FT4.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 14:32:02 2009 9

==================================================================== 10 11 Tbl3, plasma FT4 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 34 35 Total number of dose groups = 6 36 Total number of records with missing values = 0 37 Maximum number of iterations = 250 38 Relative Function Convergence has been set to: 1e-008 39 Parameter Convergence has been set to: 1e-008 40 41 MLE solution provided: Exact 42 43 44 Initial Parameter Values 45 46 Variable Model 5 47

-------- -------- 48 lnalpha 4.29134 49 rho -0.423761 50 a 25.725 51 b 0.00336354 52 c 0.381323 53 d 1 54 55 56 57 Parameter Estimates 58 59 Variable Model 5 60

-------- ------- 61 lnalpha 1.55298 62 rho 0.59724 63 a 23.1888 64 b 0.00232277 65 c 0.391713 66 d 1 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-557 1 Table of Stats From Input Data 2 3 Dose N Obs Mean Obs Std Dev 4

----- --- ---------- ------------- 5 0 8 23.4 3.111 6 14 8 24.5 5.657 7 26 8 22.4 2.828 8 47 8 19.3 9.334 9 320 8 16.3 4.243 10 1024 8 10.3 4.808 11 12 13 Estimated Values of Interest 14 15 Dose Est Mean Est Std Scaled Residual 16

------ ---------- --------- ---------------- 17 0 23.19 5.558 0.1075 18 14 22.74 5.526 0.9022 19 26 22.36 5.498 0.01946 20 47 21.73 5.451 -1.261 21 320 15.79 4.956 0.2904 22 1024 10.39 4.373 -0.0587 23 24 25 26 Other models for which likelihoods are calculated: 27 28 Model A1: Yij = Mu(i) + e(ij) 29 Var{e(ij)} = Sigma^2 30 31 Model A2: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = Sigma(i)^2 33 34 Model A3: Yij = Mu(i) + e(ij) 35 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 36 37 Model R: Yij = Mu + e(i) 38 Var{e(ij)} = Sigma^2 39 40 41 Likelihoods of Interest 42 43 Model Log(likelihood) DF AIC 44

------- ----------------- ---- ------------ 45 A1 -102.145 7 218.2901 46 A2 -94.04963 12 212.0993 47 A3 -102.143 8 220.286 48 R -117.8175 2 239.635 49 5 -103.2077 5 216.4154 50 51 52 Additive constant for all log-likelihoods = -44.11. This constant added to the 53 above values gives the log-likelihood including the term that does not 54 depend on the model parameters. 55 56 57 Explanation of Tests 58 59 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 60 Test 2: Are Variances Homogeneous? (A2 vs. A1) 61 Test 3: Are variances adequately modeled? (A2 vs. A3) 62 63 Test 7a: Does Model 5 fit the data? (A3 vs 5) 64 65 66 Tests of Interest 67 68 Test -2*log(Likelihood Ratio) D. F. p-value 69

-------- ------------------------ ------ -------------- 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-558 Test 1 47.54 10 < 0.0001 1 Test 2 16.19 5 0.00632 2 Test 3 16.19 4 0.002778 3 Test 7a 2.129 3 0.546 4 5 6 The p-value for Test 1 is less than .05. There appears to be a 7 difference between response and/or variances among the dose 8 levels, it seems appropriate to model the data. 9 10 The p-value for Test 2 is less than .1. A non-homogeneous 11 variance model appears to be appropriate. 12 13 The p-value for Test 3 is less than .1. You may want to 14 consider a different variance model. 15 16 The p-value for Test 7a is greater than .1. Model 5 seems 17 to adequately describe the data. 18 19 20 Benchmark Dose Computations: 21 22 Specified Effect = 1.000000 23 24 Risk Type = Estimated standard deviations from control 25 26 Confidence Level = 0.950000 27 28 BMD = 215.664 29 30 BMDL = 83.4225 31 32 33 

## E.3.55.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted 34

5 10 15 20 25 30

0 200 400 600 800 1000Mean Response

dose Hill Model with 0.95 Confidence Level

14:32 11/20 2009 BMD BMDL Hill

35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-559 E.3.55.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 1
2 3

==================================================================== 4 Hill Model. (Version: 2.14; Date: 06/26/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_plasma_FT4.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_plasma_FT4.plt 7 Fri Nov 20 14:32:03 2009 8

==================================================================== 9 10 Tbl3, plasma FT4 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the response function is: 14 15 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 16 17 18 Dependent variable = Mean 19 Independent variable = Dose 20 Power parameter is not restricted 21 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 22 23 Total number of dose groups = 6 24 Total number of records with missing values = 0 25 Maximum number of iterations = 250 26 Relative Function Convergence has been set to: 1e-008 27 Parameter Convergence has been set to: 1e-008 28 29 30 31 Default Initial Parameter Values 32 lalpha = 3.38957 33 rho = 0 34 intercept = 23.4 35 v = -13.1 36 n = 0.834965 37 k = 269.95 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 41 42 lalpha rho intercept v n k 43 44 lalpha 1 -1 0.2 -0.14 -0.19 0.12 45 46 rho -1 1 -0.2 0.14 0.19 -0.12 47 48 intercept 0.2 -0.2 1 -0.35 -0.58 0.27 49 50 v -0.14 0.14 -0.35 1 0.9 -0.99 51 52 n -0.19 0.19 -0.58 0.9 1 -0.89 53 54 k 0.12 -0.12 0.27 -0.99 -0.89 1 55 56 57 58 Parameter Estimates 59 60 95.0% Wald Confidence Interval 61 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 62 lalpha 1.83708 2.19197 -2.4591 6.13327 63 rho 0.498362 0.745649 -0.963083 1.95981 64 intercept 23.7686 1.71713 20.403 27.1341 65 v -26.4457 39.0446 -102.972 50.0802 66 n 0.751729 0.57261 -0.370565 1.87402 67 k 988.089 3688.99 -6242.2 8218.37 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-560 1 2 Table of Data and Estimated Values of Interest 3 4 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 5

------ --- -------- -------- ----------- ----------- ---------- 6 7 0 8 23.4 23.8 3.11 5.52 -0.189 8 14 8 24.5 22.7 5.66 5.46 0.916 9 26 8 22.4 22.2 2.83 5.42 0.127 10 47 8 19.3 21.3 9.33 5.37 -1.07 11 320 8 16.3 15.8 4.24 4.99 0.263 12 1024 8 10.3 10.4 4.81 4.49 -0.043 13 14 15 16 Model Descriptions for likelihoods calculated 17 18 19 Model A1: Yij = Mu(i) + e(ij) 20 Var{e(ij)} = Sigma^2 21 22 Model A2: Yij = Mu(i) + e(ij) 23 Var{e(ij)} = Sigma(i)^2 24 25 Model A3: Yij = Mu(i) + e(ij) 26 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 27 Model A3 uses any fixed variance parameters that 28 were specified by the user 29 30 Model R: Yi = Mu + e(i) 31 Var{e(i)} = Sigma^2 32 33 34 Likelihoods of Interest 35 36 Model Log(likelihood) # Param's AIC 37 A1 -102.145036 7 218.290071 38 A2 -94.049629 12 212.099258 39 A3 -102.143023 8 220.286046 40 fitted -103.078418 6 218.156836 41 R -117.817514 2 239.635028 42 43 44 Explanation of Tests 45 46 Test 1: Do responses and/or variances differ among Dose levels? 47 (A2 vs. R) 48 Test 2: Are Variances Homogeneous? (A1 vs A2) 49 Test 3: Are variances adequately modeled? (A2 vs. A3) 50 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 51 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 52 53 Tests of Interest 54 55 Test -2*log(Likelihood Ratio) Test df p-value 56 57 Test 1 47.5358 10 <.0001 58 Test 2 16.1908 5 0.00632 59 Test 3 16.1868 4 0.002778 60 Test 4 1.87079 2 0.3924 61 62 The p-value for Test 1 is less than .05. There appears to be a 63 difference between response and/or variances among the dose levels 64 It seems appropriate to model the data 65 66 The p-value for Test 2 is less than .1. A non-homogeneous variance 67 model appears to be appropriate 68 69 The p-value for Test 3 is less than .1. You may want to consider a 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-561 different variance model 1 2 The p-value for Test 4 is greater than .1. The model chosen seems 3 to adequately describe the data 4 5 6 Benchmark Dose Computation 7 8 Specified effect = 1 9 10 Risk Type = Estimated standard deviations from the control mean 11 12 Confidence level = 0.95 13 14 BMD = 167.752 15 16 BMDL = 34.6031 17 18 19 20 

## E.3.55.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 21

5 10 15 20 25 30

0 200 400 600 800 1000Mean Response

dose Power Model with 0.95 Confidence Level

14:32 11/20 2009 BMD BMDL Power

22 23 24 

## E.3.55.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 25 

## Unrestricted 26
27 28

==================================================================== 29 Power Model. (Version: 2.15; Date: 04/07/2008) 30 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_plasma_FT4.(d) 31 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_plasma_FT4.plt 32 Fri Nov 20 14:32:04 2009 33

==================================================================== 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-562 Tbl3, plasma FT4 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2 3 The form of the response function is: 4 5 Y[dose] = control + slope * dose^power 6 7 8 Dependent variable = Mean 9 Independent variable = Dose 10 The power is not restricted 11 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 12 13 Total number of dose groups = 6 14 Total number of records with missing values = 0 15 Maximum number of iterations = 250 16 Relative Function Convergence has been set to: 1e-008 17 Parameter Convergence has been set to: 1e-008 18 19 20 21 Default Initial Parameter Values 22 lalpha = 3.38957 23 rho = 0 24 control = 24.5 25 slope = -0.64474 26 power = 0.449494 27 28 29 Asymptotic Correlation Matrix of Parameter Estimates 30 31 lalpha rho control slope power 32 33 lalpha 1 -1 0.11 -0.098 -0.083 34 35 rho -1 1 -0.12 0.099 0.083 36 37 control 0.11 -0.12 1 -0.8 -0.75 38 39 slope -0.098 0.099 -0.8 1 0.99 40 41 power -0.083 0.083 -0.75 0.99 1 42 43 44 45 Parameter Estimates 46 47 95.0% Wald Confidence Interval 48 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 49 lalpha 1.96489 2.14806 -2.24522 6.175 50 rho 0.456282 0.730608 -0.975684 1.88825 51 control 23.9768 1.64641 20.7499 27.2037 52 slope -0.373722 0.513355 -1.37988 0.632435 53 power 0.52088 0.188688 0.151059 0.890701 54 55 56 57 Table of Data and Estimated Values of Interest 58 59 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 60

------ --- -------- -------- ----------- ----------- ---------- 61 62 0 8 23.4 24 3.11 5.51 -0.296 63 14 8 24.5 22.5 5.66 5.43 1.04 64 26 8 22.4 21.9 2.83 5.4 0.242 65 47 8 19.3 21.2 9.33 5.36 -1 66 320 8 16.3 16.4 4.24 5.06 -0.0759 67 1024 8 10.3 10.2 4.81 4.53 0.0903 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-563 1 Model Descriptions for likelihoods calculated 2 3 4 Model A1: Yij = Mu(i) + e(ij) 5 Var{e(ij)} = Sigma^2 6 7 Model A2: Yij = Mu(i) + e(ij) 8 Var{e(ij)} = Sigma(i)^2 9 10 Model A3: Yij = Mu(i) + e(ij) 11 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 12 Model A3 uses any fixed variance parameters that 13 were specified by the user 14 15 Model R: Yi = Mu + e(i) 16 Var{e(i)} = Sigma^2 17 18 19 Likelihoods of Interest 20 21 Model Log(likelihood) # Param's AIC 22 A1 -102.145036 7 218.290071 23 A2 -94.049629 12 212.099258 24 A3 -102.143023 8 220.286046 25 fitted -103.188719 5 216.377438 26 R -117.817514 2 239.635028 27 28 29 Explanation of Tests 30 31 Test 1: Do responses and/or variances differ among Dose levels? 32 (A2 vs. R) 33 Test 2: Are Variances Homogeneous? (A1 vs A2) 34 Test 3: Are variances adequately modeled? (A2 vs. A3) 35 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 36 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 37 38 Tests of Interest 39 40 Test -2*log(Likelihood Ratio) Test df p-value 41 42 Test 1 47.5358 10 <.0001 43 Test 2 16.1908 5 0.00632 44 Test 3 16.1868 4 0.002778 45 Test 4 2.09139 3 0.5537 46 47 The p-value for Test 1 is less than .05. There appears to be a 48 difference between response and/or variances among the dose levels 49 It seems appropriate to model the data 50 51 The p-value for Test 2 is less than .1. A non-homogeneous variance 52 model appears to be appropriate 53 54 The p-value for Test 3 is less than .1. You may want to consider a 55 different variance model 56 57 The p-value for Test 4 is greater than .1. The model chosen seems 58 to adequately describe the data 59 60 61 Benchmark Dose Computation 62 63 Specified effect = 1 64 65 Risk Type = Estimated standard deviations from the control mean 66 67 Confidence level = 0.95 68 69 BMD = 175.43 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-564 1 2 BMDL = 32.1986 3 4 5 

## E.3.56. Van Birgelen et al. (1995a): Plasma TT4 6 

## E.3.56.1. Summary Table of BMDS Modeling Results 7

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 4 0.94 10.42 0.03 241.86 4.4E+02 2.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.94 10.42 0.03 241.86 4.4E+02 2.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.94 9.83 0.02 243.27 2.8E+02 2.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.94 9.83 0.02 243.27 2.8E+02 2.0E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.94 9.83 0.02 243.27 2.8E+02 2.0E+01 nonconstant variance, power unrestricted

Hill 3 0.94 5.45 0.14 238.89 4.4E+01 error nonconstant variance, n restricted >1, bound hit

Hill 3 0.94 5.45 0.14 238.89 4.4E+01 error nonconstant variance, n unrestricted

linear 4 0.94 10.82 0.03 242.26 5.0E+02 3.5E+02 nonconstant variance

polynomial 4 0.94 10.82 0.03 242.26 5.0E+02 3.5E+02 nonconstant variance

power 4 0.94 10.82 0.03 242.26 5.0E+02 3.5E+02 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.94 8.70 0.03 242.14 1.6E+02 2.2E+01 nonconstant variance, power unrestricted exponential (M2) c 4 0.94 9.83 0.04 239.86 4.4E+02 3.0E+02 constant variance, power restricted ≥ 1
exponential (M3) 4 0.94 9.83 0.04 239.86 4.4E+02 3.0E+02 constant variance, power restricted ≥ 1
exponential (M4) 3 0.94 9.24 0.03 241.27 2.8E+02 2.6E+01 constant variance, power restricted ≥ 1
exponential (M5) 3 0.94 9.24 0.03 241.27 2.8E+02 2.3E+01 constant variance, power restricted ≥ 1 exponential (M5) d 3 0.94 9.24 0.03 241.27 2.8E+02 2.3E+01 constant variance, power unrestricted

Hill 3 0.94 6.31 0.10 238.33 4.5E+01 error constant variance, n restricted >1, bound hit

Hill d 3 0.94 6.31 0.10 238.33 4.5E+01 error constant variance, n unrestricted

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-565 Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

linear 4 0.94 10.23 0.04 240.26 5.0E+02 3.7E+02 constant variance

polynomial 4 0.94 10.23 0.04 240.26 5.0E+02 3.7E+02 constant variance

power 4 0.94 10.23 0.04 240.26 5.0E+02 3.7E+02 constant variance, power restricted ≥ 1, bound hit

power d 3 0.94 8.14 0.04 240.16 1.7E+02 2.4E+01 constant variance, power unrestricted

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 1 2 

## E.3.56.2. Figure for Selected Model: Exponential (M 2), C onstant Variance, Power Restricted 3 

## ≥ 1 4

20 25 30 35 40 45

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

14:32 11/20 2009 BMD BMDL Exponential

5 6 7

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-566 E.3.56.3. Output File for Selected Model: Expo nential (M2), Constant Variance, Power 1 

## Restricted ≥ 1 2
3 4

==================================================================== 5 Exponential Model. (Version: 1.5; Date: 4/23/2009) 6 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_CV_BMR1_plasma_TT4.(d) 7 Gnuplot Plotting File: 8 Fri Nov 20 14:32:54 2009 9

==================================================================== 10 11 Tbl3, plasma TT4 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13 14 The form of the response function by Model: 15 Model 2: Y[dose] = a * exp{sign * b * dose} 16 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 17 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 18 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 19 20 Note: Y[dose] is the median response for exposure = dose; 21 sign = +1 for increasing trend in data; 22 sign = -1 for decreasing trend. 23 24 Model 2 is nested within Models 3 and 4. 25 Model 3 is nested within Model 5. 26 Model 4 is nested within Model 5. 27 28 29 Dependent variable = Mean 30 Independent variable = Dose 31 Data are assumed to be distributed: normally 32 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 33 rho is set to 0. 34 A constant variance model is fit. 35 36 Total number of dose groups = 6 37 Total number of records with missing values = 0 38 Maximum number of iterations = 250 39 Relative Function Convergence has been set to: 1e-008 40 Parameter Convergence has been set to: 1e-008 41 42 MLE solution provided: Exact 43 44 45 Initial Parameter Values 46 47 Variable Model 2 48

-------- -------- 49 lnalpha 3.66719 50 rho(S) 0 51 a 43.47 52 b 0.00268876 53 c 0.558678 54 d 1 55 56 (S) = Specified 57 58 59 60 Parameter Estimates 61 62 Variable Model 2 63

-------- ------- 64 lnalpha 3.85975 65 rho 0 66 a 39.9223 67 b 0.00192618 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-567 c 0.587293 1 d 1 2 3 4 Table of Stats From Input Data 5 6 Dose N Obs Mean Obs Std Dev 7

----- --- ---------- ------------- 8 0 8 40.9 6.788 9 14 8 41.4 5.374 10 26 8 41.4 6.505 11 47 8 32.3 7.354 12 320 8 33.6 6.223 13 1024 8 25.5 7.637 14 15 16 Estimated Values of Interest 17 18 Dose Est Mean Est Std Scaled Residual 19

------ ---------- --------- ---------------- 20 0 39.36 6.931 0.6265 21 14 39.12 6.931 0.9302 22 26 38.91 6.931 1.015 23 47 38.55 6.931 -2.551 24 320 34.15 6.931 -0.2227 25 1024 24.97 6.931 0.2158 26 27 28 29 Other models for which likelihoods are calculated: 30 31 Model A1: Yij = Mu(i) + e(ij) 32 Var{e(ij)} = Sigma^2 33 34 Model A2: Yij = Mu(i) + e(ij) 35 Var{e(ij)} = Sigma(i)^2 36 37 Model A3: Yij = Mu(i) + e(ij) 38 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 39 40 Model R: Yij = Mu + e(i) 41 Var{e(ij)} = Sigma^2 42 43 44 Likelihoods of Interest 45 46 Model Log(likelihood) DF AIC 47

------- ----------------- ---- ------------ 48 A1 -112.0125 7 238.025 49 A2 -111.4015 12 246.8029 50 A3 -112.0125 7 238.025 51 R -127.4455 2 258.891 52 2 -116.929 3 239.858 53 54 55 Additive constant for all log-likelihoods = -44.11. This constant added to the 56 above values gives the log-likelihood including the term that does not 57 depend on the model parameters. 58 59 60 Explanation of Tests 61 62 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 63 Test 2: Are Variances Homogeneous? (A2 vs. A1) 64 Test 3: Are variances adequately modeled? (A2 vs. A3) 65 Test 4: Does Model 2 fit the data? (A3 vs. 2) 66 67 68 Tests of Interest 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-568 Test -2*log(Likelihood Ratio) D. F. p-value 1

-------- ------------------------ ------ -------------- 2 Test 1 32.09 10 0.0003871 3 Test 2 1.222 5 0.9427 4 Test 3 1.222 5 0.9427 5 Test 4 9.833 4 0.04334 6 7 8 The p-value for Test 1 is less than .05. There appears to be a 9 difference between response and/or variances among the dose 10 levels, it seems appropriate to model the data. 11 12 The p-value for Test 2 is greater than .1. A homogeneous 13 variance model appears to be appropriate here. 14 15 The p-value for Test 3 is greater than .1. The modeled 16 variance appears to be appropriate here. 17 18 The p-value for Test 4 is less than .1. Model 2 may not adequately 19 describe the data; you may want to consider another model. 20 21 22 Benchmark Dose Computations: 23 24 Specified Effect = 1.000000 25 26 Risk Type = Estimated standard deviations from control 27 28 Confidence Level = 0.950000 29 30 BMD = 435.731 31 32 BMDL = 296.489 33 34 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-569 E.3.56.4. Figure for Unrestricted Model: Expone ntial (M5), Constant Variance, Power 1 

## Unrestricted 2

20 25 30 35 40 45

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:33 11/20 2009 BMD BMDL Exponential

3 4 5 

## E.3.56.5. Output File for Unrestricted Model: E xponential (M5), Constant Varian ce, Power 6 

## Unrestricted 7
8 9

==================================================================== 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 11 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_CV_Unrest_BMR1_plasma_TT4.(d) 12 Gnuplot Plotting File: 13 Fri Nov 20 14:33:03 2009 14

==================================================================== 15 16 Tbl3, plasma TT4 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the response function by Model: 20 Model 2: Y[dose] = a * exp{sign * b * dose} 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 24 25 Note: Y[dose] is the median response for exposure = dose; 26 sign = +1 for increasing trend in data; 27 sign = -1 for decreasing trend. 28 29 Model 2 is nested within Models 3 and 4. 30 Model 3 is nested within Model 5. 31 Model 4 is nested within Model 5. 32 33 34 Dependent variable = Mean 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-570 Independent variable = Dose 1 Data are assumed to be distributed: normally 2 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 3 rho is set to 0. 4 A constant variance model is fit. 5 6 Total number of dose groups = 6 7 Total number of records with missing values = 0 8 Maximum number of iterations = 250 9 Relative Function Convergence has been set to: 1e-008 10 Parameter Convergence has been set to: 1e-008 11 12 MLE solution provided: Exact 13 14 15 Initial Parameter Values 16 17 Variable Model 5 18

-------- -------- 19 lnalpha 3.66719 20 rho(S) 0 21 a 43.47 22 b 0.00268876 23 c 0.558678 24 d 1 25 26 (S) = Specified 27 28 29 30 Parameter Estimates 31 32 Variable Model 5 33

-------- ------- 34 lnalpha 3.85975 35 rho 0 36 a 39.9223 37 b 0.00192618 38 c 0.587293 39 d 1 40 41 42 Table of Stats From Input Data 43 44 Dose N Obs Mean Obs Std Dev 45

----- --- ---------- ------------- 46 0 8 40.9 6.788 47 14 8 41.4 5.374 48 26 8 41.4 6.505 49 47 8 32.3 7.354 50 320 8 33.6 6.223 51 1024 8 25.5 7.637 52 53 54 Estimated Values of Interest 55 56 Dose Est Mean Est Std Scaled Residual 57

------ ---------- --------- ---------------- 58 0 39.92 6.889 0.4014 59 14 39.48 6.889 0.7867 60 26 39.12 6.889 0.9372 61 47 38.5 6.889 -2.544 62 320 32.34 6.889 0.5167 63 1024 25.74 6.889 -0.09785 64 65 66 67 Other models for which likelihoods are calculated: 68 69 Model A1: Yij = Mu(i) + e(ij) 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-571 Var{e(ij)} = Sigma^2 1 2 Model A2: Yij = Mu(i) + e(ij) 3 Var{e(ij)} = Sigma(i)^2 4 5 Model A3: Yij = Mu(i) + e(ij) 6 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 7 8 Model R: Yij = Mu + e(i) 9 Var{e(ij)} = Sigma^2 10 11 12 Likelihoods of Interest 13 14 Model Log(likelihood) DF AIC 15

------- ----------------- ---- ------------ 16 A1 -112.0125 7 238.025 17 A2 -111.4015 12 246.8029 18 A3 -112.0125 7 238.025 19 R -127.4455 2 258.891 20 5 -116.634 4 241.268 21 22 23 Additive constant for all log-likelihoods = -44.11. This constant added to the 24 above values gives the log-likelihood including the term that does not 25 depend on the model parameters. 26 27 28 Explanation of Tests 29 30 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 31 Test 2: Are Variances Homogeneous? (A2 vs. A1) 32 Test 3: Are variances adequately modeled? (A2 vs. A3) 33 34 Test 7a: Does Model 5 fit the data? (A3 vs 5) 35 36 37 Tests of Interest 38 39 Test -2*log(Likelihood Ratio) D. F. p-value 40

-------- ------------------------ ------ -------------- 41 Test 1 32.09 10 0.0003871 42 Test 2 1.222 5 0.9427 43 Test 3 1.222 5 0.9427 44 Test 7a 9.243 3 0.02623 45 46 47 The p-value for Test 1 is less than .05. There appears to be a 48 difference between response and/or variances among the dose 49 levels, it seems appropriate to model the data. 50 51 The p-value for Test 2 is greater than .1. A homogeneous 52 variance model appears to be appropriate here. 53 54 The p-value for Test 3 is greater than .1. The modeled 55 variance appears to be appropriate here. 56 57 The p-value for Test 7a is less than .1. Model 5 may not adequately 58 describe the data; you may want to consider another model. 59 60 61 Benchmark Dose Computations: 62 63 Specified Effect = 1.000000 64 65 Risk Type = Estimated standard deviations from control 66 67 Confidence Level = 0.950000 68 69 BMD = 281.101 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-572 1 BMDL = 23.4709 2 3 4 

## E.3.56.6. Figure for Unrestricted Model: Hill , Constant Variance, n Unrestricted 5

20 25 30 35 40 45

0 200 400 600 800 1000Mean Response

dose Hill Model

14:33 11/20 2009 BMD Hill

6 7 8 

## E.3.56.7. Output File for Unrestricted Model: Hil l, consta nt Variance, n Unrestricted 9
10 11

==================================================================== 12 Hill Model. (Version: 2.14; Date: 06/26/2008) 13 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_CV_Unrest_BMR1_plasma_TT4.(d) 14 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_CV_Unrest_BMR1_plasma_TT4.plt 15 Fri Nov 20 14:33:05 2009 16

==================================================================== 17 18 Tbl3, plasma TT4 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 20 21 The form of the response function is: 22 23 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 24 25 26 Dependent variable = Mean 27 Independent variable = Dose 28 rho is set to 0 29 Power parameter is not restricted 30 A constant variance model is fit 31 32 Total number of dose groups = 6 33 Total number of records with missing values = 0 34 Maximum number of iterations = 250 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-573 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 alpha = 44.7333 7 rho = 0 Specified 8 intercept = 40.9 9 v = -15.4 10 n = 2.59801 11 k = 44.9231 12 13 14 Asymptotic Correlation Matrix of Parameter Estimates 15 16 ( *** The model parameter(s) -rho -n 17 have been estimated at a boundary point, or have been specified by the user, 18 and do not appear in the correlation matrix ) 19 20 alpha intercept v k 21 22 alpha 1 1.6e-009 -1e-009 8.3e-008 23 24 intercept 1.6e-009 1 -0.63 -0.12 25 26 v -1e-009 -0.63 1 -0.29 27 28 k 8.3e-008 -0.12 -0.29 1 29 30 31 32 Parameter Estimates 33 34 95.0% Wald Confidence Interval 35 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 36 alpha 44.637 9.11149 26.7788 62.4952 37 intercept 41.2336 1.36385 38.5605 43.9067 38 v -11.6836 2.15625 -15.9098 -7.45747 39 n 18 NA 40 k 44.0222 3.14538 37.8573 50.187 41 42 NA - Indicates that this parameter has hit a bound 43 implied by some inequality constraint and thus 44 has no standard error. 45 46 47 48 Table of Data and Estimated Values of Interest 49 50 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 51

------ --- -------- -------- ----------- ----------- ---------- 52 53 0 8 40.9 41.2 6.79 6.68 -0.141 54 14 8 41.4 41.2 5.37 6.68 0.0704 55 26 8 41.4 41.2 6.51 6.68 0.0708 56 47 8 32.3 32.3 7.35 6.68 -3.05e-005 57 320 8 33.6 29.5 6.22 6.68 1.71 58 1024 8 25.5 29.5 7.64 6.68 -1.71 59 60 61 62 Model Descriptions for likelihoods calculated 63 64 65 Model A1: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma^2 67 68 Model A2: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma(i)^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-574 1 Model A3: Yij = Mu(i) + e(ij) 2 Var{e(ij)} = Sigma^2 3 Model A3 uses any fixed variance parameters that 4 were specified by the user 5 6 Model R: Yi = Mu + e(i) 7 Var{e(i)} = Sigma^2 8 9 10 Likelihoods of Interest 11 12 Model Log(likelihood) # Param's AIC 13 A1 -112.012501 7 238.025002 14 A2 -111.401462 12 246.802924 15 A3 -112.012501 7 238.025002 16 fitted -115.165512 4 238.331023 17 R -127.445484 2 258.890968 18 19 20 Explanation of Tests 21 22 Test 1: Do responses and/or variances differ among Dose levels? 23 (A2 vs. R) 24 Test 2: Are Variances Homogeneous? (A1 vs A2) 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 26 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 27 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 28 29 Tests of Interest 30 31 Test -2*log(Likelihood Ratio) Test df p-value 32 33 Test 1 32.088 10 0.0003871 34 Test 2 1.22208 5 0.9427 35 Test 3 1.22208 5 0.9427 36 Test 4 6.30602 3 0.09763 37 38 The p-value for Test 1 is less than .05. There appears to be a 39 difference between response and/or variances among the dose levels 40 It seems appropriate to model the data 41 42 The p-value for Test 2 is greater than .1. A homogeneous variance 43 model appears to be appropriate here 44 45 46 The p-value for Test 3 is greater than .1. The modeled variance appears 47 to be appropriate here 48 49 The p-value for Test 4 is less than .1. You may want to try a different 50 model 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 1 56 57 Risk Type = Estimated standard deviations from the control mean 58 59 Confidence level = 0.95 60 61 BMD = 44.7355 62 63 64 BMDL computation failed. 65 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-575 E.3.56.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

20 25 30 35 40 45

0 200 400 600 800 1000Mean Response

dose Power Model with 0.95 Confidence Level

14:33 11/20 2009 BMD BMDL Power

2 3 4 

## E.3.56.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5
6

==================================================================== 7 Power Model. (Version: 2.15; Date: 04/07/2008) 8 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_CV_Unrest_BMR1_plasma_TT4.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_CV_Unrest_BMR1_plasma_TT4.plt 10 Fri Nov 20 14:33:06 2009 11

==================================================================== 12 13 Tbl3, plasma TT4 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the response function is: 17 18 Y[dose] = control + slope * dose^power 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 rho is set to 0 24 The power is not restricted 25 A constant variance model is fit 26 27 Total number of dose groups = 6 28 Total number of records with missing values = 0 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-576 alpha = 44.7333 1 rho = 0 Specified 2 control = 41.4 3 slope = -4.42652 4 power = 0.155038 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 8 9 ( *** The model parameter(s) -rho 10 have been estimated at a boundary point, or have been specified by the user, 11 and do not appear in the correlation matrix ) 12 13 alpha control slope power 14 15 alpha 1 5.3e-011 3.5e-010 5.9e-010 16 17 control 5.3e-011 1 -0.81 -0.76 18 19 slope 3.5e-010 -0.81 1 0.99 20 21 power 5.9e-010 -0.76 0.99 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 alpha 46.3718 9.4656 27.8195 64.924 30 control 41.441 2.1824 37.1636 45.7184 31 slope -0.626626 0.890104 -2.3712 1.11795 32 power 0.464532 0.195802 0.0807676 0.848296 33 34 35 36 Table of Data and Estimated Values of Interest 37 38 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 39

------ --- -------- -------- ----------- ----------- ---------- 40 41 0 8 40.9 41.4 6.79 6.81 -0.225 42 14 8 41.4 39.3 5.37 6.81 0.87 43 26 8 41.4 38.6 6.51 6.81 1.17 44 47 8 32.3 37.7 7.35 6.81 -2.24 45 320 8 33.6 32.3 6.22 6.81 0.538 46 1024 8 25.5 25.8 7.64 6.81 -0.108 47 48 49 50 Model Descriptions for likelihoods calculated 51 52 53 Model A1: Yij = Mu(i) + e(ij) 54 Var{e(ij)} = Sigma^2 55 56 Model A2: Yij = Mu(i) + e(ij) 57 Var{e(ij)} = Sigma(i)^2 58 59 Model A3: Yij = Mu(i) + e(ij) 60 Var{e(ij)} = Sigma^2 61 Model A3 uses any fixed variance parameters that 62 were specified by the user 63 64 Model R: Yi = Mu + e(i) 65 Var{e(i)} = Sigma^2 66 67 68 Likelihoods of Interest 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-577 Model Log(likelihood) # Param's AIC 1 A1 -112.012501 7 238.025002 2 A2 -111.401462 12 246.802924 3 A3 -112.012501 7 238.025002 4 fitted -116.080583 4 240.161165 5 R -127.445484 2 258.890968 6 7 8 Explanation of Tests 9 10 Test 1: Do responses and/or variances differ among Dose levels? 11 (A2 vs. R) 12 Test 2: Are Variances Homogeneous? (A1 vs A2) 13 Test 3: Are variances adequately modeled? (A2 vs. A3) 14 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 15 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 16 17 Tests of Interest 18 19 Test -2*log(Likelihood Ratio) Test df p-value 20 21 Test 1 32.088 10 0.0003871 22 Test 2 1.22208 5 0.9427 23 Test 3 1.22208 5 0.9427 24 Test 4 8.13616 3 0.04328 25 26 The p-value for Test 1 is less than .05. There appears to be a 27 difference between response and/or variances among the dose levels 28 It seems appropriate to model the data 29 30 The p-value for Test 2 is greater than .1. A homogeneous variance 31 model appears to be appropriate here 32 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 35 to be appropriate here 36 37 The p-value for Test 4 is less than .1. You may want to try a different 38 model 39 40 41 Benchmark Dose Computation 42 43 Specified effect = 1 44 45 Risk Type = Estimated standard deviations from the control mean 46 47 Confidence level = 0.95 48 49 BMD = 170.004 50 51 52 BMDL = 24.0807 53 54 55

56 57 58 59

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-578 E.3.57. White et al. (1986): CH50 1 

## E.3.57.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance 

## p -Value

a 

## χ 2 Test Statistic 

## χ 2 

## p

Value b AIC BMD(ng/kgd) BMDL(ng/kgd) Model Notes

exponential (M2) 5 0.09 20.99 0.00 391.47 4.5E+02 2.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 5 0.09 20.99 0.00 391.47 4.5E+02 2.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) 4 0.09 19.65 0.00 392.13 3.1E+02 1.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 4 0.09 19.65 0.00 392.13 3.1E+02 1.1E+02 nonconstant variance, power restricted ≥ 1

Hill 4 0.09 18.75 0.00 391.22 2.0E+02 3.6E+01 nonconstant variance, n restricted >1, bound hit

linear 5 0.09 25.95 <.0001 396.43 8.1E+02 5.9E+02 nonconstant variance

polynomial 5 0.09 25.95 <.0001 396.43 8.1E+02 5.9E+02 nonconstant variance

power 5 0.09 25.95 <.0001 396.43 8.1E+02 5.9E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 5 0.09 21.77 0.00 390.45 4.0E+02 2.6E+02 constant variance, power restricted ≥ 1
exponential (M3) 5 0.09 21.77 0.00 390.45 4.0E+02 2.6E+02 constant variance, power restricted ≥ 1
exponential (M4) 4 0.09 20.51 0.00 391.19 2.7E+02 7.2E+01 constant variance, power restricted ≥ 1
exponential (M5) 4 0.09 20.51 0.00 391.19 2.7E+02 7.2E+01 constant variance, power restricted ≥ 1

Hill c 4 0.09 19.30 0.00 389.98 1.3E+02 2.9E+01 constant variance, n restricted >1, bound hit

linear 5 0.09 26.50 <.0001 395.18 7.3E+02 5.7E+02 constant variance

polynomial 5 0.09 26.50 <.0001 395.18 7.3E+02 5.7E+02 constant variance

power 5 0.09 26.50 <.0001 395.18 7.3E+02 5.7E+02 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant varian ce model should be selected; Values ≥ 0.1 means a constant variance model should be selected b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-579 E.3.57.2. Figure for Selected Model: Hill, Consta nt Variance, n Restricted >1, Bound Hit 1

0 20 40 60 80 100

0 500 1000 1500 2000Mean Response

dose Hill Model with 0.95 Confidence Level

19:52 10/06 2009 BMD BMDL Hill

2 3 4 

## E.3.57.3. Output File for Selected Model: Hill, Co nstant Variance, n Restricted >1, Bound 5 

## Hit 6
7 8

==================================================================== 9 Hill Model. (Version: 2.14; Date: 06/26/2008) 10 Input Data File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_CH50.(d) 11 Gnuplot Plotting File: C:\USEPA\BMDS21\AniDose\HillConstVar_BMR1_CH50.plt 12 Tue Oct 06 19:52:50 2009 13

==================================================================== 14 15 [insert study notes] 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the response function is: 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 21 22 23 Dependent variable = Mean 24 Independent variable = Dose 25 rho is set to 0 26 Power parameter restricted to be greater than 1 27 A constant variance model is fit 28 29 Total number of dose groups = 7 30 Total number of records with missing values = 0 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-580 1 Default Initial Parameter Values 2 alpha = 273.143 3 rho = 0 Specified 4 intercept = 91 5 v = -74 6 n = 0.0969998 7 k = 10 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 ( *** The model parameter(s) -rho -n 13 have been estimated at a boundary point, or have been specified by the user, 14 and do not appear in the correlation matrix ) 15 16 alpha intercept v k 17 18 alpha 1 -1.4e-008 -3.3e-008 6.7e-009 19 20 intercept -1.4e-008 1 0.38 -0.8 21 22 v -3.3e-008 0.38 1 -0.81 23 24 k 6.7e-009 -0.8 -0.81 1 25 26 27 28 Parameter Estimates 29 30 95.0% Wald Confidence Interval 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 32 alpha 337.326 63.7486 212.381 462.271 33 intercept 73.1945 6.21329 61.0167 85.3723 34 v -58.2543 12.308 -82.3776 -34.131 35 n 1 NA 36 k 289.939 354.891 -405.635 985.512 37 38 NA - Indicates that this parameter has hit a bound 39 implied by some inequality constraint and thus 40 has no standard error. 41 42 43 44 Table of Data and Estimated Values of Interest 45 46 Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 47

------ --- -------- -------- ----------- ----------- ---------- 48 49 0 8 91 73.2 14.1 18.4 2.74 50 10 8 54 71.3 8.49 18.4 -2.66 51 50 8 63 64.6 11.3 18.4 -0.25 52 100 8 56 58.3 25.5 18.4 -0.347 53 500 8 41 36.3 17 18.4 0.72 54 1000 8 32 28 17 18.4 0.611 55 2000 8 17 22.3 17 18.4 -0.819 56 57 58 59 Model Descriptions for likelihoods calculated 60 61 62 Model A1: Yij = Mu(i) + e(ij) 63 Var{e(ij)} = Sigma^2 64 65 Model A2: Yij = Mu(i) + e(ij) 66 Var{e(ij)} = Sigma(i)^2 67 68 Model A3: Yij = Mu(i) + e(ij) 69 Var{e(ij)} = Sigma^2 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-581 Model A3 uses any fixed variance parameters that 1 were specified by the user 2 3 Model R: Yi = Mu + e(i) 4 Var{e(i)} = Sigma^2 5 6 7 Likelihoods of Interest 8 9 Model Log(likelihood) # Param's AIC 10 A1 -181.340979 8 378.681959 11 A2 -175.820265 14 379.640529 12 A3 -181.340979 8 378.681959 13 fitted -190.989397 4 389.978794 14 R -212.367055 2 428.734109 15 16 17 Explanation of Tests 18 19 Test 1: Do responses and/or variances differ among Dose levels? 20 (A2 vs. R) 21 Test 2: Are Variances Homogeneous? (A1 vs A2) 22 Test 3: Are variances adequately modeled? (A2 vs. A3) 23 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 24 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 25 26 Tests of Interest 27 28 Test -2*log(Likelihood Ratio) Test df p-value 29 30 Test 1 73.0936 12 <.0001 31 Test 2 11.0414 6 0.0871 32 Test 3 11.0414 6 0.0871 33 Test 4 19.2968 4 0.0006871 34 35 The p-value for Test 1 is less than .05. There appears to be a 36 difference between response and/or variances among the dose levels 37 It seems appropriate to model the data 38 39 The p-value for Test 2 is less than .1. Consider running a 40 non-homogeneous variance model 41 42 The p-value for Test 3 is less than .1. You may want to consider a 43 different variance model 44 45 The p-value for Test 4 is less than .1. You may want to try a different 46 model 47 48 49 Benchmark Dose Computation 50 51 Specified effect = 1 52 53 Risk Type = Estimated standard deviations from the control mean 54 55 Confidence level = 0.95 56 57 BMD = 133.503 58 59 BMDL = 28.903 60 61 62

63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-582 E.4. REFERENCES 1 

## Amin, S; Moore, RW; Peterson, RE; et al. (2000) Gestational and lactational exposure to TCDD 2 

## or coplanar PCBs alters adult expression of saccharin preferen ce behavior in female rats. 3 

## Neurotoxicol Teratol 22(5):675–682. 4 

## Bell, DR; Clode, S; Fan, MQ; et al. (2007a ) Toxicity of 2,3,7,8- tetrachlorodibenzo- p -dioxin in 5 

## the developing male Wistar(Han) rat. II: Chronic dosing causes developmental delay. Toxicol 6 

## Sci 99(1):224

− 233. 7 

## Bell, DR; Clode, S; Fan, MQ; et al. (2007b) Relationships between tissue levels of 2,3,7,8- 8 

## tetrachlorodibenzo-p-dioxin (TC DD), mRNAs, and toxicity in th e developing male Wistar (Han) 9 

## rat. Toxicol Sci 99(2):591-604. 10 

## Cantoni, L; Salmona, M; Rizzardini, M. (1981) Po rphyrogenic effect of ch ronic treatment with 11 

## 2,3,7,8-tetrachlorodibenzo-p-dioxin in female rate s. Dose-effect relationship following urinary 12 

## excretion of porphyrins. Toxicol Appl Pharmacol 57:156

− 157. 13 

## Crofton, KM; Craft, ES; Hedge, JM; et al. (2 005) Thyroid-hormone-d isrupting chemicals: 14 

## evidence for dose-dependent additivity or syne rgism. Environ Health Perspect 113(11):1549– 15 

## 1554. 16 

## DeCaprio, AP; McMartin, DN; O’Keefe, PE; et al. (1986) Subchronic oral toxicity of 2,3,7,8- 17 

## tetrachlorodibenzo-p-dioxin in the guinea pig: comparisons with a PCB-containing transformer 18 

## fluid pyrolysate. Fund Appl Toxicol 6:454–463. 19 

## Hojo, R; Stern, S; Zareba, G; et al. (2002) Sexually dimorphic beha vioral responses to prenatal 20 

## dioxin exposure. Environ Health Perspect 110(3):247

− 254. 21 

## Kattainen, H; Tuukanan, J; Simanainen, U; et al. (2001) In utero/lactational 2,3,7,8- 22 

## tetrachlorodibenzo- p- dioxin exposure impairs molar tooth de velopment in rats. Toxicol Appl 23 

## Pharmacol 17:216

− 224. 24 

## Keller, JM; Huet-Hudson, YM; Leamy, LJ. (2007) Qu alitative effects of dioxin on molars vary 25 

## among inbred mouse strains. Arch Oral Biol 52:450

− 454. 26 

## Keller, JM; Zelditch, ML; Huet, YM; et al. (2 008a) Genetic differences in sensitivity to 27 

## alterations of mandible structure caused by the teratogen 2,3, 7,8-tetrachlorodibenzo- p -dioxin. 28 

## Toxicol Pathol 36:1006–1013. 29 

## Keller, JM; Huet-Hudson, Y; Leamy, LJ. (2008b) Effects of 2,3,7,8-tetrachl orodibenzo-p-dioxin 30 

## on molar development among non-resi stant inbred strain s of mice: a geometric morphometric 31 

## analysis. Growth Devel Aging 71:3

− 16. 32 

## Kociba, RJ; Keyes, DG; Beyer, JE; et al. (1978) Results of a two-year chronic toxicity and 33 

## oncogenicity study of 2,3,7,8-tetrachlorodibenzo-p- dioxin in rats. Toxicol Appl Pharmacol 34 

## 46(2):279

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## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-583 Latchoumycandane, C; Mathur, PP. (2002) Effects of vitamin E on reactive oxygen species1 

## mediated 2,3,7,8-tetrachlorodi-benzo-p -dioxin toxicity in rat testis . J Appl Toxicol 22(5):345– 2 

## 351. 3 

## Li, B; Liu, H-Y; Dai, L- J; et al. (2006) The early embryo loss caused by 2,3,7,8- 4 

## tetrachlorodibenzo- p -dioxin may be related to the accumulation of this compound in the uterus. 5 

## Reprod Toxicol 21:301

− 306. 6 

## Markowski, VP; Zareba, G; St ern, S; et al. (2001) Altered operant responding for motor 7 

## reinforcement and the determination of benchm ark doses following perinatal exposure to low8 

## level 2,3,7,8-tetrachlorodibenzo-p-dioxin. Environ Health Perspect 109(6):621

− 627. 9 

## Miettinen, HM; Sorvari, R; Alaluusua, S; et al . (2006) The Effect of perinatal TCDD exposure 10 

## on caries susceptibility in rats. Toxicol Sci 91(2):568

− 575. 11 

## NTP (National Toxicology Program). (1982) NT P Technical Report on ca rcinogenesis bioassay 12 

## of 2,3,7,8-tetrachlorodibenzo-p-di oxin in Osborne-Mendel rats and B6C3F1 mice (gavage 13 

## study). Public Health Service, U.S. Department of Health and Human Services; NTP TR 209. 14 

## Available from the National Institute of Environm ental Health Sciences, Research Triangle Park, 15 

## NC. 16 

## NTP (National Toxicology Program). (2006) Toxi cology and carcinogenesis studies of a mixture 17 

## of 2,3,7,8-tetrachlorodibenzo -p- dioxin (TCDD) (CAS No. 1746-01-6), 2,3,4,7,8- 18 

## pentachlorodibenzofuran (PeCDF) (CAS No. 57117-31-4), and 3,3',4,4',5-pentachlorobiphenyl 19 

## (PCB 126) (CAS No. 57465-28-8) in female Harlan Sprague-Dawley Rats (gavage studies). 20 

## Public Health Service, U.S. Department of H ealth and Human Services ; NTP TR 526. Available 21 

## from the National Institute of Environmental H ealth Sciences, Research Triangle Park, NC. 22 

## Available at: http://ntp.niehs.nih.gov/index.c fm ?objectid=070B7300-0E62-BF12- 23 

## F4C3E3B5B645A92B 24 

## Ohsako, S; Miyabara, Y; Nish imura, N; et al. (2001) Maternal exposure to a low dose of 2,3,7,8- 25 

## tetrachlorodibenzo- p- dioxin (TCDD) suppressed the developm ent of reproductive organs of male 26 

## rats: dose-dependent increas e of mRNA levels of 5 α -reductase type 2 in c ontrast to decrease of 27 

## androgren receptor in the pubertal ve ntral prostate. Toxicol Sci 60:132

– 143. 28 

## Schantz, SL; Seo, BW; Moshtaghian, J; et al. (1996) Effects of gestational and lactational 29 

## exposure to TCDD or coplanar PCBs on spatial learning. Ne urotoxicol Teratol 18(3):305–313. 30 

## Shi, Z; Valdez, KE; Ying, AY; et al. (2007) Ov arian endocrine disrup tion underlies premature 31 

## reproduction senescence following environmentall y relevant chronic exposure to aryl 32 

## hydrocarbon receptor agonist 2,3,7,8-tetrachlorodibenzo- p -dioxin. Biol Reprod 30(4):293

− 342. 33 

## Smialowicz, RJ; DeVito, MJ; Williams, WC; et al . (2008) Relative potency based on hepatic 34 

## enzyme induction predicts immunosuppressive effects of a mixture of PCDDS/PCDFS and 35 

## PCBS. Toxicol Appl Pharmacol 227:477–484. 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE E-584 Toth, KJ; Sugar, S; Somfai-Relle, S; et al. (1978) Carcinogenic bioassay of the herbicide 2,4,5- 1 

## trichlorphenoxy ethanol (TCPE) with Sw iss mice. Prog Biochem Pharmacol 14:82

− 93. 2 

## Toth, L; Somfai-Relle, S; Sugá r, J; et al. (1979) Carcinogenicity testing of herbicide 2,4,5- 3 

## trichlorophenoxyethanol contai ning dioxin and of pure dioxin in Swiss mice. Nature 4 

## 278:548

− 549. 5 

## Van Birgelen, AP; Van der Kolk, J; Fase, KM; et al. (1995) Subchronic dose-response study of 6 

## 2,3,7,8-tetrachlorodibenzo-p-dioxin in female Sp rague-Dawley rats. Toxicol Appl Pharmacol 7 

## 132:1-13. 8 

## White, KL, Jr; Lysy, HH; McCay, JA; et al. (19 86) Modulation of serum complement levels 9 

## following exposure to polychlori nated dibenzo-p-dioxins. Toxicol Appl Pharmacol 84:209–219. 10

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX F
Cancer Benchmark Dose Modeling

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-ii CONTENTS—APPENDIX F: Can cer Benchmark Dose Modeling

APPENDIX F. CANCER BENCHMARK DOSE MODELING ............................................... F-1 F.1. BLOOD SERUM BMDS RESULTS ........................................................................... F-1 F.1.1. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate or Nasal Turbinates

................................................................... F-1 F.1.1.1. Summary Table of BMDS Modeling Results .................................. F-1 F.1.1.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

........................................................................... F-2 F.1.1.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0.......................................................... F-2 F.1.2. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Tongue

.......................................................................................................... F-4 F.1.2.1. Summary Table of BMDS Modeling Results .................................. F-4 F.1.2.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

........................................................................... F-4 F.1.2.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0.......................................................... F-5 F.1.3. Kociba et al. (1978): Female, Adenoma of Adrenal Cortex............................ F-6 F.1.3.1. Summary Table of BMDS Modeling Results .................................. F-6 F.1.3.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

........................................................................... F-7 F.1.3.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0.......................................................... F-7 F.1.4. Kociba et al. (1978): Female , Hepatocellular Adenom a(s) or Carcinoma(s)..................................................................................................... F-9 F.1.4.1. Summary Table of BMDS Modeling Results .................................. F-9 F.1.4.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

........................................................................... F-9 F.1.4.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-10 F.1.5. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate or Nasal Turbinates

................................................................. F-11 F.1.5.1. Summary Table of BMDS Modeling Results ................................ F-11 F.1.5.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-12 F.1.5.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-12 F.1.6. Kociba et al. (1978): Fema le, Keratinizing Squamous Cell Carcinom a of Lung ......................................................................................... F-14 F.1.6.1. Summary Table of BMDS Modeling Results ................................ F-14 F.1.6.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-15 F.1.6.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-15

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-iii CONTENTS (continued)

F.1.7. National Toxicology Program (1982): Fem ale Rat, Subcutaneous Tissue. Fibrosarcoma ...................................................................................... F-17 F.1.7.1. Summary Table of BMDS Modeling Results ................................ F-17 F.1.7.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-17 F.1.7.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-18 F.1.8. National Toxicology Program (1982) : Fem ale Rat, Liver, Neoplastic Nodule or Hepatocellular Carcinoma ............................................................. F-19 F.1.8.1. Summary Table of BMDS Modeling Results ................................ F-19 F.1.8.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-20 F.1.8.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-20 F.1.9. National Toxicology Program (1982): Fem ale Rat, Adrenal, Cortical Adenoma, or Carcinoma or Adenoma, NOS .................................................. F-22 F.1.9.1. Summary Table of BMDS Modeling Results ................................ F-22 F.1.9.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-22 F.1.9.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-23 F.1.10. National Toxicology Program ( 1982): Fem ale Rat, Thyroid, Follicular-Cell Adenoma ................................................................................ F-24 F.1.10.1. Summary Table of BMDS Modeling Results ................................ F-24 F.1.10.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-25 F.1.10.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-25 F.1.11. National Toxicology Program (1982) : Male Rat, Liver, Neoplastic Nodule or Hepatocellular Carcinom a ............................................................. F-27 F.1.11.1. Summary Table of BMDS Modeling Results ................................ F-27 F.1.11.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-28 F.1.11.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-28 F.1.12. National Toxicology Program (1982): Male Ra, Thyroid, Follicu lar-Cell Adenoma or Carcinoma.......................................................... F-30 F.1.12.1. Summary Table of BMDS Modeling Results ................................ F-30 F.1.12.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-31 F.1.12.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-iv CONTENTS (continued)

F.1.13. National Toxicology Program (198 2): Male Rat, Adrenal C ortex, Adenoma......................................................................................................... F-33 F.1.13.1. Summary Table of BMDS Modeling Results ................................ F-33 F.1.13.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-34 F.1.13.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-34 F.1.14. National Toxicology Program (198 2): Fem ale Mice, Subcutaneous Tissue, Fibrosarcoma ...................................................................................... F-36 F.1.14.1. Summary Table of BMDS Modeling Results ................................ F-36 F.1.14.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-37 F.1.14.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-37 F.1.15. National Toxicology Program (198 2): Fem ale Mice, Hematopoietic System, Lymphoma ........................................................................................ F-39 F.1.15.1. Summary Table of BMDS Modeling Results ................................ F-39 F.1.15.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-40 F.1.15.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-40 F.1.16. National Toxicology Program ( 1982): Fem ale Mice, Liver, Hepatocellular Adenoma or Carcinoma.......................................................... F-42 F.1.16.1. Summary Table of BMDS Modeling Results ................................ F-42 F.1.16.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-43 F.1.16.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-43 F.1.17. National Toxicology Program ( 1982): Fem ale Mice, Thyroid, Follicular-Cell Adenoma ................................................................................ F-45 F.1.17.1. Summary Table of BMDS Modeling Results ................................ F-45 F.1.17.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-46 F.1.17.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-46 F.1.18. National Toxicology Program (1982): Male Mice, Lung, Alveolar/Bronchiolar Ad enom a or Carcinoma............................................... F-48 F.1.18.1. Summary Table of BMDS Modeling Results ................................ F-48 F.1.18.2. Figure for Selected Model: Multistage Cancer, 2-Degree, Betas Restricted ≥ 0

......................................................................... F-49 F.1.18.3. Output File for Selected Model: Multistage Cancer, 2-Degree, B etas Restricted ≥ 0........................................................ F-49

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-v CONTENTS (continued)

F.1.19. National Toxicology Program (1982): Male Mice, Liver, Hepatocellular Adenom a or Carcinoma.......................................................... F-51 F.1.19.1. Summary Table of BMDS Modeling Results ................................ F-51 F.1.19.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-52 F.1.19.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-52 F.1.20. National Toxicology Program (2006): Liver, Cholangiocarcinom a.............. F-54 F.1.20.1. Summary Table of BMDS Modeling Results ................................ F-54 F.1.20.2. Figure for Selected Model: Multistage Cancer, 3-Degree, Betas Restricted ≥ 0

......................................................................... F-55 F.1.20.3. Output File for Selected Model: Multistage Cancer, 3-Degree, B etas Restricted ≥ 0........................................................ F-55 F.1.21. National Toxicology Program (2006): Liver, Hepatocellular Adenom a......................................................................................................... F-57 F.1.21.1. Summary Table of BMDS Modeling Results ................................ F-57 F.1.21.2. Figure for Selected Model: Multistage Cancer, 3-Degree, Betas Restricted ≥ 0

......................................................................... F-58 F.1.21.3. Output File for Selected Model: Multistage Cancer, 3-Degree, B etas Restricted ≥ 0........................................................ F-58 F.1.22. National Toxicology Program (200 6): Oral m ucosa, Squamous Cell Carcinoma....................................................................................................... F-60 F.1.22.1. Summary Table of BMDS Modeling Results ................................ F-60 F.1.22.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0, Bound Hit

...................................................... F-61 F.1.22.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0, Bound Hit ..................................... F-61 F.1.23. National Toxicology Program (2006): Pancreas, Adenoma or Carcinom a....................................................................................................... F-63 F.1.23.1. Summary Table of BMDS Modeling Results ................................ F-63 F.1.23.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-64 F.1.23.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-64 F.1.24. National Toxicology Program (2006): Lung, Cystic Keratinizing Epitheliom a..................................................................................................... F-66 F.1.24.1. Summary Table of BMDS Modeling Results ................................ F-66 F.1.24.2. Figure for Selected Model: Multistage Cancer, 2-Degree, Betas Restricted ≥ 0

......................................................................... F-67 F.1.24.3. Output File for Selected Model: Multistage Cancer, 2-Degree, B etas Restricted ≥ 0........................................................ F-67 F.1.25. Toth et al. (1978): 1YR, Liver, Tumors......................................................... F-69 F.1.25.1. Summary Table of BMDS Modeling Results ................................ F-69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-vi CONTENTS (continued)

F.1.25.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-70 F.1.25.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-70 F.2. ADMINISTERED DOSE BMDS RESULTS ............................................................ F-72 F.2.1. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate or Nasal Turbinates

................................................................. F-72 F.2.1.1. Summary Table of BMDS Modeling Results ................................ F-72 F.2.1.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-73 F.2.1.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-73 F.2.2. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Tongue

........................................................................................................ F-75 F.2.2.1. Summary Table of BMDS Modeling Results ................................ F-75 F.2.2.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-76 F.2.2.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-76 F.2.3. Kociba et al. (1978): Female. Adenoma of Adrenal Cortex.......................... F-78 F.2.3.1. Summary Table of BMDS Modeling Results ................................ F-78 F.2.3.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-79 F.2.3.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-79 F.2.4. Kociba et al. (1978): Female , Hepatocellular Adenom a(S) or Carcinoma(s)................................................................................................... F-81 F.2.4.1. Summary Table of BMDS Modeling Results ................................ F-81 F.2.4.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-82 F.2.4.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-82 F.2.5. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate or Nasal Turbinates

................................................................. F-84 F.2.5.1. Summary Table of BMDS Modeling Results ................................ F-84 F.2.5.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-85 F.2.5.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-85 F.2.6. Kociba et al. (1978): Fema le, Keratinizing Squamous Cell Carcinom a of Lung ......................................................................................... F-87 F.2.6.1. Summary Table of BMDS Modeling Results ................................ F-87

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-vii CONTENTS (continued)

F.2.6.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-88 F.2.6.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-88 F.2.7. National Toxicology Program (1982): Fem ale Rats, Subcutaneous Tissue, Fibrosarcoma ...................................................................................... F-90 F.2.7.1. Summary Table of BMDS Modeling Results ................................ F-90 F.2.7.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-91 F.2.7.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-91 F.2.8. National Toxicology Program ( 1982): Fem ale Rats, Liver, Neoplastic Nodule or Hepatocellular Carcinoma ........................................... F-93 F.2.8.1. Summary Table of BMDS Modeling Results ................................ F-93 F.2.8.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-94 F.2.8.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-94 F.2.9. National Toxicology Program ( 1982): Fem ale Rats, Adrenal, Cortical Adenoma, or Carcinoma or Adenoma, NOS .................................... F-96 F.2.9.1. Summary Table of BMDS Modeling Results ................................ F-96 F.2.9.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

......................................................................... F-97 F.2.9.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0........................................................ F-97 F.2.10. National Toxicology Program ( 1982): Fem ale Rats, Thyroid, Follicular-Cell Adenoma ................................................................................ F-99 F.2.10.1. Summary Table of BMDS Modeling Results ................................ F-99 F.2.10.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-100 F.2.10.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-100 F.2.11. National Toxicology Program (1982) : Male Rats, Liver, Neoplastic Nodule or Hepatocellular Carcinom a ........................................................... F-102 F.2.11.1. Summary Table of BMDS Modeling Results .............................. F-102 F.2.11.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-103 F.2.11.3. Output File for selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-103 F.2.12. National Toxicology Program (1982): Male Rats, Thyroid, Follicu lar-Cell Adenoma or Carcinoma........................................................ F-105 F.2.12.1. Summary Table of BMDS Modeling Results .............................. F-105

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-viii CONTENTS (continued)

F.2.12.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-106 F.2.12.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-106 F.2.13. National Toxicology Program (198 2): Male Rats, Adrenal cortex, Adenom a....................................................................................................... F-108 F.2.13.1. Summary Table of BMDS Modeling Results .............................. F-108 F.2.13.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-109 F.2.13.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-109 F.2.14. National Toxicology Program (198 2): Fem ale Mice, Subcutaneous Tissue, Fibrosarcoma .................................................................................... F-111 F.2.14.1. Summary Table of BMDS Modeling Results .............................. F-111 F.2.14.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-112 F.2.14.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-112 F.2.15. National Toxicology Program (198 2): Fem ale Mice, Hematopoietic System, Lymphoma ...................................................................................... F-114 F.2.15.1. Summary Table of BMDS Modeling Results .............................. F-114 F.2.15.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-115 F.2.15.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-115 F.2.16. National Toxicology Program ( 1982): Fem ale Mice, Liver, Hepatocellular Adenoma or Carcinoma........................................................ F-117 F.2.16.1. Summary Table of BMDS Modeling Results .............................. F-117 F.2.16.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-118 F.2.16.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-118 F.2.17. National Toxicology Program ( 1982): Fem ale Mice, Thyroid Follicular Cell Adenoma............................................................................... F-120 F.2.17.1. Summary Table of BMDS Modeling Results .............................. F-120 F.2.17.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-121 F.2.17.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-121 F.2.18. National Toxicology Program (1982): Male Mice, Lung, Alveolar/Bronchiolar Ad enom a or Carcinoma............................................. F-123 F.2.18.1. Summary Table of BMDS Modeling Results .............................. F-123

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-ix CONTENTS (continued)

F.2.18.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-124 F.2.18.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-124 F.2.19. National Toxicology Program (1982): Male Mice, Liver, Hepatocellular Adenom a or Carcinoma........................................................ F-126 F.2.19.1. Summary Table of BMDS Modeling Results .............................. F-126 F.2.19.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-127 F.2.19.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-127 F.2.20. National Toxicology Program (2006): Liver, Cholangiocarcinom a............ F-129 F.2.20.1. Summary Table of BMDS Modeling Results .............................. F-129 F.2.20.2. Figure for Selected Model: Multistage Cancer, 3-Degree, Betas Restricted ≥ 0

....................................................................... F-130 F.2.20.3. Output File for Selected Model: Multistage Cancer, 3-Degree, B etas Restricted ≥ 0...................................................... F-130 F.2.21. National Toxicology Program (2006): Liver, Hepatocellular Adenom a....................................................................................................... F-132 F.2.21.1. Summary Table of BMDS Modeling Results .............................. F-132 F.2.21.2. Figure for Selected Model: Multistage Cancer, 3-Degree, Betas Restricted ≥ 0

....................................................................... F-133 F.2.21.3. Output File for Selected Model: Multistage Cancer, 3-Degree, B etas Restricted ≥ 0...................................................... F-133 F.2.22. National Toxicology Program (200 6): Oral Mucosa, Squamous Cell Carcinom a..................................................................................................... F-135 F.2.22.1. Summary Table of BMDS Modeling Results .............................. F-135 F.2.22.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0, Bound Hit

.................................................... F-136 F.2.22.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0, Bound Hit ................................... F-136 F.2.23. National Toxicology Program (2006): Pancreas, Adenoma or Carcinom a..................................................................................................... F-138 F.2.23.1. Summary Table of BMDS Modeling Results .............................. F-138 F.2.23.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-139 F.2.23.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-139 F.2.24. National Toxicology Program (2006): Lung, Cystic Keratinizing Epitheliom a................................................................................................... F-141 F.2.24.1. Summary Table of BMDS Modeling Results .............................. F-141 F.2.24.2. Figure for Selected Model: Multistage Cancer, 2-Degree, Betas Restricted ≥ 0

....................................................................... F-142

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-x CONTENTS (continued)

F.2.24.3. Output File for Selected Model: Multistage Cancer, 2-Degree, B etas Restricted ≥ 0...................................................... F-142 F.2.25. Toth et al. (1978): 1YR, Liver, Tumors....................................................... F-144 F.2.25.1. Summary Table of BMDS Modeling Results .............................. F-144 F.2.25.2. Figure for Selected Model: Multistage Cancer, 1-Degree, Betas Restricted ≥ 0

....................................................................... F-145 F.2.25.3. Output File for Selected Model: Multistage Cancer, 1-Degree, B etas Restricted ≥ 0...................................................... F-145 F.3. HUMAN EQUIVALENT DOSES FO R 1, 5, AND 10% EXTRA RISK

................ F-148 F.4. REFERENCES ......................................................................................................... F-149

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-1 APPENDIX F. CANCER BENCHMARK DOS E MODELING 1 2 3 

## F.1. BLOOD SERUM BMDS RESULTS 4 

## F.1.1. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate 5 

## or Nasal Turbinates 6 

## F.1.1.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.94 0.82 31.56 3.2E+03 1.5E+03 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.15 0.99 30.17 7.5E+03 1.9E+03 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.03 1.00 29.93 1.1E+04 2.0E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-2 F.1.1.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2 3 

## F.1.1.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 4
5 6

==================================================================== 7 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 8 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_palate_nasal.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_palate_nasal.plt 10 Mon Nov 23 15:42:08 2009 11

==================================================================== 12 13 Source - Table 4 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the probability function is: 17 18 P[response] = background + (1-background)*[1-EXP( 19 -beta1*dose^1)] 20 21 The parameter betas are restricted to be positive 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 27 Total number of observations = 5 28 Total number of records with missing values = 1 29 Total number of parameters in model = 2 30 Total number of specified parameters = 0 31 Degree of polynomial = 1 32 33 34 Maximum number of iterations = 250 35 Relative Function Convergence has been set to: 1e-008 36 0 0.05 0.1 0.15 0.2

0 5000 10000 15000 20000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:42 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-3 Parameter Convergence has been set to: 1e-008 1 2 3 4 Default Initial Parameter Values 5 Background = 0 6 Beta(1) = 4.1047e-006 7 8 9 Asymptotic Correlation Matrix of Parameter Estimates 10 11 ( *** The model parameter(s) -Background 12 have been estimated at a boundary point, or have been specified by the user, 13 and do not appear in the correlation matrix ) 14 15 Beta(1) 16 17 Beta(1) 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0 * * * 26 Beta(1) 3.16499e-006 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -13.9385 4 36 Fitted model -14.782 1 1.68697 3 0.6398 37 Reduced model -20.2589 1 12.6409 3 0.005481 38 39 AIC: 31.5639 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0000 0.000 0.000 85 0.000 47 860.4590 0.0027 0.136 0.000 50 -0.369 48 3944.9299 0.0124 0.620 0.000 50 -0.793 49 21334.0000 0.0653 3.265 4.000 50 0.421 50 51 Chi^2 = 0.94 d.f. = 3 P-value = 0.8153 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 3175.47 63 64 BMDL = 1539.87 65 66 BMDU = 8231.22 67 68 Taken together, (1539.87, 8231.22) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-4 1 Multistage Cancer Slope Factor = 6.49406e-006 2 3 4 

## F.1.2. Kociba et al. (1978): Female, Stratifi ed Squamous Cell Carcinoma of Tongue 5 

## F.1.2.1. Summary Table of BMDS Modeling Results 6

7



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 1.50 0.47 47.93 3.4E+03 1.4E+03 betas restricted ≥ 0

Multistage cancer, 2-degree 2 1.50 0.47 47.93 3.4E+03 1.4E+03 betas restricted ≥ 0

Multistage cancer, 3-degree 2 1.50 0.47 47.93 3.4E+03 1.4E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
8 9 

## F.1.2.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 10

11

0 0.05 0.1 0.15

0 5000 10000 15000 20000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:42 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-5 F.1.2.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 1
2 3

==================================================================== 4 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_tongue.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_tongue.plt 7 Mon Nov 23 15:42:27 2009 8

==================================================================== 9 10 Source - Table 4 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background + (1-background)*[1-EXP( 16 -beta1*dose^1)] 17 18 The parameter betas are restricted to be positive 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 24 Total number of observations = 5 25 Total number of records with missing values = 1 26 Total number of parameters in model = 2 27 Total number of specified parameters = 0 28 Degree of polynomial = 1 29 30 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 Background = 0.00925136 39 Beta(1) = 2.49061e-006 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 Background Beta(1) 45 46 Background 1 -0.58 47 48 Beta(1) -0.58 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 Background 0.00510493 * * * 57 Beta(1) 2.99496e-006 * * * 58 59 * - Indicates that this value is not calculated. 60 61 62 63 Analysis of Deviance Table 64 65 Model Log(likelihood) # Param's Deviance Test d.f. P-value 66 Full model -21.1523 4 67 Fitted model -21.9667 2 1.6288 2 0.4429 68 Reduced model -24.1972 1 6.08976 3 0.1073 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-6 1 AIC: 47.9334 2 3 4 Goodness of Fit 5 Scaled 6 Dose Est._Prob. Expected Observed Size Residual 7

------------------------------------------------------------------------ 8 0.0000 0.0051 0.434 0.000 85 -0.660 9 860.4590 0.0077 0.383 1.000 50 1.000 10 3944.9299 0.0168 0.840 1.000 50 0.177 11 21334.0000 0.0667 3.334 3.000 50 -0.189 12 13 Chi^2 = 1.50 d.f. = 2 P-value = 0.4716 14 15 16 Benchmark Dose Computation 17 18 Specified effect = 0.01 19 20 Risk Type = Extra risk 21 22 Confidence level = 0.95 23 24 BMD = 3355.75 25 26 BMDL = 1432.78 27 28 BMDU = 19112.8 29 30 Taken together, (1432.78, 19112.8) is a 90 % two-sided confidence 31 interval for the BMD 32 33 Multistage Cancer Slope Factor = 6.97946e-006 34 35 36 

## F.1.3. Kociba et al. (1978): Female, Adenoma of Adrenal Cortex 37 

## F.1.3.1. Summary Table of BMDS Modeling Results 38

39



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 1.09 0.78 52.49 1.8E+03 1.0E+03 betas restricted ≥ 0

Multistage cancer, 2-degree 3 1.09 0.78 52.49 1.8E+03 1.0E+03 betas restricted ≥ 0

Multistage cancer, 3-degree 3 1.09 0.78 52.49 1.8E+03 1.0E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
40 41 42

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-7 F.1.3.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.3.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adre_adenoma.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adre_adenoma.plt 11 Mon Nov 23 15:42:49 2009 12

==================================================================== 13 14 Source - Table 5 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 5 29 Total number of records with missing values = 1 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2

0 5000 10000 15000 20000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:42 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-8 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.00493749 8 Beta(1) = 4.83499e-006 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 5.60622e-006 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -24.6514 4 38 Fitted model -25.2438 1 1.18487 3 0.7566 39 Reduced model -31.4904 1 13.6781 3 0.003378 40 41 AIC: 52.4876 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 85 0.000 49 860.4590 0.0048 0.241 0.000 50 -0.492 50 3944.9299 0.0219 1.094 2.000 50 0.876 51 21334.0000 0.1127 5.636 5.000 50 -0.285 52 53 Chi^2 = 1.09 d.f. = 3 P-value = 0.7793 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 1792.71 65 66 BMDL = 1020.18 67 68 BMDU = 3628.63 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-9 Taken together, (1020.18, 3628.63) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 9.8022e-006 4 5 6 

## F.1.4. Kociba et al. (1978): Female, Hepato cellular A denoma(s) or Carcinoma(s) 7 

## F.1.4.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 2.81 0.24 143.26 3.9E+02 2.8E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 2.81 0.24 143.26 3.9E+02 2.8E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 2.81 0.24 143.26 3.9E+02 2.8E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11 

## F.1.4.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 12

13

0 0.1 0.2 0.3 0.4 0.5 0.6

0 5000 10000 15000 20000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:43 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-10 F.1.4.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 1
2 3

==================================================================== 4 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_liver_ad_carc.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_liver_ad_carc.plt 7 Mon Nov 23 15:43:10 2009 8

==================================================================== 9 10 Source - Table 1 in Goodman and Sauer 1992 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background + (1-background)*[1-EXP( 16 -beta1*dose^1)] 17 18 The parameter betas are restricted to be positive 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 24 Total number of observations = 4 25 Total number of records with missing values = 0 26 Total number of parameters in model = 2 27 Total number of specified parameters = 0 28 Degree of polynomial = 1 29 30 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 Background = 0.0400267 39 Beta(1) = 2.26421e-005 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 Background Beta(1) 45 46 Background 1 -0.51 47 48 Beta(1) -0.51 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 Background 0.022147 * * * 57 Beta(1) 2.60216e-005 * * * 58 59 * - Indicates that this value is not calculated. 60 61 62 63 Analysis of Deviance Table 64 65 Model Log(likelihood) # Param's Deviance Test d.f. P-value 66 Full model -68.2561 4 67 Fitted model -69.6304 2 2.74863 2 0.253 68 Reduced model -89.1983 1 41.8843 3 <.0001 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-11 1 AIC: 143.261 2 3 4 Goodness of Fit 5 Scaled 6 Dose Est._Prob. Expected Observed Size Residual 7

------------------------------------------------------------------------ 8 0.0000 0.0221 1.905 2.000 86 0.070 9 852.5169 0.0436 2.180 1.000 50 -0.817 10 3941.9464 0.1175 5.874 9.000 50 1.373 11 21246.0000 0.4374 19.685 18.000 45 -0.506 12 13 Chi^2 = 2.81 d.f. = 2 P-value = 0.2449 14 15 16 Benchmark Dose Computation 17 18 Specified effect = 0.01 19 20 Risk Type = Extra risk 21 22 Confidence level = 0.95 23 24 BMD = 386.23 25 26 BMDL = 276.228 27 28 BMDU = 577.635 29 30 Taken together, (276.228, 577.635) is a 90 % two-sided confidence 31 interval for the BMD 32 33 Multistage Cancer Slope Factor = 3.6202e-005 34 35 36 

## F.1.5. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate 37 

## or Nasal Turbinates 38 

## F.1.5.1. Summary Table of BMDS Modeling Results 39

40



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.94 0.82 31.56 3.2E+03 1.5E+03 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.15 0.99 30.17 7.5E+03 1.9E+03 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.03 1.00 29.93 1.1E+04 2.0E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
41 42

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-12 F.1.5.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.5.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_nasal.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_nasal.plt 11 Mon Nov 23 15:43:31 2009 12

==================================================================== 13 14 Source - Table 5 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2

0 5000 10000 15000 20000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:43 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-13 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 7.11589e-005 9 Beta(1) = 4.0351e-006 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(1) 19 20 Beta(1) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 4.0463e-006 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -18.7562 4 39 Fitted model -18.9547 1 0.397016 3 0.9409 40 Reduced model -24.1972 1 10.882 3 0.01238 41 42 AIC: 39.9093 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0000 0.000 0.000 86 0.000 50 852.5169 0.0034 0.172 0.000 50 -0.416 51 3941.9464 0.0158 0.791 1.000 50 0.237 52 21246.0000 0.0824 4.036 4.000 49 -0.019 53 54 Chi^2 = 0.23 d.f. = 3 P-value = 0.9728 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.01 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 2483.84 66 67 BMDL = 1289.34 68 69 BMDU = 5762.51 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-14 1 Taken together, (1289.34, 5762.51) is a 90 % two-sided confidence 2 interval for the BMD 3 4 Multistage Cancer Slope Factor = 7.7559e-006 5 6 7 

## F.1.6. Kociba et al. (1978): Female, Keratini z ing Squamous Cell Carcinoma of Lung 8 

## F.1.6.1. Summary Table of BMDS Modeling Results 9

10



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 1.75 0.63 45.30 1.7E+03 9.8E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.28 0.96 42.74 5.5E+03 1.5E+03 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.05 1.00 42.29 8.6E+03 1.7E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
11 12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-15 F.1.6.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.6.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_kera_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_kera_carc.plt 11 Mon Nov 23 15:43:52 2009 12

==================================================================== 13 14 Source - Table 5 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3

