EPA/635/R-09/005-F

 www.epa.gov/iris

TOXICOLOGICAL REVIEW 

 

OF

1,4-Dioxane

(CAS No. 123-91-1) 

 

In Support of Summary Information on the 

Integrated Risk Information System (IRIS)

August 2010

 U.S. Environmental Protection Agency 

Washington, DC
DISCLAIMER 

This document has been reviewed in accordance with U.S. Environmental Protection 

Agency policy and approved for publication. Mention of trade names or commercial products 

does not constitute endorsement or recommendation for use. 

 ii 
CONTENTS – TOXICOLOGICAL REVIEW OF 1,4-DIOXANE 

(CAS No. 123-91-1) 

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

LIST OF FIGURES ....................................................................................................................... xi 

LIST OF ABBREVIATIONS AND ACRONYMS .................................................................... xiv 

1. INTRODUCTION ...................................................................................................................... 1 

2. CHEMICAL AND PHYSICAL INFORMATION .................................................................... 3 

3. TOXICOKINETICS ................................................................................................................... 6 

3.1. ABSORPTION ............................................................................................................... 6 

3.2. DISTRIBUTION............................................................................................................. 7 

3.3. METABOLISM.............................................................................................................. 8 

3.4. ELIMINATION............................................................................................................ 12 

3.5. PHYSIOLOGICALLY BASED pharmacokinetic MODELS...................................... 12 

3.5.1. Available Pharmacokinetic Data........................................................................... 14 

3.5.2. Published PBPK Models for 1,4-Dioxane ............................................................ 15 

3.5.2.1. Leung and Paustenbach........................................................................................ 15 

3.5.2.2. Reitz et al. ............................................................................................................ 16 

3.5.2.3. Fisher et al............................................................................................................ 18 

3.5.3. Implementation of Published PBPK Models for 1,4-Dioxane.............................. 18 

3.6. RAT NASAL EXPOSURE VIA DRINKING WATER .............................................. 21 

4. HAZARD IDENTIFICATION................................................................................................. 23 

4.1. STUDIES IN HUMANS – EPIDEMIOLOGY, CASE REPORTS, CLINICAL 

CONTROLS ............................................................................................................................. 23 

4.1.1. Thiess et al. ........................................................................................................... 25 

4.1.2. Buffler et al. .......................................................................................................... 26 

4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS - ORAL AND INHALATION............................................................................... 27 

4.2.1. Oral Toxicity......................................................................................................... 27 

4.2.1.1. Subchronic Oral Toxicity..................................................................................... 27 

4.2.1.1.1. Stoner et al. ................................................................................................... 27 

4.2.1.1.2. Stott et al. ...................................................................................................... 28 

4.2.1.1.3. Kano et al. ..................................................................................................... 28 

4.2.1.1.4. Yamamoto et al............................................................................................. 33 

4.2.1.2. Chronic Oral Toxicity and Carcinogenicity......................................................... 34 

4.2.1.2.1. Argus et al..................................................................................................... 34 

4.2.1.2.2. Argus et al.; Hoch-Ligeti et al....................................................................... 35 

4.2.1.2.3. Hoch-Ligeti and Argus. ................................................................................ 36 

4.2.1.2.4. Kociba et al. .................................................................................................. 37 

4.2.1.2.5. National Cancer Institute (NCI).................................................................... 39 

4.2.1.2.6. Kano et al.; Japan Bioassay Research Center; Yamazaki et al..................... 43 

4.2.2. Inhalation Toxicity................................................................................................ 55 

 iii 
4.2.2.1. Subchronic Inhalation Toxicity............................................................................ 55 

4.2.2.1.1. Fairley et al. .................................................................................................. 55 

4.2.2.2. Chronic Inhalation Toxicity and Carcinogenicity................................................ 55 

4.2.2.2.1. Torkelson et al............................................................................................... 55 

4.2.3. Initiation/Promotion Studies................................................................................. 56 

4.2.3.1. Bull et al............................................................................................................... 56 

4.2.3.2. King et al.............................................................................................................. 57 

4.2.3.3. Lundberg et al. ..................................................................................................... 58 

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND INHALATION 58 

4.3.1. Giavini et al........................................................................................................... 58 

4.4. OTHER DURATION OR ENDPOINT-SPECIFIC STUDIES.................................... 59 

4.4.1. Acute and Short-term Toxicity ............................................................................. 59 

4.4.1.1. Oral Toxicity........................................................................................................ 59 

4.4.1.2. Inhalation Toxicity............................................................................................... 59 

4.4.2. Neurotoxicity ........................................................................................................ 62 

4.4.2.1. Frantik et al. ......................................................................................................... 62 

4.4.2.2. Goldberg et al....................................................................................................... 63 

4.4.2.3. Kanada et al.......................................................................................................... 64 

4.4.2.4. Knoefel................................................................................................................. 64 

4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF 

ACTION ................................................................................................................................... 64 

4.5.1. Genotoxicity.......................................................................................................... 64 

4.5.2. Mechanistic Studies.............................................................................................. 73 

4.5.2.1. Free Radical Generation ...................................................................................... 73 

4.5.2.2. Induction of Metabolism...................................................................................... 73 

4.5.2.3. Mechanisms of Tumor Induction......................................................................... 74 

4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS................................................. 76 

4.6.1. Oral ....................................................................................................................... 76 

4.6.2. Inhalation .............................................................................................................. 80 

4.6.3. Mode of Action Information................................................................................. 80 

4.7. EVALUATION OF CARCINOGENICITY................................................................. 81 

4.7.1. Summary of Overall Weight of Evidence............................................................. 81 

4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence............................ 83 

4.7.3. Mode of Action Information................................................................................. 84 

4.7.3.1. Identification of Key Events for Carcinogenicity................................................ 84 

4.7.3.1.1. Liver.............................................................................................................. 84 

4.7.3.1.2. Nasal cavity................................................................................................... 86 

4.7.3.2. Strength, Consistency, Specificity of Association............................................... 87 

4.7.3.2.1. Liver.............................................................................................................. 87 

4.7.3.2.2. Nasal cavity................................................................................................... 88 

4.7.3.3. Dose-Response Relationship ............................................................................... 88 

4.7.3.3.1. Liver.............................................................................................................. 88 

4.7.3.3.2. Nasal cavity................................................................................................... 90 

4.7.3.4. Temporal Relationship......................................................................................... 90 

4.7.3.4.1. Liver.............................................................................................................. 90 

4.7.3.4.2. Nasal cavity................................................................................................... 91 

4.7.3.5. Biological Plausibility and Coherence................................................................. 91 

4.7.3.5.1. Liver.............................................................................................................. 91 

4.7.3.5.2. Nasal cavity................................................................................................... 91 

 iv 
4.7.3.6. Other Possible Modes of Action.......................................................................... 92 

4.7.3.7. Conclusions About the Hypothesized Mode of Action ....................................... 92 

4.7.3.7.1. Liver.............................................................................................................. 92 

4.7.3.7.2. Nasal cavity................................................................................................... 93 

4.7.3.8. Relevance of the Mode of Action to Humans...................................................... 93 

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES............................................. 93 

5. DOSE-RESPONSE ASSESSMENTS...................................................................................... 95 

5.1. ORAL REFERENCE DOSE (RfD).............................................................................. 95 

5.1.1. Choice of Principal Studies and Critical Effect with Rationale and Justification 95 

5.1.2. Methods of Analysis—Including Models (PBPK, BMD, etc.) ............................ 96 

5.1.3. RfD Derivation - Including Application of Uncertainty Factors (UFs)................ 99 

5.1.4. RfD Comparison Information............................................................................. 100 

5.1.5. Previous RfD Assessment................................................................................... 104 

5.2. INHALATION REFERENCE CONCENTRATION (RfC) ...................................... 104 

5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE (RfD) ............................. 105 

5.4. CANCER ASSESSMENT.......................................................................................... 107 

5.4.1. Choice of Study/Data – with Rationale and Justification ................................... 107 

5.4.2. Dose-Response Data ........................................................................................... 109 

5.4.3. Dose Adjustments and Extrapolation Method(s)................................................ 110 

5.4.3.1. Dose Adjustments.............................................................................................. 110 

5.4.3.2. Extrapolation Method(s).................................................................................... 111 

5.4.4. Oral Slope Factor and Inhalation Unit Risk........................................................ 112 

5.4.5. Previous Cancer Assessment .............................................................................. 114 

5.5. UNCERTAINTIES IN CANCER RISK VALUES.................................................... 115 

5.5.1. Sources of Uncertainty........................................................................................ 115 

5.5.1.1. Choice of Low-Dose Extrapolation Approach .................................................. 115 

5.5.1.2. Dose Metric........................................................................................................ 116 

5.5.1.3. Cross-Species Scaling........................................................................................ 117 

5.5.1.4. Statistical Uncertainty at the POD..................................................................... 117 

5.5.1.5. Bioassay Selection ............................................................................................. 117 

5.5.1.6. Choice of Species/Gender.................................................................................. 117 

5.5.1.7. Relevance to Humans ........................................................................................ 118 

5.5.1.8. Human Population Variability ........................................................................... 118 

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE 

RESPONSE................................................................................................................................. 120 

6.1. HUMAN HAZARD POTENTIAL............................................................................. 120 

6.2. DOSE RESPONSE..................................................................................................... 121 

6.2.1. Noncancer/Oral................................................................................................... 121 

6.2.2. Noncancer/Inhalation.......................................................................................... 122 

6.2.3. Cancer/Oral......................................................................................................... 122 

6.2.3.1. Choice of Low-Dose Extrapolation Approach .................................................. 123 

6.2.3.2. Dose Metric........................................................................................................ 124 

6.2.3.3. Cross-Species Scaling........................................................................................ 124 

6.2.3.4. Statistical Uncertainty at the POD..................................................................... 124 

6.2.3.5. Bioassay Selection ............................................................................................. 124 

6.2.3.6. Choice of Species/Gender.................................................................................. 124 

6.2.3.7. Relevance to Humans ........................................................................................ 125 

 v 
6.2.3.8. Human Population Variability ........................................................................... 125 

6.2.4. Cancer/Inhalation................................................................................................ 125 

7. REFERENCES ....................................................................................................................... 126 

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS 

AND DISPOSITION .................................................................................................................. A-1 

APPENDIX B. EVALUATION OF EXISTING PBPK MODELS FOR 1,4-DIOXANE......... B-1 

APPENDIX C. DETAILS OF BMD ANALYSIS FOR ORAL RfD FOR 1,4-DIOXANE ...... C-1 

APPENDIX D. DETAILS OF BMD ANALYSIS FOR ORAL CSF FOR 1,4-DIOXANE...... D-1 

APPENDIX E. COMPARISON OF SEVERAL DATA REPORTS FOR THE JBRC 2-YEAR 

1,4-DIOXANE DRINKING WATER STUDY...........................................................................E-1 

 vi 
LIST OF TABLES 

Table 2-1. Physical properties and chemical identity of 1,4-dioxane ........................................... 4 

Table 4-1. Incidence of histopathological lesions in F344/DuCrj rats exposed to 1,4-dioxane in 

drinking water for 13 weeks...................................................................................... 31 

Table 4-2. Incidence of histopathological lesions in Crj:BDF1 mice exposed to 1,4-dioxane in 

drinking water for 13 weeks...................................................................................... 33 

Table 4-3. Number of incipient liver tumors and hepatomas in male Sprague- Dawley rats 

exposed to 1,4-dioxane in drinking water for 13 months.......................................... 36 

Table 4-4. Incidence of liver and nasal tumors in male and female Sherman rats (combined) 

treated with 1,4-dioxane in the drinking water for 2 years........................................ 39 

Table 4-5. Incidence of nonneoplastic lesions in Osborne-Mendel rats exposed to 1,4-dioxane in 

drinking water............................................................................................................ 40 

Table 4-6. Incidence of nasal cavity squamous cell carcinoma and liver hepatocellular adenoma 

in Osborne-Mendel rats exposed to 1,4-dioxane in drinking water........................... 41 

Table 4-7. Incidence of hepatocellular adenoma or carcinoma in B6C3F1 mice exposed to 

1,4-dioxane in drinking water.................................................................................... 43 

Table 4-8. Incidence of histopathological lesions in male F344/DuCrj rats exposed to 

1,4-dioxane in drinking water for 2 years.................................................................. 47 

Table 4-9. Incidence of histopathological lesions in female F344/DuCrj rats exposed to 

1,4-dioxane in drinking water for 2 years.................................................................. 48 

Table 4-10. Incidence of nasal cavity, peritoneum, and mammary gland tumors in F344/DuCrj 

rats exposed to 1,4-dioxane in drinking water for 2 years......................................... 50 

Table 4-11. Incidence of liver tumors in F344/DuCrj rats exposed to 1,4-dioxane in drinking 

water for 2 years ........................................................................................................ 50 

Table 4-12. Incidence of histopathological lesions in male Crj:BDF1 mice exposed to 

1,4-dioxane in drinking water for 2 years.................................................................. 52 

Table 4-13. Incidence of histopathological lesions in female Crj:BDF1 mice exposed to 

1,4-dioxane in drinking water for 2 years.................................................................. 53 

Table 4-14. Incidence of tumors in Crj:BDF1 mice exposed to 1,4-dioxane in drinking water for 

2 years........................................................................................................................ 54 

Table 4-15. Acute and short-term toxicity studies of 1,4-dioxane................................................ 60 

Table 4-16. Genotoxicity studies of 1,4-dioxane; in vitro ............................................................ 67 

Table 4-17. Genotoxicity studies of 1,4-dioxane; mammalian in vivo......................................... 71 

Table 4-18. Oral toxicity studies (noncancer effects) for 1,4-dioxane ......................................... 77 

Table 4-19. Temporal sequence and dose-response relationship for possible key events and liver 

tumors in rats and mice.............................................................................................. 89 

Table 5-1. Incidence of cortical tubule degeneration in Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water for 2 years.................................................................. 98 

Table 5-2. BMD and BMDL values derived from BMD modeling of cortical tubule 

degeneration in male and female Osborne-Mendel rats exposed to 1,4-dioxane in 

drinking water for 2 years.......................................................................................... 98 

Table 5-3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to 1,4-dioxane in drinking 

water for 2 yearsa

....................................................................................................... 98 

Table 5-4. BMD and BMDL values derived from BMD modeling of liver hyperplasia in male 

and female F344/DuCrj rats exposed to 1,4-dioxane in drinking water for 2 years.. 99 

 vii 
Table 5-5. Incidence of liver, nasal cavity, peritoneal, and mammary gland tumors in rats and 

mice exposed to 1,4-dioxane in drinking water for 2 years (based on survival to 

12 months) ............................................................................................................... 108 

Table 5-6. Incidence of hepatocellular adenoma or carcinoma in rats and mice exposed to 

1,4-dioxane in drinking water for 2 years................................................................ 110 

Table 5-7. Calculated HEDs for the tumor incidence data used for dose-response modeling .. 111 

Table 5-8. BMD HED and BMDLHED values from models fit to tumor incidence data for rats and 

mice exposed to 1,4-dioxane in drinking water for 2 years and corresponding oral 

CSFs......................................................................................................................... 113 

Table 5-9. Summary of uncertainty in the 1,4-dioxane cancer risk estimation ......................... 119 

Table B-1. Human PBPK model parameter values for 1,4-dioxane........................................ B-11 

Table B-2. PBPK metabolic and elimination parameter values resulting from re-calibration of 

the human model using alternative values for physiological flow ratesa and tissue:air 

partition coefficients.............................................................................................. B-13 

Table B-3. PBPK metabolic and elimination parameter values resulting from recalibration of the 

human model using biologically plausible values for physiological flow ratesa

 and 

selected upper and lower boundary values for tissue:air partition coefficients..... B-20 

Table C-1. Incidence of cortical tubule degeneration in Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water for 2 years................................................................ C-1 

Table C-2. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

incidence data for cortical tubule degeneration in male and female Osborne-Mendel 

rats (NCI, 1978, 062935) exposed to 1,4-dioxane in drinking water ...................... C-2 

Table C-3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to 1,4-dioxane in drinking 

watera ....................................................................................................................... C-7 

Table C-4. Benchmark dose modeling results based on the incidence of liver hyperplasias in 

male and female F344 rats exposed to 1,4-dioxane in drinking water for 2 years.. C-8 

Table D-1. Recommended models for rodents exposed to 1,4-dioxane in drinking water (Kano et 

al., 2009, 594539).................................................................................................... D-4 

Table D-2. Data for hepatic adenomas and carcinomas in female F344 rats (Kano et al., 2009, 

594539).................................................................................................................... D-5 

Table D-3. BMDS dose-response modeling results for the combined incidence of hepatic 

adenomas and carcinomas in female F344 rats (Kano et al., 2009, 594539) .......... D-5 

Table D-4. Data for hepatic adenomas and carcinomas in male F344 rats (Kano et al., 2009, 

594539).................................................................................................................... D-8 

Table D-5. BMDS dose-response modeling results for the combined incidence of adenomas and 

carcinomas in livers of male F344 rats (Kano et al., 2009, 594539)....................... D-9 

Table D-6. Data for significant tumors at other sites in male and female F344 rats (Kano et al., 

2009, 594539)........................................................................................................ D-14 

Table D-7. BMDS dose-response modeling results for the incidence of nasal cavity tumors in 

female F344 ratsa

 (Kano et al., 2009, 594539)...................................................... D-15 

Table D-8. BMDS dose-response modeling results for the incidence of nasal cavity tumors in 

male F344 ratsa

 (Kano et al., 2009, 594539) ......................................................... D-18 

Table D-9. BMDS dose-response modeling results for the incidence of mammary gland 

adenomas in female F344 rats (Kano et al., 2009, 594539) .................................. D-21 

Table D-10. BMDS dose-response modeling results for the incidence of peritoneal 

mesotheliomas in male F344 rats (Kano et al., 2009, 594539) ............................. D-26 

Table D-11. Data for hepatic adenomas and carcinomas in female BDF1 mice (Kano et al., 2009, 

594539).................................................................................................................. D-31 

 viii 
Table D-12. BMDS dose-response modeling results for the combined incidence of hepatic 

adenomas and carcinomas in female BDF1 mice (Kano et al., 2009, 594539)..... D-32 

Table D-13. BMDS LogLogistic dose-response modeling results using BMRs of 10, 30, and 50% 

for the combined incidence of hepatic adenomas and carcinomas in female BDF1 

mice (Kano et al., 2009, 594539). ......................................................................... D-32 

Table D-14. Data for hepatic adenomas and carcinomas in male BDF1 mice (Kano et al., 2009, 

594539).................................................................................................................. D-41 

Table D-15. BMDS dose-response modeling results for the combined incidence of hepatic 

adenomas and carcinomas in male BDF1 mice (Kano et al., 2009, 594539)........ D-42 

Table D-16. Summary of BMDS dose-response modeling estimates associated with liver and 

nasal tumor incidence data resulting from chronic oral exposure to 1,4-dioxane in 

rats and mice.......................................................................................................... D-47 

Table D-17. Incidence of hepatocellular carcinoma and nasal squamous cell carcinoma in male 

and female Sherman rats (combined) (Kociba et al., 1974, 062929) treated with 

1,4-dioxane in the drinking water for 2 years........................................................ D-48 

Table D-18. BMDS dose-response modeling results for the incidence of hepatocellular 

carcinoma in male and female Sherman rats (combined) (Kociba et al., 1974, 

062929) exposed to 1,4-dioxane in the drinking water for 2 years....................... D-49 

Table D-19. BMDS dose-response modeling results for the incidence of nasal squamous cell 

carcinoma in male and female Sherman rats (combined) (Kociba et al., 1974, 

062929) exposed to 1,4-dioxane in the drinking water for 2 years....................... D-54 

Table D-20. Incidence of nasal cavity squamous cell carcinoma and hepatocellular adenoma in 

Osborne-Mendel rats (NCI, 1978, 062935) exposed to 1,4-dioxane in the drinking 

water ...................................................................................................................... D-57 

Table D-21. BMDS dose-response modeling results for the incidence of hepatocellular adenoma 

in female Osborne-Mendel rats (NCI, 1978, 062935) exposed to 1,4-dioxane in the 

drinking water for 2 years...................................................................................... D-58 

Table D-22. BMDS dose-response modeling results for the incidence of nasal cavity squamous 

cell carcinoma in female Osborne-Mendel rats (NCI, 1978, 062935) exposed to 

1,4-dioxane in the drinking water for 2 years........................................................ D-63 

Table D-23. BMDS dose-response modeling results for the incidence of nasal cavity squamous 

cell carcinoma in male Osborne-Mendel rats (NCI, 1978, 062935) exposed to 

1,4-dioxane in the drinking water for 2 years........................................................ D-68 

Table D-24. Incidence of hepatocellular adenoma or carcinoma in male and female B6C3F1 mice 

(NCI, 1978, 062935) exposed to 1,4-dioxane in drinking water........................... D-73 

Table D-25. BMDS dose-response modeling results for the combined incidence of hepatocellular 

adenoma or carcinoma in female B6C3F1 mice (NCI, 1978, 062935) exposed to 

1,4-dioxane in the drinking water for 2 years........................................................ D-74 

Table D-26. BMDS dose-response modeling results for the combined incidence of hepatocellular 

adenoma or carcinoma in male B6C3F1 mice (NCI, 1978, 062935) exposed to 

1,4-dioxane in drinking water................................................................................ D-77 

Table E-1. Nonneoplastic lesions: Comparison of histological findings reported for the 2-year 

JBRC drinking water study in male F344 rats..........................................................E-2 

Table E-2. Nonneoplastic lesions: Comparison of histological findings reported for the 2-year 

JBRC drinking water study in female F344 rats.......................................................E-3 

Table E-3. Neoplastic lesions: Comparison of histological findings reported for the 2-year JBRC 

drinking water study in male F344 rats ....................................................................E-5 

Table E-4. Neoplastic lesions: Comparison of histological findings reported for the 2-year JBRC 

drinking water study in female F344 rats.................................................................E-6 

 ix 
Table E-5. Nonneoplastic lesions: Comparison of histological findings reported for the 2-year 

JBRC drinking water study in male Crj:BDF1 mice................................................E-8 

Table E-6. Nonneoplastic lesions: Comparison of histological findings reported for the 2-year 

JBRC drinking water study in female Crj:BDF1 mice...........................................E-10 

Table E-7. Neoplastic lesions: Comparison of histological findings reported for the 2-year JBRC 

drinking water study in male Crj:BDF1 mice.........................................................E-11 

Table E-8. Neoplastic lesions: Comparison of histological findings reported for the 2-year JBRC 

drinking water study in female Crj:BDF1 mice .....................................................E-12 

 x 
 LIST OF FIGURES 

Figure 2-1. 1,4-Dioxane chemical structure................................................................................... 3 

Figure 3-1. Suggested metabolic pathways of 1,4-dioxane in the rat. ........................................... 9 

Figure 3-2. Plasma 1,4-dioxane levels in rats following i.v. doses of 3-5,600 mg/kg. ................ 11 

Figure 3-3. General PBPK model structure consisting of blood-flow limited tissue compartments 

connected via arterial and venous blood flows.......................................................... 13 

Figure 4-1. A schematic representation of the possible key events in the delivery of 1,4-dioxane 

to the liver and the hypothesized MOA(s) for liver carcinogenicity......................... 86 

Figure 4-2. A schematic representation of the possible key events in the delivery of 1,4-dioxane 

to the nasal cavity and the hypothesized MOA(s) for nasal cavity carcinogenicity.. 87 

Figure 5-1. Potential points of departure (POD) for liver toxicity endpoints with corresponding 

applied uncertainty factors and derived RfDs following oral exposure to 1,4-dioxane.

................................................................................................................................. 101 

Figure 5-2. Potential points of departure (POD) for kidney toxicity endpoints with 

corresponding applied uncertainty factors and derived RfDs following oral exposure 

to 1,4-dioxane. ......................................................................................................... 102 

Figure 5-3. Potential points of departure (POD) for nasal inflammation with corresponding 

applied uncertainty factors and derived sample RfDs following oral exposure to 

1,4-dioxane. ............................................................................................................. 103 

Figure 5-4. Potential points of departure (POD) for organ specific toxicity endpoints with 

corresponding applied uncertainty factors and derived sample RfDs following oral 

exposure to 1,4-dioxane........................................................................................... 104 

Figure B-1. Schematic representation of empirical model for 1,4-dioxane in rats.................... B-3 

Figure B-2. Schematic representation of empirical model for 1,4-dioxane in humans. ............ B-4 

Figure B-3. Output of 1,4-dioxane blood level data from the acslXtreme implementation (left) 

and published (right) empirical rat model simulations of i.v. administration 

experiments.............................................................................................................. B-5 

Figure B-4. Output of HEAA urine level data from acslXtreme implementation (left) and 

published (right) empirical rat model simulations of i.v. administration experiments.

................................................................................................................................. B-6 

Figure B-5. acslXtreme predictions of blood 1,4-dioxane and urine HEAA levels from the 

empirical rat model simulations of a 6-hour, 50-ppm inhalation exposure............. B-7 

Figure B-6. Output of 1,4-dioxane blood level data from the acslXtreme implementation (left) 

and published (right) empirical human model simulations of a 6-hour, 50-ppm 

inhalation exposure.................................................................................................. B-8 

Figure B-7. Observations and acslXtreme predictions of cumulative HEAA in human urine 

following a 6-hour, 50-ppm inhalation exposure. ................................................... B-9 

Figure B-8. Predicted and observed blood 1,4-dioxane concentrations (left) and urinary HEAA 

levels (right) following re-calibration of the human PBPK model with tissue:air 

partition coefficient values. ................................................................................... B-13 

Figure B-9. Predicted and observed blood 1,4-dioxane concentrations (left) and urinary HEAA 

levels (right) following re-calibration of the human PBPK model with tissue:air 

partition coefficient values. ................................................................................... B-14 

Figure B-10. Predicted and observed blood 1,4-dioxane concentrations (left) and urinary HEAA 

levels (right)........................................................................................................... B-15 

 xi 
Figure B-11. The highest seven sensitivity coefficients (and associated parameters) for blood 

1,4-dioxane concentrations (CV) at 1 (left) and 4 (right) hours of a 50-ppm 

inhalation exposure................................................................................................ B-17 

Figure B-12. Comparisons of the range of PBPK model predictions from upper and lower 

boundaries on partition coefficients with empirical model predictions and 

experimental observations for blood 1,4-dioxane concentrations (left) and urinary 

HEAA levels (right) from a 6-hour, 50-ppm inhalation exposure......................... B-19 

Figure B-13. Comparisons of the range of PBPK model predictions from upper and lower 

boundaries on partition coefficients with empirical model predictions and 

experimental observations for blood 1,4-dioxane concentrations (left) and urinary 

HEAA levels (right) from a 6-hour, 50-ppm inhalation exposure......................... B-19 

Figure B-14. Predictions of blood 1,4-dioxane concentration following calibration of a zeroorder metabolism rate constant, kLC, to the experimental data.............................. B-21 

Figure B-15. Predictions of blood 1,4-dioxane concentration following calibration of a zeroorder metabolism rate constant, kLC, to only the exposure phase of the experimental 

data......................................................................................................................... B-22 

Figure B-16. Predictions of blood 1,4-dioxane concentration following simultaneous calibration 

of a zero-order metabolism rate constant, kLC, and slowly perfused tissue:air partition 

coefficient to the experimental data....................................................................... B-23 

Figure C-1. BMD Log-probit model of cortical tubule degeneration incidence data for male rats 

exposed to 1,4-dioxane in drinking water for 2 years to support the results in 

Table C-2. ................................................................................................................ C-3 

Figure C-2. BMD Weibull model of cortical tubule degeneration incidence data for female rats 

exposed to 1,4-dioxane in drinking water for 2 years to support the results in 

Table C-2. ................................................................................................................ C-5 

Figure C-3. BMD gamma model of liver hyperplasia incidence data for F344 male rats exposed 

to 1,4-dioxane in drinking water for 2 years to support results Table C-4.............. C-9 

Figure C-4. BMD multistage (2 degree) model of liver hyperplasia incidence data for F344 male 

rats exposed to 1,4-dioxane in drinking water for 2 years to support results 

Table C-4. .............................................................................................................. C-11 

Figure C-5. BMD Weibull model of liver hyperplasia incidence data for F344 male rats exposed 

to 1,4-dioxane in drinking water for 2 years to support the results in Table C-4.. C-13 

Figure C-6. BMD quantal-linear model of liver hyperplasia incidence data for F344 male rats 

exposed to 1,4-dioxane in drinking water for 2 years to support the results in 

Table C-4. .............................................................................................................. C-15 

Figure C-7. BMD log-probit model of liver hyperplasia incidence data for F344 female rats 

exposed to 1,4-dioxane in drinking water for 2 years to support the results in 

Table C-4. .............................................................................................................. C-17 

Figure D-1. Multistage BMD model (2 degree) for the combined incidence of hepatic adenomas 

and carcinomas in female F344 rats. ....................................................................... D-6 

Figure D-2. Probit BMD model for the combined incidence of hepatic adenomas and 

carcinomas in male F344 rats. ............................................................................... D-10 

Figure D-3. Multistage BMD model (3 degree) for the combined incidence of hepatic adenomas 

and carcinomas in male F344 rats. ........................................................................ D-12 

Figure D-4. Multistage BMD model (3 degree) for nasal cavity tumors in female F344 rats. D-16 

Figure D-5. Multistage BMD model (3 degree) for nasal cavity tumors in male F344 rats.... D-19 

Figure D-6. LogLogistic BMD model for mammary gland adenomas in female F344 rats. .. D-22 

Figure D-7. Multistage BMD model (1 degree) for mammary gland adenomas in female F344 

rats.......................................................................................................................... D-24 

 xii 
Figure D-8.Probit BMD model for peritoneal mesotheliomas in male F344 rats.................... D-27 

Figure D-9.Multistage BMD (2 degree) model for peritoneal mesotheliomas in male F344 rats.

............................................................................................................................... D-29 

Figure D-10. LogLogistic BMD model for the combined incidence of hepatic adenomas and 

carcinomas in female BDF1 mice with a BMR of 10%. ....................................... D-33 

Figure D-11. LogLogistic BMD model for the combined incidence of hepatic adenomas and 

carcinomas in female BDF1 mice with a BMR of 30%. ....................................... D-35 

Figure D-12. LogLogistic BMD model for the combined incidence of hepatic adenomas and 

carcinomas in female BDF1 mice with a BMR of 50%. ....................................... D-37 

Figure D-13. Multistage BMD model (1 degree) for the combined incidence of hepatic adenomas 

and carcinomas in female BDF1 mice................................................................... D-39 

Figure D-14. LogLogistic BMD model for the combined incidence of hepatic adenomas and 

carcinomas in male BDF1 mice............................................................................. D-43 

Figure D-15. Multistage BMD model (1 degree) for the combined incidence of hepatic adenomas 

and carcinomas in male BDF1 mice...................................................................... D-45 

Figure D-16. Probit BMD model for the incidence of hepatocellular carcinoma in male and 

female Sherman rats exposed to 1,4-dioxane in drinking water............................ D-50 

Figure D-17. Multistage BMD model (1 degree) for the incidence of hepatocellular carcinoma in 

male and female Sherman rats exposed to 1,4-dioxane in drinking water. ........... D-52 

Figure D-18. Multistage BMD model (3 degree) for the incidence of nasal squamous cell 

carcinoma in male and female Sherman rats exposed to 1,4-dioxane in drinking 

water. ..................................................................................................................... D-55 

Figure D-19. LogLogistic BMD model for the incidence of hepatocellular adenoma in female 

Osborne-Mendel rats exposed to 1,4-dioxane in drinking water........................... D-59 

Figure D-20. Multistage BMD model (1 degree) for the incidence of hepatocellular adenoma in 

female Osborne-Mendel rats exposed to 1,4-dioxane in drinking water............... D-61 

Figure D-21. LogLogistic BMD model for the incidence of nasal cavity squamous cell 

carcinoma in female Osborne-Mendel rats exposed to 1,4-dioxane in drinking water.

............................................................................................................................... D-64 

Figure D-22. Multistage BMD model (1 degree) for the incidence of nasal cavity squamous cell 

carcinoma in female Osborne-Mendel rats exposed to 1,4-dioxane in drinking water.

............................................................................................................................... D-66 

Figure D-23. LogLogistic BMD model for the incidence of nasal cavity squamous cell 

carcinoma in male Osborne-Mendel rats............................................................... D-69 

Figure D-24. Multistage BMD model (1 degree) for the incidence of nasal cavity squamous cell 

carcinoma in male Osborne-Mendel rats............................................................... D-71 

Figure D-25. Multistage BMD model (2 degree) for the incidence of hepatocellular adenoma or 

carcinoma in female B6C3F1 mice ........................................................................ D-75 

Figure D-26. Gamma BMD model for the incidence of hepatocellular adenoma or carcinoma in 

male B6C3F1 mice exposed to 1,4-dioxane in drinking water. ............................. D-78 

Figure D-27. Multistage BMD model (2 degree) for the incidence of hepatocellular adenoma or 

carcinoma in male B6C3F1 mice exposed to 1,4-dioxane in drinking water. ...... D-80 

 xiii 
LIST OF ABBREVIATIONS AND ACRONYMS 

AIC Akaike’s Information Criterion 

ALP alkaline phosphatase 

ALT alanine aminotransferase 

AST aspartate aminotransferase 

ATSDR Agency for Toxic Substances and Disease Registry

BMD benchmark dose 

BMD10 benchmark dose at 10% extra risk 

BMD30 benchmark dose at 30% extra risk 

BMD50 benchmark dose at 50% extra risk 

BMDL benchmark dose, lower 95% confidence limit 

BMDL10 benchmark dose, lower 95% confidence limit at 10% extra risk 

BMDL30 benchmark dose, lower 95% confidence limit at 30% extra risk 

BMDL50 benchmark dose, lower 95% confidence limit at 50% extra risk 

BMDS Benchmark Dose Software 

BMR benchmark response 

BrdU 5-bromo-2’-deoxyuridine 

BUN blood urea nitrogen 

BW(s) body weight(s) 

CASE computer automated structure evaluator 

CASRN Chemical Abstracts Service Registry Number 

CHO Chinese hamster ovary (cells) 

CI confidence interval(s) 

CNS central nervous system 

CPK creatinine phosphokinase 

CREST antikinetochore 

CSF cancer slope factor 

CV concentration in venous blood 

CYP450 cytochrome P450 

DEN diethylnitrosamine 

FISH fluorescence in situ hybridization 

G-6-Pase glucose-6-phosphatase 

GC gas chromatography 

GGT γ-glutamyl transpeptidase 

HEAA β-hydroxyethoxy acetic acid 

HED(s) human equivalent dose(s) 

HPLC high-performance liquid chromatography 

HSDB Hazardous Substances Data Bank 

Hz Hertz 

IARC International Agency for Research on Cancer 

i.p. intraperitoneal 

i.v. intravenous 

IRIS Integrated Risk Information System 

JBRC Japan Bioassay Research Center 

ke 1st order elimination rate of 1,4-dioxane 

kINH 1st order 1,4-dioxane inhalation rate constant 

kLC 1st order, non-saturable metabolism rate constant for 1,4-dioxane in the liver

 xiv 
Km Michaelis constant for metabolism of 1,4-dioxane in the liver 

kme 1st order elimination rate of HEAA (1,4-dioxane metabolite) 

kOC soil organic carbon-water portioning coeffecient 

LAP leucine aminopeptidase 

LD50 median lethal dose 

LDH lactate dehydrogenase 

LOAEL lowest-observed-adverse-effect-level 

MCV mean corpuscular volume 

MOA mode of action 

MS mass spectrometry, multi-stage 

MTD maximum tolerated dose 

MVK Moolgavkar-Venzon-Knudsen (model) 

NCE normochromatic erythrocyte 

NCI National Cancer Institute 

ND no data, not detected 

NE not estimated

NOAEL no-observed-adverse-effect-level 

NRC National Research Council 

NTP National Toxicology Program 

OCT ornithine carbamyl transferase 

ODC ornithine decarboxylase 

OECD Organization for Economic Co-operation and Development

PB blood:air partition coefficient 

PBPK physiologically based pharmacokinetic 

PC partition coefficient 

PCB polychlorinated biphenyl 

PCE polychromatic erythrocyte 

PFA fat:air partition coefficient 

PLA liver:air partition coefficient 

POD point of departure 

ppm parts per million 

PRA rapidly perfused tissue:air partition coefficient 

PSA slowly perfused tissue:air partition coefficient 

QCC normalized cardiac output 

QPC normalized alveolar ventilation rate 

RBC red blood cell 

RfC inhalation reference concentration 

RfD oral reference dose 

SCE sister chromatid exchange 

SDH sorbitol dehydrogenase 

SMR standardized mortality ratio 

SRC Syracuse Research Corporation 

TPA 12-O-tetradecanoylphorbol-13-acetate 

TWA time-weighted average 

UF uncertainty factor 

UNEP United Nations Environment Programme 

U.S. EPA U.S. Environmental Protection Agency 

V volts 

VAS visual analogue scale 

 xv 
Vd volume of distribution 

Vmax maximal rate of metabolism 

VmaxC normalized maximal rate of metabolism of 1,4-dioxane in liver 

VOC(s) volatile organic compound(s) 

WBC white blood cell 

χ

2 Chi-squared 

 xvi 
FOREWORD 

The purpose of this Toxicological Review is to provide scientific support and rationale 

for the hazard and dose-response assessment in IRIS pertaining to chronic exposure to 

1,4-dioxane. It is not intended to be a comprehensive treatise on the chemical or toxicological 

nature of 1,4-dioxane. 

The intent of Section 6, Major Conclusions in the Characterization of Hazard and Dose 

Response, is to present the major conclusions reached in the derivation of the reference dose, 

reference concentration, and cancer assessment, where applicable, and to characterize the overall 

confidence in the quantitative and qualitative aspects of hazard and dose response by addressing 

the quality of the data and related uncertainties. The discussion is intended to convey the 

limitations of the assessment and to aid and guide the risk assessor in the ensuing steps of the 

risk assessment process. 

For other general information about this assessment or other questions relating to IRIS, 

the reader is referred to EPA’s IRIS Hotline at (202) 566-1676 (phone), (202) 566-1749 (fax), or 

hotline.iris@epa.gov (email address). 

 xvii 
AUTHORS, CONTRIBUTORS, AND REVIEWERS 

CHEMICAL MANAGERS/AUTHORS 

Eva D. McLanahan, Ph.D. 

Lieutenant, U.S. Public Health Service 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Reeder Sams II, Ph.D. 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

AUTHORS AND CONTRIBUTORS

J. Allen Davis, MSPH 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Hisham El-Masri, Ph.D. 

National Health and Environmental Effects Research Laboratory 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Jeff S. Gift, Ph.D. 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Karen Hogan 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Washington, DC 

Fernando Llados 

Environmental Science Center 

Syracuse Research Corporation 

Syracuse, NY 

Michael Lumpkin, Ph.D. 

Environmental Science Center 

Syracuse Research Corporation 

Syracuse, NY 

 xviii 
Allan Marcus, Ph.D. 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Marc Odin, Ph.D. 

Environmental Science Center 

Syracuse Research Corporation 

Syracuse, NY 

Susan Rieth 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Washington, DC 

Andrew Rooney, Ph.D.* 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

 *Currently at National Toxicology Program 

National Institute of Environmental Health Sciences 

 Research Triangle Park, NC

Paul Schlosser, Ph.D. 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Julie Stickney, Ph.D. 

Environmental Science Center 

Syracuse Research Corporation 

Syracuse, NY 

John Vandenberg, Ph.D. 

National Center for Environmental Assessment 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

 xix 
REVIEWERS

This document has been provided for review to EPA scientists, interagency reviewers 

from other federal agencies and White House offices, and the public, and peer reviewed by 

independent scientists external to EPA. A summary and EPA’s disposition of the comments 

received from the independent external peer reviewers and from the public is included in 

Appendix A. 

INTERNAL EPA REVIEWERS

Anthony DeAngelo, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

Nagu Keshava, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

Jason Lambert, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

Connie Meacham, M.S. 

National Center for Environmental Assessment 

Research Triangle Park, NC 

Debra Walsh, M.S. 

National Center for Environmental Assessment 

Research Triangle Park, NC 

Douglas Wolf, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

 xx 
EXTERNAL PEER REVIEWERS 

George V. Alexeeff, Ph.D., DABT 

Office of Environmental Health Hazard Assessment (OEHHA) 

California EPA 

Bruce C. Allen, M.S. 

Bruce Allen Consulting 

James V. Bruckner, Ph.D. 

Department of Pharmaceutical and Biomedical Sciences 

College of Pharmacy 

The University of Georgia 

Harvey J. Clewell III, Ph.D., DABT 

Center for Human Health Assessment 

The Hamner Institutes for Health Sciences 

Lena Ernstgård, Ph.D. 

Institute of Environmental Medicine 

Karolinska Institutet 

Frederick J. Kaskel, M.D., Ph.D. 

Children’s Hospital at Montefiore 

Albert Einstein College of Medicine of Yeshiva University 

Kannan Krishnan, Ph.D., DABT 

Inter-University Toxicology Research Center (CIRTOX) 

Université de Montréal 

Ragubir P. Sharma, DVM, Ph.D. 

Department of Physiology and Pharmacology 

College of Veterinary Medicine (retired) 

The University of Georgia

 xxi 
 

1. INTRODUCTION 

This document presents background information and justification for the Integrated Risk 

Information System (IRIS) Summary of the hazard and dose-response assessment of 

1,4-dioxane. IRIS Summaries may include oral reference dose (RfD) and inhalation reference 

concentration (RfC) values for chronic and subchronic exposure durations, and a carcinogenicity 

assessment. 

The RfD and RfC, if derived, provide quantitative information for use in risk assessments 

for health effects known or assumed to be produced through a nonlinear (presumed threshold) 

mode of action. The RfD (expressed in units of mg/kg-day) is defined as an estimate (with 

uncertainty spanning perhaps an order of magnitude) of a daily exposure to the human 

population (including sensitive subgroups) that is likely to be without an appreciable risk of 

deleterious effects during a lifetime. The inhalation RfC (expressed in units of mg/m3

) is 

analogous to the oral RfD, but provides a continuous inhalation exposure estimate. The 

inhalation RfC considers toxic effects for both the respiratory system (portal-of-entry) and for 

effects peripheral to the respiratory system (extrarespiratory or systemic effects). Reference 

values are generally derived for chronic exposures (up to a lifetime), but may also be derived for 

acute (≤ 24 hours), short-term (>24 hours up to 30 days), and subchronic (>30 days up to 10% of 

lifetime) exposure durations, all of which are derived based on an assumption of continuous 

exposure throughout the duration specified. Unless specified otherwise, the RfD and RfC are 

derived for chronic exposure duration. 

The carcinogenicity assessment provides information on the carcinogenic hazard 

potential of the substance in question and quantitative estimates of risk from oral and inhalation 

exposure may be derived. The information includes a weight-of-evidence judgment of the 

likelihood that the agent is a human carcinogen and the conditions under which the carcinogenic 

effects may be expressed. Quantitative risk estimates may be derived from the application of a 

low-dose extrapolation procedure. If derived, the oral slope factor is a plausible upper bound on 

the estimate of risk per mg/kg-day of oral exposure. Similarly, an inhalation unit risk is a 

plausible upper bound on the estimate of risk per μg/m3

 air breathed. 

Development of these hazard identification and dose-response assessments for 

1,4-dioxane has followed the general guidelines for risk assessment as set forth by the National 

Research Council (NRC, 1983, 194806). EPA guidelines and Risk Assessment Forum Technical 

Panel Reports that may have been used in the development of this assessment include the 

following: Guidelines for the Health Risk Assessment of Chemical Mixtures (U.S. EPA, 1986, 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 1 
 

001468), Guidelines for Mutagenicity Risk Assessment (U.S. EPA, 1986, 001466), 

Recommendations for and Documentation of Biological Values for Use in Risk Assessment

(U.S. EPA, 1988, 064560), Guidelines for Developmental Toxicity Risk Assessment (U.S. EPA, 

1991, 008567), Interim Policy for Particle Size and Limit Concentration Issues in Inhalation 

Toxicity (U.S. EPA, 1994, 076133), Methods for Derivation of Inhalation Reference 

Concentrations and Application of Inhalation Dosimetry (U.S. EPA, 1994, 006488), Use of the 

Benchmark Dose Approach in Health Risk Assessment (U.S. EPA, 1995, 005992), Guidelines for 

Reproductive Toxicity Risk Assessment (U.S. EPA, 1996, 030019), Guidelines for Neurotoxicity 

Risk Assessment (U.S. EPA, 1998, 030021), Science Policy Council Handbook: Risk 

Characterization (U.S. EPA, 2000, 052149), Benchmark Dose Technical Guidance Document

(External Review Draft) (U.S. EPA, 2000, 052150), Supplementary Guidance for Conducting 

Health Risk Assessment of Chemical Mixture s (U.S. EPA, 2000, 004421; U.S. EPA, 2000, 

196144), A Review of the Reference Dose and Reference Concentration Processes (U.S. EPA, 

2002, 088824), Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237),

Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens 

(U.S. EPA, 2005, 088823), Science Policy Council Handbook: Peer Review (U.S. EPA, 2006, 

194566), and A Framework for Assessing Health Risks of Environmental Exposures to Children

(U.S. EPA, 2006, 194567). 

The literature search strategy employed for this compound was based on the Chemical 

Abstracts Service Registry Number (CASRN) and at least one common name. Any pertinent 

scientific information submitted by the public to the IRIS Submission Desk was also considered 

in the development of this document. The relevant literature was reviewed through September 

2009. Note that during the development of this assessment, new data regarding the toxicity of 

1,4-dioxane through the inhalation route of exposure became available. These data have not been 

included in the current assessment and will be evaluated in a separate IRIS assessment. 

 2 
 

2. CHEMICAL AND PHYSICAL INFORMATION 

1,4-Dioxane, a volatile organic compound (VOC), is a colorless liquid with a pleasant 

odor (Hawley and Lewis, 2001, 196089; Lewis, 2000, 625540). Synonyms include diethylene 

ether, 1,4-diethylene dioxide, diethylene oxide, dioxyethylene ether, and dioxane (Hawley and 

Lewis, 2001, 196089). The chemical structure of 1,4-dioxane is shown in Figure 2-1. Selected 

chemical and physical properties of this substance are listed in Table 2-1 below: 

Figure 2-1. 1,4-Dioxane chemical structure. 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 3 
 

Table 2-1. Physical properties and chemical identity of 1,4-dioxane 

CASRN: 123-91-1 (CRC, 2000, 196090) 

Molecular weight: 88.10 (Merck, 2001, 595055) 

Chemical formula: C4H8O2 (Merck, 2001, 595055) 

Boiling point: 101.1°C (Merck, 2001, 595055) 

Melting point: 11.8°C (CRC, 2000, 196090) 

Vapor pressure: 40 mmHg at 25°C (Lewis, 2000, 625540) 

Density: 1.0337 g/mL at 20°C (CRC, 2000, 196090) 

Vapor density: 3.03 (air = 1) (Lewis, 2000, 625540) 

Water solubility: Miscible with water (Hawley and Lewis, 2001, 196089) 

Other solubilities: Miscible with ethanol, ether, and acetone (CRC, 2000, 

196090) 

Log Kow: –0.27 (Hansch et al., 1995, 051424) 

Henry’s Law constant: 4.80 × 10-6 atm-m3

/molecule at 25°C (Park et al., 1987, 

194328) 

OH reaction rate constant: 1.09 × 10-11

 cm3/molecule sec at 25°C (Atkinson, 1989, 

042876) 

Koc: 17 (estimated using log Kow) (ACS, 1990, 004237) 

Bioconcentration factor: 0.4 (estimated using log Kow) (Meylan et al., 1999, 

194377) 

Conversion factors (in air): 1 ppm = 3.6 mg/m3; 1 mg/m3 = 0.278 ppm 

(25oC and 1 atm) (HSDB, 2007, 196232) 

1,4-Dioxane is produced commercially through the dehydration and ring closure of 

diethylene glycol (Surprenant, 2002, 196117). Concentrated sulfuric acid is used as a catalyst 

(Surprenant, 2002, 196117). This is a continuous distillation process with operating 

temperatures and pressures of 130–200°C and 188–825 mmHg, respectively (Surprenant, 2002, 

196117). During the years 1986 and 1990, the U.S. production of 1,4-dioxane reported by 

manufacturers was within the range of 10–50 million pounds (U.S. EPA, 2002, 594597). The 

production volume reported during the years 1994, 1998, and 2002 was within the range of 

1–10 million pounds (U.S. EPA, 2002, 594597). 

Historically, 1,4-dioxane has been used as a stabilizer for the solvent 1,1,1-trichloroethane (Surprenant, 2002, 196117). However, this use is no longer expected to be important due 

to the 1990 Amendments to the Clean Air Act and the Montreal Protocol, which mandate the 

eventual phase-out of 1,1,1-trichloroethane production in the U.S. (ATSDR, 2007, 196127; 

U.S. EPA, 1990, 196139; UNEP, 2000, 196125). 1,4-Dioxane is a contaminant of some 

ingredients used in the manufacture of personal care products and cosmetics. 1,4-Dioxane is also 

 4 
 

used as a solvent for cellulosics, organic products, lacquers, paints, varnishes, paint and varnish 

removers, resins, oils, waxes, dyes, cements, fumigants, emulsions, and polishing compositions 

(Hawley and Lewis, 2001, 196089; IARC, 1999, 196238; Merck, 2001, 595055). 1,4-Dioxane 

has been used as a solvent in the formulation of inks, coatings, and adhesives and in the 

extraction of animal and vegeTable oil (Surprenant, 2002, 196117). Reaction products of 

1,4-dioxane are used in the manufacture of insecticides, herbicides, plasticizers, and monomers 

(Surprenant, 2002, 196117). 

When 1,4-dioxane enters the air, it will exist as a vapor, as indicated by its vapor pressure 

(HSDB, 2007, 196232). It is expected to be degraded in the atmosphere through photooxidation 

with hydroxyl radicals (HSDB, 2007, 196232; Surprenant, 2002, 196117). The estimated halflife for this reaction is 6.7 hours (HSDB, 2007, 196232). It may also be broken down by reaction 

with nitrate radicals, although this removal process is not expected to compete with hydroxyl 

radical photooxidation (Grosjean, 1990, 196213). 1,4-Dioxane is not expected to undergo direct 

photolysis (Wolfe and Jeffers, 2000, 196109). 1,4-Dioxane is primarily photooxidized to 

2-oxodioxane and through reactions with nitrogen oxides (NOx) results in the formation of 

ethylene glycol diformate (Platz et al., 1997, 196086). 1,4-Dioxane is expected to be highly 

mobile in soil based on its estimated Koc and is expected to leach to lower soil horizons and 

groundwater (ACS, 1990, 004237; ATSDR, 2007, 196127). This substance may volatilize from 

dry soil surfaces based on its vapor pressure (HSDB, 2007, 196232). The estimated 

bioconcentration factor value indicates that 1,4-dioxane will not bioconcentrate in aquatic or 

marine organisms (Franke et al., 1994, 194356; Meylan et al., 1999, 194377). 1,4-Dioxane is not 

expected to undergo hydrolysis or to biodegrade readily in the environment (ATSDR, 2007, 

196127; HSDB, 2007, 196232). Therefore, volatilization is expected to be the dominant removal 

process for moist soil and surface water. Based on a Henry's Law constant of 4.8×10-6

atm-m3

/mole, the half-life for volatilization of 1,4-dioxane from a model river is 5 days and that 

from a model lake is 56 days (ACS, 1990, 004237; HSDB, 2007, 196232; Park et al., 1987, 

194328). 1,4-Dioxane may be more persistent in groundwater where volatilization is hindered. 

Recent environmental monitoring data for 1,4-dioxane are lacking. Existing data indicate 

that 1,4-dioxane may leach from hazardous waste sites into drinking water sources located 

nearby (Lesage et al., 1990, 195913; Yasuhara et al., 1997, 195909; Yasuhara et al., 2003, 

195095). 1,4-Dioxane has been detected in contaminated surface and groundwater samples 

collected near hazardous waste sites and industrial facilities (Derosa et al., 1996, 194371). 

 5 
 

3. TOXICOKINETICS 

Data for the toxicokinetics of 1,4-dioxane in humans are very limited. However, 

absorption, distribution, metabolism, and elimination of 1,4-dioxane are well described in rats 

exposed via the oral, inhalation, or intravenous (i.v.) routes. 1,4-Dioxane is extensively absorbed 

and metabolized in humans and rats. The metabolite most often measured and reported is 

β-hydroxyethoxy acetic acid (HEAA), which is predominantly excreted in the urine; however, 

other metabolites have also been identified. Saturation of 1,4-dioxane metabolism has been 

observed in rats and would be expected in humans; however, human exposure levels associated 

with nonlinear toxicokinetics are not known. 

Important data elements that have contributed to our current understanding of the 

toxicokinetics of 1,4-dioxane are summarized in the following sections. 

3.1. ABSORPTION 

Absorption of 1,4-dioxane following inhalation exposure has been qualitatively 

demonstrated in workers and volunteers. Workers exposed to a time-weighted average (TWA) 

of 1.6 parts per million (ppm) of 1,4-dioxane in air for 7.5 hours showed a HEAA/1,4-dioxane 

ratio of 118:1 in urine (Young et al., 1976, 062953). The authors assumed lung absorption to be 

100% and calculated an average absorbed dose of 0.37 mg/kg, although no exhaled breath 

measurements were taken. In a study with four healthy male volunteers, Young et al. (1977, 

062956) reported 6-hour inhalation exposures of adult volunteers to 50 ppm of 1,4-dioxane in a 

chamber, followed by blood and urine analysis for 1,4-dioxane and HEAA. The study protocol 

was approved by a seven-member Human Research Review Committee of the Dow Chemical 

Company, and written informed consent of study participants was obtained. At a concentration 

of 50 ppm, uptake of 1,4-dioxane into plasma was rapid and approached steady-state conditions 

by 6 hours. The authors reported a calculated absorbed dose of 5.4 mg/kg. However, the 

exposure chamber atmosphere was kept at a constant concentration of 50 ppm and exhaled 

breath was not analyzed. Accordingly, gas uptake could not be measured. As a result, the 

absorbed fraction of inhaled 1,4-dioxane could not be accurately determined in humans. Rats 

inhaling 50 ppm for 6 hours exhibited 1,4-dioxane and HEAA in urine with an HEAA to 

1,4-dioxane ratio of over 3,100:1 (Young et al., 1978, 062955; Young et al., 1978, 625640). 

Plasma concentrations at the end of the 6-hour exposure period averaged 7.3 μg/mL. The 

authors calculated an absorbed 1,4-dioxane dose of 71.9 mg/kg; however, the lack of exhaled 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 6 
 

breath data and dynamic exposure chamber precluded the accurate determination of the absorbed 

fraction of inhaled 1,4-dioxane. 

No human data are available to evaluate the oral absorption of 1,4-dioxane. 

Gastrointestinal absorption was nearly complete in male Sprague Dawley rats orally dosed with 

10–1,000 mg/kg of [14C]-1,4-dioxane given as a single dose or as 17 consecutive daily doses 

(Young et al., 1978, 062955; Young et al., 1978, 625640). Cumulative recovery of radiolabel in 

the feces was <1–2% of administered dose regardless of dose level or frequency. 

No human data are available to evaluate the dermal absorption of 1,4-dioxane; however, 

Bronaugh (1982, 196146) reported an in vitro study in which 1,4-dioxane penetrated excised 

human skin 10 times more under occluded conditions (3.2% of applied dose) than unoccluded 

conditions (0.3% of applied dose). [14C]-1,4-Dioxane was dissolved in lotion, applied to the 

excised skin in occluded and unoccluded diffusion cells, and absorption of the dose was recorded 

205 minutes after application. Bronaugh (1982, 196146) also reported observing rapid 

evaporation, which further decreased the small amount available for skin absorption. 

Dermal absorption data in animals are also limited. Dermal absorption in animals was 

reported to be low following exposure of forearm skin of monkeys (Marzulli et al., 1981, 

194326). In this study, Rhesus monkeys were exposed to [14C]-1,4-dioxane in methanol or skin 

lotion vehicle for 24 hours (skin was uncovered/unoccluded). Only 2–3% of the original 

radiolabel was cumulatively recovered in urine over a 5-day period. 

3.2. DISTRIBUTION 

No data are available for the distribution of 1,4-dioxane in human tissues. No data are 

available for the distribution of 1,4-dioxane in animals following oral or inhalation exposures. 

Mikheev et al. (1990, 195061) studied the distribution of [14C]-1,4-dioxane in the blood, 

liver, kidney, brain, and testes of rats (strain not reported) for up to 6 hours following 

intraperitoneal (i.p.) injection of approximately one-tenth the median lethal dose (LD50) (actual 

dose not reported). While actual tissue concentrations were not reported, tissue:blood ratios 

were given for each tissue at six time points ranging from 5 minutes to 6 hours. The time to 

reach maximum accumulation of radiolabel was shorter for liver and kidney than for blood or the 

other tissues, which the authors suggested was indicative of selective membrane transport. 

Tissue:blood ratios were less than one for all tissues except testes, which had a ratio greater than 

one at the 6-hour time point. The significance of these findings is questionable since the 

contribution of residual blood in the tissues was unknown (though saline perfusion may serve to 

clear tissues of highly water-soluble 1,4-dioxane), the tissue concentrations of radiolabel were 

not reported, and data were collected from so few time points. 

Woo et al. (1977, 194355) administered i.p. doses of [3

H]-1,4-dioxane (5 mCi/kg body 

weight [BW]) to male Sprague Dawley rats with and without pretreatment using mixed-function 

oxidase inducers (phenobarbital, 3-methylcholanthrene, or polychlorinated biphenyls [PCBs]). 

 7 
 

Liver, kidney, spleen, lung, colon, and skeletal muscle tissues were collected from 1, 2, 6, and 

12 hours after dosing. Distribution was generally uniform across tissues, with blood 

concentrations higher than tissues at all times except for 1 hour post dosing, when kidney levels 

were approximately 20% higher than blood. Since tissues were not perfused prior to analysis, 

the contribution of residual blood to radiolabel measurements is unknown, though loss of 

1,4-dioxane from tissues would be unknown had saline perfusion been performed. Covalent 

binding reached peak percentages at 6 hours after dosing in liver (18.5%), spleen (22.6%), and 

colon (19.5%). At 16 hours after dosing, peak covalent binding percentages were observed in 

whole blood (3.1%), kidney (9.5%), lung (11.2%), and skeletal muscle (11.2%). Within 

hepatocytes, radiolabel distribution at 6 hours after dosing was greatest in the cytosolic fraction 

(43.8%) followed by the microsomal (27.9%), mitochondrial (16.6%), and nuclear (11.7%) 

fractions. While little covalent binding of radiolabel was measured in the hepatic cytosol (4.6%), 

greater binding was observed at 16 hours after dosing in the nuclear (64.8%), mitochondrial 

(45.7%), and microsomal (33.4%) fractions. Pretreatment with inducers of mixed-function 

oxidase activity did not significantly change the extent of covalent binding in subcellular 

fractions. 

3.3. METABOLISM 

The major product of 1,4-dioxane metabolism appears to be HEAA, although there is 

one report that identified 1,4-dioxane-2-one as a major metabolite (Woo et al., 1977, 194355). 

However, the presence of this compound in the sample was believed to result from the acidic 

conditions (pH of 4.0–4.5) of the analytical procedures. The reversible conversion of HEAA and 

p-1,4-dioxane-2-one is pH-dependent (Braun and Young, 1977, 194370). Braun and Young 

(1977, 194370) identified HEAA (85%) as the major metabolite, with most of the remaining 

dose excreted as unchanged 1,4-dioxane in the urine of Sprague Dawley rats dosed with 

1,000 mg/kg of uniformly labeled 1,4-[14C]dioxane. In fact, toxicokinetic studies of 1,4-dioxane 

in humans and rats (Young et al., 1977, 062956; 1978, 062955; Young et al., 1978, 625640) 

employed an analytical technique that converted HEAA to the more volatile 1,4-dioxane-2-one 

prior to gas chromatography (GC); however, it is still unclear as to whether HEAA or 

1,4-dioxane-2-one is the major metabolite of 1,4-dioxane. 

A proposed metabolic scheme for 1,4-dioxane metabolism (Woo et al., 1977, 194355) in 

Sprague Dawley rats is shown in Figure 3-1. Oxidation of 1,4-dioxane to diethylene glycol 

(pathway a), 1,4-dioxane-2-ol (pathway c), or directly to 1,4-dioxane-2-one (pathway b) could 

result in the production of HEAA. 1,4-Dioxane oxidation appears to be cytochrome P450 

(CYP450)-mediated, as CYP450 induction with phenobarbital or Aroclor 1254 (a commercial 

PCB mixture) and suppression with 2,4-dichloro-6-phenylphenoxy ethylamine or cobaltous 

chloride were effective in significantly increasing and decreasing, respectively, the appearance of 

HEAA in the urine of male Sprague Dawley rats following 3 g/kg i.p. dose (Woo et al., 1977, 

 8 
 

062951; Woo et al., 1978, 194345). 1,4-Dioxane itself induced CYP450-mediated metabolism 

of several barbiturates in Hindustan mice given i.p. injections of 25 and 50 mg/kg 1,4-dioxane 

(Mungikar and Pawar, 1978, 194344). Of the three possible pathways proposed in this scheme, 

oxidation to diethylene glycol and HEAA appears to be the most likely, because diethylene 

glycol was found as a minor metabolite in Sprague Dawley rat urine following a single 

1,000 mg/kg gavage dose of 1,4-dioxane (Braun and Young, 1977, 194370). Additionally, i.p. 

injection of 100–400 mg/kg diethylene glycol in Sprague Dawley rats resulted in urinary 

elimination of HEAA (Woo et al., 1977, 062950). 

Source: Adapted with permission from Elsevier Ltd., Woo et al. (1977, 194355; 1977, 

062951). 

Figure 3-1. Suggested metabolic pathways of 1,4-dioxane in the rat. 

I = 1,4-dioxane; II = diethylene glycol; III = β-hydroxyethoxy acetic acid (HEAA); 

IV = 1,4-dioxane-2-one; V = 1,4-dioxane-2-ol; VI = β-hydroxyethoxy acetaldehyde. 

Note: Metabolite [V] is a likely intermediate in pathway b as well as pathway c. 

The proposed pathways are based on the metabolites identified; the enzymes 

responsible for each reaction have not been determined. The proposed pathways do 

not account for metabolite degradation to the labeled carbon dioxide (CO2) 

identified in expired air after labeled 1,4-dioxane exposure. 

Metabolism of 1,4-dioxane in humans is extensive. In a survey of 1,4-dioxane plant 

workers exposed to a TWA of 1.6 ppm of 1,4-dioxane for 7.5 hours, Young et al. (1976, 062953) 

found HEAA and 1,4-dioxane in the worker’s urine at a ratio of 118:1. Similarly, in adult male 

volunteers exposed to 50 ppm for 6 hours (Young et al., 1977, 062956), over 99% of inhaled 

1,4-dioxane (assuming negligible exhaled excretion) appeared in the urine as HEAA. The linear 

 9 
 

elimination of 1,4-dioxane in both plasma and urine indicated that 1,4-dioxane metabolism was a 

nonsaturated, first-order process at this exposure level. 

Like humans, rats extensively metabolize inhaled 1,4-dioxane, as HEAA content in urine 

was over 3,000-fold higher than that of 1,4-dioxane following exposure to 50 ppm for 6 hours 

(Young et al., 1978, 062955; Young et al., 1978, 625640). 1,4-Dioxane metabolism in rats was a 

saturable process, as exhibited by oral and i.v. exposures to various doses of [14C]-1,4-dioxane 

(Young et al., 1978, 062955; Young et al., 1978, 625640). Plasma data from Sprague Dawley 

rats given single i.v. doses of 3, 10, 30, 100, 300, or 1,000 mg [14C]-1,4-dioxane/kg demonstrated 

a dose-related shift from linear, first-order to nonlinear, saturable metabolism of 1,4-dioxane 

between plasma 1,4-dioxane levels of 30 and 100 μg/mL (Figure 3-2). Similarly, in rats given, 

via gavage in distilled water, 10, 100, or 1,000 mg [14C]-1,4-dioxane/kg singly or 10 or 1,000 mg 

[

14C]-1,4-dioxane/kg in 17 daily doses, the percent urinary excretion of the radiolabel decreased 

significantly with dose while radiolabel in expired air increased. Specifically, with single 

[

14C]-1,4-dioxane/kg doses, urinary radiolabel decreased from 99 to 76% and expired 

1,4-dioxane increased from <1 to 25% as dose increased from 10 to 1,000 mg/kg. Likewise, 

with multiple daily doses 10 or 1,000 mg [14C]-1,4-dioxane/kg, urinary radiolabel decreased 

from 99 to 82% and expired 1,4-dioxane increased from 1 to 9% as dose increased. The 

differences between single and multiple doses in urinary and expired radiolabel support the 

notion that 1,4-dioxane may induce its own metabolism. 

 10 
 

Source: Used with permission from Taylor and Francis, Young et al. (1978, 062955). 

Figure 3-2. Plasma 1,4-dioxane levels in rats following i.v. doses of 

3-5,600 mg/kg. 

1,4-Dioxane has been shown to induce several isoforms of CYP450 in various tissues 

following acute oral administration by gavage or drinking water (Nannelli et al., 2005, 195067). 

Male Sprague Dawley rats were exposed to either 2,000 mg/kg 1,4-dioxane via gavage for 

2 consecutive days or by ingestion of a 1.5% 1,4-dioxane drinking water solution for 10 days. 

Both exposures resulted in significantly increased CYP2B1/2, CYP2C11, and CYP2E1 activities 

in hepatic microsomes. The gavage exposure alone resulted in increased CYP3A activity. The 

increase in 2C11 activity was unexpected, as that isoform has been observed to be under 

hormonal control and was typically suppressed in the presence of 2B1/2 and 2E1 induction. In 

the male rat, hepatic 2C11 induction is associated with masculine pulsatile plasma profiles of 

growth hormone (compared to the constant plasma levels in the female), resulting in 

masculinization of hepatocyte function (Waxman et al., 1991, 196102). The authors postulated 

that 1,4-dioxane may alter plasma growth hormone levels, resulting in the observed 2C11 

induction. However, growth hormone induction of 2C11 is primarily dependent on the duration 

between growth hormone pulses and secondarily on growth hormone plasma levels (Agrawal 

 11 
 

and Shapiro, 2000, 196132; Waxman et al., 1991, 196102). Thus, the induction of 2C11 by 

1,4-dioxane may be mediated by changes in the time interval between growth hormone pulses 

rather than changes in growth hormone levels. This may be accomplished by 1,4-dioxane 

temporarily influencing the presence of growth hormone cell surface binding sites (Agrawal and 

Shapiro, 2000, 196132). However, no studies are available to confirm the influence of 

1,4-dioxane on either growth hormone levels or changes in growth hormone pulse interval. 

In nasal and renal mucosal cell microsomes, CYP2E1 activity, but not CYP2B1/2 

activity, was increased. Pulmonary mucosal CYP450 activity levels were not significantly 

altered. Observed increases in 2E1 mRNA in rats exposed by gavage and i.p. injection suggest 

that 2E1 induction in kidney and nasal mucosa is controlled by a transcriptional activation of 

2E1 genes. The lack of increased mRNA in hepatocytes suggests that induction is regulated via 

a post-transcriptional mechanism. Differences in 2E1 induction mechanisms in liver, kidney, 

and nasal mucosa suggest that induction is controlled in a tissue-specific manner. 

3.4. ELIMINATION 

In workers exposed to a TWA of 1.6 ppm for 7.5 hours, 99% of 1,4-dioxane eliminated in 

urine was in the form of HEAA (Young et al., 1976, 062953). The elimination half-life was 

59 minutes in adult male volunteers exposed to 50 ppm 1,4-dioxane for 6 hours, with 90% of 

urinary 1,4-dioxane and 47% of urinary HEAA excreted within 6 hours of onset of exposure 

(Young et al., 1977, 062956). There are no data for 1,4-dioxane elimination in humans from oral 

exposures. 

Elimination of 1,4-dioxane in rats (Young et al., 1978, 062955; Young et al., 1978, 

625640) was primarily via urine. Like humans, the elimination half-life in rats exposed to 

50 ppm 1,4-dioxane for 6 hours was calculated to be 1.01 hours. In Sprague Dawley rats given 

single daily doses of 10, 100, or 1,000 mg [14C]-1,4-dioxane/kg or multiple doses of 10 or 

1,000 mg [14C]-1,4-dioxane/kg, urinary radiolabel ranged from 99% down to 76% of total 

radiolabel. Fecal elimination was less than 2% for all doses. The effect of saturable metabolism 

on expired 1,4-dioxane was apparent, as expired 1,4-dioxane in singly dosed rats increased with 

dose from 0.4 to 25% while expired 14CO2 changed little (between 2 and 3%) across doses. The 

same relationship was seen in Sprague Dawley rats dosed i.v. with 10 or 1,000 mg 

[

14C]-1,4-dioxane/kg. Higher levels of 14CO2 relative to 1,4-dioxane were measured in expired 

air of the 10 mg/kg group, while higher levels of expired 1,4-dioxane relative to 14CO2 were 

measured in the 1,000 mg/kg group. 

3.5. PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELS 

Physiologically based pharmacokinetic models (PBPK) models have been developed for 

1,4-dioxane in rats and humans (Leung and Paustenbach, 1990, 062932; Reitz et al., 1990, 

094806) and lactating women (Fisher et al., 1997, 194390). Each of the models simulates the 

 12 
 

body as a series of compartments representing tissues or tissue groups that receive blood from 

the central vascular compartment (Figure 3-3). Modeling was conducted under the premise that 

transfers of 1,4-dioxane between blood and tissues occur sufficiently fast to be effectively blood 

flow-limited, which is consistent with the available data (Ramsey and Andersen, 1984, 063020). 

Blood time course and metabolite production data in rats and humans suggest that absorption and 

metabolism are accomplished through common mechanisms in both species (Young et al., 1977, 

062956; 1978, 062955) (Young et al., 1978, 625640), allowing identical model structures to be 

used for both species (and by extension, for mice as well). In all three models, physiologically 

relevant, species-specific parameter values for tissue volume, blood flow, and metabolism and 

elimination are used. The models and supporting data are reviewed below, from the perspective 

of assessing their utility for predicting internal dosimetry and for cross-species extrapolation of 

exposure-response relationships for critical neoplastic and nonneoplastic endpoints (also see 

Appendix B). 

Figure 3-3. General PBPK model structure consisting of blood-flow 

limited tissue compartments connected via arterial and venous blood flows. 

Note: Orally administered chemicals are absorbed directly into the liver while 

inhaled and intravenously infused chemicals enter directly into the arterial and 

venous blood pools, respectively. 

 13 
 

3.5.1. Available Pharmacokinetic Data 

Animal and human data sets available for model calibration derive from Young et al. 

(1977, 062956; 1978, 062955; 1978, 625640), Mikheev et al. (1990, 195061), and Woo et al. 

(1977, 062950; 1977, 194355). Young et al. (1978, 062955; 1978, 625640) studied the 

disposition of radiolabeled [14C]-1,4-dioxane in adult male Sprague Dawley rats following i.v., 

inhalation, and single and multiple oral gavage exposures. Plasma concentration-time profiles 

were reported for i.v. doses of 3, 10, 30, 100, and 1,000 mg/kg. In addition, exhaled 14CO2 and 

urinary 1,4-dioxane and HEAA profiles were reported following i.v. doses of 10 and 

1,000 mg/kg. The plasma 1,4-dioxane concentration-time course, cumulative urinary 

1,4-dioxane and cumulative urinary HEAA concentrations were reported following a 6-hour 

inhalation exposure to 50 ppm. Following oral gavage doses of 10–1,000 mg/kg, percentages of 

total orally administered radiolabel were measured in urine, feces, expired air, and the whole 

body. 

Oral absorption of 1,4-dioxane was extensive, as only approximately 1% of the 

administered dose appeared in the feces within 72 hours of dosing (Young et al., 1978, 062955) 

(Young et al., 1978, 625640). Although it may be concluded that the rate of oral absorption was 

high enough to ensure nearly complete absorption by 72 hours, a more quantitative estimate of 

the rate of oral absorption is not possible due to the absence of plasma time course data by oral 

exposure. 

Saturable metabolism of 1,4-dioxane was observed in rats exposed by either the i.v. or 

oral routes (Young et al., 1978, 062955; Young et al., 1978, 625640). Elimination of 

1,4-dioxane from plasma appeared to be linear following i.v. doses of 3-30 mg/kg, but was 

nonlinear following doses of 100–1,000 mg/kg. Accordingly, 10 mg/kg i.v. doses resulted in 

higher concentrations of 14CO2 (from metabolized 1,4-dioxane) in expired air relative to 

unchanged 1,4-dioxane, while 1,000 mg/kg i.v. doses resulted in higher concentrations of 

expired 1,4-dioxane relative to 14CO2. Thus, at higher i.v. doses, a higher proportion of 

unmetabolized 1,4-dioxane is available for exhalation. Taken together, the i.v. plasma and 

expired air data from Young et al. (1978, 062955; 1978, 625640) corroborate previous studies 

describing the saturable nature of 1,4-dioxane metabolism in rats (Woo et al., 1977, 062950; 

1977, 194355) and are useful for optimizing metabolic parameters (Vmax and Km) in a PBPK 

model. 

Similarly, increasing single or multiple oral doses of 10–1,000 mg/kg resulted in 

increasing percentage of 1,4-dioxane in exhaled air and decreasing percentage of radiolabel 

(either as 1,4-dioxane or a metabolite) in the urine, with significant differences in both metrics 

being observed between doses of 10 and 100 mg/kg (Young et al., 1978, 062955; Young et al., 

1978, 625640). These data identify the region (10–100 mg/kg) in which oral exposures will 

result in nonlinear metabolism of 1,4-dioxane and can be used to test whether metabolic 

 14 
 

parameter value estimates derived from i.v. dosing data are adequate for modeling oral 

exposures. 

Post-exposure plasma data from a single 6-hour, 50 ppm inhalation exposure in rats were 

reported (Young et al., 1978, 062955; Young et al., 1978, 625640). The observed linear 

elimination of 1,4-dioxane after inhalation exposure suggests that, via this route, metabolism is 

in the linear region at this exposure level. 

The only human data adequate for use in PBPK model development (Young et al., 1977, 

062956) come from adult male volunteers exposed to 50 ppm 1,4-dioxane for 6 hours. Plasma 

1,4-dioxane and HEAA concentrations were measured both during and after the exposure period, 

and urine concentrations were measured following exposure. Plasma levels of 1,4-dioxane 

approached steady-state at 6 hours. HEAA data were insufficient to describe the appearance or 

elimination of HEAA in plasma. Data on elimination of 1,4-dioxane and HEAA in the urine up 

to 24 hours from the beginning of exposure were reported. At 6 hours from onset of exposure, 

approximately 90% and 47% of the cumulative (0–24 hours) urinary 1,4-dioxane and HEAA, 

respectively, were measured in the urine. The ratio of HEAA to 1,4-dioxane in urine 24 hours 

after onset of exposure was 192:1 (similar to the ratio of 118:1 observed by Young et al. (1976, 

062953) in workers exposed to 1.6 ppm for 7.5 hours), indicating extensive metabolism of 

1,4-dioxane As with Sprague Dawley rats, the elimination of 1,4-dioxane from plasma was 

linear across all observations (6 hours following end of exposure), suggesting that human 

metabolism of 1,4-dioxane is linear for a 50 ppm inhalation exposure to steady-state. Thus, 

estimation of human Vmax and Km from these data will introduce uncertainty into internal 

dosimetry performed in the nonlinear region of metabolism. 

Further data were reported for the tissue distribution of 1,4-dioxane in rats. Mikheev 

et al. (1990, 195061) administered i.p. doses of [14C]-1,4-dioxane to white rats (strain not 

reported) and reported time-to-peak blood, liver, kidney, and testes concentrations. They also 

reported ratios of tissue to blood concentrations at various time points after dosing. Woo et al. 

(1977, 062950; 1977, 194355) administered i.p. doses of [14C]-1,4-dioxane to Sprague Dawley 

rats and measured radioactivity levels in urine. However, since i.p. dosing is not relevant to 

human exposures, these data are of limited use for PBPK model development. 

3.5.2. Published PBPK Models for 1,4-Dioxane 

3.5.2.1. Leung and Paustenbach 

Leung and Paustenbach (1990, 062932) developed a PBPK model for 1,4-dioxane and its 

primary metabolite, HEAA, in rats and humans. The model, based on the structure of a PBPK 

model for styrene (Ramsey and Andersen, 1984, 063020), consists of a central blood 

compartment and four tissue compartments: liver, fat, slowly perfused tissues (mainly muscle 

and skin), and richly perfused tissues (brain, kidney, and viscera other than the liver). Tissue 

 15 
 

volumes were calculated as percentages of total BW, and blood flow rates to each compartment 

were calculated as percentages of cardiac output. Equivalent cardiac output and alveolar 

ventilation rates were allometrically scaled to a power (0.74) of BW for each species. The 

concentration of 1,4-dioxane in alveolar blood was assumed to be in equilibrium with alveolar 

air at a ratio equal to the experimentally measured blood:air partition coefficient. Transfers of 

1,4-dioxane between blood and tissues were assumed to be blood flow-limited and to achieve 

rapid equilibrium between blood and tissue, governed by tissue:blood equilibrium partition 

coefficients. The latter were derived from the quotient of blood:air and tissue:air partition 

coefficients, which were measured in vitro (Leung and Paustenbach, 1990, 062932) for blood, 

liver, fat, and skeletal muscle (slowly perfused tissue). Blood:air partition coefficients were 

measured for both humans and rats. Rat tissue:air partition coefficients were used as surrogate 

values for humans, with the exception of slowly perfused tissue:blood, which was estimated by 

optimization to the plasma time-course data. Portals of entry included i.v. infusion (over a 

period of 36 seconds) into the venous blood, inhalation by diffusion from the alveolar air into the 

lung blood at the rate of alveolar ventilation, and oral administration via zero-order absorption 

from the gastrointestinal tract to the liver. Elimination of 1,4-dioxane was accomplished through 

pulmonary exhalation and saturable hepatic metabolism. Urinary excretion of HEAA was 

assumed to be instantaneous with the generation of HEAA from the hepatic metabolism of 

1,4-dioxane. 

The parameter values for hepatic metabolism of 1,4-dioxane, Vmax and Km, were 

optimized and validated against plasma and/or urine time course data for 1,4-dioxane and HEAA 

in rats following i.v. and inhalation exposures and humans following inhalation exposure (Young 

et al., 1977, 062956; 1978, 062955; 1978, 625640); the exact data (i.e., i.v., inhalation, or both) 

used for the optimization and calibration were not reported. Although the liver and fat were 

represented by tissue-specific compartments, no tissue-specific concentration data were available 

for model development, raising uncertainty as the model’s ability to adequately predict exposure 

to these tissues. The human inhalation exposure of 50 ppm for 6 hours (Young et al., 1977, 

062956) was reported to be in the linear range for metabolism; thus, uncertainty exists in the 

ability of the allometrically-scaled value for the human metabolic Vmax to accurately describe 

1,4-dioxane metabolism from exposures resulting in metabolic saturation. Nevertheless, these 

values resulted in the model producing good fits to the data. For rats, the values for Vmax had to 

be adjusted upwards by a factor of 1.8 to reasonably simulate exposures greater than 300 mg/kg. 

The model authors attributed this to metabolic enzyme induction by high doses of 1,4-dioxane. 

3.5.2.2. Reitz et al. 

Reitz et al. (1990, 094806) developed a model for 1,4-dioxane and HEAA in the mouse, 

rat, and human. This model, also based on the styrene model of Ramsey and Andersen (1984, 

063020), included a central blood compartment and compartments for liver, fat, and rapidly and 

 16 
 

slowly perfused tissues. Tissue volumes and blood flow rates were defined as percentages of 

total BW and cardiac output, respectively. Physiological parameter values were similar to those 

used by Andersen et al. (1987, 001938), except that flow rates for cardiac output and alveolar 

ventilation were doubled in order to produce a better fit of the model to human blood level data 

(Young et al., 1977, 062956). Portals of entry included i.v. injection into the venous blood, 

inhalation, oral bolus dosing, and oral dosing via drinking water. Oral absorption of 1,4-dioxane 

was simulated, in all three species, as a first-order transfer to liver (halftime approximately 

8 minutes). 

Alveolar blood levels of 1,4-dioxane were assumed to be in equilibrium with alveolar air 

at a ratio equal to the experimentally measured blood:air partition coefficient. Transfers of 

1,4-dioxane between blood and tissues were assumed to be blood flow-limited and to achieve 

rapid equilibrium between blood and tissue, governed by tissue:blood equilibrium partition 

coefficients. These coefficients were derived by dividing experimentally measured (Leung and 

Paustenbach, 1990, 062932) in vitro blood:air and tissue:air partition coefficients for blood, liver, 

fat. Blood:air partition coefficients were measured for both humans and rats. The mouse 

blood:air partition coefficient was different from rat or human values; the source of the partition 

coefficient for blood in mice was not reported. Rat tissue:air partition coefficients were used as 

surrogate values for humans. Rat tissue partition coefficient values were the same values as used 

in the Leung and Paustenbach (1990, 062932) model (with the exception of slowly perfused 

tissues) and were used in the models for all three species. The liver value was used for the 

rapidly perfused tissues, as well as slowly perfused tissues. Although slowly perfused tissue:air 

partition coefficients for rats were measured, the authors suggested that 1,4-dioxane in the 

muscle and air may not have reached equilibrium in the highly gelatinous tissue homogenate 

(Reitz et al., 1990, 094806). Substitution of the liver value provided much closer agreement to 

the plasma data than when the muscle value was used. Further, doubling of the measured human 

blood:air partition coefficient improved the fit of the model to the human blood level data 

compared to the fit resulting from the measured value (Reitz et al., 1990, 094806). The Reitz 

et al. (1990, 094806) model simulated three routes of 1,4-dioxane elimination: pulmonary 

exhalation, hepatic metabolism to HEAA, and urinary excretion of HEAA. The elimination of 

HEAA was modeled as a first-order transfer of 1,4-dioxane metabolite to urine. 

Values for the metabolic rate constants, Vmax and Km, were optimized to achieve 

agreement with various observations. Reitz et al. (1990, 094806) optimized values for human 

Vmax and Km against the experimental human 1,4-dioxane inhalation data (Young et al., 1977, 

062956). As noted previously, because the human exposures were below the level needed to 

exhibit nonlinear kinetics, uncertainty exists in the ability of the optimized value of Vmax to 

simulate human 1,4-dioxane metabolism above the concentration that would result in saturation 

of metabolism. Rat metabolic rate constants were obtained by optimization to simulated data 

 17 
 

from a two-compartment empirical pharmacokinetic model, which was fitted to i.v. exposure 

data (Young et al., 1978, 062955; Young et al., 1978, 625640). As with the Leung and 

Paustenbach (1990, 062932) model, the Reitz et al. (1990, 094806) model included 

compartments for the liver and fat, although no tissue-specific concentration data were available 

to validate dosimetry for these organs. The derivations of human and rat HEAA elimination rate 

constants were not reported. Since no pharmacokinetics data for 1,4-dioxane in mice were 

available, mouse metabolic rate constants were allometrically scaled from rat and human values. 

3.5.2.3. Fisher et al. 

A PBPK model was developed by Fisher et al. (1997, 194390) to simulate a variety of 

volatile organic compounds (VOCs, including 1,4-dioxane) in lactating humans. This model was 

similar in structure to those of Leung and Paustenbach (1990, 062932) and Reitz et al. (1990, 

094806) with the addition of elimination of 1,4-dioxane to breast milk. Experimental 

measurements were made for blood:air and milk:air partition coefficients. Other partition 

coefficient values were taken from Reitz et al. (1990, 094806). The model was not optimized, 

nor was performance tested against experimental exposure data. Thus, the ability of the model to 

simulate 1,4-dioxane exposure data is unknown. 

3.5.3. Implementation of Published PBPK Models for 1,4-Dioxane 

As previously described, several pharmacokinetic models have been developed to predict 

the absorption, distribution, metabolism, and elimination of 1,4-dioxane in rats and humans. 

Single compartment, empirical models for rats (Young et al., 1978, 062955; Young et al., 1978, 

625640) and humans (Young et al., 1977, 062956) were developed to predict blood levels of 

1,4-dioxane and urine levels of the primary metabolite, HEAA. PBPK models that describe the 

kinetics of 1,4-dioxane using biologically realistic flow rates, tissue volumes, enzyme affinities, 

metabolic processes, and elimination behaviors were also developed (Fisher et al., 1997, 194390; 

Leung and Paustenbach, 1990, 062932; Reitz et al., 1990, 094806; Sweeney et al., 2008, 

195085). 

In developing updated toxicity values for 1,4-dioxane the available PBPK models were 

evaluated for their ability to predict observations made in experimental studies of rat and human 

exposures to 1,4-dioxane (Appendix B). The Reitz et al. (1990, 094806) and Leung and 

Paustenbach (1990, 062932) PBPK models were both developed from a PBPK model of styrene 

(Ramsey and Andersen, 1984, 063020), with the exception of minor differences in the use of 

partition coefficients and biological parameters. The model code for Leung and Paustenbach 

(1990, 062932) was unavailable in contrast to Reitz et al. (1990, 094806). The model of Reitz 

et al. (1990, 094806) was identified for further consideration to assist in the derivation of toxicity 

values, and the Sweeney et al. (2008, 195085) PBPK model was also evaluated. 

 18 
 

The biological plausibility of parameter values in the Reitz et al. (1990, 094806) human 

model were examined. The model published by Reitz et al. (1990, 094806) was able to predict 

the only available human inhalation data (50 ppm 1,4-dioxane for 6 hours; Young et al., (1977, 

062956)) by increasing (i.e., approximately doubling) the parameter values for human alveolar 

ventilation (30 L/hour/kg0.74), cardiac output (30 L/hour/kg0.74), and the blood:air partition 

coefficient (3,650) above the measured values of 13 L/minute/kg0.74 (Brown et al., 1997, 

020304), 14 L/hour/kg0.74 (Brown et al., 1997, 020304), and 1,825 (Leung and Paustenbach, 

1990, 062932), respectively. Furthermore, Reitz et al. (1990, 094806) replaced the measured 

value for the slowly perfused tissue:air partition coefficient (i.e., muscle—value not reported in 

manuscript) with the measured liver value (1,557) to improve the fit. Analysis of the Young 

et al. (1977, 062956) human data suggested that the apparent volume of distribution (Vd) for 

1,4-dioxane was approximately 10-fold higher in rats than humans, presumably due to species 

differences in tissue partitioning or other process not represented in the model. Based upon these 

observations, several model parameters (e.g., metabolism/elimination parameters) were recalibrated using biologically plausible values for flow rates and tissue:air partition coefficients. 

Appendix B describes all activities that were conducted in the evaluation of the empirical 

models and the re-calibration and evaluation of the Reitz et al. (1990, 094806) PBPK model to 

determine the adequacy and preference for the potential use of the models. 

The evaluation consisted of implementation of the Young et al. (1977, 062956; 1978, 

062955; 1978, 625640) empirical rat and human models using the acslXtreme simulation 

software, re-calibration of the Reitz et al. (1990, 094806) human PBPK model, and evaluation of 

the model parameters published by Sweeney et al. (2008, 195085). Using the model descriptions 

and equations given in Young et al. (1977, 062956; 1978, 062955; 1978, 625640), model code 

was developed for the empirical models and executed, simulating the reported experimental 

conditions. The model output was then compared with the model output reported in Young et al. 

(1977, 062956; 1978, 062955; 1978, 625640). 

The PBPK model of Reitz et al. (1990, 094806) was re-calibrated using measured values 

for cardiac and alveolar flow rates and tissue:air partition coefficients. The predictions of blood 

and urine levels of 1,4-dioxane and HEAA, respectively, from the re-calibrated model were 

compared with the empirical model predictions of the same dosimeters to determine whether the 

re-calibrated PBPK model could perform similarly to the empirical model. As part of the PBPK 

model evaluation, EPA performed a sensitivity analysis to identify the model parameters having 

the greatest influence on the primary dosimeter of interest, the blood level of 1,4-dioxane. 

Variability data for the experimental measurements of the tissue:air partition coefficients were 

incorporated to determine a range of model outputs bounded by biologically plausible values for 

these parameters. Model parameters from Sweeney et al. (2008, 195085) were also tested to 

evaluate the ability of the PBPK model to predict human data following exposure to 1,4-dioxane. 

 19 
 

The rat and human empirical models of Young et al. (1977, 062956; 1978, 062955; 1978, 

625640) were successfully implemented in acslXtreme and perform identically to the models 

reported in the published papers (Figures B-3 through B-7), with the exception of the lower 

predicted HEAA concentrations and early appearance of the peak HEAA levels in rat urine. The 

early appearance of peak HEAA levels cannot presently be explained, but may result from 

manipulations of kme or other parameters by Young et al. (1978, 062955; 1978, 625640) that 

were not reported. The lower predictions of HEAA levels are likely due to reliance on a standard 

urine volume production rate in the absence of measured (but unreported) urine volumes. While 

the human urinary HEAA predictions were lower than observations, this is due to parameter 

fitting of Young et al. (1977, 062956). No model output was published in Young et al. (1977, 

062956) for comparison. The empirical models were modified to allow for user-defined 

inhalation exposure levels. However, no modifications were made to model oral exposures as 

adequate data to parameterize such modifications do not exist for rats or humans. 

Several procedures were applied to the Reitz et al. (1990, 094806) human PBPK model to 

determine if an adequate fit of the model to the empirical model output or experimental 

observations could be attained using biologically plausible values for the model parameters. The 

re-calibrated model predictions for blood 1,4-dioxane levels do not come within 10-fold of the 

experimental values using measured tissue:air partition coefficients from Leung and Paustenbach 

(1990, 062932) or Sweeney et al. (2008, 195085) (Figures B-8 and B-9). The utilization of a 

slowly perfused tissue:air partition coefficient 10-fold lower than measured values produces 

exposure-phase predictions that are much closer to observations, but does not replicate the 

elimination kinetics (Figure B-10). Recalibration of the model with upper bounds on the 

tissue:air partition coefficients results in predictions that are still six- to sevenfold lower than 

empirical model prediction or observations (Figures B-12 and B-13). Exploration of the model 

space using an assumption of zero-order metabolism (valid for the 50 ppm inhalation exposure) 

showed that an adequate fit to the exposure and elimination data can be achieved only when 

unrealistically low values are assumed for the slowly perfused tissue:air partition coefficient 

(Figure B-16). Artificially low values for the other tissue:air partition coefficients are not 

expected to improve the model fit, as these parameters are shown in the sensitivity analysis to 

exert less influence on blood 1,4-dioxane than VmaxC and Km. In the absence of actual 

measurements for the human slowly perfused tissue:air partition coefficient, high uncertainty 

exists for this model parameter value. Differences in the ability of rat and human blood to bind 

1,4-dioxane may contribute to the difference in Vd. However, this is expected to be evident in 

very different values for rat and human blood:air partition coefficients, which is not the case 

(Table B-1). Therefore, some other, as yet unknown, modification to model structure may be 

necessary. 

Similarly, Sweeney et al. (2008, 195085) also evaluated the available PBPK models 

(Leung and Paustenbach, 1990, 062932; Reitz et al., 1990, 094806) for 1,4-dioxane. To address 

 20 
 

uncertainties and deficiencies in these models, the investigators conducted studies to fill data 

gaps and reduce uncertainties pertaining to the pharmacokinetics of 1,4-dioxane and HEAA in 

rats, mice, and humans. The following studies were performed: 

• Partition coefficients, including measurements for mouse blood and tissues (liver, kidney, 

fat, and muscle) and confirmatory measurements for human blood and rat blood and 

muscle. 

• Blood time course measurements in mice conducted for gavage administration of 

nominal single doses (20, 200, or 2,000 mg/kg) of 1,4-dioxane administered in water. 

• Metabolic rate constants for rat, mouse, and human liver based on incubations of 

1,4-dioxane with rat, mouse, and human hepatocytes and measurement of HEAA. 

The studies conducted by Sweeney et al. (2008, 195085) resulted in partition coefficients 

that were consistent with previously measured values and those used in the Leung and 

Paustenbach (1990, 062932) model. Of noteworthy significance, the laboratory results of 

Sweeney et al. (2008, 195085) did not confirm the human blood:air partition coefficient Reitz 

et al. (1990, 094806) reported. Furthermore, Sweeney et al. (2008, 195085) estimated metabolic 

rate constants (VmaxC and Km) within the range used in the previous models (Leung and 

Paustenbach, 1990, 062932; Reitz et al., 1990, 094806). Overall, the Sweeney et al. (2008, 

195085) model utilized more rodent in vivo and in vitro data in model parameterization and 

refinement; however, the model was still unable to adequately predict the human blood data from 

Young et al. (1977, 062956). 

Updated PBPK models were developed based on these new data and data from previous 

kinetic studies in rats, workers, and human volunteers reported by Young et al. (1976, 062953; 

1977, 062956; 1978, 062955; 1978, 625640). The optimized rate of metabolism for the mouse 

was significantly higher than the value previously estimated. The optimized rat kinetic 

parameters were similar to those in the 1990 models. Of the two available human studies 

(Young et al., 1976, 062953; 1977, 062956), model predictions were consistent with one study, 

but did not fit the second as well. 

3.6. RAT NASAL EXPOSURE VIA DRINKING WATER 

Sweeney et al. (2008, 195085) conducted a rat nasal exposure study to explore the 

potential for direct contact of nasal tissues with 1,4-dioxane-containing drinking water under 

bioassay conditions. Two groups of male Sprague Dawley rats (5/group) received drinking 

water in 45-mL drinking water bottles containing a fluorescent dye mixture (Cell Tracker 

Red/FluoSpheres). The drinking water for one of these two groups also contained 0.5% 

1,4-dioxane, a concentration within the range used in chronic toxicity studies. A third group of 

five rats received tap water alone (controls). Water was provided to the rats overnight. The next 

morning, the water bottles were weighed to estimate the amounts of water consumed. Rats were 

 21 
 

sacrificed and heads were split along the midline for evaluation by fluorescence microscopy. 

One additional rat was dosed twice by gavage with 2 mL of drinking water containing 

fluorescent dye (the second dose was 30 minutes after the first dose; total of 4 mL administered) 

and sacrificed 5 hours later to evaluate the potential for systemic delivery of fluorescent dye to 

the nasal tissues. 

The presence of the fluorescent dye mixture had no measurable impact on water 

consumption; however, 0.5% 1,4-dioxane reduced water consumption by an average of 62% of 

controls following a single, overnight exposure. Fluorescent dye was detected in the oral cavity 

and nasal airways of each animal exposed to the Cell Tracker Red/FluoSpheres mixture in their 

drinking water, including numerous areas of the anterior third of the nose along the nasal 

vestibule, maxillary turbinates, and dorsal nasoturbinates. Fluorescent dye was occasionally 

detected in the ethmoid turbinate region and nasopharynx. 1,4-Dioxane had no effect on the 

detection of the dye. Little or no fluorescence at the wavelength associated with the dye mixture 

was detected in control animals or in the single animal that received the dye mixture by oral 

gavage. The investigators concluded that the findings indicate rat nasal tissues are exposed by 

direct contact with drinking water under bioassay conditions. 

 22 
 

4. HAZARD IDENTIFICATION 

4.1. STUDIES IN HUMANS – EPIDEMIOLOGY, CASE REPORTS, CLINICAL 

CONTROLS 

Case reports of acute occupational poisoning with 1,4-dioxane indicated that exposure to 

high concentrations resulted in liver, kidney, and central nervous system (CNS) toxicity (Barber, 

1934, 062913; Johnstone, 1959, 062927). Barber (1934, 062913) described four fatal cases of 

hemorrhagic nephritis and centrilobular necrosis of the liver attributed to acute inhalation 

exposure to high (unspecified) concentrations of 1,4-dioxane. Death occurred within 5–8 days of 

the onset of illness. Autopsy findings suggested that the kidney toxicity may have been 

responsible for lethality, while the liver effects may have been compatible with recovery. 

Jaundice was not observed in subjects and fatty change was not apparent in the liver. Johnstone 

(1959, 062927) presented the fatal case of one worker exposed to high concentrations of 

1,4-dioxane through both inhalation and dermal exposure for a 1 week exposure duration. 

Measured air concentrations in the work environment of this subject were 208–650 ppm, with a 

mean value of 470 ppm. Clinical signs that were observed following hospital admission 

included severe epigastric pain, renal failure, headache, elevation in blood pressure, agitation and 

restlessness, and coma. Autopsy findings revealed significant changes in the liver, kidney, and 

brain. These included centrilobular necrosis of the liver and hemorrhagic necrosis of the kidney 

cortex. Perivascular widening was observed in the brain with small foci of demyelination in 

several regions (e.g., cortex, basal nuclei). It was suggested that these neurological changes may 

have been secondary to anoxia and cerebral edema. 

Several studies examined the effects of acute inhalation exposure in volunteers. In a 

study performed at the Pittsburgh Experimental Station of the U.S. Bureau of Mines, eye 

irritation and a burning sensation in the nose and throat were reported in five men exposed to 

5,500 ppm of 1,4-dioxane vapor for 1 minute (Yant et al., 1930, 062952). Slight vertigo was 

also reported by three of these men. Exposure to 1,600 ppm of 1,4-dioxane vapor for 10 minutes 

resulted in similar symptoms with a reduced intensity of effect. In a study conducted by the 

Government Experimental Establishment at Proton, England (Fairley et al., 1934, 062919), four 

men were exposed to 1,000 ppm of 1,4-dioxane for 5 minutes. Odor was detected immediately 

and one volunteer noted a constriction in the throat. Exposure of six volunteers to 2,000 ppm for 

3 minutes resulted in no symptoms of discomfort. Wirth and Klimmer (1936, 196105), of the 

Institute of Pharmacology, University of Wurzburg, reported slight mucous membrane irritation 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 23 
 

in the nose and throat of several human subjects exposed to concentrations greater than 280 ppm 

for several minutes. Exposure to approximately 1,400 ppm for several minutes caused a 

prickling sensation in the nose and a dry and scratchy throat. Silverman et al. (1946, 063013) 

exposed 12 male and 12 female subjects to varying air concentrations of 1,4-dioxane for 

15 minutes. A 200 ppm concentration was reported to be tolerable, while a concentration of 

300 ppm caused irritation to the eyes, nose, and throat. The study conducted by Silverman et al. 

(1946, 063013) was conducted by the Department of Industrial Hygiene, Harvard School of 

Public Health, and was sponsored and supported by a grant from the Shell Development 

Company. These volunteer studies published in the 1930s and 1940s (Fairley et al., 1934, 

062919; Silverman et al., 1946, 063013; Wirth and Klimmer, 1936, 196105; Yant et al., 1930, 

062952) did not provide information on the human subjects research ethics procedures 

undertaken in these studies; however, there is no evidence that the conduct of the research was 

fundamentally unethical or significantly deficient relative to the ethical standards prevailing at 

the time the research was conducted. 

Young et al. (1977, 062956) exposed four healthy adult male volunteers to a 50-ppm 

concentration of 1,4-dioxane for 6 hours. The investigators reported that the protocol of this 

study was approved by a seven-member Human Research Review Committee of the Dow 

Chemical Company and was followed rigorously. Perception of the odor of 1,4-dioxane 

appeared to diminish over time, with two of the four subjects reporting inability to detect the 

odor at the end of the exposure period. Eye irritation was the only clinical sign reported in this 

study. The pharmacokinetics and metabolism of 1,4-dioxane in humans were also evaluated in 

this study (see Section 3.3). Clinical findings were not reported in four workers exposed in the 

workplace to a TWA concentration of 1.6 ppm for 7.5 hours (Young et al., 1976, 062953). 

Ernstgård et al. (2006, 195034) examined the acute effects of 1,4-dioxane vapor in male 

and female volunteers. The study protocol was approved by the Regional Ethics Review Board 

in Stockholm, and performed following informed consent and according to the Helsinki 

declaration. In a screening study by these investigators, no self-reported symptoms (based on a 

visual analogue scale (VAS) that included ratings for discomfort in eyes, nose, and throat, 

breathing difficulty, headache, fatigue, nausea, dizziness, or feeling of intoxication) were 

observed at concentrations up to 20 ppm; this concentration was selected as a tentative noobserved-adverse-effect-level (NOAEL) in the main study. In the main study, six male and six 

female healthy volunteers were exposed to 0 or 20 ppm 1,4-dioxane, at rest, for 2 hours. This 

exposure did not significantly affect symptom VAS ratings, blink frequency, pulmonary function 

or nasal swelling (measured before and at 0 and 3 hours after exposure), or inflammatory 

markers in the plasma (C-reactive protein and interleukin-6) of the volunteers. Only ratings for 

“solvent smell” were significantly increased during exposure. 

Only two well documented epidemiology studies were available for occupational workers 

exposed to 1,4-dioxane (Buffler et al., 1978, 062914; Thiess et al., 1976, 062943). These studies 

 24 
 

did not provide evidence of effects in humans; however, the cohort size and number of reported 

cases were small. 

4.1.1. Thiess et al. 

A cross-sectional survey was conducted by Thiess et al. (1976, 062943) in German 

workers exposed to 1,4-dioxane. The study evaluated health effects in 74 workers, including 

24 who were still actively employed in 1,4-dioxane production at the time of the investigation, 

23 previously exposed workers who were still employed by the manufacturer, and 27 retired or 

deceased workers. The actively employed workers were between 32 and 62 years of age and had 

been employed in 1,4-dioxane production for 5–41 years. Former workers (age range not given) 

had been exposed to 1,4-dioxane for 3–38 years and retirees (age range not given) had been 

exposed for 12–41 years. Air concentrations in the plant at the time of the study were 

0.06–0.69 ppm. A simulation of previous exposure conditions (prior to 1969) resulted in air 

measurements between 0.06 and 7.2 ppm. 

Active and previously employed workers underwent a thorough clinical examination and 

X-ray, and hematological and serum biochemistry parameters were evaluated. The examination 

did not indicate pathological findings for any of the workers and no indication of malignant 

disease was noted. Hematology results were generally normal. Serum transaminase levels were 

elevated in 16 of the 47 workers studied; however, this finding was consistent with chronic 

consumption of more than 80 g of alcohol per day, as reported for these workers. No liver 

enlargement or jaundice was found. Renal function tests and urinalysis were normal in exposed 

workers. Medical records of the 27 retired workers (15 living at the time of the study) were 

reviewed. No symptoms of liver or kidney disease were reported and no cancer was detected. 

Medical reasons for retirement did not appear related to 1,4-dioxane exposure (e.g., emphysema, 

arthritis). 

Chromosome analysis was performed on six actively employed workers and six control 

persons (not characterized). Lymphocyte cultures were prepared and chromosomal aberrations 

were evaluated. No differences were noted in the percent of cells with gaps or other 

chromosome aberrations. Mortality statistics were calculated for 74 workers of different ages 

and varying exposure periods. The proportional contribution of each of the exposed workers to 

the total time of observation was calculated as the sum of man-years per 10-year age group. 

Each person contributed one man-year per calendar year to the specific age group in which he 

was included at the time. The expected number of deaths for this population was calculated from 

the age-specific mortality statistics for the German Federal Republic for the years 1970–1973. 

From the total of 1,840.5 person-years, 14.5 deaths were expected; however, only 12 deaths were 

observed in exposed workers between 1964 and 1974. Two cases of cancer were reported, 

including one case of lamellar epithelial carcinoma and one case of myelofibrosis leukemia. 

These cancers were not considered to be the cause of death in these cases and other severe 

 25 
 

illnesses were present. Standardized mortality ratios (SMRs) for cancer did not significantly 

differ from the control population (SMR for overall population = 0.83; SMR for 65–75-year-old 

men = 1.61; confidence intervals (CIs) were not provided). 

4.1.2. Buffler et al. 

Buffler et al. (1978, 062914) conducted a mortality study on workers exposed to 

1,4-dioxane at a chemical manufacturing facility in Texas. 1,4-Dioxane exposure was known to 

occur in a manufacturing area and in a processing unit located 5 miles from the manufacturing 

plant. Employees who worked between April 1, 1954, and June 30, 1975, were separated into 

two cohorts based on at least 1 month of exposure in either the manufacturing plant 

(100 workers) or the processing area (65 workers). Company records and follow-up techniques 

were used to compile information on name, date of birth, gender, ethnicity, job assignment and 

duration, and employment status at the time of the study. Date and cause of death were obtained 

from copies of death certificates and autopsy reports (if available). Exposure levels for each job 

category were estimated using the 1974 Threshold Limit Value for 1,4-dioxane (i.e., 50 ppm) 

and information from area and personal monitoring. Exposure levels were classified as low 

(<25 ppm), intermediate (50–75 ppm), and high (>75 ppm). Monitoring was not conducted prior 

to 1968 in the manufacturing areas or prior to 1974 in the processing area; however, the study 

authors assumed that exposures would be comparable, considering that little change had been 

made to the physical plant or the manufacturing process during that time. Exposure to 

1,4-dioxane was estimated to be below 25 ppm for all individuals in both cohorts. 

Manufacturing area workers were exposed to several other additional chemicals and processing 

area workers were exposed to vinyl chloride. 

Seven deaths were identified in the manufacturing cohort and five deaths were noted for 

the processing cohort. The average exposure duration was not greater for those workers who 

died, as compared to those still living at the time of the study. Cancer was the underlying cause 

of death for two cases from the manufacturing area (carcinoma of the stomach, alveolar cell 

carcinoma) and one case from the processing area (malignant mediastinal tumor). The workers 

from the manufacturing area were exposed for 28 or 38 months and both had a positive smoking 

history (>1 pack/day). Smoking history was not available for processing area workers. The 

single case of cancer in this area occurred in a 21-year-old worker exposed to 1,4-dioxane for 

1 year. The mortality data for both industrial cohorts were compared to age-race-sex specific 

death rates for Texas (1960–1969). Person-years of observation contributed by workers were 

determined over five age ranges with each worker contributing one person-year for each year of 

observation in a specific age group. The expected number of deaths was determined by applying 

the Texas 1960–1969 death rate statistics to the number of person years calculated for each 

cohort. The observed and expected number of deaths for overall mortality (i.e., all causes) was 

comparable for both the manufacturing area (7 observed versus 4.9 expected) and the processing 

 26 
 

area (5 observed versus 4.9 expected). No significant excess in cancer-related deaths was 

identified for both areas of the facility combined (3 observed versus 1.7 expected). A separate 

analysis was performed to evaluate mortality in manufacturing area workers exposed to 

1,4-dioxane for more than 2 years. Six deaths occurred in this group as compared to 

4.1 expected deaths. The use of a conditional Poisson distribution indicated no apparent excess 

in mortality or death due to malignant neoplasms in this study. It is important to note that the 

cohorts evaluated were limited in size. In addition, the mean exposure duration was less than 

5 years (<2 years for 43% of workers) and the latency period for evaluation was less than 

10 years for 59% of workers. The study authors recommended a follow-up investigation to 

allow for a longer latency period; however, no follow-up study of these workers has been 

published. 

4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS - ORAL AND INHALATION 

The majority of the subchronic and chronic studies conducted for 1,4-dioxane were oral 

drinking water studies. Longer-term inhalation studies consisted of only one subchronic study 

(Fairley et al., 1934, 062919) and one chronic study (Torkelson et al., 1974, 094807). These 

studies were not sufficient to characterize the inhalation risks of 1,4-dioxane (see Section 4.2.2.). 

4.2.1. Oral Toxicity 

4.2.1.1. Subchronic Oral Toxicity 

Six rats and six mice (unspecified strains) were given drinking water containing 1.25% 

1,4-dioxane for up to 67 days (Fairley et al., 1934, 062919). Using reference BWs and drinking 

water ingestion rates for rats and mice (U.S. EPA, 1988, 064560), it can be estimated that these 

rats and mice received doses of approximately 1,900 and 3,300 mg/kg-day, respectively. Gross 

pathology and histopathology were evaluated in all animals. Five of the six rats in the study died 

or were sacrificed in extremis prior to day 34 of the study. Mortality was lower in mice, with 

five of six mice surviving up to 60 days. Kidney enlargement was noted in 5/6 rats and 2/5 mice. 

Renal cortical degeneration was observed in all rats and 3/6 mice. Large areas of necrosis were 

observed in the cortex, while cell degeneration in the medulla was slight or absent. Tubular casts 

were observed and vascular congestion and hemorrhage were present throughout the kidney. 

Hepatocellular degeneration with vascular congestion was also noted in five rats and three mice. 

For this assessment, EPA identified the tested doses of 1,900 mg/kg-day in rats and 3,300 mg/kgday in mice as the lowest-observed-adverse-effect-levels (LOAELs) for liver and kidney 

degeneration in this study. 

4.2.1.1.1. Stoner et al. 1,4-Dioxane was evaluated by Stoner et al. (1986, 064678)for its ability 

to induce lung adenoma formation in A/J mice. Six- to 8-week-old male and female A/J mice 

 27 
 

(16/sex/group) were given 1,4-dioxane by gavage or i.p. injection, 3 times/week for 8 weeks. 

Total cumulative dose levels were given as 24,000 mg/kg (oral), and 4,800, 12,000, or 

24,000 mg/kg (i.p.). Average daily dose estimates were calculated to be 430 mg/kg-day (oral), 

and 86, 210, or 430 mg/kg-day (i.p.) by assuming an exposure duration of 56 days. The authors 

indicated that i.p. doses represent the maximum tolerated dose (MTD), 0.5 times the MTD, and 

0.2 times the MTD. Mice were killed 24 weeks after initiation of the bioassay, and lungs, liver, 

kidney, spleen, intestines, stomach, thymus, salivary, and endocrine glands were examined for 

gross lesions. Histopathology examination was performed if gross lesions were detected. 

1,4-Dioxane did not induce lung tumors in male or female A/J mice in this study. 

4.2.1.1.2. Stott et al. In the Stott et al. (1981, 063021) study, male Sprague Dawley rats (4–

6/group) were given average doses of 0, 10, or 1,000 mg/kg-day 1,4-dioxane (>99% pure) in 

their drinking water, 7 days/week for 11 weeks. It should be noted that the methods description 

in this report stated that the high dose was 100 mg/kg-day, while the abstract, results, and 

discussion sections indicated that the high dose was 1,000 mg/kg-day. Rats were implanted with 

a [6-3H]thymidine loaded osmotic pump 7 days prior to sacrifice. Animals were sacrificed by 

cervical dislocation and livers were removed, weighed, and prepared for histopathology 

evaluation. [3H]-Thymidine incorporation was measured by liquid scintillation spectroscopy. 

An increase in the liver to BW ratio was observed in rats from the high dose group 

(assumed to be 1,000 mg/kg-day). Histopathological alterations, characterized as minimal 

centrilobular swelling, were also seen in rats from this dose group (incidence values were not 

reported). Hepatic DNA synthesis, measured by [3

H]-thymidine incorporation, was increased 

1.5-fold in high-dose rats. No changes relative to control were observed for rats exposed to 

10 mg/kg-day. EPA found a NOAEL value of 10 mg/kg-day and a LOAEL value of 

1,000 mg/kg-day for this study based on histopathological changes in the liver. 

Stott et al. (1981, 063021) also performed several acute experiments designed to evaluate 

potential mechanisms for the carcinogenicity of 1,4-dioxane. These experiments are discussed 

separately in Section 4.5.2 (Mechanistic Studies). 

4.2.1.1.3. Kano et al. In the Kano et al. (2008, 196245) study, groups of 6-week-old 

F344/DuCrj rats (10/sex/group) and Crj:BDF1 mice (10/sex/group) were administered 

1,4-dioxane (>99% pure) in the drinking water for 13 weeks. The animals were observed daily 

for clinical signs of toxicity. Food consumption and BWs were measured once per week and 

water consumption was measured twice weekly. Food and water were available ad libitum. The 

concentrations of 1,4-dioxane in the water for rats and mice were 0, 640, 1,600, 4,000, 10,000, or 

25,000 ppm. The investigators used data from water consumption and BW changes to calculate 

a daily intake of 1,4-dioxane by the male and female animals. Thus, male rats received doses of 

approximately 0, 52, 126, 274, 657, and 1,554 mg 1,4-dioxane/kg-day and female rats received 

 28 
 

0, 83, 185, 427, 756, and 1,614 mg/kg-day. Male mice received 0, 86, 231, 585, 882, or 

1,570 mg/kg-day and female mice received 0, 170, 387, 898, 1,620, or 2,669 mg/kg-day. 

No information was provided as to when the blood and urine samples were collected. 

Hematology analysis included red blood cell (RBC) count, hemoglobin, hematocrit, mean 

corpuscular volume (MCV), platelet count, white blood cell (WBC) count, and differential 

WBCs. Serum biochemistry included total protein, albumin, bilirubin, glucose, cholesterol, 

triglyceride (rat only), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate 

dehydrogenase (LDH), leucine aminopeptidase (LAP), alkaline phosphatase (ALP), creatinine 

phosphokinase (CPK) (rat only), urea nitrogen, creatinine (rat only), sodium, potassium, 

chloride, calcium (rat only), and inorganic phosphorous (rat only). Urinalysis parameters were 

pH, protein, glucose, ketone body, bilirubin (rat only), occult blood, and urobilinogen. Organ 

weights (brain, lung, liver, spleen, heart, adrenal, testis, ovary, and thymus) were measured, and 

gross necropsy and histopathologic examination of tissues and organs were performed on all 

animals (skin, nasal cavity, trachea, lungs, bone marrow, lymph nodes, thymus, spleen, heart, 

tongue, salivary glands, esophagus, stomach, small and large intestine, liver, pancreas, kidney, 

urinary bladder, pituitary thyroid adrenal, testes, epididymis, seminal vesicle, prostate, ovary, 

uterus, vagina, mammary gland, brain, spinal cord, sciatic nerve, eye, Harderian gland, muscle, 

bone, and parathyroid). Dunnett’s test and χ

2

 test were used to assess the statistical significance 

of changes in continuous and discrete variables, respectively. 

Clinical signs of toxicity in rats were not discussed in the study report. One female rat in 

the high dose group (1,614 mg/kg-day) group died, but cause and time of death were not 

specified. Final BWs were reduced at the two highest dose levels in females (12 and 21%) and 

males (7 and 21%), respectively. Food consumption was reduced 13% in females at 

1,614 mg/kg-day and 8% in 1,554 mg/kg-day males. A dose-related decrease in water 

consumption was observed in male rats starting at 52 mg/kg-day (15%) and in females starting at 

185 mg/kg-day (12%). Increases in RBCs, hemoglobin, hematocrit, and neutrophils, and a 

decrease in lymphocytes were observed in males at 1554 mg/kg-day. In females, MCV was 

decreased at doses ≥ 756 mg/kg and platelets were decreased at 1,614 mg/kg-day. With the 

exception of the 30% increase in neutrophils in high-dose male rats, hematological changes were 

within 2–15% of control values. Total serum protein and albumin were significantly decreased 

in males at doses ≥ 274 mg/kg-day and in females at doses ≥ 427 mg/kg-day. Additional 

changes in high-dose male and female rats included decreases in glucose, total cholesterol, 

triglycerides, and sodium (and calcium in females), and increases in ALT (males only), AST, 

ALP, and LAP. Serum biochemistry parameters in treated rats did not differ more than twofold 

from control values. Urine pH was decreased in males at ≥ 274 mg/kg-day and in females at 

≥ 756 mg/kg-day. 

Kidney weights were increased in females at ≥185 mg/kg-day with a maximum increase 

of 15% and 44% at 1,614 mg/kg-day for absolute and relative kidney weight, respectively. No 

 29 
 

organ weight changes were noted in male rats. Histopathology findings in rats that were related 

to exposure included nuclear enlargement of the respiratory epithelium, nuclear enlargement of 

the olfactory epithelium, nuclear enlargement of the tracheal epithelium, hepatocyte swelling of 

the centrilobular area of the liver, vacuolar changes in the liver, granular changes in the liver, 

single cell necrosis in the liver, nuclear enlargement of the proximal tubule of the kidneys, 

hydropic changes in the proximal tubule of the kidneys, and vacuolar changes in the brain. The 

incidence data for histopathological lesions in rats are presented in Table 4-1. The effects that 

occurred at the lowest doses were nuclear enlargement of the respiratory epithelium in the nasal 

cavity and hepatocyte swelling in the central area of the liver in male rats. Based on these 

histopathological findings the study authors identified the LOAEL as 126 mg/kg-day and the 

NOAEL as 52 mg/kg-day. 

 30 
 

Table 4-1. Incidence of histopathological lesions in F344/DuCrj rats 

exposed to 1,4-dioxane in drinking water for 13 weeks 

Male dose (mg/kg-day)a

Effect 0 52 126 274 657 1,554 

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 9/10b 10/10b 9/10b 10/10b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 10/10b 9/10b 10/10b

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 10/10b 10/10b 10/10b

Hepatocyte swelling 0/10 0/10 9/10b 10/10b 10/10b 10/10b

Vacuolic change; liver 0/10 0/10 0/10 0/10 10/10b 10/10b

Granular change; liver 0/10 0/10 0/10 5/10c 2/10 10/10b

Single cell necrosis; liver 0/10 0/10 0/10 5/10c 2/10 10/10b

Nuclear enlargement; renal proximal tubule 0/10 0/10 0/10 1/10 5/10c 9/10b

Hydropic change; renal proximal tubule 0/10 0/10 0/10 0/10 0/10 7/10b

Vacuolic change; brain 0/10 0/10 0/10 0/10 0/10 10/10b

Female dose (mg/kg-day)a

0 83 185 427 756 1,614 

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 5/10c 10/10b 10/10b 8/9b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 9/10b 10/10b 8/9b

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 9/10b 10/10b 9/9b

Hepatocyte swelling 0/10 0/10 0/10 0/10 9/10b 9/9b

Vacuolic change; liver 0/10 0/10 0/10 0/10 0/10 9/9b

Granular change; liver 2/10 0/10 1/10 5/10c 5/10c 8/9b

Single cell necrosis; liver 2/10 0/10 1/10 5/10 5/10 8/9b

Nuclear enlargement; proximal tubule 0/10 0/10 0/10 0/10 8/10b 9/9b

Hydropic change; proximal tubule 0/10 0/10 0/10 0/10 0/10 5/9c

Vacuolic change; brain 0/10 0/10 0/10 0/10 0/10 9/9b

a

Data are presented for sacrificed animals. 

b

p ≤ 0.01 by χ

2

 test. c

p ≤ 0.05. 

Source: Kano et al. (2008, 196245) 

Clinical signs of toxicity in mice were not discussed in the study report One male mouse 

in the high-dose group (1,570 mg/kg-day) died, but no information was provided regarding cause 

or time of death. Final BWs were decreased 29% in male mice at 1,570 mg/kg-day, but changed 

less than 10% relative to controls in the other male dose groups and in female mice. Food 

consumption was not significantly reduced in any exposure group. Water consumption was 

reduced 14–18% in male mice exposed to 86, 231, or 585 mg/kg-day. Water consumption was 

further decreased by 48 and 70% in male mice exposed to 882 and 1,570 mg/kg-day, 

respectively. Water consumption was also decreased 31 and 57% in female mice treated with 

1,620 and 2,669 mg/kg-day, respectively. An increase in MCV was observed in the two highest 

dose groups in both male (882 and 1,570 mg/kg-day) and female mice (1,620 and 

2,669 mg/kg-day). Increases in RBCs, hemoglobin, and hematocrit were also observed in high 

 31 
 

dose males (1,570 mg/kg-day). Hematological changes were within 2–15% of control values. 

Serum biochemistry changes in exposed mice included decreased total protein (at 

1,570 mg/kg-day in males, ≥1,620 mg/kg-day in females), decreased glucose (at 

1,570 mg/kg-day in males, ≥1,620 mg/kg-day in females), decreased albumin (at 

1,570 mg/kg-day in males, 2,669 mg/ kg-day in females), decreased total cholesterol 

(≥ 585 mg/kg-day in males, ≥1,620 mg/kg-day in females), increased serum ALT (at 

1,570 mg/kg-day in males, ≥ 620 mg/kg-day in females), increased AST (at 1,570 mg/kg-day in 

males, 2,669 mg/kg-day in females), increased ALP (≥ 585 mg/kg-day in males, 2,669 mg/kgday in females), and increased LDH (in females only at doses ≥ 1,620 mg/kg-day). With the 

exception of a threefold increase in ALT in male and female mice, serum biochemistry 

parameters in treated rats did not differ more than twofold from control values. Urinary pH was 

decreased in males at ≥ 882 mg/kg-day and in females at ≥ 1,620 mg/kg-day. 

Absolute and relative lung weights were increased in males at 1,570 mg/kg-day and in 

females at 1,620 and 2,669 mg/kg-day. Absolute kidney weights were also increased in females 

at 1,620 and 2,669 mg/kg-day and relative kidney weight was elevated at 2,669 mg/kg-day. 

Histopathology findings in mice that were related to exposure included nuclear enlargement of 

the respiratory epithelium, nuclear enlargement of the olfactory epithelium, eosinophilic change 

in the olfactory epithelium, vacuolic change in the olfactory nerve, nuclear enlargement of the 

tracheal epithelium, accumulation of foamy cells in the lung and bronchi, nuclear enlargement 

and degeneration of the bronchial epithelium, hepatocyte swelling of the centrilobular area of the 

liver, and single cell necrosis in the liver. The incidence data for histopathological lesions in 

mice are presented in Table 4-2. Based on the changes in the bronchial epithelium in female 

mice, the authors identified the dose level of 387 mg/kg-day as the LOAEL for mice; the 

NOAEL was 170 mg/kg-day (Kano et al., 2008, 196245). 

 32 
 

Table 4-2. Incidence of histopathological lesions in Crj:BDF1 mice 

exposed to 1,4-dioxane in drinking water for 13 weeks 

Male dose (mg/kg-day)a

Effect 0 86 231 585 882 1,570 

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 0/10 2/10 5/10b 0/9 

Eosinophilic change; nasal respiratory epithelium 0/10 0/10 0/10 0/10 0/10 5/9b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 9/10c 10/10c 9/9c

Eosinophilic change; nasal olfactory epithelium 0/10 0/10 0/10 0/10 0/10 6/9c

Vacuolic change; olfactory nerve 0/10 0/10 0/10 0/10 0/10 9/9c

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 7/10c 9/10c 9/9c

Accumulation of foamy cells; lung/bronchi 0/10 0/10 0/10 0/10 0/10 6/9c

Nuclear enlargement; bronchial epithelium 0/10 0/10 0/10 9/10c 9/10c 9/9c

Degeneration; bronchial epithelium 0/10 0/10 0/10 0/10 0/10 8/9c

Hepatocyte swelling 0/10 0/10 0/10 10/10c 10/10c 9/9c

Single cell necrosis; liver 0/10 0/10 0/10 5/10b 10/10c 9/9c

Female dose (mg/kg-day)a

0 170 387 898 1,620 2,669 

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 0/10 3/10 3/10 7/10c

Eosinophilic change; nasal respiratory epithelium 0/10 0/10 1/10 1/10 5/10b 9/10c

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 6/10b 10/10c 10/10c

Eosinophilic change; nasal olfactory epithelium 0/10 0/10 0/10 1/10c 6/10b 6/10b

Vacuolic change; olfactory nerve 0/10 0/10 0/10 0/10 2/10 8/10c

Nuclear enlargement; tracheal epithelium 0/10 0/10 2/10 9/10c 10/10c 10/10c

Accumulation of foamy cells; lung/bronchi 0/10 0/10 0/10 0/10 10/10c 10/10c

Nuclear enlargement; bronchial epithelium 0/10 0/10 10/10c 10/10c 10/10c 10/10c

Degeneration; bronchial epithelium 0/10 0/10 0/10 0/10 7/10c 10/10c

Hepatocyte swelling 0/10 1/10 1/10 10/10c 10/10c 9/10b

Single cell necrosis; liver 0/10 0/10 0/10 7/10c 10/10c 9/10c

a

Data are presented for sacrificed animals. 

b

p ≤ 0.01 by χ

2

 test. c

p ≤ 0.05. 

Source: Kano et al (2008, 196245). 

4.2.1.1.4. Yamamoto et al. Studies (Yamamoto et al., 1998, 196114; Yamamoto et al., 1998, 

594544) in rasH2 transgenic mice carrying the human prototype c-Ha-ras gene have been 

investigated as a bioassay model for rapid carcinogenicity testing. As part of validation studies 

of this model, 1,4-dioxane was one of many chemicals that were evaluated. RasH2 transgenic 

mice were F1 offspring of transgenic male C57BLr6J and normal female BALB/cByJ mice. 

CB6F1 mice were used as a nontransgenic control. Seven- to nine-week-old mice (10–15/group) 

were exposed to 0, 0.5, or 1% 1,4-dioxane in drinking water for 26 weeks. An increase in lung 

 33 
 

adenomas was observed in treated transgenic mice, as compared to treated nontransgenic mice. 

The tumor incidence in transgenic animals, however, was not greater than that observed in 

vehicle-treated transgenic mouse controls. Further study details were not provided. 

4.2.1.2. Chronic Oral Toxicity and Carcinogenicity

4.2.1.2.1. Argus et al. Twenty-six adult male Wistar rats (Argus et al., 1965, 017009) weighing 

between 150 and 200 g were exposed to 1,4-dioxane (purity not reported) in the drinking water 

at a concentration of 1% for 64.5 weeks. A group of nine untreated rats served as control. Food 

and water were available ad libitum. The drinking water intake for treated animals was reported 

to be 30 mL/day, resulting in a dose/rat of 300 mg/day. Using a reference BW of 0.462 kg for 

chronic exposure to male Wistar rats (U.S. EPA, 1988, 064560), it can be estimated that these 

rats received daily doses of approximately 640 mg/kg-day. All animals that died or were killed 

during the study underwent a complete necropsy. A list of specific tissues examined 

microscopically was not provided; however, it is apparent that the liver, kidneys, lungs, 

lymphatic tissue, and spleen were examined. No statistical analysis of the results was conducted. 

Six of the 26 treated rats developed hepatocellular carcinomas, and these rats had been 

treated for an average of 452 days (range, 448–455 days). No liver tumors were observed in 

control rats. In two rats that died after 21.5 weeks of treatment, histological changes appeared to 

involve the entire liver. Groups of cells were found that had enlarged hyperchromic nuclei. Rats 

that died or were killed at longer intervals showed similar changes, in addition to large cells with 

reduced cytoplasmic basophilia. Animals killed after 60 weeks of treatment showed small 

neoplastic nodules or multifocal hepatocellular carcinomas. No cirrhosis was observed in this 

study. Many rats had extensive changes in the kidneys often resembling glomerulonephritis, 

however, incidence data was not reported for these findings. This effect progressed from 

increased cellularity to thickening of the glomerular capsule followed by obliteration of the 

glomeruli. One treated rat had an early transitional cell carcinoma in the kidney’s pelvis; this rat 

also had a large tumor in the liver. The lungs from many treated and control rats (incidence not 

reported) showed severe bronchitis with epithelial hyperplasia and marked peribronchial 

infiltration, as well as multiple abscesses. One rat treated with 1,4-dioxane developed leukemia 

with infiltration of all organs, particularly the liver and spleen, with large, round, isolated 

neoplastic cells. In the liver, the distribution of cells in the sinusoids was suggestive of myeloid 

leukemia. The dose of 640 mg/kg-day tested in this study was a free-standing LOAEL, 

identified by EPA, for glomerulonephritis in the kidney and histological changes in the liver 

(hepatocytes with enlarged hyperchromic nuclei, large cells with reduced cytoplasmic 

basophilia). 

 34 
 

4.2.1.2.2. Argus et al.; Hoch-Ligeti et al. Five groups (28-32/dose group) of male 

Sprague Dawley rats (2-3 months of age) weighing 110–230 g at the beginning of the experiment 

were administered 1,4-dioxane (purity not reported) in the drinking water for up to 13 months at 

concentrations of 0, 0.75, 1.0, 1.4, or 1.8% (Argus et al., 1973, 062912; Hoch-Ligeti et al., 1970, 

062926). The drinking water intake was determined for each group over a 3-day measurement 

period conducted at the beginning of the study and twice during the study (weeks were not 

specified). The rats were killed with ether at 16 months or earlier if nasal tumors were clearly 

observable. Complete autopsies were apparently performed on all animals, but only data from 

the nasal cavity and liver were presented and discussed. The nasal cavity was studied 

histologically only from rats in which gross tumors in these locations were present; therefore, 

early tumors may have been missed and pre-neoplastic changes were not studied. No statistical 

analysis of the results was conducted. Assuming a BW of 0.523 kg for an adult male 

Sprague Dawley rat (U.S. EPA, 1988, 064560) and a drinking water intake of 30 mL/day as 

reported by the study authors, dose estimates were 0, 430, 574, 803, and 1,032 mg/kg-day. The 

progression of liver tumorigenesis was evaluated by an additional group of 10 male rats 

administered 1% 1,4-dioxane in the drinking water (574 mg/kg-day), 5 of which were sacrificed 

after 8 months of treatment and 5 were killed after 13 months of treatment. Liver tissue from 

these rats and control rats was processed for electron microscopy examination. 

Nasal cavity tumors were observed upon gross examination in six rats (1/30 in the 0.75% 

group, 1/30 in the 1.0% group, 2/30 in the 1.4% group, and 2/30 in the 1.8% group). Gross 

observation showed the tumors visible either at the tip of the nose, bulging out of the nasal 

cavity, or on the back of the nose covered by intact or later ulcerated skin. As the tumors 

obstructed the nasal passages, the rats had difficulty breathing and lost weight rapidly. No 

neurological signs or compression of the brain were observed. In all cases, the tumors were 

squamous cell carcinomas with marked keratinization and formation of keratin pearls. Bony 

structure was extensively destroyed in some animals with tumors, but there was no invasion into 

the brain. In addition to the squamous carcinoma, two adenocarcinomatous areas were present. 

One control rat had a small, firm, well-circumscribed tumor on the back of the nose, which 

proved to be subcutaneous fibroma. The latency period for tumor onset was 329–487 days. 

Evaluation of the latent periods and doses received did not suggest an inverse relationship 

between these two parameters. 

Argus et al. (1973, 062912) studied the progression of liver tumorigenesis by electron 

microscopy of liver tissues obtained following interim sacrifice at 8 and 13 months of exposure 

(5 rats/group, 574 mg/kg-day). The first change observed in the liver was an increase in the size 

of the nucleus of the hepatocytes, mostly in the periportal area. Precancerous changes were 

characterized by disorganization of the rough endoplasmic reticulum, an increase in smooth 

endoplasmic reticulum, and a decrease in glycogen and increase in lipid droplets in hepatocytes. 

 35 
 

These changes increased in severity in the hepatocellular carcinomas in rats exposed to 

1,4-dioxane for 13 months. 

Three types of liver nodules were observed in exposed rats at 13–16 months. The first 

consisted of groups of cells with reduced cytoplasmic basophilia and a slightly nodular 

appearance as viewed by light microscopy. The second type of circumscribed nodule was 

described consisting of large cells, apparently filled and distended with fat. The third type of 

nodule was described as finger-like strands, 2–3 cells thick, of smaller hepatocytes with large 

hyperchromic nuclei and dense cytoplasm. This third type of nodule was designated as an 

incipient hepatoma, since it showed all the histological characteristics of a fully developed 

hepatoma. All three types of nodules were generally present in the same liver. Cirrhosis of the 

liver was not observed. The numbers of incipient liver tumors and hepatomas in rats from this 

study (treated for 13 months and observed at 13–16 months) are presented in Table 4-3. 

Table 4-3. Number of incipient liver tumors and hepatomas in male 

Sprague- Dawley rats exposed to 1,4-dioxane in drinking water for 

13 months 

Dose (mg/kg-day)a Incipient tumors Hepatomas Total 

430 4 0 4 

574 9 0 9 

803 13 3 16 

1,032 11 12 23 

a

Precise incidences cannot be calculated since the number of rats per group was reported as 28–32; incidence in 

control rats was not reported; no statistical analysis of the results was conducted in the study. 

Source: Argus et al. (1973, 062912). 

Treatment with all dose levels of 1,4-dioxane induced marked kidney alterations, but 

quantitative incidence data were not provided. Qualitatively, the changes indicated 

glomerulonephritis and pyelonephritis, with characteristic epithelial proliferation of Bowman’s 

capsule, periglomerular fibrosis, and distension of tubules. No kidney tumors were found. No 

tumors were found in the lungs. One rat at the 1.4% treatment level showed early peripheral 

adenomatous change of the alveolar epithelium and another rat in the same group showed 

papillary hyperplasia of the bronchial epithelium. The lowest dose tested (430 mg/kg-day) was 

considered a LOAEL by EPA for hepatic and renal effects in this study. 

4.2.1.2.3. Hoch-Ligeti and Argus. Hoch-Ligeti and Argus (1970, 029386) provided a brief 

account of the results of exposure of guinea pigs to 1,4-dioxane. A group of 22 male guinea pigs 

(neither strain nor age provided) was administered 1,4-dioxane (purity not provided) in the 

drinking water for at least 23 months and possibly up to 28 months. The authors stated that the 

concentration of 1,4-dioxane was regulated so that normal growth of the guinea pigs was 

 36 
 

maintained, and varied 0.5–2% (no further information provided). The investigators further 

stated that the amount of 1,4-dioxane received by the guinea pigs over a 23-month period was 

588–635 g. Using a reference BW of 0.89 kg for male guinea pigs in a chronic study (U.S. EPA, 

1988, 064560) and assuming an exposure period of 700 days (23 months), the guinea pigs 

received doses between 944 and 1,019 mg 1,4-dioxane/kg-day. A group of ten untreated guinea 

pigs served as controls. All animals were sacrificed within 28 months, but the scope of the 

postmortem examination was not provided. 

Nine treated guinea pigs showed peri- or intrabronchial epithelial hyperplasia and nodular 

mononuclear infiltration in the lungs. Also, two guinea pigs had carcinoma of the gallbladder, 

three had early hepatomas, and one had an adenoma of the kidney. Among the controls, four 

guinea pigs had peripheral mononuclear cell accumulation in the lungs, and only one had 

hyperplasia of the bronchial epithelium. One control had formation of bone in the bronchus. No 

further information was presented in the brief narrative of this study. Given the limited reporting 

of the results, a NOAEL or LOAEL value was not provided for this study. 

4.2.1.2.4. Kociba et al. Groups of 6–8-week-old Sherman rats (60/sex/dose level) were 

administered 1,4-dioxane (purity not reported) in the drinking water at levels of 0 (controls), 

0.01, 0.1, or 1.0% for up to 716 days (Kociba et al., 1974, 062929). The drinking water was 

prepared twice weekly during the first year of the study and weekly during the second year of the 

study. Water samples were collected periodically and analyzed for 1,4-dioxane content by 

routine gas liquid chromatography. Food and water were available ad libitum. Rats were 

observed daily for clinical signs of toxicity, and BWs were measured twice weekly during the 

first month, weekly during months 2–7, and biweekly thereafter. Water consumption was 

recorded at three different time periods during the study: days 1–113, 114–198, and 446–460. 

Blood samples were collected from a minimum of five male and five female control and highdose rats during the 4th, 6th, 12th, and 18th months of the study and at termination. Each sample 

was analyzed for packed cell volume, total erythrocyte count, hemoglobin, and total and 

differential WBC counts. Additional endpoints evaluated included organ weights (brain, liver, 

kidney, testes, spleen, and heart) and gross and microscopic examination of major tissues and 

organs (brain, bone and bone marrow, ovaries, pituitary, uterus, mesenteric lymph nodes, heart, 

liver, pancreas, spleen, stomach, prostate, colon, trachea, duodenum, kidneys, esophagus, 

jejunum, testes, lungs, spinal cord, adrenals, thyroid, parathyroid, nasal turbinates, and urinary 

bladder). The number of rats with tumors, hepatic tumors, hepatocellular carcinomas, and nasal 

carcinomas were analyzed for statistical significance with Fisher’s Exact test (one-tailed), 

comparing each treatment group against the respective control group. Survival rates were 

compared using χ

2

 Contingency Tables and Fisher’s Exact test. Student’s test was used to 

compare hematological parameters, body and organ weights, and water consumption of each 

treatment group with the respective control group. 

 37 
 

Male and female rats in the high-dose group (1% in drinking water) consumed slightly 

less water than controls. BW gain was depressed in the high-dose groups relative to the other 

groups almost from the beginning of the study (food consumption data were not provided). 

Based on water consumption and BW data for specific exposure groups, Kociba et al. (1974, 

062929) calculated mean daily doses of 9.6, 94, and 1,015 mg/kg-day for male rats and 19, 148, 

and 1,599 mg/kg-day for female rats during days 114–198 for the 0.01, 0.1, and 1.0% 

concentration levels, respectively. Treatment with 1,4-dioxane significantly increased mortality 

among high-dose males and females beginning at about 2–4 months of treatment. These rats 

showed degenerative changes in both the liver and kidneys. From the 5th month on, mortality 

rates of control and treated groups were not different. There were no treatment-related 

alterations in hematological parameters. At termination, the only alteration in organ weights 

noted by the authors was a significant increase in absolute and relative liver weights in male and 

female high-dose rats (data not shown). Histopathological lesions were restricted to the liver and 

kidney from the mid- and high-dose groups and consisted of variable degrees of renal tubular 

epithelial and hepatocellular degeneration and necrosis (no quantitative incidence data were 

provided). Rats from these groups also showed evidence of hepatic regeneration, as indicated by 

hepatocellular hyperplastic nodule formation and evidence of renal tubular epithelial 

regenerative activity (observed after 2 years of exposure). These changes were not seen in 

controls or in low-dose rats. The authors determined a LOAEL of 94 mg/kg-day based on the 

liver and kidney effects in male rats. The corresponding NOAEL value was 9.6 mg/kg-day. 

Histopathological examination of all the rats in the study revealed a total of 132 tumors in 

114 rats. Treatment with 1% 1,4-dioxane in the drinking water resulted in a significant increase 

in the incidence of hepatic tumors (hepatocellular carcinomas in six males and four females). In 

addition, nasal carcinomas (squamous cell carcinoma of the nasal turbinates) occurred in one 

high-dose male and two high-dose females. Since 128 out of 132 tumors occurred in rats from 

the 12th to the 24th month, Kociba et al. (1974, 062929) assumed that the effective number of 

rats was the number surviving at 12 months, which was also when the first hepatic tumor was 

noticed. The incidences of liver and nasal tumors from Kociba et al. (1974, 062929) are 

presented in Table 4-4. Tumors in other organs were not elevated when compared to control 

incidence and did not appear to be related to 1,4-dioxane administration. 

 38 
 

Table 4-4. Incidence of liver and nasal tumors in male and female 

Sherman rats (combined) treated with 1,4-dioxane in the drinking water for 

2 years 

Dose in mg/kg-day Number of animals 

(average of male 

and female dose) 

Effective 

number of 

animalsa

Number of tumorbearing animals Hepatic tumors 

(all types) 

Hepatocellular 

carcinomas 

Nasal 

carcinomas 

0 106 31 2 1 0 

14 110 34 0 0 0 

121 106 28 1 1 0 

1307 66 21 12b 10c 3d

a

Rats surviving until 12 months on study. 

b

p = 0.00022 by one-tailed Fisher’s Exact test. c

p = 0.00033 by one-tailed Fisher’s Exact test. d

p = 0.05491 by one-tailed Fisher’s Exact test. 

Source: Used with permission from Elsevier, Ltd., Kociba et al. (1974, 062929). 

The high-dose level was the only dose that increased the formation of liver tumors over 

control (males 1,015 mg/kg-day; females 1,599 mg/kg-day) and also caused significant liver and 

kidney toxicity in these animals. The mid-dose group (males 94 mg/kg-day; females 148 mg/kgday) experienced hepatic and renal degeneration and necrosis, as well as regenerative 

hyperplasia in hepatocytes and renal tubule epithelial cells. No increase in tumor formation was 

seen in the mid-dose group. No toxicity or tumor formation was observed in either sex in the 

low-dose (males 9.6 mg/kg-day; females 19 mg/kg-day) group of rats. 

4.2.1.2.5. National Cancer Institute (NCI). Groups of Osborne-Mendel rats (35/sex/dose) and 

B6C3F1 mice (50/sex/dose) were administered 1,4-dioxane (≥ 99.95% pure) in the drinking 

water for 110 or 90 weeks, respectively, at levels of 0 (matched controls), 0.5, or 1% (NCI, 1978, 

062935). Solutions of 1,4-dioxane were prepared with tap water. The report indicated that at 

105 weeks from the earliest starting date, a new necropsy protocol was instituted. This affected 

the male controls and high-dose rats, which were started a year later than the original groups of 

rats and mice. Food and water were available ad libitum. Endpoints monitored in this bioassay 

included clinical signs (twice daily), BWs (once every 2 weeks for the first 12 weeks and every 

month during the rest of the study), food and water consumption (once per month in 20% of the 

animals in each group during the second year of the study), and gross and microscopic 

appearance of all major organs and tissues (mammary gland, trachea, lungs and bronchi, heart, 

bone marrow, liver, bile duct, spleen, thymus, lymph nodes, salivary gland, pancreas, kidney, 

esophagus, thyroid, parathyroid, adrenal, gonads, brain, spinal cord, sciatic nerve, skeletal 

muscle, stomach, duodenum, colon, urinary bladder, nasal septum, and skin). Based on the 

measurements of water consumption and BWs, the investigators calculated average daily intakes 

of 1,4-dioxane of 0, 240, and 530 mg/kg-day in male rats, 0, 350, and 640 mg/kg-day in female 

 39 
 

rats, 0, 720, and 830 mg/kg-day in male mice, and 0, 380, and 860 mg/kg-day in female mice. 

According to the report, the doses of 1,4-dioxane in high-dose male mice were only slightly 

higher than those of the low-dose group due to decreased fluid consumption in high-dose male 

mice. 

During the second year of the study, the BWs of high-dose rats were lower than controls, 

those of low-dose males were higher than controls, and those of low-dose females were 

comparable to controls. The fluctuations in the growth curves were attributed to mortality by the 

investigators; quantitative analysis of BW changes was not done. Mortality was significantly 

increased in treated rats, beginning at approximately 1 year of study. Analysis of Kaplan-Meier 

curves (plots of the statistical estimates of the survival probability function) revealed significant 

positive dose-related trends (p < 0.001, Tarone test). In male rats, 33/35 (94%) in the control 

group, 26/35 (74%) in the mid-dose group, and 33/35 (94%) in the high-dose group were alive 

on week 52 of the study. The corresponding numbers for females were 35/35 (100%), 30/35 

(86%), and 29/35 (83%). Nonneoplastic lesions associated with treatment with 1,4-dioxane were 

seen in the kidneys (males and females), liver (females only), and stomach (males only). Kidney 

lesions consisted of vacuolar degeneration and/or focal tubular epithelial regeneration in the 

proximal cortical tubules and occasional hyaline casts. Elevated incidence of hepatocytomegaly 

also occurred in treated female rats. Gastric ulcers occurred in treated males, but none were seen 

in controls. The incidence of pneumonia was increased above controls in high-dose female rats. 

The incidence of nonneoplastic lesions in rats following drinking water exposure to 1,4-dioxane 

is presented in Table 4-5. EPA identified the LOAEL in rats from this study as 240 mg/kg-day 

for increased incidence of gastric ulcer and cortical tubular degeneration in the kidney in males; 

a NOAEL was not established. 

Table 4-5. Incidence of nonneoplastic lesions in Osborne-Mendel rats 

exposed to 1,4-dioxane in drinking water 

Males (mg/kg-day) Females (mg/kg-day) 

0 240 530 0 350 640 

Cortical tubule degeneration 0/31a 20/31b

(65%) 

27/33b

(82%) 

0/31a 0/34 10/32b

(31%) 

Hepatocytomegaly 5/31 

(16%) 

3/32 

(9%) 

11/33 

(33%) 

7/31a

(23%) 

11/33 

(33%) 

17/32b

(53%) 

Gastric ulcer 0/30a 5/28b

(18%) 

5/30b

(17%) 

0/31 1/33 

(3%) 

1/30 

(3%) 

Pneumonia 8/30 

(27%) 

15/31 

(48%) 

14/33 

(42%) 

6/30a

(20%) 

5/34 

(15%) 

25/32b

(78%) 

a

Statistically significant trend for increased incidence by Cochran-Armitage test (p < 0.05) performed for this 

review. 

b

Incidence significantly elevated compared to control by Fisher’s Exact test (p < 0.05) performed for this review. 

Source: NCI (1978, 062935). 

 40 
 

Neoplasms associated with 1,4-dioxane treatment were limited to the nasal cavity 

(squamous cell carcinomas, adenocarcinomas, and one rhabdomyoma) in both sexes, liver 

(hepatocellular adenomas) in females, and testis/epididymis (mesotheliomas) in males. The first 

tumors were seen at week 52 in males and week 66 in females. The incidence of squamous cell 

carcinomas in the nasal turbinates in male and female rats is presented in Table 4-6. Squamous 

cell carcinomas were first seen on week 66 of the study. Morphologically, these tumors varied 

from minimal foci of locally invasive squamous cell proliferation to advanced growths consisting 

of extensive columns of epithelial cells projecting either into free spaces of the nasal cavity 

and/or infiltrating into the submucosa. Adenocarcinomas of the nasal cavity were observed in 

3 of 34 high-dose male rats, 1 of 35 low-dose female rats, and 1 of 35 high-dose female rats. 

The single rhabdomyoma (benign skeletal muscle tumor) was observed in the nasal cavity of a 

male rat from the low-dose group. A subsequent re-examination of the nasal tissue sections by 

Goldsworthy et al. (1991, 062925) concluded that the location of the tumors in the nasal 

apparatus was consistent with the possibility that the nasal tumors resulted from inhalation of 

water droplets by the rats (see Section 4.5.2 for more discussion of Goldsworthy et al. (1991, 

062925)). 

Table 4-6. Incidence of nasal cavity squamous cell carcinoma and liver 

hepatocellular adenoma in Osborne-Mendel rats exposed to 1,4-dioxane in 

drinking water 

Males (mg/kg-day)a

0 240b 530 

Nasal cavity squamous cell carcinoma 0/33 (0%) 12/33 (36%) 16/34 (47%)c

Hepatocellular adenoma 2/31 (6%) 2/32 (6%) 1/33 (3%) 

Females (mg/kg-day)a

0 350 640 

Nasal cavity squamous cell carcinoma 0/34 (0%)d 10/35 (29%)e 8/35 (23%)c

Hepatocellular adenoma 0/31 (0%)f 10/33 (30%)e 11/32 (34%)e

a

Tumor incidence values were not adjusted for mortality. 

b

Group not included in statistical analysis by NCI because the dose group was started a year earlier without 

appropriate controls. 

c

p ≤ 0.003 by Fisher’s Exact test pair-wise comparison with controls. d

p = 0.008 by Cochran-Armitage test. e

p ≤ 0.001 by Fisher’s Exact test pair-wise comparison with controls. f

p = 0.001 by Cochran-Armitage test. 

Source: NCI (1978, 062935). 

The incidence of hepatocellular adenomas in male and female rats is presented in Table 

4-6. Hepatocellular adenomas were first observed in high-dose females in week 70 of the study. 

These tumors consisted of proliferating hepatic cells oriented as concentric cords. Hepatic cell 

size was variable; mitoses and necrosis were rare. Mesothelioma of the vaginal tunics of the 

 41 
 

testis/epididymis was seen in male rats (2/33, 4/33, and 5/34 in controls, low-, and high-dose 

animals, respectively). The difference between the treated groups and controls was not 

statistically significant. These tumors were characterized as rounded and papillary projections of 

mesothelial cells, each supported by a core of fibrous tissue. Other reported neoplasms were 

considered spontaneous lesions not related to treatment with 1,4-dioxane. 

In mice, mean BWs of high-dose female mice were lower than controls during the second 

year of the study, while those of low-dose females were higher than controls. In males, mean 

BWs of high-dose animals were higher than controls during the second year of the study. 

According to the investigators, these fluctuations could have been due to mortality; no 

quantitative analysis of BWs was done. No other clinical signs were reported. Mortality was 

significantly increased in female mice (p < 0.001, Tarone test), beginning at approximately 

80 weeks on study. The numbers of female mice that survived to 91 weeks were 45/50 (90%) in 

the control group, 39/50 (78%) in the low-dose group, and 28/50 (56%) in the high-dose group. 

In males, at least 90% of the mice in each group were still alive at week 91. Nonneoplastic 

lesions that increased significantly due to treatment with 1,4-dioxane were pneumonia in males 

and females and rhinitis in females. The incidences of pneumonia were 1/49 (2%), 9/50 (18%), 

and 17/47 (36%) in control, low-dose, and high-dose males, respectively; the corresponding 

incidences in females were 2/50 (4%), 33/47 (70%), and 32/36 (89%). The incidences of rhinitis 

in female mice were 0/50, 7/48 (14%), and 8/39 (21%) in control, low-dose, and high-dose 

groups, respectively. Pair-wise comparisons of low-dose and high-dose incidences with controls 

for incidences of pneumonia and rhinitis in females using Fisher’s Exact test (done for this 

review) yielded p-values < 0.001 in all cases. Incidences of other lesions were considered to be 

similar to those seen in aging mice. The authors stated that hepatocytomegaly was commonly 

found in dosed mice, but the incidences were not significantly different from controls and 

showed no dose-response trend. EPA concluded the LOAEL for 1,4-dioxane in mice was 

380 mg/kg-day based on the increased incidence of pneumonia and rhinitis in female mice; a 

NOAEL was not established in this study. 

As shown in Table 4-7, treatment with 1,4-dioxane significantly increased the incidence 

of hepatocellular carcinomas or adenomas in male and female mice in a dose-related manner. 

Tumors were first observed on week 81 in high-dose females and in week 58 in high-dose males. 

Tumors were characterized by parenchymal cells of irregular size and arrangement, and were 

often hypertrophic with hyperchromatic nuclei. Mitoses were seldom seen. Neoplasms were 

locally invasive within the liver, but metastasis to the lungs was rarely observed. 

 42 
 

Table 4-7. Incidence of hepatocellular adenoma or carcinoma in B6C3F1

mice exposed to 1,4-dioxane in drinking water 

Males (mg/kg-day)a

0 720 830 

Hepatocellular carcinoma 2/49 (4%)b 18/50 (36%)c 24/47 (51%)c

Hepatocellular adenoma or carcinoma 8/49 (16%)b 19/50 (38%)d 28/47 (60%)c

Females (mg/kg-day)a

0 380 860 

Hepatocellular carcinoma 0/50 (0%)b 12/48 (25%)c 29/37 (78%)c

Hepatocellular adenoma or carcinoma 0/50 (0%)b 21/48 (44%)c 35/37 (95%)c

a

Tumor incidence values were not adjusted for mortality. 

b

p < 0.001, positive dose-related trend (Cochran-Armitage test). c

p < 0.001 by Fisher’s Exact test pair-wise comparison with controls. d

p = 0.014. 

Source: NCI (1978, 062935). 

In addition to liver tumors, a variety of other benign and malignant neoplasms occurred. 

However, the report (NCI, 1978, 062935) indicated that each type had been encountered 

previously as a spontaneous lesion in the B6C3F1 mouse. The report further stated that the 

incidences of these neoplasms were unrelated by type, site, group, or sex of the animal, and 

hence, not attributable to exposure to 1,4-dioxane. There were a few nasal adenocarcinomas 

(1/48 in low-dose females and 1/49 in high-dose males) that arose from proliferating respiratory 

epithelium lining of the nasal turbinates. These growths extended into the nasal cavity, but there 

was minimal local tissue infiltration. Nasal mucosal polyps were rarely observed. The polyps 

were derived from mucus-secreting epithelium and were otherwise unremarkable. There was a 

significant negative trend for alveolar/bronchiolar adenomas or carcinomas of the lung in male 

mice, such that the incidence in the matched controls was higher than in the dosed groups. The 

report (NCI, 1978, 062935) indicated that the probable reason for this occurrence was that the 

dosed animals did not live as long as the controls, thus diminishing the possibility of the 

development of tumors in the dosed groups. 

4.2.1.2.6. Kano et al.; Japan Bioassay Research Center; Yamazaki et al. The Japan 

Bioassay Research Center (JBRC) conducted a 2-year drinking water study determining the 

effects of 1,4-dioxane on both sexes of rats and mice. The study results have been reported 

several times: once as conference proceedings (Yamazaki et al., 1994, 196120), once as a 

laboratory report (JBRC, 1998, 196240), and most recently as a peer-reviewed manuscript (Kano 

et al., 2009, 594539). Dr. Yamazaki also provided some detailed information (Yamazaki, 2006, 

626614). Variations in the data between these three reports were noted and included: (1) the 

level of detail on dose information reported; (2) categories for incidence data reported (e.g., all 

animals or sacrificed animals); and (3) analysis of non- and neoplastic lesions. 

 43 
 

The 1,4-dioxane dose information provided in the reports varied. Specifically, Yamazaki 

et al. (1994, 196120) only included drinking water concentrations for each dose group. In 

contrast, JBRC (1998, 196240) included drinking water concentrations (ppm), in addition using 

body weights and water consumption measurements to calculate daily chemical intake 

(mg/kg-day). JBRC (1998, 196240) reported daily chemical intake for each dose group as a 

range. Thus, for the External Peer Review draft of this Toxicological Review of 1,4-Dioxane 

(U.S. EPA, 2009, 628630), the midpoint of the range was used. Kano et al. (2009, 594539) also 

reported a calculation of daily chemical intake based on body weight and water consumption 

measurements; however, for each dose group they reported a mean and standard deviation 

estimate. Therefore, because the mean more accurately represents the delivered dose than the 

midpoint of a range, the Kano et al. (2009, 594539) calculated mean chemical intake (mg/kgday) is used for quantitiative analysis of this data. 

The categories for which incidence rates were described also varied among the reports. 

Yamazaki et al. (1994, 196120) and Kano et al. (2009, 594539) reported histopathological results 

for all animals, including dead and moribund animals; however, the detailed JBRC laboratory 

findings (1998, 196240) included separate incidence reports for dead and moribund animals, 

sacrificed animals, and all animals. 

Finally, the criteria used to evaluate some of the data were updated when JBRC published 

the most recent manuscript by Kano et al. (2009, 594539). The manuscript by Kano et al. (2009, 

594539) stated that the lesions diagnosed in the earlier reports (JBRC, 1998, 196240; Yamazaki 

et al., 1994, 196120) were re-examined and recategorized as appropriate according to current 

pathological diagnostic criteria (see references in Kano et al. (2009, 594539)). 

Groups of F344/DuCrj rats (50/sex/dose level) were exposed to 1,4-dioxane (>99% pure) 

in the drinking water at levels of 0, 200, 1,000, or 5,000 ppm for 2 years. Groups of Crj:BDF1 

mice (50/sex/dose level) were similarly exposed in the drinking water to 0, 500, 2,000, or 

8,000 ppm of 1,4-dioxane. The high doses were selected based on results from the Kano et al. 

(2008, 196245) 13-week drinking water study so as not to exceed the maximum tolerated dose 

(MTD) in that study. Both rats and mice were 6 weeks old at the beginning of the study. Food 

and water were available ad libitum. The animals were observed daily for clinical signs of 

toxicity; and BWs were measured once per week for 14 weeks and once every 2 weeks until the 

end of the study. Food consumption was measured once a week for 14 weeks and once every 

4 weeks for the remainder of the study. The investigators used data from water consumption and 

BW to calculate an estimate of the daily intake of 1,4-dioxane (mg/kg-day) by male and female 

rats and mice. Kano et al. (2009, 594539) reported a calculated mean ± standard deviation for 

the daily doses of 1,4-dioxane for the duration of the study. Male rats received doses of 

approximately 0, 11±1, 55±3, or 274±18 mg/kg-day and female rats received 0, 18±3, 83±14, or 

429±69 mg/kg-day. Male mice received doses of 0, 49±5, 191±21, or 677±74 mg/kg-day and 

female mice received 0, 66±10, 278±40, or 964±88 mg/kg-day. For the remainder of this 

 44 
 

document, including the dose-response analysis, the mean calculated intake values are used to 

identify dose groups. The Kano et al. (2009, 594539) study was conducted in accordance with 

the Organization for Economic Co-operation and Development (OECD) Principles for Good 

Laboratory Practice (GLP). 

No information was provided as to when urine samples were collected. Blood samples 

were collected only at the end of the 2-year study (Yamazaki, 2006, 626614). Hematology 

analysis included RBCs, hemoglobin, hematocrit, MCV, platelets, WBCs and differential WBCs. 

Serum biochemistry included total protein, albumin, bilirubin, glucose, cholesterol, triglyceride 

(rat only), phospholipid, ALT, AST, LDH, LAP, ALP, γ-glutamyl transpeptidase (GGT), CPK, 

urea nitrogen, creatinine (rat only), sodium, potassium, chloride, calcium, and inorganic 

phosphorous. Urinalysis parameters were pH, protein, glucose, ketone body, bilirubin (rat only), 

occult blood, and urobilinogen. Organ weights (brain, lung, liver, spleen, heart, adrenal, testis, 

ovary, and thymus) were measured, and gross necropsy and histopathologic examination of 

tissues and organs were performed on all animals (skin, nasal cavity, trachea, lungs, bone 

marrow, lymph nodes, thymus, spleen, heart, tongue, salivary glands, esophagus, stomach, small 

and large intestine, liver, pancreas, kidney, urinary bladder, pituitary, thyroid, adrenal, testes, 

epididymis, seminal vesicle, prostate, ovary, uterus, vagina, mammary gland, brain, spinal cord, 

sciatic nerve, eye, Harderian gland, muscle, bone, and parathyroid). Dunnett’s test and χ

2

 test 

were used to assess the statistical significance of changes in continuous and discrete variables, 

respectively. 

For rats, growth and mortality rates were reported in Kano et al. (2009, 594539) for the 

duration of the study. Both male and female rats in the high dose groups (274 and 429 mg/kgday, respectively) exhibited slower growth rates and terminal body weights that were 

significantly different (p < 0.05) compared to controls. A statistically significant reduction in 

terminal BWs was observed in high-dose male rats (5%, p < 0.01) and in high-dose female rats 

(18%, p < 0.01) (Kano et al., 2009, 594539). Food consumption was not significantly affected 

by treatment in male or female rats; however, water consumption in female rats administered 

18 mg/kg-day was significantly greater (p < 0.05) . 

All control and exposed rats lived at least 12 months following study initiation 

(Yamazaki, 2006, 626614); however, survival at the end of the 2-year study in the high dose 

group of male and female rats (274 and 429 mg/kg-day, respectively) was approximately 50%, 

which was significantly different compared to controls. The investigators attributed these early 

deaths to the increased incidence in nasal tumors and peritoneal mesotheliomas in male rats and 

nasal and hepatic tumors in female rats. (Yamazaki, 2006, 626614). 

Several hematological changes were noted in the JBRC report (1998, 196240): 

Decreases in RBC (male rats only), hemoglobin, hematocrit, and MCV; and increases in platelets 

in high-dose groups were observed (JBRC, 1998, 196240). These changes (except for MCV) 

also occurred in mid-dose males. With the exception of a 23% decrease in hemoglobin in high-

 45 
 

dose male rats and a 27% increase in platelets in high-dose female rats, hematological changes 

were within 15% of control values. Significant changes in serum chemistry parameters occurred 

only in high-dose rats (males: increased phospholipids, AST, ALT, LDH, ALP, GGT, CPK, 

potassium, and inorganic phosphorus and decreased total protein, albumin, and glucose; females: 

increased total bilirubin, cholesterol, phospholipids, AST, ALT, LDH, GGT, ALP, CPK, and 

potassium, and decreased blood glucose) (JBRC, 1998, 196240). Increases in serum enzyme 

activities ranged from <2- to 17-fold above control values, with the largest increases seen for 

ALT, AST, and GGT. Urine pH was significantly decreased at 274 mg/kg-day in male rats (not 

tested at other dose levels) and at 83 and 429 mg/kg-day in female rats (JBRC, 1998, 196240). 

Also, blood in the urine was seen in female rats at 83 and 429 mg/kg-day (JBRC, 1998, 196240). 