0 5000 10000 15000 20000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:43 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-16 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 7.61927e-006 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 5.80969e-006 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -20.0957 4 38 Fitted model -21.6489 1 3.10635 3 0.3755 39 Reduced model -31.4904 1 22.7894 3 <.0001 40 41 AIC: 45.2978 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 86 0.000 49 852.5169 0.0049 0.247 0.000 50 -0.498 50 3941.9464 0.0226 1.132 0.000 50 -1.076 51 21246.0000 0.1161 5.690 7.000 49 0.584 52 53 Chi^2 = 1.75 d.f. = 3 P-value = 0.6263 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 1729.93 65 66 BMDL = 984.302 67 68 BMDU = 3461.69 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-17 Taken together, (984.302, 3461.69) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 1.01595e-005 4 5 6 

## F.1.7. National Toxicology Program (1982): Female Rat, Subcutaneous Tissue. 7 

## Fibrosarcoma 8 

## F.1.7.1. Summary Table of BMDS Modeling Results 9

10



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
11 12 

## F.1.7.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 13

14

0 0.05 0.1 0.15 0.2

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:44 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-18 F.1.7.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 1
2 3

==================================================================== 4 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_sub_fibro.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_sub_fibro.plt 7 Mon Nov 23 15:44:12 2009 8

==================================================================== 9 10 Source - Table 10 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background + (1-background)*[1-EXP( 16 -beta1*dose^1)] 17 18 The parameter betas are restricted to be positive 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 24 Total number of observations = 4 25 Total number of records with missing values = 0 26 Total number of parameters in model = 2 27 Total number of specified parameters = 0 28 Degree of polynomial = 1 29 30 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 Background = 0.026791 39 Beta(1) = 3.88561e-006 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 Background Beta(1) 45 46 Background 1 -0.63 47 48 Beta(1) -0.63 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 Background 0.0149169 * * * 57 Beta(1) 5.91146e-006 * * * 58 59 * - Indicates that this value is not calculated. 60 61 62 63 Analysis of Deviance Table 64 65 Model Log(likelihood) # Param's Deviance Test d.f. P-value 66 Full model -33.5998 4 67 Fitted model -35.6885 2 4.17734 2 0.1239 68 Reduced model -37.7465 1 8.29346 3 0.04032 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-19 1 AIC: 75.3769 2 3 4 Goodness of Fit 5 Scaled 6 Dose Est._Prob. Expected Observed Size Residual 7

------------------------------------------------------------------------ 8 0.0000 0.0149 1.119 0.000 75 -1.066 9 1072.2652 0.0211 1.057 2.000 50 0.927 10 3111.2349 0.0329 1.643 3.000 50 1.076 11 16207.0000 0.1049 5.141 4.000 49 -0.532 12 13 Chi^2 = 3.44 d.f. = 2 P-value = 0.1795 14 15 16 Benchmark Dose Computation 17 18 Specified effect = 0.01 19 20 Risk Type = Extra risk 21 22 Confidence level = 0.95 23 24 BMD = 1700.14 25 26 BMDL = 751.001 27 28 BMDU = 1.77581e+009 29 30 Taken together, (751.001, 1.77581e+009) is a 90 % two-sided confidence 31 interval for the BMD 32 33 Multistage Cancer Slope Factor = 1.33156e-005 34 35 36 

## F.1.8. National Toxicology Program (1982): Fema le Rat, Liver, Neoplastic Nodule or 37 

## Hepatocellular Carcinoma 38 

## F.1.8.1. Summary Table of BMDS Modeling Results 39

40



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.80 0.22 135.20 6.4E+02 4.0E+02 betas restricted ≥ 0 Multistage cancer, 2-degree 3 0.13 0.49 133.45 3.0E+03 4.8E+02 betas restricted ≥ 0
Multistage cancer, 3-degree 3 0.02 0.24 135.44 3.9E+03 4.8E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
41 42 43 44

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-20 F.1.8.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.8.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_liver_nod.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_liver_nod.plt 11 Mon Nov 23 15:45:38 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:45 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-21 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0 9 Beta(1) = 4.03747e-006 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(1) 19 20 Beta(1) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 3.00492e-006 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -11.3484 4 39 Fitted model -12.0545 1 1.41226 3 0.7027 40 Reduced model -15.9189 1 9.14109 3 0.02747 41 42 AIC: 26.109 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0000 0.000 0.000 74 0.000 50 1071.8576 0.0032 0.161 0.000 50 -0.402 51 3115.7313 0.0093 0.466 0.000 50 -0.686 52 16272.0000 0.0477 2.386 3.000 50 0.407 53 54 Chi^2 = 0.80 d.f. = 3 P-value = 0.8501 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.01 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 3344.63 66 67 BMDL = 1472.42 68 69 BMDU = 10322.4 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-22 1 Taken together, (1472.42, 10322.4) is a 90 % two-sided confidence 2 interval for the BMD 3 4 Multistage Cancer Slope Factor = 6.79156e-006 5 6 7 

## F.1.9. National Toxicology Program (1982): Fema le Rat, Adrenal, Cortical Adenoma, or 8 

## Carcinoma or Adenoma, NOS 9 

## F.1.9.1. Summary Table of BMDS Modeling Results 10

11



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 2.18 0.34 203.83 8.8E+02 4.4E+02 betas restricted ≥ 0 Multistage cancer, 2-degree 2 1.51 0.47 203.03 3.6E+03 4.9E+02 betas restricted ≥ 0
Multistage cancer, 3-degree 2 1.37 0.51 202.87 5.9E+03 5.0E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
12 13 

## F.1.9.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 14

15

0 0.1 0.2 0.3 0.4 0.5

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:44 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-23 F.1.9.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 1
2 3

==================================================================== 4 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 5 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adre_cort_ad_carc.(d) 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adre_cort_ad_carc.plt 7 Mon Nov 23 15:44:55 2009 8

==================================================================== 9 10 Source - Table 10 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = background + (1-background)*[1-EXP( 16 -beta1*dose^1)] 17 18 The parameter betas are restricted to be positive 19 20 21 Dependent variable = Mean 22 Independent variable = Dose 23 24 Total number of observations = 4 25 Total number of records with missing values = 0 26 Total number of parameters in model = 2 27 Total number of specified parameters = 0 28 Degree of polynomial = 1 29 30 31 Maximum number of iterations = 250 32 Relative Function Convergence has been set to: 1e-008 33 Parameter Convergence has been set to: 1e-008 34 35 36 37 Default Initial Parameter Values 38 Background = 0.134119 39 Beta(1) = 1.27888e-005 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 Background Beta(1) 45 46 Background 1 -0.54 47 48 Beta(1) -0.54 1 49 50 51 52 Parameter Estimates 53 54 95.0% Wald Confidence Interval 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 56 Background 0.139831 * * * 57 Beta(1) 1.14475e-005 * * * 58 59 * - Indicates that this value is not calculated. 60 61 62 63 Analysis of Deviance Table 64 65 Model Log(likelihood) # Param's Deviance Test d.f. P-value 66 Full model -98.7282 4 67 Fitted model -99.9133 2 2.37035 2 0.3057 68 Reduced model -102.201 1 6.94636 3 0.07363 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-24 1 AIC: 203.827 2 3 4 Goodness of Fit 5 Scaled 6 Dose Est._Prob. Expected Observed Size Residual 7

------------------------------------------------------------------------ 8 0.0000 0.1398 10.208 11.000 73 0.267 9 1072.2652 0.1503 7.366 9.000 49 0.653 10 3111.2349 0.1699 8.326 5.000 49 -1.265 11 16207.0000 0.2855 13.132 14.000 46 0.283 12 13 Chi^2 = 2.18 d.f. = 2 P-value = 0.3363 14 15 16 Benchmark Dose Computation 17 18 Specified effect = 0.01 19 20 Risk Type = Extra risk 21 22 Confidence level = 0.95 23 24 BMD = 877.947 25 26 BMDL = 443.554 27 28 BMDU = 6.93624e+008 29 30 Taken together, (443.554, 6.93624e+008) is a 90 % two-sided confidence 31 interval for the BMD 32 33 Multistage Cancer Slope Factor = 2.25452e-005 34 35 36 

## F.1.10. National Toxicology Program (1982): Fema le Rat, Thyroid, Follicular-Cell 37 

## Adenoma 38 

## F.1.10.1. Summary Table of BMDS Modeling Results 39

40



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 1.13 0.57 92.41 1.8E+03 8.5E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 0.62 0.74 91.75 5.2E+03 9.2E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 0.52 0.77 91.63 7.5E+03 9.4E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
41 42

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-25 F.1.10.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.10.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_thy_ad.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_thy_ad.plt 11 Mon Nov 23 15:45:17 2009 12

==================================================================== 13 14 Source - Table 10 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2 0.25

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:45 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-26 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.0282954 9 Beta(1) = 6.36609e-006 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.54 17 18 Beta(1) -0.54 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.0332349 * * * 27 Beta(1) 5.46313e-006 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -43.5264 4 37 Fitted model -44.2066 2 1.36031 2 0.5065 38 Reduced model -46.2299 1 5.40699 3 0.1443 39 40 AIC: 92.4132 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0332 2.426 3.000 73 0.375 48 1072.2652 0.0389 1.750 2.000 45 0.193 49 3111.2349 0.0495 2.427 1.000 49 -0.939 50 16207.0000 0.1152 5.412 6.000 47 0.269 51 52 Chi^2 = 1.13 d.f. = 2 P-value = 0.5677 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 1839.67 64 65 BMDL = 846.279 66 67 BMDU = 11586.6 68 69 Taken together, (846.279, 11586.6) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-27 interval for the BMD 1 2 Multistage Cancer Slope Factor = 1.18164e-005 3 4 5 

## F.1.11. National Toxicology Program (1982): Ma le Rat, Liver, Neoplastic Nodule or 6 

## Hepatocellular Carcinoma 7 

## F.1.11.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.80 0.22 135.20 6.4E+02 4.0E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.13 0.49 133.45 3.0E+03 4.8E+02 betas restricted ≥ 0

<ultistage cancer, 3-degree 3 0.02 0.24 135.44 3.9E+03 4.8E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BMDS goodness-of-fit criteria b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-28 F.1.11.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.11.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_liver_nod.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_liver_nod.plt 11 Mon Nov 23 15:45:38 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:45 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-29 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0 9 Beta(1) = 4.03747e-006 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(1) 19 20 Beta(1) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 3.00492e-006 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -11.3484 4 39 Fitted model -12.0545 1 1.41226 3 0.7027 40 Reduced model -15.9189 1 9.14109 3 0.02747 41 42 AIC: 26.109 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0000 0.000 0.000 74 0.000 50 1071.8576 0.0032 0.161 0.000 50 -0.402 51 3115.7313 0.0093 0.466 0.000 50 -0.686 52 16272.0000 0.0477 2.386 3.000 50 0.407 53 54 Chi^2 = 0.80 d.f. = 3 P-value = 0.8501 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.01 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 3344.63 66 67 BMDL = 1472.42 68 69 BMDU = 10322.4 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-30 1 Taken together, (1472.42, 10322.4) is a 90 % two-sided confidence 2 interval for the BMD 3 4 Multistage Cancer Slope Factor = 6.79156e-006 5 6 7 

## F.1.12. National Toxicology Program (1982): Ma le Ra, Thyroid, Follicula r-Cell Adenoma 8 

## or Carcinoma 9 

## F.1.12.1. Summary Table of BMDS Modeling Results 10

11



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 5.73 0.06 149.25 6.6E+02 3.8E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 5.73 0.06 149.25 6.6E+02 3.8E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 5.73 0.06 149.25 6.6E+02 3.8E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-31 F.1.12.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.12.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_thyroid.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_thyroid.plt 11 Mon Nov 23 15:45:59 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:45 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-32 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.0767848 9 Beta(1) = 1.11362e-005 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.62 17 18 Beta(1) -0.62 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.0527729 * * * 27 Beta(1) 1.52871e-005 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -69.5946 4 37 Fitted model -72.6245 2 6.05993 2 0.04832 38 Reduced model -77.5267 1 15.8643 3 0.001209 39 40 AIC: 149.249 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0528 3.641 1.000 69 -1.422 48 1071.8576 0.0682 3.272 5.000 48 0.990 49 3115.7313 0.0968 4.842 8.000 50 1.510 50 16272.0000 0.2614 13.069 11.000 50 -0.666 51 52 Chi^2 = 5.73 d.f. = 2 P-value = 0.0571 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 657.439 64 65 BMDL = 380.166 66 67 BMDU = 1571.51 68 69 Taken together, (380.166, 1571.51) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-33 interval for the BMD 1 2 Multistage Cancer Slope Factor = 2.63043e-005 3 4 5 

## F.1.13. National Toxicology Program (1982): Male Rat, Adrenal Cortex, Adenoma 6 

## F.1.13.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 5.55 0.06 199.31 2.2E+03 6.7E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 5.55 0.06 199.31 2.2E+03 6.7E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 5.55 0.06 199.31 2.2E+03 6.7E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-34 F.1.13.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.13.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adre_cort.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adre_cort.plt 11 Mon Nov 23 15:46:20 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:46 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-35 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.16365 8 Beta(1) = 2.66257e-006 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.61 16 17 Beta(1) -0.61 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.146024 * * * 26 Beta(1) 4.6499e-006 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -94.8672 4 36 Fitted model -97.6531 2 5.57181 2 0.06167 37 Reduced model -98.0432 1 6.35197 3 0.09569 38 39 AIC: 199.306 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.1460 10.514 6.000 72 -1.506 47 1071.8576 0.1503 7.513 9.000 50 0.588 48 3115.7313 0.1583 7.757 12.000 49 1.661 49 16272.0000 0.2083 10.204 9.000 49 -0.424 50 51 Chi^2 = 5.55 d.f. = 2 P-value = 0.0623 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 2161.41 63 64 BMDL = 665.411 65 66 67 BMDU did not converge for BMR = 0.010000 68 BMDU calculation failed 69 BMDU = Inf 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-36 1 2 

## F.1.14. National Toxicology Program (1982): Female Mice, Subcutaneous Tissue, 3 

## Fibrosarcoma 4 

## F.1.14.1. Summary Table of BMDS Modeling Results 5

6



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistag e cancer, 1-degree b 

### 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
7 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-37 F.1.14.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.14.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_subcu_fibro.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_subcu_fibro.plt 11 Mon Nov 23 15:46:40 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2 0.25

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:46 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-38 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.0104441 9 Beta(1) = 5.78849e-006 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.55 17 18 Beta(1) -0.55 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.0124215 * * * 27 Beta(1) 5.43453e-006 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -30.9876 4 37 Fitted model -31.0699 2 0.16463 2 0.921 38 Reduced model -34.3291 1 6.68308 3 0.08272 39 40 AIC: 66.1398 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0124 0.919 1.000 74 0.085 48 1063.6377 0.0181 0.906 1.000 50 0.100 49 3184.3353 0.0294 1.410 1.000 48 -0.350 50 17406.0000 0.1016 4.773 5.000 47 0.110 51 52 Chi^2 = 0.15 d.f. = 2 P-value = 0.9269 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 1849.35 64 65 BMDL = 916.028 66 67 BMDU = 6164.32 68 69 Taken together, (916.028, 6164.32) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-39 interval for the BMD 1 2 Multistage Cancer Slope Factor = 1.09167e-005 3 4 5 

## F.1.15. National Toxicology Program (1982): Female Mice, Hematopoietic S ystem, 6 

## Lymphoma 7 

## F.1.15.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistag e cancer, 1-degree b 

### 2 0.05 0.98 261.45 6.2E+02 3.3E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 1 0.03 0.87 263.43 9.3E+02 3.3E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 1 0.03 0.87 263.43 9.3E+02 3.3E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BMDS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-40 F.1.15.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.15.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_f_lymphoma.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_f_lymphoma.plt 11 Mon Nov 23 15:47:00 2009 12

==================================================================== 13 14 Table 15 page 64 Hematopoietic System Lymphoma or Leukemia 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0.1 0.2 0.3 0.4 0.5 0.6

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:47 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-41 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.234156 9 Beta(1) = 1.645e-005 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.54 17 18 Beta(1) -0.54 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.236108 * * * 27 Beta(1) 1.61681e-005 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -128.699 4 37 Fitted model -128.723 2 0.0471776 2 0.9767 38 Reduced model -131.412 1 5.42487 3 0.1432 39 40 AIC: 261.446 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.2361 17.472 18.000 74 0.145 48 1063.6377 0.2491 12.457 12.000 50 -0.149 49 3184.3353 0.2744 13.173 13.000 48 -0.056 50 17406.0000 0.4235 19.904 20.000 47 0.028 51 52 Chi^2 = 0.05 d.f. = 2 P-value = 0.9767 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 621.617 64 65 BMDL = 330.742 66 67 BMDU = 2332.7 68 69 Taken together, (330.742, 2332.7 ) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-42 interval for the BMD 1 2 Multistage Cancer Slope Factor = 3.0235e-005 3 4 5 

## F.1.16. National Toxicology Program (1982): Female Mice, Liver, Hepatocellular 6 

## Adenoma or Carcinoma 7 

## F.1.16.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 2.15 0.34 155.21 8.1E+02 4.5E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 2.15 0.34 155.21 8.1E+02 4.5E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 2.15 0.34 155.21 8.1E+02 4.5E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-43 F.1.16.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2 3 

## F.1.16.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 4
5 6

==================================================================== 7 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 8 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_f_liv_aden_carc.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_f_liv_aden_carc.plt 10 Mon Nov 23 15:47:20 2009 11

==================================================================== 12 13 0 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the probability function is: 17 18 P[response] = background + (1-background)*[1-EXP( 19 -beta1*dose^1)] 20 21 The parameter betas are restricted to be positive 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 27 Total number of observations = 4 28 Total number of records with missing values = 0 29 Total number of parameters in model = 2 30 Total number of specified parameters = 0 31 Degree of polynomial = 1 32 33 34 Maximum number of iterations = 250 35 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:47 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-44 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 Background = 0.0808715 7 Beta(1) = 1.07435e-005 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 Background Beta(1) 13 14 Background 1 -0.57 15 16 Beta(1) -0.57 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 Background 0.0691337 * * * 25 Beta(1) 1.24516e-005 * * * 26 27 * - Indicates that this value is not calculated. 28 29 30 31 Analysis of Deviance Table 32 33 Model Log(likelihood) # Param's Deviance Test d.f. P-value 34 Full model -74.5177 4 35 Fitted model -75.603 2 2.17074 2 0.3378 36 Reduced model -79.6703 1 10.3053 3 0.01614 37 38 AIC: 155.206 39 40 41 Goodness of Fit 42 Scaled 43 Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45 0.0000 0.0691 5.047 3.000 73 -0.944 46 1063.6377 0.0814 4.069 6.000 50 0.999 47 3184.3353 0.1053 5.055 6.000 48 0.444 48 17406.0000 0.2505 11.774 11.000 47 -0.261 49 50 Chi^2 = 2.15 d.f. = 2 P-value = 0.3405 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 0.01 56 57 Risk Type = Extra risk 58 59 Confidence level = 0.95 60 61 BMD = 807.155 62 63 BMDL = 448.599 64 65 BMDU = 2161.58 66 67 Taken together, (448.599, 2161.58) is a 90 % two-sided confidence 68 interval for the BMD 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-45 Multistage Cancer Slope Factor = 2.22916e-005 1 2 3 

## F.1.17. National Toxicology Program (1982): Fema le Mice, Thyroid, Follicular-Cell 4 

## Adenoma 5 

## F.1.17.1. Summary Table of BMDS Modeling Results 6

7



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.44 0.18 75.38 1.7E+03 7.5E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-46 F.1.17.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.17.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_f_thyroid_aden.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_f_thyroid_aden.plt 11 Mon Nov 23 15:47:40 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2 0.25

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:47 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-47 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.0202008 9 Beta(1) = 5.39488e-006 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.58 17 18 Beta(1) -0.58 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.0152512 * * * 27 Beta(1) 6.07986e-006 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -32.0017 4 37 Fitted model -34.3878 2 4.77223 2 0.09199 38 Reduced model -37.2405 1 10.4776 3 0.01491 39 40 AIC: 72.7756 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0153 1.052 0.000 69 -1.034 48 1063.6377 0.0216 1.080 3.000 50 1.868 49 3184.3353 0.0341 1.604 1.000 47 -0.485 50 17406.0000 0.1141 5.250 5.000 46 -0.116 51 52 Chi^2 = 4.81 d.f. = 2 P-value = 0.0904 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 1653.05 64 65 BMDL = 778.784 66 67 BMDU = 6460.82 68 69 Taken together, (778.784, 6460.82) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-48 interval for the BMD 1 2 Multistage Cancer Slope Factor = 1.28405e-005 3 4 5 

## F.1.18. National Toxicology Program (1982): Ma le Mice, Lung, Alveolar/Bronchiolar 6 

## Adenoma or Carcinoma 7 

## F.1.18.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree 2 4.87 0.09 168.35 3.5E+02 1.9E+02 betas restricted ≥ 0

Multistag e cancer, 2-degree b 

### 2 3.58 0.17 166.95 1.4E+03 2.3E+02 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.41 0.18 166.80 2.3E+03 2.3E+02 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-49 F.1.18.2. Figure for Selected Model: Multista ge Cancer, 2-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.18.3. Output File for Selected Model: Multis tage Can cer, 2-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc2_ngkgd_lung_aden_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc2_ngkgd_lung_aden_carc.plt 11 Mon Nov 23 15:48:02 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 3 31 Total number of specified parameters = 0 32 Degree of polynomial = 2 33 34 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 1000 2000 3000 4000 5000 6000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:48 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-50 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.086839 9 Beta(1) = 0 10 Beta(2) = 5.59843e-009 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 ( *** The model parameter(s) -Beta(1) 16 have been estimated at a boundary point, or have been specified by the user, 17 and do not appear in the correlation matrix ) 18 19 Background Beta(2) 20 21 Background 1 -0.46 22 23 Beta(2) -0.46 1 24 25 26 27 Parameter Estimates 28 29 95.0% Wald Confidence Interval 30 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 31 Background 0.0942375 * * * 32 Beta(1) 0 * * * 33 Beta(2) 5.31152e-009 * * * 34 35 * - Indicates that this value is not calculated. 36 37 38 39 Analysis of Deviance Table 40 41 Model Log(likelihood) # Param's Deviance Test d.f. P-value 42 Full model -79.5959 4 43 Fitted model -81.4737 2 3.75561 2 0.1529 44 Reduced model -85.3351 1 11.4782 3 0.009402 45 46 AIC: 166.947 47 48 49 Goodness of Fit 50 Scaled 51 Dose Est._Prob. Expected Observed Size Residual 52

------------------------------------------------------------------------ 53 0.0000 0.0942 6.691 10.000 71 1.344 54 420.0366 0.0951 4.564 2.000 48 -1.262 55 1239.6134 0.1016 4.877 4.000 48 -0.419 56 6117.5662 0.2575 12.876 13.000 50 0.040 57 58 Chi^2 = 3.58 d.f. = 2 P-value = 0.1673 59 60 61 Benchmark Dose Computation 62 63 Specified effect = 0.01 64 65 Risk Type = Extra risk 66 67 Confidence level = 0.95 68 69 BMD = 1375.56 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-51 1 BMDL = 225.385 2 3 BMDU = 2284.92 4 5 Taken together, (225.385, 2284.92) is a 90 % two-sided confidence 6 interval for the BMD 7 8 Multistage Cancer Slope Factor = 4.43686e-005 9 10 11 

## F.1.19. National Toxicology Program (1982): Ma le Mice, Liver, Hepatocellu lar Adenoma 12 

## or Carcinoma 13 

## F.1.19.1. Summary Table of BMDS Modeling Results 14

15



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 0.15 0.93 258.55 1.1E+02 7.5E+01 betas restricted ≥ 0

Multistage cancer, 2-degree 1 0.08 0.78 260.48 1.7E+02 7.5E+01 betas restricted ≥ 0

Multistage cancer, 3-degree 1 0.07 0.79 260.47 1.6E+02 7.5E+01 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
16 17

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-52 F.1.19.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.19.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_m_liver_aden_carc.(d) 10 Gnuplot Plotting File: 11 C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_mice_m_liver_aden_carc.plt 12 Mon Nov 23 15:48:23 2009 13

==================================================================== 14 15 0 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17 18 The form of the probability function is: 19 20 P[response] = background + (1-background)*[1-EXP( 21 -beta1*dose^1)] 22 23 The parameter betas are restricted to be positive 24 25 26 Dependent variable = Mean 27 Independent variable = Dose 28 29 Total number of observations = 4 30 Total number of records with missing values = 0 31 Total number of parameters in model = 2 32 Total number of specified parameters = 0 33 Degree of polynomial = 1 34 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 1000 2000 3000 4000 5000 6000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:48 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-53 1 2 Maximum number of iterations = 250 3 Relative Function Convergence has been set to: 1e-008 4 Parameter Convergence has been set to: 1e-008 5 6 7 8 Default Initial Parameter Values 9 Background = 0.201516 10 Beta(1) = 8.94392e-005 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 Background Beta(1) 16 17 Background 1 -0.53 18 19 Beta(1) -0.53 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0.204153 * * * 28 Beta(1) 8.75513e-005 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -127.199 4 38 Fitted model -127.274 2 0.151061 2 0.9273 39 Reduced model -135.589 1 16.7801 3 0.0007843 40 41 AIC: 258.549 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.2042 14.903 15.000 73 0.028 49 420.0366 0.2329 11.412 12.000 49 0.199 50 1239.6134 0.2860 14.014 13.000 49 -0.321 51 6117.5662 0.5342 26.709 27.000 50 0.083 52 53 Chi^2 = 0.15 d.f. = 2 P-value = 0.9278 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 114.794 65 66 BMDL = 74.9717 67 68 BMDU = 208.915 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-54 Taken together, (74.9717, 208.915) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 0.000133384 4 5 6 

## F.1.20. National Toxicology Program (2006 ): Liver, Cholangiocarcinoma 7 

## F.1.20.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree 5 20.87 0.00 138.46 5.2E+02 3.9E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 5 5.09 0.40 119.37 2.3E+03 1.6E+03 betas restricted ≥ 0

Multistage cancer, 3-degree b 

### 5 0.47 0.99 113.51 4.2E+03 2.3E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BMDS goodness-of-fit criteria b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-55 F.1.20.2. Figure for Selected Model: Multista ge Cancer, 3-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.20.3. Output File for Selected Model: Multis tage Can cer, 3-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc3_ngkgd_liv_cho-carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc3_ngkgd_liv_cho-carc.plt 11 Mon Nov 23 15:48:43 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 4 31 Total number of specified parameters = 0 32 Degree of polynomial = 3 33 34 35 0 0.1 0.2 0.3 0.4 0.5 0.6

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:48 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-56 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0 9 Beta(2) = 0 10 Beta(3) = 1.46324e-013 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 ( *** The model parameter(s) -Background -Beta(1) -Beta(2) 16 have been estimated at a boundary point, or have been specified by the user, 17 and do not appear in the correlation matrix ) 18 19 Beta(3) 20 21 Beta(3) 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 Background 0 * * * 30 Beta(1) 0 * * * 31 Beta(2) 0 * * * 32 Beta(3) 1.38296e-013 * * * 33 34 * - Indicates that this value is not calculated. 35 36 37 38 Analysis of Deviance Table 39 40 Model Log(likelihood) # Param's Deviance Test d.f. P-value 41 Full model -55.408 6 42 Fitted model -55.7539 1 0.691685 5 0.9834 43 Reduced model -96.9934 1 83.1708 5 <.0001 44 45 AIC: 113.508 46 47 48 Goodness of Fit 49 Scaled 50 Dose Est._Prob. Expected Observed Size Residual 51

------------------------------------------------------------------------ 52 0.0000 0.0000 0.000 0.000 49 0.000 53 1408.4504 0.0004 0.019 0.000 48 -0.136 54 3137.0446 0.0043 0.196 0.000 46 -0.444 55 5392.9593 0.0215 1.073 1.000 50 -0.071 56 9128.8027 0.0999 4.893 4.000 49 -0.426 57 16361.0000 0.4543 24.078 25.000 53 0.254 58 59 Chi^2 = 0.47 d.f. = 5 P-value = 0.9933 60 61 62 Benchmark Dose Computation 63 64 Specified effect = 0.01 65 66 Risk Type = Extra risk 67 68 Confidence level = 0.95 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-57 BMD = 4173.08 1 2 BMDL = 2277.15 3 4 BMDU = 4642.18 5 6 Taken together, (2277.15, 4642.18) is a 90 % two-sided confidence 7 interval for the BMD 8 9 Multistage Cancer Slope Factor = 4.39145e-006 10 11 12 

## F.1.21. National Toxicology Program (2006 ): Liver, Hepatocellu lar Adenoma 13 

## F.1.21.1. Summary Table of BMDS Modeling Results 14

15



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes
Multistage cancer, 1-degree 5 12.73 0.03 87.02 1.2E+03 8.0E+02 betas restricted ≥ 0 Multistage cancer, 2-degree 5 4.29 0.51 76.98 3.6E+03 2.4E+03 betas restricted ≥ 0 Multistag e cancer, 3-degree b 

### 5 1.32 0.93 72.78 5.6E+03 3.6E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
16 17

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-58 F.1.21.2. Figure for Selected Model: Multista ge Cancer, 3-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.21.3. Output File for Selected Model: Multis tage Can cer, 3-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc3_ngkgd_liv_hepat_ad.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc3_ngkgd_liv_hepat_ad.plt 11 Mon Nov 23 15:49:03 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 4 31 Total number of specified parameters = 0 32 Degree of polynomial = 3 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:49 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-59 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0 9 Beta(2) = 0 10 Beta(3) = 6.51095e-014 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 ( *** The model parameter(s) -Background -Beta(1) -Beta(2) 16 have been estimated at a boundary point, or have been specified by the user, 17 and do not appear in the correlation matrix ) 18 19 Beta(3) 20 21 Beta(3) 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 Background 0 * * * 30 Beta(1) 0 * * * 31 Beta(2) 0 * * * 32 Beta(3) 5.62766e-014 * * * 33 34 * - Indicates that this value is not calculated. 35 36 37 38 Analysis of Deviance Table 39 40 Model Log(likelihood) # Param's Deviance Test d.f. P-value 41 Full model -34.4075 6 42 Fitted model -35.3908 1 1.96651 5 0.8538 43 Reduced model -56.3333 1 43.8515 5 <.0001 44 45 AIC: 72.7815 46 47 48 Goodness of Fit 49 Scaled 50 Dose Est._Prob. Expected Observed Size Residual 51

------------------------------------------------------------------------ 52 0.0000 0.0000 0.000 0.000 49 0.000 53 1408.4504 0.0002 0.008 0.000 48 -0.087 54 3137.0446 0.0017 0.080 0.000 46 -0.283 55 5392.9593 0.0088 0.439 0.000 50 -0.666 56 9128.8027 0.0419 2.054 1.000 49 -0.751 57 16361.0000 0.2184 11.577 13.000 53 0.473 58 59 Chi^2 = 1.32 d.f. = 5 P-value = 0.9330 60 61 62 Benchmark Dose Computation 63 64 Specified effect = 0.01 65 66 Risk Type = Extra risk 67 68 Confidence level = 0.95 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-60 BMD = 5631.42 1 2 BMDL = 3596.03 3 4 BMDU = 6597.97 5 6 Taken together, (3596.03, 6597.97) is a 90 % two-sided confidence 7 interval for the BMD 8 9 Multistage Cancer Slope Factor = 2.78084e-006 10 11 12 

## F.1.22. National Toxicology Program (2006): Oral mucosa, Squamous Cell Carcinoma 13 

## F.1.22.1. Summary Table of BMDS Modeling Results 14

15



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

Multistage cancer, 1-degree 4 4.15 0.39 125.48 4.8E+00 3.0E+00 betas restricted ≥ 0
Multistage cancer, 2-degree b 

### 4 2.83 0.59 123.25 1.6E+01 3.8E+00 betas restricted ≥ 0, bound hit Multistage cancer, 3-degree 4 2.83 0.59 123.25 1.6E+01 3.8E+00 betas restricted ≥ 0, bound hit

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.

16 17

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-61 F.1.22.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0, 1 

## Bound Hit 2

3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:11 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

4 5 6 

## F.1.22.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0, 7 

## Bound Hit 8
9 10

==================================================================== 11 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 12 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_oral_carc.(d) 13 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_oral_carc.plt 14 Mon Nov 23 15:11:37 2009 15

==================================================================== 16 17 0 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 19 20 The form of the probability function is: 21 22 P[response] = background + (1-background)*[1-EXP( 23 -beta1*dose^1)] 24 25 The parameter betas are restricted to be positive 26 27 28 Dependent variable = Mean 29 Independent variable = Dose 30 31 Total number of observations = 6 32 Total number of records with missing values = 0 33 Total number of parameters in model = 2 34 Total number of specified parameters = 0 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-62 Degree of polynomial = 1 1 2 3 Maximum number of iterations = 250 4 Relative Function Convergence has been set to: 1e-008 5 Parameter Convergence has been set to: 1e-008 6 7 8 9 Default Initial Parameter Values 10 Background = 0.00607545 11 Beta(1) = 0.00265195 12 13 14 Asymptotic Correlation Matrix of Parameter Estimates 15 16 Background Beta(1) 17 18 Background 1 -0.6 19 20 Beta(1) -0.6 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0.0171416 * * * 29 Beta(1) 0.00211536 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -57.5353 6 39 Fitted model -60.7418 2 6.41293 4 0.1704 40 Reduced model -67.7782 1 20.4858 5 0.001013 41 42 AIC: 125.484 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0171 0.840 1.000 49 0.176 50 2.1400 0.0216 1.036 2.000 48 0.958 51 7.1400 0.0319 1.466 1.000 46 -0.391 52 15.7000 0.0492 2.462 0.000 50 -1.609 53 32.9000 0.0832 4.078 4.000 49 -0.040 54 71.4000 0.1549 8.211 10.000 53 0.679 55 56 Chi^2 = 4.15 d.f. = 4 P-value = 0.3855 57 58 59 Benchmark Dose Computation 60 61 Specified effect = 0.01 62 63 Risk Type = Extra risk 64 65 Confidence level = 0.95 66 67 BMD = 4.75111 68 69 BMDL = 2.9556 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-63 1 BMDU = 9.19454 2 3 Taken together, (2.9556 , 9.19454) is a 90 % two-sided confidence 4 interval for the BMD 5 6 Multistage Cancer Slope Factor = 0.0033834 7 8 9 

## F.1.23. National Toxicology Program (2006): Pancreas, Adenoma or Carcinoma 10 

## F.1.23.1. Summary Table of BMDS Modeling Results 11

12



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 5 3.39 0.64 29.37 5.8E+03 2.6E+03 betas restricted ≥ 0

Multistage cancer, 2-degree 5 1.36 0.93 27.06 8.0E+03 4.0E+03 betas restricted ≥ 0

Multistage cancer, 3-degree 5 0.64 0.99 25.97 9.6E+03 5.2E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
13 14

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-64 F.1.23.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.23.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_panc_ad_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_panc_ad_carc.plt 11 Mon Nov 23 15:49:45 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:49 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-65 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 3.46905e-006 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 1.73461e-006 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -11.4096 6 38 Fitted model -13.6863 1 4.55338 5 0.4728 39 Reduced model -16.7086 1 10.598 5 0.05996 40 41 AIC: 29.3726 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 48 0.000 49 1408.4504 0.0024 0.117 0.000 48 -0.343 50 3137.0446 0.0054 0.250 0.000 46 -0.501 51 5392.9593 0.0093 0.466 0.000 50 -0.686 52 9128.8027 0.0157 0.754 0.000 48 -0.875 53 16361.0000 0.0280 1.427 3.000 51 1.336 54 55 Chi^2 = 3.39 d.f. = 5 P-value = 0.6404 56 57 58 Benchmark Dose Computation 59 60 Specified effect = 0.01 61 62 Risk Type = Extra risk 63 64 Confidence level = 0.95 65 66 BMD = 5794 67 68 BMDL = 2550.9 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-66 BMDU = 18101.1 1 2 Taken together, (2550.9 , 18101.1) is a 90 % two-sided confidence 3 interval for the BMD 4 5 Multistage Cancer Slope Factor = 3.92019e-006 6 7 8 

## F.1.24. National Toxicology Program (2006): L ung, Cystic Keratiniz ing Epithelioma 9 

## F.1.24.1. Summary Table of BMDS Modeling Results 10

11



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree 5 10.52 0.06 64.03 1.9E+03 1.1E+03 betas restricted ≥ 0

Multistage cancer, 2-degree b 

### 5 4.30 0.51 56.94 4.6E+03 2.9E+03 betas restricted ≥ 0
Multistage cancer, 3-degree 5 2.03 0.84 53.56 6.6E+03 4.3E+03 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
12 13

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-67 F.1.24.2. Figure for Selected Model: Multista ge Cancer, 2-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.24.3. Output File for Selected Model: Multis tage Can cer, 2-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc2_ngkgd_lung_epith.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc2_ngkgd_lung_epith.plt 11 Mon Nov 23 15:50:07 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 3 31 Total number of specified parameters = 0 32 Degree of polynomial = 2 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3

0 2000 4000 6000 8000 10000 12000 14000 16000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:50 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-68 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0 9 Beta(2) = 7.12912e-010 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background -Beta(1) 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(2) 19 20 Beta(2) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 0 * * * 30 Beta(2) 4.80115e-010 * * * 31 32 * - Indicates that this value is not calculated. 33 34 35 36 Analysis of Deviance Table 37 38 Model Log(likelihood) # Param's Deviance Test d.f. P-value 39 Full model -23.958 6 40 Fitted model -27.4714 1 7.02665 5 0.2187 41 Reduced model -40.2069 1 32.4976 5 <.0001 42 43 AIC: 56.9427 44 45 46 Goodness of Fit 47 Scaled 48 Dose Est._Prob. Expected Observed Size Residual 49

------------------------------------------------------------------------ 50 0.0000 0.0000 0.000 0.000 49 0.000 51 1408.4504 0.0010 0.046 0.000 48 -0.214 52 3137.0446 0.0047 0.217 0.000 46 -0.467 53 5392.9593 0.0139 0.679 0.000 49 -0.830 54 9128.8027 0.0392 1.922 0.000 49 -1.414 55 16361.0000 0.1206 6.271 9.000 52 1.162 56 57 Chi^2 = 4.30 d.f. = 5 P-value = 0.5067 58 59 60 Benchmark Dose Computation 61 62 Specified effect = 0.01 63 64 Risk Type = Extra risk 65 66 Confidence level = 0.95 67 68 BMD = 4575.28 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-69 BMDL = 2889.79 1 2 BMDU = 6187.18 3 4 Taken together, (2889.79, 6187.18) is a 90 % two-sided confidence 5 interval for the BMD 6 7 Multistage Cancer Slope Factor = 3.46046e-006 8 9 10 

## F.1.25. Toth et al. (1978): 1YR, Liver, Tumors 11 

## F.1.25.1. Summary Table of BMDS Modeling Results 12

13



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 1 1.10 0.29 155.74 2.0E+02 1.2E+02 betas restricted ≥ 0

Multistage cancer, 2-degree 1 1.10 0.29 155.74 2.0E+02 1.2E+02 betas restricted ≥ 0

Multistage cancer, 0-degree 0.29 -999.00 error error betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
14

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-70 F.1.25.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.1.25.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adr_cor_1yr.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\msc1_ngkgd_adr_cor_1yr.plt 11 Mon Nov 23 17:29:16 2009 12

==================================================================== 13 14 Table 1 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 3 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0.1 0.2 0.3 0.4 0.5 0.6

0 1000 2000 3000 4000 5000 6000 7000 8000Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

17:29 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-71 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.234944 9 Beta(1) = 4.90901e-005 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.55 17 18 Beta(1) -0.55 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.235288 * * * 27 Beta(1) 4.96192e-005 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -75.3127 3 37 Fitted model -75.8701 2 1.11477 1 0.291 38 Reduced model -79.4897 1 8.35401 2 0.01534 39 40 AIC: 155.74 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.2353 8.941 7.000 38 -0.742 48 315.4949 0.2472 10.875 13.000 44 0.743 49 7814.0188 0.4811 21.167 21.000 44 -0.050 50 51 Chi^2 = 1.10 d.f. = 1 P-value = 0.2932 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 202.549 63 64 BMDL = 115.257 65 66 BMDU = 555.609 67 68 Taken together, (115.257, 555.609) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-72 1 Multistage Cancer Slope Factor = 8.67623e-005 2 3 4 

## F.2. ADMINISTERED DOSE BMDS RESULTS 5 

## F.2.1. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate 6 

## or Nasal Turbinates 7 

## F.2.1.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.46 0.93 30.75 1.3E+01 6.5E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.04 1.00 29.96 3.5E+01 7.2E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.00 1.00 29.89 4.9E+01 7.3E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-73 F.2.1.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.1.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_palate_nasal.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_palate_nasal.plt 11 Mon Nov 23 15:04:28 2009 12

==================================================================== 13 14 Source - Table 4 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:04 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-74 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0.000858074 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 0.00074801 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -13.9385 4 38 Fitted model -14.3726 1 0.868297 3 0.8331 39 Reduced model -20.2589 1 12.6409 3 0.005481 40 41 AIC: 30.7452 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 85 0.000 49 1.0000 0.0007 0.037 0.000 50 -0.193 50 10.0000 0.0075 0.373 0.000 50 -0.613 51 100.0000 0.0721 3.604 4.000 50 0.217 52 53 Chi^2 = 0.46 d.f. = 3 P-value = 0.9276 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 13.4361 65 66 BMDL = 6.51522 67 68 BMDU = 34.829 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-75 Taken together, (6.51522, 34.829 ) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 0.00153487 4 5 6 

## F.2.2. Kociba et al. (1978): Female, Stratifi ed Squamous Cell Carcinoma of Tongue 7 

## F.2.2.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1 - 

### degree b 

### 2 1.59 0.45 48.37 1.7E+01 7.1E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 1.59 0.45 48.37 1.7E+01 7.1E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 1.59 0.45 48.37 1.7E+01 7.1E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-76 F.2.2.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.2.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_tongue.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_tongue.plt 11 Mon Nov 23 15:04:49 2009 12

==================================================================== 13 14 Source - Table 4 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:04 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-77 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.0113883 8 Beta(1) = 0.000508703 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.52 16 17 Beta(1) -0.52 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.00809154 * * * 26 Beta(1) 0.000576915 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -21.1523 4 36 Fitted model -22.1838 2 2.06309 2 0.3565 37 Reduced model -24.1972 1 6.08976 3 0.1073 38 39 AIC: 48.3677 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0081 0.688 0.000 85 -0.833 47 1.0000 0.0087 0.433 1.000 50 0.865 48 10.0000 0.0138 0.690 1.000 50 0.376 49 100.0000 0.0637 3.185 3.000 50 -0.107 50 51 Chi^2 = 1.59 d.f. = 2 P-value = 0.4506 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 17.4208 63 64 BMDL = 7.14637 65 66 BMDU = 3.20359e+006 67 68 Taken together, (7.14637, 3.20359e+006) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-78 1 Multistage Cancer Slope Factor = 0.00139931 2 3 4 

## F.2.3. Kociba et al. (1978): Female. Adenoma of Adrenal Cortex 5 

## F.2.3.1. Summary Table of BMDS Modeling Results 6

7



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 3.11 0.38 53.52 7.6E+00 4.3E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 3 3.11 0.38 53.52 7.6E+00 4.3E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 3 3.11 0.38 53.52 7.6E+00 4.3E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-79 F.2.3.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.3.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adre_adenoma.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adre_adenoma.plt 11 Mon Nov 23 15:05:10 2009 12

==================================================================== 13 14 Source - Table 5 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:05 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-80 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.00927818 8 Beta(1) = 0.00098105 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 0.00132464 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -24.6514 4 38 Fitted model -25.759 1 2.2152 3 0.529 39 Reduced model -31.4904 1 13.6781 3 0.003378 40 41 AIC: 53.5179 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 85 0.000 49 1.0000 0.0013 0.066 0.000 50 -0.257 50 10.0000 0.0132 0.658 2.000 50 1.666 51 100.0000 0.1241 6.203 5.000 50 -0.516 52 53 Chi^2 = 3.11 d.f. = 3 P-value = 0.3755 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 7.58722 65 66 BMDL = 4.31737 67 68 BMDU = 17.638 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-81 Taken together, (4.31737, 17.638 ) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 0.00231623 4 5 6 

## F.2.4. Kociba et al. (1978): Female, Hepato cellular A denoma(S) or Carcinoma(s) 7 

## F.2.4.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 6.77 0.03 146.20 1.8E+00 1.2E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 6.77 0.03 146.20 1.8E+00 1.2E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 6.77 0.03 146.20 1.8E+00 1.2E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-82 F.2.4.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.4.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_liver_ad_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_liver_ad_carc.plt 11 Mon Nov 23 15:05:31 2009 12

==================================================================== 13 14 Source - Table 1 in Goodman and Sauer 1992 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.1 0.2 0.3 0.4 0.5 0.6

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:05 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-83 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.0591902 8 Beta(1) = 0.00458516 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.47 16 17 Beta(1) -0.47 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.0328755 * * * 26 Beta(1) 0.00568299 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -68.2561 4 36 Fitted model -71.0993 2 5.68634 2 0.05824 37 Reduced model -89.1983 1 41.8843 3 <.0001 38 39 AIC: 146.199 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0329 2.827 2.000 86 -0.500 47 1.0000 0.0384 1.918 1.000 50 -0.676 48 10.0000 0.0863 4.315 9.000 50 2.359 49 100.0000 0.4521 20.346 18.000 45 -0.703 50 51 Chi^2 = 6.77 d.f. = 2 P-value = 0.0339 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 1.7685 63 64 BMDL = 1.22517 65 66 BMDU = 2.77641 67 68 Taken together, (1.22517, 2.77641) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-84 1 Multistage Cancer Slope Factor = 0.00816214 2 3 4 

## F.2.5. Kociba et al. (1978): Female, Stratified Squamous Cell Carcinoma of Hard Palate 5 

## or Nasal Turbinates 6 

## F.2.5.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.46 0.93 30.75 1.3E+01 6.5E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.04 1.00 29.96 3.5E+01 7.2E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.00 1.00 29.89 4.9E+01 7.3E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-85 F.2.5.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.5.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_nasal.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_nasal.plt 11 Mon Nov 23 15:05:50 2009 12

==================================================================== 13 14 Source - Table 5 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:05 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-86 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.00343283 9 Beta(1) = 0.000825276 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(1) 19 20 Beta(1) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 0.000953868 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -18.7562 4 39 Fitted model -19.0532 1 0.594034 3 0.8978 40 Reduced model -24.1972 1 10.882 3 0.01238 41 42 AIC: 40.1064 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0000 0.000 0.000 86 0.000 50 1.0000 0.0010 0.048 0.000 50 -0.218 51 10.0000 0.0095 0.475 1.000 50 0.766 52 100.0000 0.0910 4.458 4.000 49 -0.227 53 54 Chi^2 = 0.69 d.f. = 3 P-value = 0.8764 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.01 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 10.5364 66 67 BMDL = 5.46907 68 69 BMDU = 25.864 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-87 1 Taken together, (5.46907, 25.864 ) is a 90 % two-sided confidence 2 interval for the BMD 3 4 Multistage Cancer Slope Factor = 0.00182846 5 6 7 

## F.2.6. Kociba et al. (1978): Female, Keratini z ing Squamous Cell Carcinoma of Lung 8 

## F.2.6.1. Summary Table of BMDS Modeling Results 9

10



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.85 0.84 43.79 7.3E+00 4.2E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.08 0.99 42.35 2.6E+01 4.9E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.01 1.00 42.21 4.0E+01 5.0E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
11 12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-88 F.2.6.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.6.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_kera_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_kera_carc.plt 11 Mon Nov 23 15:06:12 2009 12

==================================================================== 13 14 Source - Table 5 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:06 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-89 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0.00158635 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 0.0013747 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -20.0957 4 38 Fitted model -20.8959 1 1.60041 3 0.6593 39 Reduced model -31.4904 1 22.7894 3 <.0001 40 41 AIC: 43.7918 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 86 0.000 49 1.0000 0.0014 0.069 0.000 50 -0.262 50 10.0000 0.0137 0.683 0.000 50 -0.832 51 100.0000 0.1284 6.294 7.000 49 0.302 52 53 Chi^2 = 0.85 d.f. = 3 P-value = 0.8370 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 7.31091 65 66 BMDL = 4.15929 67 68 BMDU = 14.6306 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-90 Taken together, (4.15929, 14.6306) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 0.00240426 4 5 6 

## F.2.7. National Toxicology Program (1982): Female Rats, Subcutaneous Tissue, 7 

## Fibrosarcoma 8 

## F.2.7.1. Summary Table of BMDS Modeling Results 9

10



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
11 12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-91 F.2.7.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.7.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_sub_fibro.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_sub_fibro.plt 11 Mon Nov 23 15:06:33 2009 12

==================================================================== 13 14 Source - Table 10 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:06 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-92 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.030595 8 Beta(1) = 0.000799545 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.54 16 17 Beta(1) -0.54 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.0231556 * * * 26 Beta(1) 0.00102962 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -33.5998 4 36 Fitted model -36.1883 2 5.17698 2 0.07513 37 Reduced model -37.7465 1 8.29346 3 0.04032 38 39 AIC: 76.3766 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0232 1.737 0.000 75 -1.333 47 1.4000 0.0246 1.228 2.000 50 0.705 48 7.1000 0.0303 1.514 3.000 50 1.227 49 71.0000 0.0920 4.509 4.000 49 -0.252 50 51 Chi^2 = 3.84 d.f. = 2 P-value = 0.1463 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 9.76124 63 64 BMDL = 3.96354 65 66 BMDU = 1.03301e+006 67 68 Taken together, (3.96354, 1.03301e+006) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-93 1 Multistage Cancer Slope Factor = 0.002523 2 3 4 

## F.2.8. National Toxicology Program (1982): Fema le Rats, Liver, Neoplastic Nodule or 5 

## Hepatocellular Carcinoma 6 

## F.2.8.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.37 0.40 133.83 2.6E+00 1.6E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.03 0.50 133.44 1.3E+01 1.7E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.00 0.50 133.44 1.3E+01 1.7E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-94 F.2.8.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.8.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_liver_nod.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_liver_nod.plt 11 Mon Nov 23 15:07:55 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:07 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-95 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0 9 Beta(1) = 0.000900399 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(1) 19 20 Beta(1) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 0.000775683 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -11.3484 4 39 Fitted model -11.6976 1 0.698469 3 0.8736 40 Reduced model -15.9189 1 9.14109 3 0.02747 41 42 AIC: 25.3952 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0000 0.000 0.000 74 0.000 50 1.4000 0.0011 0.054 0.000 50 -0.233 51 7.1000 0.0055 0.275 0.000 50 -0.525 52 71.0000 0.0536 2.679 3.000 50 0.201 53 54 Chi^2 = 0.37 d.f. = 3 P-value = 0.9462 55 56 57 Benchmark Dose Computation 58 59 Specified effect = 0.01 60 61 Risk Type = Extra risk 62 63 Confidence level = 0.95 64 65 BMD = 12.9568 66 67 BMDL = 5.70369 68 69 BMDU = 39.9878 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-96 1 Taken together, (5.70369, 39.9878) is a 90 % two-sided confidence 2 interval for the BMD 3 4 Multistage Cancer Slope Factor = 0.00175325 5 6 7 

## F.2.9. National Toxicology Program (1982): Fema le Rats, Adrenal, Cortical Adenoma, or 8 

## Carcinoma or Adenoma, NOS 9 

## F.2.9.1. Summary Table of BMDS Modeling Results 10

11



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 1.81 0.40 203.38 3.7E+00 1.9E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 1.38 0.50 202.89 1.6E+01 2.0E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 1.33 0.51 202.83 2.6E+01 2.0E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
12 13

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-97 F.2.9.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.9.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adre_cort_ad_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adre_cort_ad_carc.plt 11 Mon Nov 23 15:07:15 2009 12

==================================================================== 13 14 Source - Table 10 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.1 0.2 0.3 0.4 0.5

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:07 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-98 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.140663 8 Beta(1) = 0.00289845 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.48 16 17 Beta(1) -0.48 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.143284 * * * 26 Beta(1) 0.00273674 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -98.7282 4 36 Fitted model -99.6898 2 1.92318 2 0.3823 37 Reduced model -102.201 1 6.94636 3 0.07363 38 39 AIC: 203.38 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.1433 10.460 11.000 73 0.180 47 1.4000 0.1466 7.181 9.000 49 0.735 48 7.1000 0.1598 7.829 5.000 49 -1.103 49 71.0000 0.2946 13.551 14.000 46 0.145 50 51 Chi^2 = 1.81 d.f. = 2 P-value = 0.4046 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 3.67237 63 64 BMDL = 1.87133 65 66 BMDU = 15.4002 67 68 Taken together, (1.87133, 15.4002) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-99 1 Multistage Cancer Slope Factor = 0.00534381 2 3 4 

## F.2.10. National Toxicology Program (1982): Fema le Rats, Thyroid, Follicular-Cell 5 

## Adenoma 6 

## F.2.10.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 0.83 0.66 92.02 7.6E+00 3.5E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 0.53 0.77 91.64 2.3E+01 3.7E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 0.49 0.78 91.60 3.3E+01 3.7E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-100 F.2.10.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.10.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_thy_ad.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_thy_ad.plt 11 Mon Nov 23 15:07:34 2009 12

==================================================================== 13 14 Source - Table 10 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2 0.25

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:07 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-101 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.032089 8 Beta(1) = 0.00143599 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.5 16 17 Beta(1) -0.5 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.0345958 * * * 26 Beta(1) 0.00132742 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -43.5264 4 36 Fitted model -44.0098 2 0.966786 2 0.6167 37 Reduced model -46.2299 1 5.40699 3 0.1443 38 39 AIC: 92.0196 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0346 2.525 3.000 73 0.304 47 1.4000 0.0364 1.637 2.000 45 0.289 48 7.1000 0.0437 2.139 1.000 49 -0.796 49 71.0000 0.1214 5.707 6.000 47 0.131 50 51 Chi^2 = 0.83 d.f. = 2 P-value = 0.6614 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 7.57131 63 64 BMDL = 3.48815 65 66 BMDU = 964541 67 68 Taken together, (3.48815, 964541 ) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-102 1 Multistage Cancer Slope Factor = 0.00286685 2 3 4 

## F.2.11. National Toxicology Program (1982): Ma le Rats, Liver, Neoplastic Nodule or 5 

## Hepatocellular Carcinoma 6 

## F.2.11.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 3 0.37 0.40 133.83 2.6E+00 1.6E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 3 0.03 0.50 133.44 1.3E+01 1.7E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 3 0.00 0.50 133.44 1.3E+01 1.7E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-103 F.2.11.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.11.3. Output File for selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_liver_nod.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_liver_nod.plt 11 Mon Nov 23 15:07:55 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:07 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-104 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0.000900399 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 0.000775683 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -11.3484 4 38 Fitted model -11.6976 1 0.698469 3 0.8736 39 Reduced model -15.9189 1 9.14109 3 0.02747 40 41 AIC: 25.3952 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 74 0.000 49 1.4000 0.0011 0.054 0.000 50 -0.233 50 7.1000 0.0055 0.275 0.000 50 -0.525 51 71.0000 0.0536 2.679 3.000 50 0.201 52 53 Chi^2 = 0.37 d.f. = 3 P-value = 0.9462 54 55 56 Benchmark Dose Computation 57 58 Specified effect = 0.01 59 60 Risk Type = Extra risk 61 62 Confidence level = 0.95 63 64 BMD = 12.9568 65 66 BMDL = 5.70369 67 68 BMDU = 39.9878 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-105 Taken together, (5.70369, 39.9878) is a 90 % two-sided confidence 1 interval for the BMD 2 3 Multistage Cancer Slope Factor = 0.00175325 4 5 6 

## F.2.12. National Toxicology Program (1982): Male Rats, Thyroid, Follicular-Cell 7 

## Adenoma or Carcinoma 8 

## F.2.12.1. Summary Table of BMDS Modeling Results 9

10



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 7.14 0.03 151.22 3.5E+00 1.9E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 7.14 0.03 151.22 3.5E+00 1.9E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 7.14 0.03 151.22 3.5E+00 1.9E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
11 12

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-106 F.2.12.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2 3 

## F.2.12.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 4
5 6

==================================================================== 7 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 8 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_thyroid.(d) 9 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_thyroid.plt 10 Mon Nov 23 15:08:16 2009 11

==================================================================== 12 13 Source - Table 9 14

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 15 16 The form of the probability function is: 17 18 P[response] = background + (1-background)*[1-EXP( 19 -beta1*dose^1)] 20 21 The parameter betas are restricted to be positive 22 23 24 Dependent variable = Mean 25 Independent variable = Dose 26 27 Total number of observations = 4 28 Total number of records with missing values = 0 29 Total number of parameters in model = 2 30 Total number of specified parameters = 0 31 Degree of polynomial = 1 32 33 34 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:08 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-107 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.0867382 8 Beta(1) = 0.00232055 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.53 16 17 Beta(1) -0.53 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.0704713 * * * 26 Beta(1) 0.00285481 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -69.5946 4 36 Fitted model -73.6119 2 8.03468 2 0.018 37 Reduced model -77.5267 1 15.8643 3 0.001209 38 39 AIC: 151.224 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0705 4.863 1.000 69 -1.817 47 1.4000 0.0742 3.561 5.000 48 0.793 48 7.1000 0.0891 4.456 8.000 50 1.759 49 71.0000 0.2410 12.051 11.000 50 -0.347 50 51 Chi^2 = 7.14 d.f. = 2 P-value = 0.0281 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 3.5205 63 64 BMDL = 1.91558 65 66 BMDU = 9.76663 67 68 Taken together, (1.91558, 9.76663) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-108 1 Multistage Cancer Slope Factor = 0.00522034 2 3 4 

## F.2.13. National Toxicology Program (1982): Male Rats, Adrenal cortex, Ad enoma 5 

## F.2.13.1. Summary Table of BMDS Modeling Results 6

7



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 5.83 0.05 199.67 1.4E+01 3.4E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 5.83 0.05 199.67 1.4E+01 3.4E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 5.83 0.05 199.67 1.4E+01 3.4E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-109 F.2.13.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.13.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adre_cort.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adre_cort.plt 11 Mon Nov 23 15:08:35 2009 12

==================================================================== 13 14 Source - Table 9 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:08 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-110 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.168444 8 Beta(1) = 0.000395949 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.53 16 17 Beta(1) -0.53 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.153096 * * * 26 Beta(1) 0.000718012 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -94.8672 4 36 Fitted model -97.8359 2 5.93732 2 0.05137 37 Reduced model -98.0432 1 6.35197 3 0.09569 38 39 AIC: 199.672 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.1531 11.023 6.000 72 -1.644 47 1.4000 0.1539 7.697 9.000 50 0.510 48 7.1000 0.1574 7.713 12.000 49 1.682 49 71.0000 0.1952 9.564 9.000 49 -0.203 50 51 Chi^2 = 5.83 d.f. = 2 P-value = 0.0541 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 13.9974 63 64 BMDL = 3.4443 65 66 67 BMDU did not converge for BMR = 0.010000 68 BMDU calculation failed 69 BMDU = Inf 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-111 1 2 

## F.2.14. National Toxicology Program (1982): Female Mice, Subcutaneous Tissue, 3 

## Fibrosarcoma 4 

## F.2.14.1. Summary Table of BMDS Modeling Results 5

6



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
7 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-112 F.2.14.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.14.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_subcu_fibro.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_subcu_fibro.plt 11 Mon Nov 23 15:08:56 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 Maximum number of iterations = 250 36 0 0.05 0.1 0.15 0.2 0.25

0 50 100 150 200 250 300Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:08 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-113 Relative Function Convergence has been set to: 1e-008 1 Parameter Convergence has been set to: 1e-008 2 3 4 5 Default Initial Parameter Values 6 Background = 0.0143554 7 Beta(1) = 0.000341874 8 9 10 Asymptotic Correlation Matrix of Parameter Estimates 11 12 Background Beta(1) 13 14 Background 1 -0.5 15 16 Beta(1) -0.5 1 17 18 19 20 Parameter Estimates 21 22 95.0% Wald Confidence Interval 23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24 Background 0.0145028 * * * 25 Beta(1) 0.000338561 * * * 26 27 * - Indicates that this value is not calculated. 28 29 30 31 Analysis of Deviance Table 32 33 Model Log(likelihood) # Param's Deviance Test d.f. P-value 34 Full model -30.9876 4 35 Fitted model -31.0199 2 0.0645971 2 0.9682 36 Reduced model -34.3291 1 6.68308 3 0.08272 37 38 AIC: 66.0397 39 40 41 Goodness of Fit 42 Scaled 43 Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45 0.0000 0.0145 1.073 1.000 74 -0.071 46 5.7000 0.0164 0.820 1.000 50 0.200 47 28.6000 0.0240 1.152 1.000 48 -0.143 48 286.0000 0.1055 4.956 5.000 47 0.021 49 50 Chi^2 = 0.07 d.f. = 2 P-value = 0.9675 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 0.01 56 57 Risk Type = Extra risk 58 59 Confidence level = 0.95 60 61 BMD = 29.6855 62 63 BMDL = 14.3524 64 65 BMDU = 100.382 66 67 Taken together, (14.3524, 100.382) is a 90 % two-sided confidence 68 interval for the BMD 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-114 Multistage Cancer Slope Factor = 0.000696747 1 2 3 

## F.2.15. National Toxicology Program (1982): Female Mice, Hematopoietic S ystem, 4 

## Lymphoma 5 

## F.2.15.1. Summary Table of BMDS Modeling Results 6

7



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 0.03 0.99 261.43 1.0E+01 5.5E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 0.03 0.99 261.43 1.0E+01 5.5E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 0.03 0.99 261.43 1.0E+01 5.5E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-115 F.2.15.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.15.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_f_lymphoma.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_f_lymphoma.plt 11 Mon Nov 23 15:09:17 2009 12

==================================================================== 13 14 Table 15 page 64 Hematopoietic System Lymphoma or Leukemia 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0.1 0.2 0.3 0.4 0.5 0.6

0 50 100 150 200 250 300Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:09 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-116 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.242959 8 Beta(1) = 0.000967723 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.48 16 17 Beta(1) -0.48 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.242712 * * * 26 Beta(1) 0.000971954 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -128.699 4 36 Fitted model -128.712 2 0.0264819 2 0.9868 37 Reduced model -131.412 1 5.42487 3 0.1432 38 39 AIC: 261.425 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.2427 17.961 18.000 74 0.011 47 5.7000 0.2469 12.345 12.000 50 -0.113 48 28.6000 0.2635 12.647 13.000 48 0.116 49 286.0000 0.4265 20.045 20.000 47 -0.013 50 51 Chi^2 = 0.03 d.f. = 2 P-value = 0.9868 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 10.3403 63 64 BMDL = 5.45599 65 66 BMDU = 38.9139 67 68 Taken together, (5.45599, 38.9139) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-117 1 Multistage Cancer Slope Factor = 0.00183285 2 3 4 

## F.2.16. National Toxicology Program (1982): Female Mice, Liver, Hepatocellular 5 

## Adenoma or Carcinoma 6 

## F.2.16.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 2.82 0.24 156.00 1.5E+01 7.8E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 2.82 0.24 156.00 1.5E+01 7.8E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 2.82 0.24 156.00 1.5E+01 7.8E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-118 F.2.16.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.16.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_f_liv_aden_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_f_liv_aden_carc.plt 11 Mon Nov 23 15:09:36 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 50 100 150 200 250 300Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:09 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-119 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.0888873 9 Beta(1) = 0.000616931 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.5 17 18 Beta(1) -0.5 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.0788077 * * * 27 Beta(1) 0.000689385 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -74.5177 4 37 Fitted model -76.0006 2 2.96597 2 0.227 38 Reduced model -79.6703 1 10.3053 3 0.01614 39 40 AIC: 156.001 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0788 5.753 3.000 73 -1.196 48 5.7000 0.0824 4.121 6.000 50 0.966 49 28.6000 0.0968 4.646 6.000 48 0.661 50 286.0000 0.2436 11.452 11.000 47 -0.153 51 52 Chi^2 = 2.82 d.f. = 2 P-value = 0.2436 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 14.5787 64 65 BMDL = 7.82902 66 67 BMDU = 42.4536 68 69 Taken together, (7.82902, 42.4536) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-120 interval for the BMD 1 2 Multistage Cancer Slope Factor = 0.0012773 3 4 5 

## F.2.17. National Toxicology Program (1982): Fema le Mice, Thyroid Follicular Cell 6 

## Adenoma 7 

## F.2.17.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.84 0.15 76.38 9.8E+00 4.0E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-121 F.2.17.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.17.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_f_thyroid_aden.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_f_thyroid_aden.plt 11 Mon Nov 23 15:09:56 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15 0.2 0.25

0 50 100 150 200 250 300Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:09 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-122 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.02405 8 Beta(1) = 0.000315564 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.51 16 17 Beta(1) -0.51 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.0207192 * * * 26 Beta(1) 0.000331835 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -32.0017 4 36 Fitted model -34.6122 2 5.22112 2 0.07349 37 Reduced model -37.2405 1 10.4776 3 0.01491 38 39 AIC: 73.2245 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.0207 1.430 0.000 69 -1.208 47 5.7000 0.0226 1.128 3.000 50 1.782 48 28.6000 0.0300 1.409 1.000 47 -0.350 49 286.0000 0.1094 5.032 5.000 46 -0.015 50 51 Chi^2 = 4.76 d.f. = 2 P-value = 0.0927 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 30.2871 63 64 BMDL = 13.993 65 66 BMDU = 130.014 67 68 Taken together, (13.993 , 130.014) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-123 1 Multistage Cancer Slope Factor = 0.000714641 2 3 4 

## F.2.18. National Toxicology Program (1982): Ma le Mice, Lung, Alveolar/Bronchiolar 5 

## Adenoma or Carcinoma 6 

## F.2.18.1. Summary Table of BMDS Modeling Results 7

8



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 3.97 0.14 167.34 3.7E+00 2.0E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 2 3.41 0.18 166.81 1.6E+01 2.1E+00 betas restricted ≥ 0

Multistage cancer, 3-degree 2 3.38 0.18 166.78 2.6E+01 2.1E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-124 F.2.18.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.18.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_lung_aden_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_lung_aden_carc.plt 11 Mon Nov 23 15:10:17 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:10 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-125 1 Maximum number of iterations = 250 2 Relative Function Convergence has been set to: 1e-008 3 Parameter Convergence has been set to: 1e-008 4 5 6 7 Default Initial Parameter Values 8 Background = 0.0827179 9 Beta(1) = 0.00298266 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 Background Beta(1) 15 16 Background 1 -0.49 17 18 Beta(1) -0.49 1 19 20 21 22 Parameter Estimates 23 24 95.0% Wald Confidence Interval 25 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 26 Background 0.0925449 * * * 27 Beta(1) 0.00271189 * * * 28 29 * - Indicates that this value is not calculated. 30 31 32 33 Analysis of Deviance Table 34 35 Model Log(likelihood) # Param's Deviance Test d.f. P-value 36 Full model -79.5959 4 37 Fitted model -81.6704 2 4.14885 2 0.1256 38 Reduced model -85.3351 1 11.4782 3 0.009402 39 40 AIC: 167.341 41 42 43 Goodness of Fit 44 Scaled 45 Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47 0.0000 0.0925 6.571 10.000 71 1.404 48 1.4000 0.0960 4.607 2.000 48 -1.278 49 7.1000 0.1099 5.273 4.000 48 -0.588 50 71.0000 0.2515 12.574 13.000 50 0.139 51 52 Chi^2 = 3.97 d.f. = 2 P-value = 0.1375 53 54 55 Benchmark Dose Computation 56 57 Specified effect = 0.01 58 59 Risk Type = Extra risk 60 61 Confidence level = 0.95 62 63 BMD = 3.70603 64 65 BMDL = 2.0263 66 67 BMDU = 10.562 68 69 Taken together, (2.0263 , 10.562 ) is a 90 % two-sided confidence 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-126 interval for the BMD 1 2 Multistage Cancer Slope Factor = 0.0049351 3 4 5 

## F.2.19. National Toxicology Program (1982): Ma le Mice, Liver, Hepatocellu lar Adenoma 6 

## or Carcinoma 7 

## F.2.19.1. Summary Table of BMDS Modeling Results 8

9



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 2 0.17 0.92 258.57 1.3E+00 8.6E-01 betas restricted ≥ 0

Multistage cancer, 2-degree 2 0.17 0.92 258.57 1.3E+00 8.6E-01 betas restricted ≥ 0

Multistage cancer, 3-degree 2 0.17 0.92 258.57 1.3E+00 8.6E-01 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
10 11

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-127 F.2.19.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.19.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_m_liver_aden_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_mice_m_liver_aden_carc.plt 11 Mon Nov 23 15:10:37 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:10 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-128 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.22264 8 Beta(1) = 0.0074005 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.46 16 17 Beta(1) -0.46 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.219315 * * * 26 Beta(1) 0.00750879 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -127.199 4 36 Fitted model -127.286 2 0.174343 2 0.9165 37 Reduced model -135.589 1 16.7801 3 0.0007843 38 39 AIC: 258.572 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.2193 16.010 15.000 73 -0.286 47 1.4000 0.2275 11.146 12.000 49 0.291 48 7.1000 0.2598 12.732 13.000 49 0.087 49 71.0000 0.5419 27.096 27.000 50 -0.027 50 51 Chi^2 = 0.17 d.f. = 2 P-value = 0.9164 52 53 54 Benchmark Dose Computation 55 56 Specified effect = 0.01 57 58 Risk Type = Extra risk 59 60 Confidence level = 0.95 61 62 BMD = 1.33848 63 64 BMDL = 0.861975 65 66 BMDU = 2.4671 67 68 Taken together, (0.861975, 2.4671 ) is a 90 % two-sided confidence 69 interval for the BMD 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-129 1 Multistage Cancer Slope Factor = 0.0116013 2 3 4 

## F.2.20. National Toxicology Program (2006 ): Liver, Cholangiocarcinoma 5 

## F.2.20.1. Summary Table of BMDS Modeling Results 6

7



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree 5 12.91 0.02 129.07 1.9E+00 1.4E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 5 1.18 0.95 114.35 9.4E+00 5.3E+00 betas restricted ≥ 0

Multistag e cancer, 3-degree b 

### 4 0.22 0.99 115.16 1.3E+01 4.5E+00 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
8 9

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-130 F.2.20.2. Figure for Selected Model: Multista ge Cancer, 3-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.20.3. Output File for Selected Model: Multis tage Can cer, 3-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc3_ngkgd_liv_cho-carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc3_ngkgd_liv_cho-carc.plt 11 Mon Nov 23 15:10:57 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 4 31 Total number of specified parameters = 0 32 Degree of polynomial = 3 33 34 35 0 0.1 0.2 0.3 0.4 0.5 0.6

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:10 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-131 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0.000561481 9 Beta(2) = 1.74365e-005 10 Beta(3) = 1.40248e-006 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 ( *** The model parameter(s) -Background -Beta(1) 16 have been estimated at a boundary point, or have been specified by the user, 17 and do not appear in the correlation matrix ) 18 19 Beta(2) Beta(3) 20 21 Beta(2) 1 -0.99 22 23 Beta(3) -0.99 1 24 25 26 27 Parameter Estimates 28 29 95.0% Wald Confidence Interval 30 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 31 Background 0 * * * 32 Beta(1) 0 * * * 33 Beta(2) 4.35927e-005 * * * 34 Beta(3) 1.14186e-006 * * * 35 36 * - Indicates that this value is not calculated. 37 38 39 40 Analysis of Deviance Table 41 42 Model Log(likelihood) # Param's Deviance Test d.f. P-value 43 Full model -55.408 6 44 Fitted model -55.5789 2 0.34181 4 0.987 45 Reduced model -96.9934 1 83.1708 5 <.0001 46 47 AIC: 115.158 48 49 50 Goodness of Fit 51 Scaled 52 Dose Est._Prob. Expected Observed Size Residual 53

------------------------------------------------------------------------ 54 0.0000 0.0000 0.000 0.000 49 0.000 55 2.1400 0.0002 0.010 0.000 48 -0.101 56 7.1400 0.0026 0.121 0.000 46 -0.349 57 15.7000 0.0150 0.752 1.000 50 0.288 58 32.9000 0.0841 4.121 4.000 49 -0.062 59 71.4000 0.4716 24.994 25.000 53 0.002 60 61 Chi^2 = 0.22 d.f. = 4 P-value = 0.9945 62 63 64 Benchmark Dose Computation 65 66 Specified effect = 0.01 67 68 Risk Type = Extra risk 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-132 Confidence level = 0.95 1 2 BMD = 13.1014 3 4 BMDL = 4.46755 5 6 BMDU = 19.1783 7 8 Taken together, (4.46755, 19.1783) is a 90 % two-sided confidence 9 interval for the BMD 10 11 Multistage Cancer Slope Factor = 0.00223836 12 13 14 

## F.2.21. National Toxicology Program (2006 ): Liver, Hepatocellu lar Adenoma 15 

## F.2.21.1. Summary Table of BMDS Modeling Results 16

17



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree 5 8.50 0.13 82.31 4.4E+00 2.9E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 5 1.94 0.86 73.66 1.5E+01 8.6E+00 betas restricted ≥ 0

Multistag e cancer, 3-degree b 

### 5 0.24 1.00 71.22 2.4E+01 1.2E+01 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BMDS goodness-of-fit criteria b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded
18

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-133 F.2.21.2. Figure for Selected Model: Multista ge Cancer, 3-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.21.3. Output File for Selected Model: Multis tage Can cer, 3-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc3_ngkgd_liv_hepat_ad.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc3_ngkgd_liv_hepat_ad.plt 11 Mon Nov 23 15:11:17 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 4 31 Total number of specified parameters = 0 32 Degree of polynomial = 3 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:11 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-134 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0 9 Beta(2) = 0 10 Beta(3) = 7.77141e-007 11 12 13 Asymptotic Correlation Matrix of Parameter Estimates 14 15 ( *** The model parameter(s) -Background -Beta(1) -Beta(2) 16 have been estimated at a boundary point, or have been specified by the user, 17 and do not appear in the correlation matrix ) 18 19 Beta(3) 20 21 Beta(3) 1 22 23 24 25 Parameter Estimates 26 27 95.0% Wald Confidence Interval 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 29 Background 0 * * * 30 Beta(1) 0 * * * 31 Beta(2) 0 * * * 32 Beta(3) 7.46408e-007 * * * 33 34 * - Indicates that this value is not calculated. 35 36 37 38 Analysis of Deviance Table 39 40 Model Log(likelihood) # Param's Deviance Test d.f. P-value 41 Full model -34.4075 6 42 Fitted model -34.6078 1 0.40065 5 0.9953 43 Reduced model -56.3333 1 43.8515 5 <.0001 44 45 AIC: 71.2156 46 47 48 Goodness of Fit 49 Scaled 50 Dose Est._Prob. Expected Observed Size Residual 51

------------------------------------------------------------------------ 52 0.0000 0.0000 0.000 0.000 49 0.000 53 2.1400 0.0000 0.000 0.000 48 -0.019 54 7.1400 0.0003 0.012 0.000 46 -0.112 55 15.7000 0.0029 0.144 0.000 50 -0.380 56 32.9000 0.0262 1.285 1.000 49 -0.255 57 71.4000 0.2379 12.609 13.000 53 0.126 58 59 Chi^2 = 0.24 d.f. = 5 P-value = 0.9986 60 61 62 Benchmark Dose Computation 63 64 Specified effect = 0.01 65 66 Risk Type = Extra risk 67 68 Confidence level = 0.95 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-135 BMD = 23.7904 1 2 BMDL = 11.5343 3 4 BMDU = 27.8755 5 6 Taken together, (11.5343, 27.8755) is a 90 % two-sided confidence 7 interval for the BMD 8 9 Multistage Cancer Slope Factor = 0.000866978 10 11 12 

## F.2.22. National Toxicology Program (2006): Oral Mucosa, Squamous Cell Carcinoma 13 

## F.2.22.1. Summary Table of BMDS Modeling Results 14

15

Model Degrees of Freedom 

### χ 2 Test Statistic 

### χ 2 p-Value a AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

multistage cancer, 1-degree 4 4.15 0.39 125.48 4.8E+00 3.0E+00 betas restricted ≥ 0

Multistage cancer, 2-degree b 4 2.83 0.59 123.25 1.6E+01 3.8E+00 betas restricted ≥ 0, bound hit
Multistage cancer, 3-degree 4 2.83 0.59 123.25 1.6E+01 3.8E+00 betas restricted ≥ 0, bound hit

a Values <0.1 fail to meet BMDS goodness-of-fit criteria. b Best-fitting model as assessed by lowest-AIC criterion, bolded.
16 17

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-136 F.2.22.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0, 1 

## Bound Hit 2

3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:11 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

4 5 6 

## F.2.22.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0, 7 

## Bound Hit 8
9 10

==================================================================== 11 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 12 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_oral_carc.(d) 13 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_oral_carc.plt 14 Mon Nov 23 15:11:37 2009 15

==================================================================== 16 17 0 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 19 20 The form of the probability function is: 21 22 P[response] = background + (1-background)*[1-EXP( 23 -beta1*dose^1)] 24 25 The parameter betas are restricted to be positive 26 27 28 Dependent variable = Mean 29 Independent variable = Dose 30 31 Total number of observations = 6 32 Total number of records with missing values = 0 33 Total number of parameters in model = 2 34 Total number of specified parameters = 0 35

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-137 Degree of polynomial = 1 1 2 3 Maximum number of iterations = 250 4 Relative Function Convergence has been set to: 1e-008 5 Parameter Convergence has been set to: 1e-008 6 7 8 9 Default Initial Parameter Values 10 Background = 0.00607545 11 Beta(1) = 0.00265195 12 13 14 Asymptotic Correlation Matrix of Parameter Estimates 15 16 Background Beta(1) 17 18 Background 1 -0.6 19 20 Beta(1) -0.6 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0.0171416 * * * 29 Beta(1) 0.00211536 * * * 30 31 * - Indicates that this value is not calculated. 32 33 34 35 Analysis of Deviance Table 36 37 Model Log(likelihood) # Param's Deviance Test d.f. P-value 38 Full model -57.5353 6 39 Fitted model -60.7418 2 6.41293 4 0.1704 40 Reduced model -67.7782 1 20.4858 5 0.001013 41 42 AIC: 125.484 43 44 45 Goodness of Fit 46 Scaled 47 Dose Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49 0.0000 0.0171 0.840 1.000 49 0.176 50 2.1400 0.0216 1.036 2.000 48 0.958 51 7.1400 0.0319 1.466 1.000 46 -0.391 52 15.7000 0.0492 2.462 0.000 50 -1.609 53 32.9000 0.0832 4.078 4.000 49 -0.040 54 71.4000 0.1549 8.211 10.000 53 0.679 55 56 Chi^2 = 4.15 d.f. = 4 P-value = 0.3855 57 58 59 Benchmark Dose Computation 60 61 Specified effect = 0.01 62 63 Risk Type = Extra risk 64 65 Confidence level = 0.95 66 67 BMD = 4.75111 68 69 BMDL = 2.9556 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-138 1 BMDU = 9.19454 2 3 Taken together, (2.9556 , 9.19454) is a 90 % two-sided confidence 4 interval for the BMD 5 6 Multistage Cancer Slope Factor = 0.0033834 7 8 9 

## F.2.23. National Toxicology Program (2006): Pancreas, Adenoma or Carcinoma 10 

## F.2.23.1. Summary Table of BMDS Modeling Results 11

12



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree b 

### 5 2.37 0.80 28.32 2.1E+01 9.3E+00 betas restricted ≥ 0

Multistage cancer, 2-degree 5 0.80 0.98 26.23 3.3E+01 1.4E+01 betas restricted ≥ 0

Multistage cancer, 3-degree 5 0.32 1.00 25.43 4.1E+01 1.8E+01 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
13 14

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-139 F.2.23.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.23.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_panc_ad_carc.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_panc_ad_carc.plt 11 Mon Nov 23 15:11:58 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0 0.05 0.1 0.15

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:11 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-140 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0.000817541 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 ( *** The model parameter(s) -Background 14 have been estimated at a boundary point, or have been specified by the user, 15 and do not appear in the correlation matrix ) 16 17 Beta(1) 18 19 Beta(1) 1 20 21 22 23 Parameter Estimates 24 25 95.0% Wald Confidence Interval 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 27 Background 0 * * * 28 Beta(1) 0.000474004 * * * 29 30 * - Indicates that this value is not calculated. 31 32 33 34 Analysis of Deviance Table 35 36 Model Log(likelihood) # Param's Deviance Test d.f. P-value 37 Full model -11.4096 6 38 Fitted model -13.1581 1 3.49702 5 0.6238 39 Reduced model -16.7086 1 10.598 5 0.05996 40 41 AIC: 28.3163 42 43 44 Goodness of Fit 45 Scaled 46 Dose Est._Prob. Expected Observed Size Residual 47

------------------------------------------------------------------------ 48 0.0000 0.0000 0.000 0.000 48 0.000 49 2.1400 0.0010 0.049 0.000 48 -0.221 50 7.1400 0.0034 0.155 0.000 46 -0.395 51 15.7000 0.0074 0.371 0.000 50 -0.611 52 32.9000 0.0155 0.743 0.000 48 -0.869 53 71.4000 0.0333 1.697 3.000 51 1.017 54 55 Chi^2 = 2.37 d.f. = 5 P-value = 0.7964 56 57 58 Benchmark Dose Computation 59 60 Specified effect = 0.01 61 62 Risk Type = Extra risk 63 64 Confidence level = 0.95 65 66 BMD = 21.2031 67 68 BMDL = 9.33481 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-141 BMDU = 65.4351 1 2 Taken together, (9.33481, 65.4351) is a 90 % two-sided confidence 3 interval for the BMD 4 5 Multistage Cancer Slope Factor = 0.00107126 6 7 8 

## F.2.24. National Toxicology Program (2006): L ung, Cystic Keratiniz ing Epithelioma 9 

## F.2.24.1. Summary Table of BMDS Modeling Results 10

11



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

Multistage cancer, 1-degree 5 7.42 0.19 60.81 6.9E+00 4.2E+00 betas restricted ≥ 0

Multistage cancer, 2-degree b 

### 5 2.54 0.77 54.36 1.9E+01 1.1E+01 betas restricted ≥ 0

Multistage cancer, 3-degree 5 1.02 0.96 51.85 2.8E+01 1.6E+01 betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
12 13

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-142 F.2.24.2. Figure for Selected Model: Multista ge Cancer, 2-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.24.3. Output File for Selected Model: Multis tage Can cer, 2-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc2_ngkgd_lung_epith.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc2_ngkgd_lung_epith.plt 11 Mon Nov 23 15:12:20 2009 12

==================================================================== 13 14 0 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1-beta2*dose^2)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 6 29 Total number of records with missing values = 0 30 Total number of parameters in model = 3 31 Total number of specified parameters = 0 32 Degree of polynomial = 2 33 34 35 0 0.05 0.1 0.15 0.2 0.25 0.3

0 10 20 30 40 50 60 70Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

15:12 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-143 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0 8 Beta(1) = 0 9 Beta(2) = 3.77591e-005 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 13 14 ( *** The model parameter(s) -Background -Beta(1) 15 have been estimated at a boundary point, or have been specified by the user, 16 and do not appear in the correlation matrix ) 17 18 Beta(2) 19 20 Beta(2) 1 21 22 23 24 Parameter Estimates 25 26 95.0% Wald Confidence Interval 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28 Background 0 * * * 29 Beta(1) 0 * * * 30 Beta(2) 2.91011e-005 * * * 31 32 * - Indicates that this value is not calculated. 33 34 35 36 Analysis of Deviance Table 37 38 Model Log(likelihood) # Param's Deviance Test d.f. P-value 39 Full model -23.958 6 40 Fitted model -26.1815 1 4.44693 5 0.487 41 Reduced model -40.2069 1 32.4976 5 <.0001 42 43 AIC: 54.363 44 45 46 Goodness of Fit 47 Scaled 48 Dose Est._Prob. Expected Observed Size Residual 49

------------------------------------------------------------------------ 50 0.0000 0.0000 0.000 0.000 49 0.000 51 2.1400 0.0001 0.006 0.000 48 -0.080 52 7.1400 0.0015 0.068 0.000 46 -0.261 53 15.7000 0.0071 0.350 0.000 49 -0.594 54 32.9000 0.0310 1.519 0.000 49 -1.252 55 71.4000 0.1379 7.170 9.000 52 0.736 56 57 Chi^2 = 2.54 d.f. = 5 P-value = 0.7708 58 59 60 Benchmark Dose Computation 61 62 Specified effect = 0.01 63 64 Risk Type = Extra risk 65 66 Confidence level = 0.95 67 68 BMD = 18.5839 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-144 BMDL = 10.6878 1 2 BMDU = 25.1324 3 4 Taken together, (10.6878, 25.1324) is a 90 % two-sided confidence 5 interval for the BMD 6 7 Multistage Cancer Slope Factor = 0.000935646 8 9 10 

## F.2.25. Toth et al. (1978): 1YR, Liver, Tumors 11 

## F.2.25.1. Summary Table of BMDS Modeling Results 12

13



### Model Degrees of Freedom χ 2 

### Test Statistic χ 2 

### p-Value a 

### AIC BMD (ng/kg-day) BMDL (ng/kg-day) Model Notes

multistage cancer, 1-degree b 

### 1 1.30 0.25 155.95 2.7E+00 1.5E+00 betas restricted ≥ 0
multistage cancer, 2-degree 1 1.30 0.25 155.95 2.7E+00 1.5E+00 betas restricted ≥ 0
multistage cancer, 0-degree 0.25 -999.00 error error betas restricted ≥ 0

a 

### Values <0.1 fail to meet BM DS goodness-of-fit criteria. b 

### Best-fitting model as assessed by lowest-AIC criterion, bolded.
14 15

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-145 F.2.25.2. Figure for Selected Model: Multista ge Cancer, 1-Degree, Betas Restricted ≥ 0 1

2

3 4 

## F.2.25.3. Output File for Selected Model: Multis tage Can cer, 1-Degree, Betas Restricted ≥ 0 5
6 7

==================================================================== 8 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 9 Input Data File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adr_cor_1yr.(d) 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\msc1_ngkgd_adr_cor_1yr.plt 11 Mon Nov 23 17:30:17 2009 12

==================================================================== 13 14 Table 1 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16 17 The form of the probability function is: 18 19 P[response] = background + (1-background)*[1-EXP( 20 -beta1*dose^1)] 21 22 The parameter betas are restricted to be positive 23 24 25 Dependent variable = Mean 26 Independent variable = Dose 27 28 Total number of observations = 3 29 Total number of records with missing values = 0 30 Total number of parameters in model = 2 31 Total number of specified parameters = 0 32 Degree of polynomial = 1 33 34 35 0.1 0.2 0.3 0.4 0.5 0.6

0 20 40 60 80 100Fraction Affected

dose Multistage Cancer Model with 0.95 Confidence Level

17:30 11/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-146 Maximum number of iterations = 250 1 Relative Function Convergence has been set to: 1e-008 2 Parameter Convergence has been set to: 1e-008 3 4 5 6 Default Initial Parameter Values 7 Background = 0.240176 8 Beta(1) = 0.00374745 9 10 11 Asymptotic Correlation Matrix of Parameter Estimates 12 13 Background Beta(1) 14 15 Background 1 -0.53 16 17 Beta(1) -0.53 1 18 19 20 21 Parameter Estimates 22 23 95.0% Wald Confidence Interval 24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 25 Background 0.2418 * * * 26 Beta(1) 0.00373791 * * * 27 28 * - Indicates that this value is not calculated. 29 30 31 32 Analysis of Deviance Table 33 34 Model Log(likelihood) # Param's Deviance Test d.f. P-value 35 Full model -75.3127 3 36 Fitted model -75.9728 2 1.3201 1 0.2506 37 Reduced model -79.4897 1 8.35401 2 0.01534 38 39 AIC: 155.946 40 41 42 Goodness of Fit 43 Scaled 44 Dose Est._Prob. Expected Observed Size Residual 45

------------------------------------------------------------------------ 46 0.0000 0.2418 9.188 7.000 38 -0.829 47 1.0000 0.2446 10.764 13.000 44 0.784 48 100.0000 0.4783 21.044 21.000 44 -0.013 49 50 Chi^2 = 1.30 d.f. = 1 P-value = 0.2537 51 52 53 Benchmark Dose Computation 54 55 Specified effect = 0.01 56 57 Risk Type = Extra risk 58 59 Confidence level = 0.95 60 61 BMD = 2.68876 62 63 BMDL = 1.52183 64 65 BMDU = 7.54263 66 67 Taken together, (1.52183, 7.54263) is a 90 % two-sided confidence 68 interval for the BMD 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-147 Multistage Cancer Slope Factor = 0.00657103 1 2

## This document is a draft for review purpos es only and does not constitute Agency policy 1/15/10 F-148 DRAFT: DO NOT CITE OR QUOTEF.3.HUMAN EQUIVALENT DOSES FOR 1, 5, AND 10% EXTRA RISKComparison of HumanEquivalent Doses from BenchmarkDose Modeling Assuming 1%, 5%, and 10% Extra RiskBMD01HEDBMDL01HEDBMD05HEDBMDL05HEDBMD10HEDBMDL10HEDStudy Species SexMorphology: topography(ng/kg-day)(ng/kg-day)(ng/kg-day)(ng/kg-day)(ng/kg-day)(ng/kg-day)Stratified squamous cell carcinoma of hard palate or nasalturbinates4.7E-01 1.6E-01 4.6E+00 1.7E+00 1.1E+01 4.6E+00Stratified squamous cell carcinoma of tongue5.1E-01 1.4E-01 4.9E+00 1.6E+00 1.2E+01 4.1E+00MaleAdenoma of adrenal cortex2.0E-01 8.5E-02 2.1E+00 9.7E-01 5.5E+00 2.6E+00Hepatocellular adenoma(s) or carcinoma(s)1.9E-02 1.2E-02 2.3E-01 1.4E-01 6.7E-01 4.1E-01Stratified squamous cell carcinoma of hard palate or nasalturbinates3.3E-01 1.2E-01 3.3E+00 1.3E+00 8.3E+00 3.6E+00Kociba,1978RatFemaleKeratinizing squamous cell carcinoma of lung1.9E-01 8.0E-02 2.0E+00 9.2E-01 5.3E+00 2.5E+00Subcutaneous tissue: fibrosarcoma1.8E-01 5.3E-02 2.0E+00 6.2E-01 5.2E+00 1.7E+00Liver: neoplastic nodule or hepatocellular carcinoma 4.2E-02 2.1E-02 4.9E-01 2.4E-01 1.4E+00 7.1E-01Adrenal: cortical adenoma, or carcinoma or adenoma, NOS 6.8E-02 2.4E-02 7.8E-01 2.8E-01 2.2E+00 8.2E-01FemaleThyroid: follicular-cell adenoma 2.1E-01 6.4E-02 2.2E+00 7.4E-01 5.7E+00 2.0E+00Liver: neoplastic nodule or hepatocellular carcinoma 5.1E-01 1.5E-01 4.9E+00 1.6E+00 1.2E+01 4.3E+00Thyroid: follicular-cell adenoma or carcinoma4.3E-02 1.9E-02 5.1E-01 2.3E-01 1.4E+00 6.6E-01RatMaleAdrenal cortex: adenoma2.6E-01 4.4E-02 2.8E+00 5.2E-01 7.0E+00 1.5E+00Subcutaneous tissue: fibrosarcoma2.1E-01 7.2E-02 2.2E+00 8.3E-01 5.8E+00 2.3E+00Hematopoietic system: lymphoma or leukemia4.0E-02 1.5E-02 4.7E-01 1.8E-01 1.3E+00 5.3E-01Liver: hepatocellular adenoma or carcinoma5.9E-02 2.4E-02 6.9E-01 2.9E-01 1.9E+00 8.3E-01FemaleThyroid: follicular-cell adenoma 1.8E-01 5.6E-02 1.9E+00 6.5E-01 5.0E+00 1.8E+00Lung: alveolar/bronchiolar adenoma or carcinoma 1.3E-01 8.6E-03 4.6E-01 1.0E-01 7.7E-01 3.0E-01NTP, 1982MouseMaleLiver: hepatocellular adenoma or carcinoma 3.1E-03 1.7E-03 3.7E-02 1.9E-02 1.1E-01 5.7E-02Liver: cholangiocarcinoma7.0E-01 2.9E-01 1.5E+00 1.2E+00 2.1E+00 1.8E+00Liver: hepatocellular adenoma1.1E+00 5.6E-01 2.3E+00 1.8E+00 3.2E+00 2.7E+00Oral mucosa: squamous cell carcinoma1.1E-01 5.5E-02 1.2E+00 6.4E-01 3.3E+00 1.8E+00Pancreas: adenoma or carcinoma1.1E+00 3.4E-01 5.3E+00 3.1E+00 8.3E+00 5.0E+00NTP, 2006 Rat FemaleLung: cystic keratinizing epithelioma 8.0E-01 4.1E-01 2.5E+00 1.8E+00 4.1E+00 2.9E+00Toth, 1979 Mouse Male Liver: tumors5.1E-03 1.9E-03 6.7E-02 2.7E-02 2.0E-01 8.5E-02

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE F-149 F.4. REFERENCES Goodman, DG; Sauer, RM. (1992) Hepatotoxicity and carcin ogenicity in female Sprague-Dawley rats treated with 1 

### 2,3,7,8-tetrachlorordibenzo-p-dioxin (TCDD): a Pathology Working Group reevaluation. Regul Toxicol Pharmacol 2 

### 15:245–252. 3


### Kociba, RJ; Keyes, DG; Beyer, JE; et al. (1978) Results of a two-year chronic toxicity and oncogenicity study of 4 

### 2,3,7,8-tetrachlorodibenzo-p-dioxin in rats. Toxicol Appl Pharmacol 46(2):279–303. 5


### NTP (National Toxicology Program). (1982) Bioassay of 2,3,7,8-tetrachlorodibenzo-p-dioxin for possible 6 

### carcinogenicity (gavage study). Tech. Rept. Ser. No. 201. U.S. Department of Health and Human Services, Public 7 

### Health Service, Research Triangle Park, NC. 8


### NTP (National Toxicology Program). (2006) Studies of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in female 9 

### Harlan Sprague-Dawley rats (gavage studies) Tech. Rep. Ser. No. 521. U.S. Department of Health and Human 10 

### Services, Public Health Service, Research Triangle Park, NC. 11


### Toth, KJ; Sugar, S; Somfai-Relle S; et al. (1978) Carcinogenic bioassay of the herbicide 2,4,5-trichlorphenoxy 12 

### ethanol (TCPE) with Swiss mice. Prog Biochem Pharmacol 14:82–93. 13

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX G
Endpoints Excluded From Reference Dose Derivation Based on Toxicological Relevance

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE G-1 APPENDIX G. ENDPOINTS EXCLUDED FROM REFERENCE DOSE DERIVATION 1 BASED ON TOXICOLOGICAL RELEVANCE 2 3 4 The National Academy of Sciences (NAS) committee commented on the low dose model 5 predictions and the need to disc uss the biological significance of the noncancer health effects 6 modeled in the 2003 Reassessment. In selecting point of departure (POD) candidates from the 7 animal bioassays for derivation of the reference dose (RfD), U.S. Environmental Protection 8 Agency (EPA) had to consider the toxicological relevance of the identifi ed endpoint(s) from any 9 given study. Often endpoints/effects may be sensitive, but lack ge neral toxicological 10 significance due to not being clearly adverse (defined in the Integr ated Risk Information System 11 (IRIS) glossary as a biochemical change, functional impairment, or pathol ogic lesion that affects 12 the performance of the whole organism, or redu ces an organism’s ability to respond to an 13 additional environmental challenge), being an ad aptive response, or not being clearly linked to 14 downstream functional or pathological alterations. It is standard EPA RfD derivation policy not 15 to base a reference value on endpoints that are not adverse or not obvious precursors to an 16
adverse effect. For select studies , a rationale for lack of toxico logical relevance of particular 17 endpoints reported is listed here. These endpoints were not consider ed for derivation of the RfD. 18 Kitchin and Woods (1979) administered fema le Sprague-Dawley rats a single gavage 19 dose of 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD) and measured cytochrome P450 levels and 20 benzo(a)pyrene hydroxylase (BPH) activity as a marker of hepa tic microsomal cytochrome 21 P448-mediated enzyme activity. They found a sta tistically significant incr ease in BPH at doses 22
≥ 2 ng/kg and a significant increase in cytochrome P450 levels at doses ≥ 600 ng/kg. Aryl 23 hydrocarbon hydrolase and EROD were both significantly increased 3 months after exposure; 24
however the elevation did not main tain statistical significance at 6 months. No other indicators 25 of hepatic effects were analyzed. CYP induc tion alone is not cons idered a significant 26 toxicologically adverse effect given that CYPs are induced as a means of hepatic processing of 27 xenobiotic agents. Additionally, th e role of CYP induction in hepa totoxicity and carcinogenicity 28 of TCDD is unknown, and CYP induction is not considered a relevant POD without obvious 29 pathological significance. 30 In multiple studies by Hassoun et al. (1998, 2000, 2002, 2003), various indicators of 31 oxidative stress were measured in hepatic and brain tissue of female B6C3F1 mice and Sprague- 32

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE G-2 Dawley rats following 13 or 30 weeks of TCDD gava ge dosing (5 days a week). Biomarkers for 1 oxidative stress included producti on superoxide anion, lipid pe roxidation, and DNA single-strand 2 breaks. The authors report a stat istically significant effect on several oxidative stress markers as 3 a result of TCDD exposure, the lowest dose pr oducing an effect being 0.32 ng/kg-day (Hassoun 4 et al., 1998). In this study, a ll oxidative stress markers were si gnificantly effected, but no other 5 indicators of brain pathology were assessed. Th us, it is impracticable to link the markers of 6 oxidative stress to a toxicological outcome in th e brain, and this study an d its endpoints are not 7
considered relevant POD candidates. 8 Burleson et al. (1996) analyzed the effect of a TCDD on vira l host resistance following a 9 single gavage dose of TCDD by me asuring mortality mediated by influenza virus challenge in 10 B6C3F1 female mice. The study authors found that TCDD at ≥ 10 ng/kg-day increased 11 influenza-induced mortality. The experimental design calls for a 30% mortality in untreated 12 animals (15% was achieved); mortality, itself, is not a direct result of TCDD exposure. None of 13 the other immunologically-relevant measures we re affected by TCDD treatment in this study, 14 and no other effects were reported. The interpretati on of these results with respect to humans is 15 problematic. Furthermore, the findings were not reproduced by Nohara et al. (2002) using the 16 same experimental design (see Section 2.4.2). Theref ore, this endpoint is not considered relevant 17
as a POD candidate. 18 To examine the central nervous system response to TCDD, Kuchiiwa et al (2002) 19 analyzed the effect of in uter o and lactational TCDD exposure on th e serotonergic system in the 20
brainstem of male ddY mice. Female mice we re administered TCDD by oral gavage once a 21 week for 8 weeks prior to pregnancy and, usi ng an immunocytochemical detection method, the 22 raphe nuclei in the brainstem of male offspring was monitored for serotogergic neurons. TCDD 23 at 0.7 ng/kg-day caused a 25

− 50% reduction in the immunostaini ng of serotonin, however there 24 were no differences in external morphol ogy, birth or postnatal body weights between 25 TCDD-exposed and control offspring. The author s suggest that these findings may indicate that 26 TCDD acts as a neuroteratogen by mediating lo ng-term alterations in neuronal serotonin 27 synthesis and serotonergic func tion. However, no other relevant neurotoxicity endpoints were 28 examined or reported. Thus, reduced serotonin is not an adverse endpoint of toxicological 29 significance in and of itself, and this study is deemed unsuitable as a POD candidate. 30

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE G-3 Mally and Chipman (2002) evaluated th e effect of TCDD on gap junctions, 1 hypothesizing that as a nongenotoxic carci nogen, TCDD may induce tumor formation by 2 disturbing tissue homeostasis. Female F344 rats were dosed with TC DD by oral gavage for 3 either 3 consecutive days or 2 days a week for 28 days. Gap junction connexin (Cx) plaque 4 expression and hepatocyte prolif eration was measured. The st udy authors report a decrease in 5 Cx32 plaque number and area in the liver of ra ts exposed to 0.7 ng/kg-day and higher, however 6 they did not find an associated incr ease in hepatocyte pr oliferation. No clinic al signs of toxicity 7 were observed, and histological examination of the liver revealed no abnormalities. In the 8
absence of additional indicators of hepatotoxicity, a decrease in Cx32 plaque formation is not 9 clearly linked to TCDD-mediated hepatotoxicity or hepatocarcinogenicty, nor is it considered an 10 adverse effect. This endpoint is not c onsidered a toxicologi cally relevant POD. 11 Vanden Heuvel et al. (1994) analyzed ch anges in hepatic mRNA following a single 12 administration of TCDD to female Sprague-Daw ley rats by oral gavage. Four days after 13 treatment, animals were sacrificed and liver s were excised. Using reverse transcriptase14 polymerase chain reaction (RT-PCR) on hepatic RNA, they compared levels of “dioxin 15 responsive” mRNA’s (CYP 1A1, UDP-glucuronosyltransferase I, plasminogen activator inhibitor 16 2, and transforming growth factor α ) at various doses of TCDD and at control (baseline) levels. 17 They determined that CYP1A1 elicited the most sensitive response to TCDD, with a statistically 18 significant increase (3-fold) in mRNA from rat livers exposed to 1 ng/kg-day TCDD. Induction 19 of CYP1A1 expression is not considered an adverse effect, as the role of CYP1A1 in 20 TCDD-mediated carcinogenicity is unsettled. Ther efore, in the absence of other indicators of 21 hepatoxicity, increases in liver CYP1A1 cannot be considered toxicologica lly relevant for a POD 22
candidate. 23 Devito et al. (1994) assessed the activity of CYP1A1 and CYP1A2, the amount of 24 phosphorylation of phosphotyrosyl proteins (pp32, pp34, and pp38), and the levels of estrogen 25 receptor in the liver, uterus, lung and skin tissu e of female B6C3F1 mi ce administered TCDD for 26 5 days a week for 13 weeks. The authors hypothesized that these measurements may be 27 sensitive biomarkers for exposure to TCDD. Body weights were also recorded weekly. 28 Induction of CY1A1 and CYP1A2, as well as increased phosphorylated forms of pp32, pp34, 29 and pp38 were sensitive indicators of TCDD exposure , with statistically si gnificant changes seen 30 at 1.07 ng/kg-day. EROD activity in the ling, skin, and liver was also obser ved with significant 31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE G-4 increases at this dose. However, the authors di d not find a change in rat body or terminal organ 1 weights, nor did they note any pathology in the anim als at this dose level. The role of CYPs and 2 phosphorylated pp32, pp34, and pp38 in TCDD-mediated toxicity is unknown, and changes in 3 the activity or function of these proteins are not considered adve rse. Therefore, these endpoints 4
are not considered suitable as PODs. 5 Because TCDD had been detected in the soil of contaminated locations, determining the 6 bioavailability of TCDD from ingested soil may be important to the calculation of safe exposure 7 levels. Lucier et al. (1986) fed adult female Sprague-Dawley rats TCDD contaminated soil or 8 gave them TCDD in corn oil at various doses and compared the effects of TCDD on biochemical 9 parameters from liver tissue. They found that equivalent doses of TC DD in corn oil and soil 10 produced similar increases in hepatic aryl hydrocarbon hydroxylase activity (AHH) and UDP 11 glucuronyltransferase activity. Th ey determined that AHH was sta tistically induced 1.8-fold at 12 15 ng/kg in corn oil and 40 ng/kg in soil. Cytochrome P450 was signi ficantly increased at higher 13 doses. No clinical signs of acute toxicity or changes in body weight were observed. The 14 association between AHH activity and TCDD-me diated hepatotoxicity is unknown and no 15 adverse endpoints were measured. Thus, this e ndpoint is not suitable as a POD candidate. 16 Sugita-Konishi et al. (2003) i nvestigated the change in host resistance of mice offspring 17 lactationally exposed to TCDD. Pregnant C57BL/6NCji mice were administered TCDD via 18 drinking water from parturition to weaning of th e offspring (17 days). One group of offspring 19
was then infected with Listeria monocytogenes and blood and spleen sa mples were collected 20 various time points post infection. Uninfected, TCDD exposed offspring were weighed and their 21 spleens and thymuses removed for assay of cellular content and pr otein expression. TCDD 22 exposure caused a statistically-significant decrease in relative spleen weig ht and a statistically23 significant increase in thymic CD4+ cells in the high-dose group (11.3 ng/kg-day). Offspring 24
infected with Listeria following TCDD exposure exhibited a stat istically significant increase in 25 serum tumor necrosis factor alpha (TNF- α ) 2 days after infection inboth sexes in the low26 (1.14 ng/kg-day) and high-dose groups. The author s conclude that exposure to TCDD disrupted 27 the host resistance of the offspring at the lowe st dose tested, despite the primary immune 28 parameters being unaffected. Without an obvious association between TCDD and immune 29 function, however, this endpoint is not suitable for identifica tion of a LOAEL. Thus, the 30 LOAEL for this study is 11.3 ng/kg- day, and the NOAEL is 1.14 ng/kg-day. 31

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE G-5 Sewall et al. (1993) investigat ed alterations in the epider mal growth factor receptor 1 (EGFR) pathway in a two-stage initiation prom otion model of TCDD hepatic cancer. EGFR 2 signaling has been implicated in the altered cell growth inducti on by tumor promoters. Female 3 Sprague-Dawley rats were administered TCDD bi weekly by oral gavage for 30 weeks following 4 initiation by a single dose of di ethylnitrosamine (DEN). A group also received TCDD without 5 prior DEN initiation. Livers were harvested a nd fixed from sacrificed animals and sections 6 tested for EGFR binding, autophosphoryla tion, immunolocalization, and hepatic cell 7 proliferation. The authors report a significant dose-dependent decrease in plasma membrane 8 EGFR maximum binding capacity in TCDD-exposed rats beginning at 3.5 ng/kg-day. However, 9 at this same dose, the authors note a statistical ly significant decrease in cell proliferation (as 10 measured by DNA replication labeling), with incr eases in proliferation only occurring at higher 11 doses (125 ng/kg-day). No other indicators of hepatic toxicity or tumorigenicity were assessed. 12 The role of EGFR in TCDD-mediated hepatotoxi city and hepatocarcinogenicity is unknown, and 13 as such, this endpoint cannot be unequivocally linked to TCDD-induced hepatic effects nor 14 labeled as adverse. Thus, it is not suitable as a POD candidate. 15
16
G.1. REFERENCES 17 Burleson, GR; Lebrec, H; Yang, YG; et al. (1996) Effect of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on 

## 18 influenza virus host resistance in mice. Fund Appl Toxicol 29:40

− 47. 

## 19
Devito, MJ; Ma, X; Babish, JG; et al. (1994) Dose-response relationships in mice following subchronic exposure to 

## 20 2,3,7,8-tetrachlorodibenzo-p-dioxin: CYP1A1, CYP1A2, estrogen receptor, and protein tyrosine phosphoylation. 

## 21 Toxicol Appl Pharmacol 124:82–90. 

## 22
Hassoun, EA; Wilt, SC; DeVito, MJ; et al. (1998) Induc tion of oxidative stress in brain tissues of mice after 

## 23 subchronic exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin. Toxicol Sci 42:23

− 27. 

## 24
Hassoun, EA; Li, F; Abushaban, A; et al. (2000) The relative abilities of TCDD and its congeners to induce 

## 25 oxidative stress in the hepatic and brain tissues of rats after subchronic exposure. Toxicology 145:103

− 113. 

## 26
Hassoun, EA; Wang, H; Abushaban, A. (2002) Induction of oxidative stress following chronic exposure to TCDD, 

## 27 2,3,4,7,8-pentachlorodibenzofuran, and 2,3’,4,4’,5-pentachlorobiphenyl. J Toxicol Environ Health A 65:825

− 842. 

## 28
Hassoun, EA; Al-Ghafri, M; Abushaban, A. (2003) The role of antioxidant enzymes in TCDD-induced oxidative 

## 29 stress in various brain regions of rats after subchronic exposure. Free Rad Biol Medicine 35(9):1028

− 1036. 

## 30
Kitchin, KT; Woods, JS. (1979) 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) effects on hepatic microsomal 

## 31 cytochrome P-448-mediated enzyme activities. Toxicol Appl Pharmacol 47:537

− 546. 

## 32

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE G-6Kuchiiwa, S; Cheng, S-B; Nagatomo, I; et al. (2002) In utero and lactational exposure to 2,3,7,8-tetrachlorodibenso

## 1
p- dioxin decreases serotonin-immunoreactiv e neurons in raphe nuclei of male mouse offspring. Neurosci Lett 

## 2 317:73

− 76. 

## 3
Lucier, GW; Rumbaugh, RC; McCoy, Z; et al. (1986) Ingestion of soil contaminated with 2,3,7,8-tetrachloro

## 4 dibenzo-p-dioxin (TCDD) alters hepatic enzyme activities in rats. Fund Appl Toxicol 6:364–371. 

## 5
Mally, A; Chipman, JK. (2002) Non-genotoxic carcinogens: early effects on gap junctions, cell proliferation and 

## 6 apoptosis in the rat. Toxicology 180:233–248. 

## 7
Nohara, K; Izumi, H; Tamura, S; et al. (2002) Effect of low-dose 2,3,7,8-tetrachlorodibenzo- p- dioxin (TCDD) on 

## 8 influenza A virus-induced mortality in mice. Toxicology 170:131–138. 

## 9

Sewall, CH; Lucier, GW; Trits cher, AM; et al. (1993) TCDD-mediated cha nges in hepatic epidermal growth factor 

## 10 receptor may be a critical event in the hepatocarcinoge nic action of TCDD. Carci nogenesis 14:1885–1893. 

## 11
Sugita-Konishi, Y; Kobayashi, K; Naito, H; et al. (2003) Effect of lactational exposure to 2,3,7,8- 

## 12 tetrachlorodibenzo- p -dioxin on the susceptibility to Listeria infection. Biosci Biotechnol Biochem 67(1):89

− 93. 

## 13
U.S. EPA. (2003) Exposure and human health reassessment of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and 

## 14 related compounds [NAS review draft]. Volumes 1

− 3. National Center for Environmental Assessment, Washington, 

## 15 DC; EPA/600/P-00/001 Cb. Available at: http://www.epa.gov/nceawww1/pdfs/dioxin/nas-review/. 

## 16
Vanden Heuvel, JP; Clark, GC; Tritscher, A; et al. (1994) Accumulation of polychlorinated dibenzo-p-dioxins and 

## 17 dibenzofurans in liver of control laboratory rats. Fundam Appl Toxicol 23:465–469. 

## 18 19

## DRAFT DO NOT CITE OR QUOTE January 2010 Agency/Interagency Review Draft



# APPENDIX H
Cancer Precursor Benchmark Dose Modeling

NOTICE

THIS DOCUMENT IS AN AGENCY/INTERAGENC Y REVIEW DRAFT. It has not been formally released by the U.S. Environmental Protection Agency and should not at this stage be construed to represent Agency policy. It is being circulated for comment on its technical accuracy and policy implications.

National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-ii CONTENTS—APPENDIX H: Cancer Precursor Benchmark Dose Modeling

APPENDIX H. CANCER PRECURSO R BENCHMARK DOSE MODELING

....................... 1 H.1. BMDS INPUT TABLES .........................................................................................1 H.1.1. Hassoun et al. (2000) ................................................................................1 H.1.2. Kitchin et al. (1979) ..................................................................................1 H.1.3. National Toxicology Program . (2006), 31 W eek Exposure ..................... 2 H.1.4. National Toxicology Program (2006), 53 W eek Exposure ...................... 2 H.1.5. National Toxicology Program (2006), 2 Year E xposure.......................... 2 H.1.6. Van Birgelen et al. (1995a, b)................................................................... 3 H.1.7. Vanden Heuvel et al. (1994) ..................................................................... 3 H.2. ALTERNATE DOSE: BLOO D SERUM BMDS RESULTS ................................3 H.2.1. Hassoun et al. (2000): CytC liver ............................................................3 H.2.1.1. Summary Table of BMDS Modeling Results............................ 3 H.2.1.2. Figure for Selected Model: Exponential (M5), Constant Variance, P ower Restricted ≥ 1 ..................................................5 H.2.1.3. Output File for Selected Model: Exponential (M5), Constant Variance, Power Restricted ≥ 1 ...................................5 H.2.1.4. Figure for Unrestricted Model: Exponential (M5), Constant Variance, Power Unrestricted .....................................8 H.2.1.5. Output file for Unrestrict ed Model: Exponential (M5), Constant Variance, Power Unrestricted .....................................8 H.2.1.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted ..............................................................................11 H.2.1.7. Output File for Unrestrict ed Model: Hill, Constant Variance, n Unrestricted

.......................................................... 11 H.2.1.8. Figure for Unrestricted Model: Power, Constant Variance, P ower Unrestricted .................................................. 14 H.2.1.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted .................................................. 14 H.2.2. Hassoun et al. (2000): DNA SSB ..........................................................17 H.2.2.1. Summary Table of BMDS Modeling Results.......................... 17 H.2.2.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1 ................................................18 H.2.2.3. Output File For Selected Model: Exponential (M4), Constant Variance, Power Restricted ≥ 1 .................................18 H.2.2.4. Figure for Unrestricted Model: Exponential (M5), Constant Variance, Power Unrestricted ...................................21 H.2.2.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted ...................................21 H.2.2.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted ..............................................................................24 H.2.2.7. Output File For Unrestrict ed Model: Hill, Constant Variance, n Unrestricted

.......................................................... 24

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-iii CONTENTS (continued)

H.2.2.8. Figure for Unrestricted Model: Power, Constant Variance, P ower Unrestricted .................................................. 27 H.2.2.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted .................................................. 27 H.2.3. Hassoun et al. (2000): TBARs Liver .....................................................30 H.2.3.1. Summary Table of BMDS Modeling Results.......................... 30 H.2.3.2. Figure for Selected Model: Exponential (M5), Constant Variance, P ower Unrestricted .................................................. 31 H.2.3.3. Output File for Selected Model: Exponential (M5), Constant Variance, Power Unrestricted ...................................31 H.2.3.4. Figure for Unrestricted Mode l: Hill, Constant Variance, n Restricted >1 ............................................................................34 H.2.3.5. Output File for Unrestrict ed Model: Hill, Constant Variance, n Restricted >1

......................................................... 34 H.2.3.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted ..............................................................................37 H.2.3.7. Output File for Unrestrict ed Model: Hill, Constant Variance, n Unrestricted

.......................................................... 37 H.2.3.8. Figure for Unrestricted Model: Power, Constant Variance, P ower Unrestricted .................................................. 40 H.2.3.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted .................................................. 40 H.2.4. Kitchin et al. (1979): BaP Hydrolase Activity.......................................43 H.2.4.1. Summary Table of BMDS Modeling Results.......................... 43 H.2.4.2. Figure for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 ...........................44 H.2.4.3. Output File for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 ...........................44 H.2.4.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 47 H.2.4.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 47 H.2.4.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

.......................................................... 50 H.2.4.7. Output File for Unrestri cted Model: Hill, Nonco nstant Variance, n Unrestricted .......................................................... 51 H.2.4.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted .................................................. 53 H.2.4.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted .................................................. 53 H.2.5. National Toxicology Program. (2006): EROD Liver W eek 53............. 57 H.2.5.1. Summary Table of BMDS Modeling Results.......................... 57

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-iv CONTENTS (continued)

H.2.5.2. Figure for Selected Model: Hill, Nonconstant Variance, n Restricted >1 ............................................................................58 H.2.5.3. Output file for Selected Model: Hill, Nonconstant Variance, n Restricted >1

......................................................... 58 H.2.5.4. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

.......................................................... 61 H.2.5.5. Output file for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted .......................................................... 61 H.2.6. National Toxicology Program. (2006): Lung E ROD Week 31 ............. 64 H.2.6.1. Summary Table of BMDS Modeling Results.......................... 64 H.2.6.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 ...........................65 H.2.6.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 ...........................65 H.2.6.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 68 H.2.6.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 68 H.2.6.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

.......................................................... 71 H.2.6.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted .......................................................... 71 H.2.6.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted .................................................. 74 H.2.6.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted .................................................. 74 H.2.7. National Toxicology Program. (2006): Lung E ROD Week 53 ............. 77 H.2.7.1. Summary Table of BMDS Modeling Results.......................... 77 H.2.7.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 ...........................78 H.2.7.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 ...........................78 H.2.7.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 81 H.2.7.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 81 H.2.7.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

.......................................................... 84 H.2.7.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted .......................................................... 84 H.2.7.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted .................................................. 87

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-v CONTENTS (continued)

H.2.7.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted .................................................. 87 H.2.8. National Toxicology Program. ( 2006): Tbl11 Index W eek 31.............. 90 H.2.8.1. Summary Table of BMDS Modeling Results.......................... 90 H.2.8.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1 ...........................91 H.2.8.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1 ...........................91 H.2.9. Van Birgelen et al. (1995b): T4 UGT.................................................... 94 H.2.9.1. Summary Table of BMDS Modeling Results.......................... 94 H.2.9.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 ...........................95 H.2.9.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 ...........................95 H.2.9.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 98 H.2.9.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted............................. 98 H.2.9.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 101 H.2.9.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 101 H.2.9.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted ................................................ 105 H.2.9.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted ................................................ 105 H.2.10. Van Birgelen et al. (1995b): UGT 1A1 ............................................... 108 H.2.10.1. Summary Table of BMDS Modeling Results........................ 108 H.2.10.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................109 H.2.10.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................109 H.2.10.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 112 H.2.10.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 112 H.2.10.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 115 H.2.10.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 115 H.2.10.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted ................................................ 118

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-vi CONTENTS (continued)

H.2.10.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted ................................................ 118 H.2.11. Vanden Heuvel et al. (1994): Hepatic CYP1A1 mRNA Expr ession... 121 H.2.11.1. Summary Table of BMDS Modeling Results........................ 121 H.2.11.2. Figure for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 .........................122 H.2.11.3. Output File for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 .........................122 H.3. ADMINISTERED DOSE BMDS RESULTS ..................................................... 125 H.3.1. Hassoun et al. (2000): CytC Liver .......................................................125 H.3.1.1. Summary Table of BMDS Modeling Results........................ 125 H.3.1.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1 ..............................................126 H.3.1.3. Output File for Selected Model: Exponential (M4), Constant Variance, Power Restricted ≥ 1 ...............................126 H.3.1.4. Figure for Unrestricted Mode l: Exponential (M5), Constant Variance, P ower Unrestricted ................................................ 129 H.3.1.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted .................................129 H.3.1.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted ............................................................................132 H.3.1.7. Output File for Unrestrict ed Model: Hill, Constant Variance, n Unrestricted

........................................................ 132 H.3.1.8. Figure for Unrestricted Model: Power, Constant Variance, P ower Unrestricted ................................................ 135 H.3.1.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted ................................................ 135 H.3.2. Hassoun et al. (2000): DNA SSB ........................................................138 H.3.2.1. Summary Table of BMDS Modeling Results........................ 138 H.3.2.2. Figure for Selected Model: Exponential (M5), Constant Variance, P ower Unrestricted ................................................ 139 H.3.2.3. Output File for Selected Model: Exponential (M5), Constant Variance, Power Unrestricted .................................139 H.3.2.4. Figure for Unrestricted Mode l: Hill, Constant Variance, n Restricted >1, Bound Hit .......................................................142 H.3.2.5. Output File for Unrestrict ed Model: Hill, Constant Variance, n Restricted >1, Bound Hit

.................................... 142 H.3.2.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted .........................................................................145 H.3.2.7. Output File for Unrestrict ed Model: Hill, Constant Variance, n Unrestricted

........................................................ 145 H.3.2.8. Figure for Unrestricted Model: Power, Constant Variance, P ower Unrestricted ................................................ 148

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-vii CONTENTS (continued)

H.3.2.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted ................................................ 148 H.3.3. Hassoun et al. (2000): TBARs Liver ...................................................151 H.3.3.1. Summary Table of BMDS Modeling Results........................ 151 H.3.3.2. Figure for Selected Model: Exponential (M4), Constant Variance, P ower Restricted ≥ 1 ..............................................152 H.3.3.3. Output File for Selected Model: Exponential (M4), Constant Variance, Power Restricted ≥ 1 ...............................152 H.3.3.4. Figure for Unrestricted Model: Exponential (M5), Constant Variance, Power Unrestricted .................................155 H.3.3.5. Output File for Unrestri cted Model: Exponential (M5), Constant Variance, Power Unrestricted .................................155 H.3.3.6. Figure for Unrestricted Mode l: Hill, Constant Variance, n Unrestricted .........................................................................158 H.3.3.7. Output File for Unrestrict ed Model: Hill, Constant Variance, n Unrestricted

........................................................ 158 H.3.3.8. Figure for Unrestricted Model: Power, Constant Variance, P ower Unrestricted ................................................ 161 H.3.3.9. Output File for Unrestrict ed Model: Power, Constant Variance, P ower Unrestricted ................................................ 161 H.3.4. Kitchin et al. (1979): BaP Hydrolase Activity.....................................164 H.3.4.1. Summary Table of BMDS Modeling Results........................ 164 H.3.4.2. Figure for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 .........................165 H.3.4.3. Output File for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 .........................165 H.3.4.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 168 H.3.4.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 168 H.3.4.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 171 H.3.4.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 172 H.3.4.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted ................................................ 174 H.3.4.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted ................................................ 175 H.3.5. National Toxicology Program. (2006): EROD Liver W eek 53........... 177 H.3.5.1. Summary Table of BMDS Modeling Results........................ 177 H.3.5.2. Figure for Selected Model: Hill, Nonconstant Variance, n Restricted >1

....................................................................... 178

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— DO NOT CITE OR QUOTE H-viii CONTENTS (continued)

H.3.5.3. Output File for Selected Model: Hill, Nonconstant Variance, n Restricted >1

....................................................... 179 H.3.5.4. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 181 H.3.5.5. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 181 H.3.6. National Toxicology Program. (2006): Lung E ROD Week 31 ........... 184 H.3.6.1. Summary Table of BMDS Modeling Results........................ 184 H.3.6.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................185 H.3.6.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................185 H.3.6.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 188 H.3.6.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 188 H.3.6.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 191 H.3.6.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 191 H.3.6.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted ................................................ 194 H.3.6.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted ................................................ 194 H.3.7. National Toxicology Program. (2006): Lung E ROD Week 53 ........... 197 H.3.7.1. Summary Table of BMDS Modeling Results........................ 197 H.3.7.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................198 H.3.7.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................198 H.3.7.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 201 H.3.7.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 201 H.3.7.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 204 H.3.7.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 204 H.3.7.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted ................................................ 207 H.3.7.9. Output File for Unrestrict ed Model: Power, Nonconstant Variance, P ower Unrestricted ................................................ 207 H.3.8. National Toxicology Program. ( 2006): Tbl11 Index W eek 31............ 210

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-ix CONTENTS (continued)

H.3.8.1. Summary Table of BMDS Modeling Results........................ 210 H.3.8.2. Figure for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1 .........................211 H.3.8.3. Output File for Selected Model: Exponential (M2), Nonconstant Variance, P ower Restricted ≥ 1 .........................211 H.3.9. Van Birgelen et al. (1995b): T4 UGT.................................................. 214 H.3.9.1. Summary Table of BMDS Modeling Results........................ 214 H.3.9.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................215 H.3.9.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................215 H.3.9.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 218 H.3.9.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 218 H.3.9.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 221 H.3.9.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 221 H.3.9.8. Figure for Unrestricted M odel: Power, Nonconstant Variance, P ower Unrestricted ................................................ 224 H.3.9.9. Output File for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted........................... 224 H.3.10. Van Birgelen et al. (1995b): UGT 1A1 ............................................... 227 H.3.10.1. Summary Table of BMDS Modeling Results........................ 227 H.3.10.2. Figure for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................228 H.3.10.3. Output File for Selected Model: Exponential (M4), Nonconstant Variance, P ower Restricted ≥ 1 .........................228 H.3.10.4. Figure for Unrestricted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 231 H.3.10.5. Output File for Unrestri cted Model: Exponential (M5), Nonconstant Variance, P ower Unrestricted........................... 231 H.3.10.6. Figure for Unrestricted Model: Hill, Nonconstant Variance, n Unrestricted

........................................................ 234 H.3.10.7. Output File for Unrestrict ed Model: Hill, Nonco nstant Variance, n Unrestricted ........................................................ 234 H.3.10.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted................................................................. 237 H.3.10.9. Output File for Unrestricted Model: Power, Nonconstant Variance, P ower Unrestricted........................... 237 H.3.11. Vanden Heuvel et al. (1994) : Hepatic CYP1A1 mRNA Expression ........................................................................................ 240

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-x CONTENTS (continued)

H.3.11.1. Summary Table of BMDS Modeling Results........................ 240 H.3.11.2. Figure for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 .........................241 H.3.11.3. Output File for Selected Model: Exponential (M5), Nonconstant Variance, P ower Restricted ≥ 1 .........................241 H.4. REFERENCES .................................................................................................... 244

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-1 APPENDIX H. CANCER PRECURSOR BENCHM ARK DOSE MODELING 1 2 3 H.1. BMDS INPUT TABLES 4
H.1.1. Hassoun et al. (2000) 5

Administered Dose (ng/kg-day)

0 3 10 22 46 100 Internal Dose (ng/kg blood) a

0 1,068 2,542 4,489 7,718 13,960 Endpoint n = 6 n = 6 n = 6 n = 6 n = 6 n = 6 CytC liver 0.15 ± 0.07 0.18 ± 0.05 b 0.19 ± 0.06 0.27 ± 0.06 c 0.39 ± 0.06 c 0.44 ± 0.11 c

DNA SSB 7.41 ± 1.54 10.78 ± 1.25 b,c 13.6 ± 1.69 c 15.3 ± 1.71 c 20.4 ± 2.25 c 23.5 ± 1.37 c

TBARs liver 1.47 ± 0.29 1.55 ± 0.54 b 2.15 ± 0.36 c 2.28 ± 0.25 c 2.62 ± 0.52 c 2.29 ± 0.49 c

a 

### From the Emond PRPK model described in 3.3. b 

### LOEL for selected endpoint.

c 

### Statistically significant as compared to control ( p < 0.05). 

## 6 7 H.1.2. Kitchin et al. (1979) 8

Administered Dose (ng/kg-day)
0 0.2 0.667 1.33 6.67 20 Internal Dose (ng/kg blood) a
0 70 232 463 2,318 6,949 Endpoint n = 9 n = 4 n = 4 n = 4 n = 4 n = 4 BaP hydrolase activity (continued on next line) 4.9 ± 1.11 4.9 ± 1.18 b 6.7 ± 1.4 c,d 7.2 ± 1.8 d 8.3 ± 0.26 e 14 ± 5 e Administered Dose (ng/kg-day)
66.7 200 667 1,670 6,670 Internal Dose (ng/kg blood) a 23,185 69,657 232,550 581,930 2,332,100 Endpoint n = 4 n = 4 n = 4 n = 4 n = 4 BaP hydrolase activity (continued) 59 ± 6.8 e 96 ± 46 e 155 ± 16.4 e 182 ± 26 e 189 ± 26 e

a 

### From the Emond PRPK model described in 3.3. b 

### NOEL for selected endpoint.

c 

### LOEL for selected endpoint. d 

### Statistically significant as compared to control ( p < 0.05).

e 

### Statistically significant as compared to control ( p < 0.001). 

## 9 10

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-2 H.1.3. National Toxicology Program. (2006), 31 Week Exposure 1

Administered Dose (ng/kg-day)

0 2.14 7.14 15.7 32.9 71.4
Internal Dose (ng/kg blood) a

0 1,284 2,932 5,075 8,629 15,503 Endpoint n = 9 n = 10 n = 10 n = 10 n = 10 n = 10

Tbl11 Index ,week 31 0.33 ± 0.19 0.85 ± 0.65 b 0.96 ± 0.74 b 0.79 ± 0.46 b 1.33 ± 1.12 b 3.85 ± 3.08 b

Lung EROD, week 31 2.07 ± 0.97 25.34 ± 2.55 c 30.39 ± 5.83 c 50.19 ± 8.68 c 49.07 ± 13.91 c 48.42 ± 8.93 c

a 

### From the Emond PRPK model described in 3.3. b 

### Statistically significant as compared to control ( p < 0.05).

c 

### Statistically significant as compared to control ( p < 0.01). 

## 2 3 H.1.4. National Toxicology Program (2006), 53 Week Exposure 4

Administered Dose (ng/kg-day)

0 2.14 7.14 15.7 32.9 71.4
Internal Dose (ng/kg blood) a

0 1,354 3,056 5,259 8,918 16,001 Endpoint n = 8 n = 8 n = 8 n = 8 n = 8 n = 8

Liver EROD, week 53 3.61 ± 0.49 7.27 ± 0.56 b 14.76 ± 1.61 b 17.28 ± 1.59 b 20.58 ± 3.05 b 21.21 ± 3.82 b

Lung EROD, week 53 3.01 ± 1.58 27.15 ± 5.27 b 42.85 ± 11.15 b 36.57 ± 12.99 b 43.75 ± 18.55 b 43.71 ± 6.32 b

a 

### From the Emond PRPK model described in 3.3. b 

### Statistically significant as compared to control ( p < 0.01). 

## 5 6 H.1.5. National Toxicology Program (2006), 2 Year Exposure 7

Administered Dose (ng/kg-day)

0 2.14 7.14 15.7 32.9 71.4 Internal Dose (ng/kg blood) a

0 1,408 3,137 5,393 9,129 16,361 Endpoint n = 53 n = 54 n = 53 n = 53 n = 53 n = 53
Toxic Hepatopathy 0/53 (0%) 2/54 (0%) 8/53 (20%) b 30/53 (60%) b 45/53 (80%) b 53/53 (100%) b

a 

### From the Emond PRPK model described in 3.3. b 

### Statistically significant as compared to control ( p < 0.01). 

## 8

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-3 H.1.6. Van Birgelen et al. (1995a, b) 1

Administered Dose (ng/kg-day)

0 14 26 47 320 1,024
Internal Dose (ng/kg blood) a

0 3,969 6,479 9,968 47,606 137,820 Endpoint n = 8 n = 8 n = 8 n = 8 n = 8 n = 8

T4 UGT 0.33 ± 0.2 0.6 ± 0.42 0.64 ± 0.45 b 0.87 ± 0.91 b 2.08 ± 1.33 b 2.59 ± 0.88 b

UGT 1A1 101 ± 15.59 194 ± 36.37 b Not reported. 304 ± 17.32 b 452 ± 48.5 b 296 ± 148.96 b

a 

### From the Emond PRPK model described in 3.3. b 

### Statistically significant as compared to control ( p < 0.05). 

## 2 3 H.1.7. Vanden Heuvel et al. (1994) 4

Administered Dose (ng/kg-day)
0 0.1 1 10 100 1,000 10,000 Internal Dose (ng/kg blood) a
0 4 36 302 2,149 14,301 114,690 Endpoint

n = 13 n = 5 n = 12 n = 7 n = 7 n = 11 n = 5 Hepatic CYP1A1 mRNA Expression 5.4 ± 3.61 7.2 ± 5.59 14.8 ± 14.9 b 12.8 ± 4.5 b 536 ± 320.14 b 18000 ± 15223.31 b 36700 ± 22137.07 b

a 

### From the Emond PRPK model described in 3.3. b 

### Statistically significant as compared to control ( p < 0.05). 

## 5 6 H.2. ALTERNATE DOSE: BLOOD SERUM BMDS RESULTS 7
H.2.1. Hassoun et al. (2000): CytC liver 8
H.2.1.1. Summary Table of BMDS Modeling Results 9

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 0.39 10.22 0.04 -145.92 3.5E+03 2.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.39 10.22 0.04 -145.92 3.5E+03 2.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.39 3.38 0.34 -150.76 1.6E+03 9.7E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.39 0.56 0.76 -151.58 3.0E+03 1.4E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.39 0.56 0.76 -151.58 3.0E+03 1.4E+03 nonconstant variance, power unrestricted

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-4 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

Hill 2 0.39 0.66 0.72 -151.47 3.1E+03 error nonconstant variance, n restricted >1

Hill 2 0.39 0.66 0.72 -151.47 3.1E+03 error nonconstant variance, n unrestricted

linear 4 0.39 4.68 0.32 -151.45 2.1E+03 1.4E+03 nonconstant variance

polynomial 4 0.39 4.68 0.32 -151.45 2.1E+03 1.4E+03 nonconstant variance

power 4 0.39 4.68 0.32 -151.45 2.1E+03 1.4E+03 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.39 4.26 0.23 -149.87 1.6E+03 6.8E+02 nonconstant variance, power unrestricted
exponential (M2) 4 0.39 12.17 0.02 -143.33 5.1E+03 4.3E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 0.39 12.17 0.02 -143.33 5.1E+03 4.3E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 0.39 3.37 0.34 -150.14 1.9E+03 1.2E+03 constant variance, power restricted ≥ 1
exponential (M5) c 2 0.39 0.48 0.79 -151.03 3.3E+03 1.7E+03 constant variance, power restricted ≥ 1
exponential (M5) d 2 0.39 0.48 0.79 -151.03 3.3E+03 1.7E+03 constant variance, power unrestricted

Hill 2 0.39 0.59 0.74 -150.91 3.4E+03 1.8E+03 constant variance, n restricted >1

Hill d 2 0.39 0.59 0.74 -150.91 3.4E+03 1.8E+03 constant variance, n unrestricted

linear 4 0.39 6.42 0.17 -149.09 3.1E+03 2.4E+03 constant variance

polynomial 4 0.39 6.42 0.17 -149.09 3.1E+03 2.4E+03 constant variance

power 4 0.39 6.42 0.17 -149.09 3.1E+03 2.4E+03 constant variance, power restricted ≥ 1, bound hit

power d 3 0.39 4.84 0.18 -148.66 1.8E+03 7.4E+02 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant va riance model should be selected b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix d Alternate model also presented in this appendix 

## 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-5 H.2.1.2. Figure for Selected Model: Exponential (M 5), Constant Variance, Power Restricted 1 ≥ 1 2

0.1 0.2 0.3 0.4 0.5 0.6

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Exponential



## 3 4 5 H.2.1.3. Output File for Selected Model: Expo nential (M5), Constant Variance, Power 6 Restricted ≥ 1 7 8 9

==================================================================== 

## 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 11 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Exp_CV_BMR1_CytC_Liver.(d) 

## 12 Gnuplot Plotting File: 

## 13
Mon Nov 23 12:51:43 2009 

## 14

==================================================================== 

## 15 16 TBARs, liver only (Table 2) 

## 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 18 19 The form of the response function by Model: 

## 20 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 24 25 Note: Y[dose] is the median response for exposure = dose; 

## 26 sign = +1 for increasing trend in data; 

## 27 sign = -1 for decreasing trend. 

## 28 29
Model 2 is nested within Models 3 and 4. 

## 30
Model 3 is nested within Model 5. 

## 31
Model 4 is nested within Model 5. 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Data are assumed to be distributed: normally 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-6 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 1
rho is set to 0. 

## 2
A constant variance model is fit. 

## 3 4 Total number of dose groups = 6 

## 5 Total number of records with missing values = 0 

## 6
Maximum number of iterations = 250 

## 7 Relative Function Convergence has been set to: 1e-008 

## 8 Parameter Convergence has been set to: 1e-008 

## 9 10 MLE solution provided: Exact 

## 11 12 13
Initial Parameter Values 

## 14 15
Variable Model 5 

## 16

-------- -------- 

## 17 lnalpha -5.48625 

## 18 rho(S) 0 

## 19
a 0.1387 

## 20
b 4.08913e-005 

## 21
c 6.40231 

## 22
d 1 

## 23 24 (S) = Specified 

## 25 26 27 28
Parameter Estimates 

## 29 30
Variable Model 5 

## 31

-------- ------- 

## 32 lnalpha -5.47298 

## 33
rho 0 

## 34
a 0.156024 

## 35
b 0.00016181 

## 36
c 2.85354 

## 37
d 2.14237 

## 38 39 40 Table of Stats From Input Data 

## 41 42
Dose N Obs Mean Obs Std Dev 

## 43

----- --- ---------- ------------- 

## 44
0 6 0.146 0.06614 

## 45
1068 6 0.177 0.05389 

## 46
2542 6 0.191 0.05634 

## 47
4489 6 0.271 0.05634 

## 48
7718 6 0.388 0.06369 

## 49
1.396e+004 6 0.444 0.1102 

## 50 51 52
Estimated Values of Interest 

## 53 54
Dose Est Mean Est Std Scaled Residual 

## 55

------ ---------- --------- ---------------- 

## 56
0 0.156 0.0648 -0.3789 

## 57
1068 0.1627 0.0648 0.5416 

## 58
2542 0.1961 0.0648 -0.1919 

## 59
4489 0.2705 0.0648 0.01767 

## 60
7718 0.3874 0.0648 0.02225 

## 61
1.396e+004 0.4443 0.0648 -0.0107 

## 62 63 64 65
Other models for which likelihoods are calculated: 

## 66 67 Model A1: Yij = Mu(i) + e(ij) 

## 68 Var{e(ij)} = Sigma^2 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-7 Model A2: Yij = Mu(i) + e(ij) 

## 1 Var{e(ij)} = Sigma(i)^2 

## 2 3 Model A3: Yij = Mu(i) + e(ij) 

## 4 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 5 6 Model R: Yij = Mu + e(i) 

## 7 Var{e(ij)} = Sigma^2 

## 8 9 10
Likelihoods of Interest 

## 11 12 Model Log(likelihood) DF AIC 

## 13

------- ----------------- ---- ------------ 

## 14
A1 80.75258 7 -147.5052 

## 15
A2 83.37355 12 -142.7471 

## 16
A3 80.75258 7 -147.5052 

## 17
R 55.82002 2 -107.64 

## 18
5 80.51365 5 -151.0273 

## 19 20 21 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 22 above values gives the log-likelihood including the term that does not 

## 23 depend on the model parameters. 

## 24 25 26 Explanation of Tests 

## 27 28 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 29 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 30 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 31 32 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 33 34 35
Tests of Interest 

## 36 37 Test -2*log(Likelihood Ratio) D. F. p-value 

## 38

-------- ------------------------ ------ -------------- 

## 39
Test 1 55.11 10 < 0.0001 

## 40
Test 2 5.242 5 0.3871 

## 41
Test 3 5.242 5 0.3871 

## 42
Test 7a 0.4779 2 0.7875 

## 43 44 45 The p-value for Test 1 is less than .05. There appears to be a 

## 46 difference between response and/or variances among the dose 

## 47 levels, it seems appropriate to model the data. 

## 48 49 The p-value for Test 2 is greater than .1. A homogeneous 

## 50 variance model appears to be appropriate here. 

## 51 52 The p-value for Test 3 is greater than .1. The modeled 

## 53 variance appears to be appropriate here. 

## 54 55 The p-value for Test 7a is greater than .1. Model 5 seems 

## 56 to adequately describe the data. 

## 57 58 59 Benchmark Dose Computations: 

## 60 61 Specified Effect = 1.000000 

## 62 63 Risk Type = Estimated standard deviations from control 

## 64 65
Confidence Level = 0.950000 

## 66 67
BMD = 3257.85 

## 68 69
BMDL = 1709.28 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-8 H.2.1.4. Figure for Unrestricted Model: Expon ential (M5), Constant Variance, Power 1 Unrestricted 2

0.1 0.2 0.3 0.4 0.5 0.6

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Exponential



## 3 4 5 H.2.1.5. Output file for Unrestricted Model: Exponential (M5), Constant Varian ce, Power 6 Unrestricted 7 8 9

==================================================================== 

## 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 11 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Exp_CV_Unrest_BMR1_CytC_Liver.(d) 

## 12 Gnuplot Plotting File: 

## 13
Mon Nov 23 12:51:49 2009 

## 14

==================================================================== 

## 15 16 TBARs, liver only (Table 2) 

## 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 18 19 The form of the response function by Model: 

## 20 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 24 25 Note: Y[dose] is the median response for exposure = dose; 

## 26 sign = +1 for increasing trend in data; 

## 27 sign = -1 for decreasing trend. 

## 28 29
Model 2 is nested within Models 3 and 4. 

## 30
Model 3 is nested within Model 5. 

## 31
Model 4 is nested within Model 5. 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Data are assumed to be distributed: normally 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-9 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 1
rho is set to 0. 

## 2
A constant variance model is fit. 

## 3 4 Total number of dose groups = 6 

## 5 Total number of records with missing values = 0 

## 6
Maximum number of iterations = 250 

## 7 Relative Function Convergence has been set to: 1e-008 

## 8 Parameter Convergence has been set to: 1e-008 

## 9 10 MLE solution provided: Exact 

## 11 12 13
Initial Parameter Values 

## 14 15
Variable Model 5 

## 16

-------- -------- 

## 17 lnalpha -5.48625 

## 18 rho(S) 0 

## 19
a 0.1387 

## 20
b 4.08913e-005 

## 21
c 6.40231 

## 22
d 1 

## 23 24 (S) = Specified 

## 25 26 27 28
Parameter Estimates 

## 29 30
Variable Model 5 

## 31

-------- ------- 

## 32 lnalpha -5.47298 

## 33
rho 0 

## 34
a 0.156024 

## 35
b 0.00016181 

## 36
c 2.85354 

## 37
d 2.14237 

## 38 39 40 Table of Stats From Input Data 

## 41 42
Dose N Obs Mean Obs Std Dev 

## 43

----- --- ---------- ------------- 

## 44
0 6 0.146 0.06614 

## 45
1068 6 0.177 0.05389 

## 46
2542 6 0.191 0.05634 

## 47
4489 6 0.271 0.05634 

## 48
7718 6 0.388 0.06369 

## 49
1.396e+004 6 0.444 0.1102 

## 50 51 52
Estimated Values of Interest 

## 53 54
Dose Est Mean Est Std Scaled Residual 

## 55

------ ---------- --------- ---------------- 

## 56
0 0.156 0.0648 -0.3789 

## 57
1068 0.1627 0.0648 0.5416 

## 58
2542 0.1961 0.0648 -0.1919 

## 59
4489 0.2705 0.0648 0.01767 

## 60
7718 0.3874 0.0648 0.02225 

## 61
1.396e+004 0.4443 0.0648 -0.0107 

## 62 63 64
Other models for which likelihoods are calculated: 

## 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-10 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 4 5 Model R: Yij = Mu + e(i) 

## 6 Var{e(ij)} = Sigma^2 

## 7 8 9
Likelihoods of Interest 

## 10 11 Model Log(likelihood) DF AIC 

## 12

------- ----------------- ---- ------------ 

## 13
A1 80.75258 7 -147.5052 

## 14
A2 83.37355 12 -142.7471 

## 15
A3 80.75258 7 -147.5052 

## 16
R 55.82002 2 -107.64 

## 17
5 80.51365 5 -151.0273 

## 18 19 20 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 21 above values gives the log-likelihood including the term that does not 

## 22 depend on the model parameters. 

## 23 24 25 Explanation of Tests 

## 26 27 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 28 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 29 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 30 31 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 32 33
Tests of Interest 

## 34 35 Test -2*log(Likelihood Ratio) D. F. p-value 

## 36

-------- ------------------------ ------ -------------- 

## 37
Test 1 55.11 10 < 0.0001 

## 38
Test 2 5.242 5 0.3871 

## 39
Test 3 5.242 5 0.3871 

## 40
Test 7a 0.4779 2 0.7875 

## 41 42 43 The p-value for Test 1 is less than .05. There appears to be a 

## 44 difference between response and/or variances among the dose 

## 45 levels, it seems appropriate to model the data. 

## 46 47 The p-value for Test 2 is greater than .1. A homogeneous 

## 48 variance model appears to be appropriate here. 

## 49 50 The p-value for Test 3 is greater than .1. The modeled 

## 51 variance appears to be appropriate here. 

## 52 53 The p-value for Test 7a is greater than .1. Model 5 seems 

## 54 to adequately describe the data. 

## 55 56 57 Benchmark Dose Computations: 

## 58 59 Specified Effect = 1.000000 

## 60 61 Risk Type = Estimated standard deviations from control 

## 62 63
Confidence Level = 0.950000 

## 64 65
BMD = 3257.85 

## 66 67
BMDL = 1709.28 

## 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-11 H.2.1.6. Figure for Unrestricted Model: Hill, Constant Variance, n Unrestricted 1

0.1 0.2 0.3 0.4 0.5 0.6

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Hill Model with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Hill



## 2 3 4 H.2.1.7. Output File for Unrestricted Model: Hill, Constant Variance, n Unrestricted 5 6 7

==================================================================== 

## 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_Unrest_BMR1_CytC_Liver.(d) 

## 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_Unrest_BMR1_CytC_Liver.plt 

## 11
Mon Nov 23 12:51:51 2009 

## 12

==================================================================== 

## 13 14 TBARs, liver only (Table 2) 

## 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 16 17 The form of the response function is: 

## 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 20 21 22 Dependent variable = Mean 

## 23 Independent variable = Dose 

## 24
rho is set to 0 

## 25 Power parameter is not restricted 

## 26
A constant variance model is fit 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37 alpha = 0.004972 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-12 rho = 0 Specified 

## 1 intercept = 0.146 

## 2
v = 0.298 

## 3
n = 18 

## 4
k = 10285.5 

## 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 

## 8 9 ( *** The model parameter(s) -rho 

## 10 have been estimated at a boundary point, or have been specified by the user, 

## 11 and do not appear in the correlation matrix ) 

## 12 13 alpha intercept v n k 

## 14 15 alpha 1 -2.4e-008 4.5e-008 -5.6e-008 2.4e-008 

## 16 17 intercept -2.4e-008 1 -0.61 0.52 0.098 

## 18 19
v 4.5e-008 -0.61 1 -0.83 0.6 

## 20 21
n -5.6e-008 0.52 -0.83 1 -0.48 

## 22 23
k 2.4e-008 0.098 0.6 -0.48 1 

## 24 25 26 27
Parameter Estimates 

## 28 29
95.0% Wald Confidence Interval 

## 30 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 31 alpha 0.00421237 0.000992864 0.00226639 0.00615834 

## 32 intercept 0.159647 0.0202575 0.119943 0.199351 

## 33
v 0.303055 0.0583218 0.188746 0.417363 

## 34
n 2.91267 1.3832 0.201656 5.62369 

## 35
k 5344.44 923.736 3533.95 7154.93 

## 36 37 38 39
Table of Data and Estimated Values of Interest 

## 40 41
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 42

------ --- -------- -------- ----------- ----------- ---------- 

## 43 44
0 6 0.146 0.16 0.0661 0.0649 -0.515 

## 45
1068 6 0.177 0.162 0.0539 0.0649 0.551 

## 46
2542 6 0.191 0.191 0.0563 0.0649 0.00541 

## 47
4489 6 0.271 0.273 0.0563 0.0649 -0.0938 

## 48
7718 6 0.388 0.385 0.0637 0.0649 0.101 

## 49
1.396e+004 6 0.444 0.445 0.11 0.0649 -0.0481 

## 50 51 52 53 Model Descriptions for likelihoods calculated 

## 54 55 56 Model A1: Yij = Mu(i) + e(ij) 

## 57 Var{e(ij)} = Sigma^2 

## 58 59 Model A2: Yij = Mu(i) + e(ij) 

## 60 Var{e(ij)} = Sigma(i)^2 

## 61 62 Model A3: Yij = Mu(i) + e(ij) 

## 63 Var{e(ij)} = Sigma^2 

## 64 Model A3 uses any fixed variance parameters that 

## 65 were specified by the user 

## 66 67 Model R: Yi = Mu + e(i) 

## 68 Var{e(i)} = Sigma^2 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-13 1
Likelihoods of Interest 

## 2 3 Model Log(likelihood) # Param's AIC 

## 4
A1 80.752584 7 -147.505168 

## 5
A2 83.373547 12 -142.747094 

## 6
A3 80.752584 7 -147.505168 

## 7 fitted 80.455153 5 -150.910305 

## 8
R 55.820023 2 -107.640047 

## 9 10 11 Explanation of Tests 

## 12 13 Test 1: Do responses and/or variances differ among Dose levels? 

## 14 (A2 vs. R) 

## 15 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 16 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 17 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 18 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 19 20
Tests of Interest 

## 21 22 Test -2*log(Likelihood Ratio) Test df p-value 

## 23 24
Test 1 55.107 10 <.0001 

## 25
Test 2 5.24193 5 0.3871 

## 26
Test 3 5.24193 5 0.3871 

## 27
Test 4 0.594862 2 0.7427 

## 28 29 The p-value for Test 1 is less than .05. There appears to be a 

## 30 difference between response and/or variances among the dose levels 

## 31 It seems appropriate to model the data 

## 32 33 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 34 model appears to be appropriate here 

## 35 36 37 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 38 to be appropriate here 

## 39 40 The p-value for Test 4 is greater than .1. The model chosen seems 

## 41 to adequately describe the data 

## 42 43 44 Benchmark Dose Computation 

## 45 46 Specified effect = 1 

## 47 48 Risk Type = Estimated standard deviations from the control mean 

## 49 50
Confidence level = 0.95 

## 51 52
BMD = 3420.29 

## 53 54
BMDL = 1757.33 

## 55 56

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-14 H.2.1.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

0.1 0.2 0.3 0.4 0.5

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Power Model with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Power



## 2 3 4 H.2.1.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5 6 7

==================================================================== 

## 8 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Pwr_CV_Unrest_BMR1_CytC_Liver.(d) 

## 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Pwr_CV_Unrest_BMR1_CytC_Liver.plt 

## 11
Mon Nov 23 12:51:51 2009 

## 12

==================================================================== 

## 13 14 TBARs, liver only (Table 2) 

## 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 16 17 The form of the response function is: 

## 18 19 Y[dose] = control + slope * dose^power 

## 20 21 22 Dependent variable = Mean 

## 23 Independent variable = Dose 

## 24
rho is set to 0 

## 25 The power is not restricted 

## 26
A constant variance model is fit 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37 alpha = 0.004972 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-15 rho = 0 Specified 

## 1
control = 0.146 

## 2 slope = 2.56594e-005 

## 3 power = 0.980719 

## 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 

## 7 8 ( *** The model parameter(s) -rho 

## 9 have been estimated at a boundary point, or have been specified by the user, 

## 10 and do not appear in the correlation matrix ) 

## 11 12 alpha control slope power 

## 13 14 alpha 1 4.5e-009 -1.5e-009 1.3e-009 

## 15 16
control 4.5e-009 1 -0.71 0.68 

## 17 18 slope -1.5e-009 -0.71 1 -1 

## 19 20 power 1.3e-009 0.68 -1 1 

## 21 22 23 24
Parameter Estimates 

## 25 26
95.0% Wald Confidence Interval 

## 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 28 alpha 0.00474021 0.00111728 0.00255039 0.00693004 

## 29
control 0.13485 0.0248098 0.0862235 0.183476 

## 30 slope 0.000217707 0.000332694 -0.000434363 0.000869776 

## 31 power 0.766684 0.157896 0.457213 1.07615 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 6 0.146 0.135 0.0661 0.0688 0.397 

## 41
1068 6 0.177 0.181 0.0539 0.0688 -0.126 

## 42
2542 6 0.191 0.224 0.0563 0.0688 -1.16 

## 43
4489 6 0.271 0.272 0.0563 0.0688 -0.0436 

## 44
7718 6 0.388 0.343 0.0637 0.0688 1.6 

## 45
1.396e+004 6 0.444 0.463 0.11 0.0688 -0.666 

## 46 47 48 49 Model Descriptions for likelihoods calculated 

## 50 51 52 Model A1: Yij = Mu(i) + e(ij) 

## 53 Var{e(ij)} = Sigma^2 

## 54 55 Model A2: Yij = Mu(i) + e(ij) 

## 56 Var{e(ij)} = Sigma(i)^2 

## 57 58 Model A3: Yij = Mu(i) + e(ij) 

## 59 Var{e(ij)} = Sigma^2 

## 60 Model A3 uses any fixed variance parameters that 

## 61 were specified by the user 

## 62 63 Model R: Yi = Mu + e(i) 

## 64 Var{e(i)} = Sigma^2 

## 65 66 67
Likelihoods of Interest 

## 68 69 Model Log(likelihood) # Param's AIC 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-16 A1 80.752584 7 -147.505168 

## 1
A2 83.373547 12 -142.747094 

## 2
A3 80.752584 7 -147.505168 

## 3
fitted 78.330124 4 -148.660249 

## 4
R 55.820023 2 -107.640047 

## 5 6 7 Explanation of Tests 

## 8 9 Test 1: Do responses and/or variances differ among Dose levels? 

## 10 (A2 vs. R) 

## 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 15 16
Tests of Interest 

## 17 18 Test -2*log(Likelihood Ratio) Test df p-value 

## 19 20
Test 1 55.107 10 <.0001 

## 21
Test 2 5.24193 5 0.3871 

## 22
Test 3 5.24193 5 0.3871 

## 23
Test 4 4.84492 3 0.1835 

## 24 25 The p-value for Test 1 is less than .05. There appears to be a 

## 26 difference between response and/or variances among the dose levels 

## 27 It seems appropriate to model the data 

## 28 29 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 30 model appears to be appropriate here 

## 31 32 33 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 34 to be appropriate here 

## 35 36 The p-value for Test 4 is greater than .1. The model chosen seems 

## 37 to adequately describe the data 

## 38 39 40 Benchmark Dose Computation 

## 41 42 Specified effect = 1 

## 43 44 Risk Type = Estimated standard deviations from the control mean 

## 45 46
Confidence level = 0.95 

## 47 48
BMD = 1823.19 

## 49 50 51
BMDL = 743.833 

## 52 53

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-17 H.2.2. Hassoun et al. (2000): DNA SSB 1
H.2.2.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 0.75 39.08 <0.0001 112.91 4.1E+03 2.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.75 39.08 <0.0001 112.91 4.1E+03 2.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.75 4.29 0.23 80.12 5.6E+02 3.6E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.75 4.29 0.23 80.12 5.6E+02 3.6E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.75 4.29 0.23 80.12 5.6E+02 3.6E+02 nonconstant variance, power unrestricted

Hill 3 0.75 4.16 0.25 79.99 5.0E+02 3.9E+02 nonconstant variance, n restricted >1, bound hit

Hill 2 0.75 3.82 0.15 81.65 3.7E+02 1.3E+02 nonconstant variance, n unrestricted

linear 4 0.75 25.42 <.0001 99.26 1.6E+03 9.6E+02 nonconstant variance

polynomial 4 0.75 25.42 <.0001 99.26 1.6E+03 9.6E+02 nonconstant variance

power 4 0.75 25.42 <.0001 99.26 1.6E+03 9.6E+02 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.75 5.14 0.16 80.98 1.9E+02 7.4E+01 nonconstant variance, power unrestricted
exponential (M2) 4 0.75 38.85 <0.0001 111.13 3.6E+03 3.0E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 0.75 38.85 <0.0001 111.13 3.6E+03 3.0E+03 constant variance, power restricted ≥ 1
exponential (M4) c 3 0.75 4.30 0.23 78.59 6.6E+02 5.0E+02 constant variance, power restricted ≥ 1
exponential (M5) 3 0.75 4.30 0.23 78.59 6.6E+02 5.0E+02 constant variance, power restricted ≥ 1
exponential (M5) d 3 0.75 4.30 0.23 78.59 6.6E+02 5.0E+02 constant variance, power unrestricted

Hill 3 0.75 4.31 0.23 78.59 6.0E+02 4.4E+02 constant variance, n restricted >1, bound hit

Hill d 2 0.75 4.09 0.13 80.38 4.8E+02 1.5E+02 constant variance, n unrestricted

linear 4 0.75 25.33 <.0001 97.62 2.0E+03 1.6E+03 constant variance

polynomial 4 0.75 25.33 <.0001 97.62 2.0E+03 1.6E+03 constant variance

power 4 0.75 25.33 <.0001 97.62 2.0E+03 1.6E+03 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-18 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power d 3 0.75 5.61 0.13 79.89 2.5E+02 1.1E+02 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.2.2.2. Figure for Selected Model: Exponential (M 4), Constant Variance, Power Restricted 3 ≥ 1 4

5 10 15 20 25

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:50 11/23 2009 BMD BMDL Exponential



## 5 6 7 H.2.2.3. Output File For Selected Model: E xponential (M4), Constant Variance, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Exp_CV_BMR1_DNA_SSB.(d) 

## 14 Gnuplot Plotting File: 

## 15
Mon Nov 23 12:50:08 2009 

## 16

==================================================================== 

## 17 18 DNA single-strand breaks, liver only (Table 3) 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-19 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18
rho is set to 0. 