In male rats, relative liver weights were increased at 55 and 274 mg/kg-day (Kano et al., 2009, 

594539). In female rats, relative liver weight was increased at 429 mg/kg-day (Kano et al., 2009, 

594539). 

Microscopic examination of the tissues showed nonneoplastic alterations in the nasal 

cavity, liver, and kidneys mainly in high-dose rats and, in a few cases, in mid-dose rats (Table s 

4-8 and 4-9). Alterations in high-dose (274 mg/kg-day) male rats consisted of nuclear 

enlargement and metaplasia of the olfactory and respiratory epithelia, atrophy of the olfactory 

epithelium, hydropic changes and sclerosis of the lamina propria, adhesion, and inflammation. 

In female rats, nuclear enlargement of the olfactory epithelium occurred at doses ≥ 83 mg/kgday, and nuclear enlargement and metaplasia of the respiratory epithelium, squamous cell 

hyperplasia, respiratory metaplasia of the olfactory epithelium, hydropic changes and sclerosis of 

the lamina propria, adhesion, inflammation, and proliferation of the nasal gland occurred at 

429 mg/kg-day. Alterations were seen in the liver at ≥ 55 mg/kg-day in male rats (spongiosis 

hepatis, hyperplasia, and clear and mixed cell foci) and at 429 mg/kg-day in female rats 

(hyperplasia, spongiosis hepatis, cyst formation, and mixed cell foci). Nuclear enlargement of 

the renal proximal tubule occurred in males at 274 mg/kg-day and in females at ≥ 83 mg/kg-day 

(JBRC, 1998, 196240). 

 46 
 

Table 4-8. Incidence of histopathological lesions in male F344/DuCrj rats 

exposed to 1,4-dioxane in drinking water for 2 years 

Dose (mg/kg-day)a,b

0 11 55 274 

Nuclear enlargement; nasal respiratory epitheliumc 0/50 0/50 0/50 26/50e

Squamous cell metaplasia; nasal respiratory epitheliumc 0/50 0/50 0/50 31/50e

Squamous cell hyperplasia; nasal respiratory epitheliumc 0/50 0/50 0/50 2/50 

Nuclear enlargement; nasal olfactory epitheliumc 0/50 0/50 5/50f 38/50e

Respiratory metaplasia; nasal olfactory epitheliumd 12/50 11/50 20/50 43/50

Atrophy; nasal olfactory epitheliumd 0/50 0/50 0/50 36/50

Hydropic change; lamina propriad 0/50 0/50 0/50 46/50

Sclerosis; lamina propriad 0/50 0/50 1/50 44/50 

Adhesion; nasal cavityd 0/50 0/50 0/50 48/50 

Inflammation; nasal cavityd 0/50 0/50 0/50 13/50 

Hyperplasia; liverd 3/50 2/50 10/50 24/50 

Spongiosis hepatis; liverd 12/50 20/50 25/50f 40/50 

Clear cell foci; liverc 3/50 3/50 9/50 8/50 

Acidophilic cell foci; liverc 12/50 8/50 7/50 5/50 

Basophilic cell foci; liverc 7/50 11/50 8/50 16/50f

Mixed-cell foci; liverc 2/50 8/50 14/50e 13/50e

Nuclear enlargement; kidney proximal tubuled 0/50 0/50 0/50 50/50 

a

Data presented for all animals, including animals that became moribund or died before the end of the study. b

Dose levels from Kano et al. (2009, 594539). c

Data from Kano et al. (2009, 594539). d

Data from JBRC (1998, 196240). JBRC did not report statistical significance for the “All animals” 

comparison. 

e

p < 0.01 by χ

2

 test. f

p < 0.05 by χ

2

 test. 

Sources: Kano et al. (2009, 594539) and JBRC (1998, 196240). 

 47 
 

Table 4-9. Incidence of histopathological lesions in female F344/DuCrj 

rats exposed to 1,4-dioxane in drinking water for 2 years 

Dose (mg/kg-day)a,b

0 18 83 429 

Nuclear enlargement; nasal respiratory epitheliumc 0/50 0/50 0/50 13/50e

Squamous cell metaplasia; nasal respiratory epitheliumc 0/50 0/50 0/50 35/50 e

Squamous cell hyperplasia; nasal cavityc 0/50 0/50 0/50 5/50 

Nuclear enlargement; nasal olfactory epithelium c 0/50 0/50 28/50e 39/50 

Respiratory metaplasia; nasal olfactory epitheliumd 2/50 0/50 2/50 42/50 

Atrophy; nasal olfactory epitheliumd 0/50 0/50 1/50 40/50 

Hydropic change; lamina propriad 0/50 0/50 0/50 46/50 

Sclerosis; lamina propriad 0/50 0/50 0/50 48/50 

Adhesion; nasal cavityd 0/50 0/50 0/50 46/50 

Inflammation; nasal cavityd 0/50 0/50 1/50 15/50 

Proliferation; nasal glandd 0/50 0/50 0/50 11/50 

Hyperplasia; liverd 3/50 2/50 11/50e 47/50 

Spongiosis hepatis; liverd 0/50 0/50 1/50 20/50 

Cyst formation; liverd 0/50 1/50 1/50 8/50 

Acidophilic cell foci; liverc 1/50 1/50 1/50 1/50 

Basophilic cell foci; liverc 23/50 27/50 31/50 8/50e

Clear cell foci; liverc 1/50 1/50 5/50 4/50 

Mixed-cell foci; liverc 1/50 1/50 3/50 11/50f 

Nuclear enlargement; kidney proximal tubuled 0/50 0/50 6/50 39/50 

a

Data presented for all animals, including animals that became moribund or died before the end of the study. b

Dose levels from Kano et al. (2009, 594539). c

Data from Kano et al. (2009, 594539). d

Data from JBRC (1998, 196240). JBRC did not report statistical significance for the “All animals” 

comparison. 

e

p < 0.01 by χ

2

 test. f

p < 0.05 by χ

2

 test. 

Sources: Kano et al. (2009, 594539) and JBRC (1998, 196240). 

NOAEL and LOAEL values for rats in this study were identified by EPA as 55 and 

274 mg/kg-day, respectively, based on toxicity observed in nasal tissue of male rats (i.e., atrophy 

of olfactory epithelium, adhesion, and inflammation). Metaplasia and hyperplasia of the nasal 

epithelium were also observed in high-dose male and female rats. These effects are likely to be 

associated with the formation of nasal cavity tumors in these dose groups. Nuclear enlargement 

was observed in the nasal olfactory epithelium and the kidney proximal tubule at a dose of 

83 mg/kg-day in female rats; however, it is unclear whether these alterations represent adverse 

toxicological effects. Hematological effects noted in male rats given 55 and 274 mg/kg-day 

(decreased RBCs, hemoglobin, hematocrit, increased platelets) were within 20% of control 

values. In female rats decreases in hematological effects were observed in the high dose group 

(429 mg/kg-day). A reference range database for hematological effects in laboratory animals 

 48 
 

(Wolford et al., 1986, 196112) indicates that a 20% change in these parameters may fall within a 

normal range (10th–90th percentile values) and may not represent a treatment-related effect of 

concern. Liver lesions were also seen at a dose of 55 mg/kg-day in male rats; these changes are 

likely to be associated with liver tumorigenesis. Clear and mixed-cell foci are commonly 

considered preneoplastic changes and would not be considered evidence of noncancer toxicity. 

The nature of spongiosis hepatis as a preneoplastic change is less well understood (Bannasch, 

2003, 196140; Karbe and Kerlin, 2002, 196246; Stroebel et al., 1995, 196101). Spongiosis 

hepatis is a cyst-like lesion that arises from the perisinusoidal (Ito) cells (PSC) of the liver. It is 

commonly seen in aging rats, but has been shown to increase in incidence following exposure to 

hepatocarcinogens. Spongiosis hepatis can be seen in combination with preneoplastic foci in the 

liver or with hepatocellular adenoma or carcinoma and has been considered a preneoplastic 

lesion (Bannasch, 2003, 196140; Stroebel et al., 1995, 196101). This change can also be 

associated with hepatocellular hypertrophy and liver toxicity and has been regarded as a 

secondary effect of some liver carcinogens (Karbe and Kerlin, 2002, 196246). In the case of the 

JBRC (1998, 196240) study, spongiosis hepatis was associated with other preneoplastic changes 

in the liver (clear and mixed-cell foci). No other lesions indicative of liver toxicity were seen in 

this study; therefore, spongiosis hepatis was not considered indicative of noncancer effects. 

Serum chemistry changes (increases in total protein, albumin, and glucose; decreases in AST, 

ALT, LDH, and ALP, potassium, and inorganic phosphorous) were observed in both male and 

female rats (JBRC, 1998, 196240) in the high dose groups, 274 and 429 mg/kg-day, respectively. 

These serum chemistry changes seen in terminal blood samples from high-dose male and female 

rats are likely related to tumor formation in these dose groups. 

Significantly increased incidences of liver tumors (adenomas and carcinomas) and tumors 

of the nasal cavity occurred in high-dose male and female rats (Tables 4-10 and 4-11) treated 

with 1,4-dioxane for 2 years (Kano et al., 2009, 594539). The first liver tumor was seen at 

85 weeks in high-dose male rats and 73 weeks in high-dose female rats (vs. 101–104 weeks in 

lower dose groups and controls) (Yamazaki, 2006, 626614). In addition, a significant increase 

(p ≤ 0.01, Fisher’s Exact test) in mesotheliomas of the peritoneum was seen in high-dose males 

(28/50 versus 2/50 in controls). Mesotheliomas were the single largest cause of death among 

high-dose male rats, accounting for 12 of 28 pretermination deaths (Yamazaki, 2006, 626614). 

Also, in males, there were increasing trends in mammary gland fibroadenoma and fibroma of the 

subcutis, both statistically significant (p < 0.01) by the Peto test of dose-response trend. Females 

showed a significant increasing trend in mammary gland adenomas (p < 0.01 by Peto’s test). 

The tumor incidence values presented in Tables 4-10 and 4-11 were not adjusted for survival. 

 49 
 

Table 4-10. Incidence of nasal cavity, peritoneum, and mammary gland 

tumors in F344/DuCrj rats exposed to 1,4-dioxane in drinking water for 

2 years 

Males Females 

Dose (mg/kg-day) 0 11 55 274 0 18 83 429 

Nasal cavity 

Squamous cell carcinoma 0/50 0/50 0/50 3/50a 0/50 0/50 0/50 7/50a,b

Sarcoma 0/50 0/50 0/50 2/50 0/50 0/50 0/50 0/50 

Rhabdomyosarcoma 0/50 0/50 0/50 1/50 0/50 0/50 0/50 0/50 

Esthesioneuroepithelioma 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 

Peritoneum 

Mesothelioma 2/50 2/50 5/50 28/50a,b 1/50 0/50 0/50 0/50 

Mammary gland 

Fibroadenoma 1/50 1/50 0/50 4/50a 3/50 2/50 1/50 3/50 

Adenoma 0/50 1/50 2/50 2/50 6/50 7/50 10/50 16/50a,c

Either adenoma or fibroadenoma 1/50 2/50 2/50 6/50a 8/50 8/50 11/50 18/50a,c

a

Statistically significant trend for increased tumor incidence by Peto’s test (p < 0.01). b

Significantly different from control by Fisher’s exact test (p < 0.01). c

Significantly different from control by Fisher’s exact test (p < 0.05). 

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Table 4-11. Incidence of liver tumors in F344/DuCrj rats exposed to 

1,4-dioxane in drinking water for 2 years 

Males Females 

Dose (mg/kg-day) 0 11 55 274 0 18 83 429 

Hepatocellular adenoma 3/50 4/50 7/50 32/50a,b 3/50 1/50 6/50 48/50a,b

Hepatocellular carcinoma 0/50 0/50 0/50 14/50a,b 0/50 0/50 0/50 10/50a,b

Either adenoma or carcinoma 3/50 4/50 7/50 39/50a,b 3/50 1/50 6/50 48/50a,b

a

Significantly different from control by Fisher’s exact test (p < 0.01). b

Statistically significant trend for increased tumor incidence by Peto’s test (p < 0.01). 

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

For mice, growth and mortality rates were reported in Kano et al. (2009, 594539) for the 

duration of the study. Similar to rats, the growth rates of male and female mice were slower than 

controls and terminal body weights were lower for the mid (p < 0.01 for males administered 

191 mg/kg-day and p < 0.05 for females administered 278 mg/kg-day) and high doses (p < 0.05 

for males and females administered 677 and 964 mg/kg-day, respectively). There were no 

differences in survival rates between control and treated male mice; however, survival rates were 

significantly decreased compared to controls for female mice in the mid (278 mg/kg-day, 

approximately 40% survival) and high (964 mg/kg-day, approximately 20% survival) dose 

 50 
 

groups. The study authors attributed these early female mouse deaths to the significant incidence 

of hepatic tumors, and Kano et al. (2009, 594539) reported tumor incidence for all animals in the 

study (N=50), including animals that became moribund or died before the end of the study. 

Additional data on survival rates of mice were provided in a personal communication from 

Dr. Yamazaki (2006, 626614). Dr. Yamazaki reported that the survival of mice was low in all 

male groups (31/50, 33/50, 25/50 and 26/50 in control, low-, mid-, and high-dose groups, 

respectively) and particularly low in high-dose females (29/50, 29/50, 17/50, and 5/50 in control, 

low-, mid-, and high-dose groups, respectively). These deaths occurred primarily during the 

second year of the study. Survival at 12 months in male mice was 50/50, 48/50, 50/50, and 

48/50 in control, low-, mid-, and high-dose groups, respectively. Female mouse survival at 

12 months was 50/50, 50/50, 48/50, and 48/50 in control, low-, mid-, and high-dose groups, 

respectively (Yamazaki, 2006, 626614). Furthermore, these deaths were primarily tumor related. 

Liver tumors were listed as the cause of death for 31 of the 45 pretermination deaths in high-dose 

female Crj:BDF1 mice (Yamazaki, 2006, 626614). For mice, growth and mortality rates were 

reported in Kano et al. (2009, 594539) for the duration of the study. Similar to rats, the growth 

rates of male and female mice were slower than controls and terminal body weights were lower 

for the mid (p < 0.01 for males administered 191 mg/kg-day and p < 0.05 for females 

administered 278 mg/kg-day) and high doses (p < 0.05 for males and females administered 677 

and 964 mg/kg-day, respectively). 

Food consumption was not significantly affected, but water consumption was reduced 

26% in high-dose male mice and 28% in high-dose female mice. Final BWs were reduced 43% 

in high-dose male mice and 15 and 45% in mid- and high-dose female mice, respectively. Male 

mice showed increases in RBC counts, hemoglobin, and hematocrit, whereas in female mice, 

there was a decrease in platelets in mid- and high-dose rats. With the exception of a 60% 

decrease in platelets in high-dose female mice, hematological changes were within 15% of 

control values. Serum AST, ALT, LDH, and ALP activities were significantly increased in midand high-dose male mice, whereas LAP and CPK were increased only in high-dose male mice. 

AST, ALT, LDH, and ALP activities were increased in mid- and high-dose female mice, but 

CPK activity was increased only in high-dose female mice. Increases in serum enzyme activities 

ranged from less than two- to sevenfold above control values. Glucose and triglycerides were 

decreased in high-dose males and in mid- and high-dose females. High-dose female mice also 

showed decreases in serum phospholipid and albumin concentrations (not reported in males). 

Blood calcium was lower in high-dose females and was not reported in males. Urinary pH was 

decreased in high-dose males, whereas urinary protein, glucose, and occult blood were increased 

in mid- and high-dose female mice. Relative and absolute lung weights were increased in highdose males and in mid- and high-dose females (JBRC, 1998, 196240). Microscopic examination 

of the tissues for nonneoplastic lesions showed significant alterations in the epithelium of the 

respiratory tract, mainly in high-dose animals, although some changes occurred in mid-dose mice 

 51 
 

(Tables 4-12 and 4-13). Commonly seen alterations included nuclear enlargement, atrophy, and 

inflammation of the epithelium. Other notable changes observed included nuclear enlargement 

of the proximal tubule of the kidney and angiectasis in the liver in high-dose male mice. 

Table 4-12. Incidence of histopathological lesions in male Crj:BDF1 mice 

exposed to 1,4-dioxane in drinking water for 2 years 

Dose (mg/kg-day)a,b

0 49 191 677 

Nuclear enlargement; nasal respiratory epitheliumc 0/50 0/50 0/50 31/50e

Nuclear enlargement; nasal olfactory epitheliumc 0/50 0/50 9/50e 49/50e

Atrophy; nasal olfactory epitheliumd 0/50 0/50 1/50 48/50 

Inflammation; nasal cavityd 1/50 2/50 1/50 25/50 

Atrophy; tracheal epitheliumd 0/50 0/50 0/50 42/50 

Nuclear enlargement; tracheal epitheliumd 0/50 0/50 0/50 17/50 

Nuclear enlargement; bronchial epitheliumd 0/50 0/50 0/50 41/50 

Atrophy; lung/bronchial epitheliumd 0/50 0/50 0/50 43/50 

Accumulation of foamy cells; lungd 1/50 0/50 0/50 27/50 

Angiectasis; liverd 2/50 3/50 4/50 16/50 

Nuclear enlargement; kidney proximal tubuled 0/50 0/50 0/50 39/50 

a

Data presented for all animals, including animals that became moribund or died before the end of the study. b

Dose levels from Kano et al. (2009, 594539). c

Data from Kano et al. (2009, 594539). d

Data from JBRC (1998, 196240). JBRC did not report statistical significance for the “All animals” 

comparison. 

e

p < 0.01 by χ

2

 test. 

Sources: Kano et al. (2009, 594539) and JBRC (1998, 196240). 

 52 
 

Table 4-13. Incidence of histopathological lesions in female Crj:BDF1 mice 

exposed to 1,4-dioxane in drinking water for 2 years 

Dose (mg/kg-day)a,b

0 66 278 964 

Nuclear enlargement; nasal respiratory epitheliumc 0/50 0/50 0/50 41/50e

Nuclear enlargement; nasal olfactory epitheliumc 0/50 0/50 41/50e 33/50e

Atrophy; nasal olfactory epitheliumd 0/50 0/50 1/50 42/50

Inflammation; nasal cavityd 2/50 0/50 7/50 42/50

Atrophy; tracheal epitheliumd 0/50 0/50 2/50 49/50

Nuclear enlargement; bronchial epitheliumd 0/50 1/50 22/50 48/50

Atrophy; lung/bronchial epitheliumd 0/50 0/50 7/50 50/50

Accumulation of foamy cells; lungd 0/50 1/50 4/50 45/50

a

Data presented for all animals, including animals that became moribund or died before the end of the study. b

Dose levels from Kano et al. (2009, 594539). c

Data from Kano et al. (2009, 594539). d

Data from JBRC (1998, 196240). JBRC did not report statistical significance for the “All animals” 

comparison. 

e

p < 0.01 by χ

2

 test. 

Sources: Kano et al. (2009, 594539) and JBRC (1998, 196240). 

NOAEL and LOAEL values for mice in this study were identified by EPA as 66 and 

278 mg/kg-day, respectively, based on nasal inflammation observed in female mice. Nuclear 

enlargement of the nasal olfactory epithelium and bronchial epithelium was also observed at a 

dose of 278 mg/kg-day in female mice; however, it is unclear whether these alterations represent 

adverse toxicological effects. The serum chemistry changes seen in terminal blood samples from 

male and female mice (mid- and high-dose groups) are likely related to tumor formation in these 

animals. Liver angiectasis, an abnormal dilatation and/or lengthening of a blood or lymphatic 

vessel, was seen in male mice given 1,4-dioxane at a dose of 677 mg/kg-day. 

Treatment with 1,4-dioxane resulted in an increase in the formation of liver tumors 

(adenomas and carcinomas) in male and female mice. The incidence of hepatocellular adenoma 

was statistically increased in male mice in the mid-dose group only. The incidence of male mice 

with hepatocellular carcinoma or either tumor type (adenoma or carcinoma) was increased in the 

low, mid, and high-dose groups. The appearance of the first liver tumor occurred in male mice at 

64, 74, 63, and 59 weeks in the control, low- mid-, and high-dose groups, respectively 

(Yamazaki, 2006, 626614). In female mice, increased incidence was observed for hepatocellular 

carcinoma in all treatment groups, while an increase in hepatocellular adenoma incidence was 

only seen in the 66 and 278 mg/kg-day dose groups (Table 4-14). The appearance of the first 

liver tumor in female mice occurred at 95, 79, 71, and 56 weeks in the control, low-, mid-, and 

high-dose groups, respectively (Yamazaki, 2006, 626614). The tumor incidence data presented 

for male and female mice in Table 4-14 are based on reanalyzed sample data presented in Kano 

 53 
 

et al. (2009, 594539) that included lesions in animals that became moribund or died prior to the 

completion of the 2-year study. 

Katagiri et al. (1998, 193804) summarized the incidence of hepatocellular adenomas and 

carcinomas in control male and female BDF1 mice from ten 2-year bioassays at the JBRC. For 

female mice, out of 499 control mice, the incidence rates were 4.4% for hepatocellular adenomas 

and 2.0% for hepatocellular carcinomas. Kano et al. (2009, 594539) reported a 10% incidence 

rate for hepatocellular adenomas and a 0% incidence rate for hepatocellular carcinomas in 

control female BDF1. The background incidence rates for male BDF1 mice were 15% and 

22.8% for hepatocellular adenomas and carcinomas, respectively, out of 500 control mice in ten 

2-year bioassays (Katagiri et al., 1998, 193804). Background rates for B6C3F1 mice evaluated 

by the National Toxicology Program are similar (10.3% and 21.3% for hepatocellular adenomas 

and carcinomas in male mice, respectively; 4.0% and 4.1% for hepatocellular adenomas and 

carcinomas in female mice, respectively) to the BDF1 mice background rates observed by JBRC 

(Haseman et al., 1984, 020667). Thus, the BDF1 mouse is not particularly sensitive compared to 

the commonly used B6C3F1 strain and indicates that the results obtained by JBRC are 

reasonable. 

Table 4-14. Incidence of tumors in Crj:BDF1 mice exposed to 1,4-dioxane 

in drinking water for 2 years 

Males Females 

Dose (mg/kg-day) 0 49 191 677 0 66 278 964 

Nasal Cavity

Adenocarcinoma 0/50 0/50 0/50 0/50 0/50 0/50 0/50 1/50 

Esthesioneuroepithelioma 0/50 0/50 0/50 1/50 0/50 0/50 0/50 0/50 

Liver

Hepatocellular adenoma 9/50 17/50 23/50a 11/50 5/50 31/50a 20/50a 3/50 

Hepatocellular carcinoma 15/50 20/50 23/50 36/50a,b 0/50 6/50c 30/50a 45/50a,b

Either hepatocellular 

adenoma or carcinoma 23/50 31/50 37/50c 40/50a,b 5/50 35/50a 41/50a 46/50a,b

a

Significantly different from control by Fisher’s exact test (p < 0.01). b

Statistically significant trend for increased tumor incidence by Peto’s test (p < 0.01). c

Significantly different from control by Fisher’s exact test (p < 0.05). 

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

A weight of evidence evaluation of the carcinogenicity studies presented in Section 

4.2.1.2 is located in Section 4.7 and Table 4-19. 

 54 
 

4.2.2. Inhalation Toxicity 

4.2.2.1. Subchronic Inhalation Toxicity 

4.2.2.1.1. Fairley et al. Rabbits, guinea pigs, rats, and mice (3–6/species/group) were exposed 

to 1,000, 2,000, 5,000, or 10,000 ppm of 1,4-dioxane vapor two-times a day for 1.5 hours 

(3 hours/day) for 5 days/week and 1.5 hours on the 6th day (16.5 hours/week) (Fairley et al., 

1934, 062919). Animals were exposed until death occurred or were sacrificed at varying time 

periods. At the 10,000 ppm concentration, only one animal (rat) survived a 7-day exposure. The 

rest of the animals (six guinea pigs, three mice, and two rats) died within the first five exposures. 

Severe liver and kidney damage and acute vascular congestion of the lungs were observed in 

these animals. Kidney damage was described as patchy degeneration of cortical tubules with 

vascular congestion and hemorrhage. Liver lesions varied from cloudy hepatocyte swelling to 

large areas of necrosis. At 5,000 ppm, mortality was observed in two mice and one guinea pig 

following 15–34 exposures. The remaining animals were sacrificed following 49.5 hours 

(3 weeks) of exposure (three rabbits) or 94.5 hours (5 weeks) of exposure (three guinea pigs). 

Liver and kidney damage in both dead and surviving animals was similar to that described for 

the 10,000 ppm concentration. Animals (four rabbits, four guinea pigs, six rats, and five mice) 

were exposed to 2,000 ppm for 45–102 total exposure hours (approximately 2–6 weeks). Kidney 

and liver damage was still apparent in animals exposed to this concentration. Animals exposed 

to 1,000 ppm were killed at intervals with the total exposure duration ranging between 78 and 

202.5 hours (approximately 4–12 weeks). Cortical kidney degeneration and hepatocyte 

degeneration and liver necrosis were observed in these animals (two rabbits, three guinea pigs, 

three rats, and four mice). The low concentration of 1,000 ppm was identified by EPA as a 

LOAEL for liver and kidney degeneration in rats, mice, rabbits, and guinea pigs in this study. 

4.2.2.2. Chronic Inhalation Toxicity and Carcinogenicity 

4.2.2.2.1. Torkelson et al. Whole body exposures of male and female Wistar rats (288/sex) to 

1,4-dioxane vapors (99.9% pure) at a concentration of 0.4 mg/L (111 ppm), were carried out 

7 hours/day, 5 days/week for 2 years (Torkelson et al., 1974, 094807). The age of the animals at 

the beginning of the study was not provided. The concentration of 1,4-dioxane vapor during 

exposures was determined with infrared analyzers. Food and water were available ad libitum 

except during exposures. Endpoints examined included clinical signs, eye and nasal irritation, 

skin condition, respiratory distress, and tumor formation. BWs were determined weekly. 

Standard hematological parameters were determined on all surviving animals after 16 and 

23 months of exposure. Blood collected at termination was used also for determination of 

clinical chemistry parameters (serum AST and ALP activities, blood urea nitrogen [BUN], and 

total protein). Liver, kidneys, and spleen were weighed and the major tissues and organs were 

 55 
 

processed for microscopic examination (lungs, trachea, thoracic lymph nodes, heart, liver, 

pancreas, stomach, intestine, spleen, thyroid, mesenteric lymph nodes, kidneys, urinary bladder, 

pituitary, adrenals, testes, ovaries, oviduct, uterus, mammary gland, lacrimal gland, lymph nodes, 

brain, vagina, and bone marrow, and any abnormal growths). Nasal tissues were not obtained for 

histopathological evaluation. Control and experimental groups were compared statistically using 

Student’s t test, Yates corrected χ

2

 test, or Fisher’s Exact test. 

Exposure to 1,4-dioxane vapors had no significant effect on mortality or BW gain and 

induced no signs of eye or nasal irritation or respiratory distress. Slight, but statistically 

significant, changes in hematological and clinical chemistry parameters were within the normal 

physiological limits and were considered to be of no toxicological importance by the 

investigators. Altered hematological parameters included decreases in packed cell volume, RBC 

count, and hemoglobin, and an increase in WBC count in male rats. Clinical chemistry changes 

consisted of a slight decrease in both BUN (control—23 ± 9.9; 111-ppm 1,4-dioxane—19.8 ± 

8.8) and ALP activity (control—34.4 ± 12.1; 111-ppm 1,4-dioxane—29.9 ± 9.2) and a small 

increase in total protein (control—7.5 ± 0.37; 111-ppm 1,4-dioxane—7.9 ± 0.53) in male rats 

(values are mean ± standard deviation). Organ weights were not significantly affected. 

Microscopic examination of organs and tissues did not reveal any treatment-related effects. 

Based of the lack of significant effects on several endpoints, EPA identified the exposure 

concentration of 0.4 mg/L (111 ppm) as a free standing NOAEL. The true NOAEL was likely to 

be higher. 

Tumors, observed in all groups including controls, were characteristic of the rat strain 

used and were considered unrelated to 1,4-dioxane inhalation. The most common tumors were 

reticulum cell sarcomas and mammary tumors. Using Fisher’s Exact test and a significance level 

of p < 0.05, no one type of tumor occurred more frequently in treated rats than in controls. No 

hepatic or nasal cavity tumors were seen in any rat. 

4.2.3. Initiation/Promotion Studies 

4.2.3.1. Bull et al. 

Bull et al. (1986, 194336) tested 1,4-dioxane as a cancer initiator in mice using oral, 

subcutaneous, and topical routes of exposure. A group of 40 female SENCAR mice (6–8 weeks 

old) was administered a single dose of 1,000 mg/kg 1,4-dioxane (purity >99%) by gavage, 

subcutaneous injection, or topical administration (vehicle was not specified). A group of rats 

was used as a vehicle control (number of animals not specified). Food and water were provided 

ad libitum. Two weeks after administration of 1,4-dioxane, 12-O-tetradecanoylphorbol-13-

acetate (TPA) (1.0 μg in 0.2 mL of acetone) was applied to the shaved back of mice 

3 times/week for a period of 20 weeks. The yield of papillomas at 24 weeks was selected as a 

potential predictor of carcinoma yields at 52 weeks following the start of the promotion 

 56 
 

schedule. Acetone was used instead of TPA in an additional group of 20 mice in order to 

determine whether a single dose of 1,4-dioxane could induce tumors in the absence of TPA 

promotion. 

1,4-Dioxane did not increase the formation of papillomas compared to mice initiated with 

vehicle and promoted with TPA, indicating lack of initiating activity under the conditions of the 

study. Negative results were obtained for all three exposure routes. A single dose of 

1,4-dioxane did not induce tumors in the absence of TPA promotion. 

4.2.3.2. King et al. 

1,4-Dioxane was evaluated for complete carcinogenicity and tumor promotion activity in 

mouse skin (King et al., 1973, 029390). In the complete carcinogenicity study, 0.2 mL of a 

solution of 1,4-dioxane (purity not specified) in acetone was applied to the shaved skin of the 

back of Swiss Webster mice (30/sex) 3 times/week for 78 weeks. Acetone was applied to the 

backs of control mice (30/sex) for the same time period. In the promotion study, each animal 

was treated with 50 μg of dimethylbenzanthracene 1 week prior to the topical application of the 

1,4-dioxane solution described above (0.2 mL, 3 times/week, 78 weeks) (30 mice/sex). Acetone 

vehicle was used in negative control mice (30/sex). Croton oil was used as a positive control in 

the promotion study (30/sex). Weekly counts of papillomas and suspect carcinomas were made 

by gross examination. 1,4-Dioxane was also administered in the drinking water (0.5 and 1%) to 

groups of Osborne-Mendel rats (35/sex/group) and B6C3F1 mice for 42 weeks (control findings 

were only reported for 34 weeks). 

1,4-Dioxane was negative in the complete skin carcinogenicity test using dermal 

exposure. One treated female mouse had malignant lymphoma; however, no papillomas were 

observed in male or female mice by 60 weeks. Neoplastic lesions of the skin, lungs, and kidney 

were observed in mice given the promotional treatment with 1,4-dioxane. In addition, the 

percentage of mice with skin tumors increased sharply after approximately 10 weeks of 

promotion treatment. Significant mortality was observed when 1,4-dioxane was administered as 

a promoter (only 4 male and 5 female mice survived for 60 weeks), but not as a complete 

carcinogen (22 male and 25 female mice survived until 60 weeks). The survival of acetonetreated control mice in the promotion study was not affected (29 male and 26 female mice 

survived until 60 weeks); however, the mice treated with croton oil as a positive control 

experienced significant mortality (0 male and 1 female mouse survived for 60 weeks). The 

incidence of mice with papillomas was similar for croton oil and 1,4-dioxane; however, the 

tumor multiplicity (i.e., number of tumors/mouse) was higher for the croton oil treatment. 

Oral administration of 1,4-dioxane in drinking water caused appreciable mortality in rats, 

but not mice, and increased weight gain in surviving rats and male mice. Histopathological 

lesions (i.e., unspecified liver and kidney effects) were also reported in exposed male and female 

rats; however, no histopathological changes were indicated for mice. 

 57 
 

1,4-Dioxane was demonstrated to be a tumor promoter, but not a complete carcinogen in 

mouse skin, in this study. Topical administration for 78 weeks following initiation with 

dimethylbenzanthracene caused an increase in the incidence and multiplicity of skin tumors in 

mice. Tumors were also observed at remote sites (i.e., kidney and lung), and survival was 

affected. Topical application of 1,4-dioxane for 60 weeks in the absence of the initiating 

treatment produced no effects on skin tumor formation or mortality in mice. 

4.2.3.3. Lundberg et al. 

Lundberg et al. (1987, 062933) evaluated the tumor promoting activity of 1,4-dioxane in 

rat liver. Male Sprague Dawley rats (8/dose group, 19 for control group) weighing 200 g 

underwent a partial hepatectomy followed 24 hours later by an i.p. injection of 30 mg/kg 

diethylnitrosamine (DEN) (initiation treatment). 1,4-Dioxane (99.5% pure with 25 ppm 

butylated hydroxytoluene as a stabilizer) was then administered daily by gavage (in saline 

vehicle) at doses of 0, 100, or 1,000 mg/kg-day, 5 days/week for 7 weeks. Control rats were 

administered saline daily by gavage, following DEN initiation. 1,4-Dioxane was also 

administered to groups of rats that were not given the DEN initiating treatment (saline used 

instead of DEN). Ten days after the last dose, animals were sacrificed and liver sections were 

stained for GGT. The number and total volume of GGT-positive foci were determined. 

1,4-Dioxane did not increase the number or volume of GGT-foci in rats that were not 

given the DEN initiation treatment. The high dose of 1,4-dioxane (1,000 mg/kg-day) given as a 

promoting treatment (i.e., following DEN injection) produced an increase in the number of 

GGT-positive foci and the total foci volume. Histopathological changes were noted in the livers 

of high-dose rats. Enlarged, foamy hepatocytes were observed in the midzonal region of the 

liver, with the foamy appearance due to the presence of numerous fat-containing cytoplasmic 

vacuoles. These results suggest that cytotoxic doses of 1,4-dioxane may be associated with 

tumor promotion of 1,4-dioxane in rat liver. 

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND INHALATION 

4.3.1. Giavini et al. 

Pregnant female Sprague Dawley rats (18–20 per dose group) were given 1,4-dioxane 

(99% pure, 0.7% acetal) by gavage in water at concentrations of 0, 0.25, 0.5, or 1 mL/kg-day, 

corresponding to dose estimates of 0, 250, 500, or 1,000 mg/kg-day (density of 1,4-dioxane is 

approximately 1.03 g/mL) (Giavini et al., 1985, 062924). The chemical was administered at a 

constant volume of 3 mL/kg on days 6–15 of gestation. Food consumption was determined daily 

and BWs were measured every 3 days. The dams were sacrificed with chloroform on 

gestation day 21 and the numbers of corpora lutea, implantations, resorptions, and live fetuses 

were recorded. Fetuses were weighed and examined for external malformations prior to the 

 58 
 

evaluation of visceral and skeletal malformations (Wilson’s free-hand section method and 

staining with Alizarin red) and a determination of the degree of ossification. 

Maternal weight gain was reduced by 10% in the high-dose group (1,000 mg/kg-day). 

Food consumption for this group was 5% lower during the dosing period, but exceeded control 

levels for the remainder of the study. No change from control was observed in the number of 

implantations, live fetuses, or resorptions; however, fetal birth weight was 5% lower in the 

highest dose group (p < 0.01). 1,4-Dioxane exposure did not increase the frequency of major 

malformations or minor anomalies and variants. Ossification of the sternebrae was reduced in 

the 1,000 mg/kg-day dose group (p < 0.05). The study authors suggested that the observed delay 

in sternebrae ossification combined with the decrease in fetal birth weight indicated a 

developmental delay related to 1,4-dioxane treatment. NOAEL and LOAEL values of 500 and 

1,000 mg/kg-day were identified from this study by EPA and based on delayed ossification of 

the sternebrae and reduced fetal BWs. 

4.4. OTHER DURATION OR ENDPOINT-SPECIFIC STUDIES 

4.4.1. Acute and Short-term Toxicity 

The acute (≤ 24 hours) and short-term toxicity studies (<30 days) of 1,4-dioxane in 

laboratory animals are summarized in Table 4-15. Several exposure routes were employed in 

these studies, including dermal application, drinking water exposure, gavage, vapor inhalation, 

and i.v. or i.p. injection. 

4.4.1.1. Oral Toxicity 

Mortality was observed in many acute high-dose studies, and LD50 values for 

1,4-dioxane were calculated for rats, mice, and guinea pigs (Laug et al., 1939, 195055; see Table 

4-15; Pozzani et al., 1959, 063019; Smyth et al., 1941, 060695). Clinical signs of CNS 

depression were observed, including staggered gait, narcosis, paralysis, coma, and death 

(de Navasquez, 1935, 196174; Laug et al., 1939, 195055; Nelson, 1951, 196087; Schrenk and 

Yant, 1936, 195076). Severe liver and kidney degeneration and necrosis were often seen in 

acute studies (David, 1964, 195954; de Navasquez, 1935, 196174; JBRC, 1998, 196242; Kesten 

et al., 1939, 194972; Laug et al., 1939, 195055; Schrenk and Yant, 1936, 195076). JBRC (1998, 

196242) additionally reported histopathological lesions in the nasal cavity and the brain of rats 

following 2 weeks of exposure to 1,4-dioxane in the drinking water. 

4.4.1.2. Inhalation Toxicity 

Acute and short-term toxicity studies (all routes) are summarized in Table 4-15. 

Mortality occurred in many high-concentration studies (Nelson, 1951, 196087; Pozzani et al., 

1959, 063019; Wirth and Klimmer, 1936, 196105). Inhalation of 1,4-dioxane caused eye and 

nasal irritation, altered respiration, and pulmonary edema and congestion (Yant et al., 1930, 

 59 
 

062952). Clinical signs of CNS depression were observed, including staggered gait, narcosis, 

paralysis, coma, and death (Nelson, 1951, 196087; Wirth and Klimmer, 1936, 196105). Liver 

and kidney degeneration and necrosis were also seen in acute and short-term inhalation studies 

(Drew et al., 1978, 067913; Fairley et al., 1934, 062919). 

Table 4-15. Acute and short-term toxicity studies of 1,4-dioxane 

Animal Exposure route Test conditions Results Dosea Reference 

Oral studies 

Rat (inbred strain 

and gender 

unspecified) 

Oral via 

drinking water 

1–10 days of 

exposure 

Ultrastructural 

changes in the 

kidney, degenerative 

nephrosis, hyaline 

droplet accumulation, 

crystal formation in 

mitochondria 

11,000 mg/kg-day 

(5%) 

David (1964, 

195954) 

Rat (strain and 

gender unspecified) 

Oral via 

drinking water 

5–12 days of 

exposure 

Extensive 

degeneration of the 

kidney, liver damage, 

mortality in 

8/10 animals by 

12 days 

11,000 mg/kg-day 

(5%) 

Kesten et al. 

(1939, 

194972) 

F344/DuCrj rat Oral via 

drinking water 

14-Day exposure Mortality, decreased 

BWs, 

histopathological 

lesions in the nasal 

cavity, liver, kidney, 

and brain 

2,500 mg/kg-day 

(nuclear 

enlargement of 

olfactory epithelial 

cells), 

>7,500 mg/kg-day 

for all other effects 

JBRC (1998, 

196242) 

Female 

Sprague Dawley rat 

Gavage 0, 168, 840, 2550, 

or 4,200 mg/kg by 

gavage, 21 and 

4 hours prior to 

sacrifice 

Increased ODC 

activity, hepatic 

CYP450 content, and 

DNA single-strand 

breaks 

840 mg/kg (ODC 

activity only) 

Kitchin and 

Brown (1990, 

062928) 

Female Carworth 

Farms-Nelson rat 

Gavage Determination of a 

single dose LD50

Lethality LD50 = 6,400 mg/kg 

(14,200 ppm) 

Pozzani et al. 

(1959, 

063019) 

Male Wistar rat, 

guinea pig 

Gavage Single dose, 

LD50 determination

Lethality LD50 (mg/kg): 

rat = 7,120 

guinea pig = 3,150 

Smyth et al. 

(1941, 

060695) 

 60 
 

Animal Exposure route Test conditions Results Dosea Reference 

Rat, mouse, guinea 

pig 

Gavage Single dose; 

several dose 

groups 

Clinical signs of CNS 

depression, stomach 

hemorrhage, kidney 

enlargement, and 

liver and kidney 

degeneration 

LD50 (mg/kg): 

mouse = 5,900 

rat = 5,400 

guinea pig = 4,030 

Laug et al. 

(1939, 

195055) 

Rabbit Gavage Single gavage dose 

of 0, 207, 1,034, or 

2,068 mg/kg-day 

Clinical signs of CNS 

depression, mortality 

at 2068 mg/kg, renal 

toxicity (polyuria 

followed by anuria), 

histopathological 

changes in liver and 

kidneys 

1,034 mg/kg-day de Navasquez

(1935, 

196174) 

Rat, rabbit Gavage Single dose; 

mortality after 

2 weeks 

Mortality and 

narcosis 

3,160 mg/kg Nelson (1951, 

196087) 

Crj:BDF1 mouse Oral via 

drinking water 

14-Day exposure Mortality, decreased 

BWs, 

histopathological 

lesions in the nasal 

cavity, liver, kidney, 

and brain 

10,800 mg/kg-day; 

hepatocellular 

swelling 

JBRC (1998, 

196242) 

Dog Drinking water 

ingestion 

3–10 days of 

exposure 

Clinical signs of CNS 

depression, and liver 

and kidney 

degeneration 

11,000 mg/kg-day 

(5%) 

Schrenk and 

Yant (1936, 

195076) 

Inhalation studies 

Male CD1 rat Vapor 

inhalation 

Serum enzymes 

measured before 

and after a single 

4 hour exposure 

Increase in ALT, 

AST, and OCT; no 

change in G-6-Pase 

1,000 ppm Drew et al. 

(1978, 

067913) 

Rat Vapor 

inhalation 

5 hours of 

exposure 

Mortality and 

narcosis 6,000 ppm Nelson (1951,196087) 

Female Carworth 

Farms-Nelson rat 

Vapor 

inhalation 

Determination of a 

4-hour inhalation 

LC50 

Lethality LC50 = 51.3 mg/L Pozzani et al. 

(1959, 

063019) 

Mouse, cat Vapor 

inhalation 

8 hours/day for 

17 days 

Paralysis and death 8,400 ppm Wirth and 

Klimmer 

(1936, 

196105) 

Guinea pig Vapor 

inhalation 

8-Hour exposure to 

0.1–3% by volume

Eye and nasal 

irritation, retching 

movements, altered 

respiration, narcosis, 

pulmonary edema 

and congestion, 

hyperemia of the 

brain 

0.5% by volume Yant et al. 

(1930, 

062952) 

Rabbit, guinea pig, 

rat, mouse 

Vapor 

inhalation 

3 hours exposure, 

for 5 days; 

1.5 hour exposure 

for 1 day 

Degeneration and 

necrosis in the kidney 

and liver, vascular 

congestion in the 

lungs 

10,000 ppm Fairley et 

al.(1934, 

062919) 

 61 
 

Animal Exposure route Test conditions Results Dosea Reference 

Other routes 

Male COBS/Wistar 

rat 

Dermal Nonoccluded 

technique using 

shaved areas of the 

back and flank; 

single application, 

14-day observation

Negative; no effects 

noted 

8,300 mg/kg Clark et al. 

(1984, 

194970) 

Rabbit, cat i.v. injection Single injection of 

0, 207, 1,034, 

1,600 mg/kg-day 

Clinical signs of CNS 

depression, narcosis 

at 1,034 mg/kg, 

mortality at 

1,600 mg/kg 

1,034 mg/kg-day de Navasquez

(1935, 

196174) 

Female 

Sprague Dawley rat 

i.p. injection Single dose; 

LD50 values 

determined 

24 hours and 

14 days after 

injection 

Increased serum SDH 

activity at 1/16th of 

the LD50 dose; no 

change at higher or 

lower doses 

LD50 (mg/kg): 

24 hours = 4,848 

14 days = 799 

Lundberg et 

al. (1986, 

062934) 

CBA/J mouse i.p. injection Daily injection for 

7 days, 0, 0.1, 1, 5, 

and 10% 

Slightly lower 

lymphocyte response 

to mitogens 

2,000 mg/kg-day 

(10%) 

Thurman et 

al. (1978, 

018767) 

a

Lowest effective dose for positive results/ highest dose tested for negative results. 

ND = no data; OCT = ornithine carbamyl transferase; ODC = ornithine decarboxylase; SDH = sorbitol 

dehydrogenase 

4.4.2. Neurotoxicity 

Clinical signs of CNS depression have been reported in humans and laboratory animals 

following high dose exposure to 1,4-dioxane (see Sections 4.1 and 4.2.1.1). Neurological 

symptoms were reported in the fatal case of a worker exposed to high concentrations of 

1,4-dioxane through both inhalation and dermal exposure (Johnstone, 1959, 062927). These 

symptoms included headache, elevation in blood pressure, agitation and restlessness, and coma. 

Autopsy findings demonstrated perivascular widening in the brain, with small foci of 

demyelination in several regions (e.g., cortex, basal nuclei). It was suggested that these 

neurological changes may have been secondary to anoxia and cerebral edema. In laboratory 

animals, the neurological effects of acute high-dose exposure included staggered gait, narcosis, 

paralysis, coma, and death (de Navasquez, 1935, 196174; Laug et al., 1939, 195055; Nelson, 

1951, 196087; Schrenk and Yant, 1936, 195076; Yant et al., 1930, 062952). The neurotoxicity 

of 1,4-dioxane was further investigated in several studies described below (Frantik et al., 1994, 

067510; Goldberg et al., 1964, 058035; Kanada et al., 1994, 078052; Knoefel, 1935, 195914). 

4.4.2.1. Frantik et al. 

The acute neurotoxicity of 1,4-dioxane was evaluated following a 4-hour inhalation 

exposure to male Wistar rats (four per dose group) and a 2-hour inhalation exposure to female 

H-strain mice (eight per dose group) (Frantik et al., 1994, 067510). Three exposure groups and a 

 62 
 

control group were used in this study. Exposure concentrations were not specified, but 

apparently were chosen from the linear portion of the concentration-effect curve. The 

neurotoxicity endpoint measured in this study was the inhibition of the propagation and 

maintenance of an electrically-evoked seizure discharge. This endpoint has been correlated with 

the behavioral effects and narcosis that occur following acute exposure to higher concentrations 

of organic solvents. Immediately following 1,4-dioxane exposure, a short electrical impulse was 

applied through ear electrodes (0.2 seconds, 50 hertz (Hz), 180 volts (V) in rats, 90 V in mice). 

Several time characteristics of the response were recorded; the most sensitive and reproducible 

measures of chemically-induced effects were determined to be the duration of tonic hind limb 

extension in rats and the velocity of tonic extension in mice. 

Linear regression analysis of the concentration-effect data was used to calculate an 

isoeffective air concentration that corresponds to the concentration producing a 30% decrease in 

the maximal response to an electrically-evoked seizure. The isoeffective air concentrations for 

1,4-dioxane were 1,860 ± 200 ppm in rats and 2,400 ± 420 ppm in mice. A NOAEL value was 

not identified from this study. 

4.4.2.2. Goldberg et al. 

Goldberg et al. (1964, 058035) evaluated the effect of solvent inhalation on pole climb 

performance in rats. Female rats (Carworth Farms Elias strain) (eight per dose group) were 

exposed to 0, 1,500, 3,000, or 6,000 ppm of 1,4-dioxane in air for 4 hours/day, 5 days/weeks, for 

10 exposure days. Conditioned avoidance and escape behaviors were evaluated using a pole 

climb methodology. Prior to exposure, rats were trained to respond to a buzzer or shock stimulus 

by using avoidance/escape behavior within 2 seconds. Behavioral criteria were the abolishment 

or significant deferment (>6 seconds) of the avoidance response (conditioned or buzzer response) 

or the escape response (buzzer plus shock response). Behavioral tests were administered on day 

1, 2, 3, 4, 5, and 10 of the exposure period. Rat BWs were also measured on test days. 

1,4-Dioxane exposure produced a dose-related effect on conditioned avoidance behavior 

in female rats, while escape behavior was generally not affected. In the 1,500 ppm group, only 

one of eight rats had a decreased avoidance response, and this only occurred on days 2 and 5 of 

exposure. A larger number of rats exposed to 3,000 ppm (two or three of eight) experienced a 

decrease in the avoidance response, and this response was observed on each day of the exposure 

period. The maximal decrease in the avoidance response was observed in the 6,000 ppm group 

during the first 2 days of exposure (75–100% of the animals were inhibited in this response). For 

exposure days 3–10, the percent of rats in the 6,000 ppm group with significant inhibition of the 

avoidance response ranged from 37–62%. At the end of the exposure period (day 10), the BWs 

for rats in the high exposure group were lower than controls. 

 63 
 

4.4.2.3. Kanada et al. 

Kanada et al. evaluated the effect of oral exposure to 1,4-dioxane on the regional 

neurochemistry of the rat brain (Kanada et al., 1994, 078052). 1,4-Dioxane was administered by 

gavage to male Sprague Dawley rats (5/group) at a dose of 1,050 mg/kg, approximately equal to 

one-fourth the oral LD50. Rats were sacrificed by microwave irradiation to the head 2 hours 

after dosing, and brains were dissected into small brain areas. Each brain region was analyzed 

for the content of biogenic amine neurotransmitters and their metabolites using highperformance liquid chromatography (HPLC) or GC methods. 1,4-Dioxane exposure was shown 

to reduce the dopamine and serotonin content of the hypothalamus. The neurochemical profile 

of all other brain regions in exposed rats was similar to control rats. 

4.4.2.4. Knoefel 

The narcotic potency of 1,4-dioxane was evaluated following i.p. injection in rats and 

gavage administration in rabbits (Knoefel, 1935, 195914). Rats were given i.p. doses of 20, 30, 

or 50 mmol/kg. No narcotic effect was seen at the lowest dose; however, rats given 30 mmol/kg 

were observed to sleep approximately 8–10 minutes. Rats given the high dose of 50 mmol/kg 

died during the study. Rabbits were given 1,4-dioxane at oral doses of 10, 20, 50, 75, or 

100 mmol/kg. No effect on the normal erect animal posture was observed in rabbits treated with 

less than 50 mmol/kg. At 50 and 75 mmol/kg, a semi-erect or staggering posture was observed; 

lethality occurred at both the 75 and 100 mmol/kg doses. 

4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE 

OF ACTION 

4.5.1. Genotoxicity 

The genotoxicity data for 1,4-dioxane are presented in Tables 4-16 and 4-17 for in vitro 

and in vivo tests, respectively. 1,4-Dioxane has been tested for genotoxic potential using in vitro 

assay systems with prokaryotic organisms, non-mammalian eukaryotic organisms, and 

mammalian cells, and in vivo assay systems using several strains of rats and mice. In the large 

majority of in vitro systems, 1,4-dioxane was not genotoxic. Where a positive genotoxic 

response was observed, it was generally observed in the presence of toxicity. Similarly, 

1,4-dioxane was not genotoxic in the majority of available in vivo studies. 1,4-Dioxane did not 

bind covalently to DNA in a single study with calf thymus DNA. Several investigators have 

reported that 1,4-dioxane caused increased DNA synthesis indicative of cell proliferation. 

Overall, the available literature indicates that 1,4-dioxane is nongenotoxic or weakly genotoxic. 

Negative findings were reported for mutagenicity in in vitro assays with the prokaryotic 

organisms Salmonella typhimurium, Escherichia coli, and Photobacterium phosphoreum

(Mutatox assay) (Haworth et al., 1983, 028947; Hellmér and Bolcsfoldi, 1992, 194717; 

 64 
 

Khudoley et al., 1987, 194949; Kwan et al., 1990, 196078; Morita and Hayashi, 1998, 195065; 

Nestmann et al., 1984, 194339; Stott et al., 1981, 063021). In in vitro assays with 

nonmammalian eukaryotic organisms, negative results were obtained for the induction of 

aneuploidy in yeast (Saccharomyces cerevisiae) and in the sex-linked recessive lethal test in 

Drosophila melanogaster (Yoon et al., 1985, 194373; Zimmermann et al., 1985, 194343). In the 

presence of toxicity, positive results were reported for meiotic nondisjunction in Drosophila 

(Munoz and Barnett, 2002, 195066). 

The ability of 1,4-dioxane to induce genotoxic effects in mammalian cells in vitro has 

been examined in model test systems with and without exogenous metabolic activation and in 

hepatocytes that retain their xenobiotic-metabolizing capabilities. 1,4-Dioxane was reported as 

negative in the mouse lymphoma cell forward mutation assay (McGregor et al., 1991, 194381; 

Morita and Hayashi, 1998, 195065). 1,4-Dioxane did not produce chromosomal aberrations or 

micronucleus formation in Chinese hamster ovary (CHO) cells (Galloway et al., 1987, 007768; 

Morita and Hayashi, 1998, 195065). Results were negative in one assay for sister chromatid 

exchange (SCE) in CHO (Morita and Hayashi, 1998, 195065) and were weakly positive in the 

absence of metabolic activation in another (Galloway et al., 1987, 007768). In rat hepatocytes, 

1,4-dioxane exposure in vitro caused single-strand breaks in DNA at concentrations also toxic to 

the hepatocytes (Sina et al., 1983, 007323) and produced a positive genotoxic response in a cell 

transformation assay with BALB/3T3 cells also in the presence of toxicity (Sheu et al., 1988, 

195078). 

1,4-Dioxane was not genotoxic in the majority of available in vivo mammalian assays. 

Studies of micronucleus formation following in vivo exposure to 1,4-dioxane produced mostly 

negative results, including studies of bone marrow micronucleus formation in B6C3F1, BALB/c, 

CBA, and C57BL6 mice (McFee et al., 1994, 195060; Mirkova, 1994, 195062; Tinwell and 

Ashby, 1994, 195086) and micronucleus formation in peripheral blood of CD1 mice (Morita, 

1994, 196085; Morita and Hayashi, 1998, 195065). Mirkova (1994, 195062) reported a doserelated increase in the incidence of bone marrow micronuclei in male and female C57BL6 mice 

24 or 48 hours after administration of 1,4-dioxane. At a sampling time of 24 hours, a dose of 

450 mg/kg produced no change relative to control, while doses of 900, 1,800, and 3,600 mg/kg 

increased the incidence of bone marrow micronuclei by approximately two-, three-, and fourfold, 

respectively. A dose of 5,000 mg/kg also increased the incidence of micronuclei by 

approximately fourfold at 48 hours. This compares with the negative results for BALB/c male 

mice tested in the same study at a dose of 5,000 mg/kg and sampling time of 24 hours. Tinwell 

and Ashby (1994, 195086) could not explain the difference in response in the mouse bone 

marrow micronucleus assay with C57BL6 mice obtained in their laboratory (i.e., non-significant 

1.6-fold increase over control) with the dose-related positive findings reported by Mirkova 

(Mirkova, 1994, 195062) using the same mouse strain, 1,4-dioxane dose (3,600 mg/kg) and 

sampling time (24 hours). Morita and Hayashi (1998, 195065) demonstrated an increase in 

 65 
 

micronucleus formation in hepatocytes following 1,4-dioxane dosing and partial hepatectomy to 

induce cellular mitosis. DNA single-strand breaks were demonstrated in hepatocytes following 

gavage exposure to female rats (Kitchin and Brown, 1990, 062928). 

Roy et al. (2005, 196094) examined micronucleus formation in male CD1 mice exposed 

to 1,4-dioxane to confirm the mixed findings from earlier mouse micronucleus studies and to 

identify the origin of the induced micronuclei. Mice were administered 1,4-dioxane by gavage at 

doses of 0, 1,500, 2,500, and 3,500 mg/kg-day for 5 days. The mice were also implanted with 

5-bromo-2-deoxyuridine (BrdU)-releasing osmotic pumps to measure cell proliferation in the 

liver and to increase the sensitivity of the hepatocyte assay. The frequency of micronuclei in the 

bone marrow erythrocytes and in the proliferating BrdU-labeled hepatocytes was determined 

24 hours after the final dose. Significant dose-related increases in micronuclei were seen in the 

bone-marrow at all the tested doses (≥ 1,500 mg/kg-day). In the high-dose (3,500-mg/kg) mice, 

the frequency of bone marrow erythrocyte micronuclei was about 10-fold greater than the control 

frequency. Significant dose-related increases in micronuclei were also observed at the two 

highest doses (≥ 2,500 mg/kg-day) in the liver. Antikinetochore (CREST) staining or 

pancentromeric fluorescence in situ hybridization (FISH) was used to determine the origin of the 

induced micronuclei. The investigators determined that 80–90% of the micronuclei in both 

tissues originated from chromosomal breakage; small increase in micronuclei originating from 

chromosome loss was seen in hepatocytes. Dose-related statistically significant decreases in the 

ratio of bone marrow polychromatic erythrocytes (PCE):normochromatic erythrocytes (NCE), an 

indirect measure of bone marrow toxicity, were observed. Decreases in hepatocyte proliferation 

were also observed. Based on these results, the authors concluded that at high doses 1,4-dioxane 

exerts genotoxic effects in both the mouse bone marrow and liver; the induced micronuclei are 

formed primarily from chromosomal breakage; and 1,4-dioxane can interfere with cell 

proliferation in both the liver and bone marrow. The authors noted that reasons for the 

discrepant micronucleus assay results among various investigators was unclear, but could be 

related to the inherent variability present when detecting moderate to weak responses using small 

numbers of animals, as well as differences in strain, dosing regimen, or scoring criteria. 

1,4-Dioxane did not affect in vitro or in vivo DNA repair in hepatocytes or in vivo DNA 

repair in the nasal cavity (Goldsworthy et al., 1991, 062925; Stott et al., 1981, 063021), but 

increased hepatocyte DNA synthesis indicative of cell proliferation in several in vivo studies 

(Goldsworthy et al., 1991, 062925; Miyagawa et al., 1999, 195063; Stott et al., 1981, 063021; 

Uno et al., 1994, 194385). 1,4-Dioxane caused a transient inhibition of RNA polymerase A and 

B in the rat liver (Kurl et al., 1981, 195054), indicating a negative impact on the synthesis of 

ribosomal and messenger RNA (DNA transcription). Intravenous administration of 1,4-dioxane 

at doses of 10 or 100 mg/rat produced inhibition of both polymerase enzymes, with a quicker and 

more complete recovery of activity for RNA polymerase A, the polymerase for ribosomal RNA 

synthesis. 

 66 
 

1,4-Dioxane did not covalently bind to DNA under in vitro study conditions (Woo et al., 

1977, 062950). DNA alkylation was also not detected in the liver 4 hours following a single 

gavage exposure (1,000 mg/kg) in male Sprague Dawley rats (Stott et al., 1981, 063021). 

Rosenkranz and Klopman (1992, 004321) analyzed 1,4-dioxane using the computer 

automated structure evaluator (CASE) structure activity method to predict its potential 

genotoxicity and carcinogenicity. The CASE analysis is based on information contained in the 

structures of approximately 3,000 chemicals tested for endpoints related to mutagenic/genotoxic 

and carcinogenic potential. CASE selects descriptors (activating [biophore] or inactivating 

[biophobe] structural fragments) from a learning set of active and inactive molecules. Using the 

CASE methodology, Rosenkranz and Klopman (1992, 004321) predicted that 1,4-dioxane would 

be inactive for mutagenicity in several in vitro systems, including Salmonella, induction of 

chromosomal aberrations in CHO cells, and unscheduled DNA synthesis in rat hepatocytes. 

1,4-Dioxane was predicted to induce SCE in cultured CHO cells, micronuclei formation in rat 

bone marrow, and carcinogenicity in rodents. 

Gene expression profiling in cultured human hepatoma HepG2 cells was performed using 

DNA microarrays to discriminate between genotoxic and other carcinogens (van Delft et al., 

2004, 195087). Van Delft et al. (2004, 195087) examined this method using a training set of 16 

treatments (nine genotoxins and seven nongenotoxins) and a validation set (three and three), with 

discrimination models based on Pearson correlation analyses for the 20 most discriminating 

genes. As reported by the authors (van Delft et al., 2004, 195087), the gene expression profile 

for 1,4-dioxane indicated a classification of this chemical as a “nongenotoxic” carcinogen, and 

thus, 1,4-dioxane was included in the training set as a “nongenotoxic” carcinogen. The accuracy 

for carcinogen classification using this method ranged from 33 to 100%, depending on which 

chemical data sets and gene expression signals were included in the analysis. 

Table 4-16. Genotoxicity studies of 1,4-dioxane; in vitro

Resultsa

Test system Endpoint Test conditions 

Without 

activation

With 

activation Doseb Source 

Prokaryotic organisms in vitro 

S. typhimurium

strains TA98, TA100, 

TA1535, TA1537 

Reverse 

mutation 

Plate incorporation 

assay – – 10,000 μg/plate Haworth et 

al. (1983, 

028947) 

S. typhimurium 

strains TA98, TA100, 

TA1530, TA1535, 

TA1537 

Reverse 

mutation 

Plate incorporation 

assay – – ND Khudoley et 

al. (1987, 

194949) 

S. typhimurium 

strains TA98, TA100, 

TA1535, TA1537 

Reverse 

mutation 

Plate incorporation 

and preincubation 

assays 

– – 5,000 μg/plate Morita and 

Hayashi 

(1998, 

195065) 

 67 
 

Resultsa

Test system Endpoint Test conditions 

Without 

activation

With 

activation Doseb

 Source 

S. typhimurium 

strains TA100, 

TA1535 

Reverse 

mutation 

Preincubation 

assay – – 103 mg Nestmann et 

al. (1984, 

194339) 

S. typhimurium 

strains TA98, TA100, 

TA1535, TA1537, 

TA1538 

Reverse 

mutation 

Plate incorporation 

assay – – 103 mg Stott et al. 

(1981, 

063021) 

E. coli K-12 

uvrB/recA 

DNA repair Host mediated 

assay – – 1,150 mmol/L Hellmer and 

Bolcsfoldi 

(1992, 

194717) 

E. coli

WP2/WP2uvrA

Reverse 

mutation 

Plate incorporation 

and preincubation 

assays 

– – 5,000 μg/plate Morita and 

Hayashi 

(1998, 

195065) 

P. phosphoreum

M169 

Mutagenicity, 

DNA damage 

Mutatox assay – ND ND Kwan et al. 

(1990, 

196078) 

Nonmammalian eukaryotic organisms in vitro 

S. cerevisiae D61.M Aneuploidy Standard 16-hour 

incubation or coldinterruption 

regimen 

–T ND 4.75% Zimmerman 

et al. (1985, 

194343) 

D. melanogaster Meiotic 

nondisjunction 

Oocytes were 

obtained for 

evaluation 24 and 

48 hours after 

mating 

+Tc NDd 2% in sucrose 

media 

Munoz and 

Barnett 

(2002, 

195066) 

D. melanogaster Sex-linked 

recessive lethal 

test 

Exposure by 

feeding and 

injection 

– NDd 35,000 ppm in 

feed, 7 days or 

50,000 ppm 

(5% in water) 

by injection 

Yoon et al. 

(1985, 

194373) 

Mammalian cells in vitro 

Rat hepatocytes DNA damage; 

single-strand 

breaks measured 

by alkaline 

elution 

3-Hour exposure 

to isolated primary 

hepatocytes 

+Te NDd 0.3 mM Sina et al. 

(1983, 

007323) 

Primary hepatocyte 

culture from male 

F344 rats 

DNA repair Autoradiography – NDd 1 mM Goldsworthy 

et al. (1991, 

062925) 

L5178Y mouse 

lymphoma cells 

Forward 

mutation assay 

Thymidine kinase 

mutagenicity assay 

(trifluorothymidin

e resistance) 

– – 5,000 μg/mL McGregor et 

al. (1991, 

194381) 

 68 
 

Resultsa

Test system Endpoint Test conditions 

Without 

activation

With 

activation Doseb

 Source 

L5178Y mouse 

lymphoma cells 

Forward 

mutation assay 

Thymidine kinase 

mutagenicity assay 

(trifluorothymidin

e resistance) 

– –T 5,000 μg/mL Morita and 

Hayashi 

(1998, 

195065) 

BALB/3T3 cells Cell 

transformation 

48-Hour exposure 

followed by 

4 weeks 

incubation; 13 day 

exposure followed 

by 2.5 weeks 

incubation 

+Tf NDd 0.5 mg/mL Sheu et al. 

(1988, 

195078) 

CHO cells SCE BrdU was added 

2 hours after 

1,4-dioxane 

addition; chemical 

treatment was 

2 hours with S9 

and 25 hours 

without S9 

±g – 10,520 μg/mL Galloway et 

al. (1987, 

007768) 

CHO cells Chromosomal 

aberration 

Cells were 

harvested 8–

12 hours or 18–

26 hours after 

treatment (time of 

first mitosis) 

– – 10,520 μg/mL Galloway et 

al. (1987, 

007768) 

CHO cells SCE 3 hour pulse 

treatment; 

followed by 

continuous 

treatment of BrdU 

for 23 or 26 hours 

– – 5,000 μg/mL Morita and 

Hayashi 

(1998, 

195065) 

CHO cells Chromosomal 

aberration 

5 hour pulse 

treatment, 20 hour 

pulse and 

continuous 

treatments, or 

44 hour 

continuous 

treatment; cells 

were harvested 20 

or 44 hours 

following 

exposure 

– – 5,000 μg/mL Morita and 

Hayashi 

(1998, 

195065) 

CHO cells Micronucleus 

formation 

5 hour pulse 

treatment or 

44 hour 

continuous 

treatment; cells 

were harvested 

42 hours following 

exposure 

– – 5,000 μg/mL Morita and 

Hayashi 

(1998, 

195065) 

 69 
 

Resultsa

Test system Endpoint Test conditions 

Without 

activation

With 

activation Doseb

 Source 

Calf thymus DNA Covalent 

binding to DNA 

Incubation with 

microsomes from 

3-methylcholanthr

ene treated rats 

– – 0.04 pmol/mg 

DNA (bound) 

Woo et al. 

(1977, 

062950) 

a

+ = positive, ± = equivocal or weak positive, – = negative, T = toxicity. Endogenous metabolic 

activation is not applicable for in vivo studies. 

b

Lowest effective dose for positive results/highest dose tested for negative results; ND = no data. 

c

Rats were given doses of 0, 168, 840, 2,550, or 4,200 mg/kg at 4 and 21 hours prior to sacrifice. A 43 and 

50% increase in the fraction of DNA eluted was observed for doses of 2,550 and 4,200 mg/kg, 

respectively. Alkaline elution of DNA was not significantly different from control in the two lowest dose 

groups (168 and 840 mg/kg). 

d

A dose-related increase in the incidence of bone marrow micronuclei was observed in male and female 

C57BL6 mice 24 or 48 hours after administration of 1,4-dioxane. A dose of 450 mg/kg produced no 

change relative to control, while doses of 900, 1,800, 3,600, and 5,000 mg/kg increased the incidence of 

bone marrow micronuclei by approximately two-,three-, four- and fourfold, respectively. 

e

A dose-related increase in the incidence of hepatocyte micronuclei was observed in partially 

hepatectomized mice 6 days after administration of 1,4-dioxane. A dose of 1,000 mg/kg produced no 

change relative to control, while doses of 2,000 and 3,000 mg/kg increased the incidence of hepatocyte 

micronuclei by 2.4- and 3.4-fold, respectively. 

f Significant increases in the frequency of micronucleated erythrocytes were observed at each test dose of 

1,4-dioxane (1,500, 2,500 and 3,500 mg/kg-day, 5 days/week). 

g

A dose-related increase in the frequency of micronuclei was observed in proliferating cells with micronuclei at 

2,500 and 3,500 mg/kg-day, 5 days/week. No increase in the frequency of micronuclei was seen in the nonproliferating cells. 

h

No increase in the hepatocyte labeling index was observed 24 or 48 hours following a single gavage 

exposure of 1,000 mg/kg. Continuous administration of 1% 1,4-dioxane in the drinking water for up to 

2 weeks produced a twofold increase in the hepatocyte labeling index. 

i

A similar pattern of RNA polymerase inhibition was observed at doses of 10 and 100 mg/rat. Inhibition 

was more pronounced at the higher dose. 

j

Hepatocyte viability was 86, 89, 87, 88, 78, and 86% 24 hours following exposure to 0, 1,000, 1,500, 

2,000, or 4,000 mg/kg. The incidence (%) of replicative DNA synthesis was increased by 2.5-fold 

(1,000 mg/kg) or 4.5-fold (1,500 and 2,000 mg/kg). No increase in replicative DNA synthesis was 

observed at the highest dose (4,000 mg/kg). 

k

Replicative DNA synthesis was measured 24, 39, and 48 hours following a single dose of 0, 1,000, or 

2,000 mg/kg. Hepatocyte viability ranged from 71 to 82%. The only increase in replicative DNA 

synthesis was observed 24 hours after administration of 2,000 mg/kg (threefold increase). Cell viability 

for this group was 79%. 

l

Replicative DNA synthesis was increased 1.5-fold in rats given 1,000 mg/kg of 1,4-dioxane for 11 weeks. 

No change from control was observed in rats exposed to 10 mg/kg for 11 weeks or rats acutely exposed to 

10, 100, or 1,000 mg/kg. 

 70 
 

Table 4-17. Genotoxicity studies of 1,4-dioxane; mammalian in vivo

Test system Endpoint Test Conditions Resultsa Doseb Source 

Female 

Sprague Dawley 

Rat 

DNA damage; 

single-strand breaks 

measured by alkaline 

elution 

Two gavage doses given 21 

and 4 hours prior to 

sacrifice 

+c 2,550 mg/kg Kitchin and 

Brown (1990, 

062928) 

Male 

Sprague Dawley 

Rat 

DNA alkylation in 

hepatocytes 

Gavage; DNA isolation and 

HPLC analysis 4 hours after 

dosing 

– 1,000 mg/kg Stott et al. 

(1981, 

063021) 

Male 

B6C3F1 

Mouse 

Micronucleus 

formation in bone 

marrow 

i.p. injection; analysis of 

polychromatic erythrocytes 

24 or 48 hours after dosing 

– Single dose of 

4,000 mg/kg; 

3 daily doses of 

2,000 

McFee et al. 

(1994, 

195060) 

Male and female 

C57BL6 

Mouse; 

male BALB/c 

Mouse 

Micronucleus 

formation in bone 

marrow 

Gavage; analysis of 

polychromatic erythrocytes 

24 or 48 hours after dosing 

+ 

(C57BL6)d

– (BALB/c)

900 mg/kg 

(C57BL6); 

5,000 mg/kg 

(BALB/c) 

Mirkova 

(1994, 

195062) 

Male 

CD1 

Mouse

Micronucleus 

formation in 

peripheral blood 

Two i.p. injections (1/day); 

micronucleated 

reticulocytes measured 24, 

48, and 72 hours after the 

2nd dose 

– 3,200 mg/kg Morita (1994, 

196085) 

Male 

CD1 

Mouse 

Micronucleus 

formation in 

hepatocytes 

Gavage, partial 

hepatectomy 24 hours after 

dosing, hepatocytes 

analyzed 5 days after 

hepatectomy 

+e 2,000 mg/kg Morita and 

Hayashi 

(1998, 

195065) 

Male 

CD1 

Mouse 

Micronucleus 

formation in 

peripheral blood 

Gavage, partial 

hepatectomy 24 hours after 

dosing, peripheral blood 

obtained from tail vein 

24 hours after hepatectomy 

– 3,000 mg/kg Morita and 

Hayashi 

(1998, 

195065) 

Male 

CBA and 

C57BL6 Mouse 

Micronucleus 

formation in bone 

marrow 

Gavage; analysis of 

polychromatic erythrocytes 

from specimens prepared 

24 hours after dosing 

– 3,600 mg/kg Tinwell and 

Ashby (1994, 

195086) 

Male 

CD1 

Mouse 

Micronuclei 

formation in bone 

marrow 

Gavage; analysis for 

micronucleated erythrocytes 

24 hours after dosing 

+f 1,500 mg/kg-day 

for 5 days 

Roy et al. 

(2005, 

196094) 

Male 

CD1 

Mouse 

Micronuclei 

formation in 

hepatocytes 

Gavage; analysis for 

micronuclei 24 hours after 

dosing 

+g 2,500 mg/kg-day 

for 5 days 

Roy et 

al.(2005, 

196094) 

Male 

Sprague Dawley 

Rat 

DNA repair in 

hepatocytes 

Drinking water; thymidine 

incorporation with 

hydroxyurea to repress 

normal DNA synthesis 

– 1,000 mg/kg-day 

for 11 weeks 

Stott et al. 

(1981, 

063021) 

 71 
 

Test system Endpoint Test Conditions Resultsa Doseb Source 

Male 

F344 

 Rat 

DNA repair in 

hepatocytes 

(autoradiography) 

Gavage and drinking water 

exposure; thymidine 

incorporation 

– 1,000 mg/kg for 

2 or 12 hours; 

1,500 mg/kg-day 

for 2 weeks or 

3,000 mg/kg-day 

for 1 week 

Goldsworthy 

et al. (1991, 

062925) 

Male 

F344 

Rat 

DNA repair in nasal 

epithelial cells from 

the nasoturbinate or 

maxilloturbinate 

Gavage and drinking water 

exposure; thymidine 

incorporation 

– 1,500 mg/kg-day 

for 8 days + 

1,000 mg/kg 

gavage dose 

12 hours prior to 

sacrifice 

Goldsworthy 

et al. (1991, 

062925) 

Male 

F344 

Rat 

Replicative DNA 

synthesis (i.e., cell 

proliferation) in 

hepatocytes 

Gavage and drinking water 

exposure; thymidine 

incorporation 

+h

(1–2-week 

exposure) 

1,000 mg/kg for 

24 or 48 hours; 

1,500 mg/kg-day 

for 1 or 2 weeks 

Goldsworthy 

et al. (1991, 

062925) 

Male 

F344 

Rat 

Replicative DNA 

synthesis (i.e., cell 

proliferation) in nasal 

epithelial cells 

Drinking water exposure; 

thymidine incorporation – 1,500 mg/kg-day 

for 2 weeks 

Goldsworthy 

et al. (1991, 

062925) 

Male 

Sprague Dawley 

Rat 

RNA synthesis; 

inhibition of RNA 

polymerase A and B 

i.v. injection; activity 

measured in isolated 

hepatocytes 

+i 10 mg/rat Kurl et al. 

(1981, 

195054) 

Male 

F344 

Rat 

DNA synthesis in 

hepatocytes 

Gavage; thymidine and 

BrdU incorporation 

+j 1,000 mg/kg Miyagawa 

(1999, 

195063) 

Male 

F344 

Rat 

DNA synthesis in 

hepatocytes 

Thymidine incorporation ±k 2,000 mg/kg Uno et al. 

(1994, 

194385) 

Male 

Sprague Dawley 

Rat 

DNA synthesis in 

hepatocytes 

Drinking water; thymidine 

incorporation 

+l 1,000 mg/kg-day 

for 11 weeks 

Stott et al. 

(1981, 

063021) 

a

+ = positive, ± = equivocal or weak positive, – = negative, T = toxicity. Endogenous metabolic 

activation is not applicable for in vivo studies. 

b

Lowest effective dose for positive results/highest dose tested for negative results; ND = no data. 

c

Rats were given doses of 0, 168, 840, 2,550, or 4,200 mg/kg at 4 and 21 hours prior to sacrifice. A 43 and 

50% increase in the fraction of DNA eluted was observed for doses of 2,550 and 4,200 mg/kg, 

respectively. Alkaline elution of DNA was not significantly different from control in the two lowest dose 

groups (168 and 840 mg/kg). 

d

A dose-related increase in the incidence of bone marrow micronuclei was observed in male and female 

C57BL6 mice 24 or 48 hours after administration of 1,4-dioxane. A dose of 450 mg/kg produced no 

change relative to control, while doses of 900, 1,800, 3,600, and 5,000 mg/kg increased the incidence of 

bone marrow micronuclei by approximately two-,three-, four- and fourfold, respectively. 

e

A dose-related increase in the incidence of hepatocyte micronuclei was observed in partially 

hepatectomized mice 6 days after administration of 1,4-dioxane. A dose of 1,000 mg/kg produced no 

change relative to control, while doses of 2,000 and 3,000 mg/kg increased the incidence of hepatocyte 

micronuclei by 2.4- and 3.4-fold, respectively. 

f Significant increases in the frequency of micronucleated erythrocytes were observed at each test dose of 

1,4-dioxane (1,500, 2,500 and 3,500 mg/kg-day, 5 days/week). 

g

A dose-related increase in the frequency of micronuclei was observed in proliferating cells with micronuclei at 

2,500 and 3,500 mg/kg-day, 5 days/week. No increase in the frequency of micronuclei was seen in the nonproliferating cells. 

 72 
 

h

No increase in the hepatocyte labeling index was observed 24 or 48 hours following a single gavage 

exposure of 1,000 mg/kg. Continuous administration of 1% 1,4-dioxane in the drinking water for up to 

2 weeks produced a twofold increase in the hepatocyte labeling index. 

i

A similar pattern of RNA polymerase inhibition was observed at doses of 10 and 100 mg/rat. Inhibition 

was more pronounced at the higher dose. 

j

Hepatocyte viability was 86, 89, 87, 88, 78, and 86% 24 hours following exposure to 0, 1,000, 1,500, 

2,000, or 4,000 mg/kg. The incidence (%) of replicative DNA synthesis was increased by 2.5-fold 

(1,000 mg/kg) or 4.5-fold (1,500 and 2,000 mg/kg). No increase in replicative DNA synthesis was 

observed at the highest dose (4,000 mg/kg). 

k

Replicative DNA synthesis was measured 24, 39, and 48 hours following a single dose of 0, 1,000, or 

2,000 mg/kg. Hepatocyte viability ranged from 71 to 82%. The only increase in replicative DNA 

synthesis was observed 24 hours after administration of 2,000 mg/kg (threefold increase). Cell viability 

for this group was 79%. 

l

Replicative DNA synthesis was increased 1.5-fold in rats given 1,000 mg/kg of 1,4-dioxane for 11 weeks. 

No change from control was observed in rats exposed to 10 mg/kg for 11 weeks or rats acutely exposed to 

10, 100, or 1,000 mg/kg. 

4.5.2. Mechanistic Studies 

4.5.2.1. Free Radical Generation 

Burmistrov et al. (2001, 195972) investigated the effect of 1,4-dioxane inhalation on free 

radical processes in the rat ovary and brain. Female rats (6–9/group, unspecified strain) were 

exposed to 0, 10, or 100 mg/m3

 of 1,4-dioxane vapor for 4 hours/day, 5 days/week, for 1 month. 

Rats were sacrificed during the morning or evening following exposure and the ovaries and brain 

cortex were removed and frozen. Tissue preparations were analyzed for catalase activity, 

glutathione peroxidase activity, and protein peroxidation. Inhalation of 100 mg/m3

 of 

1,4-dioxane resulted in a significant increase (p < 0.05) in glutathione peroxidase activity, and 

activation of free radical processes were apparent in both the rat ovary and brain cortex. No 

change in catalase activity or protein peroxidation was observed at either concentration. A 

circadian rhythm for glutathione peroxidase activity was absent in control rats, but occurred in 

rat brain and ovary following 1,4-dioxane exposure. 

4.5.2.2. Induction of Metabolism 

The metabolism of 1,4-dioxane is discussed in detail in Section 3.3. 1,4-Dioxane has 

been shown to induce its own metabolism (Young et al., 1978, 062955; Young et al., 1978, 

625640). Nannelli et al. (2005, 195067) (study details provided in Section 3.3) characterized the 

CYP450 isozymes that were induced by 1,4-dioxane in the liver, kidney, and nasal mucosa of the 

rat. In the liver, the activities of several CYP450 isozymes were increased (i.e., CYP2B1/2, 

CYP2E1, CYPC11); however, only CYP2E1 was inducible in the kidney and nasal mucosa. 