## 19
A constant variance model is fit. 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 4 

## 33

-------- -------- 

## 34 lnalpha 0.841244 

## 35 rho(S) 0 

## 36
a 7.0395 

## 37
b 0.000187891 

## 38
c 3.50522 

## 39
d 1 

## 40 41 (S) = Specified 

## 42 43 44 45
Parameter Estimates 

## 46 47
Variable Model 4 

## 48

-------- ------- 

## 49 lnalpha 0.960792 

## 50
rho 0 

## 51
a 7.75279 

## 52
b 0.000136903 

## 53
c 3.39666 

## 54
d 1 

## 55 56 57 Table of Stats From Input Data 

## 58 59
Dose N Obs Mean Obs Std Dev 

## 60

----- --- ---------- ------------- 

## 61
0 6 7.41 1.543 

## 62
1068 6 10.78 1.249 

## 63
2542 6 13.6 1.69 

## 64
4489 6 15.3 1.715 

## 65
7718 6 20.4 2.254 

## 66
1.396e+004 6 23.5 1.372 

## 67 68 69
Estimated Values of Interest 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-20 1
Dose Est Mean Est Std Scaled Residual 

## 2

------ ---------- --------- ---------------- 

## 3
0 7.753 1.617 -0.5194 

## 4
1068 10.28 1.617 0.7575 

## 5
2542 13.21 1.617 0.5853 

## 6
4489 16.28 1.617 -1.49 

## 7
7718 19.87 1.617 0.7958 

## 8
1.396e+004 23.59 1.617 -0.1293 

## 9 10 11 12
Other models for which likelihoods are calculated: 

## 13 14 Model A1: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma^2 

## 16 17 Model A2: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = Sigma(i)^2 

## 19 20 Model A3: Yij = Mu(i) + e(ij) 

## 21 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 22 23 Model R: Yij = Mu + e(i) 

## 24 Var{e(ij)} = Sigma^2 

## 25 26 27
Likelihoods of Interest 

## 28 29 Model Log(likelihood) DF AIC 

## 30

------- ----------------- ---- ------------ 

## 31
A1 -33.14239 7 80.28478 

## 32
A2 -31.81197 12 87.62394 

## 33
A3 -33.14239 7 80.28478 

## 34
R -80.44209 2 164.8842 

## 35
4 -35.29426 4 78.58852 

## 36 37 38 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 39 above values gives the log-likelihood including the term that does not 

## 40 depend on the model parameters. 

## 41 42 43 Explanation of Tests 

## 44 45 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 46 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 47 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 48 49 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 50 51 52
Tests of Interest 

## 53 54 Test -2*log(Likelihood Ratio) D. F. p-value 

## 55

-------- ------------------------ ------ -------------- 

## 56
Test 1 97.26 10 < 0.0001 

## 57
Test 2 2.661 5 0.7521 

## 58
Test 3 2.661 5 0.7521 

## 59
Test 6a 4.304 3 0.2305 

## 60 61 62 The p-value for Test 1 is less than .05. There appears to be a 

## 63 difference between response and/or variances among the dose 

## 64 levels, it seems appropriate to model the data. 

## 65 66 The p-value for Test 2 is greater than .1. A homogeneous 

## 67 variance model appears to be appropriate here. 

## 68 69 The p-value for Test 3 is greater than .1. The modeled 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-21 variance appears to be appropriate here. 

## 1 2 The p-value for Test 6a is greater than .1. Model 4 seems 

## 3 to adequately describe the data. 

## 4 5 6 Benchmark Dose Computations: 

## 7 8 Specified Effect = 1.000000 

## 9 10 Risk Type = Estimated standard deviations from control 

## 11 12
Confidence Level = 0.950000 

## 13 14
BMD = 664.925 

## 15 16
BMDL = 504.974 

## 17 18 19 20 H.2.2.4. Figure for Unrestricted Model: Expon ential (M5), Constant Variance, Power 21 Unrestricted 22

5 10 15 20 25

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:50 11/23 2009 BMD BMDL Exponential



## 23 24 25 H.2.2.5. Output File for Unrestricted Model: Exponential (M5), Con stant Variance, Power 26 Unrestricted 27 28 29

==================================================================== 

## 30 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 31 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Exp_CV_Unrest_BMR1_DNA_SSB.(d) 

## 32 Gnuplot Plotting File: 

## 33
Mon Nov 23 12:50:16 2009 

## 34

==================================================================== 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-22 DNA single-strand breaks, liver only (Table 3) 

## 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 2 3 The form of the response function by Model: 

## 4 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 5 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 6 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 7 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 8 9 Note: Y[dose] is the median response for exposure = dose; 

## 10 sign = +1 for increasing trend in data; 

## 11 sign = -1 for decreasing trend. 

## 12 13
Model 2 is nested within Models 3 and 4. 

## 14
Model 3 is nested within Model 5. 

## 15
Model 4 is nested within Model 5. 

## 16 17 18 Dependent variable = Mean 

## 19 Independent variable = Dose 

## 20 Data are assumed to be distributed: normally 

## 21 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 22
rho is set to 0. 

## 23
A constant variance model is fit. 

## 24 25 Total number of dose groups = 6 

## 26 Total number of records with missing values = 0 

## 27
Maximum number of iterations = 250 

## 28 Relative Function Convergence has been set to: 1e-008 

## 29 Parameter Convergence has been set to: 1e-008 

## 30 31 MLE solution provided: Exact 

## 32 33 34
Initial Parameter Values 

## 35 36
Variable Model 5 

## 37

-------- -------- 

## 38 lnalpha 0.841244 

## 39 rho(S) 0 

## 40
a 7.0395 

## 41
b 0.000187891 

## 42
c 3.50522 

## 43
d 1 

## 44 45 (S) = Specified 

## 46 47 48 49
Parameter Estimates 

## 50 51
Variable Model 5 

## 52

-------- ------- 

## 53 lnalpha 0.960792 

## 54
rho 0 

## 55
a 7.75279 

## 56
b 0.000136903 

## 57
c 3.39666 

## 58
d 1 

## 59 60 61 Table of Stats From Input Data 

## 62 63
Dose N Obs Mean Obs Std Dev 

## 64

----- --- ---------- ------------- 

## 65
0 6 7.41 1.543 

## 66
1068 6 10.78 1.249 

## 67
2542 6 13.6 1.69 

## 68
4489 6 15.3 1.715 

## 69
7718 6 20.4 2.254 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-23 1.396e+004 6 23.5 1.372 

## 1 2 3
Estimated Values of Interest 

## 4 5 Dose Est Mean Est Std Scaled Residual 

## 6

------ ---------- --------- ---------------- 

## 7
0 7.753 1.617 -0.5194 

## 8
1068 10.28 1.617 0.7575 

## 9
2542 13.21 1.617 0.5853 

## 10
4489 16.28 1.617 -1.49 

## 11
7718 19.87 1.617 0.7958 

## 12
1.396e+004 23.59 1.617 -0.1293 

## 13 14 15 16
Other models for which likelihoods are calculated: 

## 17 18 Model A1: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = Sigma^2 

## 20 21 Model A2: Yij = Mu(i) + e(ij) 

## 22 Var{e(ij)} = Sigma(i)^2 

## 23 24 Model A3: Yij = Mu(i) + e(ij) 

## 25 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 26 27 Model R: Yij = Mu + e(i) 

## 28 Var{e(ij)} = Sigma^2 

## 29 30 31
Likelihoods of Interest 

## 32 33 Model Log(likelihood) DF AIC 

## 34

------- ----------------- ---- ------------ 

## 35
A1 -33.14239 7 80.28478 

## 36
A2 -31.81197 12 87.62394 

## 37
A3 -33.14239 7 80.28478 

## 38
R -80.44209 2 164.8842 

## 39
5 -35.29426 4 78.58852 

## 40 41 42 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 43 above values gives the log-likelihood including the term that does not 

## 44 depend on the model parameters. 

## 45 46 47 Explanation of Tests 

## 48 49 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 50 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 51 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 52 53 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 54 55 56
Tests of Interest 

## 57 58 Test -2*log(Likelihood Ratio) D. F. p-value 

## 59

-------- ------------------------ ------ -------------- 

## 60
Test 1 97.26 10 < 0.0001 

## 61
Test 2 2.661 5 0.7521 

## 62
Test 3 2.661 5 0.7521 

## 63
Test 7a 4.304 3 0.2305 

## 64 65 66 The p-value for Test 1 is less than .05. There appears to be a 

## 67 difference between response and/or variances among the dose 

## 68 levels, it seems appropriate to model the data. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-24 The p-value for Test 2 is greater than .1. A homogeneous 

## 1 variance model appears to be appropriate here. 

## 2 3 The p-value for Test 3 is greater than .1. The modeled 

## 4 variance appears to be appropriate here. 

## 5 6 The p-value for Test 7a is greater than .1. Model 5 seems 

## 7 to adequately describe the data. 

## 8 9 10 Benchmark Dose Computations: 

## 11 12 Specified Effect = 1.000000 

## 13 14 Risk Type = Estimated standard deviations from control 

## 15 16
Confidence Level = 0.950000 

## 17 18
BMD = 664.925 

## 19 20
BMDL = 504.974 

## 21 22 23 24 H.2.2.6. Figure for Unrestricted Model: Hill, Constant Variance, n Unrestricted 25

5 10 15 20 25

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Hill Model with 0.95 Confidence Level

12:50 11/23 2009 BMD BMDL Hill



## 26 27 28 H.2.2.7. Output File For Unrestricted Model: Hill, Constant Varian ce, n Unrestricted 29 30 31

==================================================================== 

## 32 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 33 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_Unrest_BMR1_DNA_SSB.(d) 

## 34 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_Unrest_BMR1_DNA_SSB.plt 

## 35
Mon Nov 23 12:50:18 2009 

## 36

==================================================================== 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-25 1 DNA single-strand breaks, liver only (Table 3) 

## 2

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 3 4 The form of the response function is: 

## 5 6 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 7 8 9 Dependent variable = Mean 

## 10 Independent variable = Dose 

## 11
rho is set to 0 

## 12 Power parameter is not restricted 

## 13
A constant variance model is fit 

## 14 15 Total number of dose groups = 6 

## 16 Total number of records with missing values = 0 

## 17
Maximum number of iterations = 250 

## 18 Relative Function Convergence has been set to: 1e-008 

## 19 Parameter Convergence has been set to: 1e-008 

## 20 21 22 23
Default Initial Parameter Values 

## 24 alpha = 2.7831 

## 25 rho = 0 Specified 

## 26 intercept = 7.41 

## 27
v = 16.09 

## 28
n = 0.235041 

## 29
k = 10849.8 

## 30 31 32 Asymptotic Correlation Matrix of Parameter Estimates 

## 33 34 ( *** The model parameter(s) -rho 

## 35 have been estimated at a boundary point, or have been specified by the user, 

## 36 and do not appear in the correlation matrix ) 

## 37 38 alpha intercept v n k 

## 39 40 alpha 1 -2.8e-008 7.4e-008 -6.3e-008 7.2e-008 

## 41 42 intercept -2.8e-008 1 -0.34 0.47 -0.28 

## 43 44
v 7.4e-008 -0.34 1 -0.95 1 

## 45 46
n -6.3e-008 0.47 -0.95 1 -0.95 

## 47 48
k 7.2e-008 -0.28 1 -0.95 1 

## 49 50 51 52
Parameter Estimates 

## 53 54
95.0% Wald Confidence Interval 

## 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 56 alpha 2.59837 0.612441 1.398 3.79873 

## 57 intercept 7.4823 0.666037 6.17689 8.78771 

## 58
v 32.65 17.9338 -2.49963 67.7997 

## 59
n 0.876148 0.260495 0.365588 1.38671 

## 60
k 14136.3 16730.5 -18654.9 46927.4 

## 61 62 63 64
Table of Data and Estimated Values of Interest 

## 65 66
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 67

------ --- -------- -------- ----------- ----------- ---------- 

## 68 69
0 6 7.41 7.48 1.54 1.61 -0.11 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-26 1068 6 10.8 10.6 1.25 1.61 0.336 

## 1
2542 6 13.6 13.4 1.69 1.61 0.27 

## 2
4489 6 15.3 16.2 1.71 1.61 -1.41 

## 3
7718 6 20.4 19.6 2.25 1.61 1.25 

## 4
1.396e+004 6 23.5 23.7 1.37 1.61 -0.331 

## 5 6 7 8 Model Descriptions for likelihoods calculated 

## 9 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = Sigma^2 

## 19 Model A3 uses any fixed variance parameters that 

## 20 were specified by the user 

## 21 22 Model R: Yi = Mu + e(i) 

## 23 Var{e(i)} = Sigma^2 

## 24 25 26
Likelihoods of Interest 

## 27 28 Model Log(likelihood) # Param's AIC 

## 29
A1 -33.142389 7 80.284779 

## 30
A2 -31.811970 12 87.623940 

## 31
A3 -33.142389 7 80.284779 

## 32
fitted -35.187895 5 80.375790 

## 33
R -80.442086 2 164.884172 

## 34 35 36 Explanation of Tests 

## 37 38 Test 1: Do responses and/or variances differ among Dose levels? 

## 39 (A2 vs. R) 

## 40 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 41 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 42 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 43 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 44 45
Tests of Interest 

## 46 47 Test -2*log(Likelihood Ratio) Test df p-value 

## 48 49
Test 1 97.2602 10 <.0001 

## 50
Test 2 2.66084 5 0.7521 

## 51
Test 3 2.66084 5 0.7521 

## 52
Test 4 4.09101 2 0.1293 

## 53 54 The p-value for Test 1 is less than .05. There appears to be a 

## 55 difference between response and/or variances among the dose levels 

## 56 It seems appropriate to model the data 

## 57 58 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 59 model appears to be appropriate here 

## 60 61 62 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 63 to be appropriate here 

## 64 65 The p-value for Test 4 is greater than .1. The model chosen seems 

## 66 to adequately describe the data 

## 67 68 69 Benchmark Dose Computation 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-27 1 Specified effect = 1 

## 2 3 Risk Type = Estimated standard deviations from the control mean 

## 4 5 Confidence level = 0.95 

## 6 7
BMD = 483.289 

## 8 9
BMDL = 153.678 

## 10 11 12 13 H.2.2.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 14

5 10 15 20 25

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Power Model with 0.95 Confidence Level

12:50 11/23 2009 BMD BMDL Power



## 15 16 17 H.2.2.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 18 19 20

==================================================================== 

## 21 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 22 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Pwr_CV_Unrest_BMR1_DNA_SSB.(d) 

## 23 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Pwr_CV_Unrest_BMR1_DNA_SSB.plt 

## 24
Mon Nov 23 12:50:18 2009 

## 25

==================================================================== 

## 26 27 DNA single-strand breaks, liver only (Table 3) 

## 28

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 29 30 The form of the response function is: 

## 31 32 Y[dose] = control + slope * dose^power 

## 33 34 35 Dependent variable = Mean 

## 36 Independent variable = Dose 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-28 rho is set to 0 

## 1 The power is not restricted 

## 2
A constant variance model is fit 

## 3 4 Total number of dose groups = 6 

## 5 Total number of records with missing values = 0 

## 6
Maximum number of iterations = 250 

## 7 Relative Function Convergence has been set to: 1e-008 

## 8 Parameter Convergence has been set to: 1e-008 

## 9 10 11 12
Default Initial Parameter Values 

## 13 alpha = 2.7831 

## 14 rho = 0 Specified 

## 15
control = 7.41 

## 16 slope = 0.0433022 

## 17 power = 0.620052 

## 18 19 20 Asymptotic Correlation Matrix of Parameter Estimates 

## 21 22 ( *** The model parameter(s) -rho 

## 23 have been estimated at a boundary point, or have been specified by the user, 

## 24 and do not appear in the correlation matrix ) 

## 25 26 alpha control slope power 

## 27 28 alpha 1 2.5e-009 -5.4e-009 5.7e-009 

## 29 30
control 2.5e-009 1 -0.71 0.66 

## 31 32 slope -5.4e-009 -0.71 1 -1 

## 33 34 power 5.7e-009 0.66 -1 1 

## 35 36 37 38
Parameter Estimates 

## 39 40
95.0% Wald Confidence Interval 

## 41 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 42 alpha 2.71023 0.638807 1.45819 3.96226 

## 43
control 7.26415 0.64416 6.00162 8.52668 

## 44 slope 0.0685886 0.0392449 -0.00833 0.145507 

## 45 power 0.575949 0.0589672 0.460375 0.691523 

## 46 47 48 49
Table of Data and Estimated Values of Interest 

## 50 51
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 52

------ --- -------- -------- ----------- ----------- ---------- 

## 53 54
0 6 7.41 7.26 1.54 1.65 0.217 

## 55
1068 6 10.8 11.1 1.25 1.65 -0.433 

## 56
2542 6 13.6 13.5 1.69 1.65 0.094 

## 57
4489 6 15.3 16 1.71 1.65 -0.993 

## 58
7718 6 20.4 19.2 2.25 1.65 1.85 

## 59
1.396e+004 6 23.5 24 1.37 1.65 -0.735 

## 60 61 62 63 Model Descriptions for likelihoods calculated 

## 64 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-29 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = Sigma^2 

## 4 Model A3 uses any fixed variance parameters that 

## 5 were specified by the user 

## 6 7 Model R: Yi = Mu + e(i) 

## 8 Var{e(i)} = Sigma^2 

## 9 10 11
Likelihoods of Interest 

## 12 13 Model Log(likelihood) # Param's AIC 

## 14
A1 -33.142389 7 80.284779 

## 15
A2 -31.811970 12 87.623940 

## 16
A3 -33.142389 7 80.284779 

## 17
fitted -35.946581 4 79.893162 

## 18
R -80.442086 2 164.884172 

## 19 20 21 Explanation of Tests 

## 22 23 Test 1: Do responses and/or variances differ among Dose levels? 

## 24 (A2 vs. R) 

## 25 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 27 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 28 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 29 30
Tests of Interest 

## 31 32 Test -2*log(Likelihood Ratio) Test df p-value 

## 33 34
Test 1 97.2602 10 <.0001 

## 35
Test 2 2.66084 5 0.7521 

## 36
Test 3 2.66084 5 0.7521 

## 37
Test 4 5.60838 3 0.1323 

## 38 39 The p-value for Test 1 is less than .05. There appears to be a 

## 40 difference between response and/or variances among the dose levels 

## 41 It seems appropriate to model the data 

## 42 43 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 44 model appears to be appropriate here 

## 45 46 47 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 48 to be appropriate here 

## 49 50 The p-value for Test 4 is greater than .1. The model chosen seems 

## 51 to adequately describe the data 

## 52 53 54 Benchmark Dose Computation 

## 55 56 Specified effect = 1 

## 57 58 Risk Type = Estimated standard deviations from the control mean 

## 59 60
Confidence level = 0.95 

## 61 62
BMD = 249.162 

## 63 64 65
BMDL = 111.676 

## 66 67

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-30 H.2.3. Hassoun et al. (2000): TBARs Liver 1
H.2.3.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 0.33 17.56 0.00 -7.04 7.4E+03 3.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.33 17.56 0.00 -7.04 7.4E+03 3.9E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.33 4.35 0.23 -18.26 1.0E+03 5.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.33 2.78 0.25 -17.82 1.6E+03 6.5E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.33 2.78 0.25 -17.82 1.6E+03 6.5E+02 nonconstant variance, power unrestricted

Hill 2 0.33 2.52 0.28 -18.09 1.7E+03 8.1E+02 nonconstant variance, n restricted >1

Hill 2 0.33 2.52 0.28 -18.09 1.7E+03 8.1E+02 nonconstant variance, n unrestricted

linear 4 0.33 15.72 0.00 -8.88 5.1E+03 2.4E+03 nonconstant variance

polynomial 4 0.33 15.72 0.00 -8.88 5.1E+03 2.4E+03 nonconstant variance

power 4 0.33 15.72 0.00 -8.88 5.1E+03 2.4E+03 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.33 8.40 0.04 -14.21 5.3E+02 8.3E+00 nonconstant variance, power unrestricted
exponential (M2) 4 0.33 18.02 0.00 -8.52 9.6E+03 6.7E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 0.33 18.02 0.00 -8.52 9.6E+03 6.7E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 0.33 4.79 0.19 -19.75 1.2E+03 6.3E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 0.33 2.86 0.24 -19.68 1.9E+03 8.4E+02 constant variance, power restricted ≥ 1
exponential (M5) d 2 0.33 2.86 0.24 -19.68 1.9E+03 8.4E+02 constant variance, power unrestricted

Hill c 2 0.33 2.60 0.27 -19.93 1.8E+03 9.6E+02 constant variance, n restricted >1

Hill d 2 0.33 2.60 0.27 -19.93 1.8E+03 9.6E+02 constant variance, n unrestricted

linear 4 0.33 16.75 0.00 -9.79 8.0E+03 5.3E+03 constant variance

polynomial 4 0.33 16.75 0.00 -9.79 8.0E+03 5.3E+03 constant variance

power 4 0.33 16.75 0.00 -9.79 8.0E+03 5.3E+03 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-31 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power d 3 0.33 9.75 0.02 -14.79 1.0E+03 5.7E+01 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.2.3.2. Figure for Selected Model: Exponen tial (M5), Constant Variance, Power 3 Unrestricted 4

1 1.5

2 2.5

3

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Exponential



## 5 6 7 H.2.3.3. Output File for Selected Model: Expo nential (M5), Constant Variance, Power 8 Unrestricted 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Exp_CV_Unrest_BMR1_TBARs_Liver.(d) 

## 14 Gnuplot Plotting File: 

## 15
Mon Nov 23 12:51:02 2009 

## 16

==================================================================== 

## 17 18 TBARs, liver only (Table 2) 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-32 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18
rho is set to 0. 

## 19
A constant variance model is fit. 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 5 

## 33

-------- -------- 

## 34 lnalpha -1.90388 

## 35 rho(S) 0 

## 36
a 1.39555 

## 37
b 0.000142164 

## 38
c 1.97051 

## 39
d 1 

## 40 41 (S) = Specified 

## 42 43 44 45
Parameter Estimates 

## 46 47
Variable Model 5 

## 48

-------- ------- 

## 49 lnalpha -1.82448 

## 50
rho 0 

## 51
a 1.46526 

## 52
b 0.000431089 

## 53
c 1.63651 

## 54
d 2.96871 

## 55 56 57 Table of Stats From Input Data 

## 58 59
Dose N Obs Mean Obs Std Dev 

## 60

----- --- ---------- ------------- 

## 61
0 6 1.469 0.2915 

## 62
1068 6 1.549 0.5389 

## 63
2542 6 2.15 0.3625 

## 64
4489 6 2.28 0.2474 

## 65
7718 6 2.619 0.5168 

## 66
1.396e+004 6 2.292 0.4874 

## 67 68 69
Estimated Values of Interest 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-33 1
Dose Est Mean Est Std Scaled Residual 

## 2

------ ---------- --------- ---------------- 

## 3
0 1.465 0.4016 0.0228 

## 4
1068 1.554 0.4016 -0.03039 

## 5
2542 2.147 0.4016 0.01965 

## 6
4489 2.397 0.4016 -0.7145 

## 7
7718 2.398 0.4016 1.348 

## 8
1.396e+004 2.398 0.4016 -0.646 

## 9 10 11 12
Other models for which likelihoods are calculated: 

## 13 14 Model A1: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma^2 

## 16 17 Model A2: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = Sigma(i)^2 

## 19 20 Model A3: Yij = Mu(i) + e(ij) 

## 21 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 22 23 Model R: Yij = Mu + e(i) 

## 24 Var{e(ij)} = Sigma^2 

## 25 26 27
Likelihoods of Interest 

## 28 29 Model Log(likelihood) DF AIC 

## 30

------- ----------------- ---- ------------ 

## 31
A1 16.26977 7 -18.53954 

## 32
A2 19.12783 12 -14.25565 

## 33
A3 16.26977 7 -18.53954 

## 34
R 2.44294 2 -0.8858799 

## 35
5 14.84065 5 -19.6813 

## 36 37 38 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 39 above values gives the log-likelihood including the term that does not 

## 40 depend on the model parameters. 

## 41 42 43 Explanation of Tests 

## 44 45 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 46 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 47 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 48 49 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 50 51 52
Tests of Interest 

## 53 54 Test -2*log(Likelihood Ratio) D. F. p-value 

## 55

-------- ------------------------ ------ -------------- 

## 56
Test 1 33.37 10 0.000236 

## 57
Test 2 5.716 5 0.3348 

## 58
Test 3 5.716 5 0.3348 

## 59
Test 7a 2.858 2 0.2395 

## 60 61 62 The p-value for Test 1 is less than .05. There appears to be a 

## 63 difference between response and/or variances among the dose 

## 64 levels, it seems appropriate to model the data. 

## 65 66 The p-value for Test 2 is greater than .1. A homogeneous 

## 67 variance model appears to be appropriate here. 

## 68 69 The p-value for Test 3 is greater than .1. The modeled 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-34 variance appears to be appropriate here. 

## 1 2 The p-value for Test 7a is greater than .1. Model 5 seems 

## 3 to adequately describe the data. 

## 4 5 6 Benchmark Dose Computations: 

## 7 8 Specified Effect = 1.000000 

## 9 10 Risk Type = Estimated standard deviations from control 

## 11 12
Confidence Level = 0.950000 

## 13 14
BMD = 1911.82 

## 15 16
BMDL = 840.487 

## 17 18 19 20 H.2.3.4. Figure for Unrestricted M odel: Hill, Constant Va riance, n Restricted > 1 21

1 1.5

2 2.5

3

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Hill Model with 0.95 Confidence Level

12:50 11/23 2009 BMD BMDL Hill



## 22 23 24 H.2.3.5. Output File for Unrestricted Model: Hil l, Constant Variance, n Restricted >1 25 26 27

==================================================================== 

## 28 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 29 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_BMR1_TBARs_Liver.(d) 

## 30 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_BMR1_TBARs_Liver.plt 

## 31
Mon Nov 23 12:50:58 2009 

## 32

==================================================================== 

## 33 34 TBARs, liver only (Table 2) 

## 35

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-35 The form of the response function is: 

## 1 2 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 3 4 5 Dependent variable = Mean 

## 6 Independent variable = Dose 

## 7 rho is set to 0 

## 8 Power parameter restricted to be greater than 1 

## 9
A constant variance model is fit 

## 10 11 Total number of dose groups = 6 

## 12 Total number of records with missing values = 0 

## 13
Maximum number of iterations = 250 

## 14 Relative Function Convergence has been set to: 1e-008 

## 15 Parameter Convergence has been set to: 1e-008 

## 16 17 18 19
Default Initial Parameter Values 

## 20 alpha = 0.178788 

## 21 rho = 0 Specified 

## 22 intercept = 1.469 

## 23
v = 1.15 

## 24
n = 1.27851 

## 25
k = 2801.9 

## 26 27 28 Asymptotic Correlation Matrix of Parameter Estimates 

## 29 30 ( *** The model parameter(s) -rho 

## 31 have been estimated at a boundary point, or have been specified by the user, 

## 32 and do not appear in the correlation matrix ) 

## 33 34 alpha intercept v n k 

## 35 36 alpha 1 1.1e-007 -1.4e-007 1.2e-007 -7.6e-009 

## 37 38 intercept 1.1e-007 1 -0.82 0.48 0.52 

## 39 40
v -1.4e-007 -0.82 1 -0.61 -0.22 

## 41 42
n 1.2e-007 0.48 -0.61 1 0.29 

## 43 44
k -7.6e-009 0.52 -0.22 0.29 1 

## 45 46 47 48
Parameter Estimates 

## 49 50
95.0% Wald Confidence Interval 

## 51 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 52 alpha 0.16017 0.0377524 0.0861764 0.234163 

## 53 intercept 1.46138 0.152797 1.1619 1.76086 

## 54
v 0.963032 0.20228 0.56657 1.35949 

## 55
n 3.44649 2.43475 -1.32553 8.21851 

## 56
k 2002.3 562.074 900.655 3103.95 

## 57 58 59 60
Table of Data and Estimated Values of Interest 

## 61 62
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 63

------ --- -------- -------- ----------- ----------- ---------- 

## 64 65
0 6 1.47 1.46 0.291 0.4 0.0466 

## 66
1068 6 1.55 1.56 0.539 0.4 -0.0697 

## 67
2542 6 2.15 2.13 0.363 0.4 0.12 

## 68
4489 6 2.28 2.37 0.247 0.4 -0.54 

## 69
7718 6 2.62 2.42 0.517 0.4 1.25 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-36 1.396e+004 6 2.29 2.42 0.487 0.4 -0.803 

## 1 2 3 4 Model Descriptions for likelihoods calculated 

## 5 6 7 Model A1: Yij = Mu(i) + e(ij) 

## 8 Var{e(ij)} = Sigma^2 

## 9 10 Model A2: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = Sigma(i)^2 

## 12 13 Model A3: Yij = Mu(i) + e(ij) 

## 14 Var{e(ij)} = Sigma^2 

## 15 Model A3 uses any fixed variance parameters that 

## 16 were specified by the user 

## 17 18 Model R: Yi = Mu + e(i) 

## 19 Var{e(i)} = Sigma^2 

## 20 21 22
Likelihoods of Interest 

## 23 24 Model Log(likelihood) # Param's AIC 

## 25
A1 16.269770 7 -18.539539 

## 26
A2 19.127827 12 -14.255654 

## 27
A3 16.269770 7 -18.539539 

## 28
fitted 14.967385 5 -19.934770 

## 29
R 2.442940 2 -0.885880 

## 30 31 32 Explanation of Tests 

## 33 34 Test 1: Do responses and/or variances differ among Dose levels? 

## 35 (A2 vs. R) 

## 36 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 37 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 38 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 39 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 40 41
Tests of Interest 

## 42 43 Test -2*log(Likelihood Ratio) Test df p-value 

## 44 45
Test 1 33.3698 10 0.000236 

## 46
Test 2 5.71611 5 0.3348 

## 47
Test 3 5.71611 5 0.3348 

## 48
Test 4 2.60477 2 0.2719 

## 49 50 The p-value for Test 1 is less than .05. There appears to be a 

## 51 difference between response and/or variances among the dose levels 

## 52 It seems appropriate to model the data 

## 53 54 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 55 model appears to be appropriate here 

## 56 57 58 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 59 to be appropriate here 

## 60 61 The p-value for Test 4 is greater than .1. The model chosen seems 

## 62 to adequately describe the data 

## 63 64 65 Benchmark Dose Computation 

## 66 67 Specified effect = 1 

## 68 69 Risk Type = Estimated standard deviations from the control mean 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-37 1
Confidence level = 0.95 

## 2 3
BMD = 1813.69 

## 4 5
BMDL = 957.252 

## 6 7 8 9 H.2.3.6. Figure for Unrestricted Model: Hill, Constant Variance, n Unrestricted 10

1 1.5

2 2.5

3

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Hill Model with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Hill



## 11 12 13 H.2.3.7. Output File for Unrestricted Model: Hill, Constant Variance, n Unrestricted 14 15 16

==================================================================== 

## 17 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 18 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_Unrest_BMR1_TBARs_Liver.(d) 

## 19 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Hill_CV_Unrest_BMR1_TBARs_Liver.plt 

## 20
Mon Nov 23 12:51:04 2009 

## 21

==================================================================== 

## 22 23 TBARs, liver only (Table 2) 

## 24

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 25 26 The form of the response function is: 

## 27 28 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 29 30 31 Dependent variable = Mean 

## 32 Independent variable = Dose 

## 33
rho is set to 0 

## 34 Power parameter is not restricted 

## 35
A constant variance model is fit 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-38 Total number of dose groups = 6 

## 1 Total number of records with missing values = 0 

## 2
Maximum number of iterations = 250 

## 3 Relative Function Convergence has been set to: 1e-008 

## 4 Parameter Convergence has been set to: 1e-008 

## 5 6 7 8
Default Initial Parameter Values 

## 9 alpha = 0.178788 

## 10 rho = 0 Specified 

## 11 intercept = 1.469 

## 12
v = 1.15 

## 13
n = 1.27851 

## 14
k = 2801.9 

## 15 16 17 Asymptotic Correlation Matrix of Parameter Estimates 

## 18 19 ( *** The model parameter(s) -rho 

## 20 have been estimated at a boundary point, or have been specified by the user, 

## 21 and do not appear in the correlation matrix ) 

## 22 23 alpha intercept v n k 

## 24 25 alpha 1 1.1e-007 -1.4e-007 1.2e-007 -7.6e-009 

## 26 27 intercept 1.1e-007 1 -0.82 0.48 0.52 

## 28 29
v -1.4e-007 -0.82 1 -0.61 -0.22 

## 30 31
n 1.2e-007 0.48 -0.61 1 0.29 

## 32 33
k -7.6e-009 0.52 -0.22 0.29 1 

## 34 35 36 37
Parameter Estimates 

## 38 39
95.0% Wald Confidence Interval 

## 40 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 41 alpha 0.16017 0.0377524 0.0861764 0.234163 

## 42 intercept 1.46138 0.152797 1.1619 1.76086 

## 43
v 0.963032 0.20228 0.56657 1.35949 

## 44
n 3.44649 2.43475 -1.32553 8.21851 

## 45
k 2002.3 562.074 900.655 3103.95 

## 46 47 48 49
Table of Data and Estimated Values of Interest 

## 50 51
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 52

------ --- -------- -------- ----------- ----------- ---------- 

## 53 54
0 6 1.47 1.46 0.291 0.4 0.0466 

## 55
1068 6 1.55 1.56 0.539 0.4 -0.0697 

## 56
2542 6 2.15 2.13 0.363 0.4 0.12 

## 57
4489 6 2.28 2.37 0.247 0.4 -0.54 

## 58
7718 6 2.62 2.42 0.517 0.4 1.25 

## 59
1.396e+004 6 2.29 2.42 0.487 0.4 -0.803 

## 60 61 62 63 Model Descriptions for likelihoods calculated 

## 64 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-39 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = Sigma^2 

## 4 Model A3 uses any fixed variance parameters that 

## 5 were specified by the user 

## 6 7 Model R: Yi = Mu + e(i) 

## 8 Var{e(i)} = Sigma^2 

## 9 10 11
Likelihoods of Interest 

## 12 13 Model Log(likelihood) # Param's AIC 

## 14
A1 16.269770 7 -18.539539 

## 15
A2 19.127827 12 -14.255654 

## 16
A3 16.269770 7 -18.539539 

## 17
fitted 14.967385 5 -19.934770 

## 18
R 2.442940 2 -0.885880 

## 19 20 21 Explanation of Tests 

## 22 23 Test 1: Do responses and/or variances differ among Dose levels? 

## 24 (A2 vs. R) 

## 25 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 27 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 28 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 29 30
Tests of Interest 

## 31 32 Test -2*log(Likelihood Ratio) Test df p-value 

## 33 34
Test 1 33.3698 10 0.000236 

## 35
Test 2 5.71611 5 0.3348 

## 36
Test 3 5.71611 5 0.3348 

## 37
Test 4 2.60477 2 0.2719 

## 38 39 The p-value for Test 1 is less than .05. There appears to be a 

## 40 difference between response and/or variances among the dose levels 

## 41 It seems appropriate to model the data 

## 42 43 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 44 model appears to be appropriate here 

## 45 46 47 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 48 to be appropriate here 

## 49 50 The p-value for Test 4 is greater than .1. The model chosen seems 

## 51 to adequately describe the data 

## 52 53 54 Benchmark Dose Computation 

## 55 56 Specified effect = 1 

## 57 58 Risk Type = Estimated standard deviations from the control mean 

## 59 60
Confidence level = 0.95 

## 61 62
BMD = 1813.69 

## 63 64
BMDL = 957.252 

## 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-40 H.2.3.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

1 1.5

2 2.5

3

0 2000 4000 6000 8000 10000 12000 14000Mean Response

dose Power Model with 0.95 Confidence Level

12:51 11/23 2009 BMD BMDL Power



## 2 3 4 H.2.3.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5 6 7

==================================================================== 

## 8 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 9 Input Data File: C:\USEPA\BMDS21\Nov23\Blood\Pwr_CV_Unrest_BMR1_TBARs_Liver.(d) 

## 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Blood\Pwr_CV_Unrest_BMR1_TBARs_Liver.plt 

## 11
Mon Nov 23 12:51:05 2009 

## 12

==================================================================== 

## 13 14 TBARs, liver only (Table 2) 

## 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 16 17 The form of the response function is: 

## 18 19 Y[dose] = control + slope * dose^power 

## 20 21 22 Dependent variable = Mean 

## 23 Independent variable = Dose 

## 24
rho is set to 0 

## 25 The power is not restricted 

## 26
A constant variance model is fit 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37 alpha = 0.178788 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-41 rho = 0 Specified 

## 1
control = 1.469 

## 2 slope = 0.000328724 

## 3 power = 0.885141 

## 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 

## 7 8 ( *** The model parameter(s) -rho 

## 9 have been estimated at a boundary point, or have been specified by the user, 

## 10 and do not appear in the correlation matrix ) 

## 11 12 alpha control slope power 

## 13 14 alpha 1 3.9e-011 -2.9e-010 3.6e-010 

## 15 16
control 3.9e-011 1 -0.59 0.47 

## 17 18 slope -2.9e-010 -0.59 1 -0.99 

## 19 20 power 3.6e-010 0.47 -0.99 1 

## 21 22 23 24
Parameter Estimates 

## 25 26
95.0% Wald Confidence Interval 

## 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 28 alpha 0.195332 0.0460403 0.105095 0.28557 

## 29
control 1.42145 0.17171 1.0849 1.75799 

## 30 slope 0.0382805 0.0492936 -0.0583331 0.134894 

## 31 power 0.353387 0.132966 0.0927779 0.613996 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 6 1.47 1.42 0.291 0.442 0.264 

## 41
1068 6 1.55 1.87 0.539 0.442 -1.79 

## 42
2542 6 2.15 2.03 0.363 0.442 0.649 

## 43
4489 6 2.28 2.17 0.247 0.442 0.616 

## 44
7718 6 2.62 2.33 0.517 0.442 1.62 

## 45
1.396e+004 6 2.29 2.54 0.487 0.442 -1.36 

## 46 47 48 49 Model Descriptions for likelihoods calculated 

## 50 51 52 Model A1: Yij = Mu(i) + e(ij) 

## 53 Var{e(ij)} = Sigma^2 

## 54 55 Model A2: Yij = Mu(i) + e(ij) 

## 56 Var{e(ij)} = Sigma(i)^2 

## 57 58 Model A3: Yij = Mu(i) + e(ij) 

## 59 Var{e(ij)} = Sigma^2 

## 60 Model A3 uses any fixed variance parameters that 

## 61 were specified by the user 

## 62 63 Model R: Yi = Mu + e(i) 

## 64 Var{e(i)} = Sigma^2 

## 65 66 67
Likelihoods of Interest 

## 68 69 Model Log(likelihood) # Param's AIC 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-42 A1 16.269770 7 -18.539539 

## 1
A2 19.127827 12 -14.255654 

## 2
A3 16.269770 7 -18.539539 

## 3
fitted 11.394946 4 -14.789892 

## 4
R 2.442940 2 -0.885880 

## 5 6 7 Explanation of Tests 

## 8 9 Test 1: Do responses and/or variances differ among Dose levels? 

## 10 (A2 vs. R) 

## 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 15 16
Tests of Interest 

## 17 18 Test -2*log(Likelihood Ratio) Test df p-value 

## 19 20
Test 1 33.3698 10 0.000236 

## 21
Test 2 5.71611 5 0.3348 

## 22
Test 3 5.71611 5 0.3348 

## 23
Test 4 9.74965 3 0.02082 

## 24 25 The p-value for Test 1 is less than .05. There appears to be a 

## 26 difference between response and/or variances among the dose levels 

## 27 It seems appropriate to model the data 

## 28 29 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 30 model appears to be appropriate here 

## 31 32 33 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 34 to be appropriate here 

## 35 36 The p-value for Test 4 is less than .1. You may want to try a different 

## 37
model 

## 38 39 40 Benchmark Dose Computation 

## 41 42 Specified effect = 1 

## 43 44 Risk Type = Estimated standard deviations from the control mean 

## 45 46
Confidence level = 0.95 

## 47 48
BMD = 1014.75 

## 49 50 51
BMDL = 56.7719 

## 52 53

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-43 H.2.4. Kitchin et al. (1979): BaP Hydrolase Activity 1
H.2.4.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 9 <0.0001 247.10 <0.0001 452.74 9.3E+05 4.3E+05 nonconstant variance, power restricted ≥ 1
exponential (M3) 9 <0.0001 247.10 <0.0001 452.74 9.3E+05 4.3E+05 nonconstant variance, power restricted ≥ 1
exponential (M4) 8 <0.0001 18.95 0.02 226.59 6.3E+02 4.8E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) c 7 <0.0001 16.76 0.02 226.41 1.2E+03 5.6E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) d 7 <0.0001 16.76 0.02 226.41 1.2E+03 5.6E+02 nonconstant variance, power unrestricted

Hill 7 <.0001 296.88 <.0001 506.53 error error nonconstant variance, n restricted >1

Hill d 7 <.0001 296.88 <.0001 506.53 error error nonconstant variance, n unrestricted

linear 9 <.0001 94.23 <.0001 299.87 9.6E+02 6.9E+02 nonconstant variance

polynomial 9 <.0001 -197.64 <.0001 8.00 error error nonconstant variance

power 9 <.0001 94.23 <.0001 299.87 9.6E+02 6.9E+02 nonconstant variance, power restricted ≥ 1, bound hit

power d 8 <.0001 63.63 <.0001 271.27 1.0E+02 4.4E+01 nonconstant variance, power unrestricted
exponential (M2) 9 <0.0001 129.40 <0.0001 451.64 1.3E+06 1.1E+06 constant variance, power restricted ≥ 1
exponential (M3) 9 <0.0001 129.40 <0.0001 451.64 1.3E+06 1.1E+06 constant variance, power restricted ≥ 1
exponential (M4) 8 <0.0001 6.96 0.54 331.23 9.5E+03 7.3E+03 constant variance, power restricted ≥ 1
exponential (M5) 8 <0.0001 6.96 0.54 331.23 9.5E+03 7.3E+03 constant variance, power restricted ≥ 1
exponential (M5) 8 <0.0001 6.96 0.54 331.23 9.5E+03 7.3E+03 constant variance, power unrestricted

Hill 7 <.0001 35.69 <.0001 361.95 6.3E+04 2.6E+03 constant variance, n restricted >1

Hill 7 <.0001 35.69 <.0001 361.95 6.3E+04 3.0E+02 constant variance, n unrestricted

linear 9 <.0001 120.38 <.0001 442.64 6.6E+05 5.1E+05 constant variance

polynomial 9 <.0001 120.38 <.0001 442.64 6.6E+05 5.1E+05 constant variance

power 9 <.0001 120.38 <.0001 442.64 6.6E+05 5.1E+05 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-44 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 8 <.0001 51.09 <.0001 375.35 4.1E+02 8.6E+01 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 H.2.4.2. Figure for Selected Model: Exponen tial (M5), Nonconstant Variance, Power 2 Restricted ≥ 1 3

0 50 100 150 200 250

0 500000 1e+006 1.5e+006 2e+006Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:25 11/20 2009 BMDBMDL Exponential



## 4 5 6 H.2.4.3. Output File for Selected Model: Expo nential (M5), Nonconstant Varian ce, Power 7 Restricted ≥ 1 8 9 10

==================================================================== 

## 11 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 12 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_BaP_hydro_act.(d) 

## 13 Gnuplot Plotting File: 

## 14
Fri Nov 20 13:25:02 2009 

## 15

==================================================================== 

## 16 17 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 19 20 The form of the response function by Model: 

## 21 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-45 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 1 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 2 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 3 4 Note: Y[dose] is the median response for exposure = dose; 

## 5 sign = +1 for increasing trend in data; 

## 6 sign = -1 for decreasing trend. 

## 7 8
Model 2 is nested within Models 3 and 4. 

## 9
Model 3 is nested within Model 5. 

## 10
Model 4 is nested within Model 5. 

## 11 12 13 Dependent variable = Mean 

## 14 Independent variable = Dose 

## 15 Data are assumed to be distributed: normally 

## 16 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 17 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 18 19 Total number of dose groups = 11 

## 20 Total number of records with missing values = 0 

## 21
Maximum number of iterations = 250 

## 22 Relative Function Convergence has been set to: 1e-008 

## 23 Parameter Convergence has been set to: 1e-008 

## 24 25 MLE solution provided: Exact 

## 26 27 28
Initial Parameter Values 

## 29 30
Variable Model 5 

## 31

-------- -------- 

## 32 lnalpha -3.27793 

## 33
rho 1.92227 

## 34
a 4.655 

## 35
b 1.52141e-006 

## 36
c 42.6316 

## 37
d 1 

## 38 39 40 41
Parameter Estimates 

## 42 43
Variable Model 5 

## 44

-------- ------- 

## 45 lnalpha -2.64351 

## 46
rho 1.93772 

## 47
a 5.43367 

## 48
b 1.65224e-005 

## 49
c 31.204 

## 50
d 1.21424 

## 51 52 53 Table of Stats From Input Data 

## 54 55
Dose N Obs Mean Obs Std Dev 

## 56

----- --- ---------- ------------- 

## 57
0 9 4.9 1.11 

## 58
69.5 4 4.9 1.18 

## 59
232 4 6.7 1.4 

## 60
463 4 7.2 1.8 

## 61
2318 4 8.3 0.26 

## 62
6949 4 14 5 

## 63
2.319e+004 4 59 6.8 

## 64
6.966e+004 4 96 46 

## 65
2.326e+005 4 155 16.4 

## 66
5.819e+005 4 182 26 

## 67
2.332e+006 4 189 26 

## 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-46 Estimated Values of Interest 

## 1 2
Dose Est Mean Est Std Scaled Residual 

## 3

------ ---------- --------- ---------------- 

## 4
0 5.434 1.375 -1.165 

## 5
69.5 5.478 1.385 -0.8342 

## 6
232 5.625 1.421 1.513 

## 7
463 5.875 1.483 1.787 

## 8
2318 8.529 2.127 -0.2151 

## 9
6949 16.87 4.119 -1.392 

## 10
2.319e+004 49.41 11.67 1.644 

## 11
6.966e+004 119.4 27.44 -1.708 

## 12
2.326e+005 168.6 38.32 -0.7087 

## 13
5.819e+005 169.6 38.53 0.6461 

## 14
2.332e+006 169.6 38.53 1.009 

## 15 16 17 18
Other models for which likelihoods are calculated: 

## 19 20 Model A1: Yij = Mu(i) + e(ij) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 Model A2: Yij = Mu(i) + e(ij) 

## 24 Var{e(ij)} = Sigma(i)^2 

## 25 26 Model A3: Yij = Mu(i) + e(ij) 

## 27 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 28 29 Model R: Yij = Mu + e(i) 

## 30 Var{e(ij)} = Sigma^2 

## 31 32 33
Likelihoods of Interest 

## 34 35 Model Log(likelihood) DF AIC 

## 36

------- ----------------- ---- ------------ 

## 37
A1 -158.1306 12 340.2613 

## 38
A2 -84.80028 22 213.6006 

## 39
A3 -98.82189 13 223.6438 

## 40
R -234.6252 2 473.2504 

## 41
5 -107.2031 6 226.4062 

## 42 43 44 Additive constant for all log-likelihoods = -45.03. This constant added to the 

## 45 above values gives the log-likelihood including the term that does not 

## 46 depend on the model parameters. 

## 47 48 49 Explanation of Tests 

## 50 51 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 52 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 53 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 54 55 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 56 57 58
Tests of Interest 

## 59 60 Test -2*log(Likelihood Ratio) D. F. p-value 

## 61

-------- ------------------------ ------ -------------- 

## 62
Test 1 299.6 20 < 0.0001 

## 63
Test 2 146.7 10 < 0.0001 

## 64
Test 3 28.04 9 0.0009381 

## 65
Test 7a 16.76 7 0.01899 

## 66 67 68 The p-value for Test 1 is less than .05. There appears to be a 

## 69 difference between response and/or variances among the dose 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-47 levels, it seems appropriate to model the data. 

## 1 2 The p-value for Test 2 is less than .1. A non-homogeneous 

## 3 variance model appears to be appropriate. 

## 4 5 The p-value for Test 3 is less than .1. You may want to 

## 6
consider a different variance model. 

## 7 8 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 9 describe the data; you may want to consider another model. 

## 10 11 12 Benchmark Dose Computations: 

## 13 14 Specified Effect = 1.000000 

## 15 16 Risk Type = Estimated standard deviations from control 

## 17 18
Confidence Level = 0.950000 

## 19 20
BMD = 1182.79 

## 21 22
BMDL = 556.132 

## 23 24 25 26 H.2.4.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 27 Unrestricted 28

0 50 100 150 200 250

0 500000 1e+006 1.5e+006 2e+006Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:25 11/20 2009 BMDBMDL Exponential



## 29 30 31 H.2.4.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 32 Power Unrestricted 33 34 35

==================================================================== 

## 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-48 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 1 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_BaP_hydro_act.(d) 

## 2 Gnuplot Plotting File: 

## 3
Fri Nov 20 13:25:17 2009 

## 4

==================================================================== 

## 5 6 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 7

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 8 9 The form of the response function by Model: 

## 10 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 11 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 12 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 13 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 14 15 Note: Y[dose] is the median response for exposure = dose; 

## 16 sign = +1 for increasing trend in data; 

## 17 sign = -1 for decreasing trend. 

## 18 19
Model 2 is nested within Models 3 and 4. 

## 20
Model 3 is nested within Model 5. 

## 21
Model 4 is nested within Model 5. 

## 22 23 24 Dependent variable = Mean 

## 25 Independent variable = Dose 

## 26 Data are assumed to be distributed: normally 

## 27 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 28 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 29 30 Total number of dose groups = 11 

## 31 Total number of records with missing values = 0 

## 32
Maximum number of iterations = 250 

## 33 Relative Function Convergence has been set to: 1e-008 

## 34 Parameter Convergence has been set to: 1e-008 

## 35 36 MLE solution provided: Exact 

## 37 38 39
Initial Parameter Values 

## 40 41
Variable Model 5 

## 42

-------- -------- 

## 43 lnalpha -3.27793 

## 44
rho 1.92227 

## 45
a 4.655 

## 46
b 1.52141e-006 

## 47
c 42.6316 

## 48
d 1 

## 49 50 51 52
Parameter Estimates 

## 53 54
Variable Model 5 

## 55

-------- ------- 

## 56 lnalpha -2.64351 

## 57
rho 1.93772 

## 58
a 5.43367 

## 59
b 1.65224e-005 

## 60
c 31.204 

## 61
d 1.21424 

## 62 63 64 Table of Stats From Input Data 

## 65 66
Dose N Obs Mean Obs Std Dev 

## 67

----- --- ---------- ------------- 

## 68
0 9 4.9 1.11 

## 69
69.5 4 4.9 1.18 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-49 232 4 6.7 1.4 

## 1
463 4 7.2 1.8 

## 2
2318 4 8.3 0.26 

## 3
6949 4 14 5 

## 4
2.319e+004 4 59 6.8 

## 5
6.966e+004 4 96 46 

## 6
2.326e+005 4 155 16.4 

## 7
5.819e+005 4 182 26 

## 8
2.332e+006 4 189 26 

## 9 10 11
Estimated Values of Interest 

## 12 13
Dose Est Mean Est Std Scaled Residual 

## 14

------ ---------- --------- ---------------- 

## 15
0 5.434 1.375 -1.165 

## 16
69.5 5.478 1.385 -0.8342 

## 17
232 5.625 1.421 1.513 

## 18
463 5.875 1.483 1.787 

## 19
2318 8.529 2.127 -0.2151 

## 20
6949 16.87 4.119 -1.392 

## 21
2.319e+004 49.41 11.67 1.644 

## 22
6.966e+004 119.4 27.44 -1.708 

## 23
2.326e+005 168.6 38.32 -0.7087 

## 24
5.819e+005 169.6 38.53 0.6461 

## 25
2.332e+006 169.6 38.53 1.009 

## 26 27 28 29
Other models for which likelihoods are calculated: 

## 30 31 Model A1: Yij = Mu(i) + e(ij) 

## 32 Var{e(ij)} = Sigma^2 

## 33 34 Model A2: Yij = Mu(i) + e(ij) 

## 35 Var{e(ij)} = Sigma(i)^2 

## 36 37 Model A3: Yij = Mu(i) + e(ij) 

## 38 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 39 40 Model R: Yij = Mu + e(i) 

## 41 Var{e(ij)} = Sigma^2 

## 42 43 44
Likelihoods of Interest 

## 45 46 Model Log(likelihood) DF AIC 

## 47

------- ----------------- ---- ------------ 

## 48
A1 -158.1306 12 340.2613 

## 49
A2 -84.80028 22 213.6006 

## 50
A3 -98.82189 13 223.6438 

## 51
R -234.6252 2 473.2504 

## 52
5 -107.2031 6 226.4062 

## 53 54 55 Additive constant for all log-likelihoods = -45.03. This constant added to the 

## 56 above values gives the log-likelihood including the term that does not 

## 57 depend on the model parameters. 

## 58 59 60 Explanation of Tests 

## 61 62 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 63 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 64 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 65 66 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 67 68 69
Tests of Interest 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-50 1 Test -2*log(Likelihood Ratio) D. F. p-value 

## 2

-------- ------------------------ ------ -------------- 

## 3
Test 1 299.6 20 < 0.0001 

## 4
Test 2 146.7 10 < 0.0001 

## 5
Test 3 28.04 9 0.0009381 

## 6
Test 7a 16.76 7 0.01899 

## 7 8 9 The p-value for Test 1 is less than .05. There appears to be a 

## 10 difference between response and/or variances among the dose 

## 11 levels, it seems appropriate to model the data. 

## 12 13 The p-value for Test 2 is less than .1. A non-homogeneous 

## 14 variance model appears to be appropriate. 

## 15 16 The p-value for Test 3 is less than .1. You may want to 

## 17
consider a different variance model. 

## 18 19 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 20 describe the data; you may want to consider another model. 

## 21 22 23 Benchmark Dose Computations: 

## 24 25 Specified Effect = 1.000000 

## 26 27 Risk Type = Estimated standard deviations from control 

## 28 29
Confidence Level = 0.950000 

## 30 31
BMD = 1182.79 

## 32 33
BMDL = 556.132 

## 34 35 H.2.4.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 36

0 50 100 150 200 250

0 500000 1e+006 1.5e+006 2e+006Mean Response

dose Hill Model

13:25 11/20 2009 BMD Hill



## 37 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-51 1 H.2.4.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 2 3 4

==================================================================== 

## 5 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 6 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_BaP_hydro_act.(d) 

## 7 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_BaP_hydro_act.plt 

## 8
Fri Nov 20 13:25:18 2009 

## 9

==================================================================== 

## 10 11 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 13 14 The form of the response function is: 

## 15 16 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 17 18 19 Dependent variable = Mean 

## 20 Independent variable = Dose 

## 21 Power parameter is not restricted 

## 22 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 23 24 Total number of dose groups = 11 

## 25 Total number of records with missing values = 0 

## 26
Maximum number of iterations = 250 

## 27 Relative Function Convergence has been set to: 1e-008 

## 28 Parameter Convergence has been set to: 1e-008 

## 29 30 31 32
Default Initial Parameter Values 

## 33 lalpha = 5.70855 

## 34
rho = 0 

## 35 intercept = 4.9 

## 36
v = 184.1 

## 37
n = 18 

## 38
k = 392820 

## 39 40 41 Asymptotic Correlation Matrix of Parameter Estimates 

## 42 43 lalpha rho intercept v n k 

## 44 45 lalpha NA NA NA NA NA NA 

## 46 47
rho NA NA NA NA NA NA 

## 48 49 intercept NA NA 1 NA 0.28 0.1 

## 50 51

v NA NA NA NA NA NA 

## 52 53
n NA NA 0.28 NA 1 -0.98 

## 54 55
k NA NA 0.1 NA -0.98 1 

## 56 57 58 59
Parameter Estimates 

## 60 61
95.0% Wald Confidence Interval 

## 62 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 63 lalpha 10.1833 NA NA NA 

## 64
rho 0.0839751 NA NA NA 

## 65 intercept -2.28069e-006 NA NA NA 

## 66
v 184.001 NA NA NA 

## 67
n 17.9976 NA NA NA 

## 68
k 1.41183e+007 NA NA NA 

## 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-52 1 At least some variance estimates are negative. 

## 2
THIS USUALLY MEANS THE MODEL HAS NOT CONVERGED! 

## 3 Try again from another starting point. 

## 4 5 6 7 Table of Data and Estimated Values of Interest 

## 8 9
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 10

------ --- -------- -------- ----------- ----------- ---------- 

## 11 12
0 9 4.9 -2.28e-006 1.11 94.3 0.156 

## 13
69.5 4 4.9 -2.28e-006 1.18 94.3 0.104 

## 14
232 4 6.7 -2.28e-006 1.4 94.3 0.142 

## 15
463 4 7.2 -2.28e-006 1.8 94.3 0.153 

## 16
2318 4 8.3 -2.28e-006 0.26 94.3 0.176 

## 17
6949 4 14 -2.28e-006 5 94.3 0.297 

## 18
2.319e+004 4 59 -2.28e-006 6.8 94.3 1.25 

## 19
6.966e+004 4 96 -2.28e-006 46 94.3 2.04 

## 20
2.326e+005 4 155 -2.28e-006 16.4 94.3 3.29 

## 21
5.819e+005 4 182 -2.28e-006 26 94.3 3.86 

## 22
2.332e+006 4 189 -2.28e-006 26 94.3 4.01 

## 23 24 25 26 Model Descriptions for likelihoods calculated 

## 27 28 29 Model A1: Yij = Mu(i) + e(ij) 

## 30 Var{e(ij)} = Sigma^2 

## 31 32 Model A2: Yij = Mu(i) + e(ij) 

## 33 Var{e(ij)} = Sigma(i)^2 

## 34 35 Model A3: Yij = Mu(i) + e(ij) 

## 36 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 37 Model A3 uses any fixed variance parameters that 

## 38 were specified by the user 

## 39 40 Model R: Yi = Mu + e(i) 

## 41 Var{e(i)} = Sigma^2 

## 42 43 44
Likelihoods of Interest 

## 45 46 Model Log(likelihood) # Param's AIC 

## 47
A1 -158.130647 12 340.261294 

## 48
A2 -84.800279 22 213.600558 

## 49
A3 -98.821893 13 223.643786 

## 50
fitted -247.263464 6 506.526929 

## 51
R -234.625213 2 473.250426 

## 52 53 54 Explanation of Tests 

## 55 56 Test 1: Do responses and/or variances differ among Dose levels? 

## 57 (A2 vs. R) 

## 58 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 59 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 60 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 61 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 62 63
Tests of Interest 

## 64 65 Test -2*log(Likelihood Ratio) Test df p-value 

## 66 67
Test 1 299.65 20 <.0001 

## 68
Test 2 146.661 10 <.0001 

## 69
Test 3 28.0432 9 0.0009381 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-53 Test 4 296.883 7 <.0001 

## 1 2 The p-value for Test 1 is less than .05. There appears to be a 

## 3 difference between response and/or variances among the dose levels 

## 4 It seems appropriate to model the data 

## 5 6 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 7 model appears to be appropriate 

## 8 9 The p-value for Test 3 is less than .1. You may want to consider a 

## 10
different variance model 

## 11 12 The p-value for Test 4 is less than .1. You may want to try a different 

## 13
model 

## 14 15 16 Benchmark Dose Computation 

## 17 18 Specified effect = 1 

## 19 20 Risk Type = Estimated standard deviations from the control mean 

## 21 22
Confidence level = 0.95 

## 23 24 BMD = 1.#QNAN 

## 25 26 27 BMDL computation failed. 

## 28 29 H.2.4.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 30

0 50 100 150 200 250

0 500000 1e+006 1.5e+006 2e+006Mean Response

dose Power Model with 0.95 Confidence Level

13:25 11/20 2009 BMDBMDL Power



## 31 32 33 H.2.4.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 34 Unrestricted 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-54 ==================================================================== 

## 1 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 2 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_BaP_hydro_act.(d) 

## 3 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_BaP_hydro_act.plt 

## 4
Fri Nov 20 13:25:19 2009 

## 5

==================================================================== 

## 6 7 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 8

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 9 10 The form of the response function is: 

## 11 12 Y[dose] = control + slope * dose^power 

## 13 14 15 Dependent variable = Mean 

## 16 Independent variable = Dose 

## 17 The power is not restricted 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 11 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 27 28
Default Initial Parameter Values 

## 29 lalpha = 5.70855 

## 30
rho = 0 

## 31
control = 4.9 

## 32 slope = 0.0304965 

## 33 power = 0.593743 

## 34 35 36 Asymptotic Correlation Matrix of Parameter Estimates 

## 37 38 lalpha rho control slope power 

## 39 40 lalpha 1 -0.9 -0.45 0.25 -0.23 

## 41 42
rho -0.9 1 0.35 -0.18 0.12 

## 43 44
control -0.45 0.35 1 -0.44 0.42 

## 45 46 slope 0.25 -0.18 -0.44 1 -0.98 

## 47 48 power -0.23 0.12 0.42 -0.98 1 

## 49 50 51 52
Parameter Estimates 

## 53 54
95.0% Wald Confidence Interval 

## 55 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 56 lalpha -3.42042 0.570798 -4.53917 -2.30168 

## 57
rho 2.42941 0.164247 2.10749 2.75133 

## 58
control 4.52558 0.315791 3.90665 5.14452 

## 59 slope 0.0642178 0.0318952 0.00170434 0.126731 

## 60 power 0.619697 0.0482017 0.525223 0.71417 

## 61 62 63 64
Table of Data and Estimated Values of Interest 

## 65 66
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 67

------ --- -------- -------- ----------- ----------- ---------- 

## 68 69
0 9 4.9 4.53 1.11 1.13 0.993 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-55 69.5 4 4.9 5.42 1.18 1.41 -0.732 

## 1
232 4 6.7 6.4 1.4 1.72 0.344 

## 2
463 4 7.2 7.41 1.8 2.06 -0.2 

## 3
2318 4 8.3 12.3 0.26 3.83 -2.11 

## 4
6949 4 14 20 5 6.86 -1.74 

## 5
2.319e+004 4 59 37.1 6.8 14.6 3.01 

## 6
6.966e+004 4 96 68.9 46 30.9 1.75 

## 7
2.326e+005 4 155 140 16.4 73.4 0.397 

## 8
5.819e+005 4 182 244 26 144 -0.868 

## 9
2.332e+006 4 189 572 26 404 -1.89 

## 10 11 12 13 Model Descriptions for likelihoods calculated 

## 14 15 16 Model A1: Yij = Mu(i) + e(ij) 

## 17 Var{e(ij)} = Sigma^2 

## 18 19 Model A2: Yij = Mu(i) + e(ij) 

## 20 Var{e(ij)} = Sigma(i)^2 

## 21 22 Model A3: Yij = Mu(i) + e(ij) 

## 23 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 24 Model A3 uses any fixed variance parameters that 

## 25 were specified by the user 

## 26 27 Model R: Yi = Mu + e(i) 

## 28 Var{e(i)} = Sigma^2 

## 29 30 31
Likelihoods of Interest 

## 32 33 Model Log(likelihood) # Param's AIC 

## 34
A1 -158.130647 12 340.261294 

## 35
A2 -84.800279 22 213.600558 

## 36
A3 -98.821893 13 223.643786 

## 37
fitted -130.634662 5 271.269325 

## 38
R -234.625213 2 473.250426 

## 39 40 41 Explanation of Tests 

## 42 43 Test 1: Do responses and/or variances differ among Dose levels? 

## 44 (A2 vs. R) 

## 45 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 46 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 47 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 48 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 49 50
Tests of Interest 

## 51 52 Test -2*log(Likelihood Ratio) Test df p-value 

## 53 54
Test 1 299.65 20 <.0001 

## 55
Test 2 146.661 10 <.0001 

## 56
Test 3 28.0432 9 0.0009381 

## 57
Test 4 63.6255 8 <.0001 

## 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose levels 

## 61 It seems appropriate to model the data 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 64 model appears to be appropriate 

## 65 66 The p-value for Test 3 is less than .1. You may want to consider a 

## 67
different variance model 

## 68 69 The p-value for Test 4 is less than .1. You may want to try a different 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-56 model 

## 1 2 3 Benchmark Dose Computation 

## 4 5 Specified effect = 1 

## 6 7 Risk Type = Estimated standard deviations from the control mean 

## 8 9
Confidence level = 0.95 

## 10 11
BMD = 102.508 

## 12 13 14
BMDL = 44.1703 

## 15 16

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-57 H.2.5. National Toxicology Program. (2006): EROD Liver Week 53 1
H.2.5.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 113.40 <0.0001 203.18 7.6E+03 5.1E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 113.40 <0.0001 203.18 7.6E+03 5.1E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 20.95 0.00 112.76 1.2E+02 8.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 6.69 0.04 100.50 3.1E+02 2.0E+02 nonconstant variance, power restricted ≥ 1

Hill c 2 <.0001 3.09 0.21 96.90 4.2E+02 3.0E+02 nonconstant variance, n restricted >1

Hill d 2 <.0001 3.09 0.21 96.90 4.2E+02 3.0E+02 nonconstant variance, n unrestricted

linear 4 <.0001 73.05 <.0001 162.86 1.5E+02 1.1E+02 nonconstant variance

polynomial 4 <.0001 -81.81 <.0001 8.00 6.0E-08 error nonconstant variance

power 4 <.0001 73.05 <.0001 162.86 1.5E+02 1.1E+02 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 4 <0.0001 77.17 <0.0001 201.35 7.0E+03 5.9E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 77.17 <0.0001 201.35 7.0E+03 5.9E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 7.36 0.06 133.54 4.6E+02 3.6E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 4.20 0.12 132.37 7.3E+02 4.5E+02 constant variance, power restricted ≥ 1

Hill 2 <.0001 2.31 0.31 130.49 9.1E+02 6.1E+02 constant variance, n restricted >1

Hill 2 <.0001 2.31 0.31 130.49 9.1E+02 6.1E+02 constant variance, n unrestricted

linear 4 <.0001 64.69 <.0001 188.86 4.0E+03 3.2E+03 constant variance

polynomial 4 <.0001 64.69 <.0001 188.86 4.0E+03 3.2E+03 constant variance

power 4 <.0001 64.69 <.0001 188.86 4.0E+03 3.2E+03 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-58 H.2.5.2. Figure for Selected Model: Hill, No nconstant Variance, n Restricted >1 1

5 10 15 20 25

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Hill Model with 0.95 Confidence Level

11:23 11/19 2009 BMD BMDL Hill



## 2 3 4 H.2.5.3. Output file for Selected Model: Hill , Nonconstant Variance, n Restricted >1 5 6 7

==================================================================== 

## 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_BMR1_Tbl12_wk53_EROD_liv.(d) 

## 10 Gnuplot Plotting File: C:\USEPA\BMDS21\AD\Blood\Hill_BMR1_Tbl12_wk53_EROD_liv.plt 

## 11
Thu Nov 19 11:23:04 2009 

## 12

==================================================================== 

## 13 14
0 

## 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 16 17 The form of the response function is: 

## 18 19 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 20 21 22 Dependent variable = Mean 

## 23 Independent variable = Dose 

## 24 Power parameter restricted to be greater than 1 

## 25 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 26 27 Total number of dose groups = 6 

## 28 Total number of records with missing values = 0 

## 29
Maximum number of iterations = 250 

## 30 Relative Function Convergence has been set to: 1e-008 

## 31 Parameter Convergence has been set to: 1e-008 

## 32 33 34 35
Default Initial Parameter Values 

## 36 lalpha = 1.59547 

## 37
rho = 0 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-59 intercept = 3.614 

## 1
v = 17.599 

## 2
n = 2.06282 

## 3
k = 3589.94 

## 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 

## 7 8 lalpha rho intercept v n k 

## 9 10 lalpha 1 -0.96 -0.16 0.088 -0.06 0.042 

## 11 12
rho -0.96 1 0.15 -0.12 0.062 -0.045 

## 13 14 intercept -0.16 0.15 1 -0.18 0.13 0.073 

## 15 16
v 0.088 -0.12 -0.18 1 -0.7 0.82 

## 17 18
n -0.06 0.062 0.13 -0.7 1 -0.78 

## 19 20
k 0.042 -0.045 0.073 0.82 -0.78 1 

## 21 22 23 24
Parameter Estimates 

## 25 26
95.0% Wald Confidence Interval 

## 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 28 lalpha -4.86517 0.742003 -6.31947 -3.41087 

## 29
rho 2.26994 0.287404 1.70664 2.83324 

## 30 intercept 3.62886 0.133846 3.36652 3.89119 

## 31
v 17.8693 0.946035 16.0151 19.7235 

## 32
n 2.12332 0.238762 1.65535 2.59128 

## 33
k 2573.21 216.955 2147.99 2998.43 

## 34 35 36 37
Table of Data and Estimated Values of Interest 

## 38 39
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 40

------ --- -------- -------- ----------- ----------- ---------- 

## 41 42
0 8 3.61 3.63 0.486 0.379 -0.111 

## 43
1354 8 7.27 7.27 0.557 0.834 0.013 

## 44
3056 8 14.8 14.2 1.61 1.78 0.925 

## 45
5259 8 17.3 18.3 1.59 2.38 -1.19 

## 46
8918 8 20.6 20.3 3.05 2.68 0.29 

## 47
1.6e+004 8 21.2 21.1 3.82 2.8 0.077 

## 48 49 50 51 Model Descriptions for likelihoods calculated 

## 52 53 54 Model A1: Yij = Mu(i) + e(ij) 

## 55 Var{e(ij)} = Sigma^2 

## 56 57 Model A2: Yij = Mu(i) + e(ij) 

## 58 Var{e(ij)} = Sigma(i)^2 

## 59 60 Model A3: Yij = Mu(i) + e(ij) 

## 61 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 62 Model A3 uses any fixed variance parameters that 

## 63 were specified by the user 

## 64 65 Model R: Yi = Mu + e(i) 

## 66 Var{e(i)} = Sigma^2 

## 67 68 69
Likelihoods of Interest 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-60 1 Model Log(likelihood) # Param's AIC 

## 2
A1 -59.086537 7 132.173073 

## 3
A2 -37.515858 12 99.031716 

## 4
A3 -40.906180 8 97.812359 

## 5 fitted -42.452016 6 96.904031 

## 6
R -116.710291 2 237.420582 

## 7 8 9 Explanation of Tests 

## 10 11 Test 1: Do responses and/or variances differ among Dose levels? 

## 12 (A2 vs. R) 

## 13 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 14 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 15 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 16 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 17 18
Tests of Interest 

## 19 20 Test -2*log(Likelihood Ratio) Test df p-value 

## 21 22
Test 1 158.389 10 <.0001 

## 23
Test 2 43.1414 5 <.0001 

## 24
Test 3 6.78064 4 0.1479 

## 25
Test 4 3.09167 2 0.2131 

## 26 27 The p-value for Test 1 is less than .05. There appears to be a 

## 28 difference between response and/or variances among the dose levels 

## 29 It seems appropriate to model the data 

## 30 31 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 32 model appears to be appropriate 

## 33 34 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 35 to be appropriate here 

## 36 37 The p-value for Test 4 is greater than .1. The model chosen seems 

## 38 to adequately describe the data 

## 39 40 41 Benchmark Dose Computation 

## 42 43 Specified effect = 1 

## 44 45 Risk Type = Estimated standard deviations from the control mean 

## 46 47
Confidence level = 0.95 

## 48 49
BMD = 423.477 

## 50 51
BMDL = 304.577 

## 52 53

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-61 H.2.5.4. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 1

5 10 15 20 25

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Hill Model with 0.95 Confidence Level

11:23 11/19 2009 BMD BMDL Hill



## 2 3 4 H.2.5.5. Output file for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 5 6 7

==================================================================== 

## 8 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 9 Input Data File: C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_Tbl12_wk53_EROD_liv.(d) 

## 10 Gnuplot Plotting File: 

## 11 C:\USEPA\BMDS21\AD\Blood\Hill_Unrest_BMR1_Tbl12_wk53_EROD_liv.plt 

## 12
Thu Nov 19 11:23:13 2009 

## 13

==================================================================== 

## 14 15
0 

## 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 17 18 The form of the response function is: 

## 19 20 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 21 22 23 Dependent variable = Mean 

## 24 Independent variable = Dose 

## 25 Power parameter is not restricted 

## 26 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37 lalpha = 1.59547 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-62 rho = 0 

## 1 intercept = 3.614 

## 2
v = 17.599 

## 3
n = 2.06282 

## 4
k = 3589.94 

## 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 

## 8 9 lalpha rho intercept v n k 

## 10 11 lalpha 1 -0.96 -0.16 0.088 -0.06 0.042 

## 12 13
rho -0.96 1 0.15 -0.12 0.062 -0.045 

## 14 15 intercept -0.16 0.15 1 -0.18 0.13 0.073 

## 16 17
v 0.088 -0.12 -0.18 1 -0.7 0.82 

## 18 19
n -0.06 0.062 0.13 -0.7 1 -0.78 

## 20 21
k 0.042 -0.045 0.073 0.82 -0.78 1 

## 22 23 24 25
Parameter Estimates 

## 26 27
95.0% Wald Confidence Interval 

## 28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 29 lalpha -4.86517 0.742003 -6.31947 -3.41087 

## 30
rho 2.26994 0.287404 1.70664 2.83324 

## 31 intercept 3.62886 0.133846 3.36652 3.89119 

## 32
v 17.8693 0.946034 16.0151 19.7235 

## 33
n 2.12332 0.238762 1.65535 2.59128 

## 34
k 2573.21 216.955 2147.99 2998.43 

## 35 36 37 38
Table of Data and Estimated Values of Interest 

## 39 40
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 41

------ --- -------- -------- ----------- ----------- ---------- 

## 42 43
0 8 3.61 3.63 0.486 0.379 -0.111 

## 44
1354 8 7.27 7.27 0.557 0.834 0.013 

## 45
3056 8 14.8 14.2 1.61 1.78 0.925 

## 46
5259 8 17.3 18.3 1.59 2.38 -1.19 

## 47
8918 8 20.6 20.3 3.05 2.68 0.29 

## 48
1.6e+004 8 21.2 21.1 3.82 2.8 0.077 

## 49 50 51 52 Model Descriptions for likelihoods calculated 

## 53 54 55 Model A1: Yij = Mu(i) + e(ij) 

## 56 Var{e(ij)} = Sigma^2 

## 57 58 Model A2: Yij = Mu(i) + e(ij) 

## 59 Var{e(ij)} = Sigma(i)^2 

## 60 61 Model A3: Yij = Mu(i) + e(ij) 

## 62 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 63 Model A3 uses any fixed variance parameters that 

## 64 were specified by the user 

## 65 66 Model R: Yi = Mu + e(i) 

## 67 Var{e(i)} = Sigma^2 

## 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-63 Likelihoods of Interest 

## 1 2 Model Log(likelihood) # Param's AIC 

## 3
A1 -59.086537 7 132.173073 

## 4
A2 -37.515858 12 99.031716 

## 5
A3 -40.906180 8 97.812359 

## 6
fitted -42.452016 6 96.904032 

## 7
R -116.710291 2 237.420582 

## 8 9 10 Explanation of Tests 

## 11 12 Test 1: Do responses and/or variances differ among Dose levels? 

## 13 (A2 vs. R) 

## 14 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 15 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 16 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 17 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 18 19
Tests of Interest 

## 20 21 Test -2*log(Likelihood Ratio) Test df p-value 

## 22 23
Test 1 158.389 10 <.0001 

## 24
Test 2 43.1414 5 <.0001 

## 25
Test 3 6.78064 4 0.1479 

## 26
Test 4 3.09167 2 0.2131 

## 27 28 The p-value for Test 1 is less than .05. There appears to be a 

## 29 difference between response and/or variances among the dose levels 

## 30 It seems appropriate to model the data 

## 31 32 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 33 model appears to be appropriate 

## 34 35 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 36 to be appropriate here 

## 37 38 The p-value for Test 4 is greater than .1. The model chosen seems 

## 39 to adequately describe the data 

## 40 41 42 Benchmark Dose Computation 

## 43 44 Specified effect = 1 

## 45 46 Risk Type = Estimated standard deviations from the control mean 

## 47 48
Confidence level = 0.95 

## 49 50
BMD = 423.477 

## 51 52
BMDL = 304.577 

## 53 54

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-64 H.2.6. National Toxicology Program. (2006): Lung EROD Week 31 1
H.2.6.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 123.80 <0.0001 390.99 1.2E+04 8.1E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 123.80 <0.0001 390.99 1.2E+04 8.1E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 13.01 0.00 282.20 4.1E+01 2.9E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 13.01 0.00 282.20 4.1E+01 2.9E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 <0.0001 13.01 0.00 282.20 4.1E+01 2.9E+01 nonconstant variance, power unrestricted

Hill 4 <.0001 59.49 <.0001 326.67 1.3E-11 1.3E-11 nonconstant variance, n restricted >1, bound hit

Hill d 4 <.0001 59.49 <.0001 326.67 1.3E-11 1.3E-11 nonconstant variance, n unrestricted

linear 4 <.0001 116.14 <.0001 383.32 4.1E+03 1.5E+03 nonconstant variance

polynomial 4 <.0001 123.25 <.0001 390.43 1.3E+04 7.5E+01 nonconstant variance

power 4 <.0001 116.14 <.0001 383.32 4.1E+03 1.5E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 23.64 <.0001 292.82 4.5E-02 4.5E-02 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 80.66 <0.0001 390.82 9.0E+03 7.5E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 80.66 <0.0001 390.82 9.0E+03 7.5E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 12.08 0.01 324.24 4.6E+02 3.4E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 12.08 0.00 326.24 4.6E+02 3.4E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 12.08 0.00 326.24 4.6E+02 3.4E+02 constant variance, power unrestricted

Hill 2 <.0001 14.17 0.00 328.33 5.1E+02 2.4E+02 constant variance, n restricted >1

Hill 2 <.0001 14.17 0.00 328.33 5.1E+02 1.9E+02 constant variance, n unrestricted

linear 4 <.0001 71.44 <.0001 381.60 5.6E+03 4.4E+03 constant variance

polynomial 4 <.0001 71.44 <.0001 381.60 5.6E+03 4.4E+03 constant variance

power 4 <.0001 71.44 <.0001 381.60 5.6E+03 4.4E+03 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-65 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 3 <.0001 23.14 <.0001 335.30 2.0E+01 2.0E+00 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.2.6.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:16 11/20 2009 BMD BMDL Exponential



## 5 6 7 H.2.6.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_Lung_EROD_wk31.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 13:16:38 2009 

## 16

==================================================================== 

## 17 18 Tbl 12, Week 31, Lung Microsomes EROD 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-66 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 6 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 4 

## 32

-------- -------- 

## 33 lnalpha -1.42653 

## 34
rho 1.46168 

## 35
a 1.96745 

## 36
b 0.000226755 

## 37
c 26.7857 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 4 

## 45

-------- ------- 

## 46 lnalpha -1.47384 

## 47
rho 1.57432 

## 48
a 2.11972 

## 49
b 0.000440068 

## 50
c 23.6215 

## 51
d 1 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 10 2.071 0.9708 

## 59
1284 10 25.34 2.549 

## 60
2932 10 30.39 5.831 

## 61
5075 10 50.19 8.68 

## 62
8629 10 49.07 13.91 

## 63
1.55e+004 10 48.42 8.933 

## 64 65 66
Estimated Values of Interest 

## 67 68
Dose Est Mean Est Std Scaled Residual 

## 69

------ ---------- --------- ---------------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-67 0 2.12 0.8646 -0.1782 

## 1
1284 22.82 5.612 1.423 

## 2
2932 36.88 8.189 -2.506 

## 3
5075 44.93 9.567 1.738 

## 4
8629 49 10.24 0.02179 

## 5
1.55e+004 50.02 10.41 -0.4854 

## 6 7 8 9
Other models for which likelihoods are calculated: 

## 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Model R: Yij = Mu + e(i) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) DF AIC 

## 27

------- ----------------- ---- ------------ 

## 28
A1 -152.0793 7 318.1586 

## 29
A2 -123.367 12 270.734 

## 30
A3 -129.5911 8 275.1823 

## 31
R -206.5175 2 417.0349 

## 32
4 -136.0978 5 282.1956 

## 33 34 35 Additive constant for all log-likelihoods = -55.14. This constant added to the 

## 36 above values gives the log-likelihood including the term that does not 

## 37 depend on the model parameters. 

## 38 39 40 Explanation of Tests 

## 41 42 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 43 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 44 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 45 46 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 47 48 49
Tests of Interest 

## 50 51 Test -2*log(Likelihood Ratio) D. F. p-value 

## 52

-------- ------------------------ ------ -------------- 

## 53
Test 1 166.3 10 < 0.0001 

## 54
Test 2 57.42 5 < 0.0001 

## 55
Test 3 12.45 4 0.01431 

## 56
Test 6a 13.01 3 0.004608 

## 57 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose 

## 61 levels, it seems appropriate to model the data. 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous 

## 64 variance model appears to be appropriate. 

## 65 66 The p-value for Test 3 is less than .1. You may want to 

## 67
consider a different variance model. 

## 68 69 The p-value for Test 6a is less than .1. Model 4 may not adequately 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-68 describe the data; you may want to consider another model. 