CYP2E1 mRNA was increased approximately two- to threefold in the kidney and nasal mucosa, 

but mRNA levels were not increased in the liver, suggesting that regulation of CYP2E1 is organspecific. Induction of hepatic CYPB1/2 and CYP2E1 levels by phenobarbital or fasting did not 

increase the liver toxicity of 1,4-dioxane, as measured by hepatic glutathione content or serum 

ALT activity. This result suggested that highly reactive and toxic intermediates did not play a 

 73 
 

large role in the liver toxicity of 1,4-dioxane, even under conditions where metabolism was 

enhanced. This finding is similar to an earlier conclusion by Kociba et al. (1975, 062930) who 

evaluated toxicity from a chronic drinking water study alongside data providing a 

pharmacokinetic profile for 1,4-dioxane. Kociba et al. (1975, 062930) concluded that liver 

toxicity and eventual tumor formation occurred only at doses where clearance pathways were 

saturated and elimination of 1,4-dioxane from the blood was reduced. Nannelli et al. (2005, 

195067) further suggested that a sustained induction of CYP2E1 may lead to generation of 

reactive oxygen species contributing to target organ toxicity and regenerative cell proliferation; 

however, no data were provided to support this hypothesis. 

4.5.2.3. Mechanisms of Tumor Induction 

Several studies have been performed to evaluate potential mechanisms for the 

carcinogenicity of 1,4-dioxane (Goldsworthy et al., 1991, 062925; Kitchin and Brown, 1990, 

062928; Stott et al., 1981, 063021). Stott et al. (1981, 063021) evaluated 1,4-dioxane in several 

test systems, including salmonella mutagenicity in vitro, rat hepatocyte DNA repair activity in 

vitro, DNA synthesis determination in male Sprague Dawley rats following acute gavage dosing 

or an 11-week drinking water exposure (described in Section 4.2.1), and hepatocyte DNA 

alkylation and DNA repair following a single gavage dose. This study used doses of 0, 10, 100, 

or 1,000 mg/kg-day, with the highest dose considered to be a tumorigenic dose level. Liver 

histopathology and liver to BW ratios were also evaluated in rats from acute gavage or repeated 

dose drinking water experiments. 

The histopathology evaluation indicated that liver cytotoxicity (i.e., centrilobular 

hepatocyte swelling) was present in rats from the 1,000 mg/kg-day dose group that received 

1,4-dioxane in the drinking water for 11 weeks (Stott et al., 1981, 063021). An increase in the 

liver to BW ratio accompanied by an increase in hepatic DNA synthesis was also seen in this 

group of animals. No effect on histopathology, liver weight, or DNA synthesis was observed in 

acutely exposed rats or rats that were exposed to a lower dose of 10 mg/kg-day for 11 weeks. 

1,4-Dioxane produced negative findings in the remaining genotoxicity assays conducted as part 

of this study (i.e., Salmonella mutagenicity, in vitro and in vivo rat hepatocyte DNA repair, and 

DNA alkylation in rat liver). The study authors suggested that the observed lack of genotoxicity 

at tumorigenic and cytotoxic dose levels indicates an epigenetic mechanism for 1,4-dioxane 

hepatocellular carcinoma in rats. 

Goldsworthy et al. (1991, 062925) evaluated potential mechanisms for the nasal and liver 

carcinogenicity of 1,4-dioxane in the rat. DNA repair activity was evaluated as a measure of 

DNA reactivity and DNA synthesis was measured as an indicator of cell proliferation or 

promotional activity. In vitro DNA repair was evaluated in primary hepatocyte cultures from 

control and 1,4-dioxane-treated rats (1 or 2% in the drinking water for 1 week). DNA repair and 

DNA synthesis were also measured in vivo following a single gavage dose of 1,000 mg/kg, a 

 74 
 

drinking water exposure of 1% (1,500 mg/kg-day) for 1 week, or a drinking water exposure of 

2% (3,000 mg/kg-day) for 2 weeks. Liver to BW ratios and palmitoyl CoA oxidase activity were 

measured in the rat liver to determine whether peroxisome proliferation played a role in the liver 

carcinogenesis of 1,4-dioxane. In vivo DNA repair was evaluated in rat nasal epithelial cells 

derived from either the nasoturbinate or the maxilloturbinate of 1,4-dioxane-treated rats. These 

rats received 1% 1,4-dioxane (1,500 mg/kg-day) in the drinking water for 8 days, followed by a 

single gavage dose of 10, 100, or 1,000 mg/kg 12 hours prior to sacrifice. Archived tissues from 

the NCI (1978, 062935) bioassay were reexamined to determine the primary sites for tumor 

formation in the nasal cavity following chronic exposure in rats. Histopathology and cell 

proliferation were determined for specific sites in the nasal cavity that were related to tumor 

formation. This evaluation was performed in rats that were exposed to drinking water containing 

1% 1,4-dioxane (1,500 mg/kg-day) for 2 weeks. 

1,4-Dioxane and its metabolite 1,4-dioxane-2-one did not affect in vitro DNA repair in 

primary hepatocyte cultures (Goldsworthy et al., 1991, 062925). In vivo DNA repair was also 

unaffected by acute gavage exposure or ingestion of 1,4-dioxane in the drinking water for a 1- or 

2-week period. Hepatocyte cell proliferation was not affected by acute gavage exposure, but was 

increased approximately twofold following a 1–2-week drinking water exposure. A 5-day 

drinking water exposure to 1% 1,4-dioxane (1,500 mg/kg-day) did not increase the activity of 

palmitoyl coenzyme A or the liver to BW ratio, suggesting that peroxisome proliferation did not 

play a role in the hepatocarcinogenesis of 1,4-dioxane. Nannelli et al. (2005, 195067) also 

reported a lack of hepatic palmitoyl CoA induction following 10 days of exposure to 1.5% 

1,4-dioxane in the drinking water (2,100 mg/kg-day). 

Treatment of rats with 1% (1,500 mg/kg-day) 1,4-dioxane for 8 days did not alter DNA 

repair in nasal epithelial cells (Goldsworthy et al., 1991, 062925). The addition of a single 

gavage dose of up to 1,000 mg/kg 12 hours prior to sacrifice also did not induce DNA repair. 

Reexamination of tissue sections from the NCI (1978, 062935) bioassay suggested that the 

majority of nasal tumors were located in the dorsal nasal septum or the nasoturbinate of the 

anterior portion of the dorsal meatus (Goldsworthy et al., 1991, 062925). No histopathological 

lesions were observed in nasal section of rats exposed to drinking water containing 1% 

1,4-dioxane (1,500 mg/kg-day) for 2 weeks and no increase was observed in cell proliferation at 

the sites of highest tumor formation in the nasal cavity. 

Female Sprague Dawley rats (three to nine per group) were given 0, 168, 840, 2,550, or 

4,200 mg/kg 1,4-dioxane (99% purity) by corn oil gavage in two doses at 21 and 4 hours prior to 

sacrifice (Kitchin and Brown, 1990, 062928). DNA damage (single-strand breaks measured by 

alkaline elution), ODC activity, reduced glutathione content, and CYP450 content were 

measured in the liver. Serum ALT activity and liver histopathology were also evaluated. No 

changes were observed in hepatic reduced glutathione content or ALT activity. Light 

microscopy revealed minimal to mild vacuolar degeneration in the cytoplasm of hepatocytes 

 75 
 

from three of five rats from the 2,550 mg/kg dose group. No histopathological lesions were seen 

in any other dose group, including rats given a higher dose of 4,200 mg/kg. 1,4-Dioxane caused 

43 and 50% increases in DNA single-strand breaks at dose levels of 2,550 and 4,200 mg/kg, 

respectively. CYP450 content was also increased at the two highest dose levels (25 and 66% 

respectively). ODC activity was increased approximately two-, five-, and eightfold above 

control values at doses of 840, 2,550, and 4,200 mg/kg, respectively. The results of this study 

demonstrated that hepatic DNA damage can occur in the absence of significant cytotoxicity. 

Parameters associated with tumor promotion (i.e., ODC activity, CYP450 content) were also 

elevated, suggesting that promotion may play a role in the carcinogenesis of 1,4-dioxane. 

4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS 

Liver and kidney toxicity were the primary noncancer health effects associated with 

exposure to 1,4-dioxane in humans and laboratory animals. Several fatal cases of hemorrhagic 

nephritis and centrilobular necrosis of the liver were related to occupational exposure (i.e., 

inhalation and dermal contact) to 1,4-dioxane (Barber, 1934, 062913; Johnstone, 1959, 062927). 

Neurological changes were also reported in one case; including, headache, elevation in blood 

pressure, agitation and restlessness, and coma (Johnstone, 1959, 062927). Perivascular widening 

was observed in the brain of this worker, with small foci of demyelination in several regions 

(e.g., cortex, basal nuclei). Liver and kidney degeneration and necrosis were observed in acute 

oral and inhalation studies (David, 1964, 195954; de Navasquez, 1935, 196174; Drew et al., 

1978, 067913; Fairley et al., 1934, 062919; JBRC, 1998, 196242; Kesten et al., 1939, 194972; 

Laug et al., 1939, 195055; Schrenk and Yant, 1936, 195076). The results of subchronic and 

chronic studies are discussed below. 

4.6.1. Oral 

Table 4-18 presents a summary of the noncancer results for the subchronic and chronic 

oral studies of 1,4-dioxane toxicity in experimental animals. Liver and kidney toxicity were the 

primary noncancer health effects of oral exposure to 1,4-dioxane in animals. Kidney damage at 

high doses was characterized by degeneration of the cortical tubule cells, necrosis with 

hemorrhage, and glomerulonephritis (Argus et al., 1965, 017009; Fairley et al., 1934, 062919; 

Kociba et al., 1974, 062929; NCI, 1978, 062935). Renal cell degeneration generally began with 

cloudy swelling of cells in the cortex (Fairley et al., 1934, 062919). Nuclear enlargement of 

proximal tubule cells was observed at doses below those producing renal necrosis (JBRC, 1998, 

196240; Kano et al., 2008, 196245), but is of uncertain toxicological significance. The lowest 

dose reported to produce kidney damage was 94 mg/kg-day, which produced renal degeneration 

and necrosis of tubule epithelial cells in male rats in the Kociba et al. (1974, 062929) study. 

Cortical tubule degeneration was seen at higher doses in the NCI (1978, 062935) bioassay 

 76 
 

(240 mg/kg-day, male rats), and glomerulonephritis was reported for rats given doses of 

≥ 430 mg/kg-day (Argus et al., 1965, 017009; 1973, 062912). 

Table 4-18. Oral toxicity studies (noncancer effects) for 1,4-dioxane 

Species Dose/duration 

NOAEL 

(mg/kg-day)

LOAEL 

(mg/kg-day) Effect Reference 

Subchronic studies 

Rat and mouse 

(6/species); 

unknown strain 

Rats 0 or 1,900 mg/kgday; mice 0 or 

3,300 mg/kg-day for 

67 days 

NA 1,900 rats 

3,300 mice 

Renal cortical degeneration 

and necrosis, hemorrhage; 

hepatocellular degeneration 

Fairley et al. 

(1934, 

062919) 

Male 

Sprague Dawley 

Rat 

(4–6/group) 

0, 10, or 1,000 mg/kg-day 

for 11 weeks 

10 1,000 Minimal centrilobular 

hepatocyte swelling; 

increased DNA synthesis 

Stott et al. 

(1981, 

063021) 

F344/DuCrj rat 

(10/sex/group) 

Males 0, 52, 126, 274, 

657, or 1,554 mg/kg-day; 

females 0, 83, 185, 427, 

756, or 1,614 mg/kg-day 

for 13 weeks 

52 126 Nuclear enlargement of 

nasal respiratory 

epithelium; hepatocyte 

swelling 

Kano et al. 

(2008, 

196245) 

Crj:BDF1 

Mouse 

(10/sex/group) 

Males 0, 86, 231, 585, 

882, or 1,570 mg/kg-day; 

females 0, 170, 387, 898, 

1,620, or 2,669 mg/kgday for 13 weeks 

170 387 Nuclear enlargement of 

bronchial epithelium 

Kano et al. 

(2008, 

196245) 

Chronic studies 

Male 

Wistar 

Rat (26 treated, 

9 controls) 

0 or 640 mg/kg-day for 

63 weeks 

NA 640 Hepatocytes with enlarged 

hyperchromic nuclei; 

glomerulonephritis 

Argus et al. 

(1965, 

017009) 

Male 

Sprague Dawley 

rats (30/group) 

0, 430, 574, 803, or 

1,032 mg/kg-day for 

13 months 

NA 430 Hepatocytomegaly; 

glomerulonephritis 

Argus et al. 

(1973, 

062912) 

Sherman rat 

(60/sex/dose 

group) 

Males 0, 9.6, 94, or 

1,015 mg/kg-day; females 

0, 19, 148, or 

1,599 mg/kg-day for 

2 years 

9.6 94 Degeneration and necrosis 

of renal tubular cells and 

hepatocytes 

Kociba et al. 

(1974, 

062929) 

Osborne-Mendel 

rat (35/sex/dose 

level) 

Males 0, 240, or 

530 mg/kg-day; females 

0, 350, or 640 mg/kg-day 

for 110 weeks 

NA 240 Pneumonia, gastric ulcers, 

and cortical tubular 

degeneration in the kidney 

NCI (1978, 

062935) 

B6C3F1 mouse 

(50/sex/dose 

level) 

Males 0, 720, or 

830 mg/kg-day; females 

0, 380, or 860 mg/kg-day 

for 90 weeks 

NA 380 Pneumonia and rhinitis NCI (1978, 

062935) 

 77 
 

Species Dose/duration 

NOAEL 

(mg/kg-day)

LOAEL 

(mg/kg-day) Effect Reference 

F344/DuCrj rat 

(50/sex/dose 

level) 

Males 0, 11, 55, or 

274 mg/kg-day; females 

0, 18, 83, or 429 mg/kgday for 2 years 

55 274 Atrophy of nasal olfactory 

epithelium; nasal adhesion 

and inflammation 

JBRC (1998, 

196240); 

Kano et al. 

(2009, 

594539) 

F344/DuCrj rat 

(50/sex/dose 

level) 

Males 0, 11, 55, or 

274 mg/kg-day; females 

0, 18, 83, or 429 mg/kgday for 2 years 

11 55 Liver hyperplasia JBRC (1998, 

196240); 

Kano et al. 

(2009, 

594539) 

F344/DuCrj rat 

(50/sex/dose 

level) 

Males 0, 11, 55, or 

274 mg/kg-day; females 

0, 18, 83, or 429 mg/kgday for 2 years 

55 274 Increases in serum liver 

enzymes (GOT, GPT, LDH, 

and ALP) 

JBRC (1998, 

196240); 

Kano et al. 

(2009, 

594539) 

Crj:BDF1 mouse 

(50/sex/dose 

level) 

Males 0, 49, 191 or 

677 mg/kg-day; females 

0, 66, 278, or 964 mg/kgday for 2 years 

66 278 Nasal inflammation JBRC (1998, 

196240); 

Kano et al. 

(2009, 

594539) 

Crj:BDF1 mouse 

(50/sex/dose 

level) 

Males 0, 49, 191 or 

677 mg/kg-day; females 

0, 66, 278, or 964 mg/kgday for 2 years 

49 191 Increases in serum liver 

enzymes (GOT, GPT, LDH, 

and ALP) 

JBRC (1998, 

196240); 

Kano et al. 

(2009, 

594539) 

Developmental studies 

Sprague Dawley 

rat 

(18–20/group) 

Pregnant dams 0, 250, 

500, or 1,000 mg/kg-day 

on gestation days 6–15 

500 1,000 Delayed ossification of the 

sternebrae and reduced fetal 

BWs 

Giavani et al. 

(1985, 

062924) 

 

Liver effects included degeneration and necrosis, hepatocyte swelling, cells with 

hyperchromic nuclei, spongiosis hepatis, hyperplasia, and clear and mixed cell foci of the liver 

(Argus et al., 1965, 017009; Argus et al., 1973, 062912; Fairley et al., 1934, 062919; Kano et al., 

2008, 196245; Kociba et al., 1974, 062929; NCI, 1978, 062935). Hepatocellular degeneration 

and necrosis were seen at high doses in a subchronic study (1,900 mg/kg-day in rats) (Fairley et 

al., 1934, 062919) and at lower doses in a chronic study (94 mg/kg-day, male rats) (Kociba et al., 

1974, 062929). Argus et al. (1973, 062912) described a progression of preneoplastic effects in 

the liver of rats exposed to a dose of 575 mg/kg-day. Early changes (8 months exposure) were 

described as an increased nuclear size of hepatocytes, disorganization of the rough endoplasmic 

reticulum, an increase in smooth endoplasmic reticulum, a decrease in glycogen, an increase in 

lipid droplets in hepatocytes, and formation of liver nodules. Spongiosis hepatis, hyperplasia, 

and clear and mixed-cell foci were also observed in the liver of rats (doses >55 mg/kg-day in 

male rats) (JBRC, 1998, 196240; Kano et al., 2009, 594539). Clear and mixed-cell foci are 

commonly considered preneoplastic changes and would not be considered evidence of noncancer 

toxicity when observed in conjunction with tumor formation. If exposure to 1,4-dioxane had not 

 78 
 

resulted in tumor formation, these lesions could represent potential noncancer toxicity. The 

nature of spongiosis hepatis as a preneoplastic change is less well understood (Bannasch, 2003, 

196140; Karbe and Kerlin, 2002, 196246; Stroebel et al., 1995, 196101). Spongiosis hepatis is a 

cyst-like lesion that arises from the perisinusoidal Ito cells of the liver. This change is 

sometimes associated with hepatocellular hypertrophy and liver toxicity (Karbe and Kerlin, 

2002, 196246), but may also occur in combination with preneoplastic foci, or hepatocellular 

adenoma or carcinoma (Bannasch, 2003, 196140; Stroebel et al., 1995, 196101). In the case of 

the JBRC (1998, 196240) study, spongiosis hepatis was associated with other preneoplastic 

changes in the liver (hyperplasia, clear and mixed-cell foci). No other lesions indicative of liver 

toxicity were seen in this study; therefore, spongiosis hepatis was not considered indicative of 

noncancer effects. The activity of serum enzymes (i.e., AST, ALT, LDH, and ALP) was 

increased in rats and mice exposed to 1,4-dioxane, although only in groups with high incidence 

of liver tumors. Blood samples were collected only at the end of the 2-year study, so altered 

serum chemistry may be associated with the tumorigenic changes in the liver. 

Hematological changes were reported in the JBRC (1998, 196240) study only. Mean 

doses are reported based on information provided in Kano et al. (2009, 594539). Observed 

increases in RBCs, hematocrit, hemoglobin in high-dose male mice (677 mg/kg-day) may be 

related to lower drinking water consumption (74% of control drinking water intake). 

Hematological effects noted in male rats given 55 mg/kg-day (decreased RBCs, hemoglobin, 

hematocrit, increased platelets) were within 20% of control values. A reference range database 

for hematological effects in laboratory animals (Wolford et al., 1986, 196112) indicates that a 

20% change in these parameters may fall within a normal range (10th–90th percentile values) 

and may not represent a treatment-related effect of concern. 

Rhinitis and inflammation of the nasal cavity were reported in both the NCI (1978, 

062935) (mice only, dose ≥ 380 mg/kg-day) and JBRC (1998, 196240) studies (≥ 274 mg/kg-day 

in rats, >278 mg/kg-day in mice). The JBRC (1998, 196240) study also demonstrates atrophy of 

the nasal epithelium and adhesion in rats and mice. Nasal inflammation may be a response to 

direct contact of the nasal mucosa with drinking water containing 1,4-dioxane (Goldsworthy et 

al., 1991, 062925; Sweeney et al., 2008, 195085) or could result from systemic exposure. 

Regardless, inflammation may indicate toxicity due to 1,4-dioxane exposure. A significant 

increase in the incidence of pneumonia was reported in mice from the NCI (1978, 062935) study. 

The significance of this effect is unclear, as it was not observed in other studies that evaluated 

lung histopathology (JBRC, 1998, 196240; Kano et al., 2008, 196245; Kociba et al., 1974, 

062929). No studies were available regarding the potential for 1,4-dioxane to cause 

immunological effects. Metaplasia and hyperplasia of the nasal epithelium were also observed in 

high-dose male and female rats (JBRC, 1998, 196240); however, these effects are likely to be 

associated with the formation of nasal cavity tumors in these dose groups. Nuclear enlargement 

of the nasal olfactory epithelium was observed at a dose of 83 mg/kg-day in female rats (Kano et 

 79 
 

al., 2009, 594539); however, it is unclear whether this alteration represents an adverse 

toxicological effect. Nuclear enlargement of the tracheal and bronchial epithelium and an 

accumulation of foamy cells in the lung were also seen in male and female mice give 

1,4-dioxane at doses of ≥ 278 mg/kg for 2 years (JBRC, 1998, 196240). 

4.6.2. Inhalation 

Only one subchronic study (Fairley et al., 1934, 062919) and one chronic inhalation study 

(Torkelson et al., 1974, 094807) were identified. In the subchronic study, rabbits, guinea pigs, 

rats, and mice (3–6/species/group) were exposed to 1,000, 2,000, 5,000, or 10,000 ppm of 

1,4-dioxane vapor for 1.5 hours two times a day for 5 days, 1.5 hours for one day, and no 

exposure on the seventh day. Animals were exposed until death occurred or were sacrificed after 

various durations of exposure (3–202.5 hours). Detailed dose-response information was not 

provided; however, severe liver and kidney damage and acute vascular congestion of the lungs 

were noted for all exposure concentrations tested. Kidney damage was described as patchy 

degeneration of cortical tubules with vascular congestion and hemorrhage. Liver lesions varied 

from cloudy hepatocyte swelling to large areas of necrosis. Torkelson et al. (1974, 094807) 

performed a chronic inhalation study in which male and female Wistar rats (288/sex) were 

exposed to 111 ppm 1,4-dioxane vapor for 7 hours/day, 5 days/week for 2 years. Control rats 

(192/sex) were exposed to filtered air. No significant effects were observed on BWs, survival, 

organ weights, hematology, clinical chemistry, or histopathology. These studies were not 

sufficient to characterize the inhalation risks of 1,4-dioxane, due to the nature of the available 

data (i.e., free-standing LOAEL and NOAEL values). 

4.6.3. Mode of Action Information 

The metabolism of 1,4-dioxane in humans was extensive at low doses (<50 ppm). The 

linear elimination of 1,4-dioxane in both plasma and urine indicated that 1,4-dioxane metabolism 

was a nonsaturated, first-order process at this exposure level (1976, 062953; Young et al., 1977, 

062956). Like humans, rats extensively metabolized inhaled 1,4-dioxane; however, plasma data 

from rats given single i.v. doses of 3, 10, 30, 100, or 1,000 mg [14C]-1,4-dioxane/kg 

demonstrated a dose-related shift from linear, first-order to nonlinear, saturable metabolism of 

1,4-dioxane (Young et al., 1978, 062955; Young et al., 1978, 625640). 

1,4-Dioxane oxidation appeared to be CYP450-mediated, as CYP450 induction with 

phenobarbital or Aroclor 1254 and suppression with 2,4-dichloro-6-phenylphenoxy ethylamine 

or cobaltous chloride was effective in significantly increasing and decreasing, respectively, the 

appearance of HEAA in the urine of rats (Woo et al., 1977, 062951; Woo et al., 1978, 194345). 

1,4-Dioxane itself induced CYP450-mediated metabolism of several barbiturates in Hindustan 

mice given i.p. injections of 25 and 50 mg/kg of 1,4-dioxane (Mungikar and Pawar, 1978, 

 80 
 

194344). The differences between single and multiple doses in urinary and expired radiolabel 

support the notion that 1,4-dioxane may induce its own metabolism. 1,4-Dioxane has been 

shown to induce several isoforms of CYP450 in various tissues following acute oral 

administration by gavage or drinking water (Nannelli et al., 2005, 195067). In the liver, the 

activity of several CYP450 isozymes was increased (i.e., CYP2B1/2, CYP2E1, CYPC11); 

however, only CYP2E1 was inducible in the kidney and nasal mucosa. CYP2E1 mRNA was 

increased approximately two- to threefold in the kidney and nasal mucosa, but mRNA levels 

were not increased in the liver, suggesting that regulation of CYP2E1 was organ-specific. 

Nannelli et al. (2005, 195067) investigated the role of CYP450 isozymes in the liver 

toxicity of 1,4-dioxane. Hepatic CYPB1/2 and CYP2E1 levels were induced by phenobarbital or 

fasting and liver toxicity was measured as hepatic glutathione content or serum ALT activity. 

No increase in glutathione content or ALT activity was observed, suggesting that highly reactive 

and toxic intermediates did not play a large role in the liver toxicity of 1,4-dioxane, even under 

conditions where metabolism was enhanced. Pretreatment with inducers of mixed-function 

oxidases also did not significantly change the extent of covalent binding in subcellular fractions 

(Woo et al., 1977, 062950). Covalent binding was measured in liver, kidney, spleen, lung, colon, 

and skeletal muscle 1–12 hours after i.p. dosing with 1,4-dioxane. Covalent binding was highest 

in liver, spleen, and colon. Within hepatocytes, 1,4-dioxane distribution was greatest in the 

cytosolic fraction, followed by the microsomal, mitochondrial, and nuclear fractions. 

The absence of an increase in toxicity following an increase in metabolism suggests that 

accumulation of the parent compound may be related to 1,4-dioxane toxicity. This hypothesis is 

supported by a comparison of the pharmacokinetic profile of 1,4-dioxane with the toxicology 

data from a chronic drinking water study (Kociba et al., 1975, 062930). This analysis indicated 

that liver toxicity did not occur unless clearance pathways were saturated and elimination of 

1,4-dioxane from the blood was reduced. Alternative metabolic pathways (i.e., not CYP450 

mediated) may be present at high doses of 1,4-dioxane; however, the available studies have not 

characterized these pathways or identified any possible reactive intermediates. The mechanism 

by which 1,4-dioxane induces tissue damage is not known, nor is it known whether the toxic 

moiety is 1,4-dioxane or a transient or terminal metabolite. 

4.7. EVALUATION OF CARCINOGENICITY 

4.7.1. Summary of Overall Weight of Evidence 

Under the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237), 

1,4-dioxane is “likely to be carcinogenic to humans” based on evidence of liver carcinogenicity 

in several 2-year bioassays conducted in three strains of rats, two strains of mice, and in guinea 

pigs (Argus et al., 1965, 017009; Argus et al., 1973, 062912; Hoch-Ligeti and Argus, 1970, 

029386; Hoch-Ligeti et al., 1970, 062926; JBRC, 1998, 196240; Kano et al., 2009, 594539; 

 81 
 

Kociba et al., 1974, 062929; NCI, 1978, 062935; Yamazaki et al., 1994, 196120). Additionally, 

mesotheliomas of the peritoneum (JBRC, 1998, 196240; Kano et al., 2009, 594539; Yamazaki et 

al., 1994, 196120), mammary (JBRC, 1998, 196240; Kano et al., 2009, 594539; Yamazaki et al., 

1994, 196120), and nasal tumors (Argus et al., 1973, 062912; Hoch-Ligeti et al., 1970, 062926; 

JBRC, 1998, 196240; Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 

062935; Yamazaki et al., 1994, 196120) have been observed in rats due to exposure to 

1,4-dioxane. Studies in humans are inconclusive regarding evidence for a causal link between 

occupational exposure to 1,4-dioxane and increased risk for cancer; however, only two studies 

were available and these were limited by small cohort size and a small number of reported cancer 

cases (Buffler et al., 1978, 062914; Thiess et al., 1976, 062943). 

The available evidence is inadequate to establish a mode of action (MOA) by which 

1,4-dioxane induces liver tumors in rats and mice. A MOA hypothesis involving sustained 

proliferation of spontaneously transformed liver cells has some support from data indicating that 

1,4-dioxane acts as a tumor promoter in mouse skin and rat liver bioassays (King et al., 1973, 

029390; Lundberg et al., 1987, 062933). Dose-response and temporal data support the 

occurrence of cell proliferation and hyperplasia prior to the development of liver tumors (JBRC, 

1998, 196240; Kociba et al., 1974, 062929) in the rat model. However, the dose-response 

relationship for induction of hepatic cell proliferation has not been characterized, and it is 

unknown if it would reflect the dose-response relationship for liver tumors in the 2-year rat and 

mouse studies. Conflicting data from rat and mouse bioassays (JBRC, 1998, 196240; Kociba et 

al., 1974, 062929) suggest that cytotoxicity may not be a required precursor event for 

1,4-dioxane-induced cell proliferation. Data regarding a plausible dose response and temporal 

progression (see Table 4-18) from cytotoxicity and cell proliferation to eventual liver tumor 

formation are not available. 

The MOA by which 1,4-dioxane produces liver, nasal, peritoneal (mesotheliomas), and 

mammary gland tumors is unknown, and the available data do not support any hypothesized 

carcinogenic MOA for 1,4-dioxane. 

U.S. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237) 

indicate that for tumors occurring at a site other than the initial point of contact, the weight of 

evidence for carcinogenic potential may apply to all routes of exposure that have not been 

adequately tested at sufficient doses. An exception occurs when there is convincing information 

(e.g., toxicokinetic data) that absorption does not occur by other routes. Information available on 

the carcinogenic effects of 1,4-dioxane via the oral route demonstrates that tumors occur in 

tissues remote from the site of absorption. Information on the carcinogenic effects of 

1,4-dioxane via the inhalation and dermal routes in humans and animals is absent. (Note: Note 

that during the development of this assessment, new data regarding the toxicity of 1,4-dioxane 

through the inhalation route of exposure became available. These data have not been included in 

the current assessment and will be evaluated in a separate IRIS assessment.) Based on the 

 82 
 

observance of systemic tumors following oral exposure, and in the absence of information to 

indicate otherwise, it is assumed that an internal dose will be achieved regardless of the route of 

exposure. Therefore, 1,4-dioxane is “likely to be carcinogenic to humans” by all routes of 

exposure. 

4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence 

Human studies of occupational exposure to 1,4-dioxane were inconclusive; in each case, 

the cohort size and number of reported cases were of limited size (Buffler et al., 1978, 062914; 

Thiess et al., 1976, 062943). 

Several carcinogenicity bioassays have been conducted for 1,4-dioxane in mice, rats, and 

guinea pigs (Argus et al., 1965, 017009; Argus et al., 1973, 062912; Hoch-Ligeti and Argus, 

1970, 029386; Hoch-Ligeti et al., 1970, 062926; JBRC, 1998, 196240; Kano et al., 2009, 

594539; Kociba et al., 1974, 062929; NCI, 1978, 062935; Torkelson et al., 1974, 094807; 

Yamazaki et al., 1994, 196120). Liver tumors have been observed following drinking water 

exposure in male Wistar rats (Argus et al., 1965, 017009), male guinea pigs (Hoch-Ligeti and 

Argus, 1970, 029386), male Sprague Dawley rats (Argus et al., 1973, 062912; Hoch-Ligeti et al., 

1970, 062926), male and female Sherman rats (Kociba et al., 1974, 062929), female OsborneMendel rats (NCI, 1978, 062935), male and female F344/DuCrj rats (JBRC, 1998, 196240; Kano 

et al., 2009, 594539; Yamazaki et al., 1994, 196120), male and female B6C3F1 mice (NCI, 1978, 

062935), and male and female Crj:BDF1 mice (JBRC, 1998, 196240; Kano et al., 2009, 594539; 

Yamazaki et al., 1994, 196120). In the earliest cancer bioassays, the liver tumors were described 

as hepatomas (Argus et al., 1965, 017009; Argus et al., 1973, 062912; Hoch-Ligeti and Argus, 

1970, 029386; Hoch-Ligeti et al., 1970, 062926); however, later studies made a distinction 

between hepatocellular carcinoma and hepatocellular adenoma (JBRC, 1998, 196240; Kano et 

al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 062935; Yamazaki et al., 1994, 

196120). Both tumor types have been seen in rats and mice exposed to 1,4-dioxane. Kociba 

et al. (1974, 062929) noted evidence of liver toxicity at or below the dose levels that produced 

liver tumors but did not report incidence data for these effects. Hepatocellular degeneration and 

necrosis were observed in the mid- and high-dose groups of male and female Sherman rats 

exposed to 1,4-dioxane, while tumors were only observed at the highest dose. Hepatic 

regeneration was indicated in the mid- and high-dose groups by the formation of hepatocellular 

hyperplastic nodules. Findings from JBRC (1998, 196240) also provided evidence of liver 

hyperplasia in male F344/DuCrj rats at a dose level below the dose that induced a statistically 

significant increase in tumor formation. 

Nasal cavity tumors were also observed in Sprague Dawley rats (Argus et al., 1973, 

062912; Hoch-Ligeti et al., 1970, 062926), Osborne-Mendel rats (NCI, 1978, 062935), Sherman 

rats (Kociba et al., 1974, 062929), and F344/DuCrj rats (JBRC, 1998, 196240; Kano et al., 2009, 

594539; Yamazaki et al., 1994, 196120). Most tumors were characterized as squamous cell 

 83 
 

carcinomas. Nasal tumors were not elevated in B6C3F1 or Crj:BDF1 mice. JBRC (1998, 

196240) was the only study that evaluated nonneoplastic changes in nasal cavity tissue following 

prolonged exposure to 1,4-dioxane in the drinking water. Histopathological lesions in female 

F344/DuCrj rats were suggestive of toxicity and regeneration in this tissue (i.e., atrophy, 

adhesion, inflammation, nuclear enlargement, and hyperplasia and metaplasia of respiratory and 

olfactory epithelium). Some of these effects occurred at a lower dose (83 mg/kg-day) than that 

shown to produce nasal cavity tumors (429 mg/kg-day) in female rats. Re-examination of tissue 

sections from the NCI (1978, 062935) bioassay suggested that the majority of nasal tumors were 

located in the dorsal nasal septum or the nasoturbinate of the anterior portion of the dorsal 

meatus. Nasal tumors were not observed in an inhalation study in Wistar rats exposed to 

111 ppm for 5 days/week for 2 years (Torkelson et al., 1974, 094807). 

Tumor initiation and promotion studies in mouse skin and rat liver suggested that 

1,4-dioxane does not initiate the carcinogenic process, but instead acts as a tumor promoter (Bull 

et al., 1986, 194336; King et al., 1973, 029390; Lundberg et al., 1987, 062933) (see Section 

4.2.3). 

In addition to the liver and nasal tumors observed in several studies, a statistically 

significant increase in mesotheliomas of the peritoneum was seen in male rats from the Kano et 

al. (2009, 594539) study (also JBRC, 1998, 196240; Yamazaki et al., 1994, 196120). Female 

rats dosed with 429 mg/kg-day in drinking water for 2 years also showed a statistically 

significant increase in mammary gland adenomas (JBRC, 1998, 196240; Kano et al., 2009, 

594539; Yamazaki et al., 1994, 196120). A significant increase in the incidence of these tumors 

was not observed in other chronic oral bioassays of 1,4-dioxane (Kociba et al., 1974, 062929; 

NCI, 1978, 062935). 

4.7.3. Mode of Action Information 

The MOA by which 1,4-dioxane produces liver, nasal, peritoneal (mesotheliomas), and 

mammary gland tumors is unknown, and the available data do not support any hypothesized 

mode of carcinogenic action for 1,4-dioxane. Available data also do not clearly identify whether 

1,4-dioxane or one of its metabolites is responsible for the observed effects. The hypothesized 

MOAs for 1,4-dioxane carcinogenicity are discussed below within the context of the modified 

Hill criteria of causality as recommended in the most recent Agency guidelines (U.S. EPA, 2005, 

086237). MOA analyses were not conducted for peritoneal or mammary gland tumors due to the 

absence of any chemical specific information for these tumor types. 

4.7.3.1. Identification of Key Events for Carcinogenicity 

4.7.3.1.1. Liver. A key event in this MOA hypothesis is sustained proliferation of 

spontaneously transformed liver cells, resulting in the eventual formation of liver tumors. 

Precursor events in which 1,4-dioxane may promote proliferation of transformed liver cells are 

 84 
 

uncertain. One study suggests that induced liver cytotoxicity may be a key precursor event to 

cell proliferation leading to the formation of liver tumors (Kociba et al., 1974, 062929), however, 

this study did not report incidence data for these effects. Other studies suggest that cell 

proliferation can occur in the absence of liver cytotoxicity. Liver tumors were observed in female 

rats and female mice in the absence of lesions indicative of cytotoxicity (JBRC, 1998, 196240; 

Kano et al., 2008, 196245; NCI, 1978, 062935). Figure 4-1 presents a schematic representation 

of possible key events in the MOA for 1,4-dioxane liver carcinogenicity. These include: 

(1) oxidation by CYP2E1 and CYP2B1/2 (i.e., detoxification pathway for 1,4-dioxane), 

(2) saturation of metabolism/clearance leading to accumulation of the parent 1,4-dioxane, 

(3) liver damage followed by regenerative cell proliferation, or (4) cell proliferation in the 

absence of cytotoxicity (i.e., mitogenesis), (5) hyperplasia, and (6) tumor formation. It is 

suggested that liver toxicity is related to the accumulation of the parent compound following 

metabolic saturation at high doses (Kociba et al., 1975, 062930); however, no in vivo or in vitro 

assays have examined the toxicity of metabolites resulting from 1,4-dioxane to support this 

hypothesis. Nanelli et al. (2005, 195067) demonstrated that an increase in the oxidative 

metabolism of 1,4-dioxane via CYP450 induction using phenobarbital or fasting does not result 

in an increase in liver toxicity. This result suggested that highly reactive and toxic intermediates 

did not play a large role in the liver toxicity of 1,4-dioxane, even under conditions where 

metabolism was enhanced. Alternative metabolic pathways (e.g., not CYP450 mediated) may be 

present at high doses of 1,4-dioxane; although the available studies have not characterized these 

pathways nor identified any possible reactive intermediates. Tumor promotion studies in mouse 

skin and rat liver suggest that 1,4-dioxane may enhance the growth of previously initiated cells 

(King et al., 1973, 029390; Lundberg et al., 1987, 062933). This is consistent with the increase 

in hepatocyte cell proliferation observed in several studies (Goldsworthy et al., 1991, 062925; 

Miyagawa et al., 1999, 195063; Stott et al., 1981, 063021; Uno et al., 1994, 194385). These 

mechanistic studies provide evidence of cell proliferation, but do not indicate whether 

mitogenesis or cytotoxicity is responsible for increased cell turnover. 

 85 
 

Toxicokinetics

Oral absorption of 

1,4-dioxane

Metabolism by 

CYP2E1 and 

CYP2B1/2

HEAA elimination 

in the urine

Metabolic 

saturation and 

accumulation of 

1,4-dioxane in the 

blood

MOA for Liver Tumors

Hepatocellular 

cytotoxicity

Cell proliferation in 

absence of 

cytotoxicity

Regenerative cell 

proliferation Hyperplasia

Hyperplasia

Tumor formation

Tumor promotion

Figure 4-1. A schematic representation of the possible key events in the 

delivery of 1,4-dioxane to the liver and the hypothesized MOA(s) for liver 

carcinogenicity. 

4.7.3.1.2. Nasal cavity. A possible key event in the MOA hypothesis for nasal tumors is 

sustained proliferation of spontaneously transformed nasal epithelial cells, resulting in the 

eventual formation of nasal cavity tumors. Precursor events in which 1,4-dioxane may promote 

proliferation of transformed nasal cells are highly uncertain. Figure 4-2 presents a schematic 

representation of possible key events leading to the formation of nasal cavity tumors. 

Histopathological lesions in female rats were suggestive of toxicity and regeneration in this 

tissue (i.e., atrophy, adhesion, inflammation, nuclear enlargement, and hyperplasia and 

metaplasia of respiratory and olfactory epithelium) (JBRC, 1998, 196240; Kano et al., 2009, 

594539). 

 86 
 

Toxicokinetics

Inhalation of 

water droplets

Metabolism 

by CYP2E1 

and 

CYP2B1/2

HEAA 

elimination in 

the urine

Metabolic 

saturation and 

accumulation of 

1,4-dioxane in the 

blood, exhalation 

of 1,4-dioxane in 

breath

MOA for Nasal Cavity 

Tumors

Chronic 

irritation due to 

direct contact 

with nasal 

epithelium

Cytotoxicity to 

nasal cell 

epithelium

Regenerative 

cell 

proliferation

Hyperplasia

Oral 

absorption of 

1,4-dioxane

Tumor formation

Figure 4-2. A schematic representation of the possible key events in the 

delivery of 1,4-dioxane to the nasal cavity and the hypothesized MOA(s) 

for nasal cavity carcinogenicity. 

4.7.3.2. Strength, Consistency, Specificity of Association 

4.7.3.2.1. Liver. The plausibility of a MOA that would include liver cytotoxicity, with 

subsequent reparative cell proliferation, as precursor events to liver tumor formation is 

minimally supported by findings that nonneoplastic liver lesions occurred at exposure levels 

lower than those resulting in significantly increased incidences of hepatocellular tumors (Kociba 

et al., 1974, 062929) and the demonstration of nonneoplastic liver lesions in subchronic (Kano et 

al., 2008, 196245) and acute and short-term oral studies (see Table 4-15). Because the incidence 

of nonneoplastic lesions was not reported by Kociba et al. (1974, 062929), it is difficult to know 

whether the incidence of liver lesions increased with increasing 1,4-dioxane concentration. 

Contradicting the observations by Kociba et al. (1974, 062929), liver tumors were observed in 

female rats and female mice in the absence of lesions indicative of cytotoxicity (JBRC, 1998, 

196240; Kano et al., 2008, 196245; NCI, 1978, 062935). This suggests that cytotoxicity may not 

be a requisite step in the MOA for liver cancer. Mechanistic and tumor promotion studies 

suggest that enhanced cell proliferation without cytotoxicity may be a key event; however, data 

showing a plausible dose response and temporal progression from cell proliferation to eventual 

liver tumor formation are not available (see Sections 4.7.3.3 and 4.7.3.4). Mechanistic studies 

that demonstrated cell proliferation after short-term exposure did not evaluate liver cytotoxicity 

(Goldsworthy et al., 1991, 062925; Miyagawa et al., 1999, 195063; Uno et al., 1994, 194385). 

Studies have not investigated possible precursor events that may lead to cell proliferation in the 

absence of cytotoxicity (i.e., genetic regulation of mitogenesis). 

 87 
 

4.7.3.2.2. Nasal cavity. Nasal cavity tumors have been demonstrated in several rat strains 

(JBRC, 1998, 196240; Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 

062935; Yamazaki et al., 1994, 196120), but were not elevated in two strains of mice (JBRC, 

1998, 196240; Kano et al., 2009, 594539; NCI, 1978, 062935; Yamazaki et al., 1994, 196120). 

Chronic irritation was indicated by the observation of rhinitis and inflammation of the nasal 

cavity in rats from the JBRC (1998, 196240) study. This study also showed atrophy of the nasal 

epithelium and adhesion in rats. Regeneration of the nasal epithelium is demonstrated by 

metaplasia and hyperplasia observed in rats exposed to 1,4-dioxane (JBRC, 1998, 196240; Kano 

et al., 2009, 594539; Yamazaki et al., 1994, 196120). 

4.7.3.3. Dose-Response Relationship 

4.7.3.3.1. Liver. Table 4-19 presents the temporal sequence and dose-response relationship for 

possible key events in the liver carcinogenesis of 1,4-dioxane. Dose-response information 

provides some support for enhanced cell proliferation as a key event in the liver tumorigenesis of 

1,4-dioxane; however, the role of cytotoxicity as a required precursor event is not supported by 

data from more than one study. Kociba et al. (1974, 062929) demonstrated that liver toxicity and 

hepatocellular regeneration occurred at a lower dose level than tumor formation. Hepatocellular 

degeneration and necrosis were observed in the mid- and high-dose groups of Sherman rats 

exposed to 1,4-dioxane, although it is not possible to discern whether this effect was observed in 

both genders due to the lack of incidence data (Kociba et al., 1974, 062929). Hepatic tumors 

were only observed at the highest dose (Kociba et al., 1974, 062929). Hepatic regeneration was 

indicated in the mid- and high-dose group by the formation of hepatocellular hyperplastic 

nodules. Liver hyperplasia was also seen in rats from the JBRC (1998, 196240) study, at or 

below the dose level that resulted in tumor formation (Kano et al., 2009, 594539); however, 

hepatocellular degeneration and necrosis were not observed. These results suggest that hepatic 

cell proliferation and hyperplasia may occur in the absence of significant cytotoxicity. Liver 

angiectasis (i.e., dilation of blood or lymphatic vessels) was observed in male mice at the same 

dose that produced liver tumors; however, the relationship between this vascular abnormality and 

tumor formation is unclear. 

 88 
 

Table 4-19. Temporal sequence and dose-response relationship for possible 

key events and liver tumors in rats and mice 

Key event (time →) 

Dose (mg/kg-day) 

Metabolism 

1,4-dioxane Liver damage 

Cell 

proliferation Hyperplasia 

Adenomas 

and/or 

carcinomas 

Kociba et al., (1974, 062929)—Sherman rats (male and female combined) 

0 —a —a

14 +b —a —a —a —a

121 +b +c —a +c —a

1,307 +b +c —a +c +c

NCI, (1978, 062935)—female Osborne-Mendel rats 

0 —a —a —a —a —a

350 +b —a —a —a +c

640 +b —a —a —a +c

NCI, (1978, 062935)—male B6C3F1 mice 

0 —a —a —a —a —a

720 +b —a —a —a +c

830 +b —a —a —a +c

NCI, (1978, 062935)—female B6C3F1 mice 

0 —a —a —a —a —a

380 +b —a —a —a +c

860 +b —a —a —a +c

Kano et al., (2009, 594539); JBRC, (1998, 196240)—male F344/DuCrj rats 

0 —a —a —a —a —a

11 +b —a —a —a —a

55 +b —a —a +c,e —a

274 +b +c,d —a +c,e +c,e

Kano et al., (2009, 594539); JBRC, (1998, 196240)—female F344/DuCrj rats 

0 —a —a —a —a —a

18 +b —a —a —a —a

83 +b —a —a —a —a

429 +b —a —a +c,e +c,e

Kano et al., (2009, 594539); JBRC, (1998, 196240)—male Crj:BDF1 mice 

0 —a —a —a —a —a

49 +b —a —a —a +c,e

191 +b —a —a —a +c,e

677 +b +c,d —a —a +c,e

 89 
 

Key event (time →) 

Dose (mg/kg-day) 

Metabolism 

1,4-dioxane Liver damage 

Cell 

proliferation Hyperplasia 

Adenomas 

and/or 

carcinomas 

Kano et al., (2009, 594539); JBRC, (1998, 196240)—female Crj:BDF1 mice 

0 —a —a —a —a —a

66 +b —a —a —a +c,e

278 +b —a —a —a +c,e

964 +b +c,d —a —a +c,e

a

— No evidence demonstrating key event. 

b

+ 1,4-dioxane metabolism was not evaluated as part of the chronic bioassays. Data from pharmacokinetic studies 

suggest that metabolism of 1,4-dioxane by CYP2E1 and CYP2B2 occurs immediately and continues throughout the 

duration of exposure at all exposure levels. c

+ Evidence demonstrating key event. d

+ Single cell necrosis was observed in a 13 week bioassay for male rats (274 mg/kg-day), male mice (585 mg/kgday), and female mice (898 mg/kg-day) exposed to 1,4-dioxane in drinking water (Kano et al., 2008, 196245). e

+ Kano et al. (2009, 594539) reported incidence rates for hepatocellular adenomas and carcinomas; however, 

information from JBRC (1998, 196240) on incidence of liver hyperplasia was used to create this table. 

4.7.3.3.2. Nasal cavity. Toxicity and regeneration in nasal epithelium (i.e., atrophy, adhesion, 

inflammation, and hyperplasia and metaplasia of respiratory and olfactory epithelium) was 

evident in one study at the same dose levels that produced nasal cavity tumors (see also JBRC, 

1998, 196240; Kano et al., 2009, 594539). 

4.7.3.4. Temporal Relationship 

4.7.3.4.1. Liver. Available information regarding temporal relationships between the key event 

(sustained proliferation of spontaneously transformed liver cells) and the eventual formation of 

liver tumors is limited. A comparison of 13-week and 2-year studies conducted in F344/DuCrj 

rats and Crj:BDF1 mice at the same laboratory revealed that tumorigenic doses of 1,4-dioxane 

produced liver toxicity by 13 weeks of exposure (JBRC, 1998, 196240; Kano et al., 2008, 

196245; Kano et al., 2009, 594539). Hepatocyte swelling of the centrilobular area of the liver, 

vacuolar changes in the liver, granular changes in the liver, and single cell necrosis in the liver 

were observed in mice and rats given 1,4-dioxane in the drinking water for 13 weeks. Sustained 

liver damage could presumably lead to regenerative hyperplasia and tumor formation following 

chronic exposure. As discussed above, histopathological evidence of regenerative hyperplasia 

has been seen following long-term exposure to 1,4-dioxane (JBRC, 1998, 196240; Kociba et al., 

1974, 062929). Tumors occurred earlier at high doses in both mice and rats from this study 

(Yamazaki, 2006, 626614); however, temporal information regarding hyperplasia or other 

possible key events was not available (i.e., interim blood samples not collected, interim sacrifices 

were not performed). Argus et al. (1973, 062912) studied the progression of tumorigenesis by 

electron microscopy of liver tissues obtained following interim sacrifices at 8 and 13 months of 

 90 
 

exposure (five rats/group, 574 mg/kg-day). The first change observed was an increase in the size 

of the nuclei of the hepatocytes, mostly in the periportal area. Precancerous changes were 

characterized by disorganization of the rough endoplasmic reticulum, increase in smooth 

endoplasmic reticulum, and decrease in glycogen and increase in lipid droplets in hepatocytes. 

These changes increased in severity in the hepatocellular carcinomas in rats exposed to 

1,4-dioxane for 13 months. 

Three types of liver nodules were observed in exposed rats at 13–16 months. The first 

consisted of groups of these cells with reduced cytoplasmic basophilia and a slightly nodular 

appearance as viewed by light microscopy. The second type of nodule was described consisting 

of large cells, apparently filled and distended with fat. The third type of nodule was described as 

finger-like strands, 2–3 cells thick, of smaller hepatocytes with large hyperchromic nuclei and 

dense cytoplasm. This third type of nodule was designated as an incipient hepatoma, since it 

showed all the histological characteristics of a fully developed hepatoma. All three types of 

nodules were generally present in the same liver. 

4.7.3.4.2. Nasal cavity. No information was available regarding the temporal relationship 

between toxicity in the nasal epithelium and the formation of nasal cavity tumors. 

4.7.3.5. Biological Plausibility and Coherence 

4.7.3.5.1. Liver. The hypothesis that sustained proliferation of spontaneously transformed liver 

cells is a key event within a MOA is possible based on supporting evidence indicating that 

1,4-dioxane is a tumor promoter of mouse skin and rat liver tumors (Bull et al., 1986, 194336; 

King et al., 1973, 029390; Lundberg et al., 1987, 062933). Further support for this hypothesis is 

provided by studies demonstrating that 1,4-dioxane increased hepatocyte DNA synthesis, 

indicative of cell proliferation (Goldsworthy et al., 1991, 062925; Miyagawa et al., 1999, 

195063; Stott et al., 1981, 063021; Uno et al., 1994, 194385). In addition, the generally negative 

results for 1,4-dioxane in a number of genotoxicity assays indicates the carcinogenicity of 

1,4-dioxane may not be mediated by a mutagenic MOA. The importance of cytotoxicity as a 

necessary precursor to sustained cell proliferation is biologically plausible, but is not supported 

by the dose-response in the majority of studies of 1,4-dioxane carcinogenicity. 

4.7.3.5.2. Nasal cavity. Sustained cell proliferation in response to cell death from toxicity may 

be related to the formation of nasal cavity tumors; however, this MOA is also not established . 

Nasal carcinogens are generally characterized as potent genotoxins (Ashby, 1994, 195021); 

however, other MOAs have been proposed for nasal carcinogens that induce effects through 

other mechanisms (Green et al., 2000, 196210; Kasper et al., 2007, 195045). 

The National Toxicological Program (NTP) database identified 12 chemicals from 

approximately 500 bioassays as nasal carcinogens and 1,4-dioxane was the only identified nasal 

 91 
 

carcinogen that showed little evidence of genotoxicity (Haseman and Hailey, 1997, 195983). 

Nasal tumors were not observed in an inhalation study in Wistar rats exposed to 111 ppm for 

5 days/week for 2 years (Torkelson et al., 1974, 094807). 

4.7.3.6. Other Possible Modes of Action 

An alternate MOA could be hypothesized that 1,4-dioxane alters DNA, either directly or 

indirectly, which causes mutations in critical genes for tumor initiation, such as oncogenes or 

tumor suppressor genes. Following these events, tumor growth may be promoted by a number of 

molecular processes leading to enhanced cell proliferation or inhibition of programmed cell 

death. The results from in vitro and in vivo assays do not provide overwhelming support for the 

hypothesis of a genotoxic MOA for 1,4-dioxane carcinogenicity. The genotoxicity data for 

1,4-dioxane were reviewed in Section 4.5.1 and were summarized in Table 4-16. Negative 

findings were reported for mutagenicity in Salmonella typhimurium, Escherichia coli, and 

Photobacterium phosphoreum (Mutatox assay) (Haworth et al., 1983, 028947; Hellmér and 

Bolcsfoldi, 1992, 194717; Khudoley et al., 1987, 194949; Kwan et al., 1990, 196078; Morita and 

Hayashi, 1998, 195065; Nestmann et al., 1984, 194339; Stott et al., 1981, 063021). Negative 

results were also indicated for the induction of aneuploidy in yeast (Saccharomyces cerevisiae) 

and the sex-linked recessive lethal test in Drosophila melanogaster (Zimmermann et al., 1985, 

194343). In contrast, positive results were reported in assays for sister chromatid exchange 

(Galloway et al., 1987, 007768), DNA damage (Kitchin and Brown, 1990, 062928), and in in 

vivo micronucleus formation in bone marrow (Mirkova, 1994, 195062; Roy et al., 2005, 

196094), and liver (Morita and Hayashi, 1998, 195065; Roy et al., 2005, 196094). Lastly, in the 

presence of toxicity, positive results were reported for meiotic nondisjunction in drosophila 

(Munoz and Barnett, 2002, 195066), DNA damage (Sina et al., 1983, 007323), and cell 

transformation (Sheu et al., 1988, 195078). 

Additionally, 1,4-dioxane metabolism did not produce reactive intermediates that 

covalently bound to DNA (Stott et al., 1981, 063021; Woo et al., 1977, 062950) and DNA repair 

assays were generally negative (Goldsworthy et al., 1991, 062925; Stott et al., 1981, 063021). 

No studies were available to assess the ability of 1,4-dioxane or its metabolites to induce 

oxidative damage to DNA. 

4.7.3.7. Conclusions About the Hypothesized Mode of Action 

4.7.3.7.1. Liver. The MOA by which 1,4-dioxane produces liver tumors is unknown, and 

available evidence in support of any hypothetical mode of carcinogenic action for 1,4-dioxane is 

inconclusive. A MOA hypothesis involving 1,4-dioxane induced cell proliferation is possible 

but data are not available to support this hypothesis. Pharmacokinetic data suggest that 

clearance pathways were saturable and target organ toxicity occurs after metabolic saturation. 

Liver toxicity preceded tumor formation in one study (Kociba et al., 1974, 062929) and a 

 92 
 

regenerative response to tissue injury was demonstrated by histopathology. Liver hyperplasia 

and tumor formation have also been observed in the absence of cytotoxicity (see also JBRC, 

1998, 196240; Kano et al., 2009, 594539). Cell proliferation and tumor promotion have been 

shown to occur after prolonged exposure to 1,4-dioxane (Bull et al., 1986, 194336; Goldsworthy 

et al., 1991, 062925; King et al., 1973, 029390; Lundberg et al., 1987, 062933; Miyagawa et al., 

1999, 195063; Stott et al., 1981, 063021; Uno et al., 1994, 194385). 

4.7.3.7.2. Nasal cavity. The MOA for the formation of nasal cavity tumors is unknown, and 

evidence in support of any hypothetical mode of carcinogenic action for 1,4-dioxane is 

inconclusive. 

4.7.3.8. Relevance of the Mode of Action to Humans 

Several hypothesized MOAs for 1,4-dioxane induced tumors in laboratory animals have 

been discussed along with the supporting evidence for each. As was stated, the MOA by which 

1,4-dioxane produces liver, nasal, peritoneal, and mammary gland tumors is unknown. Some 

mechanistic information is available to inform the MOA of the liver and nasal tumors but no 

information exists to inform the MOA of the observed peritoneal or mammary gland tumors (see 

also JBRC, 1998, 196240; Kano et al., 2009, 594539; Yamazaki et al., 1994, 196120). 

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES 

There is no direct evidence to establish that certain populations and lifestages may be 

potentially susceptible to 1,4-dioxane. Changes in susceptibility with lifestage as a function of 

the presence of microsomal enzymes that metabolize and detoxify this compound (i.e., CYP2E1 

present in liver, kidney, and nasal mucosa can be hypothesized). Vieira et al. (1996, 011956) 

reported that large increases in hepatic CYP2E1 protein occur postnatally between 1 and 

3 months in humans. Adult hepatic concentrations of CYP2E1 are achieved sometime between 1 

and 10 years. To the extent that hepatic CYP2E1 levels are lower, children may be more 

susceptible to liver toxicity from 1,4-dioxane than adults. CYP2E1 has been shown to be 

inducible in the rat fetus. The level of CYP2E1 protein was increased by 1.4-fold in the maternal 

liver and 2.4-fold in the fetal liver following ethanol treatment, as compared to the untreated or 

pair-fed groups (Carpenter et al., 1996, 080660). Pre- and postnatal induction of microsomal 

enzymes resulting from exposure to 1,4-dioxane or other drugs or chemicals may reduce overall 

toxicity following sustained exposure to 1,4-dioxane. 

Genetic polymorphisms have been identified for the human CYP2E1 gene (Hayashi et 

al., 1991, 196219; Watanabe et al., 1994, 196099) and were considered to be possible factors in 

the abnormal liver function seen in workers exposed to vinyl chloride (Huang et al., 1997, 

005276). Individuals with a CYP2E1 genetic polymorphism resulting in increased expression of 

this enzyme may be less susceptible to toxicity following exposure to 1,4-dioxane. 

 93 
 

Gender differences were noted in subchronic and chronic toxicity studies of 1,4-dioxane 

in mice and rats (see Sections 4.6 and 4.7). No consistent pattern of gender sensitivity was 

identified across studies. 

 94 
 

5. DOSE-RESPONSE ASSESSMENTS 

5.1. ORAL REFERENCE DOSE (RfD) 

5.1.1. Choice of Principal Studies and Critical Effect with Rationale and Justification 

Liver and kidney toxicity were the primary noncancer health effects associated with 

exposure to 1,4-dioxane in humans and laboratory animals. Occupational exposure to 

1,4-dioxane has resulted in hemorrhagic nephritis and centrilobular necrosis of the liver (Barber, 

1934, 062913; Johnstone, 1959, 062927). In animals, liver and kidney degeneration and necrosis 

were observed frequently in acute oral and inhalation studies (David, 1964, 195954; 

de Navasquez, 1935, 196174; Drew et al., 1978, 067913; Fairley et al., 1934, 062919; JBRC, 

1998, 196242; Kesten et al., 1939, 194972; Laug et al., 1939, 195055; Schrenk and Yant, 1936, 

195076). Liver and kidney effects were also observed following chronic oral exposure to 

1,4-dioxane in animals (Argus et al., 1965, 017009; Argus et al., 1973, 062912; JBRC, 1998, 

196240; Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 062935; Yamazaki 

et al., 1994, 196120) (see Table 4-18). 

Liver toxicity in the available chronic studies was characterized by necrosis, spongiosis 

hepatic, hyperplasia, cyst formation, clear foci, and mixed cell foci. Kociba et al. (1974, 062929) 

demonstrated hepatocellular degeneration and necrosis at doses of 94 mg/kg-day (LOAEL in 

male rats) or greater. The NOAEL for liver toxicity was 9.6 mg/kg-day and 19 mg/kg-day in 

male and female rats, respectively. No quantitative incidence data were provided in this study. 

Argus et al. (1973, 062912) described early preneoplastic changes in the liver and JBRC (1998, 

196240) demonstrated liver lesions that are primarily associated with the carcinogenic process. 

Clear and mixed-cell foci in the liver are commonly considered preneoplastic changes and would 

not be considered evidence of noncancer toxicity. In the JBRC (1998, 196240) study, spongiosis 

hepatis was associated with other preneoplastic changes in the liver (clear and mixed-cell foci) 

and no other lesions indicative of liver toxicity were seen. Spongiosis hepatis was therefore not 

considered indicative of noncancer effects in this study. The activity of serum enzymes (i.e., 

AST, ALT, LDH, and ALP) was increased in mice and rats chronically exposed to 1,4-dioxane 

(JBRC, 1998, 196240); however, these increases were seen only at tumorigenic dose levels. 

Blood samples were collected at study termination and elevated serum enzymes may reflect 

changes associated with tumor formation. Histopathological evidence of liver toxicity was not 

seen in rats from the JBRC (1998, 196240) study. The highest non-tumorigenic dose levels for 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 95 
 

this study approximated the LOAEL derived from the Kociba et al. (1974, 062929) study (94 and 

148 mg/kg-day for male and female rats, respectively). 

Kidney damage in chronic toxicity studies was characterized by degeneration of the 

cortical tubule cells, necrosis with hemorrhage, and glomerulonephritis (Argus et al., 1965, 

017009; Argus et al., 1973, 062912; Fairley et al., 1934, 062919; Kociba et al., 1974, 062929; 

NCI, 1978, 062935). Kociba et al. (1974, 062929) described renal tubule epithelial cell 

degeneration and necrosis at doses of 94 mg/kg-day (LOAEL in male rats) or greater, with a 

NOAEL of 9.6 mg/kg-day. No quantitative incidence data were provided in this study (Kociba 

et al., 1974, 062929). Doses of ≥ 430 mg/kg-day 1,4-dioxane induced marked kidney alterations 

(Argus et al., 1973, 062912). The observed changes included glomerulonephritis and 

pyelonephritis, with characteristic epithelial proliferation of Bowman’s capsule, periglomerular 

fibrosis, and distension of tubules. Quantitative incidence data were not provided in this study. 

In the NCI (1978, 062935) study, kidney lesions in rats consisted of vacuolar degeneration 

and/or focal tubular epithelial regeneration in the proximal cortical tubules and occasional 

hyaline casts. Kidney toxicity was not seen in rats from the JBRC (1998, 196240) study at any 

dose level (highest dose was 274 mg/kg-day in male rats and 429 mg/kg-day in female rats). 

Kociba et al. (1974, 062929) was chosen as the principal study for derivation of the RfD 

because the liver and kidney effects in this study are considered adverse and represent the most 

sensitive effects identified in the database (NOAEL 9.6 mg/kg-day, LOAEL 94 mg/kg-day in 

male rats). Kociba et al. (1974, 062929) reported degenerative effects in the liver, while liver 

lesions reported in other studies (Argus et al., 1973, 062912; JBRC, 1998, 196240) appeared to 

be related to the carcinogenic process. Kociba et al. (1974, 062929) also reported degenerative 

changes in the kidney. NCI (1978, 062935) and Argus et al. (1973, 062912) provided supporting 

data for this endpoint; however, kidney toxicity was observed in these studies at higher doses. 

JBRC (1998, 196240) reported nasal inflammation in rats (NOAEL 55 mg/kg-day, LOAEL 

274 mg/kg-day) and mice (NOAEL 66 mg/kg-day, LOAEL 278 mg/kg-day). 

Even though the study reported by Kociba et al. (1974, 062929) had one noteworthy 

weakness, it had several noted strengths, including: (1) two-year study duration; (2) use of both 

male and female rats and three dose levels, 10-fold apart, plus a control group; (3) a sufficient 

number of animals per dose group (60 animals/sex/dose group; and (4) the authors conducted a 

comprehensive evaluation of the animals including body weights and clinical observations, blood 

samples, organ weights of all the major tissues, and a complete histopathological examination of 

all rats. The authors did not report individual incidence data that would have allowed for a BMD 

analysis of this robust dataset. 

5.1.2. Methods of Analysis—Including Models (PBPK, BMD, etc.) 

Several procedures were applied to the human PBPK model to determine if an adequate 

fit of the model to the empirical model output or experimental observations could be attained 

 96 
 

using biologically plausible values for the model parameters. The re-calibrated model 

predictions for blood 1,4-dioxane levels did not come within 10-fold of the experimental values 

using measured tissue:air partition coefficients of Leung and Paustenbach (1990, 062932) or 

Sweeney et al. (2008, 195085) (Figures B-8 and B-9). The utilization of a slowly perfused 

tissue:air partition coefficient 10-fold lower than measured values produces exposure-phase 

predictions that are much closer to observations, but does not replicate the elimination kinetics 

(Figure B-10). Re-calibration of the model with upper bounds on the tissue:air partition 

coefficients results in predictions that are still six- to sevenfold lower than empirical model 

prediction or observations (Figures B-12 and B-13). Exploration of the model space using an 

assumption of zero-order metabolism (valid for the 50 ppm inhalation exposure) showed that an 

adequate fit to the exposure and elimination data can be achieved only when unrealistically low 

values are assumed for the slowly perfused tissue:air partition coefficient (Figure B-16). 

Artificially low values for the other tissue:air partition coefficients are not expected to improve 

the model fit, as these parameters are shown in the sensitivity analysis to exert less influence on 

blood 1,4-dioxane than VmaxC and Km. This suggests that the model structure is insufficient to 

capture the apparent 10-fold species difference in the blood 1,4-dioxane between rats and 

humans. In the absence of actual measurements for the human slowly perfused tissue:air 

partition coefficient, high uncertainty exists for this model parameter value. Differences in the 

ability of rat and human blood to bind 1,4-dioxane may contribute to the difference in Vd. 

However, this is expected to be evident in very different values for rat and human blood:air 

partition coefficients, which is not the case (Table B-1). Therefore, some other, as yet unknown, 

modification to model structure may be necessary. 

Kociba et al. (1974, 062929) did not provide quantitative incidence or severity data for 

liver and kidney degeneration and necrosis. Benchmark dose (BMD) modeling could not be 

performed for this study and the NOAEL for liver and kidney degeneration (9.6 mg/kg-day in 

male rats) was used as the point of departure (POD) in deriving the RfD for 1,4-dioxane. 

Alternative PODs were calculated using incidence data reported for cortical tubule 

degeneration in male and female rats (NCI, 1978, 062935) and liver hyperplasia (JBRC, 1998, 

196240). The incidence data for cortical tubule cell degeneration in male and female rats 

exposed to 1,4-dioxane in the drinking water for 2 years are presented in Table 5-1. Details of 

the BMD analysis of these data are presented in Appendix C. Male rats were more sensitive to 

the kidney effects of 1,4-dioxane than females and the male rat data provided the lowest POD for 

cortical tubule degeneration in the NCI (1978, 062935) study (BMDL10 of 22.3 mg/kg-day) 

(Table 5-2). Incidence data (JBRC, 1998, 196240; Kano et al., 2009, 594539) for liver 

hyperplasia in male and female rats exposed to 1,4-dioxane in the drinking water for 2 years are 

presented in Table 5-3. Details of the BMD analysis of these data are presented in Appendix C. 

Male rats were more sensitive to developing liver hyperplasia due to exposure to 1,4-dioxane 

than females and the male rat data provided the lowest POD for hyperplasia in the JBRC (1998, 

 97 
 

196240) study (BMDL10 of 23.8 mg/kg-day) (Table 5-4). The BMDL10 values of 22.3 mg/kgday and 23.8 mg/kg-day from the NCI (1978, 062935) and JBRC (1998, 196240) studies, 

respectively, are about double the NOAEL (9.6 mg/kg-day) observed by Kociba et al. (1974, 

062929). 

Table 5-1. Incidence of cortical tubule degeneration in Osborne-Mendel rats 

exposed to 1,4-dioxane in drinking water for 2 years 

Males (mg/kg-day) Females (mg/kg-day) 

0 240 530 0 350 640 

0/31a 20/31b 27/33b 0/31a 0/34 10/32b

a

Statistically significant trend for increased incidence by Cochran-Armitage test (p < 0.05) performed for this 

review. 

b

Incidence significantly elevated compared to control by Fisher’s Exact test (p < 0.001) performed for this review. 

Source: NCI (1978, 062935). 

Table 5-2. BMD and BMDL values derived from BMD modeling of cortical 

tubule degeneration in male and female Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water for 2 years 

BMD10 (mg/kg-day) BMDL10 (mg/kg-day) 

Male rats 28.8 22.3 

Female rats 596.4 452.4 

Source: NCI (1978, 062935). 

Table 5-3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to 

1,4-dioxane in drinking water for 2 yearsa

Males (mg/kg-day) Females (mg/kg-day) 

0 11 55 274 0 18 83 429 

3/40 2/45 9/35b 12/22c 0/38b 0/37 1/38 14/24c

a

Dose information from Kano et al. (2009, 594539) and incidence data for sacrificed animals from JBRC (1998, 

196240). b

Statistically significant compared to controls by the Dunnett’s test (p < 0.05). c

Incidence significantly elevated compared to control by χ

2

 test (p < 0.01). 

Sources: Kano et al. (2009, 594539); JBRC (1998, 196240). 

 98 
 

Table 5-4. BMD and BMDL values derived from BMD modeling of liver 

hyperplasia in male and female F344/DuCrj rats exposed to 1,4-dioxane in 

drinking water for 2 years 

BMD10 (mg/kg-day) BMDL10 (mg/kg-day) 

Male rats 35.9 23.8 

Female rats 137.3 88.5 

Source: Kano et al. (2009, 594539); JBRC (1998, 196240). 

5.1.3. RfD Derivation - Including Application of Uncertainty Factors (UFs) 

The RfD of 3 × 10–2 mg/kg-day is based on liver and kidney toxicity in rats exposed to 

1,4-dioxane in the drinking water for 2 years (Kociba et al., 1974, 062929). The Kociba et al. 

(1974, 062929) study was chosen as the principal study because it provides the most sensitive 

measure of adverse effects by 1,4-dioxane. The incidence of liver and kidney lesions was not 

reported for each dose group. Therefore, BMD modeling could not be used to derive a POD. 

The RfD for 1,4-dioxane is derived by dividing the NOAEL of 9.6 mg/kg-day (Kociba et al., 

1974, 062929) by a composite UF of 300, as follows: 

 RfD = NOAEL / UF 

 = 9.6 mg/kg-day / 300 

 = 0.03 or 3 × 10–2 mg/kg-day 

The composite UF of 300 includes factors of 10 for animal-to-human extrapolation and 

for interindividual variability, and an UF of 3 for database deficiencies. 

A default interspecies UF of 10 was used to account for pharmacokinetic and 

pharmacodynamic differences across species. Existing PBPK models could not be used to derive 

an oral RfD for 1,4-dioxane (Appendix B). 

A default interindividual variability UF of 10 was used to account for variation in 

sensitivity within human populations because there is limited information on the degree to which 

humans of varying gender, age, health status, or genetic makeup might vary in the disposition of, 

or response to, 1,4-dioxane. 

An UF of 3 for database deficiencies was applied due to the lack of a multigeneration 

reproductive toxicity study. A single oral prenatal developmental toxicity study in rats was 

available for 1,4-dioxane (Giavini et al., 1985, 062924). This developmental study indicates that 

the developing fetus may be a target of toxicity. 

An UF to extrapolate from a subchronic to a chronic exposure duration was not necessary 

because the RfD was derived from a study using a chronic exposure protocol. 

An UF to extrapolate from a LOAEL to a NOAEL was not necessary because the RfD 

was based on a NOAEL. Kociba et al. (1974, 062929) was a well-conducted, chronic drinking 

water study with an adequate number of animals. Histopathological examination was performed 

 99 
 

for many organs and tissues, but clinical chemistry analysis was not performed. NOAEL and 

LOAEL values were derived by the study authors based on liver and kidney toxicity; however 

quantitative incidence data was not reported. Several additional oral studies (acute/short-term, 

subchronic, and chronic durations) were available that support liver and kidney toxicity as the 

critical effect (Argus et al., 1973, 062912; JBRC, 1998, 196240; Kano et al., 2008, 196245; NCI, 

1978, 062935) (Tables 4-15 and 4-17). Although degenerative liver and kidney toxicity was not 

observed in rats from the JBRC (1998, 196240) study at doses at or below the LOAEL in the 

Kociba et al. (1974, 062929) study, other endpoints such as metaplasia and hyperplasia of the 

nasal epithelium, nuclear enlargement, and hematological effects, were noted. 

5.1.4. RfD Comparison Information 

PODs and sample oral RfDs based on selected studies included in Table 4-18 are arrayed 

in Figures 5-1 to 5-3, and provide perspective on the RfD supported by Kociba et al. (1974, 

062929). These figures should be interpreted with caution because the PODs across studies are 

not necessarily comparable, nor is the confidence in the data sets from which the PODs were 

derived the same. PODs in these figures may be based on a NOAEL, LOAEL, or BMDL (as 

indicated), and the nature, severity, and incidence of effects occurring at a LOAEL are likely to 

vary. To some extent, the confidence associated with the resulting sample RfD is reflected in the 

magnitude of the total UF applied to the POD (i.e., the size of the bar); however, the text of 

Sections 5.1.1 and 5.1.2 should be consulted for a more complete understanding of the issues 

associated with each data set and the rationale for the selection of the critical effect and principal 

study used to derive the RfD. 

The predominant noncancer effect of chronic oral exposure to 1,4-dioxane is 

degenerative effects in the liver and kidney. Figure 5-1 provides a graphical display of effects 

that were observed in the liver following chronic oral exposure to 1,4-dioxane. Information 

presented includes the PODs and UFs that could be considered in deriving the oral RfD. As 

discussed in Sections 5.1.1 and 5.1.2, among those studies that demonstrated liver toxicity, the 

study by Kociba et al. (1974, 062929) provided the data set most appropriate for deriving the 

RfD. For degenerative liver effects resulting from 1,4-dioxane exposure, the Kociba et al. (1974, 

062929) study represents the most sensitive effect and dataset observed in a chronic bioassay 

(Figure 5-1). 

Kidney toxicity as evidenced by glomerulonephritis (Argus et al., 1965, 017009; Argus et 

al., 1973, 062912) and degeneration of the cortical tubule (Kociba et al., 1974, 062929; NCI, 

1978, 062935) has also been observed in response to chronic exposure to 1,4-dioxane. As was 

discussed in Sections 5.1 and 5.2, degenerative effects were observed in the kidney at the same 

dose level as effects in the liver (Kociba et al., 1974, 062929). A comparison of the available 

datasets from which an RfD could potentially be derived is presented in Figure 5-2. 

 100 
 

Rhinitis and inflammation of the nasal cavity were reported in both the NCI (1978, 

062935) (mice only, dose ≥ 380 mg/kg-day) and JBRC (1998, 196240) studies (≥ 274 mg/kg-day 

in rats, >278 mg/kg-day in mice). JBRC (1998, 196240) reported nasal inflammation in rats 

(NOAEL 55 mg/kg-day, LOAEL 274 mg/kg-day) and mice (NOAEL 66 mg/kg-day, LOAEL 

278 mg/kg-day). A comparison of the available datasets from which an RfD could potentially be 

derived is presented in Figure 5-3. 

Figure 5-4 displays PODs for the major targets of toxicity associated with oral exposure 

to 1,4-dioxane. Studies in experimental animals have also found that relatively high doses of 

1,4-dioxane (1,000 mg/kg-day) during gestation can produce delayed ossification of the 

sternebrae and reduced fetal BWs (Giavini et al., 1985, 062924). This graphical display 

(Figure 5-4) compares organ specific toxicity for 1,4-dioxane, including a single developmental 

study. The most sensitive measures of degenerative liver are and kidney effects. The sample 

RfDs for degenerative liver and kidney effects are identical since they were derived from the 

same study and dataset (Kociba et al., 1974, 062929) and are presented for completeness. 

0.01

0.1

1

10

100

Liver hyperplasia;

NOAEL; 2 yr rat

drinking water study 

Hepatocellular

degeneration and

necrosis; NOAEL; 2 yr

rat drinking water study 

Increase in serum liver

enzymes; NOAEL; 2 yr

mouse drinking water

study 

Increase in serum liver

enzymes; NOAEL; 2 yr

rat drinking water study 

Liver hyperplasia;

BMDL10; 2 yr rat

drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Rat Rat Mouse Rat Rat

Figure 5-1. Potential points of departure (POD) for liver toxicity endpoints 

with corresponding applied uncertainty factors and derived RfDs following 

oral exposure to 1,4-dioxane. 

 101 
 

0.01

0.1

1

10

100

1000

Glomerulonephritis; LOAEL; 13 month

rat drinking water study 

Degeneration and necrosis of tubular

epithelium; NOAEL; 2 yr rat drinking

water study 

Cortical tubule degeneration; BMDL10;

2 yr rat drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Rat Rat Rat

Figure 5-2. Potential points of departure (POD) for kidney toxicity endpoints 

with corresponding applied uncertainty factors and derived RfDs following 

oral exposure to 1,4-dioxane. 

 102 
 

0.1

1

10

100

Nasal inflammation; NOAEL; 2 yr mouse drinking water study Nasal inflammation; NOAEL; 2 yr rat drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Mouse Rat

Figure 5-3. Potential points of departure (POD) for nasal inflammation with 

corresponding applied uncertainty factors and derived sample RfDs 

following oral exposure to 1,4-dioxane. 

 103 
 

0.01

0.1

1

10

100

1000

Degeneration and necrosis

of tubular epithelium;

NOAEL; 2 yr rat drinking

water study 

Hepatocellular

degeneration and necrosis;

NOAEL; 2 yr rat drinking

water sduy 

Delayed ossification of

sternebrae and reduced

fetal body weight; NOAEL;

rat study gestation days 6-

15 

Nasal inflammation;

NOAEL; 2 yr mouse

drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Rat Rat Rat Mouse

Figure 5-4. Potential points of departure (POD) for organ specific toxicity 

endpoints with corresponding applied uncertainty factors and derived 

sample RfDs following oral exposure to 1,4-dioxane. 

5.1.5. Previous RfD Assessment 

An assessment for 1,4-dioxane was previously posted on the IRIS database in 1988. An 

oral RfD was not developed as part of the 1988 assessment. 

5.2. INHALATION REFERENCE CONCENTRATION (RFC) 

NOTE: During the development of this assessment, new data regarding the toxicity of 

1,4-dioxane through the inhalation route of exposure became available. The IRIS Program will 

evaluate the more recently published 1,4-dioxane inhalation data for the potential to derive an 

RfC in a separate assessment. A description of the studies that were available at the time that this 

assessment was under development are summarized below. 

Inhalation studies for 1,4-dioxane evaluated in this assessment were not adequate for the 

determination of an RfC value. Only one subchronic study (Fairley et al., 1934, 062919) and one 

chronic inhalation study (Torkelson et al., 1974, 094807) were identified. In the subchronic 

study, rabbits, guinea pigs, rats, and mice (3–6/species/group) were exposed to 1,000, 2,000, 

5,000, or 10,000 ppm of 1,4-dioxane vapor for 1.5 hours two times a day for 5 days, 1.5 hours 

 104 
 

for one day, and no exposure on the seventh day. Animals were exposed until death occurred or 

were sacrificed after various durations of exposure (3-202.5 hours). Detailed dose-response 

information was not provided; however, severe liver and kidney damage and acute vascular 

congestion of the lungs were observed at concentrations ≥ 1,000 ppm. Kidney damage was 

described as patchy degeneration of cortical tubules with vascular congestion and hemorrhage. 

Liver lesions varied from cloudy hepatocyte swelling to large areas of necrosis. 

Torkelson et al. (1974, 094807) performed a chronic inhalation study in which male and 

female Wistar rats (288/sex) were exposed to 111 ppm 1,4-dioxane vapor for 7 hours/day, 

5 days/week for 2 years. Control rats (192/sex) were exposed to filtered air. No significant 

effects were observed on BWs, survival, organ weights, hematology, clinical chemistry, or 

histopathology. Because Fairley et al. (1934, 062919) identified a free-standing LOAEL only, 

and Torkelson et al. (1974, 094807) identified a free-standing NOAEL only, neither study was 

sufficient to characterize the inhalation risks of 1,4-dioxane. A route extrapolation from oral 

toxicity data was not performed because 1,4-dioxane inhalation causes direct effects on the 

respiratory tract (i.e., respiratory irritation in humans, pulmonary congestion in animals) (Fairley 

et al., 1934, 062919; Wirth and Klimmer, 1936, 196105; Yant et al., 1930, 062952), which 

would not be accounted for in a cross-route extrapolation. In addition, available kinetic models 

are not suitable for this purpose (Appendix B). 