## 1 2 3 Benchmark Dose Computations: 

## 4 5 Specified Effect = 1.000000 

## 6 7 Risk Type = Estimated standard deviations from control 

## 8 9
Confidence Level = 0.950000 

## 10 11
BMD = 41.3446 

## 12 13
BMDL = 28.8946 

## 14 15 16 17 H.2.6.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 18 Unrestricted 19

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:16 11/20 2009 BMD BMDL Exponential



## 20 21 22 H.2.6.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 23 Power Unrestricted 24 25 26

==================================================================== 

## 27 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 28 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_Lung_EROD_wk31.(d) 

## 29 Gnuplot Plotting File: 

## 30
Fri Nov 20 13:16:45 2009 

## 31

==================================================================== 

## 32 33 Tbl 12, Week 31, Lung Microsomes EROD 

## 34

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-69 The form of the response function by Model: 

## 1 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 2 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 3 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 4 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 5 6 Note: Y[dose] is the median response for exposure = dose; 

## 7 sign = +1 for increasing trend in data; 

## 8 sign = -1 for decreasing trend. 

## 9 10
Model 2 is nested within Models 3 and 4. 

## 11
Model 3 is nested within Model 5. 

## 12
Model 4 is nested within Model 5. 

## 13 14 15 Dependent variable = Mean 

## 16 Independent variable = Dose 

## 17 Data are assumed to be distributed: normally 

## 18 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 19 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 5 

## 33

-------- -------- 

## 34 lnalpha -1.42653 

## 35
rho 1.46168 

## 36
a 1.96745 

## 37
b 0.000226755 

## 38
c 26.7857 

## 39
d 1 

## 40 41 42 43
Parameter Estimates 

## 44 45
Variable Model 5 

## 46

-------- ------- 

## 47 lnalpha -1.47384 

## 48
rho 1.57432 

## 49
a 2.11972 

## 50
b 0.000440068 

## 51
c 23.6215 

## 52
d 1 

## 53 54 55 Table of Stats From Input Data 

## 56 57
Dose N Obs Mean Obs Std Dev 

## 58

----- --- ---------- ------------- 

## 59
0 10 2.071 0.9708 

## 60
1284 10 25.34 2.549 

## 61
2932 10 30.39 5.831 

## 62
5075 10 50.19 8.68 

## 63
8629 10 49.07 13.91 

## 64
1.55e+004 10 48.42 8.933 

## 65 66 67
Estimated Values of Interest 

## 68 69
Dose Est Mean Est Std Scaled Residual 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-70 ------ ---------- --------- ---------------- 

## 1
0 2.12 0.8646 -0.1782 

## 2
1284 22.82 5.612 1.423 

## 3
2932 36.88 8.189 -2.506 

## 4
5075 44.93 9.567 1.738 

## 5
8629 49 10.24 0.02179 

## 6
1.55e+004 50.02 10.41 -0.4854 

## 7 8 9 10
Other models for which likelihoods are calculated: 

## 11 12 Model A1: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma^2 

## 14 15 Model A2: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma(i)^2 

## 17 18 Model A3: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Model R: Yij = Mu + e(i) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) DF AIC 

## 28

------- ----------------- ---- ------------ 

## 29
A1 -152.0793 7 318.1586 

## 30
A2 -123.367 12 270.734 

## 31
A3 -129.5911 8 275.1823 

## 32
R -206.5175 2 417.0349 

## 33
5 -136.0978 5 282.1956 

## 34 35 36 Additive constant for all log-likelihoods = -55.14. This constant added to the 

## 37 above values gives the log-likelihood including the term that does not 

## 38 depend on the model parameters. 

## 39 40 41 Explanation of Tests 

## 42 43 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 44 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 45 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 46 47 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 48 49 50
Tests of Interest 

## 51 52 Test -2*log(Likelihood Ratio) D. F. p-value 

## 53

-------- ------------------------ ------ -------------- 

## 54
Test 1 166.3 10 < 0.0001 

## 55
Test 2 57.42 5 < 0.0001 

## 56
Test 3 12.45 4 0.01431 

## 57
Test 7a 13.01 3 0.004608 

## 58 59 60 The p-value for Test 1 is less than .05. There appears to be a 

## 61 difference between response and/or variances among the dose 

## 62 levels, it seems appropriate to model the data. 

## 63 64 The p-value for Test 2 is less than .1. A non-homogeneous 

## 65 variance model appears to be appropriate. 

## 66 67 The p-value for Test 3 is less than .1. You may want to 

## 68
consider a different variance model. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-71 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 1 describe the data; you may want to consider another model. 

## 2 3 4 Benchmark Dose Computations: 

## 5 6 Specified Effect = 1.000000 

## 7 8 Risk Type = Estimated standard deviations from control 

## 9 10
Confidence Level = 0.950000 

## 11 12
BMD = 41.3446 

## 13 14
BMDL = 28.8946 

## 15 16 17 18 H.2.6.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 19

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Hill Model with 0.95 Confidence Level

13:16 11/20 2009 BMDBMDL Hill



## 20 21 22 H.2.6.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 23 24 25

==================================================================== 

## 26 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 27 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_Lung_EROD_wk31.(d) 

## 28 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_Lung_EROD_wk31.plt 

## 29
Fri Nov 20 13:16:47 2009 

## 30

==================================================================== 

## 31 32 Tbl 12, Week 31, Lung Microsomes EROD 

## 33

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 34 35 The form of the response function is: 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-72 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 1 2 3 Dependent variable = Mean 

## 4 Independent variable = Dose 

## 5 Power parameter is not restricted 

## 6 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 7 8 Total number of dose groups = 6 

## 9 Total number of records with missing values = 0 

## 10
Maximum number of iterations = 250 

## 11 Relative Function Convergence has been set to: 1e-008 

## 12 Parameter Convergence has been set to: 1e-008 

## 13 14 15 16
Default Initial Parameter Values 

## 17 lalpha = 4.17467 

## 18
rho = 0 

## 19 intercept = 2.071 

## 20
v = 48.119 

## 21
n = 18 

## 22
k = 4322.89 

## 23 24 25 Asymptotic Correlation Matrix of Parameter Estimates 

## 26 27 ( *** The model parameter(s) -n -k 

## 28 have been estimated at a boundary point, or have been specified by the user, 

## 29 and do not appear in the correlation matrix ) 

## 30 31 lalpha rho intercept v 

## 32 33 lalpha 1 -0.95 -0.49 0.11 

## 34 35
rho -0.95 1 0.45 -0.22 

## 36 37 intercept -0.49 0.45 1 -0.15 

## 38 39
v 0.11 -0.22 -0.15 1 

## 40 41 42 43
Parameter Estimates 

## 44 45
95.0% Wald Confidence Interval 

## 46 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 47 lalpha -1.47774 0.642044 -2.73613 -0.219359 

## 48
rho 1.8037 0.187436 1.43633 2.17107 

## 49 intercept 2.071 0.291246 1.50017 2.64183 

## 50
v 38.6102 1.9322 34.8232 42.3972 

## 51
n 18 NA 

## 52
k 1.5503e-011 NA 

## 53 54 NA - Indicates that this parameter has hit a bound 

## 55 implied by some inequality constraint and thus 

## 56
has no standard error. 

## 57 58 59 60
Table of Data and Estimated Values of Interest 

## 61 62
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 63

------ --- -------- -------- ----------- ----------- ---------- 

## 64 65
0 10 2.07 2.07 0.971 0.921 -2.27e-007 

## 66
1284 10 25.3 40.7 2.55 13.5 -3.59 

## 67
2932 10 30.4 40.7 5.83 13.5 -2.41 

## 68
5075 10 50.2 40.7 8.68 13.5 2.23 

## 69
8629 10 49.1 40.7 13.9 13.5 1.96 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-73 1.55e+004 10 48.4 40.7 8.93 13.5 1.81 

## 1 2 3 4 Model Descriptions for likelihoods calculated 

## 5 6 7 Model A1: Yij = Mu(i) + e(ij) 

## 8 Var{e(ij)} = Sigma^2 

## 9 10 Model A2: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = Sigma(i)^2 

## 12 13 Model A3: Yij = Mu(i) + e(ij) 

## 14 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 15 Model A3 uses any fixed variance parameters that 

## 16 were specified by the user 

## 17 18 Model R: Yi = Mu + e(i) 

## 19 Var{e(i)} = Sigma^2 

## 20 21
Likelihoods of Interest 

## 22 23 Model Log(likelihood) # Param's AIC 

## 24
A1 -152.079318 7 318.158637 

## 25
A2 -123.366985 12 270.733969 

## 26
A3 -129.591134 8 275.182269 

## 27
fitted -159.335928 4 326.671856 

## 28
R -206.517459 2 417.034919 

## 29 30 31 Explanation of Tests 

## 32 33 Test 1: Do responses and/or variances differ among Dose levels? 

## 34 (A2 vs. R) 

## 35 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 36 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 37 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 38 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 39 40
Tests of Interest 

## 41 42 Test -2*log(Likelihood Ratio) Test df p-value 

## 43 44
Test 1 166.301 10 <.0001 

## 45
Test 2 57.4247 5 <.0001 

## 46
Test 3 12.4483 4 0.01431 

## 47
Test 4 59.4896 4 <.0001 

## 48 49 The p-value for Test 1 is less than .05. There appears to be a 

## 50 difference between response and/or variances among the dose levels 

## 51 It seems appropriate to model the data 

## 52 53 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 54 model appears to be appropriate 

## 55 56 The p-value for Test 3 is less than .1. You may want to consider a 

## 57 different variance model 

## 58 59 The p-value for Test 4 is less than .1. You may want to try a different 

## 60
model 

## 61 62 63 Benchmark Dose Computation 

## 64 65 Specified effect = 1 

## 66 67 Risk Type = Estimated standard deviations from the control mean 

## 68 69
Confidence level = 0.95 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-74 1
BMD = 1.26143e-011 

## 2 3
BMDL = 1.26143e-011 

## 4 5 H.2.6.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 6

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Power Model with 0.95 Confidence Level

13:16 11/20 2009 BMDBMDL Power



## 7 8 9 H.2.6.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 10 Unrestricted 11 12 13

==================================================================== 

## 14 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 15 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_Lung_EROD_wk31.(d) 

## 16 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_Lung_EROD_wk31.plt 

## 17
Fri Nov 20 13:16:48 2009 

## 18

==================================================================== 

## 19 20 Tbl 12, Week 31, Lung Microsomes EROD 

## 21

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 22 23 The form of the response function is: 

## 24 25 Y[dose] = control + slope * dose^power 

## 26 27 28 Dependent variable = Mean 

## 29 Independent variable = Dose 

## 30 The power is not restricted 

## 31 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 32 33 Total number of dose groups = 6 

## 34 Total number of records with missing values = 0 

## 35
Maximum number of iterations = 250 

## 36 Relative Function Convergence has been set to: 1e-008 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-75 Parameter Convergence has been set to: 1e-008 

## 1 2 3 4
Default Initial Parameter Values 

## 5 lalpha = 4.17467 

## 6
rho = 0 

## 7
control = 2.071 

## 8 slope = 2.58483 

## 9 power = 0.313845 

## 10 11 12 Asymptotic Correlation Matrix of Parameter Estimates 

## 13 14 lalpha rho control slope power 

## 15 16 lalpha 1 -0.94 -0.42 0.14 -0.14 

## 17 18
rho -0.94 1 0.38 -0.17 0.15 

## 19 20
control -0.42 0.38 1 -0.11 0.094 

## 21 22 slope 0.14 -0.17 -0.11 1 -1 

## 23 24 power -0.14 0.15 0.094 -1 1 

## 25 26 27 28
Parameter Estimates 

## 29 30
95.0% Wald Confidence Interval 

## 31 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 32 lalpha -1.53087 0.573913 -2.65572 -0.406018 

## 33
rho 1.64612 0.167167 1.31848 1.97376 

## 34
control 2.1082 0.270802 1.57744 2.63896 

## 35 slope 2.35281 0.945551 0.499559 4.20605 

## 36 power 0.325737 0.0465627 0.234476 0.416998 

## 37 38 39 40
Table of Data and Estimated Values of Interest 

## 41 42
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 43

------ --- -------- -------- ----------- ----------- ---------- 

## 44 45
0 10 2.07 2.11 0.971 0.859 -0.137 

## 46
1284 10 25.3 26.3 2.55 6.86 -0.453 

## 47
2932 10 30.4 33.8 5.83 8.43 -1.28 

## 48
5075 10 50.2 40 8.68 9.69 3.33 

## 49
8629 10 49.1 47.2 13.9 11.1 0.545 

## 50
1.55e+004 10 48.4 56.6 8.93 12.9 -2.01 

## 51 52 53 54 Model Descriptions for likelihoods calculated 

## 55 56 57 Model A1: Yij = Mu(i) + e(ij) 

## 58 Var{e(ij)} = Sigma^2 

## 59 60 Model A2: Yij = Mu(i) + e(ij) 

## 61 Var{e(ij)} = Sigma(i)^2 

## 62 63 Model A3: Yij = Mu(i) + e(ij) 

## 64 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 65 Model A3 uses any fixed variance parameters that 

## 66 were specified by the user 

## 67 68 Model R: Yi = Mu + e(i) 

## 69 Var{e(i)} = Sigma^2 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-76 1 2
Likelihoods of Interest 

## 3 4 Model Log(likelihood) # Param's AIC 

## 5
A1 -152.079318 7 318.158637 

## 6
A2 -123.366985 12 270.733969 

## 7
A3 -129.591134 8 275.182269 

## 8
fitted -141.409222 5 292.818443 

## 9
R -206.517459 2 417.034919 

## 10 11 12 Explanation of Tests 

## 13 14 Test 1: Do responses and/or variances differ among Dose levels? 

## 15 (A2 vs. R) 

## 16 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 17 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 18 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 19 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 20 21
Tests of Interest 

## 22 23 Test -2*log(Likelihood Ratio) Test df p-value 

## 24 25
Test 1 166.301 10 <.0001 

## 26
Test 2 57.4247 5 <.0001 

## 27
Test 3 12.4483 4 0.01431 

## 28
Test 4 23.6362 3 <.0001 

## 29 30 The p-value for Test 1 is less than .05. There appears to be a 

## 31 difference between response and/or variances among the dose levels 

## 32 It seems appropriate to model the data 

## 33 34 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 35 model appears to be appropriate 

## 36 37 The p-value for Test 3 is less than .1. You may want to consider a 

## 38
different variance model 

## 39 40 The p-value for Test 4 is less than .1. You may want to try a different 

## 41
model 

## 42 43 44 Benchmark Dose Computation 

## 45 46 Specified effect = 1 

## 47 48 Risk Type = Estimated standard deviations from the control mean 

## 49 50
Confidence level = 0.95 

## 51 52
BMD = 0.0454117 

## 53 54 55
BMDL = 0.0454112 

## 56 57

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-77 H.2.7. National Toxicology Program. (2006): Lung EROD Week 53 1
H.2.7.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 64.02 <0.0001 314.33 1.8E+04 1.1E+04 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 64.02 <0.0001 314.33 1.8E+04 1.1E+04 nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 3.63 0.30 255.94 5.3E+01 3.3E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 2.58 0.28 256.88 5.8E+02 3.6E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) d 2 <0.0001 2.58 0.28 256.88 5.8E+02 3.6E+01 nonconstant variance, power unrestricted

Hill 3 <.0001 16.10 0.00 268.40 1.7E-05 1.7E-05 nonconstant variance, n restricted >1

Hill d 3 <.0001 16.10 0.00 268.40 1.7E-05 1.7E-05 nonconstant variance, n unrestricted

linear 4 <.0001 62.93 <.0001 313.23 1.5E+04 6.9E+03 nonconstant variance

polynomial 5 <.0001 81.88 <.0001 330.18 error 2.0E+03 nonconstant variance

power 4 <.0001 62.93 <.0001 313.23 1.5E+04 6.9E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 8.76 0.03 261.07 1.1E-04 1.1E-04 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 39.91 <0.0001 316.45 1.1E+04 8.8E+03 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 39.91 <0.0001 316.45 1.1E+04 8.8E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 3.69 0.30 282.22 4.0E+02 2.4E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 2.71 0.26 283.24 1.1E+03 2.7E+02 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 2.71 0.26 283.24 1.1E+03 2.7E+02 constant variance, power unrestricted

Hill 3 <.0001 2.71 0.44 281.24 1.2E+03 1.6E+02 constant variance, n restricted >1, bound hit

Hill 3 <.0001 2.71 0.44 281.24 1.2E+03 3.8E+01 constant variance, n unrestricted

linear 4 <.0001 36.71 <.0001 313.25 8.3E+03 5.9E+03 constant variance

polynomial 4 <.0001 36.71 <.0001 313.25 8.3E+03 5.9E+03 constant variance

power 4 <.0001 36.71 <.0001 313.25 8.3E+03 5.9E+03 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-78 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 3 <.0001 6.08 0.11 284.61 2.8E+00 9.6E-05 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.2.7.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:27 11/20 2009 BMD BMDL Exponential



## 5 6 7 H.2.7.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_Lung_EROD_wk53.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 12:27:08 2009 

## 16

==================================================================== 

## 17 18 Tbl 12, Week 53, Lung Microsomes EROD 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-79 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 6 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 4 

## 32

-------- -------- 

## 33 lnalpha -0.80064 

## 34
rho 1.47683 

## 35
a 2.86045 

## 36
b 0.000243673 

## 37
c 16.0581 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 4 

## 45

-------- ------- 

## 46 lnalpha -1.14118 

## 47
rho 1.62714 

## 48
a 3.06882 

## 49
b 0.000715169 

## 50
c 13.702 

## 51
d 3.78652 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 8 3.011 1.584 

## 59
1354 8 27.15 5.269 

## 60
3056 8 42.85 11.15 

## 61
5259 8 36.57 12.99 

## 62
8918 8 43.75 18.55 

## 63
1.6e+004 8 43.71 6.322 

## 64 65 66
Estimated Values of Interest 

## 67 68
Dose Est Mean Est Std Scaled Residual 

## 69

------ ---------- --------- ---------------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-80 0 3.061 1.408 -0.1008 

## 1
1354 27.14 8.377 0.001867 

## 2
3056 38.19 11.07 1.191 

## 3
5259 42.16 12.01 -1.317 

## 4
8918 43.23 12.25 0.1192 

## 5
1.6e+004 43.33 12.28 0.08869 

## 6 7 8 9
Other models for which likelihoods are calculated: 

## 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Model R: Yij = Mu + e(i) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) DF AIC 

## 27

------- ----------------- ---- ------------ 

## 28
A1 -135.2677 7 284.5353 

## 29
A2 -115.6885 12 255.3771 

## 30
A3 -121.1517 8 258.3034 

## 31
R -162.0902 2 328.1805 

## 32
4 -122.9684 5 255.9369 

## 33 34 35 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 36 above values gives the log-likelihood including the term that does not 

## 37 depend on the model parameters. 

## 38 39 40 Explanation of Tests 

## 41 42 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 43 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 44 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 45 46 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 47 48 49
Tests of Interest 

## 50 51 Test -2*log(Likelihood Ratio) D. F. p-value 

## 52

-------- ------------------------ ------ -------------- 

## 53
Test 1 92.8 10 < 0.0001 

## 54
Test 2 39.16 5 < 0.0001 

## 55
Test 3 10.93 4 0.0274 

## 56
Test 6a 3.633 3 0.3039 

## 57 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose 

## 61 levels, it seems appropriate to model the data. 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous 

## 64 variance model appears to be appropriate. 

## 65 66 The p-value for Test 3 is less than .1. You may want to 

## 67
consider a different variance model. 

## 68 69 The p-value for Test 6a is greater than .1. Model 4 seems 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-81 to adequately describe the data. 

## 1 2 3 Benchmark Dose Computations: 

## 4 5 Specified Effect = 1.000000 

## 6 7 Risk Type = Estimated standard deviations from control 

## 8 9
Confidence Level = 0.950000 

## 10 11
BMD = 52.8515 

## 12 13
BMDL = 32.5706 

## 14 15 16 17 H.2.7.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 18 Unrestricted 19

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:27 11/20 2009 BMD BMDL Exponential



## 20 21 22 H.2.7.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 23 Power Unrestricted 24 25 26

==================================================================== 

## 27 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 28 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_Lung_EROD_wk53.(d) 

## 29 Gnuplot Plotting File: 

## 30
Fri Nov 20 12:27:17 2009 

## 31

==================================================================== 

## 32 33 Tbl 12, Week 53, Lung Microsomes EROD 

## 34

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-82 The form of the response function by Model: 

## 1 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 2 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 3 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 4 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 5 6 Note: Y[dose] is the median response for exposure = dose; 

## 7 sign = +1 for increasing trend in data; 

## 8 sign = -1 for decreasing trend. 

## 9 10
Model 2 is nested within Models 3 and 4. 

## 11
Model 3 is nested within Model 5. 

## 12
Model 4 is nested within Model 5. 

## 13 14 15 Dependent variable = Mean 

## 16 Independent variable = Dose 

## 17 Data are assumed to be distributed: normally 

## 18 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 19 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 5 

## 33

-------- -------- 

## 34 lnalpha -0.80064 

## 35
rho 1.47683 

## 36
a 2.86045 

## 37
b 0.000243673 

## 38
c 16.0581 

## 39
d 1 

## 40 41 42 43
Parameter Estimates 

## 44 45
Variable Model 5 

## 46

-------- ------- 

## 47 lnalpha -1.14118 

## 48
rho 1.62714 

## 49
a 3.06882 

## 50
b 0.000715169 

## 51
c 13.702 

## 52
d 3.78652 

## 53 54 55 Table of Stats From Input Data 

## 56 57
Dose N Obs Mean Obs Std Dev 

## 58

----- --- ---------- ------------- 

## 59
0 8 3.011 1.584 

## 60
1354 8 27.15 5.269 

## 61
3056 8 42.85 11.15 

## 62
5259 8 36.57 12.99 

## 63
8918 8 43.75 18.55 

## 64
1.6e+004 8 43.71 6.322 

## 65 66 67
Estimated Values of Interest 

## 68 69
Dose Est Mean Est Std Scaled Residual 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-83 ------ ---------- --------- ---------------- 

## 1
0 3.069 1.407 -0.1162 

## 2
1354 25.95 7.993 0.4234 

## 3
3056 42.05 11.84 0.1907 

## 4
5259 42.05 11.84 -1.309 

## 5
8918 42.05 11.84 0.4055 

## 6
1.6e+004 42.05 11.84 0.3976 

## 7 8 9 10
Other models for which likelihoods are calculated: 

## 11 12 Model A1: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma^2 

## 14 15 Model A2: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma(i)^2 

## 17 18 Model A3: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Model R: Yij = Mu + e(i) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) DF AIC 

## 28

------- ----------------- ---- ------------ 

## 29
A1 -135.2677 7 284.5353 

## 30
A2 -115.6885 12 255.3771 

## 31
A3 -121.1517 8 258.3034 

## 32
R -162.0902 2 328.1805 

## 33
5 -122.4411 6 256.8821 

## 34 35 36 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 37 above values gives the log-likelihood including the term that does not 

## 38 depend on the model parameters. 

## 39 40 41 Explanation of Tests 

## 42 43 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 44 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 45 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 46 47 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 48 49 50
Tests of Interest 

## 51 52 Test -2*log(Likelihood Ratio) D. F. p-value 

## 53

-------- ------------------------ ------ -------------- 

## 54
Test 1 92.8 10 < 0.0001 

## 55
Test 2 39.16 5 < 0.0001 

## 56
Test 3 10.93 4 0.0274 

## 57
Test 7a 2.579 2 0.2755 

## 58 59 60 The p-value for Test 1 is less than .05. There appears to be a 

## 61 difference between response and/or variances among the dose 

## 62 levels, it seems appropriate to model the data. 

## 63 64 The p-value for Test 2 is less than .1. A non-homogeneous 

## 65 variance model appears to be appropriate. 

## 66 67 The p-value for Test 3 is less than .1. You may want to 

## 68
consider a different variance model. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-84 The p-value for Test 7a is greater than .1. Model 5 seems 

## 1 to adequately describe the data. 

## 2 3 4 Benchmark Dose Computations: 

## 5 6 Specified Effect = 1.000000 

## 7 8 Risk Type = Estimated standard deviations from control 

## 9 10
Confidence Level = 0.950000 

## 11 12
BMD = 584.449 

## 13 14
BMDL = 36.2497 

## 15 16 17 18 H.2.7.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 19

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Hill Model with 0.95 Confidence Level

12:27 11/20 2009 BMDBMDL Hill



## 20 21 22 H.2.7.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 23 24 25

==================================================================== 

## 26 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 27 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_Lung_EROD_wk53.(d) 

## 28 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_Lung_EROD_wk53.plt 

## 29
Fri Nov 20 12:27:19 2009 

## 30

==================================================================== 

## 31 32 Tbl 12, Week 53, Lung Microsomes EROD 

## 33

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 34 35 The form of the response function is: 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-85 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 1 2 3 Dependent variable = Mean 

## 4 Independent variable = Dose 

## 5 Power parameter is not restricted 

## 6 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 7 8 Total number of dose groups = 6 

## 9 Total number of records with missing values = 0 

## 10
Maximum number of iterations = 250 

## 11 Relative Function Convergence has been set to: 1e-008 

## 12 Parameter Convergence has been set to: 1e-008 

## 13 14 15 16
Default Initial Parameter Values 

## 17 lalpha = 4.76968 

## 18
rho = 0 

## 19 intercept = 3.011 

## 20
v = 40.735 

## 21
n = 2.49974 

## 22
k = 1565.11 

## 23 24 25 Asymptotic Correlation Matrix of Parameter Estimates 

## 26 27 ( *** The model parameter(s) -k 

## 28 have been estimated at a boundary point, or have been specified by the user, 

## 29 and do not appear in the correlation matrix ) 

## 30 31 lalpha rho intercept v n 

## 32 33 lalpha 1 -0.96 -0.5 0.17 NA 

## 34 35
rho -0.96 1 0.47 -0.25 NA 

## 36 37 intercept -0.5 0.47 1 -0.25 NA 

## 38 39
v 0.17 -0.25 -0.25 1 NA 

## 40 41

n NA NA NA NA NA 

## 42 43 44 NA - This parameter's variance has been estimated as zero or less. 

## 45
THE MODEL HAS PROBABLY NOT CONVERGED!!! 

## 46 47 48 49
Parameter Estimates 

## 50 51
95.0% Wald Confidence Interval 

## 52 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 53 lalpha -1.07501 NA NA NA 

## 54
rho 1.68859 NA NA NA 

## 55 intercept 3.011 NA NA NA 

## 56
v 35.7938 NA NA NA 

## 57
n 5.85653 NA NA NA 

## 58
k 2.91999e-005 NA 

## 59 60 At least some variance estimates are negative. 

## 61
THIS USUALLY MEANS THE MODEL HAS NOT CONVERGED! 

## 62 Try again from another starting point. 

## 63 64 65 66
Table of Data and Estimated Values of Interest 

## 67 68
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 69

------ --- -------- -------- ----------- ----------- ---------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-86 1
0 8 3.01 3.01 1.58 1.48 -2.78e-009 

## 2
1354 8 27.1 38.8 5.27 12.8 -2.57 

## 3
3056 8 42.8 38.8 11.2 12.8 0.891 

## 4
5259 8 36.6 38.8 13 12.8 -0.493 

## 5
8918 8 43.7 38.8 18.5 12.8 1.09 

## 6
1.6e+004 8 43.7 38.8 6.32 12.8 1.08 

## 7 8 9 10 Model Descriptions for likelihoods calculated 

## 11 12 13 Model A1: Yij = Mu(i) + e(ij) 

## 14 Var{e(ij)} = Sigma^2 

## 15 16 Model A2: Yij = Mu(i) + e(ij) 

## 17 Var{e(ij)} = Sigma(i)^2 

## 18 19 Model A3: Yij = Mu(i) + e(ij) 

## 20 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 21 Model A3 uses any fixed variance parameters that 

## 22 were specified by the user 

## 23 24 Model R: Yi = Mu + e(i) 

## 25 Var{e(i)} = Sigma^2 

## 26 27 28
Likelihoods of Interest 

## 29 30 Model Log(likelihood) # Param's AIC 

## 31
A1 -135.267662 7 284.535325 

## 32
A2 -115.688533 12 255.377067 

## 33
A3 -121.151707 8 258.303413 

## 34
fitted -129.200555 5 268.401110 

## 35
R -162.090242 2 328.180484 

## 36 37 38 Explanation of Tests 

## 39 40 Test 1: Do responses and/or variances differ among Dose levels? 

## 41 (A2 vs. R) 

## 42 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 43 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 44 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 45 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 46 47
Tests of Interest 

## 48 49 Test -2*log(Likelihood Ratio) Test df p-value 

## 50 51
Test 1 92.8034 10 <.0001 

## 52
Test 2 39.1583 5 <.0001 

## 53
Test 3 10.9263 4 0.0274 

## 54
Test 4 16.0977 3 0.001083 

## 55 56 The p-value for Test 1 is less than .05. There appears to be a 

## 57 difference between response and/or variances among the dose levels 

## 58 It seems appropriate to model the data 

## 59 60 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 61 model appears to be appropriate 

## 62 63 The p-value for Test 3 is less than .1. You may want to consider a 

## 64
different variance model 

## 65 66 The p-value for Test 4 is less than .1. You may want to try a different 

## 67
model 

## 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-87 Benchmark Dose Computation 

## 1 2 Specified effect = 1 

## 3 4 Risk Type = Estimated standard deviations from the control mean 

## 5 6
Confidence level = 0.95 

## 7 8
BMD = 1.70749e-005 

## 9 10
BMDL = 1.70749e-005 

## 11 12 13 14 H.2.7.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 15

0 10 20 30 40 50 60

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Power Model with 0.95 Confidence Level

12:27 11/20 2009 BMDBMDL Power



## 16 17 18 H.2.7.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 19 Unrestricted 20 21 22

==================================================================== 

## 23 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 24 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_Lung_EROD_wk53.(d) 

## 25 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_Lung_EROD_wk53.plt 

## 26
Fri Nov 20 12:27:20 2009 

## 27

==================================================================== 

## 28 29 Tbl 12, Week 53, Lung Microsomes EROD 

## 30

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 31 32 The form of the response function is: 

## 33 34 Y[dose] = control + slope * dose^power 

## 35 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-88 Dependent variable = Mean 

## 1 Independent variable = Dose 

## 2 The power is not restricted 

## 3 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 4 5 Total number of dose groups = 6 

## 6 Total number of records with missing values = 0 

## 7 Maximum number of iterations = 250 

## 8 Relative Function Convergence has been set to: 1e-008 

## 9 Parameter Convergence has been set to: 1e-008 

## 10 11 12 13
Default Initial Parameter Values 

## 14 lalpha = 4.76968 

## 15
rho = 0 

## 16
control = 3.011 

## 17 slope = 7.10636 

## 18 power = 0.187655 

## 19 20 21 Asymptotic Correlation Matrix of Parameter Estimates 

## 22 23 lalpha rho control slope power 

## 24 25 lalpha 1 -0.96 -0.49 0.062 -0.046 

## 26 27
rho -0.96 1 0.45 -0.074 0.051 

## 28 29
control -0.49 0.45 1 -0.075 0.049 

## 30 31 slope 0.062 -0.074 -0.075 1 -1 

## 32 33 power -0.046 0.051 0.049 -1 1 

## 34 35 36 37
Parameter Estimates 

## 38 39
95.0% Wald Confidence Interval 

## 40 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 41 lalpha -1.02691 0.818371 -2.63089 0.577065 

## 42
rho 1.6303 0.240525 1.15888 2.10172 

## 43
control 3.01554 0.519298 1.99773 4.03334 

## 44 slope 7.64061 4.22038 -0.631172 15.9124 

## 45 power 0.18001 0.0639858 0.0546001 0.30542 

## 46 47 48 49
Table of Data and Estimated Values of Interest 

## 50 51
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 52

------ --- -------- -------- ----------- ----------- ---------- 

## 53 54
0 8 3.01 3.02 1.58 1.47 -0.00872 

## 55
1354 8 27.1 31 5.27 9.83 -1.11 

## 56
3056 8 42.8 35.4 11.2 11 1.92 

## 57
5259 8 36.6 38.7 13 11.8 -0.52 

## 58
8918 8 43.7 42.3 18.5 12.7 0.323 

## 59
1.6e+004 8 43.7 46.7 6.32 13.7 -0.607 

## 60 61 62 63 Model Descriptions for likelihoods calculated 

## 64 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-89 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 4 Model A3 uses any fixed variance parameters that 

## 5 were specified by the user 

## 6 7 Model R: Yi = Mu + e(i) 

## 8 Var{e(i)} = Sigma^2 

## 9 10 11
Likelihoods of Interest 

## 12 13 Model Log(likelihood) # Param's AIC 

## 14
A1 -135.267662 7 284.535325 

## 15
A2 -115.688533 12 255.377067 

## 16
A3 -121.151707 8 258.303413 

## 17
fitted -125.533162 5 261.066325 

## 18
R -162.090242 2 328.180484 

## 19 20 21 Explanation of Tests 

## 22 23 Test 1: Do responses and/or variances differ among Dose levels? 

## 24 (A2 vs. R) 

## 25 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 27 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 28 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 29 30
Tests of Interest 

## 31 32 Test -2*log(Likelihood Ratio) Test df p-value 

## 33 34
Test 1 92.8034 10 <.0001 

## 35
Test 2 39.1583 5 <.0001 

## 36
Test 3 10.9263 4 0.0274 

## 37
Test 4 8.76291 3 0.03261 

## 38 39 The p-value for Test 1 is less than .05. There appears to be a 

## 40 difference between response and/or variances among the dose levels 

## 41 It seems appropriate to model the data 

## 42 43 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 44 model appears to be appropriate 

## 45 46 The p-value for Test 3 is less than .1. You may want to consider a 

## 47
different variance model 

## 48 49 The p-value for Test 4 is less than .1. You may want to try a different 

## 50
model 

## 51 52 53 Benchmark Dose Computation 

## 54 55 Specified effect = 1 

## 56 57 Risk Type = Estimated standard deviations from the control mean 

## 58 59
Confidence level = 0.95 

## 60 61
BMD = 0.000106161 

## 62 63 64
BMDL = 0.000106161 

## 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-90 H.2.8. National Toxicology Program. ( 2006): Tbl11 Index Week 31 1
H.2.8.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) c 4 <0.0001 20.59 0.00 46.55 4.8E+03 3.8E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 20.59 0.00 46.55 4.8E+03 3.8E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 23.01 <0.0001 50.97 1.7E+03 1.0E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 23.01 <0.0001 50.97 1.7E+03 1.0E+03 nonconstant variance, power restricted ≥ 1

Hill 3 <0.0001 23.01 <0.0001 50.97 1.7E+03 error nonconstant variance, n restricted >1, bound hit

linear 4 <0.0001 23.01 0.00 48.97 1.7E+03 1.0E+03 nonconstant variance

polynomial 3 <0.0001 22.24 <.0001 50.20 3.4E+03 1.1E+03 nonconstant variance

power 4 <0.0001 23.01 0.00 48.97 1.7E+03 1.0E+03 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 4 <0.0001 1.20 0.88 101.67 1.0E+04 9.0E+03 constant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 0.97 0.81 103.44 1.1E+04 9.0E+03 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 5.31 0.15 107.78 6.8E+03 5.2E+03 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 1.08 0.58 105.55 1.1E+04 7.5E+03 constant variance, power restricted ≥ 1

Hill 2 <0.0001 1.08 0.58 105.55 1.1E+04 7.5E+03 constant variance, n restricted >1

linear 4 <0.0001 5.31 0.26 105.78 6.8E+03 5.2E+03 constant variance

polynomial 4 <0.0001 1.44 0.84 101.91 1.0E+04 8.9E+03 constant variance

power 3 <0.0001 1.08 0.78 103.55 1.1E+04 7.5E+03 constant variance, power restricted ≥ 1

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 

## 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-91 H.2.8.2. Figure for Selected Model: Exponen tial (M2), Nonconstant Variance, Power 1 Restricted ≥ 1 2

0 1 2 3 4 5 6

0 2000 4000 6000 8000 10000 12000 14000 16000Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

11:23 11/19 2009 BMD BMDL Exponential



## 3 4 5 H.2.8.3. Output File for Selected Model: Expo nential (M2), Nonconstant Varian ce, Power 6 Restricted ≥ 1 7 8 9

==================================================================== 

## 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_BMR1_Tbl11_31wk.(d) 

## 12 Gnuplot Plotting File: 

## 13
Thu Nov 19 11:23:48 2009 

## 14

==================================================================== 

## 15 16 Tbl 11, 31wk, Hep Cell Proliferation Labeling Index 

## 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 18 19 The form of the response function by Model: 

## 20 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 24 25 Note: Y[dose] is the median response for exposure = dose; 

## 26 sign = +1 for increasing trend in data; 

## 27 sign = -1 for decreasing trend. 

## 28 29
Model 2 is nested within Models 3 and 4. 

## 30
Model 3 is nested within Model 5. 

## 31
Model 4 is nested within Model 5. 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Data are assumed to be distributed: normally 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-92 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 1 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 2 3 Total number of dose groups = 6 

## 4 Total number of records with missing values = 0 

## 5 Maximum number of iterations = 250 

## 6 Relative Function Convergence has been set to: 1e-008 

## 7 Parameter Convergence has been set to: 1e-008 

## 8 9 MLE solution provided: Exact 

## 10 11 12
Initial Parameter Values 

## 13 14
Variable Model 2 

## 15

-------- -------- 

## 16 lnalpha -0.674004 

## 17
rho 2.29189 

## 18
a 0.31065 

## 19
b 3.44963e-005 

## 20
c 24.761 

## 21
d 1 

## 22 23 24 25
Parameter Estimates 

## 26 27
Variable Model 2 

## 28

-------- ------- 

## 29 lnalpha -0.467457 

## 30
rho 2.1664 

## 31
a 0.394038 

## 32
b 5.38146e-009 

## 33
c 78344.1 

## 34
d 1 

## 35 36 37 Table of Stats From Input Data 

## 38 39
Dose N Obs Mean Obs Std Dev 

## 40

----- --- ---------- ------------- 

## 41
0 9 0.327 0.189 

## 42
1284 10 0.852 0.6514 

## 43
2932 10 0.956 0.7368 

## 44
5075 10 0.792 0.4617 

## 45
8629 10 1.333 1.123 

## 46
1.55e+004 10 3.846 3.08 

## 47 48 49
Estimated Values of Interest 

## 50 51
Dose Est Mean Est Std Scaled Residual 

## 52

------ ---------- --------- ---------------- 

## 53
0 0.5305 0.4275 -1.428 

## 54
1284 0.6219 0.4983 1.46 

## 55
2932 0.7627 0.6067 1.007 

## 56
5075 0.9946 0.7837 -0.8176 

## 57
8629 1.545 1.198 -0.5587 

## 58
1.55e+004 3.619 2.722 0.2635 

## 59 60 61 62
Other models for which likelihoods are calculated: 

## 63 64 Model A1: Yij = Mu(i) + e(ij) 

## 65 Var{e(ij)} = Sigma^2 

## 66 67 Model A2: Yij = Mu(i) + e(ij) 

## 68 Var{e(ij)} = Sigma(i)^2 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-93 Model A3: Yij = Mu(i) + e(ij) 

## 1 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 2 3 Model R: Yij = Mu + e(i) 

## 4 Var{e(ij)} = Sigma^2 

## 5 6 7 Likelihoods of Interest 

## 8 9 Model Log(likelihood) DF AIC 

## 10

------- ----------------- ---- ------------ 

## 11
A1 -47.23498 7 108.47 

## 12
A2 -8.679256 12 41.35851 

## 13
A3 -8.980651 8 33.9613 

## 14
R -63.44829 2 130.8966 

## 15
2 -19.27346 4 46.54692 

## 16 17 18 Additive constant for all log-likelihoods = -54.22. This constant added to the 

## 19 above values gives the log-likelihood including the term that does not 

## 20 depend on the model parameters. 

## 21 22 23 Explanation of Tests 

## 24 25 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 26 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 27 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 28 Test 4: Does Model 2 fit the data? (A3 vs. 2) 

## 29 30 31
Tests of Interest 

## 32 33 Test -2*log(Likelihood Ratio) D. F. p-value 

## 34

-------- ------------------------ ------ -------------- 

## 35
Test 1 109.5 10 < 0.0001 

## 36
Test 2 77.11 5 < 0.0001 

## 37
Test 3 0.6028 4 0.9628 

## 38
Test 4 20.59 4 0.0003826 

## 39 40 41 The p-value for Test 1 is less than .05. There appears to be a 

## 42 difference between response and/or variances among the dose 

## 43 levels, it seems appropriate to model the data. 

## 44 45 The p-value for Test 2 is less than .1. A non-homogeneous 

## 46 variance model appears to be appropriate. 

## 47 48 The p-value for Test 3 is greater than .1. The modeled 

## 49 variance appears to be appropriate here. 

## 50 51 The p-value for Test 4 is less than .1. Model 2 may not adequately 

## 52 describe the data; you may want to consider another model. 

## 53 54 55 Benchmark Dose Computations: 

## 56 57 Specified Effect = 1.000000 

## 58 59 Risk Type = Estimated standard deviations from control 

## 60 61
Confidence Level = 0.950000 

## 62 63
BMD = 4772.05 

## 64 65
BMDL = 3816.47 

## 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-94 H.2.9. Van Birgelen et al. (1995b): T4 UGT 1
H.2.9.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 33.51 <0.0001 36.92 6.3E+04 4.4E+04 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 33.51 <0.0001 36.92 6.3E+04 4.4E+04 nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 1.50 0.68 6.90 2.7E+03 1.5E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 1.14 0.57 8.55 3.5E+03 1.6E+03 nonconstant variance, power restricted ≥ 1
exponential (M5) d 2 <0.0001 1.14 0.57 8.55 3.5E+03 1.6E+03 nonconstant variance, power unrestricted

Hill 2 <.0001 1.22 0.54 8.63 3.7E+03 1.7E+03 nonconstant variance, n restricted >1

Hill d 2 <.0001 1.22 0.54 8.63 3.7E+03 1.5E+03 nonconstant variance, n unrestricted

linear 4 <.0001 19.72 0.00 23.13 1.8E+04 9.1E+03 nonconstant variance

polynomial 4 <.0001 19.72 0.00 23.13 1.8E+04 9.1E+03 nonconstant variance

power 4 <.0001 19.72 0.00 23.13 1.8E+04 9.1E+03 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 6.02 0.11 11.42 1.3E+03 2.1E+02 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 13.46 0.01 38.87 8.2E+04 6.9E+04 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 13.46 0.01 38.87 8.2E+04 6.9E+04 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 0.11 0.99 27.51 1.3E+04 6.7E+03 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 0.07 0.97 29.47 1.5E+04 6.8E+03 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 0.07 0.97 29.47 1.5E+04 6.8E+03 constant variance, power unrestricted

Hill 2 <.0001 0.10 0.95 29.50 1.4E+04 5.6E+03 constant variance, n restricted >1

Hill 2 <.0001 0.10 0.95 29.50 1.4E+04 5.1E+03 constant variance, n unrestricted

linear 4 <.0001 8.58 0.07 33.98 5.1E+04 3.9E+04 constant variance

polynomial 4 <.0001 8.58 0.07 33.98 5.1E+04 3.9E+04 constant variance

power 4 <.0001 8.58 0.07 33.98 5.1E+04 3.9E+04 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-95 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 3 <.0001 2.70 0.44 30.10 1.1E+04 2.6E+03 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.2.9.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 0.5

1 1.5

2 2.5

3 3.5

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:32 11/20 2009 BMD BMDL Exponential



## 5 6 7 H.2.9.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_T4_UGT.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 12:32:06 2009 

## 16

==================================================================== 

## 17 18 Tbl2, T4 UGT 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-96 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 6 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 4 

## 32

-------- -------- 

## 33 lnalpha -0.937573 

## 34
rho 1.54913 

## 35
a 0.3135 

## 36
b 2.19381e-005 

## 37
c 8.67464 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 4 

## 45

-------- ------- 

## 46 lnalpha -0.934825 

## 47
rho 1.69365 

## 48
a 0.293644 

## 49
b 5.48685e-005 

## 50
c 7.66316 

## 51
d 1.27403 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 8 0.33 0.198 

## 59
3969 8 0.6 0.4243 

## 60
6479 8 0.64 0.4525 

## 61
9968 8 0.87 0.9051 

## 62
4.761e+004 8 2.08 1.329 

## 63
1.378e+005 8 2.59 0.8768 

## 64 65 66
Estimated Values of Interest 

## 67 68
Dose Est Mean Est Std Scaled Residual 

## 69

------ ---------- --------- ---------------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-97 0 0.2841 0.2186 0.594 

## 1
3969 0.5945 0.4063 0.03836 

## 2
6479 0.7663 0.5029 -0.7106 

## 3
9968 0.9778 0.6171 -0.4939 

## 4
4.761e+004 2.062 1.155 0.04516 

## 5
1.378e+005 2.351 1.289 0.5245 

## 6 7 8 9
Other models for which likelihoods are calculated: 

## 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Model R: Yij = Mu + e(i) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) DF AIC 

## 27

------- ----------------- ---- ------------ 

## 28
A1 -9.701316 7 33.40263 

## 29
A2 4.934967 12 14.13007 

## 30
A3 2.296438 8 11.40712 

## 31
R -29.51921 2 63.03841 

## 32
4 1.548351 5 6.903297 

## 33 34 35 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 36 above values gives the log-likelihood including the term that does not 

## 37 depend on the model parameters. 

## 38 39 40 Explanation of Tests 

## 41 42 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 43 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 44 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 45 46 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 47 48 49
Tests of Interest 

## 50 51 Test -2*log(Likelihood Ratio) D. F. p-value 

## 52

-------- ------------------------ ------ -------------- 

## 53
Test 1 68.91 10 < 0.0001 

## 54
Test 2 29.27 5 < 0.0001 

## 55
Test 3 5.277 4 0.26 

## 56
Test 6a 1.496 3 0.6832 

## 57 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose 

## 61 levels, it seems appropriate to model the data. 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous 

## 64 variance model appears to be appropriate. 

## 65 66 The p-value for Test 3 is greater than .1. The modeled 

## 67 variance appears to be appropriate here. 

## 68 69 The p-value for Test 6a is greater than .1. Model 4 seems 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-98 to adequately describe the data. 

## 1 2 3 Benchmark Dose Computations: 

## 4 5 Specified Effect = 1.000000 

## 6 7 Risk Type = Estimated standard deviations from control 

## 8 9
Confidence Level = 0.950000 

## 10 11
BMD = 2726.3 

## 12 13
BMDL = 1491.73 

## 14 15 16 17 H.2.9.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 18 Unrestricted 19

0 0.5

1 1.5

2 2.5

3 3.5

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:32 11/20 2009 BMD BMDL Exponential



## 20 21 22 H.2.9.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 23 Power Unrestricted 24 25 26

==================================================================== 

## 27 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 28 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_T4_UGT.(d) 

## 29 Gnuplot Plotting File: 

## 30
Fri Nov 20 12:32:13 2009 

## 31

==================================================================== 

## 32 33 Tbl2, T4 UGT 

## 34

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-99 The form of the response function by Model: 

## 1 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 2 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 3 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 4 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 5 6 Note: Y[dose] is the median response for exposure = dose; 

## 7 sign = +1 for increasing trend in data; 

## 8 sign = -1 for decreasing trend. 

## 9 10
Model 2 is nested within Models 3 and 4. 

## 11
Model 3 is nested within Model 5. 

## 12
Model 4 is nested within Model 5. 

## 13 14 15 Dependent variable = Mean 

## 16 Independent variable = Dose 

## 17 Data are assumed to be distributed: normally 

## 18 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 19 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 5 

## 33

-------- -------- 

## 34 lnalpha -0.937573 

## 35
rho 1.54913 

## 36
a 0.3135 

## 37
b 2.19381e-005 

## 38
c 8.67464 

## 39
d 1 

## 40 41 42 43
Parameter Estimates 

## 44 45
Variable Model 5 

## 46

-------- ------- 

## 47 lnalpha -0.934825 

## 48
rho 1.69365 

## 49
a 0.293644 

## 50
b 5.48685e-005 

## 51
c 7.66316 

## 52
d 1.27403 

## 53 54 55 Table of Stats From Input Data 

## 56 57
Dose N Obs Mean Obs Std Dev 

## 58

----- --- ---------- ------------- 

## 59
0 8 0.33 0.198 

## 60
3969 8 0.6 0.4243 

## 61
6479 8 0.64 0.4525 

## 62
9968 8 0.87 0.9051 

## 63
4.761e+004 8 2.08 1.329 

## 64
1.378e+005 8 2.59 0.8768 

## 65 66 67
Estimated Values of Interest 

## 68 69
Dose Est Mean Est Std Scaled Residual 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-100 ------ ---------- --------- ---------------- 

## 1
0 0.2936 0.222 0.4632 

## 2
3969 0.555 0.3806 0.334 

## 3
6479 0.7533 0.4929 -0.6498 

## 4
9968 1.019 0.6369 -0.6636 

## 5
4.761e+004 2.185 1.215 -0.2441 

## 6
1.378e+005 2.25 1.245 0.7717 

## 7 8 9 10
Other models for which likelihoods are calculated: 

## 11 12 Model A1: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma^2 

## 14 15 Model A2: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma(i)^2 

## 17 18 Model A3: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Model R: Yij = Mu + e(i) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) DF AIC 

## 28

------- ----------------- ---- ------------ 

## 29
A1 -9.701316 7 33.40263 

## 30
A2 4.934967 12 14.13007 

## 31
A3 2.296438 8 11.40712 

## 32
R -29.51921 2 63.03841 

## 33
5 1.725713 6 8.548574 

## 34 35 36 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 37 above values gives the log-likelihood including the term that does not 

## 38 depend on the model parameters. 

## 39 40 41 Explanation of Tests 

## 42 43 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 44 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 45 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 46 47 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 48 49 50
Tests of Interest 

## 51 52 Test -2*log(Likelihood Ratio) D. F. p-value 

## 53

-------- ------------------------ ------ -------------- 

## 54
Test 1 68.91 10 < 0.0001 

## 55
Test 2 29.27 5 < 0.0001 

## 56
Test 3 5.277 4 0.26 

## 57
Test 7a 1.141 2 0.5651 

## 58 59 60 The p-value for Test 1 is less than .05. There appears to be a 

## 61 difference between response and/or variances among the dose 

## 62 levels, it seems appropriate to model the data. 

## 63 64 The p-value for Test 2 is less than .1. A non-homogeneous 

## 65 variance model appears to be appropriate. 

## 66 67 The p-value for Test 3 is greater than .1. The modeled 

## 68 variance appears to be appropriate here. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-101 The p-value for Test 7a is greater than .1. Model 5 seems 

## 1 to adequately describe the data. 

## 2 3 4 Benchmark Dose Computations: 

## 5 6 Specified Effect = 1.000000 

## 7 8 Risk Type = Estimated standard deviations from control 

## 9 10
Confidence Level = 0.950000 

## 11 12
BMD = 3460.45 

## 13 14
BMDL = 1550.03 

## 15 16 17 18 H.2.9.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 19

0 0.5

1 1.5

2 2.5

3 3.5

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Hill Model with 0.95 Confidence Level

12:32 11/20 2009 BMD BMDL Hill



## 20 21 22 H.2.9.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 23 24 25

==================================================================== 

## 26 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 27 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_T4_UGT.(d) 

## 28 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_T4_UGT.plt 

## 29
Fri Nov 20 12:32:14 2009 

## 30

==================================================================== 

## 31 32 Tbl2, T4 UGT 

## 33

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 34 35 The form of the response function is: 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-102 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 1 2 3 Dependent variable = Mean 

## 4 Independent variable = Dose 

## 5 Power parameter is not restricted 

## 6 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 7 8 Total number of dose groups = 6 

## 9 Total number of records with missing values = 0 

## 10
Maximum number of iterations = 250 

## 11 Relative Function Convergence has been set to: 1e-008 

## 12 Parameter Convergence has been set to: 1e-008 

## 13 14 15 16
Default Initial Parameter Values 

## 17 lalpha = -0.462247 

## 18
rho = 0 

## 19 intercept = 0.33 

## 20
v = 2.26 

## 21
n = 0.525864 

## 22
k = 66891.8 

## 23 24 25 Asymptotic Correlation Matrix of Parameter Estimates 

## 26 27 lalpha rho intercept v n k 

## 28 29 lalpha 1 0.035 -0.26 -0.18 -0.017 0.038 

## 30 31
rho 0.035 1 0.48 -0.49 0.023 -0.21 

## 32 33 intercept -0.26 0.48 1 -0.37 0.26 -0.14 

## 34 35
v -0.18 -0.49 -0.37 1 -0.59 0.77 

## 36 37
n -0.017 0.023 0.26 -0.59 1 -0.84 

## 38 39
k 0.038 -0.21 -0.14 0.77 -0.84 1 

## 40 41 42 43
Parameter Estimates 

## 44 45
95.0% Wald Confidence Interval 

## 46 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 47 lalpha -0.933225 0.25643 -1.43582 -0.430632 

## 48
rho 1.68188 0.441442 0.816665 2.54709 

## 49 intercept 0.294743 0.0705015 0.156563 0.432924 

## 50
v 2.10713 0.497534 1.13198 3.08228 

## 51
n 1.51694 0.601141 0.33872 2.69515 

## 52
k 14931.4 7059.91 1094.23 28768.6 

## 53 54 55 56
Table of Data and Estimated Values of Interest 

## 57 58
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 59

------ --- -------- -------- ----------- ----------- ---------- 

## 60 61
0 8 0.33 0.295 0.198 0.224 0.444 

## 62
3969 8 0.6 0.544 0.424 0.376 0.424 

## 63
6479 8 0.64 0.758 0.453 0.497 -0.672 

## 64
9968 8 0.87 1.04 0.905 0.646 -0.723 

## 65
4.761e+004 8 2.08 2.09 1.33 1.17 -0.0297 

## 66
1.378e+005 8 2.59 2.33 0.877 1.28 0.571 

## 67 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-103 Model Descriptions for likelihoods calculated 

## 1 2 3 Model A1: Yij = Mu(i) + e(ij) 

## 4 Var{e(ij)} = Sigma^2 

## 5 6 Model A2: Yij = Mu(i) + e(ij) 

## 7 Var{e(ij)} = Sigma(i)^2 

## 8 9 Model A3: Yij = Mu(i) + e(ij) 

## 10 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 11 Model A3 uses any fixed variance parameters that 

## 12 were specified by the user 

## 13 14 Model R: Yi = Mu + e(i) 

## 15 Var{e(i)} = Sigma^2 

## 16 17 18
Likelihoods of Interest 

## 19 20 Model Log(likelihood) # Param's AIC 

## 21
A1 -9.701316 7 33.402631 

## 22
A2 4.934967 12 14.130066 

## 23
A3 2.296438 8 11.407124 

## 24
fitted 1.684209 6 8.631582 

## 25
R -29.519205 2 63.038411 

## 26 27 28 Explanation of Tests 

## 29 30 Test 1: Do responses and/or variances differ among Dose levels? 

## 31 (A2 vs. R) 

## 32 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 33 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 34 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 35 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 36 37
Tests of Interest 

## 38 39 Test -2*log(Likelihood Ratio) Test df p-value 

## 40 41
Test 1 68.9083 10 <.0001 

## 42
Test 2 29.2726 5 <.0001 

## 43
Test 3 5.27706 4 0.26 

## 44
Test 4 1.22446 2 0.5421 

## 45 46 The p-value for Test 1 is less than .05. There appears to be a 

## 47 difference between response and/or variances among the dose levels 

## 48 It seems appropriate to model the data 

## 49 50 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 51 model appears to be appropriate 

## 52 53 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 54 to be appropriate here 

## 55 56 The p-value for Test 4 is greater than .1. The model chosen seems 

## 57 to adequately describe the data 

## 58 59 60 Benchmark Dose Computation 

## 61 62 Specified effect = 1 

## 63 64 Risk Type = Estimated standard deviations from the control mean 

## 65 66
Confidence level = 0.95 

## 67 68
BMD = 3674.98 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-104 BMDL = 1463.66 

## 1 2

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-105 H.2.9.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 0.5

1 1.5

2 2.5

3 3.5

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Power Model with 0.95 Confidence Level

12:32 11/20 2009 BMD BMDL Power



## 2 3 4 H.2.9.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 Unrestricted 6 7 8

==================================================================== 

## 9 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 10 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_T4_UGT.(d) 

## 11 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_T4_UGT.plt 

## 12
Fri Nov 20 12:32:14 2009 

## 13

==================================================================== 

## 14 15 Tbl2, T4 UGT 

## 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 17 18 The form of the response function is: 

## 19 20 Y[dose] = control + slope * dose^power 

## 21 22 23 Dependent variable = Mean 

## 24 Independent variable = Dose 

## 25 The power is not restricted 

## 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-106 lalpha = -0.462247 

## 1
rho = 0 

## 2
control = 0.33 

## 3 slope = 0.00102277 

## 4 power = 0.650735 

## 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 

## 8 9 lalpha rho control slope power 

## 10 11 lalpha 1 0.031 -0.26 -0.13 0.074 

## 12 13
rho 0.031 1 0.58 0.11 -0.18 

## 14 15
control -0.26 0.58 1 -0.13 0.067 

## 16 17 slope -0.13 0.11 -0.13 1 -0.99 

## 18 19 power 0.074 -0.18 0.067 -0.99 1 

## 20 21 22 23
Parameter Estimates 

## 24 25
95.0% Wald Confidence Interval 

## 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 27 lalpha -0.836884 0.261303 -1.34903 -0.324739 

## 28
rho 1.68473 0.453932 0.795038 2.57442 

## 29
control 0.2748 0.0676712 0.142167 0.407433 

## 30 slope 0.00549254 0.00532631 -0.00494685 0.0159319 

## 31 power 0.516485 0.0924979 0.335192 0.697777 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 8 0.33 0.275 0.198 0.222 0.704 

## 41
3969 8 0.6 0.671 0.424 0.471 -0.43 

## 42
6479 8 0.64 0.786 0.453 0.537 -0.767 

## 43
9968 8 0.87 0.913 0.905 0.61 -0.2 

## 44
4.761e+004 8 2.08 1.71 1.33 1.03 1.02 

## 45
1.378e+005 8 2.59 2.75 0.877 1.54 -0.299 

## 46 47 48 49 Model Descriptions for likelihoods calculated 

## 50 51 52 Model A1: Yij = Mu(i) + e(ij) 

## 53 Var{e(ij)} = Sigma^2 

## 54 55 Model A2: Yij = Mu(i) + e(ij) 

## 56 Var{e(ij)} = Sigma(i)^2 

## 57 58 Model A3: Yij = Mu(i) + e(ij) 

## 59 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 60 Model A3 uses any fixed variance parameters that 

## 61 were specified by the user 

## 62 63 Model R: Yi = Mu + e(i) 

## 64 Var{e(i)} = Sigma^2 

## 65 66 67
Likelihoods of Interest 

## 68 69 Model Log(likelihood) # Param's AIC 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-107 A1 -9.701316 7 33.402631 

## 1
A2 4.934967 12 14.130066 

## 2
A3 2.296438 8 11.407124 

## 3
fitted -0.712209 5 11.424417 

## 4
R -29.519205 2 63.038411 

## 5 6 7 Explanation of Tests 

## 8 9 Test 1: Do responses and/or variances differ among Dose levels? 

## 10 (A2 vs. R) 

## 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 15 16
Tests of Interest 

## 17 18 Test -2*log(Likelihood Ratio) Test df p-value 

## 19 20
Test 1 68.9083 10 <.0001 

## 21
Test 2 29.2726 5 <.0001 

## 22
Test 3 5.27706 4 0.26 

## 23
Test 4 6.01729 3 0.1108 

## 24 25 The p-value for Test 1 is less than .05. There appears to be a 

## 26 difference between response and/or variances among the dose levels 

## 27 It seems appropriate to model the data 

## 28 29 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 30 model appears to be appropriate 

## 31 32 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 33 to be appropriate here 

## 34 35 The p-value for Test 4 is greater than .1. The model chosen seems 

## 36 to adequately describe the data 

## 37 38 39 Benchmark Dose Computation 

## 40 41 Specified effect = 1 

## 42 43 Risk Type = Estimated standard deviations from the control mean 

## 44 45
Confidence level = 0.95 

## 46 47
BMD = 1286.41 

## 48 49 50
BMDL = 212.264 

## 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-108 H.2.10. Van Birgelen et al. (1995b): UGT 1A1 1
H.2.10.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 3 0.00 29.05 <0.0001 166.85 8.1E+04 2.4E+04 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.00 29.05 <0.0001 166.85 8.1E+04 2.4E+04 nonconstant variance, power restricted ≥ 1
exponential (M4) c 2 0.00 1.04 0.60 140.83 4.0E+02 2.2E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) 1 0.00 0.97 0.32 142.77 5.0E+02 2.2E+02 nonconstant variance, power restricted ≥ 1
exponential (M5) d 1 0.00 0.97 0.32 142.77 5.0E+02 2.2E+02 nonconstant variance, power unrestricted

Hill 1 0.00 1.27 0.26 143.07 8.2E+02 error nonconstant variance, n restricted >1

Hill d 1 0.00 1.27 0.26 143.07 8.2E+02 error nonconstant variance, n unrestricted

linear 3 0.00 26.47 <.0001 164.27 1.8E+04 5.3E+02 nonconstant variance

polynomial 3 0.00 31.07 <.0001 168.87 3.5E+05 4.9E+02 nonconstant variance

power 3 0.00 26.47 <.0001 164.27 1.8E+04 5.3E+02 nonconstant variance, power restricted ≥ 1, bound hit

power d 2 0.00 5.95 0.05 145.75 3.8E+00 2.3E-04 nonconstant variance, power unrestricted
exponential (M2) 3 0.00 22.21 <0.0001 165.71 1.6E+05 8.3E+04 constant variance, power restricted ≥ 1
exponential (M3) 3 0.00 22.21 <0.0001 165.71 1.6E+05 8.3E+04 constant variance, power restricted ≥ 1
exponential (M4) 2 0.00 8.05 0.02 153.55 2.6E+03 1.2E+03 constant variance, power restricted ≥ 1
exponential (M5) 1 0.00 7.88 0.00 155.38 3.3E+03 1.2E+03 constant variance, power restricted ≥ 1
exponential (M5) 1 0.00 7.88 0.00 155.38 3.3E+03 1.2E+03 constant variance, power unrestricted

Hill 1 0.00 8.12 0.00 155.61 3.7E+03 9.6E+02 constant variance, n restricted >1

Hill 1 0.00 8.12 0.00 155.61 3.7E+03 8.8E+02 constant variance, n unrestricted

linear 3 0.00 21.83 <.0001 165.32 1.3E+05 6.2E+04 constant variance

polynomial 3 0.00 21.83 <.0001 165.32 1.3E+05 6.2E+04 constant variance

power 3 0.00 21.83 <.0001 165.32 1.3E+05 6.2E+04 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-109 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 2 0.00 13.23 0.00 158.73 7.2E+01 1.6E-06 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 H.2.10.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 2 Restricted ≥ 1 3

-100 0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

12:43 11/20 2009 BMD BMDL Exponential



## 4 5 6 H.2.10.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 7 Restricted ≥ 1 8 9 10

==================================================================== 

## 11 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 12 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_BMR1_UGT_1A1.(d) 

## 13 Gnuplot Plotting File: 

## 14
Fri Nov 20 12:43:51 2009 

## 15

==================================================================== 

## 16 17 Tbl2, UGT_1A1 

## 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 19 20 The form of the response function by Model: 

## 21 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 22 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 23

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-110 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 1 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 2 3 Note: Y[dose] is the median response for exposure = dose; 

## 4 sign = +1 for increasing trend in data; 

## 5 sign = -1 for decreasing trend. 

## 6 7 Model 2 is nested within Models 3 and 4. 

## 8
Model 3 is nested within Model 5. 

## 9
Model 4 is nested within Model 5. 

## 10 11 12 Dependent variable = Mean 

## 13 Independent variable = Dose 

## 14 Data are assumed to be distributed: normally 

## 15 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 16 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 17 18 Total number of dose groups = 5 

## 19 Total number of records with missing values = 0 

## 20
Maximum number of iterations = 250 

## 21 Relative Function Convergence has been set to: 1e-008 

## 22 Parameter Convergence has been set to: 1e-008 

## 23 24 MLE solution provided: Exact 

## 25 26 27
Initial Parameter Values 

## 28 29
Variable Model 4 

## 30

-------- -------- 

## 31 lnalpha -1.53604 

## 32
rho 1.59958 

## 33
a 95.95 

## 34
b 1.15499e-005 

## 35
c 4.94633 

## 36
d 1 

## 37 38 39 40
Parameter Estimates 

## 41 42
Variable Model 4 

## 43

-------- ------- 

## 44 lnalpha -10.3642 

## 45
rho 3.29138 

## 46
a 101.591 

## 47
b 0.000102786 

## 48
c 3.84125 

## 49
d 1.08913 

## 50 51 52 Table of Stats From Input Data 

## 53 54
Dose N Obs Mean Obs Std Dev 

## 55

----- --- ---------- ------------- 

## 56
0 3 101 15.59 

## 57
3969 3 194 36.37 

## 58
9968 3 304 17.32 

## 59
4.761e+004 3 452 48.5 

## 60
1.378e+005 3 296 149 

## 61 62 63
Estimated Values of Interest 

## 64 65
Dose Est Mean Est Std Scaled Residual 

## 66

------ ---------- --------- ---------------- 

## 67
0 101.5 11.18 -0.07335 

## 68
3969 194.7 32.89 -0.03837 

## 69
9968 282.1 60.75 0.6236 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-111 4.761e+004 389.3 103.5 1.049 

## 1
1.378e+005 392.1 104.7 -1.589 

## 2 3 4 5 Other models for which likelihoods are calculated: 

## 6 7 Model A1: Yij = Mu(i) + e(ij) 

## 8 Var{e(ij)} = Sigma^2 

## 9 10 Model A2: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = Sigma(i)^2 

## 12 13 Model A3: Yij = Mu(i) + e(ij) 

## 14 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 15 16 Model R: Yij = Mu + e(i) 

## 17 Var{e(ij)} = Sigma^2 

## 18 19 20
Likelihoods of Interest 

## 21 22 Model Log(likelihood) DF AIC 

## 23

------- ----------------- ---- ------------ 

## 24
A1 -68.74833 6 149.4967 

## 25
A2 -58.69126 10 137.3825 

## 26
A3 -64.89907 7 143.7981 

## 27
R -80.72265 2 165.4453 

## 28
4 -65.41669 5 140.8334 

## 29 30 31 Additive constant for all log-likelihoods = -13.78. This constant added to the 

## 32 above values gives the log-likelihood including the term that does not 

## 33 depend on the model parameters. 

## 34 35 36 Explanation of Tests 

## 37 38 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 39 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 40 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 41 42 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 43 44 45
Tests of Interest 