An assessment for 1,4-dioxane was previously posted on the IRIS database in 1988. An 

inhalation RfC was not developed as part of the 1988 assessment. 

5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE (RfD) 

 Risk assessments need to portray associated uncertainty. The following discussion 

identifies uncertainties associated with the RfD for 1,4-dioxane. As presented earlier in this 

section (5.1.2 and 5.1.3), the uncertainty factor approach (U.S. EPA, 1994, 006488; U.S. EPA, 

2002, 088824), was applied to a POD. Factors accounting for uncertainties associated with a 

number of steps in the analyses were adopted to account for extrapolating from an animal 

bioassay to human exposure, a diverse population of varying susceptibilities, and to account for 

database deficiencies. These extrapolations are carried out with current approaches given the 

paucity of experimental 1,4-dioxane data to inform individual steps. 

An adequate range of animal toxicology data are available for the hazard assessment of 

1,4-dioxane, as described throughout the previous section (Section 4). The database of oral 

toxicity studies includes chronic drinking water studies in rats and mice, multiple subchronic 

drinking water studies conducted in rats and mice, and a developmental study in rats. Toxicity 

associated with oral exposure to 1,4-dioxane is observed predominately in the liver and kidney. 

The database of inhalation toxicity studies in animals includes one subchronic bioassay in 

rabbits, guinea pigs, and rats, and a chronic inhalation bioassay in rats. Although the subchronic 

bioassay observed degenerative effects in the liver, kidney, and lungs of all species tested, the 

 105 
 

information reported from the study was insufficient to determine an exposure level below which 

these effects did not occur. The only available chronic inhalation bioassay did not indicate any 

treatment related effects due to exposure to 1,4-dioxane. Thus, the inhalation database lacked 

sufficient information to derive toxicity values relevant to this route of exposure for 1,4-dioxane. 

In addition to oral and inhalation data, there are PBPK models and genotoxicity studies of 

1,4-dioxane. Critical data gaps have been identified and uncertainties associated with data 

deficiencies of 1,4-dioxane are more fully discussed below. 

Consideration of the available dose-response data led to the selection of the two-year 

drinking water bioassay in Sherman rats (Kociba et al., 1974, 062929) as the principal study and 

increased liver and kidney degeneration as the critical effects for deriving the RfD for 

1,4-dioxane. The dose-response relationship for oral exposure to 1,4-dioxane and cortical tubule 

degeneration in Osborne-Mendel rats (NCI, 1978, 062935) was also suitable for deriving a RfD, 

but it is associated with higher a POD and potential RfD compared to Kociba et al. (1974, 

062929). 

The RfD was derived by applying UFs to a NOAEL for degenerative liver and kidney 

effects. The incidence data for the observed effects were not reported in the principal study 

(Kociba et al., 1974, 062929), precluding modeling of the dose-response. However confidence 

in the LOAEL can be derived from additional studies (Argus et al., 1965, 017009; Argus et al., 

1973, 062912; JBRC, 1998, 196240; NCI, 1978, 062935) that observed effects on the same 

organs at comparable dose levels and by the BMDL generated by modeling of the kidney doseresponse data from the chronic NCI (1978, 062935) study. 

Extrapolating from animals to humans embodies further issues and uncertainties. The 

effect and the magnitude associated with the dose at the POD in rodents are extrapolated to 

human response. Pharmacokinetic models are useful to examine species differences in 

pharmacokinetic processing; however, it was determined that dosimetric adjustment using 

pharmacokinetic modeling was to reduce uncertainty following oral exposure to 1,4-dioxane was 

not supported. Insufficient information was available to quantitatively assess toxicokinetic or 

toxicodynamic differences between animals and humans, so a 10-fold UF was used to account 

for uncertainty in extrapolating from laboratory animals to humans in the derivation of the RfD. 

Heterogeneity among humans is another uncertainty associated with extrapolating doses 

from animals to humans. Uncertainty related to human variation needs consideration. In the 

absence of 1,4-dioxane-specific data on human variation, a factor of 10 was used to account for 

uncertainty associated with human variation in the derivation of the RfD. Human variation may 

be larger or smaller; however, 1,4-dioxane-specific data to examine the potential magnitude of 

over- or under-estimation are unavailable. 

Uncertainties in the assessment of the health hazards of ingested 1,4-dioxane are 

associated with deficiencies in reproductive toxicity information. The oral database lacks a 

multigeneration reproductive toxicity study. A single oral prenatal developmental toxicity study 

 106 
 

in rats was available for 1,4-dioxane (Giavini et al., 1985, 062924). This developmental study 

indicates that the developing fetus may be a target of toxicity. The database of inhalation studies 

is of particular concern due to the lack of a basic toxicological studies, a multigenerational 

reproductive study, and developmental toxicity studies. 

5.4. CANCER ASSESSMENT 

5.4.1. Choice of Study/Data – with Rationale and Justification 

Three chronic drinking water bioassays provided incidence data for liver tumors in rats 

and mice, and nasal cavity, peritoneal, and mammary gland tumors in rats only (JBRC, 1998, 

196240; Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 062935; Yamazaki 

et al., 1994, 196120). The dose-response data from each of these studies are summarized in 

Table 5-5. With the exception of the NCI (1978, 062935) study, the incidence of nasal cavity 

tumors was generally lower than the incidence of liver tumors in exposed rats. The Kano et al. 

(2009, 594539) drinking water study was chosen as the principal study for derivation of an oral 

cancer slope factor (CSF) for 1,4-dioxane. This study used three dose groups in addition to 

controls and characterized the dose-response relationship at lower exposure levels, as compared 

to the high doses employed in the NCI (1978, 062935) bioassay (Table 5-5). The Kociba et al. 

(1974, 062929) study also used three dose groups and low exposures; however, the study authors 

only reported the incidence of hepatocellular carcinoma, which may underestimate the combined 

incidence of rats with adenoma or carcinoma. In addition to increased incidence of liver tumors, 

chosen as the most sensitive target organ for tumor formation, the Kano et al. (2009, 594539) 

study also noted increased incidence of peritoneal and mammary gland tumors. Nasal cavity 

tumors were also seen in high-dose male and female rats; however, the incidence of nasal tumors 

was much lower than the incidence of liver tumors in both rats and mice. 

In a personal communication, Dr. Yamazaki (2006, 626614) provided that the survival of 

mice was low in all male groups (31/50, 33/50, 25/50 and 26/50 in control, low-, mid-, and highdose groups, respectively) and particularly low in high-dose females (29/50, 29/50, 17/50, and 

5/50 in control, low-, mid-, and high-dose groups, respectively). These deaths occurred 

primarily during the second year of the study. Survival at 12 months in male mice was 50/50, 

48/50, 50/50, and 48/50 in control, low-, mid-, and high-dose groups, respectively. Female 

mouse survival at 12 months was 50/50, 50/50, 48/50, and 48/50 in control, low-, mid-, and highdose groups, respectively (Yamazaki, 2006, 626614). Furthermore, these deaths were primarily 

tumor related. Liver tumors were listed as the cause of death for 31 of the 45 pretermination 

deaths in high-dose female Crj:BDF1 mice (Yamazaki, 2006, 626614). Thus, the high mortality 

rates in the female mice were still considered to be relevant for this analysis. 

 107 
 

Table 5-5. Incidence of liver, nasal cavity, peritoneal, and mammary gland 

tumors in rats and mice exposed to 1,4-dioxane in drinking water for 2 years 

(based on survival to 12 months) 

Tumor Incidence 

Study Species/strain/gender 

Animal dose 

(mg/kg-day) Liver 

Nasal 

cavity Peritoneal 

Mammary 

gland 

0 1/106h 0/106h NA NA 

14 0/110 0/110 NA NA 

121 1/106 0/106 NA NA 

Kociba et al. 

(1974, 062929) 

Sherman rats, male 

and female 

combineda,b

1,307 10/66i 3/66 NA NA 

0 NA 0/33h NA NA 

240 NA 12/26 NA NA 

Male Osborne-Mendel 

ratsb

530 NA 16/33i NA NA 

0 0/31h 0/34h NA NA 

350 10/30i 10/30i NA NA 

Female OsborneMendel ratsb,c

640 11/29i 8/29i NA NA 

0 8/49h NA NA NA 

720 19/50i NA NA NA 

Male B6C3F1 miced

830 28/47i NA NA NA 

0 0/50h NA NA NA 

380 21/48i NA NA NA 

NCI (1978, 

062935) 

Female B6C3F1 miced

860 35/37i NA NA NA 

0 3/50 0/50 2/50 1/50 

11 4/50 0/50 2/50 2/50 

55 7/50 0/50 5/50 2/50 

Male F344/DuCrj 

ratsd,e,f,g

274 39/50j,k 7/50k 28/50j,k 6/50k

0 3/50 0/50 1/50 8/50 

18 1/50 0/50 0/50 8/50 

83 6/50 0/50 0/50 11/50 

Female F344/DuCrj 

ratsd,e,f,g

429 48/50j,k 8/50j,k 0/50 18/50i,k

0 23/50 0/50 NA NA 

49 31/50 0/50 NA NA

191 37/50i 0/50 NA NA

Male Crj:BDF1 miced

677 40/50j,k 1/50 NA NA

0 5/50 0/50 NA NA

66 35/50j 0/50 NA NA

278 41/50j 0/50 NA NA

Kano et al. (2009, 

594539) 

Female Crj:BDF1

miced

964 46/50j,k 1/50 NA NA

 108 
 

a

Incidence of hepatocellular carcinoma. 

b

Incidence of nasal squamous cell carcinoma. 

c

Incidence of hepatocellular adenoma. 

d

Incidence of hepatocellular adenoma or carcinoma. 

e

Incidence (sum) of all nasal tumors including squamous cell carcinoma, sarcoma, rhabdomyosarcoma, and 

esthesioneuroepithelioma. 

f

Incidence of peritoneal tumors (mesothelioma). 

g

Incidence of mammary gland tumors (fibroadenoma or adenoma) 

h

p < 0.05; positive dose-related trend (Cochran-Armitage or Peto’s test). i

Significantly different from control at p < 0.05 by Fisher’s Exact test. 

j

Significantly different from control at p < 0.01 by Fisher’s Exact test. k

p < 0.01; positive dose-related trend (Peto’s test). 

NA = data were not available for modeling (no significant change from controls) 

5.4.2. Dose-Response Data 

Table 5-6 summarizes the incidence of hepatocellular adenoma or carcinoma in rats and 

mice from the Kano et al. (2009, 594539) 2-year drinking water study. There were statistically 

significant increasing trends in tumorigenic response for males and females of both species. The 

dose-response curve for female mice is steep, with 70% incidence of liver tumors occurring in 

the low-dose group (66 mg/kg-day). Exposure to 1,4-dioxane increased the incidence of these 

tumors in a dose-related manner. 

A significant increase in the incidence of peritoneal mesothelioma was observed in highdose male rats only (28/50 rats, Table 5-5). The incidence of peritoneal mesothelioma was lower 

than the observed incidence of hepatocellular adenoma or carcinoma in male rats (Table 5-6); 

therefore, hepatocellular adenoma or carcinoma data were used to derive an oral CSF for 

1,4-dioxane. 

 109 
 

Table 5-6. Incidence of hepatocellular adenoma or carcinoma in rats and 

mice exposed to 1,4-dioxane in drinking water for 2 years 

Species/strain/gender 

Animal dose 

(mg/kg-day) Incidence of liver tumorsa

0 3/50 

11 4/50 

55 7/50 

Male F344/DuCrj rats 

274 39/50b,c

0 3/50 

18 1/50 

83 6/50 

Female F344/DuCrj rats 

429 48/50b,c

0 23/50 

49 31/50 

191 37/50d

Male Crj:BDF1 mice 

677 40/50b,c

0 5/50 

66 35/50c

278 41/50c

Female Crj:BDF1 mice 

964 46/50b,c

a

Incidence of either hepatocellular adenoma or carcinoma. 

b

p < 0.05; positive dose-related trend (Peto’s test). c

Significantly different from control at p < 0.01 by Fisher’s Exact test. d

Significantly different from control at p < 0.01 by Fisher’s Exact test. 

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539).

5.4.3. Dose Adjustments and Extrapolation Method(s) 

5.4.3.1. Dose Adjustments 

Human equivalent doses (HEDs) were calculated from the administered animal doses 

using a BW scaling factor (BW0.75). This was accomplished using the following equation: 

25.0

(kg)BW human 

(kg)BW animal HED (mg/kg) dose animal ⎥

⎦

⎤ ⎢

⎣

⎡ = ×

For all caculations, a human BW of 70 kg was used. HEDs for the principal study (Kano et al., 

2009, 594539) are given in Table 5-7. HEDs were also calculated for supporting studies (Kociba 

et al., 1974, 062929; NCI, 1978, 062935) and are also shown in Table 5-7. 

 110 
 

Table 5-7. Calculated HEDs for the tumor incidence data used for doseresponse modeling 

Study Species/strain/gender 

Animal BW (g) 

TWA 

Animal dose 

(mg/kg-day) 

HED 

(mg/kg-day)d

432a 11 3.1

432a 81 23

Male F344/DuCrj rats

432a 398 112

267a 18 4.5

267a 83 21

Female F344/DuCrj rats

267a 429 107

47.9a 49 7.9

47.9a 191 31

Male Crj:BDF1 mice

47.9a 677 110

35.9a 66 10

35.9a 278 42

Kano et al. (2009, 

594539) 

Female Crj:BDF1 mice

35.9a 964 145

325b 14 3.7 

325b 121 32 

Kociba et al. (1974, 

062929) 

Male and female (combined) 

Sherman rats 

285c 1,307 330 

470b Male Osborne-Mendel rats 240 69 

470b 530 152 

310b Female Osborne-Mendel rats 350 90 

310b 640 165 

32b Male B6C3F1 mice 720 105 

32b 830 121 

30b 380 55 

NCI (1978, 062935) 

Female B6C3F1 mice 

30b 860 124 

a

 TWA BWs were determined from BW growth curves provided for each species and gender.

b

TWA BWs were determined from BW curve provided for control animals. 

c

BWs of high dose male and female rats were significantly lower than controls throughout the study. TWA 

represents the mean of TWA for male and females (calculated separately from growth curves). d

HEDs are calculated as HED = (animal dose) × (animal BW / human BW)0.25. 

Sources: Kano et al. (2009, 594539); Kociba et al. (1974, 062929); and NCI (1978, 062935). 

5.4.3.2. Extrapolation Method(s) 

The U.S. EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237) 

recommend that the method used to characterize and quantify cancer risk from a chemical is 

determined by what is known about the mode of action of the carcinogen and the shape of the 

cancer dose-response curve. The linear approach is recommended if the mode of action of 

carcinogenicity is not understood (U.S. EPA, 2005, 086237). In the case of 1,4-dioxane, the 

mode of carcinogenic action for peritoneal, mammary, nasal, and liver tumors is unknown. 

Therefore, a linear low-dose extrapolation approach was used to estimate human carcinogenic 

risk associated with 1,4-dioxane exposure. 

 111 
 

However, several of the external peer review panel members (Appendix A: Summary of 

External Peer Review and Public Comments and Disposition) recommended that the mode of 

action data support the use of a nonlinear extrapolation approach to estimate human carcinogenic 

risk associated with exposure to 1,4-dioxane and that such an approach should be presented in 

the Toxicological Review. As discussed in Section 4.7.3., numerous short-term in vitro and a 

few in vivo tests were nonpositive for 1,4-dioxane-induced genotoxicity. Results from two-stage 

mouse skin tumor bioassays demonstrated that 1,4-dioxane does not initiate mouse skin tumors, 

but it is a promoter of skin tumors initiated by DMBA (King et al., 1973, 029390). These data 

suggest that a potential mode of action for 1,4-dioxane-induced tumors may involve proliferation 

of cells initiated spontaneously, or by some other agent, to become tumors (Bull et al., 1986, 

194336; Goldsworthy et al., 1991, 062925; King et al., 1973, 029390; Lundberg et al., 1987, 

062933; Miyagawa et al., 1999, 195063; Stott et al., 1981, 063021; Uno et al., 1994, 194385). 

However, key events related to the promotion of tumor formation by 1,4-dioxane are unknown. 

Therefore, under the U.S. EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 

086237), EPA concluded that the available information does not establish a plausible mode of 

action for 1,4-dioxane and data are insufficient to establish significant biological support for a 

nonlinear approach. EPA determined that there are no data available to inform the low-dose 

region of the dose response, and thus, a nonlinear approach was not included. 

Accordingly, the CSF for 1,4-dioxane was derived via a linear extrapolation from the 

POD calculated by curve fitting the experimental dose-response data. The POD is the 95% 

lower confidence limit on the dose associated with a benchmark response (BMR) near the lower 

end of the observed data. The BMD modeling analysis used to estimate the POD is described in 

detail in Appendix D and is summarized below in Section 5.4.4. 

Model estimates were derived for all available bioassays and tumor endpoints (Appendix 

D); however, the POD used to derive the CSF is based on the most sensitive species and target 

organ in the principal study (female mice; liver tumors; Kano et al., 2009, 594539). 

The oral CSF was calculated using the following equation: 

BMDL

BMR CSF =

5.4.4. Oral Slope Factor and Inhalation Unit Risk 

The dichotomous models available in the Benchmark Dose Software (BMDS, version 

2.1.1) were fit to the incidence data for “either hepatocellular carcinoma or adenoma” in rats and 

mice, as well as mammary and peritoneal tumors in rats exposed to 1,4-dioxane in the drinking 

water (Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 062935) (Table 5-5). 

Animal doses are used for BMD modeling and HED BMD and BMDL values are calculated 

using the animal TWAs (Table 5-7) and a human BW of 70kg. Doses associated with a BMR of 

10% extra risk were calculated. BMDs and BMDLs from all models are reported, and the output 

 112 
 

and plots corresponding to the best-fitting model are shown (Appendix D). When the best-fitting 

model is not a multistage model, the multistage model output and plot are also provided 

(Appendix D). A summary of the BMDS model predictions for the Kano et al. (2009, 594539), 

NCI (1978, 062935), and Kociba et al. (1974, 062929) studies is shown in Table 5-8. 

Table 5-8. BMD HED and BMDLHED values from models fit to tumor 

incidence data for rats and mice exposed to 1,4-dioxane in drinking water for 

2 years and corresponding oral CSFs 

Study Gender/strain/species Tumor type 

BMDHEDa

(mg/kg-day) 

BMDLHEDa

(mg/kgday) 

Oral CSF 

(mg/kg-day)-1

Male F344/DuCrj ratsb 17.43 14.33 7.0 x 10-3

Female F344/DuCrj ratsc 19.84 14.43 6.9 x 10-3

Male Crj:BDF1 miced 5.63 2.68 3.7 x 10-2

Female Crj:BDF1 miced 0.83 0.55 0.18 

Female Crj:BDF1 miced, e 3.22e 2.12e 0.14 

Female Crj:BDF1 miced, f

Hepatocellular 

adenoma or 

carcinoma 

7.51f 4.95f 0.10 

Female F344/DuCrj ratsg 94.84 70.23 1.4 x 10-3

Male F344/DuCrj ratsg

Nasal 

squamous cell 

carcinoma 

91.97 68.85 1.5 x 10-3

Male F344/DuCrj ratsb Peritoneal 

mesothelioma 

26.09 21.39 4.7 x 10-3

Kano et al. 

(2009, 

594539) 

Female F344/DuCrj ratsd Mammary 

gland 

adenoma 

40.01 20.35 4.9 x 10-3

Male and female (combined) 

Sherman ratsg

Nasal 

squamous cell 

carcinomas 

448.24 340.99 2.9 x 10-4 Kociba et al. 

(1974, 

062929) 

Male and female (combined) 

Sherman ratsb

Hepatocellular 

carcinoma 

290.78 240.31 4.2 x 10-4

Male Osborne Mendel ratsd 16.10 10.66 9.4 x 10-3

Female Osborne Mendel ratsd

Nasal 

squamous cell 

carcinomas 

40.07 25.82 3.9 x 10-3

Female Osborne Mendel ratsd Hepatocellular 

adenoma 

28.75 18.68 5.4 x 10-3

Female B6C3F1 micec 23.12 9.75 1.0 x 10-2

NCI (1978, 

062935) 

Male B6C3F1 miceh

Hepatocellular 

adenoma or 

carcinoma 

87.98 35.67 2.8 x 10-3

a

Values associated with a BMR of 10% unless otherwise noted. b

Probit model, slope parameter not restricted.

c

Multistage model, degree of polynomial = 2. 

d

Log-logistic model, slope restricted ≥ 1. e

Values associated with a BMR of 30%. 

f

Values associated with a BMR of 50%. 

g

Multistage model, degree of polynomial =3.

h

Gamma model. 

 113 
 

The multistage model did not provide an adequate fit (as determined by AIC, p-value 

< 0.1, and χ

2

p > |0.1|) to the data for the incidence of hepatocellular adenoma or carcinoma in 

female mice (Appendix D). The high dose was dropped for the female mouse liver tumor dataset 

in an attempt to achieve an adequate fit; however, an adequate fit was still not achieved. 

Because the female mice were clearly the most sensitive group tested, other BMD models were 

applied to the female mouse liver tumor dataset to achieve an adequate fit. The log-logistic 

model was the only model that provided adequate fit for this data set due to the steep rise in the 

dose-response curve (70% incidence at the low dose) followed by a plateau at near maximal 

tumor incidence in the mid- and high-dose regions (82 and 92% incidence, respectively). The 

predicted BMD10 and BMDL10 for the female mouse data are presented in Table 5-8, as well as 

BMDHED and BMDLHED values associated with BMRs of 30 and 50% . 

The multistage model also did not provide an adequate fit to mammary tumor incidence 

data for the female rat or male rat peritoneal tumors. The predicted BMD10 and BMDL10 for 

female rat mammary tumors and male peritoneal tumors obtained from the log-logistic and 

probit models, respectively, are presented in Table 5-8. 

A comparison of the model estimates derived for rats and mice from the Kano et al. 

(2009, 594539), NCI (1978, 062935), and Kociba et al. (1974, 062929) studies (Table 5-8) 

indicates that female mice are more sensitive to liver carcinogenicity induced by 1,4-dioxane 

compared to other species or tumor types. The BMDL50 HED for the female mouse data was 

chosen as the POD and the CSF of 0.10 (mg/kg-day)-1 was calculated as follows: 

1-

HED 50

day)-(mg/kg 0.10 (BMDLday -mg/kg 4.95 mice) femalefor 

0.50 CSF = =

Calculation of a CSF for 1,4-dioxane is based upon the dose-response data for the most 

sensitive species and gender. 

Inhalation studies for 1,4-dioxane evaluated in this assessment were not adequate for the 

determination of an inhalation unit risk. No treatment-related tumors were noted in a chronic 

inhalation study in rats; however, only a single exposure concentration was used (111 ppm 

1,4-dioxane vapor for 7 hours/day, 5 days/week for 2 years) (Torkelson et al., 1974, 094807). A 

route extrapolation from oral bioassay data was not performed (Section 5.2). In addition, 

available kinetic models are not suitable for this purpose (Appendix B). 

During the development of this assessment, new data regarding the toxicity of 

1,4-dioxane through the inhalation route of exposure became available. The IRIS Program will 

evaluate the more recently published 1,4-dioxane inhalation data for the potential to derive an 

inhalation unit risk in a separate assessment. 

5.4.5. Previous Cancer Assessment 

A previous cancer assessment was posted for 1,4-dioxane on IRIS in 1988. 1,4-Dioxane 

was classified as a Group B2 Carcinogen (probable human carcinogen; sufficient evidence from 

 114 
 

animal studies and inadequate evidence or no data from human epidemiology studies (U.S. EPA, 

1986, 199530)) based on the induction of nasal cavity and liver carcinomas in multiple strains of 

rats, liver carcinomas in mice, and gall bladder carcinomas in guinea pigs. An oral CSF of 0.011 

(mg/kg-day)-1 was derived from the tumor incidence data for nasal squamous cell carcinoma in 

male rats exposed to 1,4-dioxane in drinking water for 2 years (NCI, 1978, 062935). The 

linearized multistage extra risk procedure was used for linear low dose extrapolation. 

5.5. UNCERTAINTIES IN CANCER RISK VALUES 

As in most risk assessments, extrapolation of study data to estimate potential risks to 

human populations from exposure to 1,4-dioxane has engendered some uncertainty in the results. 

Several types of uncertainty may be considered quantitatively, but other important uncertainties 

cannot be considered quantitatively. Thus an overall integrated quantitative uncertainty analysis 

is not presented. Principal uncertainties are summarized below and in Table 5-9. 

5.5.1. Sources of Uncertainty 

5.5.1.1. Choice of Low-Dose Extrapolation Approach 

The range of possibilities for the low-dose extrapolation of tumor risk for exposure to 

1,4-dioxane, or any chemical, ranges from linear to nonlinear, but is dependent upon a plausible 

MOA(s) for the observed tumors. The MOA is a key consideration in clarifying how risks 

should be estimated for low-dose exposure. Exposure to 1,4-dioxane has been observed in 

animal models to induce multiple tumor types, including liver adenomas and carcinomas, nasal 

carcinomas, mammary adenomas and fibroadenomas, and mesotheliomas of the peritoneal cavity 

(JBRC, 1998, 196240; Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 1978, 

062935). MOA information that is available for the carcinogenicity of 1,4-dioxane has largely 

focused on liver adenomas and carcinomas, with little or no MOA information available for the 

remaining tumor types. In Section 4.7.3, hypothesized MOAs were explored for 1,4-dioxane. 

Information that would provide sufficient support for any MOA is not available. In the absence 

of a MOA(s) for the observed tumor types, a linear low-dose extrapolation approach was used to 

estimate human carcinogenic risk associated with 1,4-dioxane exposure. 

It is not possible to predict how additional MOA information would impact the doseresponse assessment for 1,4-dioxane because of the variety of tumors observed and the lack of 

data on how 1,4-dioxane or a metabolite thereof, interacts with cells starting the progression to 

the observed tumors. 

In general, the Agency has preferred to use the multistage model for analyses of tumor 

incidence and related endpoints because they have a generic biological motivation based on 

long-established mathematical models such as the Moolgavkar-Venzon-Knudsen (MVK) model. 

 115 
 

The MVK model does not necessarily characterize all modes of tumor formation, but it is 

a starting point for most investigations and, much more often than not, has provided at least an 

adequate description of tumor incidence data. 

In the studies evaluated (Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 

1978, 062935), the multistage model provided good descriptions of the incidence of a few tumor 

types in male (nasal cavity) and female (hepatocellular and nasal cavity) rats and in male mice 

(hepatocellular) exposed to 1,4-dioxane (Appendix D for details). However, the multistage 

model did not provide an adequate fit for the female mouse liver tumor dataset based upon the 

following (U.S. EPA, 2000, 052150): 

• Goodness-of-fit p-value was not greater than 0.10; 

• Akaike’s Information Criterion (AIC) was larger than other acceptable models; 

• Data deviated from the fitted model, as measured by their χ

2

 residuals (values were 

greater than an absolute value of one). 

BMDS software typically implements the guidance in the external peer review draft 

BMD technical guidance document (U.S. EPA, 2000, 052150) by imposing constraints on the 

values of certain parameters of the models. When these constraints were imposed, the multistage 

model and most other models did not fit the incidence data for female mouse liver adenomas or 

carcinomas. 

The log-logistic model was selected because it provides an adequate fit for the female 

mouse data (Kano et al., 2009, 594539). A BMR of 50% was used because it is proximate to the 

response at the lowest dose tested and the BMDL50 HED was derived by applying appropriate 

parameter constraints, consistent with recommended use of BMDS in the BMD technical 

guidance document (U.S. EPA, 2000, 052150). 

The human equivalent oral CSFs estimated from tumor datasets with statistically 

significant increases ranged from 4.2 × 10-4 to 0.18 per mg/kg-day (Table 5-8), a range of about 

three orders of magnitude, with the extremes coming from the combined male and female rat 

data for hepatocellular carcinomas (Kociba et al., 1974, 062929) and the female mouse combined 

liver adenoma and carcinomas (Kano et al., 2009, 594539). 

5.5.1.2. Dose Metric 

1,4-Dioxane is known to be metabolized in vivo. However, it is unknown whether a 

metabolite or the parent compound, or some combination of parent compound and metabolites, is 

responsible for the observed toxicity. If the actual carcinogenic moiety is proportional to 

administered exposure, then use of administered exposure as the dose metric is the least biased 

choice. On the other hand, if this is not the correct dose metric, then the impact on the CSF is 

unknown. 

 116 
 

5.5.1.3. Cross-Species Scaling 

An adjustment for cross-species scaling (BW0.75) was applied to address toxicological 

equivalence of internal doses between each rodent species and humans, consistent with the 2005 

Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237). It is assumed that equal 

risks result from equivalent constant lifetime exposures. 

5.5.1.4. Statistical Uncertainty at the POD 

Parameter uncertainty can be assessed through confidence intervals. Each description of 

parameter uncertainty assumes that the underlying model and associated assumptions are valid. 

For the log-logistic model applied to the female mouse data, there is a reasonably small degree of 

uncertainty at the 10% excess incidence level (the POD for linear low-dose extrapolation). 

5.5.1.5. Bioassay Selection 

The study by Kano et al. (2009, 594539) was used for development of an oral CSF. This 

was a well-designed study, conducted in both sexes in two species (rats and mice) with a 

sufficient number (N=50) of animals per dose group. The number of test animals allocated 

among three dose levels and an untreated control group was adequate, with examination of 

appropriate toxicological endpoints in both sexes of rats and mice. Alternative bioassays 

(Kociba et al., 1974, 062929; NCI, 1978, 062935) were available and were fully considered for 

the derivation of the oral CSF. 

5.5.1.6. Choice of Species/Gender 

The oral CSF for 1,4-dioxane was quantified using the tumor incidence data for the 

female mouse, which was shown to be more sensitive than male mice or either sex of rats to the 

carcinogenicity of 1,4-dioxane. While all data, both species and sexes reported from the Kano 

et al. (2009, 594539) study, were suitable for deriving an oral CSF, the female mouse data 

represented the most sensitive indicator of carcinogenicity in the rodent model. The lowest 

exposure level (66 mg/kg-day or 10 mg/kg-day [HED]) resulted in a considerable and significant 

increase in combined liver adenomas and carcinomas observed. Additional testing of doses 

within the range of control and the lowest dose (66 mg/kg-day or 10 mg/kg-day [HED]) could 

refine and reduce uncertainty for the oral CSF. 

A personal communication from Dr. Yamazaki (2006, 626614) provided that the survival 

of mice was particularly low in high-dose females (29/50, 29/50, 17/50, and 5/50 in control, 

low-, mid-, and high-dose groups, respectively). These deaths occurred primarily during the 

second year of the study. Female mouse survival at 12 months was 50/50, 50/50, 48/50, and 

48/50 in control, low-, mid-, and high-dose groups, respectively (Yamazaki, 2006, 626614). 

Furthermore, these deaths were primarily tumor related. Liver tumors were listed as the cause of 

death for 1/21, 2/21, 8/33, and 31/45 of the pretermination deaths in control, low-, mid- and, 

high-dose female Crj:BDF1 mice (Yamazaki, 2006, 626614). Therefore, because a number of 

 117 
 

the deaths in female mice were attributed to liver tumors, this endpoint and species was still 

considered to be relevant for this analysis; however, the high mortality rate does contribute 

uncertainty. 

Additionally, the incidence of hepatocellular adenomas and carcinomas in historical 

controls was evaluated with the data from Kano et al. (2009, 594539). Katagiri et al. (1998, 

193804) summarized the incidence of hepatocellular adenomas and carcinomas in control male 

and female BDF1 mice from ten 2-year bioassays at the JBRC. For female mice, out of 499 

control mice, the incidence rates were 4.4% for hepatocellular adenomas and 2.0% for 

hepatocellular carcinomas. Kano et al. (2009, 594539) reported a 10% incidence rate for 

hepatocellular adenomas and a 0% incidence rate for hepatocellular carcinomas in control female 

BDF1. These incidence rates are near the historical control values and thus are appropriate for 

consideration in this assessment 

5.5.1.7. Relevance to Humans 

The derivation of the oral CSF is derived using the tumor incidence in the liver of female 

mice. A thorough review of the available toxicological data available for 1,4-dioxane provides 

no scientific justification to propose that the liver adenomas and carcinomas observed in animal 

models due to exposure to 1,4-dioxane are not relevant to humans. As such, liver adenomas and 

carcinomas were considered relevant to humans due to exposure to 1,4-dioxane. 

5.5.1.8. Human Population Variability 

The extent of inter-individual variability in 1,4-dioxane metabolism has not been 

characterized. A separate issue is that the human variability in response to 1,4-dioxane is also 

unknown. Data exploring whether there is differential sensitivity to 1,4-dioxane carcinogenicity 

across life stages are unavailable. This lack of understanding about potential differences in 

metabolism and susceptibility across exposed human populations thus represents a source of 

uncertainty. Also, the lack of information linking a MOA for 1,4-dioxane to the observed 

carcinogenicity is a source of uncertainty. 

 118 
 

Table 5-9. Summary of uncertainty in the 1,4-dioxane cancer risk estimation 

Consideration/ 

approach 

Impact on oral slope 

factor Decision Justification 

Low-dose 

extrapolation 

procedure 

Departure from 

EPA’s Guidelines for 

Carcinogen Risk 

Assessment POD

paradigm, if justified, 

could ↓ or ↑ unit risk 

an unknown extent 

Log-logistic 

model to 

determine POD, 

linear low-dose 

extrapolation 

from POD 

A linear low-dose extrapolation approach was used 

to estimate human carcinogenic risk associated 

with 1,4-dioxane exposure. Where data are 

insufficient to ascertain the MOA, EPA’s 2005 

Guidelines for Carcinogen Risk Assessment 

recommend application of a linear low-dose 

extrapolation approach. 

Dose metric Alternatives could ↑

or ↓ CSF by an 

unknown extent 

Used 

administered 

exposure 

Experimental evidence supports a role for 

metabolism in toxicity, but it is unclear if the 

parent compound, metabolite or both contribute to 

1,4-dioxane toxicity. 

Cross-species 

scaling 

Alternatives could ↓

or ↑ CSF [e.g., 3.5-

fold ↓ (scaling by 

BW) or ↑ twofold 

(scaling by BW0.67 )] 

BW0.75 (default 

approach) 

There are no data to support alternatives. BW0.75

scaling was used to calculate equivalent 

cumulative exposures for estimating equivalent 

human risks. PBPK modeling was conducted but 

not deemed suitable for interspecies extrapolation. 

Bioassay Alternatives could ↑

or ↓ CSF by an 

unknown extent 

JBRC (1998, 

196240) 

Alternative bioassays were available and 

considered for derivation of oral CSF. 

Species /gender 

combination 

Human risk could ↓

or ↑, depending on 

relative sensitivity 

Female mouse There are no MOA data to guide extrapolation 

approach for any choice. It was assumed that 

humans are as sensitive as the most sensitive 

rodent gender/species tested; true correspondence 

is unknown. Calculation of the CSF for 

1,4-dioxane was based on dose-response data from 

the most sensitive species and gender. The 

carcinogenic response occurs across species. 

Human 

relevance of 

mouse tumor 

data 

If rodent tumors 

proved not to be 

relevant to humans, 

unit risk would not 

apply i.e., could ↓

CSF 

Liver adenomas 

and carcinomas 

are relevant to 

humans 

1,4-dioxane is a multi-site carcinogen in rodents 

and the MOA(s) is unknown; carcinogenicity 

observed in the rodent studies is considered 

relevant to human exposure. 

Human 

population 

variability in 

metabolism 

and response/ 

sensitive 

subpopulations 

Low-dose risk ↑ or ↓

to an unknown extent 

Considered 

qualitatively 

No data to support range of human 

variability/sensitivity, including whether children 

are more sensitive. 

 119 
 

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE 

RESPONSE 

6.1. HUMAN HAZARD POTENTIAL 

1,4-Dioxane is absorbed rapidly following oral and inhalation exposure, with much less 

absorption occurring from the dermal route. 1,4-Dioxane is primarily metabolized to HEAA, 

which is excreted in the urine. Liver and kidney toxicity are the primary noncancer health 

effects associated with exposure to 1,4-dioxane in humans and laboratory animals. Several fatal 

cases of hemorrhagic nephritis and centrilobular necrosis of the liver were related to 

occupational exposure (i.e., inhalation and dermal contact) to 1,4-dioxane (Barber, 1934, 

062913; Johnstone, 1959, 062927). Neurological changes were also reported in one case, 

including headache, elevation in blood pressure, agitation and restlessness, and coma (Johnstone, 

1959, 062927). Perivascular widening was observed in the brain of this worker, with small foci 

of demyelination in several regions (e.g., cortex, basal nuclei). Severe liver and kidney 

degeneration and necrosis were observed frequently in acute oral and inhalation studies 

(≥ 1,000 mg/kg-day oral, ≥ 1,000 ppm inhalation) (David, 1964, 195954; de Navasquez, 1935, 

196174; Drew et al., 1978, 067913; Fairley et al., 1934, 062919; JBRC, 1998, 196242; Kesten et 

al., 1939, 194972; Laug et al., 1939, 195055; Schrenk and Yant, 1936, 195076). 

Liver and kidney toxicity were the primary noncancer health effects of subchronic and 

chronic oral exposure to 1,4-dioxane in animals. Hepatocellular degeneration and necrosis were 

observed (Kociba et al., 1974, 062929) and preneoplastic changes were noted in the liver 

following chronic administration of 1,4-dioxane in drinking water (Argus et al., 1973, 062912; 

JBRC, 1998, 196240; Kano et al., 2009, 594539). Liver and kidney toxicity appear to be related 

to saturation of clearance pathways and an increase in the 1,4-dioxane concentration in the blood 

(Kociba et al., 1975). Kidney damage was characterized by degeneration of the cortical tubule 

cells, necrosis with hemorrhage, and glomerulonephritis (Argus et al., 1965, 017009; Argus et 

al., 1973, 062912; Fairley et al., 1934, 062919; Kociba et al., 1974, 062929; NCI, 1978, 062935). 

Several carcinogenicity bioassays have been conducted for 1,4-dioxane in mice, rats, and 

guinea pigs (Argus et al., 1965, 017009; Argus et al., 1973, 062912; Hoch-Ligeti and Argus, 

1970, 029386; Hoch-Ligeti et al., 1970, 062926; JBRC, 1998, 196240; Kano et al., 2009, 

594539; Kociba et al., 1974, 062929; NCI, 1978, 062935; Torkelson et al., 1974, 094807). Liver 

tumors (hepatocellular adenomas and carcinomas) have been observed following drinking water 

exposure in several species and strains of rats, mice, and guinea pigs. Nasal (squamous cell 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 120 
 

carcinomas), peritoneal, and mammary tumors were also observed in rats, but were not seen in 

mice. With the exception of the NCI (1978, 062935) study, the incidence of nasal cavity tumors 

was generally lower than that of liver tumors in the same study population. 

Under the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237), 

1,4-dioxane is “likely to be carcinogenic to humans” based on evidence of liver carcinogenicity 

in several 2-year bioassays conducted in three strains of rats, two strains of mice, and in guinea 

pigs (Argus et al., 1965, 017009; Argus et al., 1973, 062912; Hoch-Ligeti and Argus, 1970, 

029386; Hoch-Ligeti et al., 1970, 062926; JBRC, 1998, 196240; Kano et al., 2009, 594539; 

Kociba et al., 1974, 062929; NCI, 1978, 062935). Studies in humans found no conclusive 

evidence for a causal link between occupational exposure to 1,4-dioxane and increased risk for 

cancer; however, only two studies were available and these were limited by small cohort size and 

a small number of reported cancer cases (Buffler et al., 1978, 062914; Thiess et al., 1976, 

062943). 

The available evidence is inadequate to establish a MOA by which 1,4-dioxane induces 

liver tumors in rats and mice. The genotoxicity data for 1,4-dioxane is generally characterized as 

negative, although several studies may suggest the possibility of genotoxic effects (Galloway et 

al., 1987, 007768; Kitchin and Brown, 1990, 062928; Mirkova, 1994, 195062; Morita and 

Hayashi, 1998, 195065; Roy et al., 2005, 196094). A MOA hypothesis involving sustained 

proliferation of spontaneously transformed liver cells has some support by evidence that suggests 

1,4-dioxane is a tumor promoter in mouse skin and rat liver bioassays (King et al., 1973, 029390; 

Lundberg et al., 1987, 062933). Some dose-response and temporal evidence support the 

occurrence of cell proliferation and hyperplasia prior to the development of liver tumors (JBRC, 

1998, 196240; Kociba et al., 1974, 062929). However, the dose-response relationship for the 

induction of hepatic cell proliferation has not been characterized, and it is unknown if it would 

reflect the dose-response relationship for liver tumors in the 2-year rat and mouse studies. 

Conflicting data from rat and mouse bioassays (JBRC, 1998, 196240; Kociba et al., 1974, 

062929) suggest that cytotoxicity is not a required precursor event for 1,4-dioxane-induced cell 

proliferation. Liver tumors were observed in female rats and female mice in the absence of 

lesions indicative of cytotoxicity (JBRC, 1998, 196240; Kano et al., 2009, 594539; NCI, 1978, 

062935). Data regarding a plausible dose response and temporal progression from cytotoxicity 

to cell proliferation and eventual liver tumor formation are not available. 

6.2. DOSE RESPONSE 

6.2.1. Noncancer/Oral 

The RfD of 3 × 10-2 mg/kg-day was derived based on liver and kidney toxicity in rats 

exposed to 1,4-dioxane in the drinking water for 2 years (Kociba et al., 1974, 062929). This 

study was chosen as the principal study because it provides the most sensitive measure of 

 121 
 

adverse effects by 1,4-dioxane. The incidence of liver and kidney lesions was not reported for 

each dose group. Therefore, BMD modeling could not be used to derive a POD. Instead, the 

RfD is derived by dividing the NOAEL of 9.6 mg/kg-day by a composite UF of 300 (factors of 

10 for animal-to-human extrapolation and interindividual variability, and an UF of 3 for database 

deficiencies). Information was unavailable to quantitatively assess toxicokinetic or 

toxicodynamic differences between animals and humans and the potential variability in human 

susceptibility; thus, the interspecies and intraspecies uncertainty factors of 10 were applied. In 

addition, a threefold database uncertainty factor was applied due to the lack of information 

addressing the potential reproductive toxicity associated with 1,4-dioxane. 

The overall confidence in the RfD is medium. Confidence in the principal study (Kociba 

et al., 1974, 062929) is medium. Confidence in the database is medium due to the lack of a 

multigeneration reproductive toxicity study. Reflecting medium confidence in the principal 

study and medium confidence in the database, confidence in the RfD is medium. 

6.2.2. Noncancer/Inhalation 

No inhalation RfC was derived for 1,4-dioxane. Inhalation data were inadequate and a 

route extrapolation from oral toxicity data was not performed, due to direct effects of 

1,4-dioxane on the respiratory tract (i.e., respiratory irritation in humans, pulmonary congestion 

in animals) (Fairley et al., 1934, 062919; Wirth and Klimmer, 1936, 196105; Yant et al., 1930, 

062952) and lack of a suitable kinetic model (Appendix B). 

Note that during the development of this assessment, new data regarding the toxicity of 

1,4-dioxane through the inhalation route of exposure became available and have not been 

included in the current assessment. The IRIS Program will evaluate the more recently published 

1,4-dioxane inhalation in a separate assessment. 

6.2.3. Cancer/Oral 

Under EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237), 

1,4-dioxane is “likely to be carcinogenic to humans” by all routes of exposure. This descriptor is 

based on evidence of carcinogenicity from animal studies. An oral CSF for 1,4-dioxane of 

0.10 (mg/kg-day)-1 was based on liver tumors in female mice from a chronic study (Kano et al., 

2009, 594539). The available data indicate that the MOA(s) by which 1,4-dioxane induces 

peritoneal, mammary, or nasal tumors in rats and liver tumors in rats and mice is unknown (see 

Section 4.7.3 for a more detailed discussion of 1,4-dioxane’s hypothesized MOAs). Therefore, 

based on the U.S. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237), 

a linear low dose extrapolation was used. The POD was calculated by curve fitting the animal 

experimental dose-response data from the range of observation and converting it to a HED 

(BMDL50 HED of 4.95 mg/kg-day). 

The uncertainties associated with the quantitation of the oral CSF are discussed below. 

 122 
 

6.2.3.1. Choice of Low-Dose Extrapolation Approach 

The range of possibilities for the low-dose extrapolation of tumor risk for exposure to 

1,4-dioxane, or any chemical, ranges from linear to nonlinear, but is dependent upon a plausible 

MOA(s) for the observed tumors. The MOA is a key consideration in clarifying how risks 

should be estimated for low-dose exposure. Exposure to 1,4-dioxane has been observed in 

animal models to induce multiple tumor types, including liver adenomas and carcinomas, nasal 

carcinomas, mammary adenomas and fibroadenomas, and mesotheliomas of the peritoneal cavity 

(Kano et al., 2009, 594539). MOA information that is available for the carcinogenicity of 

1,4-dioxane has largely focused on liver adenomas and carcinomas, with little or no MOA 

information available for the remaining tumor types. In Section 4.7.3, hypothesized MOAs were 

explored for 1,4-dioxane. Data are not available to support a carcinogenic MOA for 

1,4-dioxane. In the absence of a MOA(s) for the observed tumor types associated with exposure 

to 1,4-dioxane, a linear low-dose extrapolation approach was used to estimate human 

carcinogenic risk associated with 1,4-dioxane exposure. 

In general, the Agency has preferred to use the multistage model for analyses of tumor 

incidence and related endpoints because they have a generic biological motivation based on 

long-established mathematical models such as the MVK model. The MVK model does not 

necessarily characterize all modes of tumor formation, but it is a starting point for most 

investigations and, much more often than not, has provided at least an adequate description of 

tumor incidence data. 

In the studies evaluated (Kano et al., 2009, 594539; Kociba et al., 1974, 062929; NCI, 

1978, 062935) the multistage model provided good descriptions of the incidence of a few tumor 

types in male (nasal cavity) and female (hepatocellular and nasal cavity) rats and in male mice 

(hepatocellular) exposed to 1,4-dioxane (see Appendix D for details). However, the multistage 

model did not provide an adequate fit for female mouse liver tumor dataset based upon the 

following (U.S. EPA, 2000, 052150): 

• Goodness-of-fit p-value was not greater than 0.10; 

• AIC was larger than other acceptable models; 

• Data deviated from the fitted model, as measured by their χ

2

 residuals (values were 

greater than an absolute value of one). 

BMDS software typically implements the guidance in the BMD technical guidance 

document (U.S. EPA, 2000, 052150) by imposing constraints on the values of certain parameters 

of the models. When these constraints were imposed, the multistage model and most other 

models did not fit the incidence data for female mouse liver adenomas or carcinomas. 

The log-logistic model was selected because it provides an adequate fit for the female 

mouse data (Kano et al., 2009, 594539). A BMR of 50% was used because it is proximate to the 

response at the lowest dose tested and the BMDL50 was derived by applying appropriate 

 123 
 

parameter constraints, consistent with recommended use of BMDS in the BMD technical 

guidance document (U.S. EPA, 2000, 052150). 

The human equivalent oral CSF estimated from liver tumor datasets with statistically 

significant increases ranged from 4.2 × 10-4 to 1.0 × 10-1 per mg/kg-day, a range of about three 

orders of magnitude, with the extremes coming from the combined male and female data for 

hepatocellular carcinomas (Kociba et al., 1974, 062929) and the female mouse liver adenoma 

and carcinoma dataset (Kano et al., 2009, 594539). 

6.2.3.2. Dose Metric 

1,4-Dioxane is known to be metabolized in vivo. However, evidence does not exist to 

determine whether the parent compound, metabolite(s), or a combination of the parent compound 

and metabolites is responsible for the observed toxicity following exposure to 1,4-dioxane. If the 

actual carcinogenic moiety is proportional to administered exposure, then use of administered 

exposure as the dose metric is the least biased choice. On the other hand, if this is not the correct 

dose metric, then the impact on the CSF is unknown. 

6.2.3.3. Cross-Species Scaling 

An adjustment for cross-species scaling (BW0.75) was applied to address toxicological 

equivalence of internal doses between each rodent species and humans, consistent with the 

Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237). It is assumed that equal 

risks result from equivalent constant lifetime exposures. 

6.2.3.4. Statistical Uncertainty at the POD 

Parameter uncertainty can be assessed through confidence intervals. Each description of 

parameter uncertainty assumes that the underlying model and associated assumptions are valid. 

For the log-logistic model applied to the female mouse data, there is a reasonably small degree of 

uncertainty at the 50% excess incidence level (the POD for linear low-dose extrapolation). 

6.2.3.5. Bioassay Selection 

The study by Kano et al. (2009, 594539) was used for development of an oral CSF. This 

was a well-designed study, conducted in both sexes in two species (rats and mice) with a 

sufficient number (N=50) of animals per dose group. The number of test animals allocated 

among three dose levels and an untreated control group was adequate, with examination of 

appropriate toxicological endpoints in both sexes of rats and mice. Alternative bioassays 

(Kociba et al., 1974, 062929; NCI, 1978, 062935) were available and were fully considered for 

the derivation of the oral CSF. 

6.2.3.6. Choice of Species/Gender 

The oral CSF for 1,4-dioxane was derived using the tumor incidence data for the female 

mouse, which was thought to be more sensitive than male mice or either sex of rats to the 

carcinogenicity of 1,4-dioxane. While all data, from both species and sexes reported from the 

 124 
 

Kano et al. (2009, 594539) study, were suitable for deriving an oral CSF, the female mouse data 

represented the most sensitive indicator of carcinogenicity in the rodent model. The lowest 

exposure level (66 mg/kg-day [animal dose] or 10 mg/kg-day [HED]) observed a considerable 

and significant increase in combined liver adenomas and carcinomas. Additional testing of doses 

within the range of control and the lowest dose (66 mg/kg-day [animal dose] or 10 mg/kg-day 

[HED]) could refine and reduce uncertainty for the oral CSF. 

6.2.3.7. Relevance to Humans 

The oral CSF was derived using the tumor incidence in the liver of female mice. A 

thorough review of the available toxicological data available for 1,4-dioxane provides no 

scientific justification to propose that the liver adenomas and carcinomas observed in animal 

models following exposure to 1,4-dioxane are not plausible in humans. Liver adenomas and 

carcinomas were considered plausible outcomes in humans due to exposure to 1,4-dioxane. 

6.2.3.8. Human Population Variability 

The extent of inter-individual variability in 1,4-dioxane metabolism has not been 

characterized. A separate issue is that the human variability in response to 1,4-dioxane is also 

unknown. Data exploring whether there is differential sensitivity to 1,4-dioxane carcinogenicity 

across life stages is unavailable. This lack of understanding about potential differences in 

metabolism and susceptibility across exposed human populations thus represents a source of 

uncertainty. Also, the lack of information linking a MOA for 1,4-dioxane to the observed 

carcinogenicity is a source of uncertainty. 

6.2.4. Cancer/Inhalation 

Inhalation studies for 1,4-dioxane were not adequate for the determination of an 

inhalation unit risk value. No treatment-related tumors were noted in a chronic inhalation study 

in rats; however only a single exposure concentration was used (111 ppm 1,4-dioxane vapor for 

7 hours/day, 5 days/week for 2 years) (Torkelson et al., 1974, 094807). Route extrapolation 

from oral bioassay data was not performed because available kinetic models were not considered 

suitable for this purpose. 

Note that during the development of this assessment, new data regarding the toxicity of 

1,4-dioxane through the inhalation route of exposure became available and have not been 

included in the current assessment. The IRIS Program will evaluate the more recently published 

1,4-dioxane inhalation data in a separate assessment. 

 125 
 

7. REFERENCES 

ACS (1990). Handbook of Chemical Property Estimation Methods: Environmental Behavior of Organic Compounds. 

Washington, DC: American Chemical Society. 004237

Agrawal AK; Shapiro BH (2000). Differential expression of gender-dependent hepatic isoforms of cytochrome P-450 by 

pulse signals in the circulating masculine episodic growth hormone profile of the rat. J Pharmacol Exp Ther, 292: 

228-237. 196132

Andersen ME; Clewell HJ III; Gargas ML; Smith FA; Reitz RH (1987). Physiologically based pharmacokinetics and the 

risk assessment process for methylene chloride. Toxicol Appl Pharmacol, 87: 185-205. doi:10.1016/0041-

008X(87)90281-X 001938

Argus MF; Arcos JC; Hoch-Ligeti C (1965). Studies on the carcinogenic activity of protein-denaturing agents: 

Hepatocarcinogenicity of dioxane. J Natl Cancer Inst, 35: 949-958. 017009

Argus MF; Sohal RS; Bryant GM; Hoch-Ligeti C; Arcos JC (1973). Dose-response and ultrastructural alterations in 

dioxane carcinogenesis. Influence of methylcholanthrene on acute toxicity. Eur J Cancer, 9: 237-243. 

doi:10.1016/0014-2964(73)90088-1 062912

Ashby J (1994). The genotoxicity of 1,4-dioxane. Mutat Res, 322: 141-142. doi:10.1016/0165-1218(94)00022-0 195021

Atkinson R (1989). Kinetics and mechanisms of the gas-phase reactions of the hydroxyl radical with organic compounds. 

Washington, DC: American Chemical Society. 042876

ATSDR (2007). Toxicological profile for 1,4 dioxane. Draft for public comment. U.S. Department of Health and Human 

Services, Public Health Service, Agency for Toxic Substances and Disease. Atlanta, 

GA.http://www.atsdr.cdc.gov/toxprofiles/tp187.pdf. 196127

Bannasch P (2003). Comments on R. Karbe and R.L. Kerlin (2002) Cystic degeneration/spongiosis hepatis (Toxicol Pathol 

30 (2), 216-227). Toxicol Pathol, 31: 566-570. doi:10.1080/01926230390224700 196140

Barber H (1934). Haemorrhagic nephritis and necrosis of the liver from dioxan poisoning. Guy's Hosp Rep, 84: 267-280. 

062913

Braun WH; Young JD (1977). Identification of beta-hydroxyethoxyacetic acid as the major urinary metabolite of 1,4-

dioxane in the rat. Toxicol Appl Pharmacol, 39: 33-38. doi:10.1016/0041-008X(77)90174-0 194370

Bronaugh RL (1982). Percutaneous absorption of cosmetic ingredients. In P Frost; SN Horwitz (Ed.),Principles of 

cosmetics for the dermatologist (pp. 277-284). St. Louis, MO: C.V. Mosby. 196146

Brown RP; Delp MD; Lindstedt SL; Rhomberg LR; Beliles RP (1997). Physiological parameter values for physiologically 

based pharmacokinetic models. Toxicol Ind Health, 13: 407-484. doi:10.1177/074823379701300401 020304

Buffler PA; Wood SM; Suarez L; Kilian DJ (1978). Mortality follow-up of workers exposed to 1,4-dioxane. J Occup 

Environ Med, 20: 255-259. 062914

Bull RJ; Robinson M; Laurie RD (1986). Association of carcinoma yield with early papilloma development in SENCAR 

mice. Environ Health Perspect, 68: 11-17. 194336

Burmistrov SO; Arutyunyan AV; Stepanov MG; Oparina TI; Prokopenko VM (2001). Effect of chronic inhalation of 

toluene and dioxane on activity of free radical processes in rat ovaries and brain. Bull Exp Biol Med, 132: 832-836. 

195972

Carpenter SP; Lasker JM; Raucy JL (1996). Expression, induction, and catalytic activity of the ethanol-inducible 

cytochrome P450 (CYP2E1) in human fetal liver and hepatocytes. Mol Pharmacol, 49: 260-268. 080660

Clark B; Furlong JW; Ladner A; Slovak AJM (1984). Dermal toxicity of dimethyl acetylene dicarboxylate, N-methyl 

pyrrolidone, triethylene glycol dimethyl ether, dioxane and tetralin in the rat. IRCS Med Sci, 12: 296-297. 194970

CRC (2000). Handbook of Chemistry and Physics. Boca Raton, FL: CRC Press LLC. 196090

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 126 
 

David H (1964). Electron-microscopic findings in dioxan-dependent nephrosis in rat kidneys. Beitr Pathol Anat, 130: 187-

212. 195954

Derosa CT; Wilbur S; Holler J; Richter P; Stevens YW (1996). Health evaluation of 1,4-dioxane. Toxicol Ind Health, 12: 1-

43. doi:10.1177/074823379601200101 194371

de Navasquez S (1935). Experimental tubular necrosis of the kidneys accompanied by liver changes due to dioxane 

poisoning. J Hyg, 35: 540-548. 196174

Drew RT; Patel JM; Lin FN (1978). Changes in serum enzymes in rats after inhalation of organic solvents singly and in 

combination. Toxicol Appl Pharmacol, 45: 809-819. doi:10.1016/0041-008X(78)90172-2 067913

Ernstgard L; Iregren A; Sjogren B; Johanson G (2006). Acute effects of exposure to vapours of dioxane in humans. Hum 

Exp Toxicol, 25: 723-729. doi:10.1177/0960327106073805 195034

Fairley A; Linton EC; Ford-Moore AH (1934). The toxicity to animals of 1:4 dioxan. J Hyg, 34: 486-501. 

doi:10.1017/S0022172400043266 062919

Fisher J; Mahle D; Bankston L; Greene R; Gearhart J (1997). Lactational transfer of volatile chemicals in breast milk. Am 

Ind Hyg Assoc J, 58: 425-431. doi:10.1080/15428119791012667 194390

Franke C; Studinger G; Berger G; Böhling S; Bruckmann U; Cohors-Fresenborg D; Jöhncke U (1994). The assessment of 

bioaccumulation. Chemosphere, 29: 1501-1514. doi:10.1016/0045-6535(94)90281-X 194356

Frantik E; Hornychova M; Horvath M (1994). Relative acute neurotoxicity of solvents: Isoeffective air concentrations of 

48 compounds evaluated in rats and mice. Environ Res, 66: 173-185. doi:10.1006/enrs.1994.1053 067510

Galloway SM; Armstrong MJ; Reuben C; Colman S; Brown B; Cannon C; Bloom AD; Nakamura F; Ahmed M; Duk S; 

Rimpo J; Margolin BH; Resnick MA; Anderson B; Zeiger E (1987). Chromosome aberrations and sister chromatid 

exchanges in Chinese hamster ovary cells: Evaluations of 108 chemicals. Environ Mol Mutagen, 10: 1-175. 

doi:10.1002/em.2850100502 007768

Giavini E; Vismara C; Broccia ML (1985). Teratogenesis study of dioxane in rats. Toxicol Lett, 26: 85-88. 

doi:10.1016/0378-4274(85)90189-4 062924

Goldberg ME; Johnson HE; Pozzani UC; Smyth HF Jr (1964). Effect of repeated inhalation of vapors of industrial solvents 

on animal behavior: I. Evaluation of nine solvent vapors on pole-climb performance in rats. Am Ind Hyg Assoc J, 

25: 369-375. 058035

Goldsworthy TL; Monticello TM; Morgan KT; Bermudez E; Wilson DM; Jäckh R; Butterworth BE (1991). Examination of 

potential mechanisms of carcinogenicity of 1,4-dioxane in rat nasal epithelial cells and hepatocytes. Arch Toxicol, 

65: 1-9. doi:10.1007/BF01973495 062925

Green T; Lee R; Moore RB; Ashby J; Willis GA; Lund VJ; Clapp MJL (2000). Acetochlor-induced rat nasal tumors: 

Further studies on the mode of action and relevance to humans. Regul Toxicol Pharmacol, 32: 127-133 . 

doi:10.1006/rtph.2000.1413 196210

Grosjean D (1990). Atmospheric chemistry of toxic contaminants. 2. Saturated aliphatics: Acetaldehyde, dioxane, ethylene 

glycol ethers, propylene oxide. J Air Waste Manag Assoc, 40: 1522-1531. 196213

Hansch C; Leo A; Hoekman D (1995). Exploring QSAR: Hydrophobic, Electronic, and Steric Constants. Washington, DC: 

American Chemical Society. 051424

Haseman JK; Hailey JR (1997). An update of the National Toxicology Program database on nasal carcinogens. Mutat Res, 

380: 3-11. doi:10.1016/S0027-5107(97)00121-8 195983

Haseman JK; Huff J; Boorman GA (1984). Use of historical control data in carcinogenicity studies in rodents. Toxicol 

Pathol, 12: 126-135. doi:10.1177/019262338401200203 020667

Hawley GG; Lewis RJ Sr (2001). Hawley's Condensed Chemical Dictionary . New York, NY: John Wiley & Sons, Inc. 

196089

Haworth S; Lawlor T; Mortelmans K; Speck W; Zeiger E (1983). Salmonella mutagenicity test results for 250 chemicals. 

Environ Mutagen, 5: 3-142. doi:10.1002/em.2860050703 028947

Hayashi S; Watanabe J; Kawajiri K (1991). Genetic polymorphisms in the 5'-flanking region change transcriptional 

regulation of the human cytochrome P450IIE1 gene. J Biochem, 110: 559-565. 196219

Hellmér L; Bolcsfoldi G (1992). An evaluation of the E. coli K-12 uvrB/recA DNA repair host-mediated assay. I. In vitro 

sensitivity of the bacteria to 61 compounds. Mutat Res, 272: 145-160. doi:10.1016/0165-1161(92)90043-L 194717

 127 
 

Hoch-Ligeti C; Argus MF (1970). Effect of carcinogens on the lung of guinea pigs. In P Nettlesheim; MG Hanna Jr; JW 

Deatherage Jr (Ed.),Morphology of Experimental Respiratory Carcinogenesis: Proceedings of a Biology Division, 

Oak Ridge National Laboratory, Conference held in Gatlinburg, Tennessee, May 13-16, 1970 (pp. 267-279). Oak 

Ridge, TN: United States Atomic Energy Comission, Division of Technical Information. 029386

Hoch-Ligeti C; Argus MF; Arcos JC (1970). Induction of carcinomas in the nasal cavity of rats by dioxane. Br J Cancer, 

24: 164-167. 062926

HSDB (2007). 1,4-Dioxane. National Library of Medicine, National Toxicology Program, Hazardous Substances Data 

Bank. Bethesda, Maryland. 196232

Huang C-Y; Huang K-L; Cheng T-J; Wang J-D; Hsieh L-L (1997). The GST T1 and CYP2E1 genotypes are possible 

factors causing vinyl chloride induced abnormal liver function. Arch Toxicol, 71: 482-488. 

doi:10.1007/s002040050416 005276

IARC (1999). 1,4-Dioxane. In IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, Volume 71: Reevaluation of Some Organic Chemicals, Hydrazine and Hydrogen Peroxide. Part Two - Other Compounds 

Reviewed in Plenary Sessions (pp. 589-602). Lyon, France: World Health Organization, International Agency for 

Research on Cancer. 196238

ICRP (1975). Report of the task group on reference man: ICRP publication 23. New York, NY: International Commission 

of Radiological Protection, Pergamon Press. 196239

JBRC (1998). Two-week studies of 1,4-dioxane in F344 rats and BDF1 mice (drinking water studies). Japan Bioassay 

Research Center. Kanagawa, Japan. 196242

JBRC (1998). Two-year studies of 1,4-dioxane in F344 rats and BDF1 mice (drinking water). Japan Bioassay Research 

Center. Kanagawa, Japan. 196240

Johnstone RT (1959). Death due to dioxane? AMA Arch Ind Health, 20: 445-447. 062927

Kanada M; Miyagawa M; Sato M; Hasegawa H; Honma T (1994). Neurochemical profile of effects of 28 neurotoxic 

chemicals on the central nervous system in rats (1) Effects of oral administration on brain contents of biogenic 

amines and metabolites. Ind Health, 32: 145-164. doi:10.2486/indhealth.32.145 078052

Kano H; Umeda Y; Kasai T; Sasaki T; Matsumoto M; Yamazaki K; Nagano K; Arito H; Fukushima S (2009). 

Carcinogenicity studies of 1,4-dioxane administered in drinking-water to rats and mice for 2 years. Food Chem 

Toxicol, 47: 2776-2784. doi:10.1016/j.fct.2009.08.012 594539

Kano H; Umeda Y; Saito M; Senoh H; Ohbayashi H; Aiso S; Yamazaki K; Nagano K; Fukushima S (2008). Thirteen-week 

oral toxicity of 1,4-dioxane in rats and mice. J Toxicol Sci, 33: 141-153. doi:10.2131/jts.33.141 196245

Karbe E; Kerlin RL (2002). Cystic degeneration/spongiosis hepatis in rats. Toxicol Pathol, 30: 216-227. 

doi:10.1080/019262302753559551 196246

Kasai T; Kano H; Umeda Y; Sasaki T; Ikawa N; Nishizawa T; Nagano K; Arito H; Nagashima H; Fukushima S (2009). 

Two-year inhalation study of carcinogenicity and chronic toxicity of 1,4-dioxane in male rats. Inhal Toxicol, 21: 

889-897. doi:10.1080/08958370802629610 193803

Kasai T; Saito M; Senoh H; Umeda Y; Aiso S; Ohbayashi H; Nishizawa T; Nagano K; Fukushima S (2008). Thirteen-week 

inhalation toxicity of 1,4-dioxane in rats. Inhal Toxicol, 20: 961-971. doi:10.1080/08958370802105397 195044

Kasper P; Uno Y; Mauthe R; Asano N; Douglas G; Matthews E; Moore M; Mueller L; Nakajima M; Singer T; Speit G 

(2007). Follow-up testing of rodent carcinogens not positive in the standard genotoxicity testing battery: IWGT 

workgroup report. Mutat Res, 627: 106-116. doi:10.1016/j.mrgentox.2006.10.007 195045

Katagiri T; Nagano K; Aiso S; Senoh H; Sakura Y; Takeuchi T; Okudaira M (1998). A pathological study on spontaneous 

hepatic neoplasms in BDF1 mice. J Toxicol Pathol, 11: 21-25. doi:10.1293/tox.11.21 193804

Kesten HD; Mulinos MG; Pomerantz L (1939). Pathologic effects of certain glycols and related compounds. Arch Pathol, 

27: 447-465. 194972

Khudoley VV; Mizgireuv I; Pliss GB (1987). The study of mutagenic activity of carcinogens and other chemical agents 

with Salmonella typhimurium assays: Testing of 126 compounds. Arch Geschwulstforsch, 57: 453-462. 194949

King ME; Shefner AM; Bates RR (1973). Carcinogenesis bioassay of chlorinated dibenzodioxins and related chemicals. 

Environ Health Perspect, 5: 163-170. 029390

Kitchin KT; Brown JL (1990). Is 1,4-dioxane a genotoxic carcinogen? Cancer Lett, 53: 67-71. doi:10.1016/0304-

3835(90)90012-M 062928

 128 
 

Knoefel PK (1935). Narcotic potency of some cyclic acetals. J Pharmacol Exp Ther, 53: 440-444. 195914

Kociba RJ; McCollister SB; Park C; Torkelson TR; Gehring PJ (1974). 1,4-dioxane. I. Results of a 2-year ingestion study 

in rats. Toxicol Appl Pharmacol, 30: 275-286. doi:10.1016/0041-008X(74)90099-4 062929

Kociba RJ; Torkelson TR; Young JD; Gehring PJ (1975). 1,4-Dioxane: Correlation of the results of chronic ingestion and 

inhalation studies with its dose-dependent fate in rats. In Proceedings of the 6th Annual Conference on 

Environmental Toxicology (pp. 345-354). Wright-Patterson Air Force Base, OH: Wright-Patterson Air Force Base, 

Air Force Systems Command, Aerospace Medical Division, Aerospace Medical Research Laboratory. 062930

Kurl RN; Poellinger L; Lund J; Gustafsson J-A (1981). Effects of dioxane on RNA synthesis in the rat liver. Arch Toxicol, 

49: 29-33. doi:10.1007/BF00352068 195054

Kwan KK; Dutka BJ; Rao SS; Liu D (1990). Mutatox test: A new test for monitoring environmental genotoxic agents. 

Environ Pollut, 65: 323-332. doi:10.1016/0269-7491(90)90124-U 196078

Laug EP; Calvery HO; Morris HJ; Woodard G (1939). The toxicology of some glycols and derivatives. J Ind Hyg Toxicol, 

21: 173-201. 195055

Lesage S; Jackson RE; Priddle MW; Riemann PG (1990). Occurrence and fate of organic solvent residues in anoxic 

groundwater at the Gloucester landfill, Canada. Environ Sci Technol, 24: 559-566. doi:10.1021/es00074a016 

195913

Leung H-W; Paustenbach DJ (1990). Cancer risk assessment for dioxane based upon a physiologically-based 

pharmacokinetic approach. Toxicol Lett, 51: 147-162. 062932

Lewandowski TA; Rhomberg LR (2005). A proposed methodology for selecting a trichloroethylene inhalation unit risk 

value for use in risk assessment. Regul Toxicol Pharmacol, 41: 39-54. doi:10.1016/j.yrtph.2004.09.003 626613

Lewis RJ Sr (2000). Sax's Dangerous Properties of Industrial Materials. New York, NY: John Wiley & Sons, Inc. 625540

Lundberg I; Ekdahl M; Kronevi T; Lidums V; Lundberg S (1986). Relative hepatotoxicity of some industrial solvents after 

intraperitoneal injection or inhalation exposure in rats. Environ Res, 40: 411-420. doi:10.1016/S0013-

9351(86)80116-5 062934

Lundberg I; Hogberg J; Kronevi T; Holmberg B (1987). Three industrial solvents investigated for tumor promoting activity 

in the rat liver. Cancer Lett, 36: 29-33. doi:10.1016/0304-3835(87)90099-1 062933

Marzulli FN; Anjo DM; Maibach HI (1981). In vivo skin penetration studies of 2,4-toluenediamine, 2,4-diaminoanisole, 2-

nitro-p-phenylenediamine, p-dioxane and N-nitrosodiethanolamine in cosmetics. Food Cosmet Toxicol, 19: 743-

747. doi:10.1016/0015-6264(81)90530-7 194326

McFee AF; Abbott MG; Gulati DK; Shelby MD (1994). Results of mouse bone marrow micronucleus studies on 1,4-

dioxane. Mutat Res, 322: 145-148. 195060

McGregor DB; Brown AG; Howgate S; McBride D; Riach C; Caspary WJ (1991). Responses of the L5178Y mouse 

lymphoma cell forward mutation assay. V: 27 coded chemicals. Environ Mol Mutagen, 17: 196-219. 

doi:10.1002/em.2850170309 194381

Merck (2001). The Merck Index: An Encyclopedia of Chemicals, Drugs, and Biologicals. Whitehouse Station, NJ: Merck 

& Co., Inc. 595055

Meylan WM; Howard PH; Boethling RS; Aronson D; Printup H; Gouchie S (1999). Improved method for estimating 

bioconcentration/bioaccumulation factor from octanol/water partition coefficient. Environ Toxicol Chem, 18: 664-

672. doi:10.1002/etc.5620180412 194377

Mikheev MI; Gorlinskaya Ye P; Solovyova TV (1990). The body distribution and biological action of xenobiotics. J Hyg 

Epidemiol Microbiol Immunol, 34: 329-36. 195061

Mirkova ET (1994). Activity of the rodent carcinogen 1,4-dioxane in the mouse bone marrow micronucleus assay. Mutat 

Res, 322: 142-144. 195062

Miyagawa M; Shirotori T; Tsuchitani M; Yoshikawa K (1999). Repeat-assessment of 1,4-dioxane in a rat-hepatocyte 

replicative DNA synthesis (RDS) test: Evidence for stimulus of hepatocyte proliferation. Exp Toxicol Pathol, 51: 

555-558. 195063

Morita T (1994). No clastogenicity of 1,4 dioxane as examined in the mouse peripheral blood micronucleus test. 

Mammalian Mutagenicity Study Group Communications, 2: 7-8. 196085

 129 
 

Morita T; Hayashi M (1998). 1,4-Dioxane is not mutagenic in five in vitro assays and mouse peripheral blood micronucleus 

assay, but is in mouse liver micronucleus assay. Environ Mol Mutagen, 32: 269-280. doi:10.1002/(SICI)1098-

2280(1998)32:3<269::AID-EM10>3.0.CO;2-8 195065

Mungikar AM; Pawar SS (1978). Induction of the hepatic microsomal mixed function oxidase system in mice by p-dioxane 

. Bull Environ Contam Toxicol, 20: 797-804. doi:10.1007/BF01683603 194344

Munoz ER; Barnett BM (2002). The rodent carcinogens 1,4-dioxane and thiourea induce meiotic non-disjunction in 

Drosophila melanogaster females. Mutat Res, 517: 231-238. doi:10.1016/S1383-5718(02)00083-9 195066

Nannelli A; De Rubertis A; Longo V; Gervasi PG (2005). Effects of dioxane on cytochrome P450 enzymes in liver, kidney, 

lung and nasal mucosa of rat. Arch Toxicol, 79: 74-82. doi:10.1007/s00204-004-0590-z 195067

NCI (1978). Bioassay of 1,4-dioxane for possible carcinogenicity. National Cancer Institute. Bethesda, MD. 78-1330 

NCICGTR-80. http://ntp.niehs.nih.gov/ntp/htdocs/LT_rpts/tr080.pdf. 062935

Nelson N (1951). Solvent toxicity with particular reference to certain octyl alcohols and dioxanes. Med Bull, 11: 226-238. 

196087

Nestmann ER; Otson R; Kowbel DJ; Bothwell PD; Harrington TR (1984). Mutagenicity in a modified Salmonella assay of 

fabric-protecting products containing 1,1,1-trichloroethane. Environ Mol Mutagen, 6: 71-80. 

doi:10.1002/em.2860060109 194339

NRC (1983). Risk assessment in the federal government: Managing the process. National Research Council, National 

Academy Press. Washington, DC. PB83-191262; ISBN0309033497. 

http://www.nap.edu/openbook.php?record_id=366&page=R1. 194806

NRC (2009). Science and decisions: Advancing risk assessment. National Research Council. Washington, 

DC.http://www.nap.edu/catalog.php?record_id=12209. 628200

Park JH; Hussam A; Couasnon P; Fritz D; Carr PW (1987). Experimental reexamination of selected partition coefficients 

from Rohrschneider's data set. Anal Chem, 59: 1970-1976. doi:10.1021/ac00142a016 194328

Platz J; Sehested J; Mogelberg T; Nielsen OJ; Wallington TJ (1997). Atmospheric chemistry of 1,4-dioxane. Faraday Trans 

1, 93: 2855-2863. doi:10.1039/a700598i 196086

Pozzani UC; Weil CS; Carpenter CP (1959). The toxicological basis of threshold limit values. 5: The experimental 

inhalation of vapor mixtures by rats, with notes upon the relationship between single dose inhalation and single 

dose oral data. Am Ind Hyg Assoc J, 20: 364-369. doi:10.1080/00028895909343733 063019

Ramsey JC; Andersen ME (1984). A physiologically based description of the inhalation pharmacokinetics of styrene in rats 

and humans. Toxicol Appl Pharmacol, 73: 159-175. doi:10.1016/0041-008X(84)90064-4 063020

Reitz RH; McCroskey PS; Park CN; Andersen ME; Gargas ML (1990). Development of a physiologically based 

pharmacokinetic model for risk assessment with 1,4-dioxane. Toxicol Appl Pharmacol, 105: 37-54. 

doi:10.1016/0041-008X(90)90357-Z 094806

Rosenkranz HS; Klopman G (1992). 1,4-dioxane: Prediction of in vivo clastogenicity. Mutat Res, 280: 245-251. 

doi:10.1016/0165-1218(92)90054-4 004321

Roy SK; Thilagar AK; Eastmond DA (2005). Chromosome breakage is primarily responsible for the micronuclei induced 

by 1,4-dioxane in the bone marrow and liver of young CD-1 mice. Mutat Res, 586: 28-37. 

doi:10.1016/j.mrgentox.2005.05.007 196094

Schrenk HH; Yant WP (1936). Toxicity of dioxan. J Ind Hyg Toxicol, 18: 448-460. 195076

Sheu CW; Moreland FM; Lee JK; Dunkel VC (1988). In vitro BALB/3T3 cell transformation assay of nonoxynol-9 and 

1,4-dioxane. Environ Mol Mutagen, 11: 41-48. doi:10.1002/em.2850110106 195078

Silverman L; Schulte HF; First MW (1946). Further studies on sensory response to certain industrial solvent vapors. J Ind 

Hyg Toxicol, 28: 262-266. 063013

Sina JF; Bean CL; Dysart GR; Taylor VI; Bradley MO (1983). Evaluation of the alkaline elution/rat hepatocyte assay as a 

predictor of carcinogenic/mutagenic potential. Mutat Res, 113: 357-391. doi:10.1016/0165-1161(83)90228-5 

007323

Smyth HF Jr; Seaton J; Fischer L (1941). The single dose toxicity of some glycols and derivatives. J Ind Hyg Toxicol, 23: 

259-268. 060695

 130 
 

Stickney JA; Sager SL; Clarkson JR; Smith LA; Locey BJ; Bock MJ; Hartung R; Olp SF (2003). An updated evaluation of 

the carcinogenic potential of 1,4-dioxane. Regul Toxicol Pharmacol, 38: 183-195. doi:10.1016/S0273-

2300(03)00090-4 195080

Stoner GD; Conran PB; Greisiger EA; Stober J; Morgan M; Pereira MA (1986). Comparison of two routes of chemical 

administration on the lung adenoma response in strain A/J mice. Toxicol Appl Pharmacol, 82: 19-31. 

doi:10.1016/0041-008X(86)90433-3 064678

Stott WT; Quast JF; Watanabe PG (1981). Differentiation of the mechanisms of oncogenicity of 1,4-dioxane and 1,3-

hexachlorobutadiene in the rat. Toxicol Appl Pharmacol, 60: 287-300. doi:10.1016/0041-008X(91)90232-4 063021

Stroebel P; Mayer F; Zerban H; Bannasch P (1995). Spongiotic pericytoma: A benign neoplasm deriving from the 

perisinusoidal (Ito) cells in rat liver. Am J Pathol, 146: 903-913. 196101

Surprenant KS (2002). Dioxane. In Ullmann's Encyclopedia of Industrial Chemistry (p. 543). Weinheim, Germany: WileyVCH Verlag. 196117

Sweeney LM; Thrall KD; Poet TS; Corley RA; Weber TJ; Locey BJ; Clarkson J; Sager S; Gargas ML (2008). 

Physiologically based pharmacokinetic modeling of 1,4-dioxane in rats, mice, and humans. Toxicol Sci, 101: 32-50. 

doi:10.1093/toxsci/kfm251 195085

Thiess AM; Tress E; Fleig I (1976). Arbeitsmedizinische Untersuchungsergebnisse von Dioxan-exponierten Mitarbeitern 

[Industrial-medical investigation results in the case of workers exposed to dioxane]. Arbeitsmedizin, Sozialmedizin, 

Umweltmedizin, 11: 35-46. 062943

Thurman GB; Simms BG; Goldstein AL; Kilian DJ (1978). The effects of organic compounds used in the manufacture of 

plastics on the responsivity of murine and human lymphocytes. Toxicol Appl Pharmacol, 44: 617-641. 

doi:10.1016/0041-008X(78)90269-7 018767

Tinwell H; Ashby J (1994). Activity of 1,4-dioxane in mouse bone marrow micronucleus assays. Mutat Res, 322: 148-150. 

195086

Torkelson TR; Leong BKJ; Kociba RJ; Richter WA; Gehring PJ (1974). 1,4-Dioxane. II. Results of a 2-year inhalation 

study in rats. Toxicol Appl Pharmacol, 30: 287-298. doi:10.1016/0041-008X(74)90100-8 094807

U.S. EPA (1986). Guidelines for carcinogen risk assessment. National Center for Environmental Assessment; Office of 

Research and Development; U.S. Environmental Protection Agency . Washington, DC. EPA/630/R-00/004 . 

http://epa.gov/raf/publications/pdfs/CA%20GUIDELINES_1986.PDF. 199530

U.S. EPA (1986). Guidelines for mutagenicity risk assessment. U.S. Environmental Protection Agency, Risk Assessment 

Forum. Washington, DC. EPA/630/R-98/003. http://www.epa.gov/osa/mmoaframework/pdfs/MUTAGEN2.PDF. 

001466

U.S. EPA (1986). Guidelines for the health risk assessment of chemical mixtures. U.S. Environmental Protection Agency, 

Risk Assessment Forum. Washington, DC. EPA/630/R-98/002. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=22567. 001468

U.S. EPA (1988). Recommendations for and documentation of biological values for use in risk assessment. U.S. 

Environmental Protection Agency, Environmental Criteria and Assessment Office, Office of Research and 

Development, Office of Health and Environmental Assessment. Cincinnati, OH. EPA/600/6-87/008. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=34855. 064560

U.S. EPA (1990). Amendments to the Clean Air Act. Sec. 604. Phase-out of production and consumption of class I 

substances. Retrieved , from . 196139

U.S. EPA (1991). Guidelines for developmental toxicity risk assessment. U.S. Environmental Protection Agency, Risk 

Assessment Forum. Washington, DC. EPA/600/FR-91/001. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=23162. 008567

U.S. EPA (1994). Interim policy for particle size and limit concentration issues in inhalation toxicity studies. U.S. 

Environmental Protection Agency, Office of Pesticide Products, Health Effects Division. Washington, 

DC.http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=186068. 076133

U.S. EPA (1994). Methods for derivation of inhalation reference concentrations and application of inhalation dosimetry. 

U.S. Environmental Protection Agency, Office of Research and Development, Office of Health and Environmental 

Assessment. Washington, DC. EPA/600/8-90/066F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=71993. 

006488

 131 
 

U.S. EPA (1995). The use of the benchmark dose approach in health risk assessment. U.S. Environmental Protection 

Agency, Risk Assessment Forum. Washington, DC. EPA/630/R-94/007. 

http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=42601. 005992

U.S. EPA (1996). Guidelines for reproductive toxicity risk assessment. U.S. Environmental Protection Agency, Risk 

Assessment Forum. Washington, DC. EPA/630/R-96/009. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=2838. 030019

U.S. EPA (1998). Guidelines for neurotoxicity risk assessment. U.S. Environmental Protection Agency, Office of Research 

and Development, National Center for Environmental Assessment. Washington, DC. EPA/630/R-95/001F. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=12479. 030021

U.S. EPA (2000). Benchmark dose technical guidance document [external review draft]. U.S. Environmental Protection 

Agency, Risk Assessment Forum. Washington, DC. EPA/630/R-00/001. 

http://www.epa.gov/raf/publications/benchmark-dose-doc-draft.htm . 052150

U.S. EPA (2000). Science policy council handbook: Risk characterization. U.S. Environmental Protection Agency, Office 

of Research and Development, Office of Science Policy. Washington, D.C.. EPA 100-B-00-002. 

www.epa.gov/spc/pdfs/rchandbk.pdf. 052149

U.S. EPA (2000). Supplemental guidance for conducting for health risk assessment of chemical mixtures. U.S. EPA. 

Washington, DC. 196144

U.S. EPA (2000). Supplementary guidance for conducting health risk assessment of chemical mixtures. Risk Assessment 

Forum, U.S. Environmental Protection Agency. Washington, DC. EPA/630/R-00/002. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=20533. 004421

U.S. EPA (2002). A review of the reference dose and reference concentration processes. U.S. Environmental Protection 

Agency, Risk Assessment Forum. Washington, DC. EPA/630/P-02/0002F. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=55365. 088824

U.S. EPA (2002). Toxic Substances Control Act (TSCA) Inventory Update Database. Retrieved February 22, 2010, from 

http://www.epa.gov/iur/ . 594597

U.S. EPA (2005). Guidelines for carcinogen risk assessment, final report. Risk Assessment Forum; U.S. Environmental 

Protection Agency. Washington, DC. EPA/630/P-03/001F. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283. 086237

U.S. EPA (2005). Supplemental guidance for assessing susceptibility from early-life exposure to carcinogens. U.S. 

Environmental Protection Agency, Risk Assessment Forum. Washington, DC. EPA/630/R-03/003F. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283. 088823

U.S. EPA (2006). A framework for assessing health risk of environmental exposures to children (final). U.S. Environmental 

Protection Agency, Office of Research and Development, National Center for Environmental Assessment . 

Washington, DC. EPA/600/R-05/093F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=158363. 194567

U.S. EPA (2006). U.S. Environmental Protection Agency peer review handbook. U.S. Environmental Protection Agency, 

Science Policy Council. Washington, DC. EPA/100/B-06/002. 

http://www.epa.gov/peerreview/pdfs/peer_review_handbook_2006.pdf. 194566

U.S. EPA (2009). Toxicological review of 1,4-dioxane (CAS No. 123-91-1) in support of summary information on the 

Intergrated Risk Information System (IRIS) [External Review Draft]. U.S. Environmental Protection Agency. 

Washington, DC. EPA/635/R-09/005. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=199330. 628630

U.S. EPA (2010). Toxicological review of 1,4-Dioxane (CAS No. 123-91-1) in support of summary information on the 

Integrated Risk Information System (IRIS). U.S. Environmental Protection Agency. Washington, DC. 625580

UNEP (2000). The Montreal Protocol on substances that deplete the ozone layer. United Nations Environment Programme, 

Ozone Secretariat. Nairobi, 

Kenya.http://www.google.com/url?sa=t&source=web&cd=1&ved=0CBIQFjAA&url=http%3A%2F%2Fwww.unep

.org%2Fozone%2Fpdfs%2Fmontreal-protocol2000.pdf&ei=-c89TPX0N9PRngf-ijdDg&usg=AFQjCNH4OHl5inPn5XFcYTvblPPRDZu-fQ&sig2=qqSaM_nuQlX1Hc409kBvgw. 196125

Uno Y; Takasawa H; Miyagawa M; Inoue Y; Murata T; Yoshikawa K (1994). An in vivo-in vitro replicative DNA synthesis 

(RDS) test using rat hepatocytes as an early prediction assay for nongenotoxic hepatocarcinogens screening of 22 

known positives and 25 noncarcinogens. Mutat Res, 320: 189-205. doi:10.1016/0165-1218(94)90046-9 194385

 132 
 

van Delft JH; van Agen E; van Breda SG; Herwijnen MH; Staal YC; Kleinjans JC (2004). Discrimination of genotoxic 

from non-genotoxic carcinogens by gene expression profiling. Carcinogenesis, 25: 1265-1276. 

doi:10.1093/carcin/bgh108 195087

Vieira I; Sonnier M; Cresteil T (1996). Developmental expression of CYP2E1 in the human liver: hypermethylation control 

of gene expression during the neonatal period. Eur J Biochem, 238: 476-483. doi:10.1111/j.1432-

1033.1996.0476z.x 011956

Watanabe J; Hayashi S; Kawajiri K (1994). Different regulation and expression of the human CYP2E1 gene due to the Rsal 

polymorphism in the 5'-flanking region. J Biochem, 116: 321-326. 196099

Waxman DJ; Pampori NA; Ram PA; Agrawal AK; Shapiro BH (1991). Interpulse interval in circulating growth hormone 

patterns regulates sexually dimorphic expression of hepatic cytochrome P450. PNAS, 88: 6868-6872. 196102

Wirth W; Klimmer O (1936). [On the toxicology of organic solvents. 1,4 dioxane (diethylene dioxide)] . Archiv fuer 

Gewerbepathologie und Gewerbehygiene, 17: 192-206. 196105

Wolfe NL; Jeffers PM (2000). Hydrolysis. In RS Boethling; D Mackay (Ed.),Handbook of Property Estimation Methods 

for Chemicals: Environmental and Health Sciences (pp. 311-333). Boca Raton, FL: Lewis Publishers. 196109

Wolford ST; Schroer RA; Gohs FX; Gallo PP; Brodeck M; Falk HB; Ruhren R (1986). Reference range data base for 

serum chemistry and hematology values in laboratory animals. J Toxicol Environ Health A Curr Iss, 18: 161-188. 

doi:10.1080/15287398609530859 196112

Woo Y-T; Arcos JC; Argus MF; Griffin GW; Nishiyama K (1977). Structural identification of p-dioxane-2-one as the major 

urinary metabolite of p-dioxane. Naunyn Schmiedebergs Arch Pharmacol, 299: 283-287. doi:10.1007/BF00500322 

194355

Woo Y-T; Argus MF; Arcos JC (1977). Metabolism in vivo of dioxane: Effect of inducers and inhibitors of hepatic mixedfunction oxidases. Biochem Pharmacol, 26: 1539-1542. doi:10.1016/0006-2952(77)90431-2 062951

Woo Y-T; Argus MF; Arcos JC (1977). Tissue and subcellular distribution of 3H-dioxane in the rat and apparent lack of 

microsome-catalyzed covalent binding in the target tissue. Life Sci, 21: 1447-1456. doi:10.1016/0024-

3205(77)90199-0 062950

Woo Y-T; Argus MF; Arcos JC (1978). Effect of mixed-function oxidase modifiers on metabolism and toxicity of the 

oncogen dioxane. Can Res, 38: 1621-1625. 194345

Yamamoto S; Ohsawa M; Nishizawa T; Saito A; Kasai T; Noguchi T; Nagano K; Matsushima T (2000). Long-term 

toxicology study of 1,4-Dioxane in the F344 rats by multiple-route exposure (drinking water and inhalation). J 

Toxicol Sci, 25: 347. 625635

Yamamoto S; Urano K; Koizumi H; Wakana S; Hioki K; Mitsumori K; Kurokawa Y; Hayashi Y; Nomura T (1998). 

Validation of transgenic mice carrying the human prototype c-Ha-ras gene as a bioassay model for rapid 

carcinogenicity testing. Environ Health Perspect, 106: 57-69. 594544

Yamamoto S; Urano K; Nomura T (1998). Validation of transgenic mice harboring the human prototype c-Ha-ras gene as a 

bioassay model for rapid carcinogenicity testing. Toxicol Lett, 102-103: 473-478. doi:10.1016/S0378-

4274(98)00341-5 196114

Yamazaki K (2006). Correspondence between Kazunori Yamazaki and Julie Stickney. 626614

Yamazaki K; Ohno H; Asakura M; Narumi A; Ohbayashi H; Fujita H; Ohnishi M; Katagiri T; Senoh H; Yamanouchi K; 

Nakayama E; Yamamoto S; Noguchi T; Nagano K; Enomoto M; Sakabe H (1994). Two-year toxicological and 

carcinogenesis studies of 1,4-dioxane in F344 rats and BDF1 mice. In K Sumino; S Sato; NG Shinkokai 

(Ed.),Proceedings: Second Asia-Pacific Symposium on Environmental and Occupational Health 22-24 July, 1993: 

Kobe (pp. 193-198). Kobe, Japan: Kobe University School of Medicine, International Center for Medical Research. 

196120

Yant WP; Schrenk HH; Waite CP; Patty FA (1930). Acute response of guinea pigs to vapors of some new commercial 

organic compounds: VI. Dioxan. Public Health Rep, 45: 2023-2032. 062952

Yasuhara A; Shiraishi H; Nishikawa M; Yamamoto T; Uehiro T; Nakasugi O; Okumura T; Kenmotsu K; Fukui H; Nagase 

M; Ono Y; Kawagoshi Y; Baba K; Noma Y (1997). Determination of organic components in leachates from 

hazardous waste disposal sites in Japan by gas chromatography-mass spectrometry. J Chromatogr A, 774: 321-332. 

doi:10.1016/S0021-9673(97)00078-2 195909

Yasuhara A; Tanaka Y; Tanabe A; Kawata K; Katami T (2003). Elution of 1,4-dioxane from waste landfill sites. Bull 

Environ Contam Toxicol, 71: 641-647. doi:10.1007/s00128-003-8917-7 195095

 133 
 

Yoon JS; Mason JM; Valencia R; Woodruff RC; Zimmering S (1985). Chemical mutagenesis testing in Drosophila. IV. 

Results of 45 coded compounds tested for the National Toxicology Program. Environ Mutagen, 7: 349-367. 

doi:10.1002/em.2860070310 194373

Young JD; Braun WH; Gehring PJ (1978). The dose-dependent fate of 1,4-dioxane in rats. J Environ Pathol Toxicol, 2: 

263-282. doi:10.1080/15287397809529693 062955

Young JD; Braun WH; Gehring PJ; Horvath BS; Daniel RL (1976). 1,4-Dioxane and beta-hydroxyethoxyacetic acid 

excretion in urine of humans exposed to dioxane vapors. Toxicol Appl Pharmacol, 38: 643-646. doi:10.1016/0041-

008X(76)90195-2 062953

Young JD; Braun WH; Gehring PJ (1978). Dose----dependent fate of 1,4-dioxane in rats(b). J Toxicol Environ Health A 

Curr Iss, 4: 709-726. doi:10.1080/15287397809529693 625640

Young JD; Braun WH; Rampy LW; Chenoweth MB; Blau GE (1977). Pharmacokinetics of 1,4-dioxane in humans. J 

Toxicol Environ Health, 3: 507-520. doi:10.1080/15287397709529583 062956

Zimmermann FK; Mayer VW; Scheel I; Resnick MA (1985). Acetone, methyl ethyl ketone, ethyl acetate, acetonitrile and 

other polar aprotic solvents are strong inducers of aneuploidy in Saccharomyces cerevisiae. Mutat Res, 149: 339-

351. doi:10.1016/0027-5107(85)90150-2 194343

 134 
 

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC 

COMMENTS AND DISPOSITION 

The Toxicological Review of 1,4-Dioxane has undergone formal external peer review 

performed by scientists in accordance with EPA guidance on peer review (U.S. EPA, 2000, 

052149; U.S. EPA, 2006, 194566). The external peer reviewers were tasked with providing 

written answers to general questions on the overall assessment and on chemical-specific 

questions in areas of scientific controversy or uncertainty. A summary of significant comments 

made by the external reviewers and EPA’s responses to these comments arranged by charge 

question follow. In many cases the comments of the individual reviewers have been synthesized 

and paraphrased for development of Appendix A. The majority of the specific observations (in 

addition to EPA’s charge questions) made by the peer reviewers were incorporated into the 

document and are not discussed further in this Appendix. Public comments that were received 

are summarized and addressed following the peer-reviewers’ comments and disposition. 

A.1. EXTERNAL PEER REVIEW PANEL COMMENTS 

The reviewers made several editorial suggestions to clarify portions of the text. These 

changes were incorporated in the document as appropriate and are not discussed further. 

 In addition, the external peer reviewers commented on decisions and analyses in the 

Toxicological Review of 1,4-Dioxane under multiple charge questions, and these comments were 

organized and summarized under the most appropriate charge question. 

A.1.1. General Charge Questions 

1. Is the Toxicological Review logical, clear and concise? Has EPA accurately, clearly and 

objectively represented and synthesized the scientific evidence for noncancer and cancer 

hazards? 

Comment: All reviewers found the Toxicological Review to be logical, clear, and concise. 

One reviewer remarked that it was an accurate, open-minded and balanced analysis of the 

literature. Most reviewers found that the scientific evidence was presented objectively 

and transparently; however, one reviewer suggested two things to improve the objectivity 

and transparency (1) provide a clear description of the mode of action and how it feeds 

into the choice of the extrapolation for the cancer endpoint and (2) provide a presentation 

of the outcome if internal dose was used in the cancer and noncancer assessments. 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 A-1 
 

 One reviewer commented that conclusions could not be evaluated in a few places 

where dose information was not provided (Sections 3.2, 3.3 and 4.5.2.2). The same 

reviewer found the MOA schematics, key event temporal sequence/dose-response table, 

and the POD plots to be very helpful in following the logic employed in the assessment. 

Response: The mode of action analysis and how conclusions from that analysis fed into 

the choice of extrapolation method for the cancer assessment are discussed further under 

charge questions C2 and C5. Because of the decision not to utilize the PBPK models, 

internal doses were not calculated and thus were not included as alternatives to using the 

external dose as the POD for the cancer and noncancer assessments. 

In the sections noted by the reviewer (3.2, 3.3, and 4.5.2.2) dose information was 

added as available. In Section 3.2, Mikheev et al. (1990, 195061) did not report actual 

doses, which is noted in this section. All other dose information in this section was found 

to be present after further review by the Agency. In Section 3.3, dose information for 

Woo et al. (1977, 062951; 1978, 194345) was added to the paragraph. In Section 4.5.2.2, 

study details for Nannelli et al. (2005, 195067) were provided earlier in Section 3.3 and a 

statement referring the reader to this section was added. 

2. Please identify any additional studies that should be considered in the assessment of the 

noncancer and cancer health effects of 1,4-dioxane. 

Comment: Five reviewers stated they were unaware of any additional studies available to 

add to the oral toxicity evaluation of 1,4-dioxane. These reviewers also acknowledged 

the Kasai et al. (2008, 195044; 2009, 193803) publications that may be of use to derive 

toxicity values following inhalation of 1,4-dioxane. 

a. Kasai T; Saito H; Senoh Y; et al. (2008, 195044) Thirteen-week inhalation 

toxicity of 1,4-dioxane in rats. Inhal Toxicol 20: 961-971. 

b. Kasai T; Kano Y; Umeda T; et al. (2009, 193803) Two-year inhalation study of 

carcinogenicity and chronic toxicity of 1,4-dioxane in male rats. Inhal Toxicol in 

press. 

Other references suggested by reviewers include: 

c. California Department of Health Services (1989) Risk Specific Intake Levels for 

the Proposition 65 Carcinogen 1, 4-dioxane. Reproductive and Cancer Hazard 

Assessment Section. Office of Environmental Health Hazard Assessment 

d. National Research Council (2009, 628200) Science and Decisions: Advancing 

Risk Assessment. Committee on Improving Risk Analysis Approaches Used by 

the U.S. EPA. Washington, D.C., National Academy Press. 

e. ATSDR (2007, 196127) Toxicological Profile for 1,4-dioxane. Agency for 

Toxic Substances and Disease Registry. Atlanta, GA. 

 A-2 
 

f. Stickney JA; Sager SL; Clarkson JR; et al. (2003, 195080) An updated 

evaluation of the carcinogenic potential of 1,4-dioxane. Regul Toxicol Pharmacol 

38: 183-195. 

g. Yamamoto S; Ohsawa M; Nishizawa T; et al. (2000, 625635) Long-term 

toxicology study of 1,4-dioxane in R344 rats by multiple-route exposure (drinking 

water and inhalation). J Toxicol Sci 25: 347. 

Response: The references a-b above will be evaluated for derivation of an RfC and IUR, 

which will follow as an update to this oral assessment. References c and e noted above 

were considered during development of this assessment as to the value they added to the 

cancer and noncancer analyses. Reference g listed above is an abstract from conference 

proceedings from the 27th Annual Meeting of the Japanese Society of Toxicology; 

abstracts are not generally considered in the development of an IRIS assessment. 

Reference d reviews EPA’s current risk assessment procedures and provides no specific 

information regarding 1,4-dioxane. The Stickney et al. (2003, 195080) reference was a 

review article and no new data were presented, thus it was not referenced in this 

Toxicological Review but the data were considered during the development of this 

assessment. 

Following external peer review (as noted above) Kano et al. (2009, 594539) was 

added to the assessment, which was an update and peer-reviewed published manuscript 

of the JBRC (1998, 196240) report. 

3. Please discuss research that you think would be likely to increase confidence in the database 

for future assessments of 1,4-dioxane. 

Comment: All reviewers provided suggestions for additional research that would 

strengthen the assessment and reduce uncertainty in several areas. The following is a 

brief list of questions that were identified that could benefit from further research. What 

are the mechanisms responsible for the acute and chronic nephrotoxicity? Is the acute 

kidney injury (AKI) multifactorial? Are there both tubular and glomerular/vascular 

toxicities that result in cortical tubule degeneration and evidence for glomerulonephritis? 

What are the functional correlates of the histologic changes in terms of assessment of 

renal function? What is the exposure in utero and risk to the fetus and newborn? What are 

the concentrations in breast milk following maternal exposure to 1,4-dioxane? What is 

the risk for use of contaminated drinking water to reconstitute infant formula? What are 

the exposures during early human development? What is the pharmacokinetic and 

metabolic profile of 1,4-dioxane during development? What are the susceptible 

populations (e.g., individuals with decreased renal function or chronic renal disease, 

obese individuals, gender, age)? 

 A-3 
 

 Additional suggestions for future research include: evaluation of potential 

epigenetic mechanisms of carcinogenicity, additional information on sources of exposure 

and biological concentrations as well as human toxicokinetic data for derivation of 

parameter to refine PBPK model, studies to determine toxic moiety, focused studies to 

inform mode of action, additional inhalation studies and a multigeneration reproductive 

toxicity study. 

 One reviewer suggested additional analyses of the existing data including a 

combined analysis of the multiple datasets and outcomes for cancer and non-cancer 

endpoints, evaluation of the dose metrics relevant to the MOA to improve confidence in 

extrapolation approach and uncertainty factors, and complete a Bayesian analysis of 

human pharmacokinetic data to estimate human variability in key determinants of 

toxicity (e.g., metabolic rates and partition coefficients). 

Response: A number of research suggestions were provided for further research that may 

enhance future health assessments of 1,4-dioxane. Regarding the suggested additional 

analyses for the existing data, EPA did not identify a MOA in this assessment, thus 

combined analysis of the cancer and non-cancer endpoints as well as application of 

various dose metrics to a MOA is not applicable. Because the human PBPK model was 

not implemented in this assessment for oral exposure to 1,4-dioxane a Bayesian analysis 

was not completed. No additional changes to the Toxicological Review of 1,4-Dioxane

were made in response to these research recommendations. 

4. Please comment on the identification and characterization of sources of uncertainty in 

Sections 5 and 6 of the assessment document. Please comment on whether the key sources of 

uncertainty have been adequately discussed. Have the choices and assumptions made in the 

discussion of uncertainty been transparently and objectively described? Has the impact of the 

uncertainty on the assessment been transparently and objectively described? 

Comment: Six reviewers stated Sections 5 and 6 adequately discussed and characterized 

uncertainty, in a succinct, and transparent manner. One reviewer suggested adding 

additional discussion of uncertainty relating to the critical study used in the cancer 

assessment and another reviewer suggested adding more discussion around the 

uncertainty of the toxic moiety. 

 One reviewer made specific comments on uncertainty surrounding the Kociba et 

al. (1974, 062929) study as used for derivation of the RfD, choice of the non-cancer dose 

metric, and use of a 10%BMR as the basis for the CSF derivation. These comments and 

responses are summarized below under their appropriate charge question. 

 A-4 
 

Response: The majority of the reviewers thought the amount of uncertainty discussion 

was appropriate. Since the external review, Kano et al. (2009, 594539) was published 

and this assessment was updated accordingly (previously JBRC (1998, 196240). It is 

assumed the uncertainty referred to by the reviewer was addressed by the published Kano 

et al. (2009, 594539) paper. 

Clarification regarding the uncertainty surrounding the identification of the toxic 

moiety was added to Section 4.6.3 stating that the mechanism by which 1,4-dioxane 

induces tissue damage is not known, nor is it known whether the toxic moiety is 

1,4-dioxane or a metabolite of 1,4-dioxane. Additional text was added to Section 4.7.3 

clarifying that available data also do not clearly identify whether 1,4-dioxane or one of its 

metabolites is responsible for the observed effects. The impact of the lack of evidence to 

clearly identify a toxic moiety related to 1,4-dioxane exposure was summarized in 

Sections 5.5.1.2 and 6.2.3.2. 

A.1.2. Oral reference dose (RfD) for 1,4-dioxane 

1. A chronic RfD for 1,4-dioxane has been derived from a 2-year drinking water study (Kociba 

et al., 1974, 062929) in rats and mice. Please comment on whether the selection of this study 

as the principal study has been scientifically justified. Has the selection of this study been 

transparently and objectively described in the document? Are the criteria and rationale for 

this selection transparently and objectively described in the document? Please identify and 

provide the rationale for any other studies that should be selected as the principal study. 

Comment: Seven of the reviewers agreed that the use of the Kociba et al. (1974, 062929) 

study was the best choice for the principal study. 

One reviewer stated that Kociba et al. (1974, 062929) was not the best choice 

because it reported only NOAEL and LOAELs without providing incidence data for the 

endpoints. This reviewer also stated that the study should not have been selected based 

on sensitivity of the endpoints, but rather study design and adequacy of reporting of the 

study results. Additionally, this reviewer suggested a better principal study would be 

either the NCI (1978, 062935) or JBRC (1998, 196240) study. 

Response: The reviewer is correct that Kociba et al. (1974, 062929) did not provide 

incidence data; however, Kociba et al. (1974, 062929) identified a NOAEL (9.6 mg/kgday) and LOAEL (94 mg/kg-day) within the text of the manuscript. Kociba et al. (1974, 

062929) was a well conducted chronic bioassay (four dose levels, including controls, 

with 60 rats/sex/group) and seven of the peer reviewers found this study to be appropriate 

as the basis for the RfD. Further support for the selection of the Kociba et al. (1974, 

062929) as the principal study comes from comparison of the liver and kidney toxicity 

data reported by JBRC (1998, 196240) and NCI (1978, 062935), which was presented in 

 A-5 
 

Section 5.1. The effects reported by JBRC (1998, 196240) and NCI (1978, 062935) were 

consistent with what was observed by Kociba et al. (1974, 062929) and within a similar 

dose range. Derivation of an RfD from these datasets resulted in a similar value (Section 

5.1.). 

2. Degenerative liver and kidney effects were selected as the critical effect. Please comment on 

whether the rationale for the selection of this critical effect has been scientifically justified. 

Are the criteria and rationale for this selection transparently and objectively described in the 

document? Please provide a detailed explanation. Please comment on whether EPA’s 

rationale regarding adversity of the critical effect for the RfD has been adequately and 

transparently described and is scientifically supported by the available data. Please identify 

and provide the rationale for any other endpoints that should be considered in the selection of 

the critical effect. 

Comment: Five of the reviewers agreed with the selection of liver and kidney effects as 

the critical effect. One of these reviewers suggested analyzing all datasets following dose 

adjustment (e.g., body weight scaling or PBPK model based) to provide a better rationale 

for selection of a critical effect. 

One reviewer stated that 1,4-dioxane causing liver and kidney organ specific 

effects is logical; however, with regards to nephrotoxicity, the models and limited human 

data have not addressed the mechanisms of injury or the clinical correlates to the 

histologic data. Also, advances in the field of biomarkers have not yet been used for the 

study of 1,4-dioxane. 

One reviewer found the selection of these endpoints to be ‘without merit’ because 

of the lack of incidence data to justify the NOAEL and LOAEL values identified in the 

study. This reviewer suggested selecting the most sensitive endpoint(s) from the NCI 

(NCI, 1978, 062935) or JBRC (1998, 196240) studies for the basis of the RfD, but did 

not provide a suggestion as to what effect should be selected. 

Response: The liver and kidney effects from Kociba et al. (1974, 062929) was supported 

as the critical effect by most of the reviewers. PBPK model adjustment was not 

performed because the PBPK model was found to be inadequate for use in the 

assessment. EPA acknowledges that neither the mechanisms of injury nor the clinical 

correlates to histologic data exist for 1,4-dioxane. This type of information could improve 

future health assessments of 1,4-dioxane. 

As stated above, Kociba et al. (1974, 062929) identified a NOAEL (9.6 mg/kgday) and LOAEL (94 mg/kg-day) within the text of the manuscript and was a well 

conducted chronic bioassay (four dose levels, including controls, with 60 rats/sex/group). 

 A-6 
 

3. Kociba et al. (1974, 062929) derived a NOAEL based upon the observation of degenerative 

liver and kidney effects and these data were utilized to derive the point of departure (POD) 

for the RfD. Please provide comments with regard to whether the NOAEL approach is the 

best approach for determining the POD. Has the approach been appropriately conducted and 

objectively and transparently described? Please identify and provide rationales for any 

alternative approaches for the determination of the POD and discuss whether such 

approaches are preferred to EPA’s approach. 

Comment: Seven reviewers agreed with the NOAEL approach described in the 

document. One of these reviewers also questioned whether any attempt was made to 

“semi-qualitatively represent the histopathological observations to facilitate a quantitative 

analysis”. 

 One reviewer stated that data were not used to derive the POD, but rather a claim 

by the authors of Kociba et al. (1974, 062929) of the NOAEL and LOAEL for the 

endpoints. This reviewer preferred the use of a BMD approach for which data include 

the reported incidence rather than a study reported NOAEL or LOAEL. 

Response: The suggestion to “semi-qualitatively represent the histopathological 

observations to facilitate a quantitative analysis” was not incorporated into the document 

because it is unclear how this would be conducted since Kociba et al. (1974, 062929) did 

not provide incidence data and the reviewer did not illustrate their suggested approach. 

See responses to B1 and B2 regarding the NOAEL and LOAEL approach. The Agency 

agrees that a Benchmark Dose approach is preferred over the use of a NOAEL or 

LOAEL for the POD if suitable data (e.g., reflecting the most sensitive sex, species, and 

endpoint identified) are available for modeling and, if suitable data are not available, then 

NOAEL and LOAEL values are utilized. In this case, the data were not suitable for 

BMD modeling and the LOAEL or NOAEL approach was used. 

4. EPA evaluated the PBPK and empirical models available to describe kinetics following 

inhalation of 1,4-dioxane (Reitz et al., 1990, 094806; Young et al., 1977, 062956; Young et 

al., 1978, 625640; Young et al., 1978, 062955). EPA concluded that the use of existing, 

revised, and recalibrated PBPK models for 1,4-dioxane were not superior to default 

approaches for the dose-extrapolation between species. Please comment on whether EPA’s 

rationale regarding the decision to not utilize existing or revised PBPK models has been 

adequately and transparently described and is supported by the available data. Please identify 

and provide the rationale for any alternative approaches that should be considered or 

preferred to the approach presented in the toxicological review. 

Comment: Six reviewers found the decision not to utilize the available PBPK models to 

be appropriate and supported by available data. One of these reviewers suggested 

 A-7 
 

presenting as part of the uncertainty evaluation an adjustment of the experimental doses 

based on metabolic saturation. Another reviewer stated Appendix B was hard to follow 

and that the main document should include a more complete description of the model 

refinement effort performed by Sweeney et al. (2008, 195085). 

Two reviewers noted a complete evaluation of the models was evident; one of the 

reviewers questioned the decision not to use the models on the basis that they were 

unable to fit the human blood PK data for 1,4-dioxane. This reviewer suggested the rat 

model might fit the human blood PK data, thus raising concern in the reliance on the 

human blood PK data to evaluate the PBPK model for 1,4-dioxane. Instead, the reviewer 

suggested the human urinary metabolite data may be sufficient to give confidence in the 

model. One other reviewer also questioned the accuracy of the available human data. 

One reviewer commented that the rationale for not using the PBPK model to extrapolate 

from high to low dose was questioned. In addition, the reviewer suggested that two 

aspects of the model code for Reitz et al. (1990, 094806) need to be verified: 

a. In the document, KLC is defined as a first-order rate constant and is scaled by 

BW0.7. This is inconsistent when multiplied by concentration does not result 

in units of mg/hr. However, if the parameter is actually considered a 

clearance constant (zero-order rate constant) then the scaling rule used, as well 

as the interpretations provided, would be acceptable. 

b. It is unclear as to why AM is calculated on the basis of RAM and not RMEX. 

RMEX seems to represent the amount metabolized per unit time. 

Response: The USEPA performed a rigorous evaluation of the PBPK models available 

for 1,4-dioxane. This effort was extensively described in Section 3.5 and in Appendix B. 

In short, several procedures were applied to the human PBPK model to determine if an 

adequate fit of the model to the empirical model output or experimental observations 

could be attained using biologically plausible values for the model parameters. The recalibrated model predictions for blood 1,4-dioxane levels did not come within 10-fold of 

the experimental values using measured tissue:air partition coefficients of (Leung and 

Paustenbach, 1990, 062932) or (Sweeney et al., 2008, 195085) (Figures B-8 and B-9). 

The utilization of a slowly perfused tissue:air partition coefficient 10-fold lower than 

measured values produces exposure-phase predictions that are much closer to 

observations, but does not replicate the elimination kinetics (Figure B-10). Recalibration of the model with upper bounds on the tissue:air partition coefficients results 

in predictions that are still six- to sevenfold lower than empirical model prediction or 

observations (Figures B-12 and B-13). Exploration of the model space using an 

assumption of first-order metabolism (valid for the 50 ppm inhalation exposure) showed 

that an adequate fit to the exposure and elimination data can be achieved only when 

 A-8 
 

unrealistically low values are assumed for the slowly perfused tissue:air partition 

coefficient (Figure B-16). Artificially low values for the other tissue:air partition 

coefficients are not expected to improve the model fit, as these parameters are shown in 

the sensitivity analysis to exert less influence on blood 1,4-dioxane than VmaxC and Km. 

In the absence of actual measurements for the human slowly perfused tissue:air partition 

coefficient, high uncertainty exists for this model parameter value. Differences in the 

ability of rat and human blood to bind 1,4-dioxane may contribute to the difference in Vd. 

However, this is expected to be evident in very different values for rat and human 

blood:air partition coefficients, which is not the case (Table B-1). Therefore, some other, 

as yet unknown, modification to model structure may be necessary. 

The results of USEPA’s model evaluation were confirmed by other investigators 

(Sweeney et al., 2008, 195085). Sweeney et al. (2008, 195085) concluded that the 

available PBPK model with refinements resulted in an under-prediction of human blood 

levels for 1,4-dioxane by six- to seven fold. It is anticipated that the high uncertainty in 

predictions of the PBPK model for 1,4-dioxane would not result in a more accurate 

derivation of human health toxicity values. 

Because it is unknown whether the parent or the metabolite is the toxic moiety, 

analyses were not conducted to adjust the experimental doses on the basis of metabolic 

saturation. 

The discussion of Sweeney et al. (2008, 195085) was expanded in the main 

document in Section 3.5.3. In the absence of evidence to the contrary, the Agency cannot 

discount the human blood kinetic data published by Young et al. (1977, 062956). Even 

though the PBPK model provided satisfactory fits to the rodent kinetic data, it was not 

used to extrapolate from high dose to low dose in the animal because an internal dose 

metric was not identified and external doses were utilized in derivation of the toxicity 

values. 

KLC was implemented by USEPA during the evaluation of the model and should 

have been described as a clearance constant (zero-order rate constant) with units of 

L/hr/kg0.70. These corrections have been made in the document; however, this does not 

impact the model predictions because it was in reference to the terminology used to 

describe this constant. 

The reviewer is correct that RMEX is the rate of metabolism of 1,4-dioxane per 

unit time; however an amount of 1,4-dioxane metabolized was not calculated in the Reitz 

et al. (1990, 094806) model code. Thus, AM is the amount of the metabolite (i.e., 

HEAA) in the body rather than the amount metabolized of 1,4-dioxane. RAM was 

published by Reitz et al. (1990, 094806) as equation 2 for the change in the amount of 

metabolite in the body per unit time. AMEX is the amount of the metabolite excreted in 

the urine. While the variables used are confusing, the code describes the metabolism of 

 A-9 
 

1,4-dioxane as published in the manuscripts. The comments in the model code were 

updated to make this description more clear (Appendix B). 

5. Please comment on the selection of the uncertainty factors applied to the POD for the 

derivation of the RfD. For instance, are they scientifically justified and transparently and 

objectively described in the document? If changes to the selected uncertainty factors are 

proposed, please identify and provide a rationale(s). Please comment specifically on the 

following uncertainty factors: 

• An interspecies uncertainty factor of 10 was used to account for uncertainties in 

extrapolating from laboratory animals to humans because a PBPK model to support 

interspecies extrapolation was not suitable. 

• An intraspecies (human variability) uncertainty factor of 10 was applied in deriving the 

RfD because the available information on the variability in human response to 

1,4-dioxane is considered insufficient to move away from the default uncertainty factor 

of 10.

• A database uncertainty factor of 3 was used to account for lack of adequate 

reproductive toxicity data for 1,4-dioxane, and in particular absence of a 

multigeneration reproductive toxicity study. Has the rationale for the selection of these 

uncertainty factors been transparently and objectively described in the document? 

Please comment on whether the application of these uncertainty factors has been 

scientifically justified.

Comment: 

One reviewer noted the uncertainty factors appear to be the standard default choices and 

had no alternatives to suggest. 

o Five reviewers agreed that the use of an uncertainty factor of 10 for the interspecies 

extrapolation is fully supportable. One reviewer suggested using BW3/4 scaling 

rather than an uncertainty factor of 10 for animal to human extrapolation. Along 

the same lines, one reviewer suggested a steady-state quantitative analysis to 

determine the importance of pulmonary clearance and hepatic clearance and stated 

that if hepatic clearance scales to body surface and pulmonary clearance is 

negligible, then an adjusted uncertainty factor based on body surface scaling would 

be more appropriate. 

o Seven reviewers stated that the uncertainty factor of 10 for interindividual 

variability (intraspecies) is fully supportable. 

o Six reviewers commented that the uncertainty factor of 3 for database deficiencies 

is fully justifiable. One reviewer suggested adding text to clearly articulate the 

science policy for the use of a factor of 3 for database deficiencies. 

 A-10 
 

Response: The preferred approach to interspecies scaling is the use of a PBPK model; 

however, the PBPK models available for 1,4-dioxane are not suitable for use in this 

health assessment as outlined elsewhere. Another approach that has been commonly 

implemented in the cancer assessments is the use of body weight scaling based on body 

surface area (BW3/4 scaling). It is not standard practice to to apply BW3/4 scaling in 

noncancer assessments at this time. The current default approach used by the Agency 

when PBPK models are not available for extrapolation is the application of an UFA of 10, 

which was implemented in this assessment. 

The absence of a multigenerational reproductive study is why the uncertainty 

factor for database deficiencies (UFD) was retained; however, it was reduced from 10 to 

3. In the text in Section 5.1.3 text was included to clearly state that because of the 

absence of a multigenerational reproductive study for 1,4-dioxane an uncertainty factor of 

3 was used for database deficiencies. No other changes regarding the use of the 

uncertainty factors were made to the document. 

A.1.3. Carcinogenicity of 1,4-dioxane 

1. Under the EPA’s 2005 Guidelines for Carcinogen Risk Assessment 

(www.epa.gov/iris/backgr-d.htm), the Agency concluded that 1,4-dioxane is likely to be 

carcinogenic to humans. Please comment on the cancer weight of evidence characterization. 

Has the scientific justification for the weight of evidence descriptor been sufficiently, 

transparently and objectively described? Do the available data for both liver tumors in rats 

and mice and nasal, mammary, and peritoneal tumors in rats support the conclusion that 

1,4-dioxane is a likely human carcinogen? 

Comment: All reviewers agreed with the Agency’s conclusion that 1,4-dioxane is “likely 

to be carcinogenic to humans”. However, two reviewers also thought 1,4-dioxane could 

be categorized as a potential human carcinogen, since low-dose environmental exposures 

would be unlikely to result in cancer. One reviewer also suggested providing a brief 

recapitulation of the guidance provided by the 2005 Guidelines for Carcinogen Risk 

Assessment regarding classification of a compound as likely to be carcinogenic to 

humans and how a chemical falls into this category. 

Response: The document includes a weight-of-evidence approach to categorize the 

carcinogenic potential of 1,4-dioxane. This was included in Section 4.7.1 based upon 

U.S. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237). 

1,4-Dioxane can be described as likely to be carcinogenic to humans based on evidence 

of liver carcinogenicity in several 2-year bioassays conducted in three strains of rats, two 

 A-11 
 

strains of mice, and in guinea pigs. Additionally, tumors in other organs and tissues have 

been observed in rats due to exposure to 1,4-dioxane. 

2. Evidence indicating the mode of action of carcinogenicity of 1,4-dioxane was considered. 

Several hypothesized MOAs were evaluated within the Toxicological Review and EPA 

reached the conclusion that a MOA(s) could not be supported for any tumor types observed 

in animal models. Please comment on whether the weight of the scientific evidence supports 

this conclusion. Please comment on whether the rationale for this conclusion has been 

transparently and objectively described. Please comment on data available for 1,4-dioxane 

that may provide significant biological support for a MOA beyond what has been described 

in the Toxicological Review. Considerations should include the scientific support regarding 

the plausibility for the hypothesized MOA(s), and the characterization of uncertainty 

regarding the MOA(s). 

Comment: Three reviewers commented that the weight of evidence clearly supported the 

conclusion that a mode of action could not be identified for any of the tumor sites. One 

reviewer commented that there is inadequate evidence to support a specific MOA with 

any confidence and low-dose linear extrapolation is necessary; this reviewer also pointed 

out that EPA should not rule out a metabolite as the toxic moiety. 

One reviewer stated this was outside of his/her area of expertise but indicated that 

the discussion was too superficial and suggested adding statements as to what the Agency 

would consider essential information to make a determination about a MOA. 

Two reviewers commented that even though the MOA for 1,4-dioxane is not clear 

there is substantial evidence that the MOA is non-genotoxic. One of these reviewers also 

suggested that a nonlinear cancer risk assessment model should be utilized. 

One reviewer suggested adding more text to the summary statement to fully 

reflect the available MOA information which should be tied to the conclusion and choice 

of an extrapolation model. 

 

Response: The Agency agrees with the reviewer not to rule out a toxic metabolite as the 

toxic moiety. In Section 5.5.1.2 text is included relating that there is not enough 

information to determine whether the parent compound, its metabolite(s), or a 

combination is responsible for the observed toxicities following exposure to 1,4-dioxane. 

 It is not feasible to describe the exact data that would be necessary to conclude 

that a particular MOA was operating to induce the tumors observed following 

1,4-dioxane exposure. In general, the data would fit the general criteria described in the 

U.S. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237). For 

1,4-dioxane, several MOA hypotheses have been proposed and are explored for the 

 A-12 
 

observed liver tumors in Section 4.7.3. This analysis represents the extent to which data 

could provide support for any particular MOA. 

One reviewer suggested that the evidence indicating that 1,4-dioxane is not 

genotoxic supports a nonlinear approach to low-dose extrapolation. In accordance with 

the U.S. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237), 

the absence of evidence for genotoxicity does not invoke the use of nonlinear low-dose 

extrapolation, nor does it define a MOA. A nonlinear low-dose extrapolation can be 

utilized when a MOA supporting a nonlinear dose response is identified. For 1,4-dioxane 

this is not the case; a cancer MOA for any of the tumor types observed in animal models 

has not been elucidated. Therefore, as concluded in the Toxicological Review, the 

application of a nonlinear low-dose extrapolation approach was not supported. 

Additional text has been added to Section 5.4.3.2 to relay the fact that several 

reviewers recommended that the MOA data support the use of a nonlinear extrapolation 

approach to estimate human carcinogenic risk associated with exposure to 1,4-dioxane 

and that such an approach should be presented in the Toxicological Review. Additional 

text has also been added to the summary statement in Section 6.2.3 stating that the weight 

of evidence is inadequate to establish a MOA(s) by which 1,4-dioxane induces peritoneal, 

mammary, or nasal tumors in rats and liver tumors in rats and mice (see Section 4.7.3 for 

a more detailed discussion of 1,4-dioxane’s hypothesized MOAs). 

3. A two-year drinking water cancer bioassay (JBRC, 1998, 196240) was selected as the 

principal study for the development of an oral slope factor (OSF). Please comment on the 

appropriateness of the selection of the principal study. Has the rationale for this choice been 

transparently and objectively described? 

Comment: 

Seven reviewers agreed with the choice of the JBRC (1998, 196240) study as the 

principal study for the development of an OSF. However, two reviewers that agreed with 

the choice of JBRC (1998, 196240) also commented on the description and evaluation of 

the study. One reviewer commented the evaluation of the study should be separated from 

the evaluation/selection of endpoints within the study. The other reviewer suggested that 

details on the following aspects should be added to improve transparency of the study: 

(1) rationale for selection of doses; (2) temporal information on body weight for 

individual treatment groups; (3) temporal information on mortality rates; and (4) dosing 

details. 

One reviewer thought that the complete rationale for selection of the JBRC (1998, 

196240) study was not provided because there was no indication of whether the study 

was conducted under GLP conditions, and the study was not peer reviewed or published. 

This reviewer noted the NCI (1978, 062935) study was not appropriate for use, but that 

 A-13 
 

the Kociba et al. (1974, 062929) study may have resulted in a lower POD had they 

employed both sexes of mice and combined benign and malignant tumors. 

Response: Since the External Peer Review draft of the Toxicological Review of 

1,4-Dioxane was released (U.S. EPA, 2009, 628630), the cancer portion of the study 

conducted by the JBRC laboratory was published in the peer-reviewed literature as Kano 

et al. (2009, 594539). This manuscript was reviewed by EPA. EPA determined that the 

data published by Kano et al. (2009, 594539) should be included in the assessment of 

1,4-dioxane for several reasons: (1) while the JBRC (1998, 196240) was a detailed 

laboratory report, it was not peer-reviewed; (2) the JBRC improved the diagnosis of preand neoplastic lesions in the liver according to the current diagnostic criteria and 

submitted the manuscript based on this updated data; (3) the Kano et al. (2009, 594539) 

peer-reviewed manuscript included additional information such as body weight growth 

curves and means and standard deviations of estimated dose for both rats and mice of 

both sexes. Thus, the Toxicological Review was updated to reflect the inclusion of the 

data from Kano et al. (2009, 594539), and Appendix E was added for a clear and 

transparent display of the data included in the multiple reports. 

In response to the peer reviewers, dose information was updated throughout the 

assessment and are also provided in detail in Section 4.2.1.2.6, along with temporal 

information on body weights and mortality. Text was also added to Section 4.2.1.2.6 

regarding the choice of high dose selection as included in the Kano et al. (2009, 594539) 

manuscript. Additional discussoin regarding the mortality rates was also added to 

Section 5.4.1 in selection of the critical study for the oral cancer assessment. 

Documentation that the study was conducted in accordance with Organization for 

Economic Co-operation and Development (OECD) Principles of Good Laboratory 

Practice (GLP) is provided in the manuscript (Kano et al., 2009, 594539) and this was 

also added to the text in Section 4.2.1.2.6. 

4. Combined liver tumors (adenomas and carcinomas) in female Cjr:BDF1 mice from the JBRC 

(1998, 196240) study were chosen as the most sensitive species and gender for the derivation 

of the final OSF. Please comment on the appropriateness of the selections of species and 

gender. Please comment on whether the rationale for these selections is scientifically 

justified. Has the rationale for these choices been transparently and objectively described? 

Comment: Six reviewers agreed the female Cjr:BDF1 mice should be used for the 

derivation of the OSF. Five of these reviewers agreed with the rationale for the selection 

of the female Cjr:BDF1 mouse as the most sensitive gender and species. However, one 

reviewer suggested that the specific rationale (i.e., that the final OSF is determined by 

 A-14 
 

selecting the gender/species that gives the greatest OSF value) be stated clearly in a 

paragraph separate from the other considerations of study selection. 

One reviewer was unsure of both the scientific justification for combining benign 

and malignant liver tumors, as well as the background incidence of the observed liver 

tumors in historical control Cjr:BDF1 male and female mice. 

One reviewer commented that the scientific basis for the selection of female 

Cjr:BDF1 mice was unclear. This reviewer thought that the rationale for the choice of 

this strain/sex compared to all others was not clearly articulated. 

Response: Using the approach described in the Guidelines for Carcinogen Risk 

Assessment (U.S. EPA, 2005, 086237) studies were first evaluated based on their quality 

and suitability for inclusion in the assessment. Once the studies were found to be of 

sufficient quality for inclusion in the assessment, the dose-response analysis was 

performed with the goal of determining the most appropriate endpoint and species for use 

in the derivation of an OSF. These topics are discussed in detail in Section 4.7 and 5.4. 

Benign and malignant tumors that arise from the same cell type (e.g., 

hepatocellular) may be combined to more clearly identify the weight of evidence for a 

chemical. This is in accordance with the US EPA’s 2005 Guidelines for Carcinogen Risk 

Assessment as referenced in the Toxicological Review. In the absence of a MOA (MOA 

analysis described in detail in Section 4.7.) for 1,4-dioxane carcinogenicity, it is not 

possible to determine which species may more closely resemble humans. Text in Section 

5.4.4 indicates that the calculation of an OSF for 1,4-dioxane is based upon the doseresponse data for the most sensitive species and gender. 

5. Has the scientific justification for deriving a quantitative cancer assessment been 

transparently and objectively described? Regarding liver cancer, a linear low-dose 

extrapolation approach was utilized to derive the OSF. Please provide detailed comments on 

whether this approach to dose-response assessment is scientifically sound, appropriately 

conducted, and objectively and transparently described in the document. Please identify and 

provide the rationale for any alternative approaches for the determination of the OSF and 

discuss whether such approaches are preferred to EPA’s approach. 

Comment: Four reviewers agreed with the approach for the dose-response assessment. 

One reviewer commented that even if a nongenotoxic MOA were identified for 

1,4-dioxane it may not be best evaluated by threshold modeling. One reviewer 

commented the use of the female mouse data provided an appropriate health protective 

and scientifically valid approach. 

One reviewer commented that the basic adjustments and extrapolation method for 

derivation of the OSF were clearly and adequately described, but disagreed with the 

 A-15 
 

linear low-dose extrapolation. This reviewer suggested that the lack of certainty regarding 

the MOA was not a sufficient cause to default to a linear extrapolation. Another reviewer 

commented that the rationale for a linear low-dose extrapolation to derive the OSF was 

not clear, but may be in accordance with current Agency policy in the absence of a 

known MOA. This reviewer also commented that 1,4-dioxane appears to be nongenotoxic and nonlinear models should be tested on the available data to determine if 

they provide a better fit and are more appropriate. 

One reviewer thought that the justification for a linear extrapolation was not 

clearly provided and that a disconnect between the MOA summary and the choice of a 

linear extrapolation model existed. In addition, this reviewer commented that the 

pharmacokinetic information did not support the use of a linear extrapolation approach, 

but rather use of animal PBPK models to extrapolate from high to low dose that would 

result in a mixture of linear and nonlinear extrapolation models was warranted. 

One reviewer suggested consideration of an integrated assessment of the cancer 

and noncancer endpoints; however, if linear low-dose extrapolation remains the approach 

of choice by the Agency, then the effect of choosing BMRs other than 10% was 

recommended to at least be included in the uncertainty discussion. Using BMRs lower 

than 10% may allow for the identification of a risk level for which the low-dose slope is 

‘best’ estimated. 

Response: The EPA conducted a cancer MOA analysis evaluating all of the 

available data for 1,4-dioxane. Application of the framework in the USEPA’s Guidelines 

for Carcinogen Risk Assessment (2005, 086237) demonstrates that the available evidence 

to support any hypothesized MOA for 1,4-dioxane-induced tumors does not exist. In the 

absence of a MOA, the USEPA’s Guidelines for Carcinogen Risk Assessment (2005, 

086237) indicate that a low dose linear extrapolation should be utilized for dose response 

analysis (see Section 5.4). Some of the potential uncertainty associated with this 

conclusion was characterized in Section 5.5. Note that there is no scientific basis to 

indicate that in the absence of evidence for genotoxicity a nonlinear low-dose 

extrapolation should be used. As concluded in the Toxicological Review, the application 

of a nonlinear low-dose extrapolation approach was not supported. 

With regards to the PBPK model available for 1,4-dioxane, it is clear that there 

currently exist deficiencies within the model and as such, the model was not utilized for 

interspecies extrapolation. Given the deficiencies and uncertainty in the 1,4-dioxane 

model it also does not provide support for a MOA. 

Lastly, in the absence of a MOA for 1,4-dioxane carcinogenicity it is not possible 

to harmonize the cancer and noncancer effects to assess the risk of health effects due to 

exposure. However, the choice of the BMDL10,which was more than 15-fold lower than 

 A-16 
 

the response at the lowest dose (66 mg/kg-day), was reconsidered in response to a public 

comment. BMDs and BMDLs were calculated using a BMR of 30 and 50% extra risk 

(BMD30, BMDL30, BMD50, and BMDL50). A BMR of 50% was used as it resulted in a 

BMDL closest to the response level at the lowest dose tested in the bioassay. 

A.2. PUBLIC COMMENTS 

Comments on the Toxicological Review of 1,4-Dioxane submitted by the public are summarized 

below in the following categories: Oral reference dose for 1,4-dioxane, carcinogenicity of 

1,4-dioxane, PBPK modeling, and other comments. 

A.2.1. Oral reference dose (RfD) for 1,4-dioxane 

Comment: An UF for database deficiencies is not necessary because of considerable 

evidence showing no reproductive or developmental effects from 1,4-dioxane exposure. 

Response: Due to the lack of a multigenerational reproductive study for 1,4-dioxane an 

UF of 3 was retained for database deficiencies. Without clear evidence showing a lack of 

reproductive or developmental effects in a multigenerational reproductive study, there is 

still uncertainty in this area. 

A.2.2. Carcinogenicity of 1,4-dioxane 

Comment: Using liver tumors as the basis for the oral CSF is more appropriate than 

nasal tumors (1988 IRIS assessment of 1,4-dioxane); however, the use of mouse liver 

tumor data is inappropriate because it is inconsistent with other liver models both 

quantitatively and in the dose-response pattern. High mortality rates in the study are also 

a limitation. Liver tumor data from rats should be used instead, which represents a better 

animal model for 1,4-dioxane carcinogenicity assessment. 

Response: Even though the dose-response is different for mice and rats, the female mice 

were considered to be appropriate for the carcinogenicity assessment for several reasons. 

The female mouse liver tumors from the Kano et al. (2009, 594539)report were found to 

be the most sensitive species and endpoint. Section 4.2.1.2.6 was updated to include 

additional information on mortality rates. The majority of the animals lived past 

52 weeks (only 4 females died prior to 52 weeks, 2 in each the mid- and high-dose 

groups). The cause of death in the female mice that died between 1 and 2 years was 

attributed to liver tumors. 

 A-17 
 

Comment: The OSF was based on the most sensitive group, Crj:BDF1 mice; however 

BDF1 mice have a high background rate of liver tumors. The incidence of liver tumors in 

historical controls for this gender/species should be considered in the assessment. 

Sensitivity of the test species/gender as well as other criteria should be considered in the 

selection of the appropriate study, including internal and external validity as outlined in 

Lewandowski and Rhomberg (2005, 626613). The female Crj:BDF1 mice had a low 

survival rate that should be considered in the selection of the animal model for 

1,4-dioxane carcinogenicity. 

Response: Katagiri et al. (1998, 193804) summarized the incidence of hepatocellular 

adenomas and carcinomas in control male and female BDF1 mice from ten 2-year 

bioassays at the JBRC. For female mice, out of 499 control mice, the incidence rates 

were 4.4% for hepatocellular adenomas and 2.0% for hepatocellular carcinomas. Kano 

et al. (2009, 594539) reported a 10% incidence rate for hepatocellular adenomas and a 

0% incidence rate for hepatocellular carcinomas in control female BDF1. These 

incidence rates are near the historical control values and thus are appropriate for 

consideration in this assessment. Additional text regarding these historical controls was 

added to the study description in Section 4.2.1.2.6. 

Comment: Low-dose linear extrapolation for the oral CSF is not appropriate nor justified 

by the data. The weight of evidence supports a threshold (nonlinear) MOA when 

metabolic pathway is saturated at high doses. Nonlinear extrapolations should be 

evaluated and presented for 1,4-dioxane. Oral CSFs should be derived and presented 

using both the BW3/4 scaling as well as available PBPK models to extrapolate across 

species. 

Response: The absence of evidence for genotoxicity/mutagenicity does not indicate the 

use of nonlinear low-dose extrapolation. For 1,4-dioxane, a MOA to explain the 

induction of tumors does not exist so the nature of the low-dose region of the doseresponse is unknown. The oral CSF for 1,4-dioxane was derived using BW3/4 scaling for 

interspecies extrapolation. The PBPK and empirical models available for 1,4-dioxane 

were evaluated and found not to be adequate for use in this assessment, described in 

detail in Appendix B. 

Comment: The POD for the BDF1 female mouse is 15-fold lower than the lowest dose 

in the bioassay, thus the POD is far below the lower limit of the data and does not follow 

the U.S. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237). 

 A-18 
 

Response: The comment is correct that the animal BMDL10 was more than 15-fold 

lower than the response at the lowest dose (66 mg/kg-day) in the bioassay. BMDs and 

BMDLs were calculated using a BMR of 30 and 50% extra risk (BMD30, BMDL30, 

BMD50, and BMDL50). A BMR of 50% was chosen as it resulted in a BMDL closest to 

the response level at the lowest dose tested in the bioassay. 

Comment: The geometric mean of the oral cancer slope factors (as done with B[a]P & 

DDT) should have been used instead of relying on the female BDF1 mouse data, since a 

MOA could not be determined for 1,4-dioxane. 

Response: In accordance with the BMD technical guidance document (U.S. EPA, 2000, 

052150), averaging tumor incidence is not a standard or default approach. Averaging the 

tumor incidence response diminishes the effect seen in the sensitive species/gender. 

Comment: EPA should critically reexamine the choice of JBRC (1998, 196240) as the 

principal study since it has not been published or peer-reviewed. A transcript of e-mail 

correspondence should be provided. 

Response: JBRC (1998, 196240) was published as conference proceedings as Yamazaki 

et al. (1994, 196120) and recently in the peer-reviewed literature as Kano et al. (2009, 

594539). Additional study information was also gathered from the authors (Yamazaki, 

2006, 626614) and is available upon request from the IRIS Hotline. The peer-reviewed 

and published data from Kano et al. (2009, 594539) was incorporated into the final 

version of the Toxicological Review of 1,4-Dioxane. 

Comment: The WOE does not support a cancer descriptor of likely to be carcinogenic to 

humans determination, but rather suggestive human carcinogen at the high dose levels 

used in rodent studies seems more appropriate for the following reasons: 1) lack of 

conclusive human epidemiological data; 2) 1,4-dioxane is not mutagenic; and 3) evidence 

at high doses it would act via cell proliferation MOA. 

Response: A cancer classification of “likely,” based on evidence of liver carcinogenicity 

in several two-year bioassays conducted in three strains of rats, two strains of mice, and 

in guinea pigs was chosen. Also, mesotheliomas of the peritoneum, mammary, and nasal 

tumors have been observed in rats. The Agency agrees that human epidemiological 

studies are inconclusive. The evidence at any dose is insufficient to determine a MOA. 

 A-19 
 

A.2.3. PBPK Modeling

Comment: EPA should have used and considered PBPK models to derive the oral 

toxicity values (rat to human extrapolation) rather than relying on a default method. The 

draft did not consider the Sweeney et al. (2008, 195085) model. The PBPK model should 

be used for both noncancer and cancer dose extrapolation. 

Response: The Agency evaluated the Sweeney et al. (2008, 195085) publication and this 

was included in Appendix B of the document. Text was added to the main document in 

Section 3.5.2.4 and 3.5.3 regarding the evaluation of Sweeney et al. (2008, 195085). This 

model was determined not to be appropriate for interspecies extrapolation. Additionally, 

see response to the external peer review panel comment B4. 

Comment: EPA should use the modified inhalation inputs used in the Reitz et al. (1990, 

094806) model and the updated input parameters provided in Sweeney et al. (2008, 

195085) and add a compartment for the kidney 

Response: See response to previous comment regarding evaluation of Sweeney et al. 

(2008, 195085). Modification of the model to add a kidney compartment is not within 

the scope of this assessment. 

A.2.4. Other Comments 

Comment: EPA should consider the Kasai et al. (2008, 195044; 2009, 193803) studies 

for inhalation and MOA relevance. 

Response: The 13 week and 2-year inhalation studies by Kasai et al. (2008, 195044; 

2009, 193803) were published late in the development stage of this assessment. The IRIS 

Program will evaluate these recently published 1,4-dioxane inhalation data for the 

potential to derive an RfC in a separate assessment. 

Comment: 1,4-Dioxane is not intentionally added to cosmetics and personal care 

products – correct sentence on page 4. 

Response: This oversight was corrected in the document. 

 A-20 
 

APPENDIX B. EVALUATION OF EXISTING PBPK MODELS FOR 1,4-DIOXANE 

B.1. BACKGROUND 

Several pharmacokinetic models have been developed to predict the absorption, 

distribution, metabolism, and elimination of 1,4-dioxane in rats and humans. Single 

compartment, empirical models for rats (Young et al., 1978, 062955; Young et al., 1978, 

625640) and humans (Young et al., 1977, 062956) were developed to predict blood levels of 

1,4-dioxane and urine levels of the primary metabolite, β-hydroxyethoxy acetic acid (HEAA). 

Physiologically based pharmacokinetic (PBPK) models that describe the kinetics of 1,4-dioxane 

using biologically realistic flow rates, tissue volumes and affinities, metabolic processes, and 

elimination behaviors, were also developed (Fisher et al., 1997, 194390; Leung and Paustenbach, 

1990, 062932; Reitz et al., 1990, 094806). 

In developing updated toxicity values for 1,4-dioxane, the available PBPK models were 

evaluated for their ability to predict observations made in experimental studies of rat and human 

exposures to 1,4-dioxane. The model of Reitz et al. (1990, 094806) was identified for further 

consideration to assist in the derivation of toxicity values. Issues related to the biological 

plausibility of parameter values in the Reitz et al. (1990, 094806) human model were identified. 

The model was able to predict the only available human inhalation data set (50 ppm 1,4 dioxane 

for 6 hours; Young et al., 1977, 062956) by increasing (i.e., doubling) parameter values for 

human alveolar ventilation, cardiac output, and the blood:air partition coefficient above the 

measured values. Furthermore, the measured value for the slowly perfused tissue:air partition 

coefficient (i.e., muscle) was replaced with the measured liver value to improve the fit. Analysis 

of the Young et al. (1977, 062956) human data suggested that the apparent volume of 

distribution (Vd) for 1,4-dioxane was approximately 10-fold higher in rats than humans, 

presumably due to species differences in tissue partitioning or other process not represented in 

the model. Subsequent exercising of the model demonstrated that selecting a human slowly 

perfused tissue:air partition coefficient much lower than the measured rat value resulted in better 

agreement between model predictions of 1,4-dioxane in blood and experimental observations. 

Based upon these observations, several model parameters (e.g., metabolism/elimination 

parameters) were re-calibrated using biologically plausible values for flow rates and tissue:air 

partition coefficients. 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS). 

 B-1 
 

This appendix describes activities conducted in the evaluation of the empirical models 

(Young et al., 1977, 062956; Young et al., 1978, 062955; Young et al., 1978, 625640), and recalibration and exercising of the Reitz et al. (1990, 094806) PBPK model, and evaluation of the 

Sweeney et al. (2008, 195085) model to determine the potential utility of the PBPK models for 

1,4-dioxane for interspecies and route-to-route extrapolation. 

B.2. SCOPE 

The scope of this effort consisted of implementation of the Young et al. (1977, 062956; 

1978, 062955; 1978, 625640) empirical rat and human models using the acslXtreme simulation 

software, re-calibration of the Reitz et al. (1990, 094806) human PBPK model, and evaluation of 

model parameters published by Sweeney et al. (2008, 195085). Using the model descriptions 

and equations given in Young et al. (1977, 062956; 1978, 062955; 1978, 625640), model code 

was developed for the empirical models and executed, simulating the reported experimental 

conditions. The model output was then compared with the model output reported in Young et al. 

(1977, 062956; 1978, 062955; 1978, 625640). 

The PBPK model of Reitz et al. (1990, 094806) was re-calibrated using measured values 

for cardiac and alveolar flow rates and tissue:air partition coefficients. The predictions of blood 

and urine levels of 1,4-dioxane and HEAA, respectively, from the re-calibrated model were 

compared with the empirical model predictions of the same dosimeters to determine whether the 

re-calibrated PBPK model could perform similarly to the empirical model. As part of the PBPK 

model evaluation, EPA performed a sensitivity analysis to identify the model parameters having 

the greatest influence on the primary dosimeter of interest, the blood level of 1,4-dioxane. 

Variability data for the experimental measurements of the tissue:air partition coefficients were 

incorporated to determine a range of model outputs bounded by biologically plausible values for 

these parameters. Model parameters from Sweeney et al. (2008, 195085) were also tested to 

evaluate the ability of the PBPK model to predict human data following exposure to 1,4-dioxane. 

B.3. IMPLEMENTATION OF THE EMPIRICAL MODELS IN acslXtreme 

The empirical models of Young et al. (1977, 062956; 1978, 062955; 1978, 625640) for 

1,4-dioxane in rats and humans were reproduced using acslXtreme, version 2.3 (Aegis 

Technologies, Huntsville, AL). Model code files were developed using the equations described 

in the published papers. Additional files containing experiment-specific information (i.e., BWs, 

exposure levels, and duration) were also generated. 

B.3.1. Model Descriptions 

The empirical model of Young et al. (1978, 062955; 1978, 625640) for 1,4-dioxane in 

rats is shown in Figure B-1. This is a single-compartment model that describes the absorption 

and metabolism kinetics of 1,4-dioxane in blood and urine. No information is reported 

 B-2 
 

describing pulmonary absorption or intravenous (i.v.) injection/infusion of 1,4-dioxane. The 

metabolism of 1,4-dioxane and subsequent appearance of HEAA is described by MichaelisMenten kinetics governed by a maximum rate (Vmax, μg/mL-hour) and affinity constant (Km, 

μg/mL) . Both 1,4-dioxane and HEAA are eliminated via the first-order elimination rate 

constants, ke and kme, respectively (hour-1) by which 35% of 1,4-dioxane and 100% of HEAA 

appear in the urine, while 65% of 1,4-dioxane is exhaled. Blood concentration of 1,4-dioxane is 

determined by dividing the instantaneous amount of 1,4-dioxane in blood by a Vd of 301 mL/kg 

BW. 

Inhalation (kINH)

i.v. admin me body

m body

body body HEAAk

DioxK

DioxV

dt

dHEAA ×− +

× = max

e body

m body

body body Dioxk

DioxK

DioxV

dt

dDiox ×− +

× −= max Dioxke ×

HEAAkme × Urine

Urine (35%)

Exhaled (65%)

Inhalation (kINH)

i.v. admin me body

m body

body body HEAAk

DioxK

DioxV

dt

dHEAA ×− +

× = max

e body

m body

body body Dioxk

DioxK

DioxV

dt

dDiox ×− +

× −= max Dioxke ×

HEAAkme × Urine

Urine (35%)

Exhaled (65%)

Source: Used with permission from Taylor & Francis, Young et al. (1978, 062955; 1978, 

625640). 

Figure B-1. Schematic representation of empirical model for 1,4-dioxane in 

rats. 

Figure B-2 illustrates the empirical model for 1,4-dioxane in humans as described in 

Young et al. (1977, 062956). Like the rat model, the human model predicts blood 1,4-dioxane 

and urinary 1,4-dioxane and HEAA levels using a single-compartment structure. However, the 

metabolism of 1,4-dioxane to HEAA in humans is modeled as a first-order process governed by 

a rate constant, KM (hour-1). Urinary deposition of 1,4-dioxane and HEAA is described using the 

first order rate constants, ke(diox) and kme(HEAA), respectively. Pulmonary absorption is described 

by a fixed rate of 76.1 mg/hour (kINH). Blood concentrations of 1,4-dioxane and HEAA are 

calculated as instantaneous amount (mg) divided by Vd(diox) or Vd(HEAA), respectively (104 and 

480 mL/kg BW, respectively). 

 B-3 
 

Inhalation (kINH)

HEAA =VA HEAAd )( ×ConcHEAA

Dioxane Urine

HEAA

KM

ke (diox)

kme (HEAA)

Cumulative 

Dioxane and 

HEAA

Diox =VA Dioxd )( ×ConcDiox

Inhalation (kINH)

HEAA =VA HEAAd )( ×ConcHEAA

Dioxane Urine

HEAA

KM

ke (diox)

kme (HEAA)

Cumulative 

Dioxane and 

HEAA

Diox =VA Dioxd )( ×ConcDiox

Source: Used with permission from Taylor & Francis, Young et al. (1977, 062956). 

Figure B-2. Schematic representation of empirical model for 1,4-dioxane in 

humans. 

B.3.2. Modifications to the Empirical Models 

Several modifications were made to the empirical models. The need for the 

modifications arose in some cases from incomplete reporting of the Young et al. (1977, 062956; 

1978, 062955; 1978, 625640) studies and in other cases from the desire to add capabilities to the 

models to assist in the derivation of toxicity values. 

For the rat model, no information was given by Young et al. (1978, 062955; 1978, 

625640) regarding the parameterization of pulmonary absorption (or exhalation) or i.v. 

administration of 1,4-dioxane. Therefore, additional parameters were added to simulate these 

processes in the simplest form. To replicate 1,4-dioxane inhalation, a first-order rate constant, 

kINH (hour-1), was introduced. kINH was multiplied by the inhalation concentration and the 

respiratory minute volume of 0.238 L/minute (Young et al., 1978, 062955; 1978, 625640). The 

value for kINH was estimated by optimization against the blood time course data of Young et al. 

(1978, 062955; 1978, 625640). Intravenous (i.v.) administration was modeled as instantaneous 

appearance of the full dose at the start of the simulation. Rat urinary HEAA data were reported 

by Young et al. (1978, 062955; 1978, 625640) in units of concentration. To simulate urinary 

HEAA concentration, an estimate of urine volume was required. Since observed urinary 

volumes were not reported by Young et al. (1978, 062955; 1978, 625640), a standard rat urine 

production rate of 0.00145 L/hour was used. 

For humans, Young et al. (1977, 062956) used a fixed 1,4-dioxane inhalation uptake rate 

of 76.1 mg/hour, which corresponded to observations during a 50 ppm exposure. In order to 

facilitate user-specified inhalation concentrations, pulmonary absorption was modeled. The 

modeling was performed identically to the rat model, but using a human minute volume of 

7 L/minute. Urinary HEAA data were reported by Young et al. (1977, 062956) as a cumulative 

amount (mg) of HEAA. Cumulative amount of HEAA in the urine is readily calculated from the 

 B-4 
 

rate of transfer of HEAA from plasma to urine, so no modification was necessary to simulate this 

dose metric for humans. 

Neither empirical model of Young et al. (1977, 062956; 1978, 062955; 1978, 625640) 

described oral uptake of 1,4-dioxane. Adequate data to estimate oral absorption parameters are 

not available for either rats or humans; therefore, neither empirical model was modified to 

include oral uptake. 

B.3.3. Results 

The acslXtreme implementation of the Young et al. (1978, 062955; 1978, 625640) rat 

empirical model simulates the 1,4-dioxane blood levels from the i.v. experiments identically to 

the model output reported in the published paper (Figure B-3). However, the acslXtreme version 

predicts urinary HEAA concentrations in rats that are approximately threefold lower and reach a 

maximum sooner than the predicted levels reported in the paper (Figure B-4). These 

discrepancies may be due, at least in part, to the reliance in the acslXtreme implementation on a 

constant, standard, urine volume rather than experimental measurements, which may have been 

different from the assumed value and may have varied over time. Unreported model parameters 

(e.g., lag times for appearance of excreted HEAA in bladder urine) may also contribute to the 

discrepancy. 

Observations and predictions of 1,4-dioxane in rat blood 

following 3 to 1000 mg/kg IV injection

0.1

1.0

10.0

100.0

1000.0

0 10 20 30 40 50 60 70

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

Observations and predictions of 1,4-dioxane in rat blood 

following 3 to 1000 mg/kg IV injection

0.1

1.0

10.0

100.0

1000.0

0 10 20 30 40 50 60 70

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

Source: Used with permission from Taylor & Francis, Young et al. (1978, 062955; 1978, 

625640). 

Figure B-3. Output of 1,4-dioxane blood level data from the acslXtreme 

implementation (left) and published (right) empirical rat model simulations 

of i.v. administration experiments. 

 B-5 
 

Observations and predictions of HEAA in rat urine 

following 10 or 1000 mg/kg IV injection

1

10

100

1000

10000

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

a (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

Observations and predictions of HEAA in rat urine 

following 10 or 1000 mg/kg IV injection

1

10

100

1000

10000

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

a (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

Source: Used with permission from Taylor & Francis, Young et al. (1978, 062955; 1978, 

625640). 

Figure B-4. Output of HEAA urine level data from acslXtreme 

implementation (left) and published (right) empirical rat model simulations 

of i.v. administration experiments. 

The Young et al. (1978, 062955; 1978, 625640) report did not provide model predictions 

for the 50-ppm inhalation experiment. However, the acslXtreme implementation produces blood 

1,4-dioxane predictions that are quite similar to the reported observations (Figure B-5). As with 

the urine data from the i.v. experiment, the acslXtreme-predicted urinary HEAA concentrations 

are approximately threefold lower than the observations, presumably for the same reasons 

discussed above for the i.v. predictions. 

 B-6 
 

Observations and predictions of 1,4-dioxane in rat blood 

following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et al

(1978) empirical model

Young et al (1978)

observations

Observations and predictions of HEAA in rat urine 

following a 6 hour 50 ppm inhalation exposure

0.0

5.0

10.0

15.0

20.0

25.0

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

al (1978) empirical

model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

acsl version – Young et 

al. (1978a, b) empirical 

model

Young et al. (1978a, b) 

observations

Observations and predictions of 1,4-dioxane in rat blood 

following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et al

(1978) empirical model

Young et al (1978)

observations

Observations and predictions of HEAA in rat urine 

following a 6 hour 50 ppm inhalation exposure

0.0

5.0

10.0

15.0

20.0

25.0

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

al (1978) empirical

model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

acsl version – Young et 

al. (1978a, b) empirical 

model

Young et al. (1978a, b) 

observations

Source: Used with permission from Taylor & Francis, Young et al. (1978, 062955; 1978, 

625640). 

Figure B-5. acslXtreme predictions of blood 1,4-dioxane and urine HEAA 

levels from the empirical rat model simulations of a 6-hour, 50-ppm 

inhalation exposure. 

Inhalation data for a single exposure level (50 ppm) are available for humans. The 

acslXtreme predictions of the blood 1,4-dioxane observations are identical to the predictions 

reported in Young et al. (1977, 062956) (Figure B-6). Limited blood HEAA data were reported, 

and the specimen analysis was highly problematic (e.g., an analytical interference was 

sometimes present from which HEAA could not be separated). For this reason, Young et al. 

(1977, 062956) did not compare predictions of the blood HEAA data to observations in their 

manuscript. 

 B-7 
 

Observations and predictions of 1,4-dioxane in human 

blood following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1977) empirical model

observed

Observations and predictions of 1,4-dioxane in human 

blood following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1977) empirical model

observed

Source: Used with permission from Taylor & Francis, Young et al. (1978, 062955; 1978, 

625640). 

Figure B-6. Output of 1,4-dioxane blood level data from the acslXtreme 

implementation (left) and published (right) empirical human model 

simulations of a 6-hour, 50-ppm inhalation exposure. 

Data for cumulative urinary HEAA amounts are provided in Young et al. (1977, 062956), 

and no analytical problems for these data were reported. Nevertheless, model predictions for 

urinary HEAA were not presented in the manuscript. The acslXtreme prediction of the HEAA 

kinetics profile is similar to the observations, although predicted values are approximately 1.5- to 

2-fold lower than the observed values (Figure B-7). Unlike urinary HEAA observations in the 

rat, human observations were reported as cumulative amount produced, negating the need for 

urine volume data. Therefore, discrepancies between model predictions and experimental 

observations for humans cannot be attributed to uncertainties in urine volumes in the subjects. 

 B-8 
 

Observations and predictions of HEAA in human urine 

following a 6 hour 50 ppm inhalation exposure

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

acsl version - Young et al

(1977) empirical model

observed

Source: Used with permission from Taylor & Francis, Young et al. (1977, 062956). 

Figure B-7. Observations and acslXtreme predictions of cumulative HEAA 

in human urine following a 6-hour, 50-ppm inhalation exposure. 

B.3.4. Conclusions for Empirical Model Implementation 

The empirical models described by Young et al. (1977, 062956; 1978, 062955; 1978, 

625640) for rats and humans were implemented using acslXtreme. The models were modified to 

allow for user-defined inhalation levels by addition of a first-order rate constant for pulmonary 

uptake of 1,4-dioxane, fitted to the inhalation data. No modifications were made for oral 

absorption as adequate data are not available for parameter estimation. The acslXtreme 

predictions of 1,4-dioxane in the blood are identical to the published predictions for simulations 

of 6-hour, 50-ppm inhalation exposures in rats and humans and 3 to 1,000 mg/kg i.v. doses in 

rats (Figures B-3, B-5, and B-6). However, the acslXtreme version predicts lower urinary 

HEAA concentrations in rats appearing earlier than either the Young et al. (1978, 062955; 1978, 

625640) model predictions or the experimental observations. The lower predicted urinary 

HEAA levels in the acslXtreme implementation for rats is likely due to use of default values for 

urine volume in the absence of measured volumes. The reason for differences in time-to-peak 

levels is unknown, but may be the result of an unreported adjustment by Young et al. (1978, 

062955; 1978, 625640) in model parameter values. For humans, Young et al. (1977, 062956) 

did not report model predictions of urinary HEAA levels. The urinary HEAA levels predicted by 

acslXtreme were low relative to the observations. However, unlike the situation in rats, these 

data are not dependent on unreported urine volumes (observations were reported as cumulative 

HEAA amount rather than HEAA concentration), but reflect the model parameter values 

 B-9 
 

reported by Young et al. (1977, 062956). Presently, there is no explanation for the lack of fit of 

the reported urinary HEAA elimination rate constant to the observations. 

B.4. INITIAL RE-CALIBRATION OF THE PBPK MODEL 

Concern regarding adjustments made to some of the parameter values in Reitz et al. 

(1990, 094806) prompted a re-calibration of the Reitz et al. (1990, 094806) human PBPK model 

using more biologically plausible values for all measured parameter values. Reitz et al. (1990, 

094806) doubled the measured physiological flows and blood:air partition coefficient and 

substituted the slowly-perfused tissue:air partition coefficient with the liver:air value in order to 

attain an adequate fit to the observations. This approach increases uncertainty in these parameter 

values, and in the utilization of the model for cross-species dose extrapolation. Therefore, the 

model was re-calibrated using parameter values that are more biologically plausible to determine 

whether an adequate fit of the model to the available data can be attained. 

B.4.1. Sources of Values for Flow Rates 

The cardiac output of 30 L/hour/kg0.74 (Table B-1) reported by Reitz et al. (Reitz et al., 

1990, 094806) is approximately double the mean resting value of 14 L/hour/kg0.74 reported in the 

widely accepted compendium of Brown et al. (1997, 020304). Resting cardiac output was 

reported to be 5.2 L/minute (or 14 L/hour/kg0.74), while strenuous exercise resulted in a flow of 

9.9 L/minute (or 26 L/hour/kg0.74) (Brown et al., 1997, 020304). Brown et al. (1997, 020304) 

also cite the ICRP (1975, 196239) as having a mean respiratory minute volume of 7.5 L/minute, 

which results in an alveolar ventilation rate of 5 L/minute (assuming 33% lung dead space), or 

13 L/minute/kg0.74. Again, this is roughly half the value of 30 L/hour/kg0.74 employed for this 

parameter by Reitz et al. (1990, 094806). Young et al. (1977, 062956) reported that the human 

subjects exposed to 50 ppm for 6 hours were resting inside a walk-in exposure chamber. Thus, 

use of cardiac output and alveolar ventilation rates of 30 L/hour/kg0.74 is not consistent with the 

experimental conditions being simulated. 

 B-10 
 

Table B-1. Human PBPK model parameter values for 1,4-dioxane 

Parameter 

Reitz et al. (1990, 

094806) 

Leung and 

Paustenbach (1990, 

062932) 

Sweeney et al. 