## 46 47 Test -2*log(Likelihood Ratio) D. F. p-value 

## 48

-------- ------------------------ ------ -------------- 

## 49
Test 1 44.06 8 < 0.0001 

## 50
Test 2 20.11 4 0.0004741 

## 51
Test 3 12.42 3 0.006087 

## 52
Test 6a 1.035 2 0.5959 

## 53 54 55 The p-value for Test 1 is less than .05. There appears to be a 

## 56 difference between response and/or variances among the dose 

## 57 levels, it seems appropriate to model the data. 

## 58 59 The p-value for Test 2 is less than .1. A non-homogeneous 

## 60 variance model appears to be appropriate. 

## 61 62 The p-value for Test 3 is less than .1. You may want to 

## 63
consider a different variance model. 

## 64 65 The p-value for Test 6a is greater than .1. Model 4 seems 

## 66 to adequately describe the data. 

## 67 68 69 Benchmark Dose Computations: 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-112 1 Specified Effect = 1.000000 

## 2 3 Risk Type = Estimated standard deviations from control 

## 4 5 Confidence Level = 0.950000 

## 6 7
BMD = 402.539 

## 8 9
BMDL = 221.776 

## 10 11 H.2.10.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 12 Unrestricted 13

-100 0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

12:44 11/20 2009 BMD BMDL Exponential



## 14 15 16 H.2.10.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 17 Power Unrestricted 18 19 20

==================================================================== 

## 21 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 22 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Exp_Unrest_BMR1_UGT_1A1.(d) 

## 23 Gnuplot Plotting File: 

## 24
Fri Nov 20 12:44:01 2009 

## 25

==================================================================== 

## 26 27 Tbl2, UGT_1A1 

## 28

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 29 30 The form of the response function by Model: 

## 31 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 32 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 33 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 34 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-113 Note: Y[dose] is the median response for exposure = dose; 

## 1 sign = +1 for increasing trend in data; 

## 2 sign = -1 for decreasing trend. 

## 3 4
Model 2 is nested within Models 3 and 4. 

## 5 Model 3 is nested within Model 5. 

## 6
Model 4 is nested within Model 5. 

## 7 8 9 Dependent variable = Mean 

## 10 Independent variable = Dose 

## 11 Data are assumed to be distributed: normally 

## 12 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 13 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 14 15 Total number of dose groups = 5 

## 16 Total number of records with missing values = 0 

## 17
Maximum number of iterations = 250 

## 18 Relative Function Convergence has been set to: 1e-008 

## 19 Parameter Convergence has been set to: 1e-008 

## 20 21 MLE solution provided: Exact 

## 22 23 24
Initial Parameter Values 

## 25 26
Variable Model 5 

## 27

-------- -------- 

## 28 lnalpha -1.53604 

## 29
rho 1.59958 

## 30
a 95.95 

## 31
b 1.15499e-005 

## 32
c 4.94633 

## 33
d 1 

## 34 35 36 37
Parameter Estimates 

## 38 39
Variable Model 5 

## 40

-------- ------- 

## 41 lnalpha -10.3642 

## 42
rho 3.29138 

## 43
a 101.591 

## 44
b 0.000102786 

## 45
c 3.84125 

## 46
d 1.08913 

## 47 48 49 Table of Stats From Input Data 

## 50 51
Dose N Obs Mean Obs Std Dev 

## 52

----- --- ---------- ------------- 

## 53
0 3 101 15.59 

## 54
3969 3 194 36.37 

## 55
9968 3 304 17.32 

## 56
4.761e+004 3 452 48.5 

## 57
1.378e+005 3 296 149 

## 58 59 60
Estimated Values of Interest 

## 61 62
Dose Est Mean Est Std Scaled Residual 

## 63

------ ---------- --------- ---------------- 

## 64
0 101.6 11.28 -0.09081 

## 65
3969 192.2 32.19 0.09829 

## 66
9968 286.9 62.23 0.4773 

## 67
4.761e+004 389.2 102.8 1.058 

## 68
1.378e+005 390.2 103.3 -1.581 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-114 1 2
Other models for which likelihoods are calculated: 

## 3 4 Model A1: Yij = Mu(i) + e(ij) 

## 5 Var{e(ij)} = Sigma^2 

## 6 7 Model A2: Yij = Mu(i) + e(ij) 

## 8 Var{e(ij)} = Sigma(i)^2 

## 9 10 Model A3: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 12 13 Model R: Yij = Mu + e(i) 

## 14 Var{e(ij)} = Sigma^2 

## 15 16 17
Likelihoods of Interest 

## 18 19 Model Log(likelihood) DF AIC 

## 20

------- ----------------- ---- ------------ 

## 21
A1 -68.74833 6 149.4967 

## 22
A2 -58.69126 10 137.3825 

## 23
A3 -64.89907 7 143.7981 

## 24
R -80.72265 2 165.4453 

## 25
5 -65.38628 6 142.7726 

## 26 27 28 Additive constant for all log-likelihoods = -13.78. This constant added to the 

## 29 above values gives the log-likelihood including the term that does not 

## 30 depend on the model parameters. 

## 31 32 33 Explanation of Tests 

## 34 35 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 36 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 37 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 38 39 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 40 41 42
Tests of Interest 

## 43 44 Test -2*log(Likelihood Ratio) D. F. p-value 

## 45

-------- ------------------------ ------ -------------- 

## 46
Test 1 44.06 8 < 0.0001 

## 47
Test 2 20.11 4 0.0004741 

## 48
Test 3 12.42 3 0.006087 

## 49
Test 7a 0.9744 1 0.3236 

## 50 51 52 The p-value for Test 1 is less than .05. There appears to be a 

## 53 difference between response and/or variances among the dose 

## 54 levels, it seems appropriate to model the data. 

## 55 56 The p-value for Test 2 is less than .1. A non-homogeneous 

## 57 variance model appears to be appropriate. 

## 58 59 The p-value for Test 3 is less than .1. You may want to 

## 60
consider a different variance model. 

## 61 62 The p-value for Test 7a is greater than .1. Model 5 seems 

## 63 to adequately describe the data. 

## 64 65 66 Benchmark Dose Computations: 

## 67 68 Specified Effect = 1.000000 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-115 Risk Type = Estimated standard deviations from control 

## 1 2
Confidence Level = 0.950000 

## 3 4
BMD = 504.638 

## 5 6
BMDL = 223.156 

## 7 8 9 10 H.2.10.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 11

-100 0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Hill Model

12:44 11/20 2009 BMD Hill



## 12 13 14 H.2.10.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 15 16 17

==================================================================== 

## 18 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 19 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_UGT_1A1.(d) 

## 20 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Hill_Unrest_BMR1_UGT_1A1.plt 

## 21
Fri Nov 20 12:44:02 2009 

## 22

==================================================================== 

## 23 24 Tbl2, UGT_1A1 

## 25

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 26 27 The form of the response function is: 

## 28 29 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 30 31 32 Dependent variable = Mean 

## 33 Independent variable = Dose 

## 34 Power parameter is not restricted 

## 35 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-116 Total number of dose groups = 5 

## 1 Total number of records with missing values = 0 

## 2
Maximum number of iterations = 250 

## 3 Relative Function Convergence has been set to: 1e-008 

## 4 Parameter Convergence has been set to: 1e-008 

## 5 6 7 8
Default Initial Parameter Values 

## 9 lalpha = 8.57191 

## 10
rho = 0 

## 11 intercept = 101 

## 12
v = 351 

## 13
n = 0.350477 

## 14
k = 11467.2 

## 15 16 17 Asymptotic Correlation Matrix of Parameter Estimates 

## 18 19 lalpha rho intercept v n k 

## 20 21 lalpha 1 -0.99 -0.19 0.14 0.12 -0.0083 

## 22 23
rho -0.99 1 0.18 -0.17 -0.12 -0.0038 

## 24 25 intercept -0.19 0.18 1 -0.12 0.031 0.1 

## 26 27
v 0.14 -0.17 -0.12 1 -0.57 0.79 

## 28 29
n 0.12 -0.12 0.031 -0.57 1 -0.73 

## 30 31
k -0.0083 -0.0038 0.1 0.79 -0.73 1 

## 32 33 34 35
Parameter Estimates 

## 36 37
95.0% Wald Confidence Interval 

## 38 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 39 lalpha -10.4997 3.7002 -17.752 -3.24748 

## 40
rho 3.31877 0.67548 1.99485 4.64269 

## 41 intercept 101.641 6.48455 88.9319 114.351 

## 42
v 296.324 52.8989 192.644 400.003 

## 43
n 1.52651 0.645076 0.262182 2.79084 

## 44
k 6852.92 2333.57 2279.2 11426.6 

## 45 46 47 48
Table of Data and Estimated Values of Interest 

## 49 50
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 51

------ --- -------- -------- ----------- ----------- ---------- 

## 52 53
0 3 101 102 15.6 11.2 -0.0989 

## 54
3969 3 194 191 36.4 32.1 0.141 

## 55
9968 3 304 291 17.3 64.4 0.348 

## 56
4.761e+004 3 452 383 48.5 102 1.17 

## 57
1.378e+005 3 296 395 149 107 -1.6 

## 58 59 60 61 Model Descriptions for likelihoods calculated 

## 62 63 64 Model A1: Yij = Mu(i) + e(ij) 

## 65 Var{e(ij)} = Sigma^2 

## 66 67 Model A2: Yij = Mu(i) + e(ij) 

## 68 Var{e(ij)} = Sigma(i)^2 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-117 Model A3: Yij = Mu(i) + e(ij) 

## 1 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 2 Model A3 uses any fixed variance parameters that 

## 3 were specified by the user 

## 4 5 Model R: Yi = Mu + e(i) 

## 6 Var{e(i)} = Sigma^2 

## 7 8 9
Likelihoods of Interest 

## 10 11 Model Log(likelihood) # Param's AIC 

## 12
A1 -68.748326 6 149.496653 

## 13
A2 -58.691256 10 137.382511 

## 14
A3 -64.899072 7 143.798144 

## 15
fitted -65.536514 6 143.073028 

## 16
R -80.722651 2 165.445302 

## 17 18 19 Explanation of Tests 

## 20 21 Test 1: Do responses and/or variances differ among Dose levels? 

## 22 (A2 vs. R) 

## 23 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 24 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 25 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 26 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 27 28
Tests of Interest 

## 29 30 Test -2*log(Likelihood Ratio) Test df p-value 

## 31 32
Test 1 44.0628 8 <.0001 

## 33
Test 2 20.1141 4 0.0004741 

## 34
Test 3 12.4156 3 0.006087 

## 35
Test 4 1.27488 1 0.2589 

## 36 37 The p-value for Test 1 is less than .05. There appears to be a 

## 38 difference between response and/or variances among the dose levels 

## 39 It seems appropriate to model the data 

## 40 41 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 42 model appears to be appropriate 

## 43 44 The p-value for Test 3 is less than .1. You may want to consider a 

## 45
different variance model 

## 46 47 The p-value for Test 4 is greater than .1. The model chosen seems 

## 48 to adequately describe the data 

## 49 50 51 Benchmark Dose Computation 

## 52 53 Specified effect = 1 

## 54 55 Risk Type = Estimated standard deviations from the control mean 

## 56 57 Confidence level = 0.95 

## 58 59
BMD = 823.8 

## 60 61 62 BMDL computation failed. 

## 63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-118 H.2.10.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

-100 0 100 200 300 400 500 600 700

0 20000 40000 60000 80000 100000 120000 140000Mean Response

dose Power Model with 0.95 Confidence Level

12:44 11/20 2009 BMDBMDL Power



## 2 3 4 H.2.10.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 Unrestricted 6 7 8

==================================================================== 

## 9 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 10 Input Data File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_UGT_1A1.(d) 

## 11 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Blood\Pwr_Unrest_BMR1_UGT_1A1.plt 

## 12
Fri Nov 20 12:44:03 2009 

## 13

==================================================================== 

## 14 15 Tbl2, UGT_1A1 

## 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 17 18 The form of the response function is: 

## 19 20 Y[dose] = control + slope * dose^power 

## 21 22 23 Dependent variable = Mean 

## 24 Independent variable = Dose 

## 25 The power is not restricted 

## 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 27 28 Total number of dose groups = 5 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-119 lalpha = 8.57191 

## 1
rho = 0 

## 2
control = 101 

## 3 slope = 19.8524 

## 4 power = 0.225107 

## 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 

## 8 9 lalpha rho control slope power 

## 10 11 lalpha 1 -0.99 -0.22 0.0058 0.021 

## 12 13
rho -0.99 1 0.21 0.024 -0.057 

## 14 15
control -0.22 0.21 1 -0.14 0.11 

## 16 17 slope 0.0058 0.024 -0.14 1 -0.99 

## 18 19 power 0.021 -0.057 0.11 -0.99 1 

## 20 21 22 23
Parameter Estimates 

## 24 25
95.0% Wald Confidence Interval 

## 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 27 lalpha -11.5995 3.46108 -18.3831 -4.81588 

## 28
rho 3.55351 0.629824 2.31908 4.78795 

## 29
control 101.406 6.37341 88.9147 113.898 

## 30 slope 7.06329 7.31729 -7.27833 21.4049 

## 31 power 0.337328 0.106575 0.128444 0.546212 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 3 101 101 15.6 11.1 -0.0634 

## 41
3969 3 194 217 36.4 42.9 -0.928 

## 42
9968 3 304 259 17.3 58.8 1.32 

## 43
4.761e+004 3 452 369 48.5 110 1.31 

## 44
1.378e+005 3 296 484 149 178 -1.82 

## 45 46 47 48 Model Descriptions for likelihoods calculated 

## 49 50 51 Model A1: Yij = Mu(i) + e(ij) 

## 52 Var{e(ij)} = Sigma^2 

## 53 54 Model A2: Yij = Mu(i) + e(ij) 

## 55 Var{e(ij)} = Sigma(i)^2 

## 56 57 Model A3: Yij = Mu(i) + e(ij) 

## 58 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 59 Model A3 uses any fixed variance parameters that 

## 60 were specified by the user 

## 61 62 Model R: Yi = Mu + e(i) 

## 63 Var{e(i)} = Sigma^2 

## 64 65 66
Likelihoods of Interest 

## 67 68 Model Log(likelihood) # Param's AIC 

## 69
A1 -68.748326 6 149.496653 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-120 A2 -58.691256 10 137.382511 

## 1
A3 -64.899072 7 143.798144 

## 2
fitted -67.875596 5 145.751193 

## 3
R -80.722651 2 165.445302 

## 4 5 6 Explanation of Tests 

## 7 8 Test 1: Do responses and/or variances differ among Dose levels? 

## 9 (A2 vs. R) 

## 10 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 11 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 12 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 13 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 14 15
Tests of Interest 

## 16 17 Test -2*log(Likelihood Ratio) Test df p-value 

## 18 19
Test 1 44.0628 8 <.0001 

## 20
Test 2 20.1141 4 0.0004741 

## 21
Test 3 12.4156 3 0.006087 

## 22
Test 4 5.95305 2 0.05097 

## 23 24 The p-value for Test 1 is less than .05. There appears to be a 

## 25 difference between response and/or variances among the dose levels 

## 26 It seems appropriate to model the data 

## 27 28 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 29 model appears to be appropriate 

## 30 31 The p-value for Test 3 is less than .1. You may want to consider a 

## 32
different variance model 

## 33 34 The p-value for Test 4 is less than .1. You may want to try a different 

## 35
model 

## 36 37 38 Benchmark Dose Computation 

## 39 40 Specified effect = 1 

## 41 42 Risk Type = Estimated standard deviations from the control mean 

## 43 44
Confidence level = 0.95 

## 45 46
BMD = 3.82374 

## 47 48 49
BMDL = 0.000231902 

## 50 51

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-121 H.2.11. Vanden Heuvel et al. (1994): Hepatic CYP1A1 mRNA Expression 1
H.2.11.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 5 <0.0001 518.90 <0.0001 1114.48 4.2E+03 3.2E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 5 <0.0001 518.90 <0.0001 1114.48 4.2E+03 3.2E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 4 <0.0001 71.31 <0.0001 668.92 2.2E+01 1.0E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) c 3 <0.0001 35.23 <0.0001 634.84 4.5E+02 3.3E+02 nonconstant variance, power restricted ≥ 1

Hill 3 <.0001 33.65 <.0001 633.26 5.3E+02 error nonconstant variance, n restricted >1

linear 5 <.0001 79.92 <.0001 675.53 1.6E+01 8.5E+00 nonconstant variance

polynomial 5 <.0001 235.66 <.0001 831.27 1.4E+05 3.0E+02 nonconstant variance

power 4 <.0001 77.35 <.0001 674.96 2.1E+01 1.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M2) 5 <0.0001 27.27 <0.0001 1178.21 6.7E+04 5.9E+04 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 62.38 <0.0001 1215.33 1.6E+09 6.0E+06 constant variance, power restricted ≥ 1
exponential (M4) 4 <0.0001 0.86 0.93 1153.81 5.8E+03 4.1E+03 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 0.00 1.00 1154.95 9.0E+03 4.4E+03 constant variance, power restricted ≥ 1

Hill 3 <.0001 0.00 1.00 1154.95 8.4E+03 3.5E+03 constant variance, n restricted >1

linear 5 <.0001 19.42 0.00 1170.37 3.0E+04 2.4E+04 constant variance

polynomial 5 <.0001 26.27 <.0001 1177.21 2.4E+04 2.1E+04 constant variance

power 5 <.0001 19.32 0.00 1170.27 3.1E+04 2.4E+04 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 

## 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-122 H.2.11.2. Figure for Selected Model: Exponen tial (M5), Nonconstant Variance, Power 1 Restricted ≥ 1 2

0 10000 20000 30000 40000 50000 60000 70000

0 20000 40000 60000 80000 100000 120000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

11:31 11/19 2009 BMD BMDL Exponential



## 3 4 5 H.2.11.3. Output File for Selected Model: Expo nential (M5), Nonconstant Varian ce, Power 6 Restricted ≥ 1 7 8 9

==================================================================== 

## 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 11 Input Data File: C:\USEPA\BMDS21\AD\Blood\Exp_BMR1_hepatic_CYP1A1_mRNA_expression.(d) 

## 12 Gnuplot Plotting File: 

## 13
Thu Nov 19 11:31:49 2009 

## 14

==================================================================== 

## 15 16 [insert study notes] 

## 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 18 19 The form of the response function by Model: 

## 20 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 24 25 Note: Y[dose] is the median response for exposure = dose; 

## 26 sign = +1 for increasing trend in data; 

## 27 sign = -1 for decreasing trend. 

## 28 29
Model 2 is nested within Models 3 and 4. 

## 30
Model 3 is nested within Model 5. 

## 31
Model 4 is nested within Model 5. 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Data are assumed to be distributed: normally 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-123 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 1 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 2 3 Total number of dose groups = 7 

## 4 Total number of records with missing values = 0 

## 5 Maximum number of iterations = 250 

## 6 Relative Function Convergence has been set to: 1e-008 

## 7 Parameter Convergence has been set to: 1e-008 

## 8 9 MLE solution provided: Exact 

## 10 11 12
Initial Parameter Values 

## 13 14
Variable Model 5 

## 15

-------- -------- 

## 16 lnalpha -0.89532 

## 17
rho 2.01401 

## 18
a 5.13 

## 19
b 2.68046e-005 

## 20
c 7511.7 

## 21
d 1 

## 22 23 24 25
Parameter Estimates 

## 26 27
Variable Model 5 

## 28

-------- ------- 

## 29 lnalpha 0.166401 

## 30
rho 1.90534 

## 31
a 9.80088 

## 32
b 7.30524e-005 

## 33
c 3246.67 

## 34
d 2.37353 

## 35 36 37 Table of Stats From Input Data 

## 38 39
Dose N Obs Mean Obs Std Dev 

## 40

----- --- ---------- ------------- 

## 41
0 13 5.4 3.606 

## 42
3.805 5 7.2 5.59 

## 43
35.91 12 14.8 14.9 

## 44
301.9 7 12.8 4.498 

## 45
2149 7 536 320.1 

## 46
1.43e+004 11 1.8e+004 1.522e+004 

## 47
1.147e+005 5 3.67e+004 2.214e+004 

## 48 49 50
Estimated Values of Interest 

## 51 52
Dose Est Mean Est Std Scaled Residual 

## 53

------ ---------- --------- ---------------- 

## 54
0 9.801 9.561 -1.66 

## 55
3.805 9.801 9.561 -0.6083 

## 56
35.91 9.825 9.583 1.799 

## 57
301.9 13.52 12.99 -0.1474 

## 58
2149 400.1 327.4 1.099 

## 59
1.43e+004 2.133e+004 1.446e+004 -0.7638 

## 60
1.147e+005 3.182e+004 2.117e+004 0.5154 

## 61 62 63 64
Other models for which likelihoods are calculated: 

## 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-124 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 4 5 Model R: Yij = Mu + e(i) 

## 6 Var{e(ij)} = Sigma^2 

## 7 8 9
Likelihoods of Interest 

## 10 11 Model Log(likelihood) DF AIC 

## 12

------- ----------------- ---- ------------ 

## 13
A1 -572.4744 8 1160.949 

## 14
A2 -290.7965 14 609.5929 

## 15
A3 -293.806 9 605.6119 

## 16
R -603.6646 2 1211.329 

## 17
5 -311.4203 6 634.8406 

## 18 19 20 Additive constant for all log-likelihoods = -55.14. This constant added to the 

## 21 above values gives the log-likelihood including the term that does not 

## 22 depend on the model parameters. 

## 23 24 25 Explanation of Tests 

## 26 27 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 28 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 29 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 30 31 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 32 33 34
Tests of Interest 

## 35 36 Test -2*log(Likelihood Ratio) D. F. p-value 

## 37

-------- ------------------------ ------ -------------- 

## 38
Test 1 625.7 12 < 0.0001 

## 39
Test 2 563.4 6 < 0.0001 

## 40
Test 3 6.019 5 0.3044 

## 41
Test 7a 35.23 3 < 0.0001 

## 42 43 44 The p-value for Test 1 is less than .05. There appears to be a 

## 45 difference between response and/or variances among the dose 

## 46 levels, it seems appropriate to model the data. 

## 47 48 The p-value for Test 2 is less than .1. A non-homogeneous 

## 49 variance model appears to be appropriate. 

## 50 51 The p-value for Test 3 is greater than .1. The modeled 

## 52 variance appears to be appropriate here. 

## 53 54 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 55 describe the data; you may want to consider another model. 

## 56 57 58 Benchmark Dose Computations: 

## 59 60 Specified Effect = 1.000000 

## 61 62 Risk Type = Estimated standard deviations from control 

## 63 64
Confidence Level = 0.950000 

## 65 66
BMD = 449.252 

## 67 68
BMDL = 332.057 

## 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-125 H.3. ADMINISTERED DOSE BMDS RESULTS 1
H.3.1. Hassoun et al. (2000): CytC Liver 2
H.3.1.1. Summary Table of BMDS Modeling Results 3

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 0.39 15.15 0.00 -140.98 2.8E+01 1.9E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.39 15.15 0.00 -140.98 2.8E+01 1.9E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.39 1.73 0.63 -152.40 7.5E+00 4.6E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.39 0.56 0.76 -151.57 1.2E+01 5.2E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.39 0.56 0.76 -151.57 1.2E+01 5.2E+00 nonconstant variance, power unrestricted

Hill 2 0.39 0.67 0.72 -151.46 1.3E+01 error nonconstant variance, n restricted >1

Hill 2 0.39 0.67 0.72 -151.46 1.3E+01 4.5E+00 nonconstant variance, n unrestricted

linear 4 0.39 7.87 0.10 -148.27 1.5E+01 1.0E+01 nonconstant variance

polynomial 4 0.39 7.87 0.10 -148.27 1.5E+01 1.0E+01 nonconstant variance

power 4 0.39 7.87 0.10 -148.27 1.5E+01 1.0E+01 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.39 3.95 0.27 -150.18 5.6E+00 1.7E+00 nonconstant variance, power unrestricted
exponential (M2) 4 0.39 16.43 0.00 -139.08 3.9E+01 3.3E+01 constant variance, power restricted ≥ 1
exponential (M3) 4 0.39 16.43 0.00 -139.08 3.9E+01 3.3E+01 constant variance, power restricted ≥ 1
exponential (M4) c 3 0.39 1.70 0.64 -151.81 9.1E+00 5.9E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.39 0.48 0.79 -151.02 1.4E+01 6.5E+00 constant variance, power restricted ≥ 1
exponential (M5) d 2 0.39 0.48 0.79 -151.02 1.4E+01 6.5E+00 constant variance, power unrestricted

Hill 2 0.39 0.60 0.74 -150.90 1.5E+01 6.3E+00 constant variance, n restricted >1

Hill d 2 0.39 0.60 0.74 -150.90 1.5E+01 5.9E+00 constant variance, n unrestricted

linear 4 0.39 10.56 0.03 -144.95 2.5E+01 1.9E+01 constant variance

polynomial 4 0.39 10.56 0.03 -144.95 2.5E+01 1.9E+01 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-126 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 4 0.39 10.56 0.03 -144.95 2.5E+01 1.9E+01 constant variance, power restricted ≥ 1, bound hit

power d 3 0.39 4.52 0.21 -148.99 6.6E+00 2.0E+00 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.1.2. Figure for Selected Model: Exponential (M 4), Constant Variance, Power Restricted 3 ≥ 1 4

0.1 0.2 0.3 0.4 0.5 0.6

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:45 11/23 2009 BMD BMDL Exponential



## 5 6 7 H.3.1.3. Output File for Selected Model: Expo nential (M4), Constant Variance, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov23\Exp_CV_BMR1_CytC_Liver.(d) 

## 14 Gnuplot Plotting File: 

## 15
Mon Nov 23 13:45:24 2009 

## 16

==================================================================== 

## 17 18 TBARs, liver only (Table 2) 

## 19

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-127 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 1 2 The form of the response function by Model: 

## 3 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 4 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 5 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 6 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 7 8 Note: Y[dose] is the median response for exposure = dose; 

## 9 sign = +1 for increasing trend in data; 

## 10 sign = -1 for decreasing trend. 

## 11 12
Model 2 is nested within Models 3 and 4. 

## 13
Model 3 is nested within Model 5. 

## 14
Model 4 is nested within Model 5. 

## 15 16 17 Dependent variable = Mean 

## 18 Independent variable = Dose 

## 19 Data are assumed to be distributed: normally 

## 20 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 21
rho is set to 0. 

## 22
A constant variance model is fit. 

## 23 24 Total number of dose groups = 6 

## 25 Total number of records with missing values = 0 

## 26
Maximum number of iterations = 250 

## 27 Relative Function Convergence has been set to: 1e-008 

## 28 Parameter Convergence has been set to: 1e-008 

## 29 30 MLE solution provided: Exact 

## 31 32 33
Initial Parameter Values 

## 34 35
Variable Model 4 

## 36

-------- -------- 

## 37 lnalpha -5.48625 

## 38 rho(S) 0 

## 39
a 0.1387 

## 40
b 0.027423 

## 41
c 3.36121 

## 42
d 1 

## 43 44 (S) = Specified 

## 45 46 47 48
Parameter Estimates 

## 49 50
Variable Model 4 

## 51

-------- ------- 

## 52 lnalpha -5.47287 

## 53
rho 0 

## 54
a 0.156285 

## 55
b 0.0293581 

## 56
c 2.85125 

## 57
d 1.56807 

## 58 59 60 Table of Stats From Input Data 

## 61 62
Dose N Obs Mean Obs Std Dev 

## 63

----- --- ---------- ------------- 

## 64
0 6 0.146 0.06614 

## 65
3 6 0.177 0.05389 

## 66
10 6 0.191 0.05634 

## 67
22 6 0.271 0.05634 

## 68
46 6 0.388 0.06369 

## 69
100 6 0.444 0.1102 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-128 1 2
Estimated Values of Interest 

## 3 4
Dose Est Mean Est Std Scaled Residual 

## 5

------ ---------- --------- ---------------- 

## 6
0 0.1413 0.06591 0.1762 

## 7
3 0.1646 0.06591 0.4609 

## 8
10 0.2131 0.06591 -0.8196 

## 9
22 0.2796 0.06591 -0.3199 

## 10
46 0.3676 0.06591 0.7587 

## 11
100 0.4509 0.06591 -0.2564 

## 12 13 14 15
Other models for which likelihoods are calculated: 

## 16 17 Model A1: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = Sigma^2 

## 19 20 Model A2: Yij = Mu(i) + e(ij) 

## 21 Var{e(ij)} = Sigma(i)^2 

## 22 23 Model A3: Yij = Mu(i) + e(ij) 

## 24 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 25 26 Model R: Yij = Mu + e(i) 

## 27 Var{e(ij)} = Sigma^2 

## 28 29 30
Likelihoods of Interest 

## 31 32 Model Log(likelihood) DF AIC 

## 33

------- ----------------- ---- ------------ 

## 34
A1 80.75258 7 -147.5052 

## 35
A2 83.37355 12 -142.7471 

## 36
A3 80.75258 7 -147.5052 

## 37
R 55.82002 2 -107.64 

## 38
4 79.90337 4 -151.8067 

## 39 40 41 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 42 above values gives the log-likelihood including the term that does not 

## 43 depend on the model parameters. 

## 44 45 46 Explanation of Tests 

## 47 48 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 49 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 50 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 51 52 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 53 54 55
Tests of Interest 

## 56 57 Test -2*log(Likelihood Ratio) D. F. p-value 

## 58

-------- ------------------------ ------ -------------- 

## 59
Test 1 55.11 10 < 0.0001 

## 60
Test 2 5.242 5 0.3871 

## 61
Test 3 5.242 5 0.3871 

## 62
Test 6a 1.698 3 0.6373 

## 63 64 65 The p-value for Test 1 is less than .05. There appears to be a 

## 66 difference between response and/or variances among the dose 

## 67 levels, it seems appropriate to model the data. 

## 68 69 The p-value for Test 2 is greater than .1. A homogeneous 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-129 variance model appears to be appropriate here. 

## 1 2 The p-value for Test 3 is greater than .1. The modeled 

## 3 variance appears to be appropriate here. 

## 4 5 The p-value for Test 6a is greater than .1. Model 4 seems 

## 6 to adequately describe the data. 

## 7 8 9 Benchmark Dose Computations: 

## 10 11 Specified Effect = 1.000000 

## 12 13 Risk Type = Estimated standard deviations from control 

## 14 15
Confidence Level = 0.950000 

## 16 17
BMD = 9.0851 

## 18 19
BMDL = 5.88612 

## 20 21 22 H.3.1.4. Figure for Unrestricted Model: Expon ential (M5), Constant Variance, Power 23 Unrestricted 24

0.1 0.2 0.3 0.4 0.5 0.6

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:45 11/23 2009 BMD BMDL Exponential



## 25 26 H.3.1.5. Output File for Unrestricted Model: Exponential (M5), Con stant Variance, Power 27 Unrestricted 28 29 30

==================================================================== 

## 31 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 32 Input Data File: C:\USEPA\BMDS21\Nov23\Exp_CV_Unrest_BMR1_CytC_Liver.(d) 

## 33 Gnuplot Plotting File: 

## 34
Mon Nov 23 13:45:31 2009 

## 35

==================================================================== 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-130 TBARs, liver only (Table 2) 

## 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 2 3 The form of the response function by Model: 

## 4 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 5 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 6 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 7 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 8 9 Note: Y[dose] is the median response for exposure = dose; 

## 10 sign = +1 for increasing trend in data; 

## 11 sign = -1 for decreasing trend. 

## 12 13
Model 2 is nested within Models 3 and 4. 

## 14
Model 3 is nested within Model 5. 

## 15
Model 4 is nested within Model 5. 

## 16 17 18 Dependent variable = Mean 

## 19 Independent variable = Dose 

## 20 Data are assumed to be distributed: normally 

## 21 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 22
rho is set to 0. 

## 23
A constant variance model is fit. 

## 24 25 Total number of dose groups = 6 

## 26 Total number of records with missing values = 0 

## 27
Maximum number of iterations = 250 

## 28 Relative Function Convergence has been set to: 1e-008 

## 29 Parameter Convergence has been set to: 1e-008 

## 30 31 MLE solution provided: Exact 

## 32 33 34
Initial Parameter Values 

## 35 36
Variable Model 5 

## 37

-------- -------- 

## 38 lnalpha -5.48625 

## 39 rho(S) 0 

## 40
a 0.1387 

## 41
b 0.027423 

## 42
c 3.36121 

## 43
d 1 

## 44 45 (S) = Specified 

## 46 47 48 49
Parameter Estimates 

## 50 51
Variable Model 5 

## 52

-------- ------- 

## 53 lnalpha -5.47287 

## 54
rho 0 

## 55
a 0.156285 

## 56
b 0.0293581 

## 57
c 2.85125 

## 58
d 1.56807 

## 59 60 61 Table of Stats From Input Data 

## 62 63
Dose N Obs Mean Obs Std Dev 

## 64

----- --- ---------- ------------- 

## 65
0 6 0.146 0.06614 

## 66
3 6 0.177 0.05389 

## 67
10 6 0.191 0.05634 

## 68
22 6 0.271 0.05634 

## 69
46 6 0.388 0.06369 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-131 100 6 0.444 0.1102 

## 1 2 3
Estimated Values of Interest 

## 4 5 Dose Est Mean Est Std Scaled Residual 

## 6

------ ---------- --------- ---------------- 

## 7
0 0.1563 0.0648 -0.3888 

## 8
3 0.1626 0.0648 0.5434 

## 9
10 0.1957 0.0648 -0.1766 

## 10
22 0.2708 0.0648 0.007576 

## 11
46 0.3873 0.0648 0.02644 

## 12
100 0.4443 0.0648 -0.01203 

## 13 14 15 16
Other models for which likelihoods are calculated: 

## 17 18 Model A1: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = Sigma^2 

## 20 21 Model A2: Yij = Mu(i) + e(ij) 

## 22 Var{e(ij)} = Sigma(i)^2 

## 23 24 Model A3: Yij = Mu(i) + e(ij) 

## 25 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 26 27 Model R: Yij = Mu + e(i) 

## 28 Var{e(ij)} = Sigma^2 

## 29 30 31
Likelihoods of Interest 

## 32 33 Model Log(likelihood) DF AIC 

## 34

------- ----------------- ---- ------------ 

## 35
A1 80.75258 7 -147.5052 

## 36
A2 83.37355 12 -142.7471 

## 37
A3 80.75258 7 -147.5052 

## 38
R 55.82002 2 -107.64 

## 39
5 80.51171 5 -151.0234 

## 40 41 42 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 43 above values gives the log-likelihood including the term that does not 

## 44 depend on the model parameters. 

## 45 46 47 Explanation of Tests 

## 48 49 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 50 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 51 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 52 53 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 54 55 56
Tests of Interest 

## 57 58 Test -2*log(Likelihood Ratio) D. F. p-value 

## 59

-------- ------------------------ ------ -------------- 

## 60
Test 1 55.11 10 < 0.0001 

## 61
Test 2 5.242 5 0.3871 

## 62
Test 3 5.242 5 0.3871 

## 63
Test 7a 0.4817 2 0.7859 

## 64 65 66 The p-value for Test 1 is less than .05. There appears to be a 

## 67 difference between response and/or variances among the dose 

## 68 levels, it seems appropriate to model the data. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-132 The p-value for Test 2 is greater than .1. A homogeneous 

## 1 variance model appears to be appropriate here. 

## 2 3 The p-value for Test 3 is greater than .1. The modeled 

## 4 variance appears to be appropriate here. 

## 5 6 The p-value for Test 7a is greater than .1. Model 5 seems 

## 7 to adequately describe the data. 

## 8 9 10 Benchmark Dose Computations: 

## 11 12 Specified Effect = 1.000000 

## 13 14 Risk Type = Estimated standard deviations from control 

## 15 16
Confidence Level = 0.950000 

## 17 18
BMD = 14.1987 

## 19 20
BMDL = 6.53738 

## 21 22 23 H.3.1.6. Figure for Unrestricted Model: Hill, Constant Variance, n Unrestricted 24

0.1 0.2 0.3 0.4 0.5 0.6

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

13:45 11/23 2009 BMD BMDL Hill



## 25 26 27 H.3.1.7. Output File for Unrestricted Model: Hill, Constant Variance, n Unrestricted 28 29 30

==================================================================== 

## 31 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 32 Input Data File: C:\USEPA\BMDS21\Nov23\Hill_CV_Unrest_BMR1_CytC_Liver.(d) 

## 33 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Hill_CV_Unrest_BMR1_CytC_Liver.plt 

## 34
Mon Nov 23 13:45:33 2009 

## 35

==================================================================== 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-133 TBARs, liver only (Table 2) 

## 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 2 3 The form of the response function is: 

## 4 5 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 6 7 8 Dependent variable = Mean 

## 9 Independent variable = Dose 

## 10
rho is set to 0 

## 11 Power parameter is not restricted 

## 12
A constant variance model is fit 

## 13 14 Total number of dose groups = 6 

## 15 Total number of records with missing values = 0 

## 16
Maximum number of iterations = 250 

## 17 Relative Function Convergence has been set to: 1e-008 

## 18 Parameter Convergence has been set to: 1e-008 

## 19 20 21 22
Default Initial Parameter Values 

## 23 alpha = 0.004972 

## 24 rho = 0 Specified 

## 25 intercept = 0.146 

## 26
v = 0.298 

## 27
n = 17.5689 

## 28
k = 65.0769 

## 29 30 31 Asymptotic Correlation Matrix of Parameter Estimates 

## 32 33 ( *** The model parameter(s) -rho 

## 34 have been estimated at a boundary point, or have been specified by the user, 

## 35 and do not appear in the correlation matrix ) 

## 36 37 alpha intercept v n k 

## 38 39 alpha 1 8.6e-008 -3.4e-008 3.4e-008 8.6e-008 

## 40 41 intercept 8.6e-008 1 -0.61 0.53 0.069 

## 42 43
v -3.4e-008 -0.61 1 -0.84 0.64 

## 44 45
n 3.4e-008 0.53 -0.84 1 -0.52 

## 46 47
k 8.6e-008 0.069 0.64 -0.52 1 

## 48 49 50 51
Parameter Estimates 

## 52 53
95.0% Wald Confidence Interval 

## 54 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 55 alpha 0.00421303 0.00099302 0.00226674 0.00615931 

## 56 intercept 0.159748 0.0202818 0.119997 0.1995 

## 57
v 0.305175 0.0615956 0.18445 0.4259 

## 58
n 2.11196 1.024 0.104959 4.11895 

## 59
k 28.1195 6.8986 14.5985 41.6405 

## 60 61 62 63
Table of Data and Estimated Values of Interest 

## 64 65
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 66

------ --- -------- -------- ----------- ----------- ---------- 

## 67 68
0 6 0.146 0.16 0.0661 0.0649 -0.519 

## 69
3 6 0.177 0.162 0.0539 0.0649 0.55 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-134 10 6 0.191 0.191 0.0563 0.0649 0.0134 

## 1
22 6 0.271 0.274 0.0563 0.0649 -0.1 

## 2
46 6 0.388 0.385 0.0637 0.0649 0.106 

## 3
100 6 0.444 0.445 0.11 0.0649 -0.0503 

## 4 5 6 7 Model Descriptions for likelihoods calculated 

## 8 9 10 Model A1: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = Sigma^2 

## 12 13 Model A2: Yij = Mu(i) + e(ij) 

## 14 Var{e(ij)} = Sigma(i)^2 

## 15 16 Model A3: Yij = Mu(i) + e(ij) 

## 17 Var{e(ij)} = Sigma^2 

## 18 Model A3 uses any fixed variance parameters that 

## 19 were specified by the user 

## 20 21 Model R: Yi = Mu + e(i) 

## 22 Var{e(i)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) # Param's AIC 

## 28
A1 80.752584 7 -147.505168 

## 29
A2 83.373547 12 -142.747094 

## 30
A3 80.752584 7 -147.505168 

## 31
fitted 80.452332 5 -150.904663 

## 32
R 55.820023 2 -107.640047 

## 33 34 35 Explanation of Tests 

## 36 37 Test 1: Do responses and/or variances differ among Dose levels? 

## 38 (A2 vs. R) 

## 39 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 40 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 41 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 42 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 43 44
Tests of Interest 

## 45 46 Test -2*log(Likelihood Ratio) Test df p-value 

## 47 48
Test 1 55.107 10 <.0001 

## 49
Test 2 5.24193 5 0.3871 

## 50
Test 3 5.24193 5 0.3871 

## 51
Test 4 0.600505 2 0.7406 

## 52 53 The p-value for Test 1 is less than .05. There appears to be a 

## 54 difference between response and/or variances among the dose levels 

## 55 It seems appropriate to model the data 

## 56 57 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 58 model appears to be appropriate here 

## 59 60 61 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 62 to be appropriate here 

## 63 64 The p-value for Test 4 is greater than .1. The model chosen seems 

## 65 to adequately describe the data 

## 66 67 68 Benchmark Dose Computation 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-135 Specified effect = 1 

## 1 2 Risk Type = Estimated standard deviations from the control mean 

## 3 4
Confidence level = 0.95 

## 5 6
BMD = 15.1313 

## 7 8
BMDL = 5.93521 

## 9 10 11 12 H.3.1.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 13

0.1 0.2 0.3 0.4 0.5

0 20 40 60 80 100Mean Response

dose Power Model with 0.95 Confidence Level

13:45 11/23 2009 BMD BMDL Power



## 14 15 16 H.3.1.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 17 18 19

==================================================================== 

## 20 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 21 Input Data File: C:\USEPA\BMDS21\Nov23\Pwr_CV_Unrest_BMR1_CytC_Liver.(d) 

## 22 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Pwr_CV_Unrest_BMR1_CytC_Liver.plt 

## 23
Mon Nov 23 13:45:33 2009 

## 24

==================================================================== 

## 25 26 TBARs, liver only (Table 2) 

## 27

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 28 29 The form of the response function is: 

## 30 31 Y[dose] = control + slope * dose^power 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36
rho is set to 0 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-136 The power is not restricted 

## 1
A constant variance model is fit 

## 2 3 Total number of dose groups = 6 

## 4 Total number of records with missing values = 0 

## 5 Maximum number of iterations = 250 

## 6 Relative Function Convergence has been set to: 1e-008 

## 7 Parameter Convergence has been set to: 1e-008 

## 8 9 10 11
Default Initial Parameter Values 

## 12 alpha = 0.004972 

## 13 rho = 0 Specified 

## 14
control = 0.146 

## 15 slope = 0.0109242 

## 16 power = 0.717914 

## 17 18 19 Asymptotic Correlation Matrix of Parameter Estimates 

## 20 21 ( *** The model parameter(s) -rho 

## 22 have been estimated at a boundary point, or have been specified by the user, 

## 23 and do not appear in the correlation matrix ) 

## 24 25 alpha control slope power 

## 26 27 alpha 1 -8.8e-010 -3.8e-009 4.5e-009 

## 28 29
control -8.8e-010 1 -0.77 0.68 

## 30 31 slope -3.8e-009 -0.77 1 -0.98 

## 32 33 power 4.5e-009 0.68 -0.98 1 

## 34 35 36 37
Parameter Estimates 

## 38 39
95.0% Wald Confidence Interval 

## 40 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 41 alpha 0.00469717 0.00110713 0.00252723 0.00686711 

## 42
control 0.135495 0.0246289 0.0872229 0.183766 

## 43 slope 0.0232652 0.013381 -0.00296103 0.0494915 

## 44 power 0.573772 0.119032 0.340474 0.80707 

## 45 46 47 48
Table of Data and Estimated Values of Interest 

## 49 50
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 51

------ --- -------- -------- ----------- ----------- ---------- 

## 52 53
0 6 0.146 0.135 0.0661 0.0685 0.375 

## 54
3 6 0.177 0.179 0.0539 0.0685 -0.0784 

## 55
10 6 0.191 0.223 0.0563 0.0685 -1.13 

## 56
22 6 0.271 0.273 0.0563 0.0685 -0.056 

## 57
46 6 0.388 0.345 0.0637 0.0685 1.54 

## 58
100 6 0.444 0.462 0.11 0.0685 -0.653 

## 59 60 61 62 Model Descriptions for likelihoods calculated 

## 63 64 65 Model A1: Yij = Mu(i) + e(ij) 

## 66 Var{e(ij)} = Sigma^2 

## 67 68 Model A2: Yij = Mu(i) + e(ij) 

## 69 Var{e(ij)} = Sigma(i)^2 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-137 1 Model A3: Yij = Mu(i) + e(ij) 

## 2 Var{e(ij)} = Sigma^2 

## 3 Model A3 uses any fixed variance parameters that 

## 4 were specified by the user 

## 5 6 Model R: Yi = Mu + e(i) 

## 7 Var{e(i)} = Sigma^2 

## 8 9 10
Likelihoods of Interest 

## 11 12 Model Log(likelihood) # Param's AIC 

## 13
A1 80.752584 7 -147.505168 

## 14
A2 83.373547 12 -142.747094 

## 15
A3 80.752584 7 -147.505168 

## 16
fitted 78.494318 4 -148.988637 

## 17
R 55.820023 2 -107.640047 

## 18 19 20 Explanation of Tests 

## 21 22 Test 1: Do responses and/or variances differ among Dose levels? 

## 23 (A2 vs. R) 

## 24 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 26 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 27 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 28 29
Tests of Interest 

## 30 31 Test -2*log(Likelihood Ratio) Test df p-value 

## 32 33
Test 1 55.107 10 <.0001 

## 34
Test 2 5.24193 5 0.3871 

## 35
Test 3 5.24193 5 0.3871 

## 36
Test 4 4.51653 3 0.2108 

## 37 38 The p-value for Test 1 is less than .05. There appears to be a 

## 39 difference between response and/or variances among the dose levels 

## 40 It seems appropriate to model the data 

## 41 42 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 43 model appears to be appropriate here 

## 44 45 46 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 47 to be appropriate here 

## 48 49 The p-value for Test 4 is greater than .1. The model chosen seems 

## 50 to adequately describe the data 

## 51 52 53 Benchmark Dose Computation 

## 54 55 Specified effect = 1 

## 56 57 Risk Type = Estimated standard deviations from the control mean 

## 58 59
Confidence level = 0.95 

## 60 61
BMD = 6.57302 

## 62 63 64
BMDL = 1.96558 

## 65 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-138 H.3.2. Hassoun et al. (2000): DNA SSB 1
H.3.2.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 0.75 47.92 <0.0001 121.75 3.8E+01 2.5E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.75 47.92 <0.0001 121.75 3.8E+01 2.5E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.75 8.98 0.03 84.81 3.7E+00 2.2E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.75 8.98 0.03 84.81 3.7E+00 2.2E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 0.75 8.98 0.03 84.81 3.7E+00 2.2E+00 nonconstant variance, power unrestricted

Hill 3 0.75 7.46 0.06 83.29 2.6E+00 1.4E+00 nonconstant variance, n restricted >1, bound hit

Hill 2 0.75 3.76 0.15 81.60 6.6E-01 1.8E-01 nonconstant variance, n unrestricted

linear 4 0.75 39.32 <.0001 113.16 1.9E+01 1.0E+01 nonconstant variance

polynomial 4 0.75 39.32 <.0001 113.16 1.9E+01 1.0E+01 nonconstant variance

power 4 0.75 39.32 <.0001 113.16 1.9E+01 1.0E+01 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.75 4.68 0.20 80.52 3.0E-01 8.5E-02 nonconstant variance, power unrestricted
exponential (M2) 4 0.75 48.54 <0.0001 120.83 3.0E+01 2.5E+01 constant variance, power restricted ≥ 1
exponential (M3) 4 0.75 48.54 <0.0001 120.83 3.0E+01 2.5E+01 constant variance, power restricted ≥ 1
exponential (M4) 3 0.75 8.53 0.04 82.81 3.7E+00 2.8E+00 constant variance, power restricted ≥ 1
exponential (M5) 3 0.75 8.53 0.04 82.81 3.7E+00 2.8E+00 constant variance, power restricted ≥ 1
exponential (M5) d 3 0.75 8.53 0.04 82.81 3.7E+00 2.8E+00 constant variance, power unrestricted

Hill c 3 0.75 7.12 0.07 81.41 2.9E+00 2.0E+00 constant variance, n restricted >1, bound hit

Hill d 2 0.75 4.03 0.13 80.32 9.6E-01 2.1E-01 constant variance, n unrestricted

linear 4 0.75 38.88 <.0001 111.16 1.8E+01 1.5E+01 constant variance

polynomial 4 0.75 38.88 <.0001 111.16 1.8E+01 1.5E+01 constant variance

power 4 0.75 38.88 <.0001 111.16 1.8E+01 1.5E+01 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-139 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power d 3 0.75 5.10 0.16 79.39 4.4E-01 1.5E-01 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.2.2. Figure for Selected Model: Exponen tial (M5), Constant Variance, Power 3 Unrestricted 4

5 10 15 20 25

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Exponential



## 5 6 H.3.2.3. Output File for Selected Model: Expo nential (M5), Constant Variance, Power 7 Unrestricted 8 9 10

==================================================================== 

## 11 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 12 Input Data File: C:\USEPA\BMDS21\Nov23\Exp_CV_Unrest_BMR1_DNA_SSB.(d) 

## 13 Gnuplot Plotting File: 

## 14
Mon Nov 23 13:44:02 2009 

## 15

==================================================================== 

## 16 17 DNA single-strand breaks, liver only (Table 3) 

## 18

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 19 20 The form of the response function by Model: 

## 21 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 22 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 23

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-140 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 1 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 2 3 Note: Y[dose] is the median response for exposure = dose; 

## 4 sign = +1 for increasing trend in data; 

## 5 sign = -1 for decreasing trend. 

## 6 7 Model 2 is nested within Models 3 and 4. 

## 8
Model 3 is nested within Model 5. 

## 9
Model 4 is nested within Model 5. 

## 10 11 12 Dependent variable = Mean 

## 13 Independent variable = Dose 

## 14 Data are assumed to be distributed: normally 

## 15 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 16
rho is set to 0. 

## 17
A constant variance model is fit. 

## 18 19 Total number of dose groups = 6 

## 20 Total number of records with missing values = 0 

## 21
Maximum number of iterations = 250 

## 22 Relative Function Convergence has been set to: 1e-008 

## 23 Parameter Convergence has been set to: 1e-008 

## 24 25 MLE solution provided: Exact 

## 26 27 28
Initial Parameter Values 

## 29 30
Variable Model 5 

## 31

-------- -------- 

## 32 lnalpha 0.841244 

## 33 rho(S) 0 

## 34
a 7.0395 

## 35
b 0.0279582 

## 36
c 3.50522 

## 37
d 1 

## 38 39 (S) = Specified 

## 40 41 42 43
Parameter Estimates 

## 44 45
Variable Model 5 

## 46

-------- ------- 

## 47 lnalpha 1.07816 

## 48
rho 0 

## 49
a 8.47733 

## 50
b 0.0311513 

## 51
c 2.84178 

## 52
d 1 

## 53 54 55 Table of Stats From Input Data 

## 56 57
Dose N Obs Mean Obs Std Dev 

## 58

----- --- ---------- ------------- 

## 59
0 6 7.41 1.543 

## 60
3 6 10.78 1.249 

## 61
10 6 13.6 1.69 

## 62
22 6 15.3 1.715 

## 63
46 6 20.4 2.254 

## 64
100 6 23.5 1.372 

## 65 66 67
Estimated Values of Interest 

## 68 69
Dose Est Mean Est Std Scaled Residual 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-141 ------ ---------- --------- ---------------- 

## 1
0 8.477 1.714 -1.525 

## 2
3 9.87 1.714 1.3 

## 3
10 12.66 1.714 1.348 

## 4
22 16.22 1.714 -1.318 

## 5
46 20.37 1.714 0.04957 

## 6
100 23.4 1.714 0.1459 

## 7 8 9 10
Other models for which likelihoods are calculated: 

## 11 12 Model A1: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma^2 

## 14 15 Model A2: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma(i)^2 

## 17 18 Model A3: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Model R: Yij = Mu + e(i) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) DF AIC 

## 28

------- ----------------- ---- ------------ 

## 29
A1 -33.14239 7 80.28478 

## 30
A2 -31.81197 12 87.62394 

## 31
A3 -33.14239 7 80.28478 

## 32
R -80.44209 2 164.8842 

## 33
5 -37.40682 4 82.81364 

## 34 35 36 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 37 above values gives the log-likelihood including the term that does not 

## 38 depend on the model parameters. 

## 39 40 41 Explanation of Tests 

## 42 43 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 44 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 45 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 46 47 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 48 49 50
Tests of Interest 

## 51 52 Test -2*log(Likelihood Ratio) D. F. p-value 

## 53

-------- ------------------------ ------ -------------- 

## 54
Test 1 97.26 10 < 0.0001 

## 55
Test 2 2.661 5 0.7521 

## 56
Test 3 2.661 5 0.7521 

## 57
Test 7a 8.529 3 0.03626 

## 58 59 60 The p-value for Test 1 is less than .05. There appears to be a 

## 61 difference between response and/or variances among the dose 

## 62 levels, it seems appropriate to model the data. 

## 63 64 The p-value for Test 2 is greater than .1. A homogeneous 

## 65 variance model appears to be appropriate here. 

## 66 67 The p-value for Test 3 is greater than .1. The modeled 

## 68 variance appears to be appropriate here. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-142 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 1 describe the data; you may want to consider another model. 

## 2 3 4 Benchmark Dose Computations: 

## 5 6 Specified Effect = 1.000000 

## 7 8 Risk Type = Estimated standard deviations from control 

## 9 10
Confidence Level = 0.950000 

## 11 12
BMD = 3.73387 

## 13 14
BMDL = 2.78339 

## 15 16 17 H.3.2.4. Figure for Unrestricted Mode l: Hill, Constant Varian ce, n Restricted >1, Bound 18 Hit 19

5 10 15 20 25

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

13:43 11/23 2009 BMD BMDL Hill



## 20 21 22 H.3.2.5. Output File for Unrestricted Model: Hil l, Constant Variance, n Restricted >1, 23 Bound Hit 24 25 26

==================================================================== 

## 27 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 28 Input Data File: C:\USEPA\BMDS21\Nov23\Hill_CV_BMR1_DNA_SSB.(d) 

## 29 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Hill_CV_BMR1_DNA_SSB.plt 

## 30
Mon Nov 23 13:43:57 2009 

## 31

==================================================================== 

## 32 33 DNA single-strand breaks, liver only (Table 3) 

## 34

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-143 The form of the response function is: 

## 1 2 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 3 4 5 Dependent variable = Mean 

## 6 Independent variable = Dose 

## 7 rho is set to 0 

## 8 Power parameter restricted to be greater than 1 

## 9
A constant variance model is fit 

## 10 11 Total number of dose groups = 6 

## 12 Total number of records with missing values = 0 

## 13
Maximum number of iterations = 250 

## 14 Relative Function Convergence has been set to: 1e-008 

## 15 Parameter Convergence has been set to: 1e-008 

## 16 17 18 19
Default Initial Parameter Values 

## 20 alpha = 2.7831 

## 21 rho = 0 Specified 

## 22 intercept = 7.41 

## 23
v = 16.09 

## 24
n = 0.174831 

## 25
k = 69.2706 

## 26 27 28 Asymptotic Correlation Matrix of Parameter Estimates 

## 29 30 ( *** The model parameter(s) -rho -n 

## 31 have been estimated at a boundary point, or have been specified by the user, 

## 32 and do not appear in the correlation matrix ) 

## 33 34 alpha intercept v k 

## 35 36 alpha 1 1.1e-007 1.9e-007 1.9e-007 

## 37 38 intercept 1.1e-007 1 0.099 0.61 

## 39 40
v 1.9e-007 0.099 1 0.79 

## 41 42
k 1.9e-007 0.61 0.79 1 

## 43 44 45 46
Parameter Estimates 

## 47 48
95.0% Wald Confidence Interval 

## 49 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 50 alpha 2.82659 0.666233 1.5208 4.13238 

## 51 intercept 8.16404 0.581043 7.02522 9.30286 

## 52
v 20.1253 1.69013 16.8127 23.4379 

## 53
n 1 NA 

## 54
k 31.702 8.35815 15.3203 48.0836 

## 55 56 NA - Indicates that this parameter has hit a bound 

## 57 implied by some inequality constraint and thus 

## 58
has no standard error. 

## 59 60 61 62
Table of Data and Estimated Values of Interest 

## 63 64
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 65

------ --- -------- -------- ----------- ----------- ---------- 

## 66 67
0 6 7.41 8.16 1.54 1.68 -1.1 

## 68
3 6 10.8 9.9 1.25 1.68 1.28 

## 69
10 6 13.6 13 1.69 1.68 0.889 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-144 22 6 15.3 16.4 1.71 1.68 -1.62 

## 1
46 6 20.4 20.1 2.25 1.68 0.469 

## 2
100 6 23.5 23.4 1.37 1.68 0.0802 

## 3 4 5 6 Model Descriptions for likelihoods calculated 

## 7 8 9 Model A1: Yij = Mu(i) + e(ij) 

## 10 Var{e(ij)} = Sigma^2 

## 11 12 Model A2: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma(i)^2 

## 14 15 Model A3: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma^2 

## 17 Model A3 uses any fixed variance parameters that 

## 18 were specified by the user 

## 19 20 Model R: Yi = Mu + e(i) 

## 21 Var{e(i)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) # Param's AIC 

## 27
A1 -33.142389 7 80.284779 

## 28
A2 -31.811970 12 87.623940 

## 29
A3 -33.142389 7 80.284779 

## 30
fitted -36.703273 4 81.406545 

## 31
R -80.442086 2 164.884172 

## 32 33 34 Explanation of Tests 

## 35 36 Test 1: Do responses and/or variances differ among Dose levels? 

## 37 (A2 vs. R) 

## 38 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 39 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 40 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 41 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 42 43
Tests of Interest 

## 44 45 Test -2*log(Likelihood Ratio) Test df p-value 

## 46 47
Test 1 97.2602 10 <.0001 

## 48
Test 2 2.66084 5 0.7521 

## 49
Test 3 2.66084 5 0.7521 

## 50
Test 4 7.12177 3 0.06812 

## 51 52 The p-value for Test 1 is less than .05. There appears to be a 

## 53 difference between response and/or variances among the dose levels 

## 54 It seems appropriate to model the data 

## 55 56 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 57 model appears to be appropriate here 

## 58 59 60 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 61 to be appropriate here 

## 62 63 The p-value for Test 4 is less than .1. You may want to try a different 

## 64
model 

## 65 66 67 Benchmark Dose Computation 

## 68 69 Specified effect = 1 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-145 1 Risk Type = Estimated standard deviations from the control mean 

## 2 3
Confidence level = 0.95 

## 4 5
BMD = 2.88976 

## 6 7
BMDL = 2.00669 

## 8 9 10 11 H.3.2.6. Figure for Unrestricted Model: Hill, Constant Variance, n Unrestricted 12

5 10 15 20 25

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Hill



## 13 14 15 H.3.2.7. Output File for Unrestricted Model: Hill, Constant Variance, n Unrestricted 16 17 18

==================================================================== 

## 19 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 20 Input Data File: C:\USEPA\BMDS21\Nov23\Hill_CV_Unrest_BMR1_DNA_SSB.(d) 

## 21 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Hill_CV_Unrest_BMR1_DNA_SSB.plt 

## 22
Mon Nov 23 13:44:03 2009 

## 23

==================================================================== 

## 24 25 DNA single-strand breaks, liver only (Table 3) 

## 26

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 27 28 The form of the response function is: 

## 29 30 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 31 32 33 Dependent variable = Mean 

## 34 Independent variable = Dose 

## 35
rho is set to 0 

## 36 Power parameter is not restricted 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-146 A constant variance model is fit 

## 1 2 Total number of dose groups = 6 

## 3 Total number of records with missing values = 0 

## 4
Maximum number of iterations = 250 

## 5 Relative Function Convergence has been set to: 1e-008 

## 6 Parameter Convergence has been set to: 1e-008 

## 7 8 9 10
Default Initial Parameter Values 

## 11 alpha = 2.7831 

## 12 rho = 0 Specified 

## 13 intercept = 7.41 

## 14
v = 16.09 

## 15
n = 0.174831 

## 16
k = 69.2706 

## 17 18 19 Asymptotic Correlation Matrix of Parameter Estimates 

## 20 21 ( *** The model parameter(s) -rho 

## 22 have been estimated at a boundary point, or have been specified by the user, 

## 23 and do not appear in the correlation matrix ) 

## 24 25 alpha intercept v n k 

## 26 27 alpha 1 -2.2e-008 -4.6e-008 8.4e-009 -4.3e-008 

## 28 29 intercept -2.2e-008 1 -0.33 0.47 -0.29 

## 30 31
v -4.6e-008 -0.33 1 -0.95 1 

## 32 33
n 8.4e-009 0.47 -0.95 1 -0.96 

## 34 35
k -4.3e-008 -0.29 1 -0.96 1 

## 36 37 38 39
Parameter Estimates 

## 40 41
95.0% Wald Confidence Interval 

## 42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 43 alpha 2.5942 0.611459 1.39576 3.79264 

## 44 intercept 7.47627 0.665055 6.17278 8.77975 

## 45
v 36.9014 25.5466 -13.1689 86.9718 

## 46
n 0.612877 0.190055 0.240376 0.985377 

## 47
k 148.104 303.532 -446.809 743.016 

## 48 49 50 51
Table of Data and Estimated Values of Interest 

## 52 53
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 54

------ --- -------- -------- ----------- ----------- ---------- 

## 55 56
0 6 7.41 7.48 1.54 1.61 -0.101 

## 57
3 6 10.8 10.6 1.25 1.61 0.313 

## 58
10 6 13.6 13.4 1.69 1.61 0.286 

## 59
22 6 15.3 16.2 1.71 1.61 -1.41 

## 60
46 6 20.4 19.6 2.25 1.61 1.24 

## 61
100 6 23.5 23.7 1.37 1.61 -0.33 

## 62 63 64 65 Model Descriptions for likelihoods calculated 

## 66 67 68 Model A1: Yij = Mu(i) + e(ij) 

## 69 Var{e(ij)} = Sigma^2 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-147 1 Model A2: Yij = Mu(i) + e(ij) 

## 2 Var{e(ij)} = Sigma(i)^2 

## 3 4 Model A3: Yij = Mu(i) + e(ij) 

## 5 Var{e(ij)} = Sigma^2 

## 6 Model A3 uses any fixed variance parameters that 

## 7 were specified by the user 

## 8 9 Model R: Yi = Mu + e(i) 

## 10 Var{e(i)} = Sigma^2 

## 11 12 13
Likelihoods of Interest 

## 14 15 Model Log(likelihood) # Param's AIC 

## 16
A1 -33.142389 7 80.284779 

## 17
A2 -31.811970 12 87.623940 

## 18
A3 -33.142389 7 80.284779 

## 19
fitted -35.159023 5 80.318046 

## 20
R -80.442086 2 164.884172 

## 21 22 23 Explanation of Tests 

## 24 25 Test 1: Do responses and/or variances differ among Dose levels? 

## 26 (A2 vs. R) 

## 27 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 28 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 29 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 30 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 31 32
Tests of Interest 

## 33 34 Test -2*log(Likelihood Ratio) Test df p-value 

## 35 36
Test 1 97.2602 10 <.0001 

## 37
Test 2 2.66084 5 0.7521 

## 38
Test 3 2.66084 5 0.7521 

## 39
Test 4 4.03327 2 0.1331 

## 40 41 The p-value for Test 1 is less than .05. There appears to be a 

## 42 difference between response and/or variances among the dose levels 

## 43 It seems appropriate to model the data 

## 44 45 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 46 model appears to be appropriate here 

## 47 48 49 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 50 to be appropriate here 

## 51 52 The p-value for Test 4 is greater than .1. The model chosen seems 

## 53 to adequately describe the data 

## 54 55 56 Benchmark Dose Computation 

## 57 58 Specified effect = 1 

## 59 60 Risk Type = Estimated standard deviations from the control mean 

## 61 62
Confidence level = 0.95 

## 63 64
BMD = 0.961789 

## 65 66
BMDL = 0.211403 

## 67 68

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-148 H.3.2.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 1

5 10 15 20 25

0 20 40 60 80 100Mean Response

dose Power Model with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Power



## 2 3 4 H.3.2.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 5 6 7

==================================================================== 

## 8 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 9 Input Data File: C:\USEPA\BMDS21\Nov23\Pwr_CV_Unrest_BMR1_DNA_SSB.(d) 

## 10 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Pwr_CV_Unrest_BMR1_DNA_SSB.plt 

## 11
Mon Nov 23 13:44:04 2009 

## 12

==================================================================== 

## 13 14 DNA single-strand breaks, liver only (Table 3) 

## 15

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 16 17 The form of the response function is: 

## 18 19 Y[dose] = control + slope * dose^power 

## 20 21 22 Dependent variable = Mean 

## 23 Independent variable = Dose 

## 24
rho is set to 0 

## 25 The power is not restricted 

## 26
A constant variance model is fit 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37 alpha = 2.7831 

## 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-149 rho = 0 Specified 

## 1
control = 7.41 

## 2 slope = 1.99047 

## 3 power = 0.4538 

## 4 5 6 Asymptotic Correlation Matrix of Parameter Estimates 

## 7 8 ( *** The model parameter(s) -rho 

## 9 have been estimated at a boundary point, or have been specified by the user, 

## 10 and do not appear in the correlation matrix ) 

## 11 12 alpha control slope power 

## 13 14 alpha 1 1e-010 3.4e-009 -3.5e-009 

## 15 16
control 1e-010 1 -0.79 0.66 

## 17 18 slope 3.4e-009 -0.79 1 -0.97 

## 19 20 power -3.5e-009 0.66 -0.97 1 

## 21 22 23 24
Parameter Estimates 

## 25 26
95.0% Wald Confidence Interval 

## 27 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 28 alpha 2.67247 0.629906 1.43787 3.90706 

## 29
control 7.29122 0.640201 6.03645 8.54599 

## 30 slope 2.31759 0.501503 1.33466 3.30051 

## 31 power 0.428335 0.0441267 0.341848 0.514821 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 6 7.41 7.29 1.54 1.63 0.178 

## 41
3 6 10.8 11 1.25 1.63 -0.332 

## 42
10 6 13.6 13.5 1.69 1.63 0.142 

## 43
22 6 15.3 16 1.71 1.63 -1.05 

## 44
46 6 20.4 19.2 2.25 1.63 1.74 

## 45
100 6 23.5 24 1.37 1.63 -0.678 

## 46 47 48 49 Model Descriptions for likelihoods calculated 

## 50 51 52 Model A1: Yij = Mu(i) + e(ij) 

## 53 Var{e(ij)} = Sigma^2 

## 54 55 Model A2: Yij = Mu(i) + e(ij) 

## 56 Var{e(ij)} = Sigma(i)^2 

## 57 58 Model A3: Yij = Mu(i) + e(ij) 

## 59 Var{e(ij)} = Sigma^2 

## 60 Model A3 uses any fixed variance parameters that 

## 61 were specified by the user 

## 62 63 Model R: Yi = Mu + e(i) 

## 64 Var{e(i)} = Sigma^2 

## 65 66 67
Likelihoods of Interest 

## 68 69 Model Log(likelihood) # Param's AIC 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-150 A1 -33.142389 7 80.284779 

## 1
A2 -31.811970 12 87.623940 

## 2
A3 -33.142389 7 80.284779 

## 3
fitted -35.694033 4 79.388067 

## 4
R -80.442086 2 164.884172 

## 5 6 7 Explanation of Tests 

## 8 9 Test 1: Do responses and/or variances differ among Dose levels? 

## 10 (A2 vs. R) 

## 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 15 16
Tests of Interest 

## 17 18 Test -2*log(Likelihood Ratio) Test df p-value 

## 19 20
Test 1 97.2602 10 <.0001 

## 21
Test 2 2.66084 5 0.7521 

## 22
Test 3 2.66084 5 0.7521 

## 23
Test 4 5.10329 3 0.1644 

## 24 25 The p-value for Test 1 is less than .05. There appears to be a 

## 26 difference between response and/or variances among the dose levels 

## 27 It seems appropriate to model the data 

## 28 29 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 30 model appears to be appropriate here 

## 31 32 33 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 34 to be appropriate here 

## 35 36 The p-value for Test 4 is greater than .1. The model chosen seems 

## 37 to adequately describe the data 

## 38 39 40 Benchmark Dose Computation 

## 41 42 Specified effect = 1 

## 43 44 Risk Type = Estimated standard deviations from the control mean 

## 45 46
Confidence level = 0.95 

## 47 48
BMD = 0.442709 

## 49 50 51
BMDL = 0.149473 

## 52 53

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-151 H.3.3. Hassoun et al. (2000): TBARs Liver 1
H.3.3.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 0.33 20.31 0.00 -4.29 7.0E+01 3.4E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 0.33 20.31 0.00 -4.29 7.0E+01 3.4E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 0.33 3.08 0.38 -19.53 4.3E+00 1.9E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.33 2.78 0.25 -17.82 5.5E+00 2.0E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.33 2.78 0.25 -17.82 5.5E+00 2.0E+00 nonconstant variance, power unrestricted

Hill 2 0.33 2.52 0.28 -18.08 5.7E+00 2.0E+00 nonconstant variance, n restricted >1

Hill 2 0.33 2.52 0.28 -18.08 5.7E+00 error nonconstant variance, n unrestricted

linear 4 0.33 19.16 0.00 -5.44 5.2E+01 2.2E+01 nonconstant variance

polynomial 4 0.33 19.16 0.00 -5.44 5.2E+01 2.2E+01 nonconstant variance

power 4 0.33 19.16 0.00 -5.44 5.2E+01 2.2E+01 nonconstant variance, power restricted ≥ 1, bound hit

power 3 0.33 8.22 0.04 -14.38 1.2E+00 5.2E-03 nonconstant variance, power unrestricted
exponential (M2) 4 0.33 20.40 0.00 -6.14 8.0E+01 5.3E+01 constant variance, power restricted ≥ 1
exponential (M3) 4 0.33 20.40 0.00 -6.14 8.0E+01 5.3E+01 constant variance, power restricted ≥ 1
exponential (M4) c 3 0.33 3.36 0.34 -21.18 4.9E+00 2.3E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.33 2.86 0.24 -19.68 6.7E+00 2.5E+00 constant variance, power restricted ≥ 1
exponential (M5) d 2 0.33 2.86 0.24 -19.68 6.7E+00 2.5E+00 constant variance, power unrestricted

Hill 2 0.33 2.61 0.27 -19.93 6.3E+00 2.6E+00 constant variance, n restricted >1

Hill d 2 0.33 2.61 0.27 -19.93 6.3E+00 2.6E+00 constant variance, n unrestricted

linear 4 0.33 19.52 0.00 -7.02 6.9E+01 4.4E+01 constant variance

polynomial 4 0.33 19.52 0.00 -7.02 6.9E+01 4.4E+01 constant variance

power 4 0.33 19.52 0.00 -7.02 6.9E+01 4.4E+01 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-152 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power d 3 0.33 9.55 0.02 -14.99 2.9E+00 6.1E-02 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.3.2. Figure for Selected Model: Exponential (M 4), Constant Variance, Power Restricted 3 ≥ 1 4

1 1.5

2 2.5

3

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Exponential



## 5 6 7 H.3.3.3. Output File for Selected Model: Expo nential (M4), Constant Variance, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov23\Exp_CV_BMR1_TBARs_Liver.(d) 

## 14 Gnuplot Plotting File: 

## 15
Mon Nov 23 13:44:41 2009 

## 16

==================================================================== 

## 17 18 TBARs, liver only (Table 2) 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-153 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18
rho is set to 0. 

## 19
A constant variance model is fit. 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 4 

## 33

-------- -------- 

## 34 lnalpha -1.90388 

## 35 rho(S) 0 

## 36
a 1.39555 

## 37
b 0.0194898 

## 38
c 1.97051 

## 39
d 1 

## 40 41 (S) = Specified 

## 42 43 44 45
Parameter Estimates 

## 46 47
Variable Model 4 

## 48

-------- ------- 

## 49 lnalpha -1.82448 

## 50
rho 0 

## 51
a 1.46519 

## 52
b 0.113543 

## 53
c 1.63661 

## 54
d 2.13652 

## 55 56 57 Table of Stats From Input Data 

## 58 59
Dose N Obs Mean Obs Std Dev 

## 60

----- --- ---------- ------------- 

## 61
0 6 1.469 0.2915 

## 62
3 6 1.549 0.5389 

## 63
10 6 2.15 0.3625 

## 64
22 6 2.28 0.2474 

## 65
46 6 2.619 0.5168 

## 66
100 6 2.292 0.4874 

## 67 68 69
Estimated Values of Interest 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-154 1
Dose Est Mean Est Std Scaled Residual 

## 2

------ ---------- --------- ---------------- 

## 3
0 1.404 0.4044 0.3915 

## 4
3 1.674 0.4044 -0.7582 

## 5
10 2.063 0.4044 0.527 

## 6
22 2.332 0.4044 -0.3134 

## 7
46 2.438 0.4044 1.099 

## 8
100 2.448 0.4044 -0.9458 

## 9 10 11 12
Other models for which likelihoods are calculated: 

## 13 14 Model A1: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma^2 

## 16 17 Model A2: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = Sigma(i)^2 

## 19 20 Model A3: Yij = Mu(i) + e(ij) 

## 21 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 22 23 Model R: Yij = Mu + e(i) 

## 24 Var{e(ij)} = Sigma^2 

## 25 26 27
Likelihoods of Interest 

## 28 29 Model Log(likelihood) DF AIC 

## 30

------- ----------------- ---- ------------ 

## 31
A1 16.26977 7 -18.53954 

## 32
A2 19.12783 12 -14.25565 

## 33
A3 16.26977 7 -18.53954 

## 34
R 2.44294 2 -0.8858799 

## 35
4 14.5907 4 -21.18141 

## 36 37 38 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 39 above values gives the log-likelihood including the term that does not 

## 40 depend on the model parameters. 

## 41 42 43 Explanation of Tests 

## 44 45 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 46 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 47 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 48 49 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 50 51 52
Tests of Interest 

## 53 54 Test -2*log(Likelihood Ratio) D. F. p-value 

## 55

-------- ------------------------ ------ -------------- 

## 56
Test 1 33.37 10 0.000236 

## 57
Test 2 5.716 5 0.3348 

## 58
Test 3 5.716 5 0.3348 

## 59
Test 6a 3.358 3 0.3396 

## 60 61 62 The p-value for Test 1 is less than .05. There appears to be a 

## 63 difference between response and/or variances among the dose 

## 64 levels, it seems appropriate to model the data. 

## 65 66 The p-value for Test 2 is greater than .1. A homogeneous 

## 67 variance model appears to be appropriate here. 

## 68 69 The p-value for Test 3 is greater than .1. The modeled 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-155 variance appears to be appropriate here. 