(2008, 195085) EPAc

Physiological Flows 

 Cardiac output (QCC)a 30 -- -- 17.0 

 Alveolar ventilation (QPC)a 30 -- -- 17.7 

Partition Coefficients (PCs) 

 Blood:air (PB) 3,650 1,825 ± 94 1,666 ± 287 1,850 

 Fat:air (PFA) 851 851 ± 118 -- 851 

 Liver:air (PLA) 1,557 1,557 ± 114 1,862 ± 739b 1,557 

 Rapidly perfused tissue:air (PRA) 1,557 -- -- 1,557 

 Slowly perfused tissue:air (PSA) 1,557 997 ± 254 1,348 ± 290b 166 

Metabolic Constants 

 Maximum rate for 1,4-dioxane 

metabolism (VmaxC)

d

6.35 -- -- 5.49 

 Metabolic affinity constant (Km)

e 3.00 -- -- 9.8 

 HEAA urinary elimination rate 

constant (kme)

f

0.56 -- -- 0.44 

a

L/hour/kg BW0.74

b

Measurement for rat tissue 

c

Biologically plausible values utilized by EPA in this assessment d

mg/hour/kg BW0.75

e

mg/L 

f

hour-1

Examination of the experimental data of Young et al. (1977, 062956) yields an estimated 

alveolar ventilation to be 7 L/minute (or 16 L/hour/kg0.74) for volunteers having a mean BW of 

84 kg. This rate is based on the Young et al. (1977, 062956) estimate of 76.1 mg/hour for 

1,4-dioxane uptake. Based on these findings, the cardiac output and alveolar ventilation rates of 

17.0 and 17.7 L/hour/kg0.74 were biologically plausible for the experimental subjects. These rate 

estimates are based on calculations made using empirical data and are consistent with standard 

human values and the experimental conditions (i.e., subject exertion level) reported by Young 

et al. (1977, 062956). Therefore, these flow values were chosen for the model re-calibration. 

B.4.2. Sources of Values for Partition Coefficients 

Two data sources are available for the tissue:air equilibrium partition coefficients for 

1,4-dioxane: Leung and Paustenbach (1990, 062932) and Sweeney et al. (2008, 195085). Both 

investigators report mean values and standard deviations for human blood:air, rat liver:air, and 

rat muscle:air (e.g., slowly perfused tissue:air), while Leung and Paustenbach et al. (1990, 

062932) also reported values for rat fat:air (Table B-1). 

 B-11 
 

B.4.3. Calibration Method 

The PBPK model was twice re-calibrated using the physiological flow values suggested 

values (current EPA assessment, see Table B-1) and the partition coefficients of Leung and 

Paustenbach (1990, 062932) and Sweeney et al. (2008, 195085) separately. For each calibration, 

the metabolic parameters VmaxC and Km, were simultaneously fit (using the parameter estimation 

tool provided in the acslXtreme software) to the output of 1,4-dioxane blood concentrations 

generated by the acslXtreme implementation of the Young et al. (1977, 062956) empirical 

human model for a 6 hour, 50 ppm inhalation exposure. Subsequently, the HEAA urinary 

elimination rate constant, kme, was fitted to the urine HEAA predictions from the empirical 

model. The empirical model predictions, rather than experimental observations, were used to 

provide a more robust data set for model fitting, as the empirical model simulation provided 240 

data points (one prediction every 0.1 hour) compared with hourly experimental observations, and 

to avoid introducing error by calibrating the model to data digitally captured from Young et al. 

(1977, 062956). 

B.4.4. Results 

Results of the model re-calibration are provided in Table B-2. The re-calibrated values 

for VmaxC and kme associated with the Leung and Paustenbach (1990, 062932) or Sweeney et al. 

(2008, 195085) tissue:air partition coefficients are very similar. However, the fitted value for Km

using the Sweeney et al. (2008, 195085) partition coefficients is far lower (0.0001 mg/L) than 

that resulting from use of the Leung and Paustenbach (1990, 062932) partition coefficients 

(2.5 mg/L). This appears to be due to the higher slowly perfused tissue:air partition coefficient 

determined by Sweeney et al. (2008, 195085) (1,348 vs. 997), resulting in a higher apparent Vd

than if the Leung and Paustenbach (1990, 062932) value is used. Thus, the optimization 

algorithm selects a low Km, artificially saturating metabolism in an effort to drive predicted 

blood 1,4-dioxane levels closer to the empirical model output. Saturation of metabolism during a 

50 ppm inhalation exposure is inconsistent with the observed kinetics. 

 B-12 
 

Table B-2. PBPK metabolic and elimination parameter values resulting 

from re-calibration of the human model using alternative values for 

physiological flow ratesa and tissue:air partition coefficients 

Source of Partition Coefficients 

Leung and Paustenbach (1990, 

062932) 

Sweeney et al. (2008, 

195085) 

Maximum rate for 1,4-dioxane metabolism (VmaxC)

b 16.9 20.36 

Metabolic affinity constant (Km)

c 2.5 0.0001 

HEAA urinary elimination rate constant (kme)

d 0.18 0.17 

a

Cardiac output = 17.0 L/hour/kg BW0.74, alveolar ventilation = 17.7 L/hour/kg BW0.74

b

mg/hour/kg BW0.75

c

mg/L 

d

hour-1

Plots of predicted and experimentally observed blood 1,4-dioxane and urinary HEAA 

levels are shown in Figures 4-1 and 4-2. Neither re-calibration resulted in an adequate fit to the 

blood 1,4-dioxane data from the empirical model output or the experimental observations. Recalibration using either the Leung and Paustenbach (1990, 062932) or Sweeney et al. (2008, 

195085) partition coefficients resulted in blood 1,4-dioxane predictions that were at least 10-fold 

lower than empirical model predictions or observations. 

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using 

PC values of Gargas (L&P, 1990)

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predicted

Observations and Predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: Kme fit while using PC values of 

Gargas (L&P, 1990)

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Km fit while using PC 

values from Leung and Paustenbach (1990)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Leung and Paustenbach (1990)

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using 

PC values of Gargas (L&P, 1990)

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predicted

Observations and Predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: Kme fit while using PC values of 

Gargas (L&P, 1990)

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Km fit while using PC 

values from Leung and Paustenbach (1990)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Leung and Paustenbach (1990)

Source: Used with permission from Elsevier, Ltd., Leung and Paustenbach (1990, 

062932). 

Figure B-8. Predicted and observed blood 1,4-dioxane concentrations (left) 

and urinary HEAA levels (right) following re-calibration of the human PBPK 

model with tissue:air partition coefficient values. 

The refitted values for kme resulted in HEAA levels in urine that were very similar to the 

empirical model output (compare Figures B-7, B-8, and B-9), which was not surprising, given 

the fitting of a single parameter to the data. 

 B-13 
 

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using PC 

values of Soelberg et al (2006)

0.1

1.0

10.0

100.0

0 510 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predricted

Observations and Predictions of HEAA in human urine from a 6-

hour, 50 ppm exposure: Kme fit while using PC values of 

Soelberg et al (2006)

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Km fit while using PC 

values from Sweeney et al. (2008)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Sweeney et al. (2008)

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using PC 

values of Soelberg et al (2006)

0.1

1.0

10.0

100.0

0 510 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predricted

Observations and Predictions of HEAA in human urine from a 6-

hour, 50 ppm exposure: Kme fit while using PC values of 

Soelberg et al (2006)

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Km fit while using PC 

values from Sweeney et al. (2008)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Sweeney et al. (2008)

Source: Used with permission of Oxford Journals, Sweeney et al. (2008, 195085). 

Figure B-9. Predicted and observed blood 1,4-dioxane concentrations (left) 

and urinary HEAA levels (right) following re-calibration of the human PBPK 

model with tissue:air partition coefficient values. 

 Outputs of the blood 1,4-dioxane and urinary HEAA levels using the suggested (Table B1) parameters are shown in Figure B-10. These outputs rely on a very low value for the slowly 

perfused tissue:air partition coefficient (166) that is six- to eightfold lower than the measured 

values reported in Leung and Paustenbach (1990, 062932) and Sweeney et al. (2008, 195085), 

and 10-fold lower than the value used by Reitz et al. (1990, 094806). While the predicted 

maximum blood 1,4-dioxane levels are much closer to the observations, the elimination kinetics 

are markedly different, producing higher predicted elimination rates compared to observations 

during the post-exposure phase of the experiment. 

 B-14 
 

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and predictions of 1,4-dioxane in 

human blood from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Observations and predictions of HEAA in human 

urine from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and predictions of 1,4-dioxane in 

human blood from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Observations and predictions of HEAA in human 

urine from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Figure B-10. Predicted and observed blood 1,4-dioxane concentrations (left) 

and urinary HEAA levels (right) using EPA estimated biologically plausible 

parameters (Table B-1). 

B.4.5. Conclusions for PBPK Model Implementation 

Re-calibration of the human PBPK model was performed using experiment-specific 

values for cardiac output and alveolar ventilation (values derived from Young et al., 1977, 

062956) and measured mean tissue:air 1,4-dioxane partition coefficients reported by Leung and 

Paustenbach (1990, 062932) or Sweeney et al. (2008, 195085). The resulting predictions of 

1,4-dioxane in blood following a 6-hour, 50-ppm inhalation exposure were 10-fold (or more) 

lower than either the observations or the empirical model predictions, while the predictions of 

urinary HEAA by the PBPK and empirical models were similar to each other, but lower than 

observed values (Figures B-8 and B-9). Output from the model using biologically plausible 

parameter values (Table B-1), Figure B-10 shows that application of a value for the slowly 

perfused tissue:air partition coefficient, which is 10-fold lower than the measured value reported 

by Leung and Paustenbach (1990, 062932), results in closer agreement of the predictions to 

observations during the exposure phase, but not during the elimination phase. Thus, model recalibration using experiment-specific flow rates and mean measured partition coefficients does 

not result in an adequate fit of the PBPK model to the available data. 

B.4.6. SENSITIVITY ANALYSIS 

A sensitivity analysis of the Reitz et al. (1990, 094806) model was performed to 

determine which PBPK model parameters exert the greatest influence on the outcome of 

dosimeters of interest—in this case, the concentration of 1,4-dioxane in blood. Knowledge of 

 B-15 
 

model sensitivity is useful for guiding the choice of parameter values to minimize model 

uncertainty. 

B.4.7. Method 

A univariate sensitivity analysis was performed on all of the model parameters for two 

endpoints: blood 1,4-dioxane concentrations after 1 and 4 hours of exposure. These time points 

were chosen to assess sensitivity during periods of rapid uptake (1 hour) and as the model 

approached steady state (4 hours) for blood 1,4-dioxane. Model parameters were perturbated 1% 

above and below nominal values and sensitivity coefficients were calculated as follows: 

)(

)()( )('

xf

x

x

xfxxf xf ⋅ Δ

+ Δ − ≈

where x is the model parameter, f(x) is the output variable, Δx is the perturbation of the 

parameter from the nominal value, and f’(x) is the sensitivity coefficient. The sensitivity 

coefficients were scaled to the nominal value of x and f(x) to eliminate the potential effect of 

units of expression. As a result, the sensitivity coefficient is a measure of the proportional 

change in the blood 1,4-dioxane concentration produced by a proportional change in the 

parameter value, with a maximum value of 1. 

B.4.8. Results 

The sensitivity coefficients for the seven most influential model parameters at 1 and 

4 hours of exposure are shown in Figure B-11. The three parameters with the highest sensitivity 

coefficients in descending order are alveolar ventilation (QPC) (1.0), the blood:air partition 

coefficient (PB) (0.65), and the slowly perfused tissue:air partition coefficient (PSA) (0.51). Not 

surprisingly, these were the parameters that were doubled or given surrogate values in the Reitz 

et al. (1990, 094806) model in order to achieve an adequate fit to the data. Because of the large 

influence of these parameters on the model, it is important to assign values to these parameters in 

which high confidence is placed, in order to reduce model uncertainty. 

 B-16 
 

0.01 0.10 1.00

QPC

PB

PSA

QSC

QCC

VMAXC

KM

Parameter

Sensitivity Coefficients: CV - 1hr

0.01 0.10 1.00

QPC

PB

PSA

VMAXC

KM

PRA

QSC

Parameter

Sensitivity Coefficients: CV - 4 hr

QPC

PB

PSA

QSC

QCC

VmaxC

Km

QPC

PB

PSA

VmaxC

Km

PRA

QSC

0.01 0.10 1.00

QPC

PB

PSA

QSC

QCC

VMAXC

KM

Parameter

Sensitivity Coefficients: CV - 1hr

0.01 0.10 1.00

QPC

PB

PSA

VMAXC

KM

PRA

QSC

Parameter

Sensitivity Coefficients: CV - 4 hr

QPC

PB

PSA

QSC

QCC

VmaxC

Km

QPC

PB

PSA

VmaxC

Km

PRA

QSC

Figure B-11. The highest seven sensitivity coefficients (and associated 

parameters) for blood 1,4-dioxane concentrations (CV) at 1 (left) and 4 

(right) hours of a 50-ppm inhalation exposure. 

B.5. PBPK MODEL EXERCISES USING BIOLOGICALLY PLAUSIBLE PARAMETER 

BOUNDARIES 

The PBPK model includes numerous physiological parameters whose values are typically 

taken from experimental observations. In particular, values for the flow rates (cardiac output and 

alveolar ventilation) and tissue:air partition coefficients (i.e., mean and standard deviations) are 

available from multiple sources as means and variances. The PBPK model was exercised by 

varying the partition coefficients over the range of biological plausibility (parameter mean ± 

2 standard deviations), re-calibrating the metabolism and elimination parameters, and exploring 

the resulting range of blood 1,4-dioxane concentration time course predictions. Cardiac output 

and alveolar ventilation were not varied because the experiment-specific values used did not 

include any measure of inter-individual variation. 

B.5.1. Observations Regarding the Volume of Distribution 

Young et al. (1978, 062955; 1978, 625640) used experimental observations to estimate a 

Vd for 1,4-dioxane in rats of 301 mL, or 1,204 mL/kg BW. For humans, the Vd was estimated to 

be 104 mL/kg BW (Young et al., 1977, 062956). It is possible that a very large volume of the 

slowly perfused tissues in the body of rats and humans may be a significant contributor to the 

estimated 10-fold difference in distribution volumes for the two species. This raises doubt 

regarding the appropriateness of using the measured rat slowly perfused tissue:air partition 

coefficient as a surrogate values for humans in the PBPK model. 

 B-17 
 

B.5.2. Defining Boundaries for Parameter Values 

Given the possible 10-fold species differences in the apparent Vd for 1,4-dioxane in rats 

and humans, boundary values for the partition coefficients were chosen to exercise the PBPK 

model across its performance range to either minimize or maximize the simulated Vd. This was 

accomplished by defining biologically plausible values for the partition coefficients as the 

mean ± 2 standard deviations of the measured values. Thus, to minimize the simulated Vd for 

1,4-dioxane, the selected blood:air partition coefficient was chosen to be the mean + 2 standard 

deviations, while all of the other tissue:air partition coefficients were chosen to be the mean – 2 

standard deviations. This created conditions that would sequester 1,4-dioxane in the blood, away 

from other tissues. To maximize the simulated 1,4-dioxane Vd, the opposite selections were 

made: blood and other tissue:air partition coefficients were chosen as the mean – 2 standard 

deviations and mean + 2 standard deviations, respectively. Subsequently, VmaxC, Km, and kme

were optimized to the empirical model output data as described in Section B.4.3. This procedure 

was performed for both the Leung and Paustenbach (1990, 062932) and Sweeney et al. (2008, 

195085) partition coefficients (Table B-1). The two predicted time courses resulting from the recalibrated model with partition coefficients chosen to minimize or maximize the 1,4-dioxane Vd

represent the range of model performance as bounded by biologically plausible parameter values. 

B.5.3. Results 

The predicted time courses for a 6-hour, 50-ppm inhalation exposure for the re-calibrated 

human PBPK model with mean (central tendency) and ± 2 standard deviations from the mean 

values for partition coefficients are shown in Figure B-12 for the Leung and Paustenbach (1990, 

062932) values and Figure B-13 for the Sweeney et al. (2008, 195085) values. The resulting 

fitted values for VmaxC, Km, and kme, are given in Table B-3. By bounding the tissue:air partition 

coefficients with upper and lower limits on biologically plausible values from Leung and 

Paustenbach (1990, 062932) or Sweeney et al. (2008, 195085), the model predictions are still at 

least six- to sevenfold lower than either the empirical model output or the experimental 

observations. The range of possible urinary HEAA predictions brackets the prediction of the 

empirical model, but this agreement is not surprising, as the cumulative rate of excretion depends 

only on the rate of metabolism of 1,4-dioxane, and not on the apparent Vd for 1,4-dioxane. 

These data show that the PBPK model cannot adequately reproduce the predictions of blood 

1,4-dioxane concentrations of the Young et al. (1977, 062956) human empirical model or the 

experimental observations when constrained by biologically plausible values for physiological 

flow rates and tissue:air partition coefficients. 

 B-18 
 

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

 

Source: Used with permission of Elsevier, Ltd., Leung and Paustenbach (1990, 062932) 

Figure B-12. Comparisons of the range of PBPK model predictions from 

upper and lower boundaries on partition coefficients with empirical model 

predictions and experimental observations for blood 1,4-dioxane 

concentrations (left) and urinary HEAA levels (right) from a 6-hour, 50-ppm 

inhalation exposure. 

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation 

data

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation data

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation 

data

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation data

Source: Used with permission of Oxford Journals, Sweeney et al. (2008, 195085); Used 

with permission of Taylor & Francis, Young et al. (1977, 062956). 

Figure B-13. Comparisons of the range of PBPK model predictions from 

upper and lower boundaries on partition coefficients with empirical model 

predictions and experimental observations for blood 1,4-dioxane 

concentrations (left) and urinary HEAA levels (right) from a 6-hour, 50-ppm 

inhalation exposure. 

 B-19 
 

Table B-3. PBPK metabolic and elimination parameter values resulting 

from recalibration of the human model using biologically plausible values for 

physiological flow ratesa and selected upper and lower boundary values for 

tissue:air partition coefficients 

Leung and Pausenbach (1990, 062932) Sweeney et al. (2008, 195085) 

Source of partition coefficients For maximal Vd For minimal Vd For maximal Vd For minimal Vd

Maximum rate for 1,4-dioxane 

metabolism (VmaxC)

b

14.95 18.24 17.37 21.75 

Metabolic dissociation constant 

(Km)

c

5.97 0.0001 4.88 0.0001 

HEAA urinary elimination rate 

constant (kme)

d

0.18 0.17 0.26 0.19 

a

Cardiac output = 17.0 L/hour/kg BW0.74, alveolar ventilation = 17.7 L/hour/kg BW0.74

b

mg/hour/kg BW0.75

c

mg/L 

d

hour-1

B.5.4. Alternative Model Parameterization 

Since the PBPK model does not predict the experimental observations of Young et al. 

(1977, 062956) when parameterized by biologically plausible values, an exercise was performed 

to explore alternative parameters and values capable of producing an adequate fit of the data. 

Since the metabolism of 1,4-dioxane appears to be linear in humans for a 50-ppm exposure 

(Young et al., 1977, 062956), the parameters VmaxC and Km were replaced by a zero-order, nonsaturable metabolism rate constant, kLC. This rate constant was fitted to the experimental blood 

1,4-dioxane data using partition coefficient values of Sweeney et al. (2008, 195085) to minimize 

the Vd (i.e., maximize the blood 1,4-dioxane levels). The resulting model predictions are shown 

in Figure B-14. As before, the maximum blood 1,4-dioxane levels were approximately 

sevenfold lower than the observed values. 

 B-20 
 

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure: KLC (3.0) fitted to all observations

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

KLC-fitted model

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm

exposure: kLC (3.0) fitted to all observations

Young et al. (1977) empirical 

model

kLC – fitted model

Young et al. (1977) 

observation data

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure: KLC (3.0) fitted to all observations

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

KLC-fitted model

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm

exposure: kLC (3.0) fitted to all observations

Young et al. (1977) empirical 

model

kLC – fitted model

Young et al. (1977) 

observation data

Figure B-14. Predictions of blood 1,4-dioxane concentration following 

calibration of a zero-order metabolism rate constant, kLC, to the 

experimental data. 

A re-calibration was performed using only the data from the exposure phase of the 

experiment, such that the elimination data did not influence the initial metabolism and tissue 

distribution. The model predictions from this exercise are shown in Figure B-15. These 

predictions are more similar to the observations made during the exposure phase of the 

experiment; however, this is achieved at greatly reduced elimination rate (compare Figures B-10 

and B-15). 

 B-21 
 

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure: KLC (0.1) fitted 1-6 hour

 observations

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

KLC-fitted model

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm

exposure: kLC (0.1) fitted 1 to 6-hour observations

Young et al. (1977) empirical 

model

kLC – fitted model

Young et al. (1977) 

observation data

Figure B-15. Predictions of blood 1,4-dioxane concentration following 

calibration of a zero-order metabolism rate constant, kLC, to only the 

exposure phase of the experimental data. 

Finally, the model was re-calibrated by simultaneously fitting kLC and the slowly 

perfused tissue:air partition coefficient to the experimental data with no bounds on possible 

values (except that they be non-zero). The fitted slowly perfused tissue:air partition coefficient 

was an extremely low (and biologically unlikely) value of 0.0001. The resulting model 

predictions, however, were closer to the observations than even the empirical model predictions 

(Figure B-16). These exercises show that better fits to the observed blood 1,4-dioxane kinetics 

are achieved only when parameter values are adjusted in a way that corresponds to a substantial 

decrease in apparent Vd of 1,4-dioxane in the human, relative to the rat (e.g., decreasing the 

slowly perfused tissue:air partition coefficient to extremely low values, relative to observations). 

Downward adjustment of the elimination parameters (e.g., decreasing kLC) increases the 

predicted blood concentrations of 1,4-dioxane, achieving better agreement with observations 

during the exposure phase of the experiment; however, it results in unacceptably slow 

elimination kinetics, relative to observations following cessation of exposure. These 

observations suggest that some other process not captured in the present PBPK model structure is 

responsible for the species differences in 1,4-dioxane Vd and the inability to reproduce the 

human experimental inhalation data with biologically plausible parameter values. 

 B-22 
 

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Metab and slow PCfitted model

observations

Young et al. (1977) empirical 

model

Metabolism and slow PCfitted model

Young et al. (1977) 

observation data

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Metab and slow PCfitted model

observations

Young et al. (1977) empirical 

model

Metabolism and slow PCfitted model

Young et al. (1977) 

observation data

Figure B-16. Predictions of blood 1,4-dioxane concentration following 

simultaneous calibration of a zero-order metabolism rate constant, kLC, and 

slowly perfused tissue:air partition coefficient to the experimental data. 

B.6. CONCLUSIONS 

The rat and human empirical models of Young et al. (1977, 062956; 1978, 062955; 1978, 

625640) were successfully implemented in acslXtreme and perform identically to the models 

reported in the published papers (Figures 3-3 through 3-6), with the exception of the lower 

predicted HEAA concentrations and early appearance of the peak HEAA levels in rat urine. The 

early appearance of peak HEAA levels cannot presently be explained, but may result from 

manipulations of kme or other parameters by Young et al. (1978, 062955; 1978, 625640) that 

were not reported. The lower predictions of HEAA levels are likely due to reliance on a standard 

urine volume production rate in the absence of measured (but unreported) urine volumes. While 

the human urinary HEAA predictions were lower than observations, this is due to parameter 

fitting of Young et al. (1977, 062956). No model output was published in Young et al. (1977, 

062956) for comparison. The empirical models were modified to allow for user-defined 

inhalation exposure levels. However, no modifications were made to model oral exposures 

because adequate data to parameterize such modifications do not exist for rats or humans. 

Several procedures were applied to the human PBPK model to determine if an adequate 

fit of the model to the empirical model output or experimental observations could be attained 

using biologically plausible values for the model parameters. The re-calibrated model 

predictions for blood 1,4-dioxane levels do not come within 10-fold of the experimental values 

using measured tissue:air partition coefficients from Leung and Paustenbach (1990, 062932) or 

Sweeney et al. (2008, 195085) (Figures B-8 and B-9). Use of a slowly perfused tissue:air 

 B-23 
 

partition coefficient 10-fold lower than measured values produces exposure-phase predictions 

that are much closer to observations, but does not replicate the elimination kinetics 

(Figure B-10). Re-calibration of the model with upper bounds on the tissue:air partition 

coefficients results in predictions that are still six- to sevenfold lower than empirical model 

prediction or observations (Figures B-12 and B-13). Exploration of the model space using an 

assumption of first-order metabolism (valid for the 50-ppm inhalation exposure) showed that an 

adequate fit to the exposure and elimination data can be achieved only when unrealistically low 

values are assumed for the slowly perfused tissue:air partition coefficient (Figure B-16). 

Artificially low values for the other tissue:air partition coefficients are not expected to improve 

the model fit, because the sensitivity analysis to exert less influence on blood 1,4-dioxane than 

VmaxC and Km. This suggests that the model structure is insufficient to capture the apparent 

10-fold species difference in the blood 1,4-dioxane Vd between rats and humans. In the absence 

of actual measurements for the human slowly perfused tissue:air partition coefficient, high 

uncertainty exists for this model parameter value. Differences in the ability of rat and human 

blood to bind 1,4-dioxane may contribute to the difference in Vd. However, this is expected to 

be evident in very different values for rat and human blood:air partition coefficients, which is not 

the case (Table B-1). Therefore, some other, as yet unknown, modification to model structure 

may be necessary. 

B.7. RECOMMENDATIONS FOR UTILIZING EXISTING PBPK MODELS 

The use of empirical or PBPK models to reduce uncertainty in extrapolation of doseresponses (in terms of internal dosimetry) requires accurate representation of exposure and 

biological reality. In the case of the empirical models of Young et al. (1977, 062956; 1978, 

062955; 1978, 625640), the acslXtreme implementations are adequate for predicting blood 

1,4-dioxane levels for a variety of inhalation exposure levels in rats and up to 50 ppm in humans. 

However, the absence of data with which to evaluate simulated oral absorption in either species 

precludes the inclusion of this route of exposure in the models. Therefore, the empirical models 

may be useful for assessment of toxicity by inhalation exposure, but not by oral exposure, and 

not for route-to-route extrapolation. For the PBPK model, an apparent gap in the model structure 

exists such that experimental observations of blood 1,4-dioxane levels in humans during and 

following inhalation exposures to 1,4-dioxane cannot be reproduced under the constraints of 

biologically plausible parameter values for all parameters. Therefore, the use of the PBPK 

model (in its present form) is not recommended for application to the derivation of toxicity 

values for 1,4-dioxane. 

 B-24 
 

B.8. acslXtreme CODE FOR THE YOUNG ET AL. EMPIRCAL MODEL FOR 

1,4-DIOXANE IN RATS 

PROGRAM: Young (1978, 062955) rat.csl 

!----------------------------------------------------------------- 

! Created by Michael Lumpkin, Syracuse Research Corporation, 08/06 

! This program implements the 1-compartment empirical model for 1,4-dioxane 

! in rats, developed by Young et al. 1978a, b. Program was modified to run 

! in ACSL Xtreme and to include user-defined i.v. and inhalation concentrations 

!(MLumpkin, 08/06) 

!----------------------------------------------------------------- 

INITIAL 

!*****Timing and Integration Commands***** 

ALGORITHM IALG=2 !Gear integration algorithm for stiff systems 

!MERROR %%%%=0.01 !Relative error for lead in plasma 

NSTEPS NSTP=1000 !Number of integration steps per communication interval 

CINTERVAL CINT=0.1 !Communication interval 

CONSTANT TSTART=0. !Start of simulation (hr) 

CONSTANT TSTOP=70. !End of simulation (hr) 

!*****MODEL PARAMETERS***** 

CONSTANT BW=0.215 !Body weight (kg) 

CONSTANT MINVOL=0.238 !respiratory minute volume (L/min) estimated from Young et al. 

(1978) 

CONSTANT IVDOSE = 0. !IV dose (mg/kg)! 

CONSTANT CONC = 0. !inhalation concentration (ppm) 

CONSTANT MOLWT=88.105 !mol weight of 1,4-dioxane 

CONSTANT TCHNG=6.0 !Exposure pulse 1 width (hr) 

CONSTANT TDUR=24.0 !Exposure duration (hr) 

CONSTANT TCHNG2=120.0 !Exposure pulse 2 width (hr) 

CONSTANT TDUR2=168.0 !Exposure duration 2 (hr) 

CONSTANT Vmax=4.008 !(mcg/mL/hr) 

CONSTANT Km=6.308 !(mcg/mL) 

CONSTANT Kinh=0.43 !pulmonary absorption constant (/hr) 

CONSTANT Ke=0.0149 !(/hr) 

CONSTANT Kme=0.2593 !(/hr) 

CONSTANT Vd=0.3014 !(L) 

IV = IVDOSE*BW 

AmDIOXi=IV 

END !Of Initial Section 

DYNAMIC 

 B-25 
 

DERIVATIVE 

!*** Dioxane inhalation concentration *** 

CIZONE=PULSE(0.0, TDUR, TCHNG) * PULSE(0.0, TDUR2, TCHNG2) 

 !First pulse is hours/day, second pulse is hours/week 

CI=CONC*CIZONE*MOLWT/24450. !Convert to mg/L 

!*** Dioxane metabolism/1st order elimination *** 

dAmDIOX=(Kinh*CI*(MINVOL*60))-((Vmax*(AmDIOX))/(Km+(AmDIOX)))-

(Ke*(AmDIOX)) 

AmDIOX=INTEG(dAmDIOX,AmDIOXi) 

ConcDIOX=AmDIOX/Vd !plasma dioxane concentration (mcg/mL) 

AUCDIOX=INTEG(ConcDIOX,0) !plasma dioxane AUC 

!*** HEAA production and 1st order metabolism *** 

dAmHEAA=((Vmax*(AmDIOX))/(Km+(AmDIOX)))-(Kme*(AmHEAA)) 

AmHEAA=INTEG(dAmHEAA,0.) 

ConcHEAA=AmHEAA/Vd !plasma HEAA concentration 

!*** 1st order dioxane elimination to urine *** 

dAmDIOXu=(Ke*(AmDIOX))*0.35 

AmDIOXu=INTEG(dAmDIOXu,0.) 

ConcDIOXu=Ke*AmDIOX*0.35/1.45e-3 !urine production approx 1.45e-3 L/hr in SD rats 

!*** 1st order dioxane exhaled *** 

dAmDIOXex=(Ke*(AmDIOX))*0.65 

AmDIOXex=INTEG(dAmDIOXex,0.) 

!*** 1st order HEAA elimination to urine *** 

dAmHEAAu=(Kme*(AmHEAA)) 

AmHEAAu=INTEG(dAmHEAAu,0.) 

ConcHEAAu=Kme*AmHEAA/1.45e-3 !urine production approx 1.45e-3 L/hr in SD rats 

END !of Derivative Section 

DISCRETE 

END !of Discrete Section 

TERMT (T .GT. TSTOP) 

END !of Dynamic Section 

TERMINAL 

END !of Terminal Section 

END !of Program 

 B-26 
 

B.9. acslXtreme CODE FOR THE YOUNG ET AL. EMPIRICAL MODEL FOR 

1,4-DIOXANE IN HUMANS 

PROGRAM: Young (1977, 062956) human.csl 

!----------------------------------------------------------------- 

! Created by Michael Lumpkin, Syracuse Research Corporation, 01/06 

! This program implements the 1-compartment model for 1,4-dioxane in humans, 

! developed by Young et al., 1977. Program was modified to run 

! in acslXtreme (MLumpkin, 08/06) 

!----------------------------------------------------------------- 

INITIAL 

!*****Timing and Integration Commands***** 

ALGORITHM IALG=2 !Gear integration algorithm for stiff systems 

!MERROR %%%%=0.01 !Relative error for lead in plasma 

NSTEPS NSTP=1000 !Number of integration steps per communication interval 

CINTERVAL CINT=0.1 !Communication interval 

CONSTANT TSTART=0. !Start of simulation (hr) 

CONSTANT TSTOP=120. !End of simulation (hr) 

!*****MODEL PARAMETERS***** 

!CONSTANT DATA=1 !Optimization dataset 

CONSTANT MOLWT=88.105 !mol weight for 1,4-dioxane 

CONSTANT DOSE=0. !Dose (mg/kg 

CONSTANT CONC=0. !Inhalation concentration (ppm) 

CONSTANT BW=84.1 !Body weight (kg) 

CONSTANT MINVOL=7.0 !pulmonary minute volume (L/min) 

CONSTANT F=1.0 !Fraction of dose absorbed 

CONSTANT kinh=1.06 !Rate constant for inhalation (mg/hr); optimized by MHL 

CONSTANT ke=0.0033 !Rate constant for dioxane elim to urine (hr-1) 

CONSTANT km=0.7096 !Rate constant for metab of dioxane to HEAA (hr-1) 

CONSTANT kme=0.2593 !Rate constant for transfer from rapid to blood (hr-1) 

CONSTANT VdDkg=0.104 !Volume of distribution for dioxane (L/kg BW) 

CONSTANT VdMkg=0.480 !Volume of distribution for HEAA (L/kg BW) 

CONSTANT OStart=0. !Time of first oral dose (hr) 

CONSTANT OPeriod=120. !Oral Dose pulse period (hr) 

CONSTANT OWidth=1. !Width (gavage/drink time) of oral dose (hr) 

CONSTANT IStart=0. !Time of inhalation onset (hr) 

CONSTANT IPeriod=120. !Inhalation pulse period (hr) 

CONSTANT IWidth=6. !Width (duration) of inhalation exposure (hr) 

END !Of Initial Section 

DYNAMIC 

DERIVATIVE 

 B-27 
 

! VARIABLES and DEFINED VALUES** *** 

VdD=BW*VdDkg !Volume of distribution for dioxane 

VdM=BW*VdMkg !Volume of distribution for HEAA 

InhalePulse=PULSE(IStart,IPeriod,IWidth) 

Inhale=CONC*InhalePulse*MOLWT/24450. !Convert to mg/L 

!*****DIFFERENTIAL EQUATIONS FOR COMPARTMENTS  

!** * Dioxane in the body (plasma) *** 

dAMTbD=(Kinh*Inhale*(MINVOL*60))-(AMTbD*km)-(AMTbD*ke) 

AMTbD=INTEG(dAMTbD,0.) 

CbD=AMTbD/VdD 

AUCbD=INTEG(CbD,0) 

!*** HEAA in the body (plasma)*** 

dAMTbM=AMTbD*km-AMTbM*kme 

AMTbM=INTEG(dAMTbM,0.) 

CbM=AMTbM/VdM 

!*** Cumulative Dioxane in the urine *** 

dAMTuD=(AMTbD*ke) 

AMTuD=INTEG(dAMTuD,0.) 

!*** Cumulative HEAA in the urine *** 

dAMTuM=(AMTbM*kme) 

AMTuM=INTEG(dAMTuM,0.) 

END !Of Derivative Section 

DISCRETE 

END !of Discrete Section 

TERMT (T .GT. TSTOP) 

END !Of Dynamic Section 

TERMINAL 

END !of Terminal Section 

END !of Program 

 B-28 
 

B.10. acslXtreme CODE FOR THE REITZ ET AL. PBPK MODEL FOR 1,4- DIOXANE 

(Reitz et al., 1990, 094806) 

PROGRAM: DIOXANE.CSL (Used in Risk Estimation Procedures) 

 !Added a venous blood compartment and 1st order elim of metab.' 

 !Mass Balance Checked OK for Inhal, IV, Oral, and Water RHR' 

 !Defined Dose Surrogates for Risk Assessment 01/04/89' 

 !Modified the Inhal Route to use PULSE for exposure conditions' 

 !Modifications by GLDiamond, Aug2004, marked as !** 

 ! 

 !Metabolism of dioxane modified by MLumpkin, Oct2006, to include 1st order 

 !or saturable kinetics. For 1st order, set VmaxC=0; for M-Menten, set KlC=0. 

 ! 

INITIAL 

 INTEGER I 

 I=1 

! ARRAY TDATA(20) ! CONSTANT TDATA=999, 19*1.0E-6 !** 

 CONSTANT BW = 0.40 !'Body weight (kg)' 

 CONSTANT QPC = 15. !'Alveolar ventilation rate (l/hr)' 

 CONSTANT QCC = 15. !'Cardiac output (l/hr)' 

!Flows to Tissue Compartments' 

 CONSTANT QLC = 0.25 !'Fractional blood flow to liver' 

 CONSTANT QFC = 0.05 !'Fractional blood flow to fat' 

 CONSTANT QSC = 0.18 !'Fractional blood flow to slow' 

 QRC = 1.0 - (QFC + QSC + QLC) 

 CONSTANT SPDC = 1.0 ! diffusion constant for slowly perfused tissues 

!Volumes of Tissue/Blood Compartments' 

 CONSTANT VLC = 0.04 !'Fraction liver tissue' 

 CONSTANT VFC = 0.07 !'Fraction fat tissue' 

 CONSTANT VRC = 0.05 !'Fraction Rapidly Perf tissue' 

 CONSTANT VBC = 0.05 !'Fraction as Blood' 

 VSC = 0.91 - (VLC + VFC + VRC + VBC) 

!Partition Coefficients' 

 CONSTANT PLA = 1557. !'Liver/air partition coefficient' 

 CONSTANT PFA = 851. !'Fat/air partition coefficient' 

 CONSTANT PSA = 2065. !'Muscle/air (Slow Perf) partition' 

 CONSTANT PRA = 1557. !'Richly perfused tissue/air partition' 

 CONSTANT PB = 1850. !'Blood/air partition coefficient' 

!Other Compound Specific Parameters' 

 CONSTANT MW = 88.1 !'Molecular weight (g/mol)' 

 CONSTANT KLC = 12.0 ! temp zero-order metab constant 

 CONSTANT VMAXC = 13.8 !'Maximum Velocity of Metabol.' 

 CONSTANT KM = 29.4 !'Michaelis Menten Constant' 

 CONSTANT ORAL = 0.0 !'Oral Bolus Dose (mg/kg)' 

 B-29 
 

 CONSTANT KA = 5.0 !'Oral uptake rate (/hr)' 

 CONSTANT WATER = 0.0 !'Conc in Water (mg/liter, ppm)' 

 CONSTANT WDOSE=0.0 !Water dose (mg/kg/day) ** 

 CONSTANT IV = 0.0 !'IV dose (mg/kg)' 

 CONSTANT CONC = 0.0 !'Inhaled concentration (ppm)' 

 CONSTANT KME = 0.276 !'Urinary Elim constant for met (hr-1)' 

!Timing commands' 

 CONSTANT TSTOP = 50 !'Length of experiment (hrs)' 

 CONSTANT TCHNG = 6 !'Length of inhalation exposure (hrs)' 

 CINTERVAL CINT=0.1 

 CONSTANT WIDD=24. !** 

 CONSTANT PERD=24. !** 

 CONSTANT PERW=168. !** 

 CONSTANT WIDW=168. !** 

 CONSTANT DAT=0.017 !** 

!Scaled parameters calculated in this section of Program' 

 QC=QCC*BW**0.74 

 QP=QPC*BW**0.74 

 QL=QLC*QC 

 QF=QFC*QC 

 QS=QSC*QC 

 QR=QRC*QC 

 VL=VLC*BW 

 VF=VFC*BW 

 VS=VSC*BW 

 VR=VRC*BW 

 VB=VBC*BW 

 PL=PLA/PB 

 PR=PRA/PB 

 PS=PSA/PB 

 PF=PFA/PB 

 KL = KLC*bw**0.7 ! Zero-order metab constant 

 VMAX = VMAXC*BW**0.7 

 DOSE = ORAL*BW !'Initial Amount in Stomach' 

 AB0 = IV*BW !'Initial Amount in Blood' 

 !DRINK = 0.102*BW**0.7*WATER/24 !'Input from water (mg/hr)' !** 

 !DRINKA = 0.102*BW**0.7*WATER/DAT !'Input from water (mg/hr)' !** 

 DRINKA=WDOSE*BW/DAT 

 CV = AB0/VB !'Initialize CV' 

END !'End of INITIAL' 

DYNAMIC 

 ALGORITHM IALG = 2 !'Gear method for stiff systems' 

 TERMT(T .GE. TSTOP ) 

 CR = AR/VR 

 B-30 
 

 CS = AS/VS 

 CF = AF/VF 

 BODY = AL + AR + AS + AF + AB + TUMMY 

 BURDEN = AM + BODY 

 TMASS = BURDEN + AX + AMEX 

!Calculate the Interval Excretion Data here:' 

 ! DAX = AMEX-AMEX2 

 ! IF(DOSE .LE. 0.0 .AND. IV .LE. 0.0 ) GO TO SKIP1 

 ! PCTAX = 100*(AX - AX2)/(DOSE + IV*BW) 

 ! PCTMX = 100*(AMEX - AMEX2)/(DOSE + IV*BW) 

! SKIP1.. CONTINUE 

 ! IF(T .LT. TDATA(I) .OR. I .GE. 20 ) GO TO SKIP 

 ! AX2=AX 

! AMEX2=AMEX 

! I=I+1 

! SKIP.. CONTINUE 

!DISCRETE EXPOSE 

! CIZONE = 1.0 ! CALL LOGD(.TRUE.) Turns on inhalation exposure? 

!END 

!DISCRETE CLEAR 

! CIZONE = 0.0 ! CALL LOGD(.TRUE.) 

!END 

DERIVATIVE 

!Use Zero-Crossing Form of DISCRETE Function Here' 

! SCHEDULE command must be in DERIVATIVE section' 

 ! DAILY = PULSE (0.0, PER1, TCHNG ) 

 ! WEEKLY = PULSE (0.0, PER2, LEN2 ) 

 ! SWITCHY = DAILY * WEEKLY 

!SCHEDULE EXPOSE .XP. SWITCHY - 0.995 

!SCHEDULE CLEAR .XN. SWITCHY - 0.005 

DAILY=PULSE(0.0,PERD,WIDD) 

WEEKLY=PULSE(0.0,PERW,WIDW) 

SWITCHY = DAILY * WEEKLY 

!**********************Modified Here for Wong*****************' 

 CI = CONC * MW / 24451.0 * SWITCHY!** 

 !CA = Concentration in arterial blood (mg/l)' 

 CA = (QC*CV+QP*CI)/(QC+(QP/PB)) 

 CX = CA/PB 

 DRINK=DRINKA*SWITCHY !** 

 !TUMMY = Amount in stomach' 

 B-31 
 

 RTUMMY = -KA*TUMMY 

 TUMMY = INTEG(RTUMMY,DOSE) 

 !RAX = Rate of Elimination in Exhaled air' 

 RAX = QP*CX 

 AX = INTEG(RAX, 0.0) 

 !AS = Amount in slowly perfused tissues (mg)' 

 RAS = SPDC*(CA-CVS) !now governed by diffusion-limited constant, SPDC, instead of QS 

 AS = INTEG(RAS,0.) 

 CVS = AS/(VS*PS) 

 !AR = Amount in rapidly perfused tissues (mg)' 

 RAR = QR*(CA-CVR) 

 AR = INTEG(RAR,0.) 

 CVR = AR/(VR*PR) 

 !AF = Amount in fat tissue (mg)' 

 RAF = QF*(CA-CVF) 

 AF = INTEG(RAF,0.) 

 CVF = AF/(VF*PF) 

 !AL = Amount in liver tissue (mg)' 

 RAL = QL*(CA-CVL) - KL*CVL - VMAX*CVL/(KM+CVL) + KA*TUMMY + DRINK 

 AL = INTEG(RAL,0.) 

 CVL = AL/(VL*PL) 

!Metabolism comments updated by EDM on 2/1/10 

 !AM = Amount metabolized (mg)' 

 RMEX = (KL*CVL)+(VMAX*CVL/(KM+CVL)) !Rate of 1,4-dioxane metabolism 

 RAM = (KL*CVL)+(VMAX*CVL)/(KM+CVL) - KME*AM !Rate of change of metabolite 

in body 

 AM = INTEG(RAM, 0.0) !'Amt Metabolite in body 

 CAM = AM/BW !'Conc Metabolite in body' 

 AMEX = INTEG(KME*AM, 0.0) !'Amt Metabolite Excreted via urine' 

 !AB = Amount in Venous Blood' 

 RAB = QF*CVF + QL*CVL + QS*CVS + QR*CVR - QC*CV 

 AB = INTEG(RAB, AB0) 

 CV = AB/VB 

 AUCV = INTEG(CV, 0.0) 

!Possible Dose Surrogates for Risk Assessment Defined Here' 

 CEX = 0.667*CX + 0.333*CI !'Conc in Exhal Air' 

 AVECON = PLA * (CEX+CI)/2 !'Ave Conc in Nose Tissue' 

 AUCCON = INTEG(AVECON, 0.0) !'Area under Curve (Nose)' 

 AUCMET = INTEG(CAM, 0.0) !'Area under Curve (Metab)' 

 B-32 
 

 CL = AL/VL !'Conc Liver Tissue' 

 AUCL = INTEG(CL, 0.0) !'Area under Curve (Liver)' 

 AAUCL=AUCL/TIME 

! Dose Surrogates are Average Area under Time/Conc Curve per 24 hrs' 

IF (T .GT. 0) TIME=T 

 dayS = TIME/24.0 

 NOSE = AUCCON/DAYS !'Nasal Turbinates' 

 LIVER = AUCL/DAYS !'Liver Tissues' 

 METAB = AUCMET/DAYS !'Stable Metabolite' 

END !'End of dynamic' 

END ! End of TERMINAL 

END !'End of PROGRAM

 B-33 
 

APPENDIX C. DETAILS OF BMD ANALYSIS FOR ORAL RfD FOR 1,4-DIOXANE 

C.1. CORTICAL TUBULE DEGENERATION 

All available dichotomous models in the Benchmark Dose Software (version 2.1.1) were 

fit to the incidence data shown in Table C-1, for cortical tubule degeneration in male and female 

Osborne-Mendel rats exposed to 1,4-dioxane in the drinking water (NCI, 1978, 062935). Doses 

associated with a BMR of a 10% extra risk were calculated. 

Table C-1. Incidence of cortical tubule degeneration in Osborne-Mendel rats 

exposed to 1,4-dioxane in drinking water for 2 years 

Males (mg/kg-day) Females (mg/kg-day) 

0 240 530 0 350 640 

0/31a 20/31b

(65%) 

27/33b

(82%) 

0/31a 0/34 10/32b

(31%) 

a

Statistically significant trend for increased incidence by Cochran-Armitage test (p < 0.05) performed for this 

review. 

b

Incidence significantly elevated compared to control by Fisher’s exact test (p < 0.05) performed for this review. 

Source: NCI (1978, 062935). 

As assessed by the χ

2

 goodness-of-fit test, several models in the software provided 

adequate fits to the data for the incidence of cortical tubule degeneration in male and female rats 

(χ

2

p ≥ 0.1) (Table C-2). Comparing across models, a better fit is indicated by a lower AIC 

value (U.S. EPA, 2000, 052150). As assessed by Akaike’s Information Criterion (AIC), the logprobit model provided the best fit to the cortical tubule degeneration incidence data for male rats 

(Table C-2, Figure C-1) and could be used to derive a POD of 38.5 mg/kd-ay for this endpoint. 

The Weibull model provided the best fit to the data for female rats (Table C-2, Figure C-5) and 

could be used to derive a POD of 452.4 mg/kg-day for this endpoint. For those models that 

exhibit adequate fit, models with the lower AIC values are preferred. Differences in AIC values 

of less than 1 are generally not considered important. BMDS modeling results for all 

dichotomous models are shown in Table C-2. 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS)

 C-1 
 

Table C-2. Goodness-of-fit statistics and BMD10 and BMDL10 values from 

models fit to incidence data for cortical tubule degeneration in male and 

female Osborne-Mendel rats (NCI, 1978, 062935) exposed to 1,4-dioxane in 

drinking water 

Model AIC p-valuea

Scaled 

Residual of 

Interest 

BMD10

(mg/kg-day) 

BMDL10

(mg/kg-day) 

Male

Gammab 74.458 0.6514 0 28.80 22.27

Logistic 89.0147 0.0011 -1.902 88.48 65.84

Log-logisticc 75.6174 1 0 20.85 8.59

Log-probitc 74.168 0.7532 0 51.41 38.53 

Multistage 

(2 degree)d 74.458 0.6514 0 28.80 22.27

Probit 88.782 0.0011 -1.784 87.10 66.32

Weibullb 74.458 0.6514 0 28.80 22.27

Quantal-Linear 74.458 0.6514 0 28.80 22.27

Female

Gammab 41.9712 0.945 0.064 524.73 437.08

Logistic 43.7495 0.9996 0 617.44 471.92

Log-logisticc 41.7501 0.9999 0 591.82 447.21

Log-probitc 43.7495 0.9997 0 584.22 436.19

Multistage 

(2 degree)d 48.1969 0.1443 -1.693 399.29 297.86

Probit 43.7495 0.9997 0 596.02 456.42

Weibullb 41.75 0.9999 0 596.45 452.36

Quantal-Linear 52.3035 0.03 -2.086 306.21 189.49

a

 p-Value from the χ

2

 goodness-of-fit test for the selected model. Values < 0.1 indicate that the model 

exhibited a statistically significant lack of fit, and thus a different model should be chosen. 

b

Power restricted to ≥ 1. c

Slope restricted to ≥ 1. d

Betas restricted to ≥0. 

Source: NCI (1978, 062935). 

 C-2 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 100 200 300 400 500

Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

14:49 02/01 2010

BMDL BMD

 

LogProbit

Source: NCI (1978, 062935). 

Figure C-1. BMD Log-probit model of cortical tubule degeneration 

incidence data for male rats exposed to 1,4-dioxane in drinking water for 2 

years to support the results in Table C-2. 

==================================================================== 

Probit Model. (Version: 3.1; Date: 05/16/2008) 

Input Data File: C:\14DBMDS\lnp_nci_mrat_cortdeg_Lnp-BMR10-restrict.(d) 

Gnuplot Plotting File: C:\14DBMDS\lnp_nci_mrat_cortdeg_Lnp-BMR10-restrict.plt 

 Mon Feb 01 14:49:17 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

 P[response] = Background + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Effect 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 C-3 
 

 User has chosen the log transformed model 

 Default Initial (and Specified) Parameter Values 

 background = 0 

 intercept = -5.14038 

 slope = 1 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -background -slope have been estimated at a boundary 

point, or have been specified by the user, and do not appear in the correlation 

matrix) 

 intercept 

 intercept 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0 NA 

 intercept -5.22131 0.172682 -5.55976 -4.88286 

 slope 1 NA 

NA - Indicates that this parameter has hit a bound implied by some inequality 

constraint and thus has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -35.8087 3 

 Fitted model -36.084 1 0.550629 2 0.7593 

 Reduced model -65.8437 1 60.07 2 <.0001 

 AIC: 74.168 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 31 0.000 

 240.0000 0.6023 18.672 20.000 31 0.487 

 530.0000 0.8535 28.166 27.000 33 -0.574 

 Chi^2 = 0.57 d.f. = 2 P-value = 0.7532 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 51.4062 

 BMDL = 38.5284 

 C-4 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600

Fraction Affected

dose

Weibull Model with 0.95 Confidence Level

14:20 12/04 2009

BMDL BMD

 

Weibull

Source: NCI (1978, 062935). 

Figure C-2. BMD Weibull model of cortical tubule degeneration incidence 

data for female rats exposed to 1,4-dioxane in drinking water for 2 years to 

support the results in Table C-2. 

==================================================================== 

Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

Input Data File: Z:\14Dioxane\BMDS\wei_nci_frat_cortdeg_Wei-BMR10-Restrict.(d) 

Gnuplot Plotting File: Z:\14Dioxane\BMDS\wei_nci_frat_cortdeg_Wei-BMR10-Restrict.plt 

 Fri Dec 04 14:20:41 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Power parameter is restricted as power >=1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 

 C-5 
 

 Default Initial (and Specified) Parameter Values 

 Background = 0.015625 

 Slope = 1.55776e-010 

 Power = 3.33993 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background -Power have been estimated at a boundary 

point, or have been specified by the user, and do not appear in the correlation 

matrix) 

 Slope 

 Slope -1.$ 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 NA 

 Slope 1.15454e-051 1.#QNAN 1.#QNAN 1.#QNAN 

 Power 18 NA 

NA - Indicates that this parameter has hit a bound implied by some inequality 

constraint and thus has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -19.8748 3 

 Fitted model -19.875 1 0.000487728 2 0.9998 

 Reduced model -32.1871 1 24.6247 2 <.0001 

 AIC: 41.75 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 31 0.000 

 350.0000 0.0000 0.000 0.000 34 -0.016 

 640.0000 0.3125 9.999 10.000 32 0.000 

 Chi^2 = 0.00 d.f. = 2 P-value = 0.9999 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 596.445 

 BMDL = 452.359 

 C-6 
 

C.2. LIVER HYPERPLASIA 

All available dichotomous models in the Benchmark Dose Software (version 2.1.1) were 

fit to the incidence data shown in Table C-3, for liver hyperplasia in male and female 

F344/DuCrj rats exposed to 1,4-dioxane in the drinking water (JBRC, 1998, 196240; Kano et al., 

2009, 594539). Benchmark doses associated with a BMR of a 10% extra risk were calculated. 

Table C-3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to 

1,4-dioxane in drinking watera 

Males (mg/kg-day) Females (mg/kg-day) 

0 11 55 274 0 18 83 429 

3/40 2/45 9/35a 12/22c 2/38b 2/37 9/38 24/24c

a

Dose information from Kano et al. (2009, 594539) and incidence data from sacrificed animals from JBRC (1998, 

196240). b

Incidence significantly elevated compared to control by χ

2

 test (p < 0.05). c

Incidence significantly elevated compared to control by χ

2

 test (p < 0.01). 

Sources: Kano et al. (2009, 594539); JBRC (1998, 196240). 

For incidence of liver hyperplasia in F344 male rats, the logistic, probit, and 

dichotomous-Hill models all exhibited a statistically significant lack of fit (i.e., χ2

p-value < 0.1; 

see Table C-4), and thus should not be considered further for identification of a POD. All of the 

remaining models exhibited adequate fit, but the AIC values for the gamma, multistage, quantallinear, and Weibull models were lower than the AIC values for the log-logistic and log-probit 

models. Finally, the AIC values for gamma, multistage, quantal-linear, and Weibull models in 

Table C-4 are equivalent and, in this case, essentially represent the same model. Therefore, 

consistent with the external review draft Benchmark Dose Technical Guidance (U.S. EPA, 2000, 

052150), any of them with equal AIC values (gamma, multistage, quantal-linear, or Weibull) 

could be used to identify a POD for this endpoint of 23.8 mg/kg-day. 

For liver hyperplasias in F344 female rats exposed to 1,4-dioxane, the quantal-linear and 

dichotomous-Hill models did not result in a good fit (i.e., χ2

p-value < 0.1; See Table C-4). The 

multistage (3-degree) model had the lowest AIC value and was selected as the best-fitting model. 

Therefore, consistent with the BMD technical guidance document (U.S. EPA, 2000, 052150), the 

BMDL from the multistage (3-degree) model was selected to yield a POD for this endpoint of 

27.1 mg/kg-day. 

 C-7 
 

Table C-4. Benchmark dose modeling results based on the incidence of liver 

hyperplasias in male and female F344 rats exposed to 1,4-dioxane in drinking 

water for 2 years 

Model AIC p-valuea

Scaled 

Residual of 

Interest 

BMD10

(mg/kg-day) 

BMDL10

(mg/kg-day) 

Male

Gammab 114.172 0.3421 0.886 35.90 23.81 

Logistic 117.047 0.0706 1.869 83.56 63.29 

Log-logisticc 115.772 0.1848 0.681 33.39 16.96 

Log-probitc 115.57 0.1431 1.472 54.91 37.05 

Multistaged

(2 degree) 114.172 0.3421 0.886 35.90 23.81 

Probit 116.668 0.0859 1.804 76.69 58.57 

Weibullb 114.172 0.3421 0.886 35.90 23.81 

Quantal-Linear 114.172 0.3421 0.886 35.90 23.81 

Dichotomous-Hill 117.185 NCe -0.2398 32.01 14.84 

Female

Gammab 78.8357 0.9783 0 70.78 40.51 

Logistic 77.0274 0.9174 -0.016 54.66 41.11 

Log-logisticc 78.8357 0.9781 0 77.72 51.21 

Log-probitc 78.8357 0.9781 0 74.64 50.97 

Multistaged

(2 degree) 76.9718 0.9563 -0.107 56.06 31.17 

Multistaged

(3 degree) 76.8351 0.9999 0 65.28 27.08 

Probit 77.0308 0.9095 0.017 52.53 38.44 

Weibullb 78.8349 0.9995 0 66.47 36.14 

Quantal-Linear 87.3833 0.0245 -1.116 21.52 15.61 

Dichotomous-Hill 2972.99 NCe 0 NCe NCe

a

p-Value from the χ

2

 goodness-of-fit test for the selected model. Values < 0.1 indicate that the model 

exhibited a statistically significant lack of fit, and thus a different model should be chosen. 

b

Power restricted to ≥ 1. c

Slope restricted to ≥ 1. d

Betas restricted to ≥0. e

NC=Not calculated. 

Sources: Kano et al. (2009, 594539); JBRC (1998, 196240). 

 C-8 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Gamma Multi-Hit

Figure C-3. BMD gamma model of liver hyperplasia incidence data for F344 

male rats exposed to 1,4-dioxane in drinking water for 2 years to support 

results Table C-4. 

==================================================================== 

Gamma Model. (Version: 2.13; Date: 05/16/2008) 

Input Data File: Z:\14Dioxane\BMDS\gam_jbrc1998_mrat_liver_hyper_Gam-BMR10-

Restrict.(d) 

Gnuplot Plotting File: Z:\14Dioxane\BMDS\gam_jbrc1998_mrat_liver_hyper_Gam-BMR10-

Restrict.plt 

 Fri Dec 04 14:35:02 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Effect 

 Independent variable = Dose 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 C-9 
 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0853659 

 Slope = 0.00479329 

 Power = 1.3 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Power have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.36 

 Slope -0.36 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0569658 0.0278487 0.00238329 0.111548 

 Slope 0.00293446 0.000814441 0.00133818 0.00453073 

 Power 1 NA 

NA - Indicates that this parameter has hit a bound implied by some inequality 

constraint and thus has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -53.9471 4 

 Fitted model -55.0858 2 2.27725 2 0.3203 

 Reduced model -67.6005 1 27.3066 3 <.0001 

 AIC: 114.172 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0570 2.279 3.000 40 0.492 

 11.0000 0.0869 3.911 2.000 45 -1.011 

 55.0000 0.1975 6.913 9.000 35 0.886 

 274.0000 0.5780 12.715 12.000 22 -0.309 

 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 35.9046 

 BMDL = 23.8065

 C-10 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Multistage

Figure C-4. BMD multistage (2 degree) model of liver hyperplasia incidence 

data for F344 male rats exposed to 1,4-dioxane in drinking water for 2 years 

to support results Table C-4. 

==================================================================== 

Multistage Model. (Version: 3.0; Date: 05/16/2008) 

Input Data File: Z:\14Dioxane\BMDS\mst_jbrc1998_mrat_liver_hyper_Mst-BMR10-

restrict.(d) 

Gnuplot Plotting File: Z:\14Dioxane\BMDS\mst_jbrc1998_mrat_liver_hyper_Mst-BMR10-

Restrict.plt 

 Fri Dec 04 14:35:06 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Effect 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 C-11 
 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0750872 

 Beta(1) = 0.00263797 

 Beta(2) = 0 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Beta(2) have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix) 

 Background Beta(1) 

Background 1 -0.49 

 Beta(1) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0569658 * * * 

 Beta(1) 0.00293446 * * * 

 Beta(2) 0 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -53.9471 4 

 Fitted model -55.0858 2 2.27725 2 0.3203 

 Reduced model -67.6005 1 27.3066 3 <.0001 

 AIC: 114.172 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0570 2.279 3.000 40 0.492 

 11.0000 0.0869 3.911 2.000 45 -1.011 

 55.0000 0.1975 6.913 9.000 35 0.886 

 274.0000 0.5780 12.715 12.000 22 -0.309 

 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 35.9046 

 BMDL = 23.8065 

 BMDU = 82.1206 

Taken together, (23.8065, 82.1206) is a 90% two-sided confidence interval for the BMD 

 C-12 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250

Fraction Affected

dose

Weibull Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Weibull

Figure C-5. BMD Weibull model of liver hyperplasia incidence data for F344 

male rats exposed to 1,4-dioxane in drinking water for 2 years to support the 

results in Table C-4. 

==================================================================== 

Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

Input Data File: Z:\14Dioxane\BMDS\wei_jbrc1998_mrat_liver_hyper_Wei-BMR10-

Restrict.(d) 

Gnuplot Plotting File: Z:\14Dioxane\BMDS\wei_jbrc1998_mrat_liver_hyper_Wei-BMR10-

Restrict.plt 

 Fri Dec 04 14:35:08 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 C-13 
 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0853659 

 Slope = 0.00253609 

 Power = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

(** The model parameter(s) -Power have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.36 

 Slope -0.36 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0569661 0.0278498 0.00238155 0.111551 

 Slope 0.00293445 0.000814445 0.00133816 0.00453073 

 Power 1 NA 

NA - Indicates that this parameter has hit a bound implied by some inequality 

constraint and thus has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -53.9471 4 

 Fitted model -55.0858 2 2.27725 2 0.3203 

 Reduced model -67.6005 1 27.3066 3 <.0001 

 AIC: 114.172 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0570 2.279 3.000 40 0.492 

 11.0000 0.0869 3.911 2.000 45 -1.011 

 55.0000 0.1975 6.913 9.000 35 0.886 

 274.0000 0.5780 12.715 12.000 22 -0.309 

 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 35.9047 

 BMDL = 23.8065

 C-14 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250

Fraction Affected

dose

Quantal Linear Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Quantal Linear

Figure C-6. BMD quantal-linear model of liver hyperplasia incidence data 

for F344 male rats exposed to 1,4-dioxane in drinking water for 2 years to 

support the results in Table C-4. 

==================================================================== 

Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

Input Data File: Z:\14Dioxane\BMDS\qln_jbrc1998_mrat_liver_hyper_Qln-BMR10.(d) 

Gnuplot Plotting File: Z:\14Dioxane\BMDS\qln_jbrc1998_mrat_liver_hyper_Qln-BMR10.plt 

 Fri Dec 04 14:35:09 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose)] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0853659 

 Slope = 0.00253609 

 Power = 1 Specified 

 C-15 
 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Power have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix) 

 Background Slope 

Background 1 -0.36 

 Slope -0.36 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0569665 0.02785 0.00238157 0.111551 

 Slope 0.00293447 0.000814452 0.00133818 0.00453077 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -53.9471 4 

 Fitted model -55.0858 2 2.27725 2 0.3203 

 Reduced model -67.6005 1 27.3066 3 <.0001 

 AIC: 114.172 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0570 2.279 3.000 40 0.492 

 11.0000 0.0869 3.911 2.000 45 -1.011 

 55.0000 0.1975 6.913 9.000 35 0.886 

 274.0000 0.5780 12.716 12.000 22 -0.309 

 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 35.9044 

 BMDL = 23.8065 

 C-16 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 50 100 150 200 250 300 350 400 450

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:30 05/21 2010

BMDL BMD

 

Multistage

Source: JBRC (1998, 196240). 

Figure C-7. BMD log-probit model of liver hyperplasia incidence data for 

F344 female rats exposed to 1,4-dioxane in drinking water for 2 years to 

support the results in Table C-4. 

==================================================================== 

Multistage Model. (Version: 3.0; Date: 05/16/2008) 

Input Data File: H:\14Dioxane\BMDS\mst_jbrc1998_frat_liver_hyper_Mst-BMR10-Restrict3deg.(d) 

Gnuplot Plotting File: H:\14Dioxane\BMDS\mst_jbrc1998_frat_liver_hyper_Mst-BMR10-

Restrict-3deg.plt 

 Fri May 21 10:30:14 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2-

beta3*dose^3)] 

The parameter betas are restricted to be positive 

 Dependent variable = Effect 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 4 

 Total number of specified parameters = 0 

 C-17 
 

 Degree of polynomial = 3 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0 

 Beta(2) = 0 

 Beta(3) = 1.2696e+012 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Beta(1), -Beta(2) have been estimated at a boundary 

point, or have been specified by the user, and do not appear in the correlation 

matrix) 

 Background Beta(3) 

Background 1 -0.55 

 Beta(3) -0.55 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0523101 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0 * * * 

 Beta(3) 3.78712e-007 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -36.4175 4 

 Fitted model -36.4175 2 0.00016582 2 0.9999 

 Reduced model -79.9164 1 86.9979 3 <.0001 

 AIC: 76.8351 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0523 1.988 2.000 38 0.009 

 18.0000 0.0544 2.013 2.000 37 -0.009 

 83.0000 0.2368 8.999 9.000 38 0.000 

 429.0000 1.0000 24.000 24.000 24 0.000 

 Chi^2 = 0.00 d.f. = 2 P-value = 0.9999 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 65.2814 

 BMDL = 27.0766 

 BMDU = 91.3457 

Taken together, (27.0766, 91.3457) is a 90% two-sided confidence interval for the BMD 

 C-18 
 

APPENDIX D. DETAILS OF BMD ANALYSIS FOR ORAL CSF FOR 1,4-DIOXANE 

Dichotomous models available in the Benchmark Dose Software (BMDS) (version 2.1.1) 

were fit to the incidence data for hepatocellular carcinoma and/or adenoma for mice and rats, as 

well as nasal cavity tumors, peritoneal mesotheliomas, and mammary gland adenomas in rats 

exposed to 1,4-dioxane in the drinking water. Doses associated with a benchmark response 

(BMR) of a 10% extra risk were calculated. BMD10 and BMDL10 values from the best fitting 

model, determined by adequate global- fit (χ

2 

p ≥ 0.1) and AIC values, are reported for each 

endpoint (U.S. EPA, 2000, 052150). If the multistage cancer model is not the best fitting model 

for a particular endpoint, the best-fitting multistage cancer model for that endpoint is also 

presented as a point of comparison. 

A summary of the model predictions for the Kano et al. (2009, 594539) study are shown 

in Table D-1. The data and BMD modeling results are presented separately for each dataset as 

follows: 

• Hepatic adenomas and carcinomas in female F344 rats (Tables D-2 and D-3; Figure D-1) 

• Hepatic adenomas and carcinomas in male F344 rats (Tables D-4 and D-5; Figures D-2 

and D-3) 

• Significant tumor incidence data at sites other than the liver (i.e., nasal cavity, mammary 

gland, and peritoneal) in male and female F344 rats (Table D-6) 

o Nasal cavity tumors in female F344 rats (Table D-7; Figure D-4) 

o Nasal cavity tumors in male F344 rats (Table D-8; Figure D-5) 

o Mammary gland adenomas in female F344 rats (Table D-9; Figures D-6 and D-7) 

o Peritoneal mesotheliomas in male F344 rats (Table D-10; Figures D-8 and D-9) 

• Hepatic adenomas and carcinomas in female BDF1 mice (Tables D-11, D-12, and D-13; 

Figures D-10, D-11, D-12, and D-13) 

• Hepatic adenomas and carcinomas in male BDF1 mice (Tables D-14 and D-15; Figures 

D-14 and D-15) 

Data and BMD modeling results from the additional chronic bioassays (Kociba et al., 1974, 

062929; NCI, 1978, 062935) were evaluated for comparison with the data from Kano et al. 

(2009, 594539). These results are presented as follows: 

• Summary of BMDS dose-response modeling estimates associated with liver and nasal 

tumor incidence data resulting from chronic oral exposure to 1,4-dioxane in rats and mice 

(Table D-16) 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS)

 D-1 
 

• Incidence of hepatocellular carcinoma and nasal squamous cell carcinoma in male and 

female Sherman rats (combined) (Kociba et al., 1974, 062929) treated with 1,4-dioxane 

in the drinking water for 2 years (Table D-17) 

o BMDS dose-response modeling results for incidence of hepatocellular carcinoma in 

male and female Sherman rats (combined) (Kociba et al., 1974, 062929) exposed to 

1,4-dioxane in drinking water for 2 years (Table D-18; Figures D-16 and D-17) 

o BMDS dose-response modeling results for incidence of nasal squamous cell 

carcinoma in male and female Sherman rats (combined) (Kociba et al., 1974, 062929) 

exposed to 1,4-dioxane in the drinking water for 2 years (Table D-19; Figure D-18) 

• Incidence of nasal cavity squamous cell carcinoma and hepatocellular adenoma in 

Osborne-Mendel rats (NCI, 1978, 062935) exposed to 1,4-dioxane in the drinking water 

(Table D-20) 

o BMDS dose-response modeling results for incidence of hepatocellular adenoma in 

female Osborne-Mendel rats (NCI, 1978, 062935) exposed to 1,4-dioxane in the 

drinking water for 2 years (Table D-21; Figures D-19 and D-20) 

o BMDS dose-response modeling results for incidence of nasal cavity squamous cell 

carcinoma in female Osborne-Mendel rats (NCI, 1978, 062935) exposed to 

1,4-dioxane in the drinking water for 2 years (Table D-22; Figures D-21 and D-22) 

o BMDS dose-response modeling results for incidence of nasal cavity squamous cell 

carcinoma in male Osborne-Mendel rats (NCI, 1978, 062935) exposed to 1,4-dioxane 

in the drinking water for 2 years (Table D-23; Figures D-23 and D-24) 

• Incidence of hepatocellular adenoma or carcinoma in male and female B6C3F1 mice 

(NCI, 1978, 062935) exposed to 1,4-dioxane in drinking water (Table D-24) 

o BMDS dose-response modeling results for the combined incidence of hepatocellular 

adenoma or carcinoma in female B6C3F1 mice (NCI, 1978, 062935) exposed to 

1,4-dioxane in the drinking water for 2 years (Table D-25; Figure D-25) 

o BMDS dose-response modeling results for incidence of combined hepatocellular 

adenoma or carcinoma in male B6C3F1 mice (NCI, 1978, 062935) exposed to 

1,4-dioxane in the drinking water for 2 years (Table D-26; Figures D-26 and D-27). 

D.1. GENERAL ISSUES AND APPROACHES TO BMDS MODELING 

D.1.1. Combining Data on Adenomas and Carcinomas 

The incidence of adenomas and the incidence of carcinomas within a dose group at a site 

or tissue in rodents are sometimes combined. This practice is based upon the hypothesis that 

adenomas are a severe endpoint by themselves and most would have developed into carcinomas 

if exposure at the same dose was continued (U.S. EPA, 2005, 086237). The incidence at high 

doses of both tumors in rat and mouse liver is high in the key study (Kano et al., 2009, 594539). 

 D-2 
 

The incidence of hepatic adenomas and carcinomas was summed without double-counting them 

so as to calculate the combined incidence of either a hepatic carcinoma or a hepatic adenoma in 

rodents. 

The variable N is used to denote the total number of animals tested in the dose group. 

The variable Y is used here to denote the number of rodents within a dose group that have 

characteristic X, and the notation Y(X) is used to identify the number with a specific 

characteristic X. Modeling was performed on the adenomas and carcinomas separately and the 

following combinations of tumor types: 

• Y(adenomas) = number of animals with adenomas, whether or not carcinomas are 

present; 

• Y(carcinomas) = number of animals with carcinomas, whether or not adenomas are also 

present; 

• Y(either adenomas or carcinomas) = number of animals with adenomas or carcinomas, 

not both = Y(adenomas) + Y(carcinomas) – Y(both adenomas and carcinomas); 

• Y(neither adenomas nor carcinomas) = number of animals with no adenomas and no 

carcinomas = N - Y(either adenomas or carcinomas). 

D.1.2. Model Selection Criteria 

Multiple models were fit to each dataset. The model selection criteria used in the BMD 

technical guidance document (U.S. EPA, 2000, 052150) were applied as follows: 

• p-value for goodness-of-fit > 0.10 

• AIC smaller than other acceptable models 

• χ

2

 residuals as small as possible 

• No systematic patterns of deviation of model from data 

Additional criteria were applied to eliminate implausible dose-response functions: 

• Monotonic dose-response functions, e.g. no negative coefficients of polynomials in MS 

models 

• No infinitely steep dose-response functions near 0 (control dose), achieved by requiring 

the estimated parameters “power” in the Weibull and Gamma models and “slope” in the 

log-logistic model to have values ≥ 1. 

Because no single set of criteria covers all contingencies, an extended list of preferred models are 

presented below in Table D-1. 

D.1.3. Summary 

The BMDS models recommended to calculate rodent BMD and BMDL values and 

corresponding human BMDHED and BMDLHED values are summarized in Table D-1. 

 D-3 
 

Table D-1. Recommended models for rodents exposed to 1,4-dioxane in 

drinking water (Kano et al., 2009, 594539) 

Endpoint

Model 

selection 

criterion Model Type AIC p-value

BMDa

mg/kgday

BMDLa

mg/kgday

BMDHED

a

mg/kgday

BMDLHE

D

a

mg/kgday

Female F344 Rat 

Hepatic 

Tumors 

Lowest 

AIC 

Multistage 

(2 degree) 

91.5898 0.4516 79.83 58.09 19.84 14.43 

Mammary 

Gland 

Tumors 

Lowest 

AIC 

LogLogistic 194.151 0.8874 161.01 81.91 40.01 20.35 

Nasal 

Cavity 

Tumors 

Lowest 

AIC 

Multistage 

(3 degree) 

42.6063 0.9966 381.65 282.61 94.84 70.23 

Male R344 Rat 

Hepatic 

Tumors 

Lowest 

AIC 

Probit 147.787 0.9867 62.20 51.12 17.43 14.33 

Peritoneal 

Mesothelioma 

Lowest 

AIC 

Probit 138.869 0.9148 93.06 76.32 26.09 21.39 

Nasal 

Cavity 

Tumors 

Lowest 

AIC 

Multistage 

(3 degree) 

24.747 0.9989 328.11 245.63 91.97 68.85 

Female BDF1 Mouse 

Lowest 

AIC 

Hepatic LogLogistic 176.214 0.1421 5.54 3.66 0.83 0.55 

Tumors 

BMR 50% LogLogistic 176.214 0.1421 49.88b 32.93b 7.51b 4.95b

Male BDF1 Mouse 

Hepatic 

Tumors 

Lowest 

AIC 

LogLogistic 248.839 0.3461 34.78 16.60 5.63 2.68 

a

Values for BMR 10% unless otherwise noted. 

b

BMR 50%. 

D.2. FEMALE F344 RATS: HEPATIC CARCINOMAS AND ADENOMAS 

The incidence data for hepatic carcinomas and adenomas in female F344 rats (Kano et 

al., 2009, 594539) are shown in Table D-2. 

 D-4 
 

Table D-2. Data for hepatic adenomas and carcinomas in female F344 rats 

(Kano et al., 2009, 594539) 

Dose (mg/kg-day)

Tumor type 0 18 83 429

Hepatocellular adenomas 3 1 6 48

Hepatocellular carcinomas 0 0 0 10

Either adenomas or carcinomas 3 1 6 48

Neither adenomas nor carcinomas 47 49 44 2

Total number per group 50 50 50 50

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539).

Note that the incidence of rats with adenomas, with carcinomas, and with either 

adenomas or carcinomas are monotone non-decreasing functions of dose except for 3 female rats 

in the control group. These data therefore appear to be appropriate for dose-response modeling 

using BMDS. 

The results of the BMDS modeling for the entire suite of models are presented in 

Table D-3. 

Table D-3. BMDS dose-response modeling results for the combined 

incidence of hepatic adenomas and carcinomas in female F344 rats (Kano et 

al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 93.1067 0.3024 89.46 62.09 0.027 22.23 15.43 

Logistic 91.7017 0.4459 93.02 71.60 0.077 23.12 17.79 

LogLogistic 93.102 0.3028 88.34 65.52 0.016 21.95 16.28 

LogProbitb 93.0762 0.3074 87.57 66.19 0.001 21.76 16.45 

Multistage-Cancer 

(1 degree) 114.094 0.0001 25.58 19.92 -1.827 6.36 4.95 

Multistage-Cancer 

(2 degree)c 91.5898 0.4516 79.83 58.09 -0.408 19.84 14.43 

Multistage-Cancer 

(3 degree) 93.2682 0.2747 92.81 59.31 0.077 23.06 14.74 

Probit 91.8786 0.3839 85.46 67.84 -0.116 21.24 16.86 

Weibull 93.2255 0.2825 92.67 59.89 0.088 23.03 14.88 

Quantal-Linear 114.094 0.0001 25.58 19.92 -1.827 6.36 4.95 

Dichotomous-Hill 4458.37 NCd NCd NCd 0 0 0 

a

Maximum absolute χ

2

 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Slope restricted ≥ 1. c

Best-fitting model. 

d

Value unable to be calculated (NC: not calculated) by BMDS. 

 D-5 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 50 100 150 200 250 300 350 400 450

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:20 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permisison of Elservier, Ltd., Kano et al. (2009, 594539). 

Figure D-1. Multistage BMD model (2 degree) for the combined incidence of 

hepatic adenomas and carcinomas in female F344 rats. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_hepato_adcar_MscBMR10-2poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_hepato_adcar_Msc-BMR10-2poly.plt 

Mon Oct 26 08:20:52 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 3 

Total number of specified parameters = 0 

Degree of polynomial = 2 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

Background = 0.0281572 

 D-6 
 

Beta(1) = 0 

Beta(2) = 1.73306e-005 

Asymptotic Correlation Matrix of Parameter Estimates (*** The model parameter(s) -

Beta(1)have been estimated at a boundary point, or have been specified by the user, 

and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.2 

Beta(2) -0.2 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0362773 * * * 

Beta(1) 0 * * * 

Beta(2) 1.65328e-005 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -42.9938 4 

 Fitted model -43.7949 2 1.60218 2 0.4488 

 Reduced model -120.43 1 154.873 3 <.0001 

 AIC: 91.5898 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0363 1.814 3.000 50 0.897 

 18.0000 0.0414 2.071 1.000 50 -0.760 

 83.0000 0.1400 7.001 6.000 50 -0.408 

 429.0000 0.9540 47.701 48.000 50 0.202 

Chi^2 = 1.59 d.f. = 2 P-value = 0.4516 

Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 79.8299 

 BMDL = 58.085 

 BMDU = 94.0205 

Taken together, (58.085 , 94.0205) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00172161

 D-7 
 

D.3. MALE F344 RATS: HEPATIC CARCINOMAS AND ADENOMAS 

The data for hepatic adenomas and carcinomas in male F344 rats (Kano et al., 2009, 

594539) are shown in Table D-4. 

Table D-4. Data for hepatic adenomas and carcinomas in male F344 rats 

(Kano et al., 2009, 594539) 

Dose (mg/kg-day) Tumor type 

0 11 55 274 

Hepatocellular adenomas 3 4 7 32 

Hepatocellular carcinomas 0 0 0 14 

Either adenomas or carcinomas 3 4 7 39 

Neither adenomas nor carcinomas 47 46 43 11 

Total number per group 50 50 50 50 

Source: Used with permission from Elservier, Ltd., Kano et al. (2009, 594539). 

Note that the incidence of rats with hepatic adenomas, carcinomas, and with either 

adenomas or carcinomas are monotone non-decreasing functions of dose. These data therefore 

appear to be appropriate for dose-response modeling using BMDS. 

The results of the BMDS modeling for the entire suite of models tested using the data for 

hepatic adenomas and carcinomas for male F344 rats are presented in Table D-5. 

 D-8 
 

Table D-5. BMDS dose-response modeling results for the combined 

incidence of adenomas and carcinomas in livers of male F344 rats (Kano et 

al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 149.884 0.7257 62.41 30.79 -0.03 17.49 8.63 

Logistic 147.813 0.9749 68.74 55.39 0.097 19.27 15.53 

LogLogistic 149.886 0.7235 62.10 34.61 -0.021 17.41 9.70 

LogProbitb 149.913 0.6972 61.70 37.49 -0.003 17.29 10.51 

Multistage-Cancer 

(1 degree) 152.836 0.0978 23.82 18.34 -0.186 6.68 5.14 

Multistage-Cancer 

(2 degree) 149.814 0.8161 61.68 28.26 -0.063 17.29 7.92 

Multistage-Cancer 

(3 degree) 149.772 0.9171 63.62 27.49 -0.024 17.83 7.71 

Probitc 147.787 0.9867 62.20 51.12 -0.05 17.43 14.33 

Weibull 149.856 0.7576 62.63 30.11 -0.039 17.56 8.44 

Quantal-Linear 152.836 0.0978 23.82 18.34 -0.186 6.68 5.14 

Dichotomous-Hill 4441.71 NCd NCd NCd 0 0 0 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Slope restricted ≥ 1. c

Best-fitting model. 

d

Value unable to be calculated (NC: not calculated) by BMDS. 