## 1 2 The p-value for Test 6a is greater than .1. Model 4 seems 

## 3 to adequately describe the data. 

## 4 5 6 Benchmark Dose Computations: 

## 7 8 Specified Effect = 1.000000 

## 9 10 Risk Type = Estimated standard deviations from control 

## 11 12
Confidence Level = 0.950000 

## 13 14
BMD = 4.91639 

## 15 16
BMDL = 2.29952 

## 17 18 19 H.3.3.4. Figure for Unrestricted Model: Expon ential (M5), Constant Variance, Power 20 Unrestricted 21

1 1.5

2 2.5

3

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Exponential



## 22 23 24 H.3.3.5. Output File for Unrestricted Model: Exponential (M5), Con stant Variance, Power 25 Unrestricted 26 27 28

==================================================================== 

## 29 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 30 Input Data File: C:\USEPA\BMDS21\Nov23\Exp_CV_Unrest_BMR1_TBARs_Liver.(d) 

## 31 Gnuplot Plotting File: 

## 32
Mon Nov 23 13:44:47 2009 

## 33

==================================================================== 

## 34 35 TBARs, liver only (Table 2) 

## 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-156 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 1 2 The form of the response function by Model: 

## 3 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 4 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 5 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 6 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 7 8 Note: Y[dose] is the median response for exposure = dose; 

## 9 sign = +1 for increasing trend in data; 

## 10 sign = -1 for decreasing trend. 

## 11 12
Model 2 is nested within Models 3 and 4. 

## 13
Model 3 is nested within Model 5. 

## 14
Model 4 is nested within Model 5. 

## 15 16 17 Dependent variable = Mean 

## 18 Independent variable = Dose 

## 19 Data are assumed to be distributed: normally 

## 20 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 21
rho is set to 0. 

## 22
A constant variance model is fit. 

## 23 24 Total number of dose groups = 6 

## 25 Total number of records with missing values = 0 

## 26
Maximum number of iterations = 250 

## 27 Relative Function Convergence has been set to: 1e-008 

## 28 Parameter Convergence has been set to: 1e-008 

## 29 30 MLE solution provided: Exact 

## 31 32 33
Initial Parameter Values 

## 34 35
Variable Model 5 

## 36

-------- -------- 

## 37 lnalpha -1.90388 

## 38 rho(S) 0 

## 39
a 1.39555 

## 40
b 0.0194898 

## 41
c 1.97051 

## 42
d 1 

## 43 44 (S) = Specified 

## 45 46 47 48
Parameter Estimates 

## 49 50
Variable Model 5 

## 51

-------- ------- 

## 52 lnalpha -1.82448 

## 53
rho 0 

## 54
a 1.46519 

## 55
b 0.113543 

## 56
c 1.63661 

## 57
d 2.13652 

## 58 59 60 Table of Stats From Input Data 

## 61 62
Dose N Obs Mean Obs Std Dev 

## 63

----- --- ---------- ------------- 

## 64
0 6 1.469 0.2915 

## 65
3 6 1.549 0.5389 

## 66
10 6 2.15 0.3625 

## 67
22 6 2.28 0.2474 

## 68
46 6 2.619 0.5168 

## 69
100 6 2.292 0.4874 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-157 1 2
Estimated Values of Interest 

## 3 4
Dose Est Mean Est Std Scaled Residual 

## 5

------ ---------- --------- ---------------- 

## 6
0 1.465 0.4016 0.02326 

## 7
3 1.554 0.4016 -0.03103 

## 8
10 2.147 0.4016 0.02011 

## 9
22 2.397 0.4016 -0.7145 

## 10
46 2.398 0.4016 1.348 

## 11
100 2.398 0.4016 -0.6461 

## 12 13 14 15
Other models for which likelihoods are calculated: 

## 16 17 Model A1: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = Sigma^2 

## 19 20 Model A2: Yij = Mu(i) + e(ij) 

## 21 Var{e(ij)} = Sigma(i)^2 

## 22 23 Model A3: Yij = Mu(i) + e(ij) 

## 24 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 25 26 Model R: Yij = Mu + e(i) 

## 27 Var{e(ij)} = Sigma^2 

## 28 29 30
Likelihoods of Interest 

## 31 32 Model Log(likelihood) DF AIC 

## 33

------- ----------------- ---- ------------ 

## 34
A1 16.26977 7 -18.53954 

## 35
A2 19.12783 12 -14.25565 

## 36
A3 16.26977 7 -18.53954 

## 37
R 2.44294 2 -0.8858799 

## 38
5 14.8407 5 -19.68141 

## 39 40 41 Additive constant for all log-likelihoods = -33.08. This constant added to the 

## 42 above values gives the log-likelihood including the term that does not 

## 43 depend on the model parameters. 

## 44 45 46 Explanation of Tests 

## 47 48 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 49 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 50 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 51 52 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 53 54 55
Tests of Interest 

## 56 57 Test -2*log(Likelihood Ratio) D. F. p-value 

## 58

-------- ------------------------ ------ -------------- 

## 59
Test 1 33.37 10 0.000236 

## 60
Test 2 5.716 5 0.3348 

## 61
Test 3 5.716 5 0.3348 

## 62
Test 7a 2.858 2 0.2395 

## 63 64 65 The p-value for Test 1 is less than .05. There appears to be a 

## 66 difference between response and/or variances among the dose 

## 67 levels, it seems appropriate to model the data. 

## 68 69 The p-value for Test 2 is greater than .1. A homogeneous 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-158 variance model appears to be appropriate here. 

## 1 2 The p-value for Test 3 is greater than .1. The modeled 

## 3 variance appears to be appropriate here. 

## 4 5 The p-value for Test 7a is greater than .1. Model 5 seems 

## 6 to adequately describe the data. 

## 7 8 9 Benchmark Dose Computations: 

## 10 11 Specified Effect = 1.000000 

## 12 13 Risk Type = Estimated standard deviations from control 

## 14 15
Confidence Level = 0.950000 

## 16 17
BMD = 6.73152 

## 18 19
BMDL = 2.47029 

## 20 21 22 H.3.3.6. Figure for Unrestricted Model: Hill, Constant Variance, n Unrestricted 23

1 1.5

2 2.5

3

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Hill



## 24 25 26 H.3.3.7. Output File for Unrestricted Model: Hill, Constant Variance, n Unrestricted 27 28 29

==================================================================== 

## 30 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 31 Input Data File: C:\USEPA\BMDS21\Nov23\Hill_CV_Unrest_BMR1_TBARs_Liver.(d) 

## 32 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Hill_CV_Unrest_BMR1_TBARs_Liver.plt 

## 33
Mon Nov 23 13:44:49 2009 

## 34

==================================================================== 

## 35 36 TBARs, liver only (Table 2) 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-159 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 1 2 The form of the response function is: 

## 3 4 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 5 6 7 Dependent variable = Mean 

## 8 Independent variable = Dose 

## 9
rho is set to 0 

## 10 Power parameter is not restricted 

## 11
A constant variance model is fit 

## 12 13 Total number of dose groups = 6 

## 14 Total number of records with missing values = 0 

## 15
Maximum number of iterations = 250 

## 16 Relative Function Convergence has been set to: 1e-008 

## 17 Parameter Convergence has been set to: 1e-008 

## 18 19 20 21
Default Initial Parameter Values 

## 22 alpha = 0.178788 

## 23 rho = 0 Specified 

## 24 intercept = 1.469 

## 25
v = 1.15 

## 26
n = 0.921061 

## 27
k = 11.2346 

## 28 29 30 Asymptotic Correlation Matrix of Parameter Estimates 

## 31 32 ( *** The model parameter(s) -rho 

## 33 have been estimated at a boundary point, or have been specified by the user, 

## 34 and do not appear in the correlation matrix ) 

## 35 36 alpha intercept v n k 

## 37 38 alpha 1 4.6e-010 -1.2e-008 2.8e-009 3.8e-009 

## 39 40 intercept 4.6e-010 1 -0.82 0.48 0.52 

## 41 42
v -1.2e-008 -0.82 1 -0.61 -0.22 

## 43 44
n 2.8e-009 0.48 -0.61 1 0.29 

## 45 46
k 3.8e-009 0.52 -0.22 0.29 1 

## 47 48 49 50
Parameter Estimates 

## 51 52
95.0% Wald Confidence Interval 

## 53 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 54 alpha 0.160182 0.0377552 0.0861829 0.23418 

## 55 intercept 1.4615 0.152914 1.16179 1.76121 

## 56
v 0.962989 0.202872 0.565367 1.36061 

## 57
n 2.4861 1.76422 -0.971707 5.94391 

## 58
k 7.18099 2.79941 1.69424 12.6677 

## 59 60 61 62
Table of Data and Estimated Values of Interest 

## 63 64
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 65

------ --- -------- -------- ----------- ----------- ---------- 

## 66 67
0 6 1.47 1.46 0.291 0.4 0.0459 

## 68
3 6 1.55 1.56 0.539 0.4 -0.0685 

## 69
10 6 2.15 2.13 0.363 0.4 0.118 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-160 22 6 2.28 2.37 0.247 0.4 -0.541 

## 1
46 6 2.62 2.42 0.517 0.4 1.25 

## 2
100 6 2.29 2.42 0.487 0.4 -0.802 

## 3 4 5 6 Model Descriptions for likelihoods calculated 

## 7 8 9 Model A1: Yij = Mu(i) + e(ij) 

## 10 Var{e(ij)} = Sigma^2 

## 11 12 Model A2: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma(i)^2 

## 14 15 Model A3: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma^2 

## 17 Model A3 uses any fixed variance parameters that 

## 18 were specified by the user 

## 19 20 Model R: Yi = Mu + e(i) 

## 21 Var{e(i)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) # Param's AIC 

## 27
A1 16.269770 7 -18.539539 

## 28
A2 19.127827 12 -14.255654 

## 29
A3 16.269770 7 -18.539539 

## 30
fitted 14.966039 5 -19.932079 

## 31
R 2.442940 2 -0.885880 

## 32 33 34 Explanation of Tests 

## 35 36 Test 1: Do responses and/or variances differ among Dose levels? 

## 37 (A2 vs. R) 

## 38 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 39 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 40 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 41 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 42 43
Tests of Interest 

## 44 45 Test -2*log(Likelihood Ratio) Test df p-value 

## 46 47
Test 1 33.3698 10 0.000236 

## 48
Test 2 5.71611 5 0.3348 

## 49
Test 3 5.71611 5 0.3348 

## 50
Test 4 2.60746 2 0.2715 

## 51 52 The p-value for Test 1 is less than .05. There appears to be a 

## 53 difference between response and/or variances among the dose levels 

## 54 It seems appropriate to model the data 

## 55 56 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 57 model appears to be appropriate here 

## 58 59 60 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 61 to be appropriate here 

## 62 63 The p-value for Test 4 is greater than .1. The model chosen seems 

## 64 to adequately describe the data 

## 65 66 67 Benchmark Dose Computation 

## 68 69 Specified effect = 1 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-161 1 Risk Type = Estimated standard deviations from the control mean 

## 2 3
Confidence level = 0.95 

## 4 5
BMD = 6.26103 

## 6 7
BMDL = 2.57465 

## 8 9 10 H.3.3.8. Figure for Unrestricted Model: Power, Constant Variance, Power Unrestricted 11

1 1.5

2 2.5

3

0 20 40 60 80 100Mean Response

dose Power Model with 0.95 Confidence Level

13:44 11/23 2009 BMD BMDL Power



## 12 13 14 H.3.3.9. Output File for Unrestricted Model: Powe r, Constant Varia nce, Power Unrestricted 15 16 17

==================================================================== 

## 18 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 19 Input Data File: C:\USEPA\BMDS21\Nov23\Pwr_CV_Unrest_BMR1_TBARs_Liver.(d) 

## 20 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov23\Pwr_CV_Unrest_BMR1_TBARs_Liver.plt 

## 21
Mon Nov 23 13:44:49 2009 

## 22

==================================================================== 

## 23 24 TBARs, liver only (Table 2) 

## 25

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 26 27 The form of the response function is: 

## 28 29 Y[dose] = control + slope * dose^power 

## 30 31 32 Dependent variable = Mean 

## 33 Independent variable = Dose 

## 34
rho is set to 0 

## 35 The power is not restricted 

## 36
A constant variance model is fit 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-162 1 Total number of dose groups = 6 

## 2 Total number of records with missing values = 0 

## 3
Maximum number of iterations = 250 

## 4 Relative Function Convergence has been set to: 1e-008 

## 5 Parameter Convergence has been set to: 1e-008 

## 6 7 8 9
Default Initial Parameter Values 

## 10 alpha = 0.178788 

## 11 rho = 0 Specified 

## 12
control = 1.469 

## 13 slope = 0.0756538 

## 14 power = 0.652114 

## 15 16 17 Asymptotic Correlation Matrix of Parameter Estimates 

## 18 19 ( *** The model parameter(s) -rho 

## 20 have been estimated at a boundary point, or have been specified by the user, 

## 21 and do not appear in the correlation matrix ) 

## 22 23 alpha control slope power 

## 24 25 alpha 1 1.1e-008 -1.1e-009 -1.5e-008 

## 26 27
control 1.1e-008 1 -0.75 0.47 

## 28 29 slope -1.1e-009 -0.75 1 -0.91 

## 30 31 power -1.5e-008 0.47 -0.91 1 

## 32 33 34 35
Parameter Estimates 

## 36 37
95.0% Wald Confidence Interval 

## 38 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 39 alpha 0.194232 0.0457809 0.104503 0.283961 

## 40
control 1.42104 0.171077 1.08573 1.75634 

## 41 slope 0.333105 0.166768 0.00624603 0.659963 

## 42 power 0.262735 0.0983956 0.0698836 0.455587 

## 43 44 45 46
Table of Data and Estimated Values of Interest 

## 47 48
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 49

------ --- -------- -------- ----------- ----------- ---------- 

## 50 51
0 6 1.47 1.42 0.291 0.441 0.267 

## 52
3 6 1.55 1.87 0.539 0.441 -1.76 

## 53
10 6 2.15 2.03 0.363 0.441 0.661 

## 54
22 6 2.28 2.17 0.247 0.441 0.603 

## 55
46 6 2.62 2.33 0.517 0.441 1.6 

## 56
100 6 2.29 2.54 0.487 0.441 -1.37 

## 57 58 59 60 Model Descriptions for likelihoods calculated 

## 61 62 63 Model A1: Yij = Mu(i) + e(ij) 

## 64 Var{e(ij)} = Sigma^2 

## 65 66 Model A2: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma(i)^2 

## 68 69 Model A3: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-163 Var{e(ij)} = Sigma^2 

## 1 Model A3 uses any fixed variance parameters that 

## 2 were specified by the user 

## 3 4 Model R: Yi = Mu + e(i) 

## 5 Var{e(i)} = Sigma^2 

## 6 7 8
Likelihoods of Interest 

## 9 10 Model Log(likelihood) # Param's AIC 

## 11
A1 16.269770 7 -18.539539 

## 12
A2 19.127827 12 -14.255654 

## 13
A3 16.269770 7 -18.539539 

## 14
fitted 11.496634 4 -14.993268 

## 15
R 2.442940 2 -0.885880 

## 16 17 18 Explanation of Tests 

## 19 20 Test 1: Do responses and/or variances differ among Dose levels? 

## 21 (A2 vs. R) 

## 22 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 23 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 24 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 25 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 26 27
Tests of Interest 

## 28 29 Test -2*log(Likelihood Ratio) Test df p-value 

## 30 31
Test 1 33.3698 10 0.000236 

## 32
Test 2 5.71611 5 0.3348 

## 33
Test 3 5.71611 5 0.3348 

## 34
Test 4 9.54627 3 0.02284 

## 35 36 The p-value for Test 1 is less than .05. There appears to be a 

## 37 difference between response and/or variances among the dose levels 

## 38 It seems appropriate to model the data 

## 39 40 The p-value for Test 2 is greater than .1. A homogeneous variance 

## 41 model appears to be appropriate here 

## 42 43 44 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 45 to be appropriate here 

## 46 47 The p-value for Test 4 is less than .1. You may want to try a different 

## 48
model 

## 49 50 51 Benchmark Dose Computation 

## 52 53 Specified effect = 1 

## 54 55 Risk Type = Estimated standard deviations from the control mean 

## 56 57 Confidence level = 0.95 

## 58 59
BMD = 2.90232 

## 60 61 62
BMDL = 0.0614971 

## 63 64

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-164 H.3.4. Kitchin et al. (1979): BaP Hydrolase Activity 1
H.3.4.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 9 <0.0001 247.00 <0.0001 452.67 2.6E+03 1.2E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 9 <0.0001 247.00 <0.0001 452.67 2.6E+03 1.2E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 8 <0.0001 18.96 0.02 226.60 1.8E+00 1.4E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) c 7 <0.0001 16.75 0.02 226.40 3.4E+00 1.6E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) d 7 <0.0001 16.75 0.02 226.40 3.4E+00 1.6E+00 nonconstant variance, power unrestricted

Hill 7 <.0001 296.88 <.0001 506.53 error error nonconstant variance, n restricted >1

Hill d 7 <.0001 296.88 <.0001 506.53 error error nonconstant variance, n unrestricted

linear 9 <.0001 94.11 <.0001 299.75 2.8E+00 2.0E+00 nonconstant variance

polynomial 9 <.0001 -197.64 <.0001 8.00 error error nonconstant variance

power 9 <.0001 94.11 <.0001 299.75 2.8E+00 2.0E+00 nonconstant variance, power restricted ≥ 1, bound hit

power d 8 <.0001 63.59 <.0001 271.23 3.0E-01 1.3E-01 nonconstant variance, power unrestricted
exponential (M2) 9 <0.0001 129.40 <0.0001 451.61 3.6E+03 3.1E+03 constant variance, power restricted ≥ 1
exponential (M3) 9 <0.0001 129.40 <0.0001 451.61 3.6E+03 3.1E+03 constant variance, power restricted ≥ 1
exponential (M4) 8 <0.0001 6.93 0.54 331.19 2.7E+01 2.1E+01 constant variance, power restricted ≥ 1
exponential (M5) 8 <0.0001 6.93 0.54 331.19 2.7E+01 2.1E+01 constant variance, power restricted ≥ 1
exponential (M5) 8 <0.0001 6.93 0.54 331.19 2.7E+01 2.1E+01 constant variance, power unrestricted

Hill 7 <.0001 67.64 <.0001 393.90 5.7E+02 5.2E+00 constant variance, n restricted >1

Hill 7 <.0001 2.70 0.91 328.96 2.0E+01 1.1E+01 constant variance, n unrestricted

linear 9 <.0001 120.31 <.0001 442.57 1.9E+03 1.4E+03 constant variance

polynomial 9 <.0001 120.31 <.0001 442.57 1.9E+03 1.4E+03 constant variance

power 9 <.0001 120.31 <.0001 442.57 1.9E+03 1.4E+03 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-165 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 8 <.0001 51.05 <.0001 375.31 1.2E+00 2.5E-01 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.4.2. Figure for Selected Model: Exponen tial (M5), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 50 100 150 200 250

0 1000 2000 3000 4000 5000 6000 7000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:26 11/20 2009 BMDBMDL Exponential



## 5 6 7 H.3.4.3. Output File for Selected Model: Expo nential (M5), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_BaP_hydro_act.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 14:26:45 2009 

## 16

==================================================================== 

## 17 18 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-166 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 11 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 5 

## 32

-------- -------- 

## 33 lnalpha -3.27793 

## 34
rho 1.92227 

## 35
a 4.655 

## 36
b 0.000532066 

## 37
c 42.6316 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 5 

## 45

-------- ------- 

## 46 lnalpha -2.6425 

## 47
rho 1.93734 

## 48
a 5.43493 

## 49
b 0.00574894 

## 50
c 31.1998 

## 51
d 1.21529 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 9 4.9 1.11 

## 59
0.2 4 4.9 1.18 

## 60
0.667 4 6.7 1.4 

## 61
1.33 4 7.2 1.8 

## 62
6.67 4 8.3 0.26 

## 63
20 4 14 5 

## 64
66.7 4 59 6.8 

## 65
200 4 96 46 

## 66
667 4 155 16.4 

## 67
1670 4 182 26 

## 68
6670 4 189 26 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-167 1
Estimated Values of Interest 

## 2 3
Dose Est Mean Est Std Scaled Residual 

## 4

------ ---------- --------- ---------------- 

## 5
0 5.435 1.375 -1.167 

## 6
0.2 5.479 1.386 -0.8354 

## 7
0.667 5.625 1.422 1.513 

## 8
1.33 5.874 1.483 1.789 

## 9
6.67 8.524 2.127 -0.211 

## 10
20 16.86 4.118 -1.391 

## 11
66.7 49.42 11.67 1.642 

## 12
200 119.4 27.42 -1.705 

## 13
667 168.6 38.31 -0.7095 

## 14
1670 169.6 38.52 0.6454 

## 15
6670 169.6 38.52 1.009 

## 16 17 18 19
Other models for which likelihoods are calculated: 

## 20 21 Model A1: Yij = Mu(i) + e(ij) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 Model A2: Yij = Mu(i) + e(ij) 

## 25 Var{e(ij)} = Sigma(i)^2 

## 26 27 Model A3: Yij = Mu(i) + e(ij) 

## 28 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 29 30 Model R: Yij = Mu + e(i) 

## 31 Var{e(ij)} = Sigma^2 

## 32 33 34
Likelihoods of Interest 

## 35 36 Model Log(likelihood) DF AIC 

## 37

------- ----------------- ---- ------------ 

## 38
A1 -158.1306 12 340.2613 

## 39
A2 -84.80028 22 213.6006 

## 40
A3 -98.82189 13 223.6438 

## 41
R -234.6252 2 473.2504 

## 42
5 -107.1994 6 226.3987 

## 43 44 45 Additive constant for all log-likelihoods = -45.03. This constant added to the 

## 46 above values gives the log-likelihood including the term that does not 

## 47 depend on the model parameters. 

## 48 49 50 Explanation of Tests 

## 51 52 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 53 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 54 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 55 56 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 57 58 59
Tests of Interest 

## 60 61 Test -2*log(Likelihood Ratio) D. F. p-value 

## 62

-------- ------------------------ ------ -------------- 

## 63
Test 1 299.6 20 < 0.0001 

## 64
Test 2 146.7 10 < 0.0001 

## 65
Test 3 28.04 9 0.0009381 

## 66
Test 7a 16.75 7 0.01905 

## 67 68 69 The p-value for Test 1 is less than .05. There appears to be a 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-168 difference between response and/or variances among the dose 

## 1 levels, it seems appropriate to model the data. 

## 2 3 The p-value for Test 2 is less than .1. A non-homogeneous 

## 4 variance model appears to be appropriate. 

## 5 6 The p-value for Test 3 is less than .1. You may want to 

## 7 consider a different variance model. 

## 8 9 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 10 describe the data; you may want to consider another model. 

## 11 12 13 Benchmark Dose Computations: 

## 14 15 Specified Effect = 1.000000 

## 16 17 Risk Type = Estimated standard deviations from control 

## 18 19
Confidence Level = 0.950000 

## 20 21
BMD = 3.41185 

## 22 23
BMDL = 1.60436 

## 24 25 26 H.3.4.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 27 Unrestricted 28

0 50 100 150 200 250

0 1000 2000 3000 4000 5000 6000 7000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:27 11/20 2009 BMDBMDL Exponential



## 29 30 31 H.3.4.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 32 Power Unrestricted 33 34 35

==================================================================== 

## 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-169 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 1 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_Unrest_BMR1_BaP_hydro_act.(d) 

## 2 Gnuplot Plotting File: 

## 3
Fri Nov 20 14:27:02 2009 

## 4

==================================================================== 

## 5 6 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 7

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 8 9 The form of the response function by Model: 

## 10 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 11 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 12 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 13 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 14 15 Note: Y[dose] is the median response for exposure = dose; 

## 16 sign = +1 for increasing trend in data; 

## 17 sign = -1 for decreasing trend. 

## 18 19
Model 2 is nested within Models 3 and 4. 

## 20
Model 3 is nested within Model 5. 

## 21
Model 4 is nested within Model 5. 

## 22 23 24 Dependent variable = Mean 

## 25 Independent variable = Dose 

## 26 Data are assumed to be distributed: normally 

## 27 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 28 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 29 30 Total number of dose groups = 11 

## 31 Total number of records with missing values = 0 

## 32
Maximum number of iterations = 250 

## 33 Relative Function Convergence has been set to: 1e-008 

## 34 Parameter Convergence has been set to: 1e-008 

## 35 36 MLE solution provided: Exact 

## 37 38 39
Initial Parameter Values 

## 40 41
Variable Model 5 

## 42

-------- -------- 

## 43 lnalpha -3.27793 

## 44
rho 1.92227 

## 45
a 4.655 

## 46
b 0.000532066 

## 47
c 42.6316 

## 48
d 1 

## 49 50 51 52
Parameter Estimates 

## 53 54
Variable Model 5 

## 55

-------- ------- 

## 56 lnalpha -2.6425 

## 57
rho 1.93734 

## 58
a 5.43493 

## 59
b 0.00574894 

## 60
c 31.1998 

## 61
d 1.21529 

## 62 63 64 Table of Stats From Input Data 

## 65 66
Dose N Obs Mean Obs Std Dev 

## 67

----- --- ---------- ------------- 

## 68
0 9 4.9 1.11 

## 69
0.2 4 4.9 1.18 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-170 0.667 4 6.7 1.4 

## 1
1.33 4 7.2 1.8 

## 2
6.67 4 8.3 0.26 

## 3
20 4 14 5 

## 4
66.7 4 59 6.8 

## 5
200 4 96 46 

## 6
667 4 155 16.4 

## 7
1670 4 182 26 

## 8
6670 4 189 26 

## 9 10 11
Estimated Values of Interest 

## 12 13
Dose Est Mean Est Std Scaled Residual 

## 14

------ ---------- --------- ---------------- 

## 15
0 5.435 1.375 -1.167 

## 16
0.2 5.479 1.386 -0.8354 

## 17
0.667 5.625 1.422 1.513 

## 18
1.33 5.874 1.483 1.789 

## 19
6.67 8.524 2.127 -0.211 

## 20
20 16.86 4.118 -1.391 

## 21
66.7 49.42 11.67 1.642 

## 22
200 119.4 27.42 -1.705 

## 23
667 168.6 38.31 -0.7095 

## 24
1670 169.6 38.52 0.6454 

## 25
6670 169.6 38.52 1.009 

## 26 27 28 29
Other models for which likelihoods are calculated: 

## 30 31 Model A1: Yij = Mu(i) + e(ij) 

## 32 Var{e(ij)} = Sigma^2 

## 33 34 Model A2: Yij = Mu(i) + e(ij) 

## 35 Var{e(ij)} = Sigma(i)^2 

## 36 37 Model A3: Yij = Mu(i) + e(ij) 

## 38 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 39 40 Model R: Yij = Mu + e(i) 

## 41 Var{e(ij)} = Sigma^2 

## 42 43 44
Likelihoods of Interest 

## 45 46 Model Log(likelihood) DF AIC 

## 47

------- ----------------- ---- ------------ 

## 48
A1 -158.1306 12 340.2613 

## 49
A2 -84.80028 22 213.6006 

## 50
A3 -98.82189 13 223.6438 

## 51
R -234.6252 2 473.2504 

## 52
5 -107.1994 6 226.3987 

## 53 54 55 Additive constant for all log-likelihoods = -45.03. This constant added to the 

## 56 above values gives the log-likelihood including the term that does not 

## 57 depend on the model parameters. 

## 58 59 60 Explanation of Tests 

## 61 62 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 63 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 64 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 65 66 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 67 68 69
Tests of Interest 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-171 1 Test -2*log(Likelihood Ratio) D. F. p-value 

## 2

-------- ------------------------ ------ -------------- 

## 3
Test 1 299.6 20 < 0.0001 

## 4
Test 2 146.7 10 < 0.0001 

## 5
Test 3 28.04 9 0.0009381 

## 6
Test 7a 16.75 7 0.01905 

## 7 8 9 The p-value for Test 1 is less than .05. There appears to be a 

## 10 difference between response and/or variances among the dose 

## 11 levels, it seems appropriate to model the data. 

## 12 13 The p-value for Test 2 is less than .1. A non-homogeneous 

## 14 variance model appears to be appropriate. 

## 15 16 The p-value for Test 3 is less than .1. You may want to 

## 17
consider a different variance model. 

## 18 19 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 20 describe the data; you may want to consider another model. 

## 21 22 23 Benchmark Dose Computations: 

## 24 25 Specified Effect = 1.000000 

## 26 27 Risk Type = Estimated standard deviations from control 

## 28 29
Confidence Level = 0.950000 

## 30 31
BMD = 3.41185 

## 32 33
BMDL = 1.60436 

## 34 35 36 37 H.3.4.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 38

0 50 100 150 200 250

0 1000 2000 3000 4000 5000 6000 7000Mean Response

dose Hill Model

14:27 11/20 2009 BMD Hill



## 39

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-172 1 H.3.4.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 2 3 4

==================================================================== 

## 5 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 6 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_BaP_hydro_act.(d) 

## 7 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_BaP_hydro_act.plt 

## 8
Fri Nov 20 14:27:04 2009 

## 9

==================================================================== 

## 10 11 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 13 14 The form of the response function is: 

## 15 16 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 17 18 19 Dependent variable = Mean 

## 20 Independent variable = Dose 

## 21 Power parameter is not restricted 

## 22 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 23 24 Total number of dose groups = 11 

## 25 Total number of records with missing values = 0 

## 26
Maximum number of iterations = 250 

## 27 Relative Function Convergence has been set to: 1e-008 

## 28 Parameter Convergence has been set to: 1e-008 

## 29 30 31 32
Default Initial Parameter Values 

## 33 lalpha = 5.70855 

## 34
rho = 0 

## 35 intercept = 4.9 

## 36
v = 184.1 

## 37
n = 18 

## 38
k = 1126.48 

## 39 40 41 Asymptotic Correlation Matrix of Parameter Estimates 

## 42 43 lalpha rho intercept v n k 

## 44 45 lalpha NA NA NA NA NA NA 

## 46 47
rho NA NA NA NA NA NA 

## 48 49 intercept NA NA 1 -0.012 NA NA 

## 50 51
v NA NA -0.012 1 NA NA 

## 52 53

n NA NA NA NA NA NA 

## 54 55
k NA NA NA NA NA NA 

## 56 57 58 NA - This parameter's variance has been estimated as zero or less. 

## 59
THE MODEL HAS PROBABLY NOT CONVERGED!!! 

## 60 61 62 63
Parameter Estimates 

## 64 65
95.0% Wald Confidence Interval 

## 66 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 67 lalpha 8.0472 NA NA NA 

## 68
rho -0.0780259 NA NA NA 

## 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-173 intercept -1.52215e-006 NA NA NA 

## 1
v 185.167 NA NA NA 

## 2
n 17.9979 NA NA NA 

## 3
k 117036 NA NA NA 

## 4 5 At least some variance estimates are negative. 

## 6
THIS USUALLY MEANS THE MODEL HAS NOT CONVERGED! 

## 7 Try again from another starting point. 

## 8 9 10 11
Table of Data and Estimated Values of Interest 

## 12 13
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 14

------ --- -------- -------- ----------- ----------- ---------- 

## 15 16
0 9 4.9 -1.52e-006 1.11 94.3 0.156 

## 17
0.2 4 4.9 -1.52e-006 1.18 94.3 0.104 

## 18
0.667 4 6.7 -1.52e-006 1.4 94.3 0.142 

## 19
1.33 4 7.2 -1.52e-006 1.8 94.3 0.153 

## 20
6.67 4 8.3 -1.52e-006 0.26 94.3 0.176 

## 21
20 4 14 -1.52e-006 5 94.3 0.297 

## 22
66.7 4 59 -1.52e-006 6.8 94.3 1.25 

## 23
200 4 96 -1.52e-006 46 94.3 2.04 

## 24
667 4 155 -1.52e-006 16.4 94.3 3.29 

## 25
1670 4 182 -1.52e-006 26 94.3 3.86 

## 26
6670 4 189 -1.52e-006 26 94.3 4.01 

## 27 28 29 30 Model Descriptions for likelihoods calculated 

## 31 32 33 Model A1: Yij = Mu(i) + e(ij) 

## 34 Var{e(ij)} = Sigma^2 

## 35 36 Model A2: Yij = Mu(i) + e(ij) 

## 37 Var{e(ij)} = Sigma(i)^2 

## 38 39 Model A3: Yij = Mu(i) + e(ij) 

## 40 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 41 Model A3 uses any fixed variance parameters that 

## 42 were specified by the user 

## 43 44 Model R: Yi = Mu + e(i) 

## 45 Var{e(i)} = Sigma^2 

## 46 47 48
Likelihoods of Interest 

## 49 50 Model Log(likelihood) # Param's AIC 

## 51
A1 -158.130647 12 340.261294 

## 52
A2 -84.800279 22 213.600558 

## 53
A3 -98.821893 13 223.643786 

## 54
fitted -247.263464 6 506.526928 

## 55
R -234.625213 2 473.250426 

## 56 57 58 Explanation of Tests 

## 59 60 Test 1: Do responses and/or variances differ among Dose levels? 

## 61 (A2 vs. R) 

## 62 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 63 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 64 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 65 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 66 67
Tests of Interest 

## 68 69 Test -2*log(Likelihood Ratio) Test df p-value 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-174 1
Test 1 299.65 20 <.0001 

## 2
Test 2 146.661 10 <.0001 

## 3
Test 3 28.0432 9 0.0009381 

## 4
Test 4 296.883 7 <.0001 

## 5 6 The p-value for Test 1 is less than .05. There appears to be a 

## 7 difference between response and/or variances among the dose levels 

## 8 It seems appropriate to model the data 

## 9 10 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 11 model appears to be appropriate 

## 12 13 The p-value for Test 3 is less than .1. You may want to consider a 

## 14
different variance model 

## 15 16 The p-value for Test 4 is less than .1. You may want to try a different 

## 17
model 

## 18 19 20 Benchmark Dose Computation 

## 21 22 Specified effect = 1 

## 23 24 Risk Type = Estimated standard deviations from the control mean 

## 25 26
Confidence level = 0.95 

## 27 28 BMD = 1.#QNAN 

## 29 30 31 BMDL computation failed. 

## 32 33 34 35 H.3.4.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 36

0 50 100 150 200 250

0 1000 2000 3000 4000 5000 6000 7000Mean Response

dose Power Model with 0.95 Confidence Level

14:27 11/20 2009 BMDBMDL Power



## 37 38

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-175 H.3.4.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 1 Unrestricted 2 3 4

==================================================================== 

## 5 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 6 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_BaP_hydro_act.(d) 

## 7 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_BaP_hydro_act.plt 

## 8
Fri Nov 20 14:27:04 2009 

## 9

==================================================================== 

## 10 11 Kitchin 1979, Tbl3, BaP hydrolase activity 

## 12

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 13 14 The form of the response function is: 

## 15 16 Y[dose] = control + slope * dose^power 

## 17 18 19 Dependent variable = Mean 

## 20 Independent variable = Dose 

## 21 The power is not restricted 

## 22 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 23 24 Total number of dose groups = 11 

## 25 Total number of records with missing values = 0 

## 26
Maximum number of iterations = 250 

## 27 Relative Function Convergence has been set to: 1e-008 

## 28 Parameter Convergence has been set to: 1e-008 

## 29 30 31 32
Default Initial Parameter Values 

## 33 lalpha = 5.70855 

## 34
rho = 0 

## 35
control = 4.9 

## 36 slope = 0.984853 

## 37 power = 0.59404 

## 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 

## 41 42 lalpha rho control slope power 

## 43 44 lalpha 1 -0.9 -0.45 0.26 -0.23 

## 45 46
rho -0.9 1 0.35 -0.24 0.12 

## 47 48
control -0.45 0.35 1 -0.45 0.42 

## 49 50 slope 0.26 -0.24 -0.45 1 -0.92 

## 51 52 power -0.23 0.12 0.42 -0.92 1 

## 53 54 55 56
Parameter Estimates 

## 57 58
95.0% Wald Confidence Interval 

## 59 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 60 lalpha -3.42083 0.570828 -4.53963 -2.30202 

## 61
rho 2.42943 0.164289 2.10743 2.75143 

## 62
control 4.52619 0.315826 3.90719 5.1452 

## 63 slope 2.4104 0.540821 1.35041 3.47039 

## 64 power 0.619986 0.0482232 0.525471 0.714502 

## 65 66 67 68
Table of Data and Estimated Values of Interest 

## 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-176 1
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 2

------ --- -------- -------- ----------- ----------- ---------- 

## 3 4
0 9 4.9 4.53 1.11 1.13 0.991 

## 5
0.2 4 4.9 5.41 1.18 1.41 -0.732 

## 6
0.667 4 6.7 6.4 1.4 1.72 0.346 

## 7
1.33 4 7.2 7.4 1.8 2.06 -0.197 

## 8
6.67 4 8.3 12.3 0.26 3.83 -2.11 

## 9
20 4 14 20 5 6.87 -1.74 

## 10
66.7 4 59 37.1 6.8 14.6 3 

## 11
200 4 96 68.9 46 30.9 1.75 

## 12
667 4 155 140 16.4 73.4 0.399 

## 13
1670 4 182 244 26 144 -0.868 

## 14
6670 4 189 571 26 403 -1.89 

## 15 16 17 18 Model Descriptions for likelihoods calculated 

## 19 20 21 Model A1: Yij = Mu(i) + e(ij) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 Model A2: Yij = Mu(i) + e(ij) 

## 25 Var{e(ij)} = Sigma(i)^2 

## 26 27 Model A3: Yij = Mu(i) + e(ij) 

## 28 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 29 Model A3 uses any fixed variance parameters that 

## 30 were specified by the user 

## 31 32 Model R: Yi = Mu + e(i) 

## 33 Var{e(i)} = Sigma^2 

## 34 35 36
Likelihoods of Interest 

## 37 38 Model Log(likelihood) # Param's AIC 

## 39
A1 -158.130647 12 340.261294 

## 40
A2 -84.800279 22 213.600558 

## 41
A3 -98.821893 13 223.643786 

## 42
fitted -130.616947 5 271.233893 

## 43
R -234.625213 2 473.250426 

## 44 45 46 Explanation of Tests 

## 47 48 Test 1: Do responses and/or variances differ among Dose levels? 

## 49 (A2 vs. R) 

## 50 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 51 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 52 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 53 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 54 55
Tests of Interest 

## 56 57 Test -2*log(Likelihood Ratio) Test df p-value 

## 58 59
Test 1 299.65 20 <.0001 

## 60
Test 2 146.661 10 <.0001 

## 61
Test 3 28.0432 9 0.0009381 

## 62
Test 4 63.5901 8 <.0001 

## 63 64 The p-value for Test 1 is less than .05. There appears to be a 

## 65 difference between response and/or variances among the dose levels 

## 66 It seems appropriate to model the data 

## 67 68 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 69 model appears to be appropriate 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-177 1 The p-value for Test 3 is less than .1. You may want to consider a 

## 2
different variance model 

## 3 4 The p-value for Test 4 is less than .1. You may want to try a different 

## 5
model 

## 6 7 8 Benchmark Dose Computation 

## 9 10 Specified effect = 1 

## 11 12 Risk Type = Estimated standard deviations from the control mean 

## 13 14
Confidence level = 0.95 

## 15 16
BMD = 0.29535 

## 17 18 19
BMDL = 0.12727 

## 20 21 22 23 24 25 26 27 28 29 30 31 H.3.5. National Toxicology Program. (2006): EROD Liver Week 53 32
H.3.5.1. Summary Table of BMDS Modeling Results 33

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 121.00 <0.0001 210.78 5.7E+01 4.0E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 121.00 <0.0001 210.78 5.7E+01 4.0E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 7.05 0.07 98.86 2.7E-01 1.9E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 6.44 0.04 100.25 3.4E-01 2.0E-01 nonconstant variance, power restricted ≥ 1

Hill c 2 <.0001 3.05 0.22 96.86 5.4E-01 3.3E-01 nonconstant variance, n restricted >1

Hill d 2 <.0001 3.05 0.22 96.86 5.4E-01 3.3E-01 nonconstant variance, n unrestricted

linear 4 <.0001 113.79 <.0001 203.61 2.9E+01 1.1E+01 nonconstant variance

polynomial 4 <.0001 113.79 <.0001 203.61 2.9E+01 1.1E+01 nonconstant variance

power 4 <.0001 113.79 <.0001 203.61 2.9E+01 1.1E+01 nonconstant variance, power restricted ≥ 1, bound hit exponential (M2) 4 <0.0001 85.26 <0.0001 209.43 5.0E+01 4.1E+01 constant variance, power restricted ≥ 1

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-178 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M3) 4 <0.0001 85.26 <0.0001 209.43 5.0E+01 4.1E+01 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 4.50 0.21 130.67 1.5E+00 1.2E+00 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 4.50 0.21 130.67 1.5E+00 1.2E+00 constant variance, power restricted ≥ 1

Hill 2 <.0001 2.30 0.32 130.48 1.7E+00 9.3E-01 constant variance, n restricted >1

Hill 2 <.0001 2.30 0.32 130.48 1.7E+00 9.3E-01 constant variance, n unrestricted

linear 4 <.0001 77.49 <.0001 201.66 3.2E+01 2.5E+01 constant variance

polynomial 4 <.0001 77.49 <.0001 201.66 3.2E+01 2.5E+01 constant variance

power 4 <.0001 77.49 <.0001 201.66 3.2E+01 2.5E+01 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.5.2. Figure for Selected Model: Hill, No nconstant Variance, n Restricted >1 3

5 10 15 20 25

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

16:50 11/20 2009 BMD BMDL Hill



## 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-179 H.3.5.3. Output File for Selected Model: Hill , Nonconstant Variance, n Restricted >1 1 2 3

==================================================================== 

## 4 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 5 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_BMR1_Tbl12_wk53_EROD_liv.(d) 

## 6 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_BMR1_Tbl12_wk53_EROD_liv.plt 

## 7 Fri Nov 20 16:50:09 2009 

## 8

==================================================================== 

## 9 10
0 

## 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 12 13 The form of the response function is: 

## 14 15 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 16 17 18 Dependent variable = Mean 

## 19 Independent variable = Dose 

## 20 Power parameter restricted to be greater than 1 

## 21 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 22 23 Total number of dose groups = 6 

## 24 Total number of records with missing values = 0 

## 25
Maximum number of iterations = 250 

## 26 Relative Function Convergence has been set to: 1e-008 

## 27 Parameter Convergence has been set to: 1e-008 

## 28 29 30 31
Default Initial Parameter Values 

## 32 lalpha = 1.59547 

## 33
rho = 0 

## 34 intercept = 3.614 

## 35
v = 17.599 

## 36
n = 1.38584 

## 37
k = 12.1933 

## 38 39 40 Asymptotic Correlation Matrix of Parameter Estimates 

## 41 42 lalpha rho intercept v n k 

## 43 44 lalpha 1 -0.96 -0.16 0.086 -0.057 0.041 

## 45 46
rho -0.96 1 0.14 -0.11 0.06 -0.045 

## 47 48 intercept -0.16 0.14 1 -0.18 0.13 0.069 

## 49 50
v 0.086 -0.11 -0.18 1 -0.72 0.84 

## 51 52
n -0.057 0.06 0.13 -0.72 1 -0.79 

## 53 54
k 0.041 -0.045 0.069 0.84 -0.79 1 

## 55 56 57 58
Parameter Estimates 

## 59 60
95.0% Wald Confidence Interval 

## 61 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 62 lalpha -4.86544 0.741662 -6.31907 -3.4118 

## 63
rho 2.26969 0.287261 1.70667 2.83271 

## 64 intercept 3.62908 0.133826 3.36679 3.89138 

## 65
v 17.9785 0.989021 16.0401 19.917 

## 66
n 1.43249 0.162632 1.11374 1.75124 

## 67
k 7.81956 1.00384 5.85206 9.78706 

## 68 69

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-180 1 2
Table of Data and Estimated Values of Interest 

## 3 4
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 5

------ --- -------- -------- ----------- ----------- ---------- 

## 6 7
0 8 3.61 3.63 0.486 0.379 -0.113 

## 8
3 8 7.27 7.27 0.557 0.833 0.0201 

## 9
10 8 14.8 14.2 1.61 1.78 0.912 

## 10
22 8 17.3 18.3 1.59 2.37 -1.19 

## 11
46 8 20.6 20.3 3.05 2.67 0.306 

## 12
100 8 21.2 21.2 3.82 2.8 0.061 

## 13 14 15 16 Model Descriptions for likelihoods calculated 

## 17 18 19 Model A1: Yij = Mu(i) + e(ij) 

## 20 Var{e(ij)} = Sigma^2 

## 21 22 Model A2: Yij = Mu(i) + e(ij) 

## 23 Var{e(ij)} = Sigma(i)^2 

## 24 25 Model A3: Yij = Mu(i) + e(ij) 

## 26 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 27 Model A3 uses any fixed variance parameters that 

## 28 were specified by the user 

## 29 30 Model R: Yi = Mu + e(i) 

## 31 Var{e(i)} = Sigma^2 

## 32 33 34
Likelihoods of Interest 

## 35 36 Model Log(likelihood) # Param's AIC 

## 37
A1 -59.086537 7 132.173073 

## 38
A2 -37.515858 12 99.031716 

## 39
A3 -40.906180 8 97.812359 

## 40
fitted -42.430348 6 96.860697 

## 41
R -116.710291 2 237.420582 

## 42 43 44 Explanation of Tests 

## 45 46 Test 1: Do responses and/or variances differ among Dose levels? 

## 47 (A2 vs. R) 

## 48 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 49 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 50 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 51 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 52 53
Tests of Interest 

## 54 55 Test -2*log(Likelihood Ratio) Test df p-value 

## 56 57
Test 1 158.389 10 <.0001 

## 58
Test 2 43.1414 5 <.0001 

## 59
Test 3 6.78064 4 0.1479 

## 60
Test 4 3.04834 2 0.2178 

## 61 62 The p-value for Test 1 is less than .05. There appears to be a 

## 63 difference between response and/or variances among the dose levels 

## 64 It seems appropriate to model the data 

## 65 66 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 67 model appears to be appropriate 

## 68 69 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-181 to be appropriate here 

## 1 2 The p-value for Test 4 is greater than .1. The model chosen seems 

## 3 to adequately describe the data 

## 4 5 6 Benchmark Dose Computation 

## 7 8 Specified effect = 1 

## 9 10 Risk Type = Estimated standard deviations from the control mean 

## 11 12
Confidence level = 0.95 

## 13 14
BMD = 0.536614 

## 15 16
BMDL = 0.328003 

## 17 18 19 H.3.5.4. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 20

5 10 15 20 25

0 20 40 60 80 100Mean Response

dose Hill Model with 0.95 Confidence Level

16:50 11/20 2009 BMD BMDL Hill



## 21 22 23 H.3.5.5. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 24 25 26

==================================================================== 

## 27 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 28 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_Tbl12_wk53_EROD_liv.(d) 

## 29 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_Tbl12_wk53_EROD_liv.plt 

## 30
Fri Nov 20 16:50:14 2009 

## 31

==================================================================== 

## 32 33
0 

## 34

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 35 36 The form of the response function is: 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-182 1 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 2 3 4 Dependent variable = Mean 

## 5 Independent variable = Dose 

## 6 Power parameter is not restricted 

## 7 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 8 9 Total number of dose groups = 6 

## 10 Total number of records with missing values = 0 

## 11
Maximum number of iterations = 250 

## 12 Relative Function Convergence has been set to: 1e-008 

## 13 Parameter Convergence has been set to: 1e-008 

## 14 15 16 17
Default Initial Parameter Values 

## 18 lalpha = 1.59547 

## 19
rho = 0 

## 20 intercept = 3.614 

## 21
v = 17.599 

## 22
n = 1.38584 

## 23
k = 12.1933 

## 24 25 26 Asymptotic Correlation Matrix of Parameter Estimates 

## 27 28 lalpha rho intercept v n k 

## 29 30 lalpha 1 -0.96 -0.16 0.086 -0.057 0.041 

## 31 32
rho -0.96 1 0.14 -0.11 0.06 -0.045 

## 33 34 intercept -0.16 0.14 1 -0.18 0.13 0.069 

## 35 36
v 0.086 -0.11 -0.18 1 -0.72 0.84 

## 37 38
n -0.057 0.06 0.13 -0.72 1 -0.79 

## 39 40
k 0.041 -0.045 0.069 0.84 -0.79 1 

## 41 42 43 44
Parameter Estimates 

## 45 46
95.0% Wald Confidence Interval 

## 47 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 48 lalpha -4.86544 0.741662 -6.31907 -3.4118 

## 49
rho 2.26969 0.287261 1.70667 2.83271 

## 50 intercept 3.62908 0.133826 3.36679 3.89138 

## 51
v 17.9785 0.989021 16.0401 19.917 

## 52
n 1.43249 0.162632 1.11374 1.75124 

## 53
k 7.81956 1.00384 5.85206 9.78706 

## 54 55 56 57 Table of Data and Estimated Values of Interest 

## 58 59
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 60

------ --- -------- -------- ----------- ----------- ---------- 

## 61 62
0 8 3.61 3.63 0.486 0.379 -0.113 

## 63
3 8 7.27 7.27 0.557 0.833 0.0201 

## 64
10 8 14.8 14.2 1.61 1.78 0.912 

## 65
22 8 17.3 18.3 1.59 2.37 -1.19 

## 66
46 8 20.6 20.3 3.05 2.67 0.306 

## 67
100 8 21.2 21.2 3.82 2.8 0.061 

## 68 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-183 1 Model Descriptions for likelihoods calculated 

## 2 3 4 Model A1: Yij = Mu(i) + e(ij) 

## 5 Var{e(ij)} = Sigma^2 

## 6 7 Model A2: Yij = Mu(i) + e(ij) 

## 8 Var{e(ij)} = Sigma(i)^2 

## 9 10 Model A3: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 12 Model A3 uses any fixed variance parameters that 

## 13 were specified by the user 

## 14 15 Model R: Yi = Mu + e(i) 

## 16 Var{e(i)} = Sigma^2 

## 17 18 19
Likelihoods of Interest 

## 20 21 Model Log(likelihood) # Param's AIC 

## 22
A1 -59.086537 7 132.173073 

## 23
A2 -37.515858 12 99.031716 

## 24
A3 -40.906180 8 97.812359 

## 25
fitted -42.430348 6 96.860697 

## 26
R -116.710291 2 237.420582 

## 27 28 29 Explanation of Tests 

## 30 31 Test 1: Do responses and/or variances differ among Dose levels? 

## 32 (A2 vs. R) 

## 33 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 34 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 35 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 36 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 37 38
Tests of Interest 

## 39 40 Test -2*log(Likelihood Ratio) Test df p-value 

## 41 42
Test 1 158.389 10 <.0001 

## 43
Test 2 43.1414 5 <.0001 

## 44
Test 3 6.78064 4 0.1479 

## 45
Test 4 3.04834 2 0.2178 

## 46 47 The p-value for Test 1 is less than .05. There appears to be a 

## 48 difference between response and/or variances among the dose levels 

## 49 It seems appropriate to model the data 

## 50 51 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 52 model appears to be appropriate 

## 53 54 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 55 to be appropriate here 

## 56 57 The p-value for Test 4 is greater than .1. The model chosen seems 

## 58 to adequately describe the data 

## 59 60 61 Benchmark Dose Computation 

## 62 63 Specified effect = 1 

## 64 65 Risk Type = Estimated standard deviations from the control mean 

## 66 67
Confidence level = 0.95 

## 68 69
BMD = 0.536614 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-184 1
BMDL = 0.328003 

## 2 3 4
H.3.6. National Toxicology Program. (2006): Lung EROD Week 31 5
H.3.6.1. Summary Table of BMDS Modeling Results 6

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 129.30 <0.0001 396.45 8.9E+01 6.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 129.30 <0.0001 396.45 8.9E+01 6.2E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 20.80 0.00 289.99 1.0E-01 6.9E-02 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 20.80 0.00 289.99 1.0E-01 6.9E-02 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 <0.0001 20.80 0.00 289.99 1.0E-01 6.9E-02 nonconstant variance, power unrestricted

Hill 3 <.0001 78.84 <.0001 348.02 9.6E+00 error nonconstant variance, n restricted >1, bound hit

Hill d 3 <.0001 78.84 <.0001 348.02 9.6E+00 error nonconstant variance, n unrestricted

linear 4 <.0001 125.96 <.0001 393.15 6.3E+01 3.1E+01 nonconstant variance

polynomial 4 <.0001 128.35 <.0001 395.53 1.0E+02 2.3E+01 nonconstant variance

power 4 <.0001 125.96 <.0001 393.15 6.3E+01 3.1E+01 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 22.50 <.0001 291.68 1.9E-06 1.9E-06 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 87.28 <0.0001 397.44 6.6E+01 5.3E+01 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 87.28 <0.0001 397.44 6.6E+01 5.3E+01 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 15.56 0.00 327.72 1.7E+00 1.2E+00 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 15.56 0.00 327.72 1.7E+00 1.2E+00 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 15.56 0.00 327.72 1.7E+00 1.2E+00 constant variance, power unrestricted

Hill 2 <.0001 34.01 <.0001 348.17 2.8E+00 2.4E-01 constant variance, n restricted >1

Hill 2 <.0001 34.01 <.0001 348.17 2.8E+00 5.0E-05 constant variance, n unrestricted

linear 4 <.0001 81.72 <.0001 391.88 4.6E+01 3.5E+01 constant variance

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-185 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

polynomial 4 <.0001 81.72 <.0001 391.88 4.6E+01 3.5E+01 constant variance

power 4 <.0001 81.72 <.0001 391.88 4.6E+01 3.5E+01 constant variance, power restricted ≥ 1, bound hit

power 3 <.0001 22.22 <.0001 334.38 1.0E-02 6.9E-04 constant variance, power unrestricted

a Values < 0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant va riance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.6.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:28 11/20 2009 BMDBMDL Exponential



## 5 6 7 H.3.6.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_Lung_EROD_wk31.(d) 

## 14 Gnuplot Plotting File: 

## 15

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-186 Fri Nov 20 14:28:10 2009 

## 1

==================================================================== 

## 2 3 Tbl 12, Week 31, Lung Microsomes EROD 

## 4

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 5 6 The form of the response function by Model: 

## 7 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 8 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 9 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 10 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 11 12 Note: Y[dose] is the median response for exposure = dose; 

## 13 sign = +1 for increasing trend in data; 

## 14 sign = -1 for decreasing trend. 

## 15 16
Model 2 is nested within Models 3 and 4. 

## 17
Model 3 is nested within Model 5. 

## 18
Model 4 is nested within Model 5. 

## 19 20 21 Dependent variable = Mean 

## 22 Independent variable = Dose 

## 23 Data are assumed to be distributed: normally 

## 24 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 26 27 Total number of dose groups = 6 

## 28 Total number of records with missing values = 0 

## 29
Maximum number of iterations = 250 

## 30 Relative Function Convergence has been set to: 1e-008 

## 31 Parameter Convergence has been set to: 1e-008 

## 32 33 MLE solution provided: Exact 

## 34 35 36
Initial Parameter Values 

## 37 38
Variable Model 4 

## 39

-------- -------- 

## 40 lnalpha -1.42653 

## 41
rho 1.46168 

## 42
a 1.96745 

## 43
b 0.034997 

## 44
c 26.7857 

## 45
d 1 

## 46 47 48 49
Parameter Estimates 

## 50 51
Variable Model 4 

## 52

-------- ------- 

## 53 lnalpha -1.46439 

## 54
rho 1.61106 

## 55
a 2.12443 

## 56
b 0.19145 

## 57
c 22.311 

## 58
d 1 

## 59 60 61 Table of Stats From Input Data 

## 62 63
Dose N Obs Mean Obs Std Dev 

## 64

----- --- ---------- ------------- 

## 65
0 10 2.071 0.9708 

## 66
3 10 25.34 2.549 

## 67
10 10 30.39 5.831 

## 68
22 10 50.19 8.68 

## 69
46 10 49.07 13.91 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-187 100 10 48.42 8.933 

## 1 2 3
Estimated Values of Interest 

## 4 5 Dose Est Mean Est Std Scaled Residual 

## 6

------ ---------- --------- ---------------- 

## 7
0 2.124 0.8823 -0.1915 

## 8
3 21.91 5.779 1.88 

## 9
10 40.72 9.524 -3.432 

## 10
22 46.73 10.64 1.029 

## 11
46 47.39 10.76 0.4921 

## 12
100 47.4 10.76 0.3006 

## 13 14 15 16
Other models for which likelihoods are calculated: 

## 17 18 Model A1: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = Sigma^2 

## 20 21 Model A2: Yij = Mu(i) + e(ij) 

## 22 Var{e(ij)} = Sigma(i)^2 

## 23 24 Model A3: Yij = Mu(i) + e(ij) 

## 25 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 26 27 Model R: Yij = Mu + e(i) 

## 28 Var{e(ij)} = Sigma^2 

## 29 30 31
Likelihoods of Interest 

## 32 33 Model Log(likelihood) DF AIC 

## 34

------- ----------------- ---- ------------ 

## 35
A1 -152.0793 7 318.1586 

## 36
A2 -123.367 12 270.734 

## 37
A3 -129.5911 8 275.1823 

## 38
R -206.5175 2 417.0349 

## 39
4 -139.9927 5 289.9853 

## 40 41 42 Additive constant for all log-likelihoods = -55.14. This constant added to the 

## 43 above values gives the log-likelihood including the term that does not 

## 44 depend on the model parameters. 

## 45 46 47 Explanation of Tests 

## 48 49 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 50 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 51 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 52 53 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 54 55 56
Tests of Interest 

## 57 58 Test -2*log(Likelihood Ratio) D. F. p-value 

## 59

-------- ------------------------ ------ -------------- 

## 60
Test 1 166.3 10 < 0.0001 

## 61
Test 2 57.42 5 < 0.0001 

## 62
Test 3 12.45 4 0.01431 

## 63
Test 6a 20.8 3 0.0001157 

## 64 65 66 The p-value for Test 1 is less than .05. There appears to be a 

## 67 difference between response and/or variances among the dose 

## 68 levels, it seems appropriate to model the data. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-188 The p-value for Test 2 is less than .1. A non-homogeneous 

## 1 variance model appears to be appropriate. 

## 2 3 The p-value for Test 3 is less than .1. You may want to 

## 4
consider a different variance model. 

## 5 6 The p-value for Test 6a is less than .1. Model 4 may not adequately 

## 7 describe the data; you may want to consider another model. 

## 8 9 10 Benchmark Dose Computations: 

## 11 12 Specified Effect = 1.000000 

## 13 14 Risk Type = Estimated standard deviations from control 

## 15 16
Confidence Level = 0.950000 

## 17 18
BMD = 0.102798 

## 19 20
BMDL = 0.069311 

## 21 22 23 H.3.6.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 24 Unrestricted 25

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:28 11/20 2009 BMDBMDL Exponential



## 26 27 28 H.3.6.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 29 Power Unrestricted 30 31 32

==================================================================== 

## 33 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 34 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_Unrest_BMR1_Lung_EROD_wk31.(d) 

## 35 Gnuplot Plotting File: 

## 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-189 Fri Nov 20 14:28:17 2009 

## 1

==================================================================== 

## 2 3 Tbl 12, Week 31, Lung Microsomes EROD 

## 4

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 5 6 The form of the response function by Model: 

## 7 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 8 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 9 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 10 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 11 12 Note: Y[dose] is the median response for exposure = dose; 

## 13 sign = +1 for increasing trend in data; 

## 14 sign = -1 for decreasing trend. 

## 15 16
Model 2 is nested within Models 3 and 4. 

## 17
Model 3 is nested within Model 5. 

## 18
Model 4 is nested within Model 5. 

## 19 20 21 Dependent variable = Mean 

## 22 Independent variable = Dose 

## 23 Data are assumed to be distributed: normally 

## 24 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 25 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 26 27 Total number of dose groups = 6 

## 28 Total number of records with missing values = 0 

## 29
Maximum number of iterations = 250 

## 30 Relative Function Convergence has been set to: 1e-008 

## 31 Parameter Convergence has been set to: 1e-008 

## 32 33 MLE solution provided: Exact 

## 34 35 36
Initial Parameter Values 

## 37 38
Variable Model 5 

## 39

-------- -------- 

## 40 lnalpha -1.42653 

## 41
rho 1.46168 

## 42
a 1.96745 

## 43
b 0.034997 

## 44
c 26.7857 

## 45
d 1 

## 46 47 48 49
Parameter Estimates 

## 50 51
Variable Model 5 

## 52

-------- ------- 

## 53 lnalpha -1.46439 

## 54
rho 1.61106 

## 55
a 2.12443 

## 56
b 0.19145 

## 57
c 22.311 

## 58
d 1 

## 59 60 61 Table of Stats From Input Data 

## 62 63
Dose N Obs Mean Obs Std Dev 

## 64

----- --- ---------- ------------- 

## 65
0 10 2.071 0.9708 

## 66
3 10 25.34 2.549 

## 67
10 10 30.39 5.831 

## 68
22 10 50.19 8.68 

## 69
46 10 49.07 13.91 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-190 100 10 48.42 8.933 

## 1 2 3
Estimated Values of Interest 

## 4 5 Dose Est Mean Est Std Scaled Residual 

## 6

------ ---------- --------- ---------------- 

## 7
0 2.124 0.8823 -0.1915 

## 8
3 21.91 5.779 1.88 

## 9
10 40.72 9.524 -3.432 

## 10
22 46.73 10.64 1.029 

## 11
46 47.39 10.76 0.4921 

## 12
100 47.4 10.76 0.3006 

## 13 14 15 16
Other models for which likelihoods are calculated: 

## 17 18 Model A1: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = Sigma^2 

## 20 21 Model A2: Yij = Mu(i) + e(ij) 

## 22 Var{e(ij)} = Sigma(i)^2 

## 23 24 Model A3: Yij = Mu(i) + e(ij) 

## 25 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 26 27 Model R: Yij = Mu + e(i) 

## 28 Var{e(ij)} = Sigma^2 

## 29 30 31
Likelihoods of Interest 

## 32 33 Model Log(likelihood) DF AIC 

## 34

------- ----------------- ---- ------------ 

## 35
A1 -152.0793 7 318.1586 

## 36
A2 -123.367 12 270.734 

## 37
A3 -129.5911 8 275.1823 

## 38
R -206.5175 2 417.0349 

## 39
5 -139.9927 5 289.9853 

## 40 41 42 Additive constant for all log-likelihoods = -55.14. This constant added to the 

## 43 above values gives the log-likelihood including the term that does not 

## 44 depend on the model parameters. 

## 45 46 47 Explanation of Tests 

## 48 49 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 50 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 51 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 52 53 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 54 55 56
Tests of Interest 

## 57 58 Test -2*log(Likelihood Ratio) D. F. p-value 

## 59

-------- ------------------------ ------ -------------- 

## 60
Test 1 166.3 10 < 0.0001 

## 61
Test 2 57.42 5 < 0.0001 

## 62
Test 3 12.45 4 0.01431 

## 63
Test 7a 20.8 3 0.0001157 

## 64 65 66 The p-value for Test 1 is less than .05. There appears to be a 

## 67 difference between response and/or variances among the dose 

## 68 levels, it seems appropriate to model the data. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-191 The p-value for Test 2 is less than .1. A non-homogeneous 

## 1 variance model appears to be appropriate. 

## 2 3 The p-value for Test 3 is less than .1. You may want to 

## 4
consider a different variance model. 

## 5 6 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 7 describe the data; you may want to consider another model. 

## 8 9 10 Benchmark Dose Computations: 

## 11 12 Specified Effect = 1.000000 

## 13 14 Risk Type = Estimated standard deviations from control 

## 15 16
Confidence Level = 0.950000 

## 17 18
BMD = 0.102798 

## 19 20
BMDL = 0.0693109 

## 21 22 23 H.3.6.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 24

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Hill Model

14:28 11/20 2009 BMD Hill



## 25 26 27 H.3.6.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 28 29 30

==================================================================== 

## 31 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 32 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_Lung_EROD_wk31.(d) 

## 33 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_Lung_EROD_wk31.plt 

## 34
Fri Nov 20 14:28:19 2009 

## 35

==================================================================== 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-192 Tbl 12, Week 31, Lung Microsomes EROD 

## 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 2 3 The form of the response function is: 

## 4 5 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 6 7 8 Dependent variable = Mean 

## 9 Independent variable = Dose 

## 10 Power parameter is not restricted 

## 11 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 12 13 Total number of dose groups = 6 

## 14 Total number of records with missing values = 0 

## 15
Maximum number of iterations = 250 

## 16 Relative Function Convergence has been set to: 1e-008 

## 17 Parameter Convergence has been set to: 1e-008 

## 18 19 20 21
Default Initial Parameter Values 

## 22 lalpha = 4.17467 

## 23
rho = 0 

## 24 intercept = 2.071 

## 25
v = 48.119 

## 26
n = 18 

## 27
k = 15.9059 

## 28 29 30 Asymptotic Correlation Matrix of Parameter Estimates 

## 31 32 ( *** The model parameter(s) -n 

## 33 have been estimated at a boundary point, or have been specified by the user, 

## 34 and do not appear in the correlation matrix ) 

## 35 36 lalpha rho intercept v k 

## 37 38 lalpha 1 -0.98 0.04 -0.054 -0.092 

## 39 40
rho -0.98 1 -0.027 0.046 0.096 

## 41 42 intercept 0.04 -0.027 1 -0.82 0.36 

## 43 44
v -0.054 0.046 -0.82 1 -0.16 

## 45 46
k -0.092 0.096 0.36 -0.16 1 

## 47 48 49 50
Parameter Estimates 

## 51 52
95.0% Wald Confidence Interval 

## 53 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 54 lalpha 5.40756 1.03169 3.38548 7.42964 

## 55
rho -0.228427 0.299513 -0.815462 0.358608 

## 56 intercept 13.5736 2.48089 8.71112 18.436 

## 57
v 35.6207 3.03486 29.6725 41.5689 

## 58
n 18 NA 

## 59
k 10.0457 0.22238 9.60987 10.4816 

## 60 61 NA - Indicates that this parameter has hit a bound 

## 62 implied by some inequality constraint and thus 

## 63
has no standard error. 

## 64 65 66
Table of Data and Estimated Values of Interest 

## 67 68
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 69

------ --- -------- -------- ----------- ----------- ---------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-193 1
0 10 2.07 13.6 0.971 11.1 -3.28 

## 2
3 10 25.3 13.6 2.55 11.1 3.36 

## 3
10 10 30.4 30.7 5.83 10.1 -0.0833 

## 4
22 10 50.2 49.2 8.68 9.57 0.329 

## 5
46 10 49.1 49.2 13.9 9.57 -0.0424 

## 6
100 10 48.4 49.2 8.93 9.57 -0.255 

## 7 8 9 Model Descriptions for likelihoods calculated 

## 10 11 12 Model A1: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma^2 

## 14 15 Model A2: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma(i)^2 

## 17 18 Model A3: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 20 Model A3 uses any fixed variance parameters that 

## 21 were specified by the user 

## 22 23 Model R: Yi = Mu + e(i) 

## 24 Var{e(i)} = Sigma^2 

## 25 26 27
Likelihoods of Interest 

## 28 29 Model Log(likelihood) # Param's AIC 

## 30
A1 -152.079318 7 318.158637 

## 31
A2 -123.366985 12 270.733969 

## 32
A3 -129.591134 8 275.182269 

## 33
fitted -169.011448 5 348.022896 

## 34
R -206.517459 2 417.034919 

## 35 36 37 Explanation of Tests 

## 38 39 Test 1: Do responses and/or variances differ among Dose levels? 

## 40 (A2 vs. R) 

## 41 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 42 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 43 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 44 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 45 46
Tests of Interest 

## 47 48 Test -2*log(Likelihood Ratio) Test df p-value 

## 49 50
Test 1 166.301 10 <.0001 

## 51
Test 2 57.4247 5 <.0001 

## 52
Test 3 12.4483 4 0.01431 

## 53
Test 4 78.8406 3 <.0001 

## 54 55 The p-value for Test 1 is less than .05. There appears to be a 

## 56 difference between response and/or variances among the dose levels 

## 57 It seems appropriate to model the data 

## 58 59 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 60 model appears to be appropriate 

## 61 62 The p-value for Test 3 is less than .1. You may want to consider a 

## 63
different variance model 

## 64 65 The p-value for Test 4 is less than .1. You may want to try a different 

## 66
model 

## 67 68 69 Benchmark Dose Computation 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-194 1 Specified effect = 1 

## 2 3 Risk Type = Estimated standard deviations from the control mean 

## 4 5 Confidence level = 0.95 

## 6 7
BMD = 9.61218 

## 8 9 10 BMDL computation failed. 

## 11 12 13 H.3.6.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 14

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Power Model with 0.95 Confidence Level

14:28 11/20 2009 BMDBMDL Power



## 15 16 17 H.3.6.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 18 Unrestricted 19 20 21

==================================================================== 

## 22 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 23 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_Lung_EROD_wk31.(d) 

## 24 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_Lung_EROD_wk31.plt 

## 25
Fri Nov 20 14:28:19 2009 

## 26

==================================================================== 

## 27 28 Tbl 12, Week 31, Lung Microsomes EROD 

## 29

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 30 31 The form of the response function is: 

## 32 33 Y[dose] = control + slope * dose^power 

## 34 35 36 Dependent variable = Mean 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-195 Independent variable = Dose 

## 1 The power is not restricted 

## 2 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 3 4 Total number of dose groups = 6 

## 5 Total number of records with missing values = 0 

## 6
Maximum number of iterations = 250 

## 7 Relative Function Convergence has been set to: 1e-008 

## 8 Parameter Convergence has been set to: 1e-008 

## 9 10 11 12
Default Initial Parameter Values 

## 13 lalpha = 4.17467 

## 14
rho = 0 

## 15
control = 2.071 

## 16 slope = 18.9386 

## 17 power = 0.224076 

## 18 19 20 Asymptotic Correlation Matrix of Parameter Estimates 

## 21 22 lalpha rho control slope power 

## 23 24 lalpha 1 -0.94 -0.42 0.15 -0.13 

## 25 26
rho -0.94 1 0.38 -0.19 0.14 

## 27 28
control -0.42 0.38 1 -0.15 0.093 

## 29 30 slope 0.15 -0.19 -0.15 1 -0.94 

## 31 32 power -0.13 0.14 0.093 -0.94 1 

## 33 34 35 36
Parameter Estimates 

## 37 38
95.0% Wald Confidence Interval 

## 39 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 40 lalpha -1.53358 0.571219 -2.65315 -0.414007 

## 41
rho 1.6412 0.166321 1.31521 1.96718 

## 42
control 2.10983 0.270093 1.58046 2.6392 

## 43 slope 18.5389 2.01491 14.5897 22.488 

## 44 power 0.233238 0.0324661 0.169605 0.29687 

## 45 46 47 48
Table of Data and Estimated Values of Interest 

## 49 50
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 51

------ --- -------- -------- ----------- ----------- ---------- 

## 52 53
0 10 2.07 2.11 0.971 0.857 -0.143 

## 54
3 10 25.3 26.1 2.55 6.74 -0.338 

## 55
10 10 30.4 33.8 5.83 8.35 -1.3 

## 56
22 10 50.2 40.2 8.68 9.63 3.27 

## 57
46 10 49.1 47.4 13.9 11 0.481 

## 58
100 10 48.4 56.4 8.93 12.7 -1.98 

## 59 60 61 62 Model Descriptions for likelihoods calculated 

## 63 64 65 Model A1: Yij = Mu(i) + e(ij) 

## 66 Var{e(ij)} = Sigma^2 

## 67 68 Model A2: Yij = Mu(i) + e(ij) 

## 69 Var{e(ij)} = Sigma(i)^2 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-196 1 Model A3: Yij = Mu(i) + e(ij) 

## 2 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 3 Model A3 uses any fixed variance parameters that 

## 4 were specified by the user 

## 5 6 Model R: Yi = Mu + e(i) 

## 7 Var{e(i)} = Sigma^2 

## 8 9 10
Likelihoods of Interest 

## 11 12 Model Log(likelihood) # Param's AIC 

## 13
A1 -152.079318 7 318.158637 

## 14
A2 -123.366985 12 270.733969 

## 15
A3 -129.591134 8 275.182269 

## 16
fitted -140.838955 5 291.677909 

## 17
R -206.517459 2 417.034919 

## 18 19 20 Explanation of Tests 

## 21 22 Test 1: Do responses and/or variances differ among Dose levels? 

## 23 (A2 vs. R) 

## 24 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 25 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 26 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 27 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 28 29
Tests of Interest 

## 30 31 Test -2*log(Likelihood Ratio) Test df p-value 

## 32 33
Test 1 166.301 10 <.0001 

## 34
Test 2 57.4247 5 <.0001 

## 35
Test 3 12.4483 4 0.01431 

## 36
Test 4 22.4956 3 <.0001 

## 37 38 The p-value for Test 1 is less than .05. There appears to be a 

## 39 difference between response and/or variances among the dose levels 

## 40 It seems appropriate to model the data 

## 41 42 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 43 model appears to be appropriate 

## 44 45 The p-value for Test 3 is less than .1. You may want to consider a 

## 46
different variance model 

## 47 48 The p-value for Test 4 is less than .1. You may want to try a different 

## 49
model 

## 50 51 52 Benchmark Dose Computation 

## 53 54 Specified effect = 1 

## 55 56 Risk Type = Estimated standard deviations from the control mean 

## 57 58
Confidence level = 0.95 

## 59 60
BMD = 1.88864e-006 

## 61 62 63
BMDL = 1.88864e-006 

## 64 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-197 H.3.7. National Toxicology Program. (2006): Lung EROD Week 53 1
H.3.7.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 66.01 <0.0001 316.32 1.3E+02 8.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 66.01 <0.0001 316.32 1.3E+02 8.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 2.82 0.42 255.12 1.2E-01 7.5E-02 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 16.10 0.00 270.40 2.6E-01 1.5E-04 nonconstant variance, power restricted ≥ 1
exponential (M5) d 2 <0.0001 16.10 0.00 270.40 2.6E-01 1.5E-04 nonconstant variance, power unrestricted

Hill 2 <.0001 81.88 <.0001 336.18 3.0E+02 error nonconstant variance, n restricted >1

Hill d 2 <.0001 81.88 <.0001 336.18 3.0E+02 error nonconstant variance, n unrestricted

linear 4 <.0001 65.65 <.0001 315.96 1.2E+02 6.3E+01 nonconstant variance

polynomial 4 <.0001 65.65 <.0001 315.96 1.2E+02 6.3E+01 nonconstant variance

power 4 <.0001 65.65 <.0001 315.96 1.2E+02 6.3E+01 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 8.50 0.04 260.80 3.8E-10 3.8E-10 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 43.26 <0.0001 319.80 8.0E+01 6.0E+01 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 43.26 <0.0001 319.80 8.0E+01 6.0E+01 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 3.04 0.39 281.57 9.2E-01 5.5E-01 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 2.71 0.26 283.24 2.2E+00 5.7E-01 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 2.71 0.26 283.24 2.2E+00 5.7E-01 constant variance, power unrestricted

Hill 2 <.0001 2.71 0.26 283.24 2.7E+00 3.2E-01 constant variance, n restricted >1

Hill 2 <.0001 2.71 0.26 283.24 2.7E+00 1.2E-02 constant variance, n unrestricted

linear 4 <.0001 41.45 <.0001 317.99 6.5E+01 4.4E+01 constant variance

polynomial 4 <.0001 41.45 <.0001 317.99 6.5E+01 4.4E+01 constant variance

power 4 <.0001 41.45 <.0001 317.99 6.5E+01 4.4E+01 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-198 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 3 <.0001 5.93 0.11 284.47 5.3E-04 5.3E-04 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.7.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:29 11/20 2009 BMD BMDL Exponential



## 5 6 7 H.3.7.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_Lung_EROD_wk53.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 14:29:03 2009 

## 16

==================================================================== 

## 17 18 Tbl 12, Week 53, Lung Microsomes EROD 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-199 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 6 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 4 

## 32

-------- -------- 

## 33 lnalpha -0.80064 

## 34
rho 1.47683 

## 35
a 2.86045 

## 36
b 0.0390303 

## 37
c 16.0581 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 4 

## 45

-------- ------- 

## 46 lnalpha -1.07501 

## 47
rho 1.68859 

## 48
a 3.011 

## 49
b 3.22004 

## 50
c 12.8877 

## 51
d 18 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 8 3.011 1.584 

## 59
3 8 27.15 5.269 

## 60
10 8 42.85 11.15 

## 61
22 8 36.57 12.99 

## 62
46 8 43.75 18.55 

## 63
100 8 43.71 6.322 

## 64 65 66
Estimated Values of Interest 

## 67 68
Dose Est Mean Est Std Scaled Residual 

## 69

------ ---------- --------- ---------------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-200 0 3.068 1.404 -0.1156 

## 1
3 26.26 8.088 0.3111 

## 2
10 40.44 11.5 0.5912 

## 3
22 42.43 11.96 -1.386 

## 4
46 42.49 11.98 0.2969 

## 5
100 42.49 11.98 0.2891 

## 6 7 8 9
Other models for which likelihoods are calculated: 

## 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Model R: Yij = Mu + e(i) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) DF AIC 

## 27

------- ----------------- ---- ------------ 

## 28
A1 -135.2677 7 284.5353 

## 29
A2 -115.6885 12 255.3771 

## 30
A3 -121.1517 8 258.3034 

## 31
R -162.0902 2 328.1805 

## 32
4 -122.5608 5 255.1215 

## 33 34 35 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 36 above values gives the log-likelihood including the term that does not 

## 37 depend on the model parameters. 

## 38 39 40 Explanation of Tests 

## 41 42 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 43 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 44 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 45 46 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 47 48 49
Tests of Interest 

## 50 51 Test -2*log(Likelihood Ratio) D. F. p-value 

## 52

-------- ------------------------ ------ -------------- 

## 53
Test 1 92.8 10 < 0.0001 

## 54
Test 2 39.16 5 < 0.0001 

## 55
Test 3 10.93 4 0.0274 

## 56
Test 6a 2.818 3 0.4205 

## 57 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose 

## 61 levels, it seems appropriate to model the data. 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous 

## 64 variance model appears to be appropriate. 

## 65 66 The p-value for Test 3 is less than .1. You may want to 

## 67
consider a different variance model. 

## 68 69 The p-value for Test 6a is greater than .1. Model 4 seems 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-201 to adequately describe the data. 

## 1 2 3 Benchmark Dose Computations: 

## 4 5 Specified Effect = 1.000000 

## 6 7 Risk Type = Estimated standard deviations from control 

## 8 9
Confidence Level = 0.950000 

## 10 11
BMD = 0.122595 

## 12 13
BMDL = 0.0752795 

## 14 15 16 17 H.3.7.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 18 Unrestricted 19

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:29 11/20 2009 BMD BMDL Exponential



## 20 21 22 H.3.7.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 23 Power Unrestricted 24 25 26

==================================================================== 

## 27 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 28 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_Unrest_BMR1_Lung_EROD_wk53.(d) 

## 29 Gnuplot Plotting File: 

## 30
Fri Nov 20 14:29:09 2009 

## 31

==================================================================== 

## 32 33 Tbl 12, Week 53, Lung Microsomes EROD 

## 34

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 35 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-202 The form of the response function by Model: 

## 1 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 2 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 3 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 4 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 5 6 Note: Y[dose] is the median response for exposure = dose; 

## 7 sign = +1 for increasing trend in data; 

## 8 sign = -1 for decreasing trend. 

## 9 10
Model 2 is nested within Models 3 and 4. 

## 11
Model 3 is nested within Model 5. 

## 12
Model 4 is nested within Model 5. 

## 13 14 15 Dependent variable = Mean 

## 16 Independent variable = Dose 

## 17 Data are assumed to be distributed: normally 

## 18 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 19 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Total number of dose groups = 6 

## 22 Total number of records with missing values = 0 

## 23
Maximum number of iterations = 250 

## 24 Relative Function Convergence has been set to: 1e-008 

## 25 Parameter Convergence has been set to: 1e-008 

## 26 27 MLE solution provided: Exact 

## 28 29 30
Initial Parameter Values 

## 31 32
Variable Model 5 

## 33

-------- -------- 

## 34 lnalpha -0.80064 

## 35
rho 1.47683 

## 36
a 2.86045 

## 37
b 0.0390303 

## 38
c 16.0581 

## 39
d 1 

## 40 41 42 43
Parameter Estimates 

## 44 45
Variable Model 5 

## 46

-------- ------- 

## 47 lnalpha -1.07501 

## 48
rho 1.68859 

## 49
a 3.011 

## 50
b 3.22004 

## 51
c 12.8877 

## 52
d 18 

## 53 54 55 Table of Stats From Input Data 

## 56 57
Dose N Obs Mean Obs Std Dev 

## 58

----- --- ---------- ------------- 

## 59
0 8 3.011 1.584 

## 60
3 8 27.15 5.269 

## 61
10 8 42.85 11.15 

## 62
22 8 36.57 12.99 

## 63
46 8 43.75 18.55 

## 64
100 8 43.71 6.322 

## 65 66 67
Estimated Values of Interest 

## 68 69
Dose Est Mean Est Std Scaled Residual 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-203 ------ ---------- --------- ---------------- 

## 1
0 3.011 1.482 -4.539e-008 

## 2
3 38.8 12.82 -2.571 

## 3
10 38.8 12.82 0.8915 

## 4
22 38.8 12.82 -0.4931 

## 5
46 38.8 12.82 1.09 

## 6
100 38.8 12.82 1.082 

## 7 8 9 10
Other models for which likelihoods are calculated: 

## 11 12 Model A1: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma^2 

## 14 15 Model A2: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = Sigma(i)^2 

## 17 18 Model A3: Yij = Mu(i) + e(ij) 

## 19 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 20 21 Model R: Yij = Mu + e(i) 

## 22 Var{e(ij)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) DF AIC 

## 28

------- ----------------- ---- ------------ 

## 29
A1 -135.2677 7 284.5353 

## 30
A2 -115.6885 12 255.3771 

## 31
A3 -121.1517 8 258.3034 

## 32
R -162.0902 2 328.1805 

## 33
5 -129.2006 6 270.4011 

## 34 35 36 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 37 above values gives the log-likelihood including the term that does not 

## 38 depend on the model parameters. 

## 39 40 41 Explanation of Tests 

## 42 43 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 44 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 45 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 46 47 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 48 49 50
Tests of Interest 

## 51 52 Test -2*log(Likelihood Ratio) D. F. p-value 

## 53

-------- ------------------------ ------ -------------- 

## 54
Test 1 92.8 10 < 0.0001 

## 55
Test 2 39.16 5 < 0.0001 

## 56
Test 3 10.93 4 0.0274 

## 57
Test 7a 16.1 2 0.0003195 

## 58 59 60 The p-value for Test 1 is less than .05. There appears to be a 

## 61 difference between response and/or variances among the dose 

## 62 levels, it seems appropriate to model the data. 

## 63 64 The p-value for Test 2 is less than .1. A non-homogeneous 

## 65 variance model appears to be appropriate. 

## 66 67 The p-value for Test 3 is less than .1. You may want to 

## 68
consider a different variance model. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-204 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 1 describe the data; you may want to consider another model. 

## 2 3 4 Benchmark Dose Computations: 

## 5 6 Specified Effect = 1.000000 

## 7 8 Risk Type = Estimated standard deviations from control 

## 9 10
Confidence Level = 0.950000 

## 11 12
BMD = 0.260501 

## 13 14
BMDL = 0.000148718 

## 15 16 17 H.3.7.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 18

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Hill Model

14:29 11/20 2009 Hill



## 19 20 21 H.3.7.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 22 23 24

==================================================================== 

## 25 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 26 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_Lung_EROD_wk53.(d) 

## 27 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_Lung_EROD_wk53.plt 

## 28
Fri Nov 20 14:29:11 2009 

## 29

==================================================================== 

## 30 31 Tbl 12, Week 53, Lung Microsomes EROD 

## 32

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 33 34 The form of the response function is: 

## 35 36 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-205 1 2 Dependent variable = Mean 

## 3 Independent variable = Dose 

## 4 Power parameter is not restricted 

## 5 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 6 7 Total number of dose groups = 6 

## 8 Total number of records with missing values = 0 

## 9
Maximum number of iterations = 250 

## 10 Relative Function Convergence has been set to: 1e-008 

## 11 Parameter Convergence has been set to: 1e-008 

## 12 13 14 15
Default Initial Parameter Values 

## 16 lalpha = 4.76968 

## 17
rho = 0 

## 18 intercept = 3.011 

## 19
v = 40.735 

## 20
n = 1.63324 

## 21
k = 3.46862 

## 22 23 24 Asymptotic Correlation Matrix of Parameter Estimates 

## 25 26 lalpha rho intercept v n k 

## 27 28 lalpha 1 -1 0.00098 -0.015 NA NA 

## 29 30
rho -1 1 -0.00098 0.015 NA NA 

## 31 32 intercept 0.00098 -0.00098 1 -1.5e-005 NA NA 

## 33 34
v -0.015 0.015 -1.5e-005 1 NA NA 

## 35 36

n NA NA NA NA NA NA 

## 37 38
k NA NA NA NA NA NA 

## 39 40 41 NA - This parameter's variance has been estimated as zero or less. 

## 42
THE MODEL HAS PROBABLY NOT CONVERGED!!! 

## 43 44 45 46
Parameter Estimates 

## 47 48
95.0% Wald Confidence Interval 

## 49 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 50 lalpha 16.2956 NA NA NA 

## 51
rho -3.01917 NA NA NA 

## 52 intercept 32.8392 NA NA NA 

## 53
v 81.7793 NA NA NA 

## 54
n 17.5977 NA NA NA 

## 55
k 324.491 NA NA NA 

## 56 57 At least some variance estimates are negative. 

## 58
THIS USUALLY MEANS THE MODEL HAS NOT CONVERGED! 

## 59 Try again from another starting point. 

## 60 61 62 63
Table of Data and Estimated Values of Interest 

## 64 65
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 66

------ --- -------- -------- ----------- ----------- ---------- 

## 67 68
0 8 3.01 32.8 1.58 17.8 -4.75 

## 69
3 8 27.1 32.8 5.27 17.8 -0.906 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-206 10 8 42.8 32.8 11.2 17.8 1.59 

## 1
22 8 36.6 32.8 13 17.8 0.594 

## 2
46 8 43.7 32.8 18.5 17.8 1.74 

## 3
100 8 43.7 32.8 6.32 17.8 1.73 

## 4 5 6 7 Model Descriptions for likelihoods calculated 

## 8 9 10 Model A1: Yij = Mu(i) + e(ij) 

## 11 Var{e(ij)} = Sigma^2 

## 12 13 Model A2: Yij = Mu(i) + e(ij) 

## 14 Var{e(ij)} = Sigma(i)^2 

## 15 16 Model A3: Yij = Mu(i) + e(ij) 

## 17 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 18 Model A3 uses any fixed variance parameters that 

## 19 were specified by the user 

## 20 21 Model R: Yi = Mu + e(i) 

## 22 Var{e(i)} = Sigma^2 

## 23 24 25
Likelihoods of Interest 

## 26 27 Model Log(likelihood) # Param's AIC 

## 28
A1 -135.267662 7 284.535325 

## 29
A2 -115.688533 12 255.377067 

## 30
A3 -121.151707 8 258.303413 

## 31
fitted -162.090242 6 336.180484 

## 32
R -162.090242 2 328.180484 

## 33 34 35 Explanation of Tests 

## 36 37 Test 1: Do responses and/or variances differ among Dose levels? 

## 38 (A2 vs. R) 

## 39 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 40 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 41 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 42 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 43 44
Tests of Interest 

## 45 46 Test -2*log(Likelihood Ratio) Test df p-value 

## 47 48
Test 1 92.8034 10 <.0001 

## 49
Test 2 39.1583 5 <.0001 

## 50
Test 3 10.9263 4 0.0274 

## 51
Test 4 81.8771 2 <.0001 

## 52 53 The p-value for Test 1 is less than .05. There appears to be a 

## 54 difference between response and/or variances among the dose levels 

## 55 It seems appropriate to model the data 

## 56 57 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 58 model appears to be appropriate 

## 59 60 The p-value for Test 3 is less than .1. You may want to consider a 

## 61
different variance model 

## 62 63 The p-value for Test 4 is less than .1. You may want to try a different 

## 64
model 

## 65 66 67 Benchmark Dose Computation 

## 68 69 Specified effect = 1 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-207 1 Risk Type = Estimated standard deviations from the control mean 

## 2 3
Confidence level = 0.95 

## 4 5
BMD = 301.687 

## 6 7 8 BMDL computation failed. 

## 9 10 11 H.3.7.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 12

0 10 20 30 40 50 60

0 20 40 60 80 100Mean Response

dose Power Model with 0.95 Confidence Level

14:29 11/20 2009 BMDBMDL Power



## 13 14 15 H.3.7.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 16 Unrestricted 17 18 19

==================================================================== 

## 20 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 21 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_Lung_EROD_wk53.(d) 

## 22 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_Lung_EROD_wk53.plt 

## 23
Fri Nov 20 14:29:12 2009 

## 24

==================================================================== 

## 25 26 Tbl 12, Week 53, Lung Microsomes EROD 

## 27

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 28 29 The form of the response function is: 

## 30 31 Y[dose] = control + slope * dose^power 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 The power is not restricted 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-208 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 1 2 Total number of dose groups = 6 

## 3 Total number of records with missing values = 0 

## 4
Maximum number of iterations = 250 

## 5 Relative Function Convergence has been set to: 1e-008 

## 6 Parameter Convergence has been set to: 1e-008 

## 7 8 9 10
Default Initial Parameter Values 

## 11 lalpha = 4.76968 

## 12
rho = 0 

## 13
control = 3.011 

## 14 slope = 23.6162 

## 15 power = 0.133025 

## 16 17 18 Asymptotic Correlation Matrix of Parameter Estimates 

## 19 20 lalpha rho control slope power 

## 21 22 lalpha 1 -0.96 -0.48 0.11 -0.048 

## 23 24
rho -0.96 1 0.45 -0.14 0.053 

## 25 26
control -0.48 0.45 1 -0.14 0.05 

## 27 28 slope 0.11 -0.14 -0.14 1 -0.93 

## 29 30 power -0.048 0.053 0.05 -0.93 1 

## 31 32 33 34
Parameter Estimates 

## 35 36
95.0% Wald Confidence Interval 

## 37 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 38 lalpha -1.03233 0.815925 -2.63152 0.566849 

## 39
rho 1.63033 0.23978 1.16037 2.10029 

## 40
control 3.01788 0.518168 2.00229 4.03347 

## 41 slope 24.0756 3.58644 17.0463 31.1049 

## 42 power 0.128899 0.0448635 0.040968 0.21683 

## 43 44 45 46
Table of Data and Estimated Values of Interest 

## 47 48
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 49

------ --- -------- -------- ----------- ----------- ---------- 

## 50 51
0 8 3.01 3.02 1.58 1.47 -0.0133 

## 52
3 8 27.1 30.8 5.27 9.74 -1.05 

## 53
10 8 42.8 35.4 11.2 10.9 1.92 

## 54
22 8 36.6 38.9 13 11.8 -0.554 

## 55
46 8 43.7 42.5 18.5 12.7 0.288 

## 56
100 8 43.7 46.6 6.32 13.7 -0.599 

## 57 58 59 60 Model Descriptions for likelihoods calculated 

## 61 62 63 Model A1: Yij = Mu(i) + e(ij) 

## 64 Var{e(ij)} = Sigma^2 

## 65 66 Model A2: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma(i)^2 

## 68 69 Model A3: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-209 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 1 Model A3 uses any fixed variance parameters that 

## 2 were specified by the user 

## 3 4 Model R: Yi = Mu + e(i) 

## 5 Var{e(i)} = Sigma^2 

## 6 7 8
Likelihoods of Interest 

## 9 10 Model Log(likelihood) # Param's AIC 

## 11
A1 -135.267662 7 284.535325 

## 12
A2 -115.688533 12 255.377067 

## 13
A3 -121.151707 8 258.303413 

## 14
fitted -125.400472 5 260.800944 

## 15
R -162.090242 2 328.180484 

## 16 17 18 Explanation of Tests 

## 19 20 Test 1: Do responses and/or variances differ among Dose levels? 

## 21 (A2 vs. R) 

## 22 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 23 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 24 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 25 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 26 27
Tests of Interest 

## 28 29 Test -2*log(Likelihood Ratio) Test df p-value 

## 30 31
Test 1 92.8034 10 <.0001 

## 32
Test 2 39.1583 5 <.0001 

## 33
Test 3 10.9263 4 0.0274 

## 34
Test 4 8.49753 3 0.03677 

## 35 36 The p-value for Test 1 is less than .05. There appears to be a 

## 37 difference between response and/or variances among the dose levels 

## 38 It seems appropriate to model the data 

## 39 40 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 41 model appears to be appropriate 

## 42 43 The p-value for Test 3 is less than .1. You may want to consider a 

## 44
different variance model 

## 45 46 The p-value for Test 4 is less than .1. You may want to try a different 

## 47
model 

## 48 49 50 Benchmark Dose Computation 

## 51 52 Specified effect = 1 

## 53 54 Risk Type = Estimated standard deviations from the control mean 

## 55 56
Confidence level = 0.95 

## 57 58
BMD = 3.76923e-010 

## 59 60 61
BMDL = 3.76923e-010 

## 62 63

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-210 H.3.8. National Toxicology Program. ( 2006): Tbl11 Index Week 31 1
H.3.8.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) c 4 <0.0001 21.34 0.00 47.30 3.3E+01 2.6E+01 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 21.34 0.00 47.30 3.3E+01 2.6E+01 nonconstant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 25.36 <0.0001 53.32 1.7E+01 1.1E+01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 21.10 <0.0001 51.06 4.6E+01 2.9E+01 nonconstant variance, power restricted ≥ 1

Hill 3 <.0001 21.10 0.00 49.06 4.6E+01 error nonconstant variance, n restricted >1, bound hit

linear 4 <.0001 25.36 <.0001 51.32 1.7E+01 1.1E+01 nonconstant variance

polynomial 3 <.0001 21.87 <.0001 49.83 3.9E+01 1.7E+01 nonconstant variance

power 3 <.0001 21.87 <.0001 49.83 4.5E+01 2.4E+01 nonconstant variance, power restricted ≥ 1
exponential (M2) 4 <0.0001 1.02 0.91 101.49 6.4E+01 5.7E+01 constant variance, power restricted ≥ 1
exponential (M3) 3 <0.0001 1.00 0.80 103.47 6.7E+01 5.7E+01 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 3.38 0.34 105.85 4.4E+01 3.3E+01 constant variance, power restricted ≥ 1
exponential (M5) 2 <0.0001 1.10 0.58 105.57 6.6E+01 3.9E+01 constant variance, power restricted ≥ 1

Hill 2 <.0001 1.10 0.58 105.57 6.6E+01 3.9E+01 constant variance, n restricted >1

linear 4 <.0001 3.38 0.50 103.85 4.4E+01 3.3E+01 constant variance

polynomial 3 <.0001 1.08 0.78 103.55 6.4E+01 3.9E+01 constant variance

power 3 <.0001 1.10 0.78 103.57 6.6E+01 3.9E+01 constant variance, power restricted ≥ 1

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 

## 3 4

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-211 H.3.8.2. Figure for Selected Model: Exponen tial (M2), Nonconstant Variance, Power 1 Restricted ≥ 1 2

0 1 2 3 4 5 6

0 20 40 60 80 100Mean Response

dose Exponential_beta Model 2 with 0.95 Confidence Level

16:50 11/20 2009 BMD BMDL Exponential



## 3 4 5 H.3.8.3. Output File for Selected Model: Expo nential (M2), Nonconstant Varian ce, Power 6 Restricted ≥ 1 7 8 9

==================================================================== 

## 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 11 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_Tbl11_31wk.(d) 

## 12 Gnuplot Plotting File: 

## 13
Fri Nov 20 16:50:52 2009 

## 14

==================================================================== 

## 15 16 Tbl 11, 31wk, Hep Cell Proliferation Labeling Index 

## 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 18 19 The form of the response function by Model: 

## 20 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 24 25 Note: Y[dose] is the median response for exposure = dose; 

## 26 sign = +1 for increasing trend in data; 

## 27 sign = -1 for decreasing trend. 

## 28 29
Model 2 is nested within Models 3 and 4. 

## 30
Model 3 is nested within Model 5. 

## 31
Model 4 is nested within Model 5. 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Data are assumed to be distributed: normally 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-212 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 1 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 2 3 Total number of dose groups = 6 

## 4 Total number of records with missing values = 0 

## 5 Maximum number of iterations = 250 

## 6 Relative Function Convergence has been set to: 1e-008 

## 7 Parameter Convergence has been set to: 1e-008 

## 8 9 MLE solution provided: Exact 

## 10 11 12
Initial Parameter Values 

## 13 14
Variable Model 2 

## 15

-------- -------- 

## 16 lnalpha -0.674004 

## 17
rho 2.29189 

## 18
a 0.31065 

## 19
b 0.024912 

## 20
c 12.9995 

## 21
d 1 

## 22 23 24 25
Parameter Estimates 

## 26 27
Variable Model 2 

## 28

-------- ------- 

## 29 lnalpha -0.495833 

## 30
rho 1.97486 

## 31
a 0.740304 

## 32
b 0.0199927 

## 33
c 5.16751 

## 34
d 18 

## 35 36 37 Table of Stats From Input Data 

## 38 39
Dose N Obs Mean Obs Std Dev 

## 40

----- --- ---------- ------------- 

## 41
0 9 0.327 0.189 

## 42
3 10 0.852 0.6514 

## 43
10 10 0.956 0.7368 

## 44
22 10 0.792 0.4617 

## 45
46 10 1.333 1.123 

## 46
100 10 3.846 3.08 

## 47 48 49
Estimated Values of Interest 

## 50 51
Dose Est Mean Est Std Scaled Residual 

## 52

------ ---------- --------- ---------------- 

## 53
0 0.6166 0.4987 -1.742 

## 54
3 0.651 0.5251 1.21 

## 55
10 0.7391 0.5925 1.158 

## 56
22 0.9186 0.7287 -0.5493 

## 57
46 1.419 1.102 -0.2466 

## 58
100 3.775 2.796 0.08069 

## 59 60 61 62
Other models for which likelihoods are calculated: 

## 63 64 Model A1: Yij = Mu(i) + e(ij) 

## 65 Var{e(ij)} = Sigma^2 

## 66 67 Model A2: Yij = Mu(i) + e(ij) 

## 68 Var{e(ij)} = Sigma(i)^2 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-213 Model A3: Yij = Mu(i) + e(ij) 

## 1 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 2 3 Model R: Yij = Mu + e(i) 

## 4 Var{e(ij)} = Sigma^2 

## 5 6 7 Likelihoods of Interest 

## 8 9 Model Log(likelihood) DF AIC 

## 10

------- ----------------- ---- ------------ 

## 11
A1 -47.23498 7 108.47 

## 12
A2 -8.679256 12 41.35851 

## 13
A3 -8.980651 8 33.9613 

## 14
R -63.44829 2 130.8966 

## 15
2 -19.6508 4 47.30161 

## 16 17 18 Additive constant for all log-likelihoods = -54.22. This constant added to the 

## 19 above values gives the log-likelihood including the term that does not 

## 20 depend on the model parameters. 

## 21 22 23 Explanation of Tests 

## 24 25 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 26 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 27 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 28 Test 4: Does Model 2 fit the data? (A3 vs. 2) 

## 29 30 31
Tests of Interest 

## 32 33 Test -2*log(Likelihood Ratio) D. F. p-value 

## 34

-------- ------------------------ ------ -------------- 

## 35
Test 1 109.5 10 < 0.0001 

## 36
Test 2 77.11 5 < 0.0001 

## 37
Test 3 0.6028 4 0.9628 

## 38
Test 4 21.34 4 0.0002711 

## 39 40 41 The p-value for Test 1 is less than .05. There appears to be a 

## 42 difference between response and/or variances among the dose 

## 43 levels, it seems appropriate to model the data. 

## 44 45 The p-value for Test 2 is less than .1. A non-homogeneous 

## 46 variance model appears to be appropriate. 

## 47 48 The p-value for Test 3 is greater than .1. The modeled 

## 49 variance appears to be appropriate here. 

## 50 51 The p-value for Test 4 is less than .1. Model 2 may not adequately 

## 52 describe the data; you may want to consider another model. 

## 53 54 55 Benchmark Dose Computations: 

## 56 57 Specified Effect = 1.000000 

## 58 59 Risk Type = Estimated standard deviations from control 

## 60 61
Confidence Level = 0.950000 

## 62 63
BMD = 32.7092 

## 64 65
BMDL = 26.1405 

## 66

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-214 H.3.9. Van Birgelen et al. (1995b): T4 UGT 1
H.3.9.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 4 <0.0001 35.16 <0.0001 38.57 5.0E+02 3.5E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 35.16 <0.0001 38.57 5.0E+02 3.5E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) c 3 <0.0001 1.01 0.80 6.42 1.2E+01 6.2E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 1.01 0.80 6.42 1.2E+01 6.2E+00 nonconstant variance, power restricted ≥ 1
exponential (M5) d 3 <0.0001 1.01 0.80 6.42 1.2E+01 6.2E+00 nonconstant variance, power unrestricted

Hill 2 <.0001 1.12 0.57 8.52 1.3E+01 6.1E+00 nonconstant variance, n restricted >1

Hill d 2 <.0001 1.12 0.57 8.52 1.3E+01 3.7E+00 nonconstant variance, n unrestricted

linear 4 <.0001 23.17 0.00 26.57 1.7E+02 9.4E+01 nonconstant variance

polynomial 4 <.0001 23.17 0.00 26.57 1.7E+02 9.4E+01 nonconstant variance

power 4 <.0001 23.17 0.00 26.57 1.7E+02 9.4E+01 nonconstant variance, power restricted ≥ 1, bound hit

power d 3 <.0001 5.05 0.17 10.45 4.0E+00 4.8E-01 nonconstant variance, power unrestricted
exponential (M2) 4 <0.0001 14.22 0.01 39.63 6.1E+02 5.2E+02 constant variance, power restricted ≥ 1
exponential (M3) 4 <0.0001 14.22 0.01 39.63 6.1E+02 5.2E+02 constant variance, power restricted ≥ 1
exponential (M4) 3 <0.0001 0.16 0.98 27.56 8.8E+01 3.6E+01 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 0.16 0.98 27.56 8.8E+01 3.6E+01 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 0.16 0.98 27.56 8.8E+01 3.6E+01 constant variance, power unrestricted

Hill 2 <.0001 0.10 0.95 29.51 7.1E+01 2.7E+01 constant variance, n restricted >1

Hill 2 <.0001 0.10 0.95 29.51 7.1E+01 1.9E+01 constant variance, n unrestricted

linear 4 <.0001 9.68 0.05 35.08 4.0E+02 3.0E+02 constant variance

polynomial 4 <.0001 9.68 0.05 35.08 4.0E+02 3.0E+02 constant variance

power 4 <.0001 9.68 0.05 35.08 4.0E+02 3.0E+02 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-215 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 3 <.0001 2.09 0.55 29.49 5.7E+01 9.9E+00 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.9.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

0 0.5

1 1.5

2 2.5

3 3.5

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:33 11/20 2009 BMD BMDL Exponential



## 5 6 7 H.3.9.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_T4_UGT.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 14:33:47 2009 

## 16

==================================================================== 

## 17 18 Tbl2, T4 UGT 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-216 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 6 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 4 

## 32

-------- -------- 

## 33 lnalpha -0.937573 

## 34
rho 1.54913 

## 35
a 0.3135 

## 36
b 0.00297568 

## 37
c 8.67464 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 4 

## 45

-------- ------- 

## 46 lnalpha -0.937201 

## 47
rho 1.6967 

## 48
a 0.294922 

## 49
b 0.0100397 

## 50
c 7.64822 

## 51
d 1 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 8 0.33 0.198 

## 59
14 8 0.6 0.4243 

## 60
26 8 0.64 0.4525 

## 61
47 8 0.87 0.9051 

## 62
320 8 2.08 1.329 

## 63
1024 8 2.59 0.8768 

## 64 65 66
Estimated Values of Interest 

## 67 68
Dose Est Mean Est Std Scaled Residual 

## 69

------ ---------- --------- ---------------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-217 0 0.2949 0.2221 0.4466 

## 1
14 0.552 0.3781 0.3589 

## 2
26 0.7454 0.4878 -0.6111 

## 3
47 1.032 0.6431 -0.7146 

## 4
320 2.177 1.211 -0.2259 

## 5
1024 2.256 1.248 0.758 

## 6 7 8 9
Other models for which likelihoods are calculated: 

## 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Model R: Yij = Mu + e(i) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) DF AIC 

## 27

------- ----------------- ---- ------------ 

## 28
A1 -9.701316 7 33.40263 

## 29
A2 4.934967 12 14.13007 

## 30
A3 2.296438 8 11.40712 

## 31
R -29.51921 2 63.03841 

## 32
4 1.790563 5 6.418874 

## 33 34 35 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 36 above values gives the log-likelihood including the term that does not 

## 37 depend on the model parameters. 

## 38 39 40 Explanation of Tests 

## 41 42 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 43 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 44 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 45 46 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 47 48 49
Tests of Interest 

## 50 51 Test -2*log(Likelihood Ratio) D. F. p-value 

## 52

-------- ------------------------ ------ -------------- 

## 53
Test 1 68.91 10 < 0.0001 

## 54
Test 2 29.27 5 < 0.0001 

## 55
Test 3 5.277 4 0.26 

## 56
Test 6a 1.012 3 0.7984 

## 57 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose 

## 61 levels, it seems appropriate to model the data. 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous 

## 64 variance model appears to be appropriate. 

## 65 66 The p-value for Test 3 is greater than .1. The modeled 

## 67 variance appears to be appropriate here. 

## 68 69 The p-value for Test 6a is greater than .1. Model 4 seems 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-218 to adequately describe the data. 

## 1 2 3 Benchmark Dose Computations: 

## 4 5 Specified Effect = 1.000000 

## 6 7 Risk Type = Estimated standard deviations from control 

## 8 9
Confidence Level = 0.950000 

## 10 11
BMD = 11.9766 

## 12 13
BMDL = 6.23544 

## 14 15 16 H.3.9.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 17 Unrestricted 18

0 0.5

1 1.5

2 2.5

3 3.5

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:33 11/20 2009 BMD BMDL Exponential



## 19 20 21 H.3.9.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 22 Power Unrestricted 23 24 25

==================================================================== 

## 26 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 27 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_Unrest_BMR1_T4_UGT.(d) 

## 28 Gnuplot Plotting File: 

## 29
Fri Nov 20 14:33:53 2009 

## 30

==================================================================== 

## 31 32 Tbl2, T4 UGT 

## 33

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 34 35 The form of the response function by Model: 

## 36

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-219 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 6 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 5 

## 32

-------- -------- 

## 33 lnalpha -0.937573 

## 34
rho 1.54913 

## 35
a 0.3135 

## 36
b 0.00297568 

## 37
c 8.67464 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 5 

## 45

-------- ------- 

## 46 lnalpha -0.937201 

## 47
rho 1.6967 

## 48
a 0.294922 

## 49
b 0.0100397 

## 50
c 7.64822 

## 51
d 1 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 8 0.33 0.198 

## 59
14 8 0.6 0.4243 

## 60
26 8 0.64 0.4525 

## 61
47 8 0.87 0.9051 

## 62
320 8 2.08 1.329 

## 63
1024 8 2.59 0.8768 

## 64 65 66
Estimated Values of Interest 

## 67 68
Dose Est Mean Est Std Scaled Residual 

## 69

------ ---------- --------- ---------------- 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-220 0 0.2949 0.2221 0.4466 

## 1
14 0.552 0.3781 0.3589 

## 2
26 0.7454 0.4878 -0.6111 

## 3
47 1.032 0.6431 -0.7146 

## 4
320 2.177 1.211 -0.2259 

## 5
1024 2.256 1.248 0.758 

## 6 7 8 9
Other models for which likelihoods are calculated: 

## 10 11 Model A1: Yij = Mu(i) + e(ij) 

## 12 Var{e(ij)} = Sigma^2 

## 13 14 Model A2: Yij = Mu(i) + e(ij) 

## 15 Var{e(ij)} = Sigma(i)^2 

## 16 17 Model A3: Yij = Mu(i) + e(ij) 

## 18 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Model R: Yij = Mu + e(i) 

## 21 Var{e(ij)} = Sigma^2 

## 22 23 24
Likelihoods of Interest 

## 25 26 Model Log(likelihood) DF AIC 

## 27

------- ----------------- ---- ------------ 

## 28
A1 -9.701316 7 33.40263 

## 29
A2 4.934967 12 14.13007 

## 30
A3 2.296438 8 11.40712 

## 31
R -29.51921 2 63.03841 

## 32
5 1.790563 5 6.418874 

## 33 34 35 Additive constant for all log-likelihoods = -44.11. This constant added to the 

## 36 above values gives the log-likelihood including the term that does not 

## 37 depend on the model parameters. 

## 38 39 40 Explanation of Tests 

## 41 42 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 43 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 44 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 45 46 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 47 48 49
Tests of Interest 

## 50 51 Test -2*log(Likelihood Ratio) D. F. p-value 

## 52

-------- ------------------------ ------ -------------- 

## 53
Test 1 68.91 10 < 0.0001 

## 54
Test 2 29.27 5 < 0.0001 

## 55
Test 3 5.277 4 0.26 

## 56
Test 7a 1.012 3 0.7984 

## 57 58 59 The p-value for Test 1 is less than .05. There appears to be a 

## 60 difference between response and/or variances among the dose 

## 61 levels, it seems appropriate to model the data. 

## 62 63 The p-value for Test 2 is less than .1. A non-homogeneous 

## 64 variance model appears to be appropriate. 

## 65 66 The p-value for Test 3 is greater than .1. The modeled 

## 67 variance appears to be appropriate here. 

## 68 69 The p-value for Test 7a is greater than .1. Model 5 seems 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-221 to adequately describe the data. 

## 1 2 3 Benchmark Dose Computations: 

## 4 5 Specified Effect = 1.000000 

## 6 7 Risk Type = Estimated standard deviations from control 

## 8 9
Confidence Level = 0.950000 

## 10 11
BMD = 11.9766 

## 12 13
BMDL = 6.23544 

## 14 15 16 H.3.9.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 17

0 0.5

1 1.5

2 2.5

3 3.5

0 200 400 600 800 1000Mean Response

dose Hill Model with 0.95 Confidence Level

14:33 11/20 2009 BMD BMDL Hill



## 18 19 20 H.3.9.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 21 22 23

==================================================================== 

## 24 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 25 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_T4_UGT.(d) 

## 26 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_T4_UGT.plt 

## 27
Fri Nov 20 14:33:54 2009 

## 28

==================================================================== 

## 29 30 Tbl2, T4 UGT 

## 31

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 32 33 The form of the response function is: 

## 34 35 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 36 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-222 1 Dependent variable = Mean 

## 2 Independent variable = Dose 

## 3 Power parameter is not restricted 

## 4 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 5 6 Total number of dose groups = 6 

## 7 Total number of records with missing values = 0 

## 8
Maximum number of iterations = 250 

## 9 Relative Function Convergence has been set to: 1e-008 

## 10 Parameter Convergence has been set to: 1e-008 

## 11 12 13 14
Default Initial Parameter Values 

## 15 lalpha = -0.462247 

## 16
rho = 0 

## 17 intercept = 0.33 

## 18
v = 2.26 

## 19
n = 0.430022 

## 20
k = 459.884 

## 21 22 23 Asymptotic Correlation Matrix of Parameter Estimates 

## 24 25 lalpha rho intercept v n k 

## 26 27 lalpha 1 0.036 -0.26 -0.16 -0.017 0.037 

## 28 29
rho 0.036 1 0.48 -0.46 0.02 -0.2 

## 30 31 intercept -0.26 0.48 1 -0.37 0.26 -0.15 

## 32 33
v -0.16 -0.46 -0.37 1 -0.64 0.81 

## 34 35
n -0.017 0.02 0.26 -0.64 1 -0.85 

## 36 37
k 0.037 -0.2 -0.15 0.81 -0.85 1 

## 38 39 40 41
Parameter Estimates 

## 42 43
95.0% Wald Confidence Interval 

## 44 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 45 lalpha -0.935113 0.256585 -1.43801 -0.432217 

## 46
rho 1.68648 0.441197 0.821746 2.55121 

## 47 intercept 0.295265 0.0703668 0.157348 0.433181 

## 48
v 2.14661 0.547941 1.07267 3.22056 

## 49
n 1.16336 0.46393 0.25407 2.07264 

## 50
k 80.2777 52.4068 -22.4378 182.993 

## 51 52 53 54
Table of Data and Estimated Values of Interest 

## 55 56
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 57

------ --- -------- -------- ----------- ----------- ---------- 

## 58 59
0 8 0.33 0.295 0.198 0.224 0.439 

## 60
14 8 0.6 0.544 0.424 0.375 0.422 

## 61
26 8 0.64 0.751 0.453 0.492 -0.637 

## 62
47 8 0.87 1.04 0.905 0.65 -0.76 

## 63
320 8 2.08 2.08 1.33 1.16 -0.00947 

## 64
1024 8 2.59 2.34 0.877 1.28 0.56 

## 65 66 67 68 Model Descriptions for likelihoods calculated 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-223 1 Model A1: Yij = Mu(i) + e(ij) 

## 2 Var{e(ij)} = Sigma^2 

## 3 4 Model A2: Yij = Mu(i) + e(ij) 

## 5 Var{e(ij)} = Sigma(i)^2 

## 6 7 Model A3: Yij = Mu(i) + e(ij) 

## 8 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 9 Model A3 uses any fixed variance parameters that 

## 10 were specified by the user 

## 11 12 Model R: Yi = Mu + e(i) 

## 13 Var{e(i)} = Sigma^2 

## 14 15 16
Likelihoods of Interest 

## 17 18 Model Log(likelihood) # Param's AIC 

## 19
A1 -9.701316 7 33.402631 

## 20
A2 4.934967 12 14.130066 

## 21
A3 2.296438 8 11.407124 

## 22
fitted 1.738274 6 8.523453 

## 23
R -29.519205 2 63.038411 

## 24 25 26 Explanation of Tests 

## 27 28 Test 1: Do responses and/or variances differ among Dose levels? 

## 29 (A2 vs. R) 

## 30 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 31 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 32 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 33 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 34 35
Tests of Interest 

## 36 37 Test -2*log(Likelihood Ratio) Test df p-value 

## 38 39
Test 1 68.9083 10 <.0001 

## 40
Test 2 29.2726 5 <.0001 

## 41
Test 3 5.27706 4 0.26 

## 42
Test 4 1.11633 2 0.5723 

## 43 44 The p-value for Test 1 is less than .05. There appears to be a 

## 45 difference between response and/or variances among the dose levels 

## 46 It seems appropriate to model the data 

## 47 48 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 49 model appears to be appropriate 

## 50 51 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 52 to be appropriate here 

## 53 54 The p-value for Test 4 is greater than .1. The model chosen seems 

## 55 to adequately describe the data 

## 56 57 58 Benchmark Dose Computation 

## 59 60 Specified effect = 1 

## 61 62 Risk Type = Estimated standard deviations from the control mean 

## 63 64
Confidence level = 0.95 

## 65 66
BMD = 12.6477 

## 67 68
BMDL = 3.73502 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-224 H.3.9.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

0 0.5

1 1.5

2 2.5

3 3.5

0 200 400 600 800 1000Mean Response

dose Power Model with 0.95 Confidence Level

14:33 11/20 2009 BMD BMDL Power



## 2 3 4 H.3.9.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 Unrestricted 6 7 8

==================================================================== 

## 9 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 10 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_T4_UGT.(d) 

## 11 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_T4_UGT.plt 

## 12
Fri Nov 20 14:33:55 2009 

## 13

==================================================================== 

## 14 15 Tbl2, T4 UGT 

## 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 17 18 The form of the response function is: 

## 19 20 Y[dose] = control + slope * dose^power 

## 21 22 23 Dependent variable = Mean 

## 24 Independent variable = Dose 

## 25 The power is not restricted 

## 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 27 28 Total number of dose groups = 6 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-225 lalpha = -0.462247 

## 1
rho = 0 

## 2
control = 0.33 

## 3 slope = 0.0542809 

## 4 power = 0.537973 

## 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 

## 8 9 lalpha rho control slope power 

## 10 11 lalpha 1 0.032 -0.26 -0.19 0.071 

## 12 13
rho 0.032 1 0.57 0.021 -0.19 

## 14 15
control -0.26 0.57 1 -0.23 0.077 

## 16 17 slope -0.19 0.021 -0.23 1 -0.94 

## 18 19 power 0.071 -0.19 0.077 -0.94 1 

## 20 21 22 23
Parameter Estimates 

## 24 25
95.0% Wald Confidence Interval 

## 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 27 lalpha -0.85465 0.259915 -1.36407 -0.345225 

## 28
rho 1.67517 0.448857 0.795428 2.55492 

## 29
control 0.275898 0.0675474 0.143507 0.408288 

## 30 slope 0.12137 0.0517127 0.0200146 0.222725 

## 31 power 0.43322 0.0764873 0.283308 0.583132 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 8 0.33 0.276 0.198 0.222 0.69 

## 41
14 8 0.6 0.657 0.424 0.459 -0.349 

## 42
26 8 0.64 0.774 0.453 0.526 -0.719 

## 43
47 8 0.87 0.919 0.905 0.608 -0.229 

## 44
320 8 2.08 1.75 1.33 1.04 0.886 

## 45
1024 8 2.59 2.72 0.877 1.51 -0.245 

## 46 47 48 49 Model Descriptions for likelihoods calculated 

## 50 51 52 Model A1: Yij = Mu(i) + e(ij) 

## 53 Var{e(ij)} = Sigma^2 

## 54 55 Model A2: Yij = Mu(i) + e(ij) 

## 56 Var{e(ij)} = Sigma(i)^2 

## 57 58 Model A3: Yij = Mu(i) + e(ij) 

## 59 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 60 Model A3 uses any fixed variance parameters that 

## 61 were specified by the user 

## 62 63 Model R: Yi = Mu + e(i) 

## 64 Var{e(i)} = Sigma^2 

## 65 66 67
Likelihoods of Interest 

## 68 69 Model Log(likelihood) # Param's AIC 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-226 A1 -9.701316 7 33.402631 

## 1
A2 4.934967 12 14.130066 

## 2
A3 2.296438 8 11.407124 

## 3
fitted -0.226526 5 10.453053 

## 4
R -29.519205 2 63.038411 

## 5 6 7 Explanation of Tests 

## 8 9 Test 1: Do responses and/or variances differ among Dose levels? 

## 10 (A2 vs. R) 

## 11 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 12 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 13 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 14 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 15 16
Tests of Interest 

## 17 18 Test -2*log(Likelihood Ratio) Test df p-value 

## 19 20
Test 1 68.9083 10 <.0001 

## 21
Test 2 29.2726 5 <.0001 

## 22
Test 3 5.27706 4 0.26 

## 23
Test 4 5.04593 3 0.1685 

## 24 25 The p-value for Test 1 is less than .05. There appears to be a 

## 26 difference between response and/or variances among the dose levels 

## 27 It seems appropriate to model the data 

## 28 29 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 30 model appears to be appropriate 

## 31 32 The p-value for Test 3 is greater than .1. The modeled variance appears 

## 33 to be appropriate here 

## 34 35 The p-value for Test 4 is greater than .1. The model chosen seems 

## 36 to adequately describe the data 

## 37 38 39 Benchmark Dose Computation 

## 40 41 Specified effect = 1 

## 42 43 Risk Type = Estimated standard deviations from the control mean 

## 44 45
Confidence level = 0.95 

## 46 47
BMD = 4.02257 

## 48 49 50
BMDL = 0.480637 

## 51 52

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-227 H.3.10. Van Birgelen et al. (1995b): UGT 1A1 1
H.3.10.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 3 0.00 29.54 <0.0001 167.34 7.4E+02 2.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M3) 3 0.00 29.54 <0.0001 167.34 7.4E+02 2.1E+02 nonconstant variance, power restricted ≥ 1
exponential (M4) c 2 0.00 1.28 0.53 141.08 1.6E+00 8.5E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) 2 0.00 1.28 0.53 141.08 1.6E+00 8.5E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) d 2 0.00 1.28 0.53 141.08 1.6E+00 8.5E-01 nonconstant variance, power unrestricted

Hill 1 0.00 1.31 0.25 143.11 1.8E+00 error nonconstant variance, n restricted >1

Hill d 1 0.00 1.31 0.25 143.11 1.8E+00 error nonconstant variance, n unrestricted

linear 3 0.00 27.83 <.0001 165.63 2.1E+02 5.8E+01 nonconstant variance

polynomial 3 0.00 30.93 <.0001 168.73 1.8E+03 2.9E+01 nonconstant variance

power 3 0.00 27.83 <.0001 165.63 2.1E+02 5.8E+01 nonconstant variance, power restricted ≥ 1, bound hit

power d 2 0.00 5.39 0.07 145.19 3.4E-03 3.4E-03 nonconstant variance, power unrestricted
exponential (M2) 3 0.00 22.45 <0.0001 165.95 1.3E+03 6.4E+02 constant variance, power restricted ≥ 1
exponential (M3) 3 0.00 22.45 <0.0001 165.95 1.3E+03 6.4E+02 constant variance, power restricted ≥ 1
exponential (M4) 2 0.00 7.89 0.02 153.38 1.1E+01 4.7E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.00 7.89 0.02 153.38 1.1E+01 4.7E+00 constant variance, power restricted ≥ 1
exponential (M5) 2 0.00 7.89 0.02 153.38 1.1E+01 4.7E+00 constant variance, power unrestricted

Hill 1 0.00 8.15 0.00 155.65 1.3E+01 3.0E+00 constant variance, n restricted >1

Hill 1 0.00 8.15 0.00 155.65 1.3E+01 1.9E+00 constant variance, n unrestricted

linear 3 0.00 22.15 <.0001 165.65 1.1E+03 4.9E+02 constant variance

polynomial 3 0.00 22.15 <.0001 165.65 1.1E+03 4.9E+02 constant variance

power 3 0.00 22.15 <.0001 165.65 1.1E+03 4.9E+02 constant variance, power restricted ≥ 1, bound hit

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-228 Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

power 2 0.00 12.90 0.00 158.40 1.6E-01 5.2E-06 constant variance, power unrestricted

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix

d Alternate model also presented in this appendix 

## 1 2 H.3.10.2. Figure for Selected Model: Exponen tial (M4), Nonconstant Variance, Power 3 Restricted ≥ 1 4

-100 0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 4 with 0.95 Confidence Level

14:34 11/20 2009 BMD BMDL Exponential



## 5 6 7 H.3.10.3. Output File for Selected Model: Expo nential (M4), Nonconstant Varian ce, Power 8 Restricted ≥ 1 9 10 11

==================================================================== 

## 12 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 13 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_UGT_1A1.(d) 

## 14 Gnuplot Plotting File: 

## 15
Fri Nov 20 14:34:36 2009 

## 16

==================================================================== 

## 17 18 Tbl2, UGT_1A1 

## 19

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 20 21 The form of the response function by Model: 

## 22

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-229 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 1 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 2 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 3 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 4 5 Note: Y[dose] is the median response for exposure = dose; 

## 6 sign = +1 for increasing trend in data; 

## 7 sign = -1 for decreasing trend. 

## 8 9
Model 2 is nested within Models 3 and 4. 

## 10
Model 3 is nested within Model 5. 

## 11
Model 4 is nested within Model 5. 

## 12 13 14 Dependent variable = Mean 

## 15 Independent variable = Dose 

## 16 Data are assumed to be distributed: normally 

## 17 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 18 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 19 20 Total number of dose groups = 5 

## 21 Total number of records with missing values = 0 

## 22
Maximum number of iterations = 250 

## 23 Relative Function Convergence has been set to: 1e-008 

## 24 Parameter Convergence has been set to: 1e-008 

## 25 26 MLE solution provided: Exact 

## 27 28 29
Initial Parameter Values 

## 30 31
Variable Model 4 

## 32

-------- -------- 

## 33 lnalpha -1.53604 

## 34
rho 1.59958 

## 35
a 95.95 

## 36
b 0.00148532 

## 37
c 4.94633 

## 38
d 1 

## 39 40 41 42
Parameter Estimates 

## 43 44
Variable Model 4 

## 45

-------- ------- 

## 46 lnalpha -10.1636 

## 47
rho 3.25851 

## 48
a 101.863 

## 49
b 0.0256373 

## 50
c 3.78343 

## 51
d 1 

## 52 53 54 Table of Stats From Input Data 

## 55 56
Dose N Obs Mean Obs Std Dev 

## 57

----- --- ---------- ------------- 

## 58
0 3 101 15.59 

## 59
14 3 194 36.37 

## 60
47 3 304 17.32 

## 61
320 3 452 48.5 

## 62
1024 3 296 149 

## 63 64 65
Estimated Values of Interest 

## 66 67
Dose Est Mean Est Std Scaled Residual 

## 68

------ ---------- --------- ---------------- 

## 69
0 101.9 11.6 -0.1288 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-230 14 187.4 31.32 0.3668 

## 1
47 300.4 67.58 0.09183 

## 2
320 385.3 101.4 1.139 

## 3
1024 385.4 101.4 -1.527 

## 4 5 6 7 Other models for which likelihoods are calculated: 

## 8 9 Model A1: Yij = Mu(i) + e(ij) 

## 10 Var{e(ij)} = Sigma^2 

## 11 12 Model A2: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = Sigma(i)^2 

## 14 15 Model A3: Yij = Mu(i) + e(ij) 

## 16 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 17 18 Model R: Yij = Mu + e(i) 

## 19 Var{e(ij)} = Sigma^2 

## 20 21 22
Likelihoods of Interest 

## 23 24 Model Log(likelihood) DF AIC 

## 25

------- ----------------- ---- ------------ 

## 26
A1 -68.74833 6 149.4967 

## 27
A2 -58.69126 10 137.3825 

## 28
A3 -64.89907 7 143.7981 

## 29
R -80.72265 2 165.4453 

## 30
4 -65.54073 5 141.0815 

## 31 32 33 Additive constant for all log-likelihoods = -13.78. This constant added to the 

## 34 above values gives the log-likelihood including the term that does not 

## 35 depend on the model parameters. 

## 36 37 38 Explanation of Tests 

## 39 40 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 41 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 42 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 43 44 Test 6a: Does Model 4 fit the data? (A3 vs 4) 

## 45 46 47
Tests of Interest 

## 48 49 Test -2*log(Likelihood Ratio) D. F. p-value 

## 50

-------- ------------------------ ------ -------------- 

## 51
Test 1 44.06 8 < 0.0001 

## 52
Test 2 20.11 4 0.0004741 

## 53
Test 3 12.42 3 0.006087 

## 54
Test 6a 1.283 2 0.5264 

## 55 56 57 The p-value for Test 1 is less than .05. There appears to be a 

## 58 difference between response and/or variances among the dose 

## 59 levels, it seems appropriate to model the data. 

## 60 61 The p-value for Test 2 is less than .1. A non-homogeneous 

## 62 variance model appears to be appropriate. 

## 63 64 The p-value for Test 3 is less than .1. You may want to 

## 65
consider a different variance model. 

## 66 67 The p-value for Test 6a is greater than .1. Model 4 seems 

## 68 to adequately describe the data. 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-231 1 Benchmark Dose Computations: 

## 2 3 Specified Effect = 1.000000 

## 4 5 Risk Type = Estimated standard deviations from control 

## 6 7 Confidence Level = 0.950000 

## 8 9
BMD = 1.62983 

## 10 11
BMDL = 0.853335 

## 12 13 14 H.3.10.4. Figure for Unrestricted Model: Expon ential (M5), Nonconstant Variance, Power 15 Unrestricted 16

-100 0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

14:34 11/20 2009 BMD BMDL Exponential



## 17 18 19 H.3.10.5. Output File for Unrestricted Model: Exponential (M5), Non constant Variance, 20 Power Unrestricted 21 22 23

==================================================================== 

## 24 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 25 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_Unrest_BMR1_UGT_1A1.(d) 

## 26 Gnuplot Plotting File: 

## 27
Fri Nov 20 14:34:44 2009 

## 28

==================================================================== 

## 29 30 Tbl2, UGT_1A1 

## 31

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 32 33 The form of the response function by Model: 

## 34 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 35 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 36 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-232 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 1 2 Note: Y[dose] is the median response for exposure = dose; 

## 3 sign = +1 for increasing trend in data; 

## 4 sign = -1 for decreasing trend. 

## 5 6
Model 2 is nested within Models 3 and 4. 

## 7 Model 3 is nested within Model 5. 

## 8
Model 4 is nested within Model 5. 

## 9 10 11 Dependent variable = Mean 

## 12 Independent variable = Dose 

## 13 Data are assumed to be distributed: normally 

## 14 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 15 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 16 17 Total number of dose groups = 5 

## 18 Total number of records with missing values = 0 

## 19
Maximum number of iterations = 250 

## 20 Relative Function Convergence has been set to: 1e-008 

## 21 Parameter Convergence has been set to: 1e-008 

## 22 23 MLE solution provided: Exact 

## 24 25 26
Initial Parameter Values 

## 27 28
Variable Model 5 

## 29

-------- -------- 

## 30 lnalpha -1.53604 

## 31
rho 1.59958 

## 32
a 95.95 

## 33
b 0.00148532 

## 34
c 4.94633 

## 35
d 1 

## 36 37 38 39
Parameter Estimates 

## 40 41
Variable Model 5 

## 42

-------- ------- 

## 43 lnalpha -10.1636 

## 44
rho 3.25851 

## 45
a 101.863 

## 46
b 0.0256373 

## 47
c 3.78343 

## 48
d 1 

## 49 50 51 Table of Stats From Input Data 

## 52 53
Dose N Obs Mean Obs Std Dev 

## 54

----- --- ---------- ------------- 

## 55
0 3 101 15.59 

## 56
14 3 194 36.37 

## 57
47 3 304 17.32 

## 58
320 3 452 48.5 

## 59
1024 3 296 149 

## 60 61 62
Estimated Values of Interest 

## 63 64
Dose Est Mean Est Std Scaled Residual 

## 65

------ ---------- --------- ---------------- 

## 66
0 101.9 11.6 -0.1288 

## 67
14 187.4 31.32 0.3668 

## 68
47 300.4 67.58 0.09183 

## 69
320 385.3 101.4 1.139 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-233 1024 385.4 101.4 -1.527 

## 1 2 3 4
Other models for which likelihoods are calculated: 

## 5 6 Model A1: Yij = Mu(i) + e(ij) 

## 7 Var{e(ij)} = Sigma^2 

## 8 9 Model A2: Yij = Mu(i) + e(ij) 

## 10 Var{e(ij)} = Sigma(i)^2 

## 11 12 Model A3: Yij = Mu(i) + e(ij) 

## 13 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 14 15 Model R: Yij = Mu + e(i) 

## 16 Var{e(ij)} = Sigma^2 

## 17 18 19
Likelihoods of Interest 

## 20 21 Model Log(likelihood) DF AIC 

## 22

------- ----------------- ---- ------------ 

## 23
A1 -68.74833 6 149.4967 

## 24
A2 -58.69126 10 137.3825 

## 25
A3 -64.89907 7 143.7981 

## 26
R -80.72265 2 165.4453 

## 27
5 -65.54073 5 141.0815 

## 28 29 30 Additive constant for all log-likelihoods = -13.78. This constant added to the 

## 31 above values gives the log-likelihood including the term that does not 

## 32 depend on the model parameters. 

## 33 34 35 Explanation of Tests 

## 36 37 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 38 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 39 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 40 41 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 42 43 44
Tests of Interest 

## 45 46 Test -2*log(Likelihood Ratio) D. F. p-value 

## 47

-------- ------------------------ ------ -------------- 

## 48
Test 1 44.06 8 < 0.0001 

## 49
Test 2 20.11 4 0.0004741 

## 50
Test 3 12.42 3 0.006087 

## 51
Test 7a 1.283 2 0.5264 

## 52 53 54 The p-value for Test 1 is less than .05. There appears to be a 

## 55 difference between response and/or variances among the dose 

## 56 levels, it seems appropriate to model the data. 

## 57 58 The p-value for Test 2 is less than .1. A non-homogeneous 

## 59 variance model appears to be appropriate. 

## 60 61 The p-value for Test 3 is less than .1. You may want to 

## 62
consider a different variance model. 

## 63 64 The p-value for Test 7a is greater than .1. Model 5 seems 

## 65 to adequately describe the data. 

## 66 67 68 Benchmark Dose Computations: 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-234 Specified Effect = 1.000000 

## 1 2 Risk Type = Estimated standard deviations from control 

## 3 4
Confidence Level = 0.950000 

## 5 6
BMD = 1.62983 

## 7 8
BMDL = 0.853335 

## 9 10 11 12 H.3.10.6. Figure for Unrestricted M odel: Hill, Nonconstant Variance, n Unrestr icted 13

-100 0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Hill Model

14:34 11/20 2009 BMD Hill



## 14 15 16 H.3.10.7. Output File for Unrestricted Model: Hil l, Nonconstant Variance, n Unrestricted 17 18 19

==================================================================== 

## 20 Hill Model. (Version: 2.14; Date: 06/26/2008) 

## 21 Input Data File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_UGT_1A1.(d) 

## 22 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Hill_Unrest_BMR1_UGT_1A1.plt 

## 23
Fri Nov 20 14:34:45 2009 

## 24

==================================================================== 

## 25 26 Tbl2, UGT_1A1 

## 27

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 28 29 The form of the response function is: 

## 30 31 Y[dose] = intercept + v*dose^n/(k^n + dose^n) 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Power parameter is not restricted 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-235 The variance is to be modeled as Var(i) = exp(lalpha + rho * ln(mean(i))) 

## 1 2 Total number of dose groups = 5 

## 3 Total number of records with missing values = 0 

## 4
Maximum number of iterations = 250 

## 5 Relative Function Convergence has been set to: 1e-008 

## 6 Parameter Convergence has been set to: 1e-008 

## 7 8 9 10
Default Initial Parameter Values 

## 11 lalpha = 8.57191 

## 12
rho = 0 

## 13 intercept = 101 

## 14
v = 351 

## 15
n = 0.273231 

## 16
k = 55.25 

## 17 18 19 Asymptotic Correlation Matrix of Parameter Estimates 

## 20 21 lalpha rho intercept v n k 

## 22 23 lalpha 1 -0.99 -0.19 0.12 0.12 -0.017 

## 24 25
rho -0.99 1 0.18 -0.16 -0.12 0.0049 

## 26 27 intercept -0.19 0.18 1 -0.11 0.031 0.096 

## 28 29
v 0.12 -0.16 -0.11 1 -0.61 0.82 

## 30 31
n 0.12 -0.12 0.031 -0.61 1 -0.76 

## 32 33
k -0.017 0.0049 0.096 0.82 -0.76 1 

## 34 35 36 37
Parameter Estimates 

## 38 39
95.0% Wald Confidence Interval 

## 40 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 41 lalpha -10.516 3.69809 -17.7641 -3.26786 

## 42
rho 3.32204 0.675078 1.99891 4.64517 

## 43 intercept 101.644 6.48157 88.9405 114.348 

## 44
v 298.646 56.3141 188.273 409.02 

## 45
n 1.1568 0.50134 0.17419 2.13941 

## 46
k 29.0772 13.7717 2.08512 56.0693 

## 47 48 49 50
Table of Data and Estimated Values of Interest 

## 51 52
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 53

------ --- -------- -------- ----------- ----------- ---------- 

## 54 55
0 3 101 102 15.6 11.2 -0.0994 

## 56
14 3 194 191 36.4 32.1 0.143 

## 57
47 3 304 291 17.3 64.6 0.338 

## 58
320 3 452 383 48.5 102 1.18 

## 59
1024 3 296 396 149 107 -1.61 

## 60 61 62 63 Model Descriptions for likelihoods calculated 

## 64 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-236 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 4 Model A3 uses any fixed variance parameters that 

## 5 were specified by the user 

## 6 7 Model R: Yi = Mu + e(i) 

## 8 Var{e(i)} = Sigma^2 

## 9 10 11
Likelihoods of Interest 

## 12 13 Model Log(likelihood) # Param's AIC 

## 14
A1 -68.748326 6 149.496653 

## 15
A2 -58.691256 10 137.382511 

## 16
A3 -64.899072 7 143.798144 

## 17
fitted -65.554216 6 143.108432 

## 18
R -80.722651 2 165.445302 

## 19 20 21 Explanation of Tests 

## 22 23 Test 1: Do responses and/or variances differ among Dose levels? 

## 24 (A2 vs. R) 

## 25 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 26 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 27 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 28 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 29 30
Tests of Interest 

## 31 32 Test -2*log(Likelihood Ratio) Test df p-value 

## 33 34
Test 1 44.0628 8 <.0001 

## 35
Test 2 20.1141 4 0.0004741 

## 36
Test 3 12.4156 3 0.006087 

## 37
Test 4 1.31029 1 0.2523 

## 38 39 The p-value for Test 1 is less than .05. There appears to be a 

## 40 difference between response and/or variances among the dose levels 

## 41 It seems appropriate to model the data 

## 42 43 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 44 model appears to be appropriate 

## 45 46 The p-value for Test 3 is less than .1. You may want to consider a 

## 47
different variance model 

## 48 49 The p-value for Test 4 is greater than .1. The model chosen seems 

## 50 to adequately describe the data 

## 51 52 53 Benchmark Dose Computation 

## 54 55 Specified effect = 1 

## 56 57 Risk Type = Estimated standard deviations from the control mean 

## 58 59
Confidence level = 0.95 

## 60 61
BMD = 1.76282 

## 62 63 64 BMDL computation failed. 

## 65

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-237 H.3.10.8. Figure for Unrestricted Model: Power, Nonconstant Variance, Power Unrestricted 1

-100 0 100 200 300 400 500 600 700

0 200 400 600 800 1000Mean Response

dose Power Model with 0.95 Confidence Level

14:34 11/20 2009 BMDBMDL Power



## 2 3 4 H.3.10.9. Output File for Unrestricted Model: Power, Nonconstant Variance, Power 5 Unrestricted 6 7 8

==================================================================== 

## 9 Power Model. (Version: 2.15; Date: 04/07/2008) 

## 10 Input Data File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_UGT_1A1.(d) 

## 11 Gnuplot Plotting File: C:\USEPA\BMDS21\Nov20\Pwr_Unrest_BMR1_UGT_1A1.plt 

## 12
Fri Nov 20 14:34:47 2009 

## 13

==================================================================== 

## 14 15 Tbl2, UGT_1A1 

## 16

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 17 18 The form of the response function is: 

## 19 20 Y[dose] = control + slope * dose^power 

## 21 22 23 Dependent variable = Mean 

## 24 Independent variable = Dose 

## 25 The power is not restricted 

## 26 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 27 28 Total number of dose groups = 5 

## 29 Total number of records with missing values = 0 

## 30
Maximum number of iterations = 250 

## 31 Relative Function Convergence has been set to: 1e-008 

## 32 Parameter Convergence has been set to: 1e-008 

## 33 34 35 36
Default Initial Parameter Values 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-238 lalpha = 8.57191 

## 1
rho = 0 

## 2
control = 101 

## 3 slope = 75.1984 

## 4 power = 0.19277 

## 5 6 7 Asymptotic Correlation Matrix of Parameter Estimates 

## 8 9 lalpha rho control slope power 

## 10 11 lalpha 1 -0.99 -0.22 0.054 0.018 

## 12 13
rho -0.99 1 0.2 -0.038 -0.052 

## 14 15
control -0.22 0.2 1 -0.2 0.11 

## 16 17 slope 0.054 -0.038 -0.2 1 -0.95 

## 18 19 power 0.018 -0.052 0.11 -0.95 1 

## 20 21 22 23
Parameter Estimates 

## 24 25
95.0% Wald Confidence Interval 

## 26 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

## 27 lalpha -11.5264 3.45692 -18.3019 -4.75098 

## 28
rho 3.53579 0.629031 2.30291 4.76867 

## 29
control 101.425 6.34917 88.981 113.869 

## 30 slope 53.9904 20.7283 13.3638 94.617 

## 31 power 0.279427 0.0834726 0.115823 0.44303 

## 32 33 34 35
Table of Data and Estimated Values of Interest 

## 36 37
Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

## 38

------ --- -------- -------- ----------- ----------- ---------- 

## 39 40
0 3 101 101 15.6 11.1 -0.0666 

## 41
14 3 194 214 36.4 41.5 -0.847 

## 42
47 3 304 260 17.3 58.3 1.31 

## 43
320 3 452 372 48.5 110 1.26 

## 44
1024 3 296 476 149 170 -1.83 

## 45 46 47 48 Model Descriptions for likelihoods calculated 

## 49 50 51 Model A1: Yij = Mu(i) + e(ij) 

## 52 Var{e(ij)} = Sigma^2 

## 53 54 Model A2: Yij = Mu(i) + e(ij) 

## 55 Var{e(ij)} = Sigma(i)^2 

## 56 57 Model A3: Yij = Mu(i) + e(ij) 

## 58 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i))) 

## 59 Model A3 uses any fixed variance parameters that 

## 60 were specified by the user 

## 61 62 Model R: Yi = Mu + e(i) 

## 63 Var{e(i)} = Sigma^2 

## 64 65 66
Likelihoods of Interest 

## 67 68 Model Log(likelihood) # Param's AIC 

## 69
A1 -68.748326 6 149.496653 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-239 A2 -58.691256 10 137.382511 

## 1
A3 -64.899072 7 143.798144 

## 2
fitted -67.596085 5 145.192170 

## 3
R -80.722651 2 165.445302 

## 4 5 6 Explanation of Tests 

## 7 8 Test 1: Do responses and/or variances differ among Dose levels? 

## 9 (A2 vs. R) 

## 10 Test 2: Are Variances Homogeneous? (A1 vs A2) 

## 11 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 12 Test 4: Does the Model for the Mean Fit? (A3 vs. fitted) 

## 13 (Note: When rho=0 the results of Test 3 and Test 2 will be the same.) 

## 14 15
Tests of Interest 

## 16 17 Test -2*log(Likelihood Ratio) Test df p-value 

## 18 19
Test 1 44.0628 8 <.0001 

## 20
Test 2 20.1141 4 0.0004741 

## 21
Test 3 12.4156 3 0.006087 

## 22
Test 4 5.39403 2 0.06741 

## 23 24 The p-value for Test 1 is less than .05. There appears to be a 

## 25 difference between response and/or variances among the dose levels 

## 26 It seems appropriate to model the data 

## 27 28 The p-value for Test 2 is less than .1. A non-homogeneous variance 

## 29 model appears to be appropriate 

## 30 31 The p-value for Test 3 is less than .1. You may want to consider a 

## 32
different variance model 

## 33 34 The p-value for Test 4 is less than .1. You may want to try a different 

## 35
model 

## 36 37 38 Benchmark Dose Computation 

## 39 40 Specified effect = 1 

## 41 42 Risk Type = Estimated standard deviations from the control mean 

## 43 44
Confidence level = 0.95 

## 45 46
BMD = 0.00343319 

## 47 48 49
BMDL = 0.00343312 

## 50 51

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-240 H.3.11. Vanden Heuvel et al. (1994): Hepatic CYP1A1 mRNA Expression 1
H.3.11.1. Summary Table of BMDS Modeling Results 2

Model Degrees of Freedom Variance p -Value a 

### χ 2 Test Statistic 

### χ 2 p Value b AIC BMD(ng/kgday) BMDL(ng/kgday) Model Notes

exponential (M2) 5 <0.0001 568.80 <0.0001 1164.38 4.7E+03 1.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M3) 5 <0.0001 568.80 <0.0001 1164.38 4.7E+03 1.7E+03 nonconstant variance, power restricted ≥ 1
exponential (M4) 4 <0.0001 63.39 <0.0001 661.01 4.5E-01 2.6E-01 nonconstant variance, power restricted ≥ 1
exponential (M5) c 3 <0.0001 35.71 <0.0001 635.33 1.5E+01 1.0E+01 nonconstant variance, power restricted ≥ 1

Hill 3 <.0001 33.98 <.0001 633.59 1.9E+01 error nonconstant variance, n restricted >1

linear 5 <.0001 71.94 <.0001 667.55 5.0E-01 3.1E-01 nonconstant variance

polynomial 5 <.0001 137.66 <.0001 733.28 5.4E+03 1.7E+01 nonconstant variance

power 4 <.0001 71.83 <.0001 669.44 5.6E-01 3.2E-01 nonconstant variance, power restricted ≥ 1
exponential (M2) 5 <0.0001 27.93 <0.0001 1178.88 5.9E+03 5.1E+03 constant variance, power restricted ≥ 1
exponential (M3) 5 <0.0001 27.93 <0.0001 1178.88 5.9E+03 5.1E+03 constant variance, power restricted ≥ 1
exponential (M4) 4 <0.0001 0.34 0.99 1153.28 4.0E+02 2.8E+02 constant variance, power restricted ≥ 1
exponential (M5) 3 <0.0001 0.00 1.00 1154.95 5.7E+02 2.9E+02 constant variance, power restricted ≥ 1

Hill 3 <.0001 0.00 1.00 1154.95 5.3E+02 2.1E+02 constant variance, n restricted >1

linear 5 <.0001 21.45 0.00 1172.40 2.8E+03 2.2E+03 constant variance

polynomial 5 <.0001 22.53 0.00 1173.48 3.1E+03 2.1E+03 constant variance

power 5 <.0001 21.45 0.00 1172.40 2.8E+03 2.2E+03 constant variance, power restricted ≥ 1, bound hit

a Values <0.1 means nonconstant variance model should be selected; Values ≥ 0.1 means a constant variance model should be selected

b Values <0.1 fail to meet BMDS goodness-of-fit criteria

c Best-fitting model as assessed by lowest-AIC criterion, bolded, presen ted in this appendix 

## 3

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-241 H.3.11.2. Figure for Selected Model: Exponen tial (M5), Nonconstant Variance, Power 1 Restricted ≥ 1 2

0 10000 20000 30000 40000 50000 60000 70000

0 2000 4000 6000 8000 10000Mean Response

dose Exponential_beta Model 5 with 0.95 Confidence Level

16:52 11/20 2009 BMD BMDL Exponential



## 3 4 5 H.3.11.3. Output File for Selected Model: Expo nential (M5), Nonconstant Varian ce, Power 6 Restricted ≥ 1 7 8 9

==================================================================== 

## 10 Exponential Model. (Version: 1.5; Date: 4/23/2009) 

## 11 Input Data File: C:\USEPA\BMDS21\Nov20\Exp_BMR1_hepatic_CYP1A1_mRNA_expression.(d) 

## 12 Gnuplot Plotting File: 

## 13
Fri Nov 20 16:52:21 2009 

## 14

==================================================================== 

## 15 16 [insert study notes] 

## 17

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

## 18 19 The form of the response function by Model: 

## 20 Model 2: Y[dose] = a * exp{sign * b * dose} 

## 21 Model 3: Y[dose] = a * exp{sign * (b * dose)^d} 

## 22 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}] 

## 23 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}] 

## 24 25 Note: Y[dose] is the median response for exposure = dose; 

## 26 sign = +1 for increasing trend in data; 

## 27 sign = -1 for decreasing trend. 

## 28 29
Model 2 is nested within Models 3 and 4. 

## 30
Model 3 is nested within Model 5. 

## 31
Model 4 is nested within Model 5. 

## 32 33 34 Dependent variable = Mean 

## 35 Independent variable = Dose 

## 36 Data are assumed to be distributed: normally 

## 37

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-242 Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

## 1 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho) 

## 2 3 Total number of dose groups = 7 

## 4 Total number of records with missing values = 0 

## 5 Maximum number of iterations = 250 

## 6 Relative Function Convergence has been set to: 1e-008 

## 7 Parameter Convergence has been set to: 1e-008 

## 8 9 MLE solution provided: Exact 

## 10 11 12
Initial Parameter Values 

## 13 14
Variable Model 5 

## 15

-------- -------- 

## 16 lnalpha -0.89532 

## 17
rho 2.01401 

## 18
a 5.13 

## 19
b 0.000307638 

## 20
c 7511.7 

## 21
d 1 

## 22 23 24 25
Parameter Estimates 

## 26 27
Variable Model 5 

## 28

-------- ------- 

## 29 lnalpha 0.176234 

## 30
rho 1.90467 

## 31
a 9.74751 

## 32
b 0.00106447 

## 33
c 3247.52 

## 34
d 1.96414 

## 35 36 37 Table of Stats From Input Data 

## 38 39
Dose N Obs Mean Obs Std Dev 

## 40

----- --- ---------- ------------- 

## 41
0 13 5.4 3.606 

## 42
0.1 5 7.2 5.59 

## 43
1 12 14.8 14.9 

## 44
10 7 12.8 4.498 

## 45
100 7 536 320.1 

## 46
1000 11 1.8e+004 1.522e+004 

## 47
1e+004 5 3.67e+004 2.214e+004 

## 48 49 50
Estimated Values of Interest 

## 51 52
Dose Est Mean Est Std Scaled Residual 

## 53

------ ---------- --------- ---------------- 

## 54
0 9.748 9.551 -1.641 

## 55
0.1 9.748 9.551 -0.5965 

## 56
1 9.793 9.593 1.808 

## 57
10 13.97 13.45 -0.2296 

## 58
100 395.9 325.2 1.14 

## 59
1000 2.144e+004 1.456e+004 -0.7835 

## 60
1e+004 3.166e+004 2.11e+004 0.5347 

## 61 62 63 64
Other models for which likelihoods are calculated: 

## 65 66 Model A1: Yij = Mu(i) + e(ij) 

## 67 Var{e(ij)} = Sigma^2 

## 68 69 Model A2: Yij = Mu(i) + e(ij) 

## 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-243 Var{e(ij)} = Sigma(i)^2 

## 1 2 Model A3: Yij = Mu(i) + e(ij) 

## 3 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho) 

## 4 5 Model R: Yij = Mu + e(i) 

## 6 Var{e(ij)} = Sigma^2 

## 7 8 9
Likelihoods of Interest 

## 10 11 Model Log(likelihood) DF AIC 

## 12

------- ----------------- ---- ------------ 

## 13
A1 -572.4744 8 1160.949 

## 14
A2 -290.7965 14 609.5929 

## 15
A3 -293.806 9 605.6119 

## 16
R -603.6646 2 1211.329 

## 17
5 -311.6633 6 635.3266 

## 18 19 20 Additive constant for all log-likelihoods = -55.14. This constant added to the 

## 21 above values gives the log-likelihood including the term that does not 

## 22 depend on the model parameters. 

## 23 24 25 Explanation of Tests 

## 26 27 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

## 28 Test 2: Are Variances Homogeneous? (A2 vs. A1) 

## 29 Test 3: Are variances adequately modeled? (A2 vs. A3) 

## 30 31 Test 7a: Does Model 5 fit the data? (A3 vs 5) 

## 32 33 34
Tests of Interest 

## 35 36 Test -2*log(Likelihood Ratio) D. F. p-value 

## 37

-------- ------------------------ ------ -------------- 

## 38
Test 1 625.7 12 < 0.0001 

## 39
Test 2 563.4 6 < 0.0001 

## 40
Test 3 6.019 5 0.3044 

## 41
Test 7a 35.71 3 < 0.0001 

## 42 43 44 The p-value for Test 1 is less than .05. There appears to be a 

## 45 difference between response and/or variances among the dose 

## 46 levels, it seems appropriate to model the data. 

## 47 48 The p-value for Test 2 is less than .1. A non-homogeneous 

## 49 variance model appears to be appropriate. 

## 50 51 The p-value for Test 3 is greater than .1. The modeled 

## 52 variance appears to be appropriate here. 

## 53 54 The p-value for Test 7a is less than .1. Model 5 may not adequately 

## 55 describe the data; you may want to consider another model. 

## 56 57 58 Benchmark Dose Computations: 

## 59 60 Specified Effect = 1.000000 

## 61 62 Risk Type = Estimated standard deviations from control 

## 63 64
Confidence Level = 0.950000 

## 65 66
BMD = 15.1574 

## 67 68
BMDL = 10.4625 

## 69 70

## This document is a draft for review purpos es only and does not constitute Agency policy. 1/15/10 DRAFT

— DO NOT CITE OR QUOTE H-244 H.4. REFERENCES 1 Hassoun, EA; Li, F; Abushaban, A; et al. (2000) The relative abilities of TCDD and its congeners to induce 

## 2 oxidative stress in the hepatic and brain tissues of rats after subchronic exposure. Toxicology 145:103

− 113. 

## 3
NTP (National Toxicology Program). (2006) Studies of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in female 

## 4 Harlan Sprague-Dawley rats (gavage studies) Tech. Rep. Ser. No. 521. U.S. Department of Health and Human 

## 5 Services, Public Health Service, Research Triangle Park, NC. 

## 6
Van Birgelen et al. 1995a and 1995b – I assume below is one of them? 

## 7
Van Birgelen, AP; Van der Kolk, J; Fase, KM; et al. (1995) Subchronic dose-response study of 2,3,7,8- 

## 8 tetrachlorodibenzo-p-dioxin in female Sprague-Dawley rats. Toxicol Appl Pharmacol 132:1-13. 

## 9
van den Heuvel, JP; Clark, GC; Kohn, MC; et al. (1994) Dioxin-responsive genes: examination of dose-response 

## 10 relationships using quantitative reverse transcriptase-polymerase chai n reaction. Cancer Res 54:62–68. 

## 11