 D-9 
 

 0

 0.2

 0.4

 0.6

 0.8

 0 50 100 150 200 250

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

07:32 10/26 2009

BMDL BMD

 

Probit

Source: Used with permission from Elservier, Ltd., Kano et al. (2009, 594539). 

Figure D-2. Probit BMD model for the combined incidence of hepatic 

adenomas and carcinomas in male F344 rats. 

==================================================================== 

Probit Model. (Version: 3.1; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_hepato_adcar_PrbBMR10.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_hepato_adcar_Prb-BMR10.plt 

Mon Oct 26 08:32:08 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = CumNorm(Intercept+Slope*Dose), 

where CumNorm(.) is the cumulative normal distribution function 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is not restricted 

Total number of observations = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial (and Specified) Parameter Values 

background = 0 Specified 

intercept = -1.51718 

slope = 0.00831843 

 D-10 
 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix ) 

 intercept slope 

intercept 1 -0.69 

slope -0.69 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

intercept 1.53138 0.160195 -1.84535 -1.2174 

slope 0.00840347 0.000976752 0.00648907 0.0103179 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -71.8804 4 

 Fitted model -71.8937 2 0.0265818 2 0.9868 

 Reduced model -115.644 1 87.528 3 <.0001 

 AIC: 147.787 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0628 3.142 3.000 50 -0.083 

 11.0000 0.0751 3.754 4.000 50 0.132 

 55.0000 0.1425 7.125 7.000 50 -0.050 

 274.0000 0.7797 38.985 39.000 50 0.005 

 Chi^2 = 0.03 d.f. = 2 P-value = 0.9867 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 62.1952

 BMDL = 51.1158

 D-11 
 

 0

 0.2

 0.4

 0.6

 0.8

 0 50 100 150 200 250

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:32 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elservier, Ltd., Kano et al. (2009, 594539). 

Figure D-3. Multistage BMD model (3 degree) for the combined incidence of 

hepatic adenomas and carcinomas in male F344 rats. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_hepato_adcar_MscBMR10-3poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_hepato_adcar_Msc-BMR10-3poly.plt 

Mon Oct 26 08:32:08 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: P[response] = background + (1-background)*[1-

EXP(-beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 4 

Total number of specified parameters = 0 

Degree of polynomial = 3 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

 D-12 
 

Background = 0.0623822 

Beta(1) = 0.00142752 

Beta(2) = 0 

Beta(3) = 5.14597e-008 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Beta(2)have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix ) 

 Background Beta(1) Beta(3) 

Background 1 -0.67 0.58 

Beta(1) -0.67 1 -0.95 

Beta(3) 0.58 -0.95 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0619918 * * * 

Beta(1) 0.001449 * * * 

Beta(2) 0 * * * 

Beta(3) 5.11829e-008 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -71.8804 4 

 Fitted model -71.8858 3 0.0107754 1 0.9173 

 Reduced model -115.644 1 87.528 3 <.0001 

 AIC: 149.772 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0620 3.100 3.000 50 -0.058 

 11.0000 0.0769 3.844 4.000 50 0.083 

 55.0000 0.1412 7.059 7.000 50 -0.024 

 274.0000 0.7799 38.997 39.000 50 0.001 

 Chi^2 = 0.01 d.f. = 1 P-value = 0.9171 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 63.6179 

 BMDL = 27.4913 

 BMDU = 123.443 

Taken together, (27.4913, 123.443) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00363752 

 D-13 
 

D.4. F344 RATS: TUMORS AT OTHER SITES 

The data for tumors at sites other than the liver in male and female F344 rats (Kano et al., 

2009, 594539) are shown in Table D-6. Note that the incidence of rats with these endpoints are 

monotone non-decreasing functions (except female peritoneal mesotheliomas). These data 

therefore appear to be appropriate for dose-response modeling using BMDS. 

Table D-6. Data for significant tumors at other sites in male and female F344 

rats (Kano et al., 2009, 594539) 

Dose (mg/kg-day) 

Female Male

Tumor site and type 0 18 83 429 0 11 55 274

Nasal cavity squamous cell carcinoma 0 0 0 7 0 0 0 3 

Peritoneal mesothelioma 1 0 0 0 2 2 5 28 

Mammary gland adenoma 6 7 10 16 0 1 2 2 

Total number per group 50 50 50 50 50 50 50 50 

Source: Used with permission from Elsevier, Ltd., Kano et al., (2009, 594539). 

The results of the BMDS modeling for the entire suite of models are presented in Tables 

D-7 through Table D-10 for tumors in the nasal cavity, mammary gland, and peritoneal cavity. 

 D-14 
 

Table D-7. BMDS dose-response modeling results for the incidence of nasal 

cavity tumors in female F344 ratsa (Kano et al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2b

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 44.4964 1 403.82 269.03 0 100.35 66.85 

Logistic 44.4963 1 421.54 351.74 0 104.75 87.41 

LogLogistic 44.4963 1 413.69 268.85 0 102.80 66.81 

LogProbitc 44.4963 1 400.06 260.38 0 99.42 64.71 

Multistage-Cancer 

(1 degree) 45.6604 0.6184 375.81 213.84 0.595 93.39 53.14 

Multistage-Cancer 

(2 degree) 43.0753 0.9607 366.07 274.63 0.109 90.97 68.24 

Multistage-Cancer 

(3 degree)d 42.6063 0.9966 381.65 282.61 0.021 94.84 70.23 

Probit 44.4963 1 414.11 333.31 0 102.91 82.83 

Weibull 44.4963 1 414.86 273.73 0 103.09 68.02 

Quantal-Linear 45.6604 0.6184 375.81 213.84 0.595 93.39 53.14 

Dichotomous-Hill 46.4963 0.9997 413.96 372.57 1.64×10-8 102.87 92.58 

a

Nasal cavity tumors in female F344 rats include squamous cell carcinoma and esthesioneuro-epithelioma.

b

Maximum absolute χ

2

 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

c

Slope restricted ≥ 1. d

Best-fitting model. 

 D-15 
 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 50 100 150 200 250 300 350 400 450

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:28 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-4. Multistage BMD model (3 degree) for nasal cavity tumors in 

female F344 rats. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_nasal_car_MscBMR10-3poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_nasal_car_Msc-BMR10-3poly.plt 

Mon Oct 26 08:28:58 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: P[response] = background + (1-

background)*[1-EXP(-beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 4 

Total number of specified parameters = 0 

Degree of polynomial = 3 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

Background = 0 

Beta(1) = 0 

Beta(2) = 0 

Beta(3) = 1.91485e-009 

 D-16 
 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background -Beta(1) -Beta(2) 

have been estimated at a boundary point, or have been specified by the user, 

and do not appear in the correlation matrix ) 

 Beta(3) 

 Beta(3) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 0 * * * 

Beta(2) 0 * * * 

Beta(3) 1.89531e-009 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -20.2482 4 

 Fitted model -20.3031 1 0.109908 3 0.9906 

 Reduced model -30.3429 1 20.1894 3 0.0001551 

 AIC: 42.6063 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 50 0.000 

 18.0000 0.0000 0.001 0.000 50 -0.024 

 83.0000 0.0011 0.054 0.000 50 -0.233 

 429.0000 0.1390 6.949 7.000 50 0.021 

 Chi^2 = 0.06 d.f. = 3 P-value = 0.9966 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 381.651 

 BMDL = 282.609 

 BMDU = 500.178 

Taken together, (282.609, 500.178) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.000353846

 D-17 
 

Table D-8. BMDS dose-response modeling results for the incidence of nasal 

cavity tumors in male F344 ratsa (Kano et al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2b

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 26.6968 1 299.29 244.10 0 83.89 68.42 

Logistic 26.6968 1 281.06 261.29 0 78.78 73.24 

LogLogistic 26.6968 1 288.31 245.29 0 80.81 68.75 

LogProbitc 26.6968 1 303.06 238.86 0 84.94 66.95 

Multistage-Cancer 

(1 degree) 26.0279 0.8621 582.49 256.43 0.384 163.28 71.88 

Multistage-Cancer 

(2 degree) 24.9506 0.988 365.19 242.30 0.073 102.37 67.92 

Multistage-Cancer 

(3 degree)d 24.747 0.9989 328.11 245.63 0.015 91.97 68.85 

Probit 26.6968 1 287.96 257.01 0 80.72 72.04 

Weibull 26.6968 1 288.00 246.36 0 80.73 69.06 

Quantal-Linear 26.0279 0.8621 582.49 256.43 0.384 163.28 71.88 

Dichotomous-Hill 28.6968 0.9994 290.52 261.47 6.25×10-5 81.44 73.29 

a

Nasal cavity tumors in male F344 rats include squamous cell carcinoma, Sarcoma: NOS, rhabdomyosarcoma, and 

esthesioneuro-epithelioma. 

b

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

c

Slope restricted ≥ 1. d

Best-fitting model. 

 D-18 
 

 0

 0.05

 0.1

 0.15

 0 50 100 150 200 250 300

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:34 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permisison from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-5. Multistage BMD model (3 degree) for nasal cavity tumors in 

male F344 rats. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_nasal_car_MscBMR10-3poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_nasal_car_Msc-BMR10-3poly.plt 

Mon Oct 26 08:34:20 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: P[response] = background + (1-background)*[1-

EXP(-beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 4 

Total number of specified parameters = 0 

Degree of polynomial = 3 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

Background = 0 

 D-19 
 

Beta(1) = 0 

Beta(2) = 0 

Beta(3) = 3.01594e-009 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background -Beta(1) -Beta(2) 

have been estimated at a boundary point, or have been specified by the user, 

and do not appear in the correlation matrix ) 

 Beta(3) 

 Beta(3) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 0 * * * 

Beta(2) 0 * * * 

Beta(3) 2.98283e-009 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -11.3484 4 

 Fitted model -11.3735 1 0.0502337 3 0.9971 

 Reduced model -15.5765 1 8.45625 3 0.03747 

 AIC: 24.747 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 50 0.000 

 11.0000 0.0000 0.000 0.000 50 -0.014 

 55.0000 0.0005 0.025 0.000 50 -0.158 

 274.0000 0.0595 2.976 3.000 50 0.015 

 Chi^2 = 0.03 d.f. = 3 P-value = 0.9989 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 328.108 

 BMDL = 245.634 

 BMDU = 1268.48 

Taken together, (245.634, 1268.48) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00040711 

 D-20 
 

Table D-9. BMDS dose-response modeling results for the incidence of 

mammary gland adenomas in female F344 rats (Kano et al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 194.222 0.8559 176.66 99.13 0.465 43.90 24.63 

Logistic 194.475 0.7526 230.35 159.73 0.612 57.24 39.69 

LogLogisticb 194.151 0.8874 161.01 81.91 0.406 40.01 20.35 

LogProbitc 195.028 0.5659 270.74 174.66 -0.075 67.28 43.41 

Multistage-Cancer 

(1 degree) 194.222 0.8559 176.66 99.13 0.465 43.90 24.63 

Multistage-Cancer 

(2 degree) 194.222 0.8559 176.66 99.13 0.465 43.90 24.63 

Multistage-Cancer 

(3 degree) 194.222 0.8559 176.66 99.13 0.465 43.90 24.63 

Probit 194.441 0.7656 223.04 151.60 0.596 55.43 37.67 

Weibull 194.222 0.8559 176.65 99.13 0.465 43.90 24.63 

Quantal-Linear 194.222 0.8559 176.65 99.13 0.465 43.90 24.63 

Dichotomous-Hill 197.916 NCd 94.06 14.02 3.49×10-5 23.37 3.48 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model. 

c

Slope restricted ≥ 1. d

Value unable to be calculated (NC: not calculated) by BMDS. 

 D-21 
 

Source: Use with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200 250 300 350 400 450

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

11:31 02/01 2010

BMDL BMD

 

Log-Logistic

Figure D-6. LogLogistic BMD model for mammary gland adenomas in 

female F344 rats. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: C:\14DBMDS\lnl_kano2009_frat_mamm_ad_Lnl-BMR10-Restrict.(d) 

Gnuplot Plotting File: C:\14DBMDS\lnl_kano2009_frat_mamm_ad_Lnl-BMR10-Restrict.plt 

 Mon Feb 01 11:31:31 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.12 

 intercept = -7.06982 

 slope = 1 

Asymptotic Correlation Matrix of Parameter Estimates 

 D-22 
 

(*** The model parameter(s) -slope have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.53 

 intercept -0.53 1 

 Parameter Estimates 

5.0% Wald Confidence Interval 

 Analysis of Deviance Table 

89 

 Goodness of Fit 

 9

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0.130936 * * * 

 intercept -7.2787 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated. 

 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.958 4 

 Fitted model -95.0757 2 0.235347 2 0.8

 Reduced model -98.6785 1 7.4409 3 0.0591 

 AIC: 194.151 

 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------

 0.0000 0.1309 6.547 6.000 50 -0.229 

 18.0000 0.1416 7.080 7.000 50 -0.032 

 83.0000 0.1780 8.901 10.000 50 0.406 

 429.0000 0.3294 16.472 16.000 50 -0.142 

 Chi^2 = 0.24 d.f. = 2 P-value = 0.8874 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 161.012 

 BMDL = 81.9107

 D-23 
 

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200 250 300 350 400 450

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:27 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-7. Multistage BMD model (1 degree) for mammary gland 

adenomas in female F344 rats. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_mamm_ad_Msc-BMR10-

1poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_mamm_ad_Msc-BMR10-1poly.plt 

Mon Oct 26 08:27:02 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 2 

Total number of specified parameters = 0 

Degree of polynomial = 1 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

Background = 0.136033 

Beta(1) = 0.000570906 

 D-24 
 

Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

Beta(1) -0.58 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background .133161 * * * 

Beta(1) 0.000596394 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.958 4 

 Fitted model -95.111 2 0.305898 2 0.8582 

 Reduced model -98.6785 1 7.4409 3 0.0591 

 AIC: 194.222 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1332 6.658 6.000 50 -0.274 

 18.0000 0.1424 7.121 7.000 50 -0.049 

 83.0000 0.1750 8.751 10.000 50 0.465 

 429.0000 0.3288 16.442 16.000 50 -0.133 

 Chi^2 = 0.31 d.f. = 2 P-value = 0.8559 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 176.663 

 BMDL = 99.1337 

 BMDU = 501.523 

Taken together, (99.1337, 501.523) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00100874 

 D-25 
 

Table D-10. BMDS dose-response modeling results for the incidence of 

peritoneal mesotheliomas in male F344 rats (Kano et al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 140.701 0.9189 73.52 35.62 0.018 20.61 9.98 

Logistic 139.016 0.8484 103.52 84.35 0.446 29.02 23.65 

LogLogistic 140.699 0.9242 72.56 36.37 0.014 20.34 10.19 

LogProbitb 140.69 0.9852 70.29 52.59 0.001 19.70 14.74 

Multistage-Cancer 

(1 degree) 140.826 0.3617 41.04 30.51 -1.066 11.50 8.55 

Multistage-Cancer 

(2 degree) 140.747 0.8135 77.73 35.43 0.067 21.79 9.93 

Multistage-Cancer 

(3 degree) 140.747 0.8135 77.73 35.43 0.067 21.79 9.93 

Probitc 138.869 0.9148 93.06 76.32 0.315 26.09 21.39 

Weibull 140.709 0.8915 74.77 35.59 0.027 20.96 9.97 

Quantal-Linear 140.826 0.3617 41.04 30.51 -1.066 11.50 8.55 

Dichotomous-Hill 2992 NCd NCd NCd 0 0 0 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Slope restricted ≥ 1. c

Best-fitting model. 

d

Value unable to be calculated (NC: not calculated) by BMDS. 

 D-26 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 50 100 150 200 250

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

07:41 10/26 2009

BMDL BMD

 

Probit

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-8. Probit BMD model for peritoneal mesotheliomas in male F344 

rats. 

==================================================================== 

Probit Model. (Version: 3.1; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_peri_meso_PrbBMR10.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_peri_meso_Prb-BMR10.plt 

Mon Oct 26 08:41:29 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: P[response] = CumNorm(Intercept+Slope*Dose), 

where CumNorm(.) is the cumulative normal distribution function 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is not restricted 

Total number of observations = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial (and Specified) Parameter Values 

background = 0 Specified 

intercept = -1.73485 

slope = 0.00692801 

Asymptotic Correlation Matrix of Parameter Estimates 

 D-27 
 

(*** The model parameter(s) -background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.75 

slope -0.75 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

intercept -1.73734 0.18348 -2.09695 -1.37772 

slope 0.00691646 0.000974372 0.00500672 0.00882619 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.3451 4 

 Fitted model -67.4344 2 0.178619 2 0.9146 

 Reduced model -95.7782 1 56.8663 3 <.0001 

 AIC: 138.869 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0412 2.058 2.000 50 -0.041 

 11.0000 0.0483 2.417 2.000 50 -0.275 

 55.0000 0.0874 4.370 5.000 50 0.315 

 274.0000 0.5627 28.134 28.000 50 -0.038 

 Chi^2 = 0.18 d.f. = 2 P-value = 0.9148 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 93.0615 

 BMDL = 76.3242 

 D-28 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 50 100 150 200 250

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:41 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-9. Multistage BMD (2 degree) model for peritoneal 

mesotheliomas in male F344 rats. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_peri_meso_MscBMR10-2poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_peri_meso_Msc-BMR10-2poly.plt 

Mon Oct 26 08:41:28 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 3 

Total number of specified parameters = 0 

 Degree of polynomial = 2 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

 D-29 
 

Default Initial Parameter Values 

Background = 0.0358706 

Beta(1) = 0.000816174 

Beta(2) = 7.47062e-006 

Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) Beta(2) 

Background 1 -0.67 0.59 

Beta(1) -0.67 1 -0.98 

Beta(2) 0.59 -0.98 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0366063 * * * 

Beta(1) 0.000757836 * * * 

Beta(2) 7.6893e-006 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.3451 4 

 Fitted model -67.3733 3 0.056567 1 0.812 

 Reduced model -95.7782 1 56.8663 3 <.0001 

 AIC: 140.747 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0366 1.830 2.000 50 0.128 

 11.0000 0.0455 2.275 2.000 50 -0.186 

 55.0000 0.0972 4.859 5.000 50 0.067 

 274.0000 0.5605 28.027 28.000 50 -0.008 

 Chi^2 = 0.06 d.f. = 1 P-value = 0.8135 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 77.7277 

 BMDL = 35.4296 

 BMDU = 118.349 

Taken together, (35.4296, 118.349) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.0028225 

 D-30 
 

D.5. FEMALE BDF1 MICE: HEPATIC CARCINOMAS AND ADENOMAS 

Data for female BDF1 mouse hepatic carcinomas and adenomas are shown in Table D11. Note that the incidence of carcinomas and the incidence of either adenomas or carcinomas 

are monotone non-decreasing functions of dose. These data therefore appear to be appropriate 

for dose-response modeling using BMDS. However, the incidence of adenomas clearly reaches 

a peak value at 66 mg/kg-day and then decreases sharply with increasing dose. This cannot be 

modeled by a multistage model using only non-negative coefficients. To some extent the 

incidence of “either adenomas or carcinomas” retains some of the inverted-U shaped doseresponse of the adenomas, which dominate based on their high incidence at the lowest dose 

groups (66 and 278 mg/kg-day), thus is not well characterized by any multistage model. 

Table D-11. Data for hepatic adenomas and carcinomas in female BDF1 mice 

(Kano et al., 2009, 594539) 

Dose (mg/kg-day) 

Tumor type 0 66 278 964 

Hepatocellular adenomas 5 31 20 3 

Hepatocellular carcinomas 0 6 30 45 

Either adenomas or carcinomas 5 35 41 46 

Neither adenomas nor carcinomas 45 15 9 4 

Total number per group 50 50 50 50 

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

The results of the BMDS modeling for the entire suite of models for hepatic adenomas 

and carcinomas in female BDF1 mice are presented in Table D-12. The multistage models did 

not provide reasonable fits to the incidence data for hepatocellular adenoma or carcinoma in 

female BDF1 mice. The log-logistic model provided the best-fit to the data as indicated by the 

AIC and p-value as was chosen as the best-fitting model to carry forward in the analysis; 

however, this model resulted in a BMDL10 much lower than the response level at the lowest dose 

in the study (Kano et al., 2009, 594539). Thus, the log-logistic model was run for BMRs of 30 

and 50%. The output from these models are shown in Figures D-11 and D-12. A summary of 

the BMD results for BMRs of 10, 30, and 50% are shown in Table D-13. Using a higher BMR 

resulted in BMDLs closer to the lowest observed response data, and a BMR of 50% was chosen 

to carry forward in the analysis. 

The graphical output from fitting these models suggested that a simpler model obtained 

by dropping the data point for the highest dose (964 mg/kg-day) might also be adequate. This 

was tested and the results did not affect the choice of the model, nor significantly affect the 

resulting BMDs and BMDLs. 

 D-31 
 

Table D-12. BMDS dose-response modeling results for the combined 

incidence of hepatic adenomas and carcinomas in female BDF1 mice (Kano 

et al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 203.331 0 26.43 19.50 -2.654 3.98 2.94 

Logistic 214.951 0 58.05 44.44 3.201 8.74 6.69 

LogLogisticb 176.214 0.1421 5.54 3.66 -0.121 0.83 0.55 

LogProbitc 198.354 0 26.37 19.57 -1.166 3.97 2.95 

Multistage-Cancer 

(1 degree) 203.331 0 26.43 19.50 -2.654 3.98 2.94 

Multistage-Cancer 

(2 degree) 203.331 0 26.43 19.50 -2.654 3.98 2.94 

Multistage-Cancer 

(3 degree) 203.331 0 26.43 19.50 -2.654 3.98 2.94 

Probit 217.671 0 69.89 56.22 3.114 10.5 8.46 

Weibull 203.331 0 26.43 19.50 -2.654 3.98 2.94 

Quantal-Linear 203.331 0 26.43 19.50 -2.654 3.98 2.94 

Dichotomous-Hill 7300.48 NCd NCd NCd 0 0 0 

a

Maximum absolute χ

2

 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model, lowest AIC value. 

c

Slope restricted ≥ 1. d

Value unable to be calculated (NC: not calculated) by BMDS. 

Table D-13. BMDS LogLogistic dose-response modeling results using BMRs 

of 10, 30, and 50% for the combined incidence of hepatic adenomas and 

carcinomas in female BDF1 mice (Kano et al., 2009, 594539). 

BMR AIC p-value 

BMD 

mg/kg-day 

BMDL 

mg/kg-day χ2a

BMDHED 

mg/kg-day 

BMDLHED 

mg/kg-day 

10% 176.214 0.1421 5.54 3.66 -0.121 0.83 0.55 

30% 176.214 0.1421 21.38 14.11 -0.121 3.22 2.12 

50% 176.214 0.1421 49.88 32.93 0 7.51 4.95 

a

Maximum absolute χ

2

 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

 D-32 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

11:26 05/12 2010

BMDLBMD

 

Log-Logistic

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-10. LogLogistic BMD model for the combined incidence of hepatic 

adenomas and carcinomas in female BDF1 mice with a BMR of 10%. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR10-

Restrict.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR10-

Restrict.plt 

 Wed May 12 11:26:35 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 D-33 
 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.1 

 intercept = -4.33618 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -slope have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.32 

 intercept -0.32 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0.105265 * * * 

 intercept -3.90961 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -84.3055 4 

 Fitted model -86.107 2 3.6029 2 0.1651 

 Reduced model -131.248 1 93.8853 3 <.0001 

 AIC: 176.214 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1053 5.263 5.000 50 -0.121 

 66.0000 0.6149 30.743 35.000 50 1.237 

 278.0000 0.8639 43.194 41.000 50 -0.905 

 964.0000 0.9560 47.799 46.000 50 -1.240 

 Chi^2 = 3.90 d.f. = 2 P-value = 0.1421 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 5.54218 

 BMDL = 3.65848 

 D-34 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

11:26 05/12 2010

BMDL BMD

 

Log-Logistic

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-11. LogLogistic BMD model for the combined incidence of hepatic 

adenomas and carcinomas in female BDF1 mice with a BMR of 30%. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR30-

Restrict.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR30-

Restrict.plt 

 Wed May 12 11:26:36 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 D-35 
 

 Default Initial Parameter Values 

 background = 0.1 

 intercept = -4.33618 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -slope have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix) 

 background intercept 

background 1 -0.32 

 intercept -0.32 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0.105265 * * * 

 intercept -3.90961 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -84.3055 4 

 Fitted model -86.107 2 3.6029 2 0.1651 

 Reduced model -131.248 1 93.8853 3 <.0001 

 AIC: 176.214 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1053 5.263 5.000 50 -0.121 

 66.0000 0.6149 30.743 35.000 50 1.237 

 278.0000 0.8639 43.194 41.000 50 -0.905 

 964.0000 0.9560 47.799 46.000 50 -1.240 

 Chi^2 = 3.90 d.f. = 2 P-value = 0.1421 

 Benchmark Dose Computation 

Specified effect = 0.3 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 21.377 

 BMDL = 14.1113 

 D-36 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

11:26 05/12 2010

BMDL BMD

 

Log-Logistic

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-12. LogLogistic BMD model for the combined incidence of hepatic 

adenomas and carcinomas in female BDF1 mice with a BMR of 50%. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR50-

Restrict.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR50-

Restrict.plt 

 Wed May 12 11:26:36 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Effect 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 D-37 
 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.1 

 intercept = -4.33618 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -slope have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix) 

 background intercept 

background 1 -0.32 

 intercept -0.32 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0.105265 * * * 

 intercept -3.90961 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -84.3055 4 

 Fitted model -86.107 2 3.6029 2 0.1651 

 Reduced model -131.248 1 93.8853 3 <.0001 

 AIC: 176.214 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1053 5.263 5.000 50 -0.121 

 66.0000 0.6149 30.743 35.000 50 1.237 

 278.0000 0.8639 43.194 41.000 50 -0.905 

 964.0000 0.9560 47.799 46.000 50 -1.240 

 Chi^2 = 3.90 d.f. = 2 P-value = 0.1421 

 Benchmark Dose Computation 

Specified effect = 0.5 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 49.8797 

 BMDL = 32.9263 

 D-38 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:26 05/12 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-13. Multistage BMD model (1 degree) for the combined incidence of 

hepatic adenomas and carcinomas in female BDF1 mice. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_fmouse_hepato_adcar_Msc-BMR10-1poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_fmouse_hepato_adcar_Msc-BMR10-1poly.plt 

 Wed May 12 11:26:31 2010 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Effect 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 D-39 
 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.51713 

 Beta(1) = 0.00201669 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.65 

 Beta(1) -0.65 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.265826 * * * 

 Beta(1) 0.00398627 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -84.3055 4 

 Fitted model -99.6653 2 30.7195 2 2.1346928e-007 

 Reduced model -131.248 1 93.8853 3 <.0001 

 AIC: 203.331 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2658 13.291 5.000 50 -2.654 

 66.0000 0.4357 21.783 35.000 50 3.770 

 278.0000 0.7576 37.880 41.000 50 1.030 

 964.0000 0.9843 49.213 46.000 50 -3.651 

 Chi^2 = 35.65 d.f. = 2 P-value = 0.0000 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 26.4309 

 BMDL = 19.5045 

 BMDU = 37.5583 

Taken together, (19.5045, 37.5583) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00512702 

 D-40 
 

D.6. MALE BDF1 MICE: HEPATIC CARCINOMAS AND ADENOMAS 

Data for hepatic carcinomas and adenomas in male BDF1 mice (Kano et al., 2009, 

594539) are shown in Table D-14. Note that the incidence of carcinomas and the incidence of 

either adenomas or carcinomas are monotone non-decreasing functions of dose. These data 

therefore appear to be appropriate for dose-response modeling using BMDS. However, the 

incidence of adenomas clearly reaches a peak value at 191 mg/kg-day and then decreases sharply 

with increasing dose. This cannot be modeled by a multistage model using only non-negative 

coefficients. To some extent the incidence of “either adenomas or carcinomas or both” retains 

some of the inverted-U shaped dose-response of the adenomas, which dominate based on their 

high incidence at the lowest dose groups (49 and 191 mg/kg-day), thus is not well characterized 

by any multistage model. 

Table D-14. Data for hepatic adenomas and carcinomas in male BDF1 mice 

(Kano et al., 2009, 594539) 

Dose (mg/kg-day)

Tumor type 0 49 191 677 

Hepatocellular adenomas 9 17 23 11 

Hepatocellular carcinomas 15 20 23 36 

Either adenomas or carcinomas 23 31 37 40 

Neither adenomas nor carcinomas 27 19 13 10 

Total number per group 50 50 50 50 

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

The results of the BMDS modeling for the entire suite of models for hepatic adenomas 

and carcinomas in male BDF1 mice are presented in Table D-15. 

 D-41 
 

Table D-15. BMDS dose-response modeling results for the combined 

incidence of hepatic adenomas and carcinomas in male BDF1 mice (Kano et 

al., 2009, 594539) 

Model AIC p-value 

BMD10

mg/kg-day

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 250.551 0.1527 70.99 44.00 0.605 11.48 7.12 

Logistic 251.187 0.112 91.89 61.98 0.529 14.86 10.02 

LogLogisticb 248.839 0.3461 34.78 16.60 0.656 5.63 2.68 

LogProbitc 252.244 0.0655 133.53 78.18 0.016 21.60 12.64 

Multistage-Cancer 

(1 degree) 250.551 0.1527 70.99 44.00 0.605 11.48 7.12 

Multistage-Cancer 

(2 degree) 250.551 0.1527 70.99 44.00 0.605 11.48 7.12 

Multistage-Cancer 

(3 degree) 250.551 0.1527 70.99 44.00 0.605 11.48 7.12 

Probit 251.326 0.1048 97.01 67.36 0.518 15.69 10.90 

Weibull 250.551 0.1527 70.99 44.00 0.605 11.48 7.12 

Quantal-Linear 250.551 0.1527 70.99 44.00 0.605 11.48 7.12 

Dichotomous-Hill 250.747 NCd 11.60 1.63 -1.25×10-5 1.88 0.26 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model. 

c

Slope restricted ≥ 1. d

Value unable to be calculated (NC: not calculated) by BMDS.

 D-42 
 

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0.9

 0 100 200 300 400 500 600 700

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

07:30 10/26 2009

BMDL BMD

 

Log-Logistic

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-14. LogLogistic BMD model for the combined incidence of hepatic 

adenomas and carcinomas in male BDF1 mice. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_mmouse_hepato_adcar_Lnl-BMR10-

Restrict.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_mmouse_hepato_adcar_Lnl-BMR10-

Restrict.plt 

Thu Nov 12 09:09:36 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is restricted as slope >= 1 

Total number of observations = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

User has chosen the log transformed model 

 D-43 
 

 Default Initial Parameter Values 

 background = 0.46 

 intercept = -5.58909 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -slope have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.69 

 intercept -0.69 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0.507468 * * * 

 intercept -5.74623 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -121.373 4 

 Fitted model -122.419 2 2.09225 2 0.3513 

 Reduced model -128.859 1 14.9718 3 0.001841 

 AIC: 248.839 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.5075 25.373 23.000 50 -0.671 

 49.0000 0.5741 28.707 31.000 50 0.656 

 191.0000 0.6941 34.706 37.000 50 0.704 

 677.0000 0.8443 42.214 40.000 50 -0.863 

 Chi^2 = 2.12 d.f. = 2 P-value = 0.3461 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 34.7787 

 BMDL = 16.5976 

 D-44 
 

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0.9

 0 100 200 300 400 500 600 700

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:30 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009, 594539). 

Figure D-15. Multistage BMD model (1 degree) for the combined incidence of 

hepatic adenomas and carcinomas in male BDF1 mice. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mmouse_hepato_adcar_Msc-BMR10-1poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mmouse_hepato_adcar_Msc-BMR10-1poly.plt 

Mon Oct 26 08:30:50 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 2 

Total number of specified parameters = 0 

Degree of polynomial = 1 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

 D-45 
 

Background = 0.573756 

Beta(1) = 0.00123152 

Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

Beta(1) -0.58 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.545889 * * * 

Beta(1) 0.00148414 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -121.373 4 

 Fitted model -123.275 2 3.80413 2 0.1493 

 Reduced model -128.859 1 14.9718 3 0.001841 

 AIC: 250.551 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.5459 27.294 23.000 50 -1.220 

 49.0000 0.5777 28.887 31.000 50 0.605 

 191.0000 0.6580 32.899 37.000 50 1.223 

 677.0000 0.8337 41.687 40.000 50 -0.641 

 Chi^2 = 3.76 d.f. = 2 P-value = 0.1527 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 70.9911 

 BMDL = 44.0047 

 BMDU = 150.117 

Taken together, (44.0047, 150.117) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00227248

 D-46 
 

D.7. BMD MODELING RESULTS FROM ADDITIONAL CHRONIC BIOASSAYS 

Data and BMDS modeling results for the additional chronic bioassays (Kociba et al., 

1974, 062929; NCI, 1978, 062935) were evaluated for comparison with the Kano et al. (2009, 

594539) study. These results are presented in the following sections. 

The BMDS dose-response modeling estimates and HEDs that resulted are presented in 

detail in the following sections and a summary is provided in Table D-16. 

Table D-16. Summary of BMDS dose-response modeling estimates associated 

with liver and nasal tumor incidence data resulting from chronic oral 

exposure to 1,4-dioxane in rats and mice 

Endpoint

Model 

selection 

criterion

Model 

Type AIC

pvalue

BMD10 

mg/kgday

BMDL10 

mg/kgday

BMD10 HED 

mg/kgday

BMDL10 HED 

mg/kg-day

Kociba et al., (1974, 062929) 

Male and Female (combined) Sherman Rats 

Hepatic 

Tumorsa

Lowest 

AIC 

Probit 84.3126 0.606 1113.94 920.62 290.78 240.31 

Nasal 

Cavity 

Tumorsb

Lowest 

AIC 

Multistage 

(3 degree) 

26.4156 0.9999 1717.16 1306.29 448.24 340.99 

NCI, (1978, 062935) 

Female Osborne-Mendel Rats 

Hepatic 

Tumorsc

Lowest 

AIC 

LogLogistic 84.2821 0.7333 111.46 72.41 28.75 18.68 

Nasal 

Cavity 

Tumorsb

Lowest 

AIC 

LogLogistic 84.2235 0.2486 155.32 100.08 40.07 25.82 

NCI, (1978, 062935) 

Male Osborne-Mendel Rats 

Nasal 

Cavity 

Tumorsb

Lowest 

AIC 

LogLogistic 92.7669 0.7809 56.26 37.26 16.10 10.66 

NCI, (1978, 062935) 

Female B6C3F1 Mice 

Hepatic 

Tumorsd

Lowest 

AIC, 

Multistage 

model 

Multistage 

(2 degree) 

85.3511 1 160.68 67.76 23.12 9.75 

NCI, (1978, 062935) 

Male B6C3F1 Mice 

Hepatic 

Tumorsd

Lowest 

AIC 

Gamma 177.539 0.7571 601.69 243.92 87.98 35.67 

a

Incidence of hepatocellular carcinoma. 

b

Incidence of nasal squamous cell carcinoma. 

c

Incidence of hepatocellular adenoma. 

d

Incidence of hepatocellular adenoma or carcinoma. 

 D-47 
 

D.7.1. Hepatocellular Carcinoma and Nasal Squamous Cell Carcinoma (Kociba et al., 1974, 

062929) 

The incidence data for hepatocellular carcinoma and nasal squamous cell carcinoma are 

presented in Table D-17. The predicted BMD10 HED and BMDL10 HED values are also presented in 

Tables D-18 and D-19 for hepatocellular carcinomas and nasal squamous cell carcinomas, 

respectively. 

Table D-17. Incidence of hepatocellular carcinoma and nasal squamous cell 

carcinoma in male and female Sherman rats (combined) (Kociba et al., 1974, 

062929) treated with 1,4-dioxane in the drinking water for 2 years

Animal Dose (mg/kg-day) 

(average of male and female dose) 

Incidence of hepatocellular 

carcinomaa

Incidence of nasal 

squamous cell carcinomaa

0 1/106b 0/106c

14 0/110 0/110

121 1/106 0/106

1307 10/66d 3/66d

a

Rats surviving until 12 months on study. 

b

p < 0.001; positive dose-related trend (Cochran-Armitage test). c

p < 0.01; positive dose-related trend (Cochran-Armitage test). d

p < 0.001; Fisher’s Exact test. 

Source: Used with permission from Elsevier, Ltd., Kociba et al. (1974, 062929). 

 D-48 
 

Table D-18. BMDS dose-response modeling results for the incidence of 

hepatocellular carcinoma in male and female Sherman rats (combined) 

(Kociba et al., 1974, 062929) exposed to 1,4-dioxane in the drinking water for 

2 years 

Model AIC p-value 

BMD10

mg/kg-day

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 86.2403 0.3105 985.13 628.48 -0.005 257.15 164.05 

Logistic 84.3292 0.6086 1148.65 980.95 -0.004 299.84 256.06 

LogLogistic 86.2422 0.3103 985.62 611.14 -0.005 257.28 159.53 

LogProbitb 84.4246 0.5977 1036.97 760.29 -0.011 270.68 198.46 

Multistage-Cancer 

(1 degree) 85.1187 0.3838 940.12 583.58 0.279 245.40 152.33 

Multistage-Cancer 

(2 degree) 86.2868 0.3109 1041.72 628.56 -0.006 271.92 164.07 

Multistage-Cancer 

(3 degree) 86.2868 0.3109 1041.72 628.56 -0.006 271.92 164.08 

Probitc 84.3126 0.606 1113.94 920.62 -0.005 290.78 240.31 

Weibull 86.2443 0.3104 998.33 629.93 -0.005 260.60 164.43 

Quantal-Linear 85.1187 0.3838 940.12 583.58 0.279 245.40 152.33 

Dichotomous-Hill 1503.63 NCd NCd NCd 0 0 0 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Slope restricted ≥ 1. c

Best-fitting model. 

d

Value unable to be calculated (NC: not calculated) by BMDS. 

 D-49 
 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0 200 400 600 800 1000 1200

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

11:54 10/27 2009

BMDL BMD

 

Probit

Source: Used with permission from Elsevier, Ltd., Kociba et al. (1974, 062929). 

Figure D-16. Probit BMD model for the incidence of hepatocellular 

carcinoma in male and female Sherman rats exposed to 1,4-dioxane in 

drinking water. 

==================================================================== 

Probit Model. (Version: 3.1; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kociba_mf_rat_hepato_car_PrbBMR10.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kociba_mf_rat_hepato_car_Prb-BMR10.plt 

Tue Oct 27 12:54:14 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = CumNorm(Intercept+Slope*Dose),where CumNorm(.) is the cumulative normal 

distribution function 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is not restricted 

Total number of observations = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Initial (and Specified) Parameter Values 

background = 0 Specified 

intercept = -2.62034 

 D-50 
 

slope = 0.0012323 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix ) 

 intercept slope 

intercept 1 -0.82 

slope -0.82 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

intercept -2.55961 0.261184 -3.07152 -2.0477 

slope 0.00117105 0.000249508 0.000682022 0.00166008 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -39.3891 4 

 Fitted model -40.1563 2 1.53445 2 0.4643 

 Reduced model -53.5257 1 28.2732 3 <.0001 

 AIC: 84.3126 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0052 0.555 1.000 106 0.598 

 14.0000 0.0055 0.604 0.000 110 -0.779 

 121.0000 0.0078 0.827 1.000 106 0.191 

 1307.0000 0.1517 10.014 10.000 66 -0.005 

 Chi^2 = 1.00 d.f. = 2 P-value = 0.6060 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1113.94 

 BMDL = 920.616 

 D-51 
 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0 200 400 600 800 1000 1200

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:54 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: Used with permission from Elsevier, Ltd., Kociba et al. (1974, 062929). 

Figure D-17. Multistage BMD model (1 degree) for the incidence of 

hepatocellular carcinoma in male and female Sherman rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_hepato_car_MscBMR10-1poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_hepato_car_Msc-BMR10-1poly.plt 

Tue Oct 27 12:54:10 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

total number of records with missing values = 0 

Total number of parameters in model = 2 

Total number of specified parameters = 0 

Degree of polynomial = 1 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

 D-52 
 

Default Initial Parameter Values 

Background = 0.000925988 

Beta(1) = 0.000124518 

Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.44 

Beta(1) -0.44 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.0038683 * * * 

Beta(1) 0.000112071 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -39.3891 4 

 Fitted model -40.5594 2 2.34056 2 0.3103 

 Reduced model -53.5257 1 28.2732 3 <.0001 

 AIC: 85.1187 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0039 0.410 1.000 106 0.923 

 14.0000 0.0054 0.597 0.000 110 -0.775 

 121.0000 0.0173 1.832 1.000 106 -0.620 

 1307.0000 0.1396 9.213 10.000 66 0.279 

 Chi^2 = 1.92 d.f. = 2 P-value = 0.3838 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 940.124 

 BMDL = 583.576 

 BMDU = 1685.88 

Taken together, (583.576, 1685.88) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.000171357 

 D-53 
 

Table D-19. BMDS dose-response modeling results for the incidence of nasal 

squamous cell carcinoma in male and female Sherman rats (combined) 

(Kociba et al., 1974, 062929) exposed to 1,4-dioxane in the drinking water for 

2 years 

Model AIC p-value 

BMD10

mg/kg-day

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 28.4078 1 1572.09 1305.86 0 410.37 340.87 

Logistic 28.4078 1 1363.46 1306.67 0 355.91 341.09 

LogLogistic 28.4078 1 1464.77 1306.06 0 382.35 340.93 

LogProbitb 28.4078 1 1644.38 1305.49 0 429.24 340.78 

Multistage-Cancer 

(1 degree) 27.3521 0.9163 3464.76 1525.36 0.272 904.42 398.17 

Multistage-Cancer 

(2 degree) 26.4929 0.9977 1980.96 1314.37 0.025 517.10 343.10 

Multistage-Cancer 

(3 degree)c 26.4156 0.9999 1717.16 1306.29 0.002 448.24 340.99 

Probit 28.4078 1 1419.14 1306.44 0 370.44 341.03 

Weibull 28.4078 1 1461.48 1306.11 0 381.50 340.94 

Quantal-Linear 27.3521 0.9163 3464.76 1525.35 0.272 904.42 398.17 

Dichotomous-Hill 30.4078 0.9997 1465.77 1319.19 5.53×10-7 382.62 344.35 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Slope restricted ≥ 1. c

Best-fitting model.

 D-54 
 

 0

 0.02

 0.04

 0.06

 0.08

 0.1

 0.12

 0.14

 0 200 400 600 800 1000 1200 1400 1600 1800

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

06:25 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure D-18. Multistage BMD model (3 degree) for the incidence of nasal 

squamous cell carcinoma in male and female Sherman rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_nasal_car_MscBMR10-3poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_nasal_car_Msc-BMR10-3poly.plt 

Tue Oct 27 07:25:02 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2-

beta3*dose^3)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 4 

Total number of records with missing values = 0 

Total number of parameters in model = 4 

Total number of specified parameters = 0 

Degree of polynomial = 3 

 D-55 
 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

Background = 0 

Beta(1) = 0 

Beta(2) = 0 

Beta(3) = 2.08414e-011 

Asymptotic Correlation Matrix of Parameter Estimates 

 (*** The model parameter(s) -Background -Beta(1) -Beta(2) 

have been estimated at a boundary point, or have been specified by the user, 

and do not appear in the correlation matrix ) 

 Beta(3) 

 Beta(3) 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 0 * * * 

Beta(2) 0 * * * 

Beta(3) 2.08088e-011 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -12.2039 4 

 Fitted model -12.2078 1 0.00783284 3 0.9998 

 Reduced model -17.5756 1 10.7433 3 0.0132 

 AIC: 26.4156 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 106 0.000 

 14.0000 0.0000 0.000 0.000 110 -0.003 

 121.0000 0.0000 0.004 0.000 106 -0.063 

 1307.0000 0.0454 2.996 3.000 66 0.002 

 Chi^2 = 0.00 d.f. = 3 P-value = 0.9999 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1717.16 

 BMDL = 1306.29 

 BMDU = 8354.46 

Taken together, (1306.29, 8354.46) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 7.65529e-005 

 D-56 
 

D.7.2. Nasal Cavity Squamous Cell Carcinoma and Liver Hepatocellular Adenoma in 

Osborne-Mendel Rats (NCI, 1978, 062935) 

The incidence data for hepatocellular adenoma (female rats) and nasal squamous cell 

carcinoma (male and female rats) are presented in Table D-20. The log-logistic model 

adequately fit both the male and female rat nasal squamous cell carcinoma data, as well as 

female hepatocellular adenoma incidence data. For all endpoints and genders evaluated in this 

section, compared to the multistage models, the log-logistic model had a higher p-value, as well 

as both a lower AIC and lower BMDL. The results of the BMDS modeling for the entire suite of 

models are presented in Tables D-21 through D-23. 

Table D-20. Incidence of nasal cavity squamous cell carcinoma and 

hepatocellular adenoma in Osborne-Mendel rats (NCI, 1978, 062935) 

exposed to 1,4-dioxane in the drinking water 

Male rat Animal Dose (mg/kg-day)a

0 240b 530 

Nasal cavity squamous cell carcinoma 0/33c 12/26d 16/33d

Female rat Animal Dose (mg/kg-day)a

0 350 640 

Nasal cavity squamous cell carcinoma 0/34c 10/30d 8/29d

Hepatocellular adenoma 0/31c 10/30d 11/29d

a

Tumor incidence values were adjusted for mortality (animals surviving to 52 weeks, presented in text of 

NCI, 1978, 062935). b

Group not included in statistical analysis by NCI (1978, 062935) because the dose group was started a 

year earlier without appropriate controls. 

c

p ≤ 0.001; positive dose-related trend (Cochran-Armitage test). d

p ≤ 0.001; Fisher’s Exact test. 

Source: NCI (1978, 062935).

 D-57 
 

Table D-21. BMDS dose-response modeling results for the incidence of 

hepatocellular adenoma in female Osborne-Mendel rats (NCI, 1978, 062935) 

exposed to 1,4-dioxane in the drinking water for 2 years

Model AIC p-value 

BMD10

mg/kg-day

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 84.6972 0.5908 132.36 94.06 0 34.144 24.26 

Logistic 92.477 0.02 284.09 220.46 1.727 73.29 56.87 

LogLogisticb 84.2821 0.7333 111.46 72.41 0 28.75 18.68 

LogProbit 85.957 0.3076 209.47 160.66 1.133 54.04 41.45 

Multistage-Cancer 

(1 degree) 84.6972 0.5908 132.36 94.06 0 34.14 24.26 

Multistage-Cancer 

(2 degree) 84.6972 0.5908 132.36 94.06 0 34.14 24.26 

Probit 91.7318 0.0251 267.02 207.18 1.7 68.88 53.44 

Weibull 84.6972 0.5908 132.36 94.06 0 34.14 24.26 

Quantal-Linear 84.6972 0.5908 132.36 94.06 0 34.14 24.26 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model. 

 D-58 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

06:32 10/27 2009

BMDL BMD

 

Log-Logistic

 

Source: NCI (1978, 062935).

Figure D-19. LogLogistic BMD model for the incidence of hepatocellular 

adenoma in female Osborne-Mendel rats exposed to 1,4-dioxane in drinking 

water. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_hepato_ad_Lnl-BMR10-

Restrict.(d) 

Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_hepato_ad_LnlBMR10-Restrict.plt 

Tue Oct 27 07:32:13 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is restricted as slope >= 1 

Total number of observations = 3 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

User has chosen the log transformed model 

 D-59 
 

Default Initial Parameter Values 

background = 0 

intercept = -6.62889 

slope = 1 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -background -slope have been estimated at a boundary 

point, or have been specified by the user, and do not appear in the correlation 

matrix) 

 intercept 

 intercept 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0 * * * 

intercept -6.91086 * * * 

slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -40.8343 3 

 Fitted model -41.141 1 0.613564 2 0.7358 

 Reduced model -50.4308 1 19.1932 2 <.0001 

 AIC: 84.2821 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 31 0.000 

 350.0000 0.2587 8.536 10.000 33 0.582 

 640.0000 0.3895 12.464 11.000 32 -0.531 

 Chi^2 = 0.62 d.f. = 2 P-value = 0.7333 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 111.457 

 BMDL = 72.4092 

 D-60 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

06:32 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 

Source: NCI (1978, 062935). 

Figure D-20. Multistage BMD model (1 degree) for the incidence of 

hepatocellular adenoma in female Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_hepato_ad_Msc-BMR10-

1poly.(d) 

Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_hepato_ad_MscBMR10-1poly.plt 

Tue Oct 27 07:32:16 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 3 

Total number of records with missing values = 0 

Total number of parameters in model = 2 

Total number of specified parameters = 0 

Degree of polynomial = 1 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

 D-61 
 

Default Initial Parameter Values 

Background = 0.0385912 

Beta(1) = 0.000670869 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix) 

 Beta(1) 

 Beta(1) 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 0.00079602 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -40.8343 3 

 Fitted model -41.3486 1 1.02868 2 0.5979 

 Reduced model -50.4308 1 19.1932 2 <.0001 

 AIC: 84.6972 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 31 0.000 

 350.0000 0.2432 8.024 10.000 33 0.802 

 640.0000 0.3992 12.774 11.000 32 -0.640 

 Chi^2 = 1.05 d.f. = 2 P-value = 0.5908 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 132.359 

 BMDL = 94.0591 

 BMDU = 194.33 

Taken together, (94.0591, 194.33 ) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00106316 

 D-62 
 

Table D-22. BMDS dose-response modeling results for the incidence of nasal 

cavity squamous cell carcinoma in female Osborne-Mendel rats (NCI, 1978, 

062935) exposed to 1,4-dioxane in the drinking water for 2 years 

Model AIC p-value 

BMD10

mg/kg-day

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 84.7996 0.1795 176.28 122.27 1.466 45.47 31.54 

Logistic 92.569 0.0056 351.51 268.75 2.148 90.68 69.33 

LogLogisticb 84.2235 0.2486 155.32 100.08 0 40.07 25.82 

LogProbitc 87.3162 0.0473 254.73 195.76 1.871 65.71 50.50 

Multistage-Cancer 

(1 degree) 84.7996 0.1795 176.28 122.27 1.466 45.47 31.54 

Multistage-Cancer 

(2 degree) 84.7996 0.1795 176.28 122.27 1.466 45.47 31.54 

Probit 91.9909 0.0064 328.46 251.31 2.136 84.73 64.83 

Weibull 84.7996 0.1795 176.28 122.27 1.466 45.47 31.54 

Quantal-Linear 84.7996 0.1795 176.28 122.27 1.466 45.47 31.54 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model. 

c

Slope restricted ≥ 1. 

 D-63 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

06:30 10/27 2009

BMDL BMD

 

Log-Logistic

Source: NCI (1978, 062935). 

Figure D-21. LogLogistic BMD model for the incidence of nasal cavity 

squamous cell carcinoma in female Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_nasal_car_Lnl-BMR10-

Restrict.(d) 

Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_nasal_car_LnlBMR10-Restrict.plt 

Tue Oct 27 07:30:09 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is restricted as slope >= 1 

Total number of observations = 3 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

 D-64 
 

User has chosen the log transformed model 

Default Initial Parameter Values 

background = 0 

intercept = -6.64005 

slope = 1 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -background -slope have been estimated at a boundary 

point, or have been specified by the user, and do not appear in the correlation 

matrix) 

 intercept 

 intercept 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0 * * * 

intercept -7.24274 * * * 

slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -39.7535 3 

 Fitted model -41.1117 1 2.71651 2 0.2571 

 Reduced model -47.9161 1 16.3252 2 0.0002851 

 AIC: 84.2235 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 34 0.000 

 350.0000 0.2002 7.008 10.000 35 1.264 

 640.0000 0.3140 10.992 8.000 35 -1.090 

 Chi^2 = 2.78 d.f. = 2 P-value = 0.2486 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 155.324 

 BMDL = 100.081 

 D-65 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

06:30 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: NCI (1978, 062935). 

Figure D-22. Multistage BMD model (1 degree) for the incidence of nasal 

cavity squamous cell carcinoma in female Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_nasal_car_Msc-BMR10-

1poly.(d) 

Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_nasal_car_MscBMR10-1poly.plt 

Tue Oct 27 07:30:12 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 3 

Total number of records with missing values = 0 

Total number of parameters in model = 2 

Total number of specified parameters = 0 

Degree of polynomial = 1 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

 D-66 
 

Default Initial Parameter Values 

Background = 0.0569154 

Beta(1) = 0.00042443 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix) 

 Beta(1) 

 Beta(1) 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 0.000597685 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -39.7535 3 

 Fitted model -41.3998 1 3.29259 2 0.1928 

 Reduced model -47.9161 1 16.3252 2 0.0002851 

 AIC: 84.7996 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 34 0.000 

 350.0000 0.1888 6.607 10.000 35 1.466 

 640.0000 0.3179 11.125 8.000 35 -1.134 

 Chi^2 = 3.44 d.f. = 2 P-value = 0.1795 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 176.281 

 BMDL = 122.274 

 BMDU = 271.474 

Taken together, (122.274, 271.474) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.000817837 

 D-67 
 

Table D-23. BMDS dose-response modeling results for the incidence of nasal 

cavity squamous cell carcinoma in male Osborne-Mendel rats (NCI, 1978, 

062935) exposed to 1,4-dioxane in the drinking water for 2 years 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 93.6005 0.5063 73.94 54.724 0 21.17 15.66 

Logistic 103.928 0.0061 179.05 139.26 2.024 51.25 39.86 

LogLogisticb 92.7669 0.7809 56.26 37.26 0 16.10 10.66 

LogProbitc 95.0436 0.2373 123.87 95.82 1.246 35.46 27.43 

Multistage-Cancer 

(1 degree) 93.6005 0.5063 73.94 54.72 0 21.16 15.66 

Multistage-Cancer 

(2 degree) 93.6005 0.5063 73.94 54.72 0 21.16 15.66 

Probit 103.061 0.0078 168.03 131.61 2.024 48.10 37.67 

Weibull 93.6005 0.5063 73.94 54.72 0 21.17 15.66 

Quantal-Linear 93.6005 0.5063 73.94 54.72 0 21.17 15.66 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model. 

c

Slope restricted ≥ 1.

 D-68 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

06:27 10/27 2009

BMDL BMD

 

Log-Logistic

Source: NCI (1978, 062935). 

Figure D-23. LogLogistic BMD model for the incidence of nasal cavity 

squamous cell carcinoma in male Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Logistic Model. (Version: 2.12; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_mrat_nasal_car_Lnl-BMR10-

Restrict.(d) 

Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_mrat_nasal_car_LnlBMR10-Restrict.plt 

Tue Oct 27 07:27:57 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

Dependent variable = Effect 

Independent variable = Dose 

Slope parameter is restricted as slope >= 1 

Total number of observations = 3 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

User has chosen the log transformed model 

 D-69 
 

Default Initial Parameter Values 

background = 0 

intercept = -6.08408 

slope = 1 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -background -slope have been estimated at a boundary 

point, or have been specified by the user, and do not appear in the correlation 

matrix) 

 intercept 

 intercept 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

background 0 * * * 

intercept -6.2272 * * * 

slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -45.139 3 

 Fitted model -45.3835 1 0.488858 2 0.7832 

 Reduced model -59.2953 1 28.3126 2 <.0001 

 AIC: 92.7669 

Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 33 0.000 

 240.0000 0.3216 10.612 12.000 33 0.517 

 530.0000 0.5114 17.388 16.000 34 -0.476 

 Chi^2 = 0.49 d.f. = 2 P-value = 0.7809 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 56.2596 

 BMDL = 37.256 

 D-70 
 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

06:28 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: NCI (1978, 062935). 

Figure D-24. Multistage BMD model (1 degree) for the incidence of nasal 

cavity squamous cell carcinoma in male Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mrat_nasal_car_Msc-BMR10-

1poly.(d) 

Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mrat_nasal_car_MscBMR10-1poly.plt 

 Tue Oct 27 07:28:00 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 3 

Total number of records with missing values = 0 

Total number of parameters in model = 2 

Total number of specified parameters = 0 

Degree of polynomial = 1 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

 D-71 
 

Background = 0.0578996 

Beta(1) = 0.00118058 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix) 

 Beta(1) 

 Beta(1) 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 0.00142499 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -45.139 3 

 Fitted model -45.8002 1 1.32238 2 0.5162 

 Reduced model -59.2953 1 28.3126 2 <.0001 

 AIC: 93.6005 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 33 -0.000 

 240.0000 0.2896 9.558 12.000 33 0.937 

 530.0000 0.5301 18.024 16.000 34 -0.695 

 Chi^2 = 1.36 d.f. = 2 P-value = 0.5063 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 73.9379 

 BMDL = 54.7238 

 BMDU = 103.07 

Taken together, (54.7238, 103.07 ) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00182736 

 D-72 
 

D.7.3. Hepatocellular Adenoma or Carcinoma in B6C3F1 Mice (NCI, 1978, 062935) 

The incidence data for hepatocellular adenoma or carcinoma in male and female 

mice are presented in Table D-24. The 2-degree polynomial model (betas restricted ≥ 0) 

was the lowest degree polynomial that provided an adequate fit to the female mouse data 

(Figure D-25), while the gamma model provided the best fit to the male mouse data 

(Figure D-26). The results of the BMDS modeling for the entire suite of models are 

presented in Tables D-25 and D-26 for the female and male data, respectively. 

Table D-24. Incidence of hepatocellular adenoma or carcinoma in male and 

female B6C3F1 mice (NCI, 1978, 062935) exposed to 1,4-dioxane in drinking 

water 

Male mouse Animal Dose (mg/kg-day)a Female mouse Animal Dose (mg/kg-day)a

0 720 830 0 380 860 

8/49b 19/50d 28/47c 0/50b 21/48c 35/37c

a

Tumor incidence values were not adjusted for mortality. 

b

p < 0.001, positive dose-related trend (Cochran-Armitage test). c

p < 0.001 by Fisher’s Exact test pair-wise comparison with controls. d

p = 0.014. 

Source: NCI (1978, 062935). 

 D-73 
 

Table D-25. BMDS dose-response modeling results for the combined 

incidence of hepatocellular adenoma or carcinoma in female B6C3F1 mice 

(NCI, 1978, 062935) exposed to 1,4-dioxane in the drinking water for 2 years 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gamma 85.3511 1 195.69 105.54 0 28.16 15.19 

Logistic 89.1965 0.0935 199.63 151.35 0.675 28.72 21.78 

LogLogistic 85.3511 1 228.08 151.16 0 32.82 21.75 

LogProbitb 85.3511 1 225.8 150.91 0 32.49 21.71 

Multistage-Cancer 

(1 degree) 89.986 0.0548 49.10 38.80 0 7.06 5.58 

Multistage-Cancer 

(2 degree)c 85.3511 1 160.68 67.76 0 23.12 9.75 

Probit 88.718 0.1165 188.24 141.49 -1.031 27.08 20.36 

Weibull 85.3511 1 161.77 89.27 0 23.28 12.84 

Quantal-Linear 89.986 0.0548 49.10 38.80 0 7.065 5.58 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Slope restricted ≥ 1. c

Best-fitting model.

 D-74 
 

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 100 200 300 400 500 600 700 800 900

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

06:36 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: NCI (1978, 062935). 

Figure D-25. Multistage BMD model (2 degree) for the incidence of 

hepatocellular adenoma or carcinoma in female B6C3F1 mice exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_fmouse_hepato_adcar_MscBMR10-2poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_fmouse_hepato_adcar_Msc-BMR10-2poly.plt 

Tue Oct 27 07:36:26 2009 

==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 3 

Total number of records with missing values = 0 

Total number of parameters in model = 3 

Total number of specified parameters = 0 

Degree of polynomial = 2 

Maximum number of iterations = 250 

 D-75 
 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

Background = 0 

Beta(1) = 2.68591e-005 

Beta(2) = 3.91383e-006 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Background have been estimated at a boundary point, or 

have been specified by the user, and do not appear in the correlation matrix) 

 Beta(1) Beta(2) 

 Beta(1) 1 -0.92 

 Beta(2) -0.92 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0 * * * 

Beta(1) 2.686e-005 * * * 

Beta(2) 3.91382e-006 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -40.6756 3 

 Fitted model -40.6756 2 3.20014e-010 1 1 

 Reduced model -91.606 1 101.861 2 <.0001 

 AIC: 85.3511 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0.000 50 0.000 

 380.0000 0.4375 21.000 21.000 48 0.000 

 860.0000 0.9459 35.000 35.000 37 0.000 

 Chi^2 = 0.00 d.f. = 1 P-value = 1.0000 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 160.678 

 BMDL = 67.7635 

 BMDU = 186.587 

Taken together, (67.7635, 186.587) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.00147572 

 D-76 
 

Table D-26. BMDS dose-response modeling results for the combined 

incidence of hepatocellular adenoma or carcinoma in male B6C3F1 mice 

(NCI, 1978, 062935) exposed to 1,4-dioxane in drinking water 

Model AIC p-value 

BMD10

mg/kg-day 

BMDL10

mg/kg-day χ2a

BMD10 HED 

mg/kg-day 

BMDL10 HED 

mg/kg-day 

Gammab 177.539 0.7571 601.69 243.92 -0.233 87.98 35.67 

Logistic 179.9 0.1189 252.66 207.15 0.214 36.94 30.29 

LogLogistic 179.443 NCc 622.39 283.04 0 91.01 41.39 

LogProbitd 179.443 NCc 631.51 305.44 0 92.34 44.66 

Multistage-Cancer 

(1 degree) 180.618 0.0762 164.29 117.37 0.079 24.02 17.16 

Multistage-Cancer 

(2 degree) 179.483 0.1554 354.41 126.24 0.124 51.82 18.46 

Probit 179.984 0.1128 239.93 196.90 0.191 35.08 28.79 

Weibull 179.443 NCc 608.81 249.71 0 89.02 36.51 

Quantal-Linear 180.618 0.0762 164.29 117.37 0.079 24.02 17.16 

a

Maximum absolute χ

2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable. 

b

Best-fitting model. 

c

Value unable to be calculated (NC: not calculated) by BMDS. d

Slope restricted ≥ 1.

 D-77 
 

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500 600 700 800

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

06:34 10/27 2009

BMDL BMD

 

Gamma Multi-Hit

Source: NCI (1978, 062935). 

Figure D-26. Gamma BMD model for the incidence of hepatocellular 

adenoma or carcinoma in male B6C3F1 mice exposed to 1,4-dioxane in 

drinking water. 

==================================================================== 

Gamma Model. (Version: 2.13; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\gam_nci_mmouse_hepato_adcar_GamBMR10-Restrict.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\gam_nci_mmouse_hepato_adcar_Gam-BMR10-Restrict.plt 

Tue Oct 27 07:34:35 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: 

P[response]= background+(1-background)*CumGamma[slope*dose,power], 

where CumGamma(.) is the cummulative Gamma distribution function 

Dependent variable = Effect 

Independent variable = Dose 

Power parameter is restricted as power >=1 

Total number of observations = 3 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial (and Specified) Parameter Values 

Background = 0.17 

Slope = 0.000671886 

Power = 1.3 

 D-78 
 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Power have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix) 

 Background Slope 

Background 1 -0.52 

 Slope -0.52 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.160326 0.0510618 0.060247 0.260405 

Slope 0.0213093 0.000971596 0.019405 0.0232136 

Power 18 NA 

NA - Indicates that this parameter has hit a bound implied by some inequality 

constraint and thus has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -86.7213 3 

 Fitted model -86.7693 2 0.096042 1 0.7566 

 Reduced model -96.715 1 19.9875 2 <.0001 

 AIC: 177.539 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1603 7.856 8.000 49 0.056 

 720.0000 0.3961 19.806 19.000 50 -0.233 

 830.0000 0.5817 27.339 28.000 47 0.196 

 Chi^2 = 0.10 d.f. = 1 P-value = 0.7571 

Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 601.692 

 BMDL = 243.917 

 D-79 
 

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500 600 700 800

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

06:34 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Source: NCI (1978, 062935). 

Figure D-27. Multistage BMD model (2 degree) for the incidence of 

hepatocellular adenoma or carcinoma in male B6C3F1 mice exposed to 

1,4-dioxane in drinking water. 

==================================================================== 

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mmouse_hepato_adcar_MscBMR10-2poly.(d) 

Gnuplot Plotting File: 

L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mmouse_hepato_adcar_Msc-BMR10-2poly.plt 

Tue Oct 27 07:34:42 2009 

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

The form of the probability function is: P[response] = background + (1-background)*[1-

EXP(-beta1*dose^1-beta2*dose^2)] 

The parameter betas are restricted to be positive 

Dependent variable = Effect 

Independent variable = Dose 

Total number of observations = 3 

Total number of records with missing values = 0 

Total number of parameters in model = 3 

Total number of specified parameters = 0 

Degree of polynomial = 2 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

 D-80 
 

Background = 0.131156 

Beta(1) = 0 

Beta(2) = 9.44437e-007 

Asymptotic Correlation Matrix of Parameter Estimates 

(*** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have 

been specified by the user, and do not appear in the correlation matrix) 

 Background Beta(2) 

Background 1 -0.72 

 Beta(2) -0.72 1 

Parameter Estimates 

 95.0% Wald Confidence Interval 

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

Background 0.1568 * * * 

Beta(1) 0 * * * 

Beta(2) 8.38821e-007 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -86.7213 3 

 Fitted model -87.7413 2 2.04001 1 0.1532 

 Reduced model -96.715 1 19.9875 2 <.0001 

 AIC: 179.483 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1568 7.683 8.000 49 0.124 

 720.0000 0.4541 22.707 19.000 50 -1.053 

 830.0000 0.5269 24.764 28.000 47 0.946 

 Chi^2 = 2.02 d.f. = 1 P-value = 0.1554 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 354.409 

 BMDL = 126.241 

 BMDU = 447.476 

Taken together, (126.241, 447.476) is a 90% two-sided confidence interval for the BMD 

Multistage Cancer Slope Factor = 0.000792138

 D-81 
 

APPENDIX E. COMPARISON OF SEVERAL DATA REPORTS FOR THE JBRC 

2-YEAR 1,4-DIOXANE DRINKING WATER STUDY 

As described in detail in Section 4.2.1.2.6 of this Toxicological Review of 1,4-Dioxane, 

the JBRC conducted a 2-year drinking water study on the effects of 1,4-dioxane in both sexes of 

rats and mice. The results from this study have been reported three times, once as conference 

proceedings (Yamazaki et al., 1994, 196120), once as a detailed laboratory report (JBRC, 1998, 

196240), and once as a published manuscript (Kano et al., 2009, 594539). After the External 

Peer Review draft of the Toxicological Review of 1,4-Dioxane (U.S. EPA, 2009, 628630) had 

been released, the Kano et al. (2009, 594539) manuscript was published; thus, minor changes to 

the Toxicological Review of 1,4-Dioxane occurred. 

The purpose of this appendix is to provide a clear and transparent comparison of the 

reporting of this 2-year 1,4-dioxane drinking water study. The variations included: (1) the level 

of detail on dose information reported; (2) categories for incidence data reported (e.g., all 

animals or sacrificed animals); and (3) analysis of non- and neoplastic lesions. Even though the 

data contained in the reports varied, the differences were minor and did not did not significantly 

affect the qualitative or quantitative cancer assessment. 

Tables contained within this appendix provide a comparison of the variations in the 

reported data (JBRC, 1998, 196240; Kano et al., 2009, 594539; Yamazaki et al., 1994, 196120). 

Tables E-1 and E-2 show the histological nonneoplastic findings provided for male and female 

F344 rats, respectively. Tables E-3 and E-4 show the histological neoplastic findings provided 

for male and female F344 rats, respectively. Tables E-5 and E-6 show the histological 

nonneoplastic findings provided for male and female F344 rats, respectively. Tables E-7 and E-8 

show the histological neoplastic findings provided for male and female Crj:BDF1 mice, 

respectively. 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database 

(Health and Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used 

by U.S. EPA in the process of developing science assessments such as the Integrated Science Assessments (ISA)

and the Integrated Risk Information System (IRIS)

 E-1 
 

Table E-1. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in male F344 rats 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

 Drinking water concentration (ppm) 

0 200 1,000 5,000 0 200 1,000 5,000 0 200 1,000 5,000 

Calculated Dose (Intake [mg/kg-day])b,c 

 Not reported Control 

(0) 

8-24 

(16) 

41-121

(81) 

209-586 

(398) 

0 11±1 55±3 274±18

All animals Not reported 0/50 0/50 0/50 26/50 0/50 0/50 0/50 26/50e Nasal 

respiratory 

epithelium; 

nuclear 

enlargement 

Sacrificed 

animals Not reported 0/40 0/45 0/35 12/22e Not reported 

All animals 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50e Nasal 

respiratory 

epithelium; 

squamous cell 

metaplasia 

Sacrificed 

animals Not reported 0/40 0/45 0/35 15/22e Not reported 

Nasal All animals 0/50 0/50 0/50 2/50 0/50 0/50 0/50 2/50 0/50 0/50 0/50 2/50 

respiratory 

epithelium; 

squamous cell 

hyperplasia 

Sacrificed 

animals Not reported 0/40 0/45 0/35 1/22 Not reported 

Nasal gland; All animals 0/50 0/50 0/50 5/50 Not reported Not reported proliferation 

Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported 0/50 0/50 5/50 38/50 0/50 0/50 5/50 38/50e Nasal olfactory 

epithelium; 

nuclear 

enlargement Sacrificed 

animals Not reported 0/40 0/45 4/35 20/22e Not reported 

Nasal olfactory All animals Not reported 12/50 11/50 20/50 43/50 Not reported epithelium; 

respiratory 

metaplasia Sacrificed 

animals Not reported 10/40 11/45 17/35 22/22e Not reported 

Nasal olfactory All animals Not reported 0/50 0/50 0/50 36/50 Not reported epithelium; 

atrophy Sacrificed 

animals Not reported 0/40 0/45 0/35 17/22e Not reported 

Lamina propria; All animals Not reported 0/50 0/50 0/50 46/50 Not reported hydropic 

change Sacrificed 

animals Not reported 0/40 0/45 0/35 20/22e Not reported 

Lamina propria; All animals Not reported 0/50 0/50 1/50 44/50 Not reported sclerosis 

Sacrificed 

animals Not reported 0/40 0/45 1/35 20/22e Not reported 

Nasal cavity; All animals Not reported 0/50 0/50 0/50 48/50 Not reported adhesion 

Sacrificed 

animals Not reported 0/40 0/45 0/35 21/22e Not reported 

Nasal cavity; All animals Not reported 0/50 0/50 0/50 13/50 Not reported inflammation 

Sacrificed 

animals Not reported 0/40 0/45 0/35 7/22e Not reported 

Hyperplasia; All animals 3/50 2/10 10/50 24/50 3/50 2/50 10/50 24/50 Not reported liver 

Sacrificed 

animals Not reported 3/40 2/45 9/35f 12/22e Not reported 

 E-2 
 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

Spongiosis All animals 12/50 20/50 25/50 40/50 12/50 20/50 25/50 40/50 Not reported hepatis; liver 

Sacrificed 

animals Not reported 12/40 20/45 21/35f 21/22e Not reported 

Clear cell foci; All animals Not reported 3/50 3/50 9/50 8/50 3/50 3/50 9/50 8/50 

liver 

Sacrificed 

animals Not reported 3/40 3/45 9/35f 7/22e Not reported 

Acidophilic cell All animals Not reported Not reported 12/50 8/50 7/50 5/50 

foci; liver 

Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported 7/50 11/50 6/50 16/50 7/50 11/50 8/50 16/50f Basophilic cell 

foci; liver 

Sacrificed 

animals Not reported 7/40 11/45 6/35 8/22f Not reported 

All animals Not reported 2/50 8/50 14/50 13/50 2/50 8/50 14/50e 13/50e Mixed-cell foci; 

liver 

Sacrificed 

animals Not reported 2/40 8/45 14/35e 22/22e Not reported 

Nuclear All animals Not reported 0/50 0/50 0/50 50/50 Not reported enlargement; 

kidney proximal 

tubule Sacrificed 

animals Not reported 0/40 0/45 0/35 22/22e Not reported 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994). Drinking water concentrations of 1,4-dioxane were used to 

identify the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in this final document (U.S. EPA, 2010, 625580). d

JBRC did not report statistical significance for the “All animals” comparison. e

p ≤ 0.01 by χ2 test. f

p ≤ 0.05 by χ2 test. 

Table E-2. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in female F344 rats 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

 Drinking water concentration (ppm) 

0 200 1,000 5,000 0 200 1,000 5,000 0 200 1,000 5,000 

Calculated Dose (Intake [mg/kg-day])b,c 

 Not reported Control

(0) 

12-29

(21) 

56-149

(103) 

307-720 

(514) 0 18±3 83±14 429±69

All animals Not reported 0/50 0/50 0/50 13/50 0/50 0/50 0/50 13/50e

Nasal respiratory 

epithelium; nuclear 

enlargement Sacrificed 

animals Not reported 0/38 0/37 0/38 7/24e Not reported 

All animals 0/50 0/50 0/50 35/50 0/50 0/50 0/50 35/50 0/50 0/50 0/50 35/50e Nasal respiratory 

epithelium; 

squamous cell 

metaplasia 

Sacrificed 

animals Not reported 0/38 0/37 0/38 18/24e Not reported 

Nasal respiratory All animals 0/50 0/50 0/50 5/50 0/50 0/50 0/50 5/50 0/50 0/50 0/50 5/50 

epithelium; 

squamous cell 

hyperplasia 

Sacrificed 

animals Not reported 0/38 0/37 0/38 4/24f Not reported 

Nasal gland; All animals 0/50 0/50 0/50 11/50 0/50 0/50 0/50 11/50 Not reported 

 E-3 
 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

proliferation Sacrificed 

animals Not reported 0/38 0/37 0/38 8/24e Not reported 

All animals Not reported 0/50 0/50 28/50 39/50 0/50 0/50 28/50e 39/50e

Nasal olfactory 

epithelium; nuclear 

enlargement Sacrificed 

animals Not reported 0/38 0/37 24/38e 22/24e Not reported 

Nasal olfactory All animals Not reported 2/50 0/50 2/50 42/50 Not reported epithelium; 

respiratory 

metaplasia 

Sacrificed 

animals Not reported 1/38 0/37 1/38 24/24e Not reported 

All animals Not reported 0/50 0/50 1/50 40/50 Not reported Nasal olfactory 

epithelium; atrophy Sacrificed 

animals Not reported 0/38 0/37 1/38 22/24e Not reported 

All animals Not reported 0/50 0/50 0/50 46/50 Not reported Lamina propria; 

hydropic change Sacrificed 

animals Not reported 0/38 0/37 0/38 23/24e Not reported 

All animals Not reported 0/50 0/50 0/50 48/50 Not reported Lamina propria; 

slerosis Sacrificed 

animals Not reported 0/38 0/37 0/38 23/24e Not reported 

All animals Not reported 0/50 0/50 0/50 46/50 Not reported Nasal cavity; 

adhesion Sacrificed 

animals Not reported 0/38 0/37 0/38 24/24e Not reported 

All animals Not reported 0/50 0/50 1/50 15/50 Not reported Nasal cavity; 

inflammation Sacrificed 

animals Not reported 0/38 0/37 1/38 7/24e Not reported 

All animals 3/50 2/50 11/50 47/50 3/50 2/50 11/50 47/50 Not reported 

Liver; hyperplasia Sacrificed 

animals Not reported 2/38 2/37 9/38 24/24e Not reported 

All animals 0/50 0/50 1/50 20/50 0/50 0/50 1/50 20/50 Not reported Liver; spongiosis 

hepatis Sacrificed 

animals Not reported 0/38 0/37 1/38 14/24e Not reported 

All animals Not reported 0/50 1/50 1/50 8/50 Not reported Liver; cyst 

formation Sacrificed 

animals Not reported 0/38 1/37 0/38 5/24f Not reported 

All animals Not reported Not reported 1/50 1/50 5/50 4/50 

Liver; clear cell foci Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported Not reported 1/50 1/50 1/50 1/50 Liver; acidophilic 

cell foci Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported Not reported 23/50 27/50 31/50 8/50e

Liver; basophilic 

cell foci Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported 1/50 1/50 3/50 11/50 1/50 1/50 3/50 11/50f

Liver; mixed-cell 

foci Sacrificed 

animals Not reported 1/38 1/37 3/38 7/24f Not reported 

Kidney proximal All animals Not reported 0/50 0/50 6/50 39/50 Not reported 

tubule; nuclear 

enlargement Sacrificed 

animals Not reported 0/38 0/37 6/38 22/24e Not reported 

 E-4 
 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994). Drinking water concentrations of 1,4-dioxane were used to identify 

the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in 

this final document (U.S. EPA, 2010, 625580). d

JBRC did not report statistical significance for the “All animals” comparison. e

p ≤ 0.01 by χ2 test. f

p ≤ 0.05 by χ2 test. 

Table E-3. Neoplastic lesions: Comparison of histological findings reported 

for the 2-year JBRC drinking water study in male F344 rats 

Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

Drinking water concentration (ppm) 

0 200 1,000 5,000 0 200 1,000 5,000 0 200 1,000 5,000 

Calculated Dose (Intake [mg/kg-day])b,c

Not reported Control 

(0) 

8-24

(16) 

41-121

(81) 

209-586

(398) 0 11±1 55±3 274±18 

Nasal cavity 

All animals 0/50 0/50 0/50 3/50 0/50 0/50 0/50 3/50e 0/50 0/50 0/50 3/50e

Squamous cell carcinoma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 0/50 0/50 2/50 0/50 0/50 0/50 2/50 0/50 0/50 0/50 2/50 Sarcoma NOS 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 Rabdomyosarcoma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 Esthesioneuroepithelioma 

 Sacrificed 

animals Not reported Not reported Not reported 

Liver 

All animals 0/50 2/50 4/50 24/50 0/50 2/50 4/49 24/50d,e 3/50 4/50 7/50 32/50d,e

Hepatocellular adenoma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 0/50 0/50 14/50 0/50 0/50 0/49 14/50d,e 0/50 0/50 0/50 14/50d,e

Hepatocellular carcinoma 

 Sacrificed 

animals Not reported Not reported Not reported 

 E-5 
 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

All animals Not reported 0/50 2/50 4/49 33/50d,e 3/50 4/50 7/50 39/50d,e

Hepatocellular adenoma 

or carcinoma Sacrificed 

animals Not reported Not reported Not reported 

Tumors at other sites 

All animals 2/50 2/50 5/50 28/50 2/50 2/50 5/50 28/50d,e 2/50 2/50 5/50 28/50d,e Peritoneum 

mesothelioma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 5/50 3/50 5/50 12/50 5/50 3/50 5/50 12/50e 5/50 3/50 5/50 12/50e

Subcutis fibroma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 1/50 1/50 0/50 4/50 1/50 1/50 0/50 4/50e 1/50 1/50 0/50 4/50e Mammary gland 

fibroadenoma 

 Sacrificed 

animals Not reported Not reported Not reported 

Mammary gland All animals 0/50 0/50 0/50 0/50 Not reported 0/50 1/50 2/50 2/50 

adenoma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported Not reported 1/50 2/50 2/50 6/50e

Mammary gland 

fibroadenoma 

or adenoma Sacrificed 

animals Not reported Not reported Not reported 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994). Drinking water concentrations of 1,4-dioxane were used to 

identify the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in 

this final document (U.S. EPA, 2010, 625580). d

p ≤ 0.01 by Fisher's Exact test. e

Significantly increased by Peto test for trend p < 0.01. 

Table E-4. Neoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in female F344 rats 

Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

Drinking water concentration (ppm) 

0 200 1,000 5,000 0 200 1,000 5,000 0 200 1,000 5,000 

Calculated Dose (Intake [mg/kg-day])b,c 

Not Reported Control

(0) 

12-29 

(21) 

56-149

(103) 

307-720 

(514) 

0 18±3 83±14 429±69

Nasal cavity 

All animals 0/50 0/50 0/50 7/50 0/50 0/50 0/50 7/50d,f 0/50 0/50 0/50 7/50e,f Squamous cell 

carcinoma 

 Sacrificed 

animals Not reported Not reported Not reported 

Sarcoma NOS All animals 0/50 0/50 0/50 0/50 Not reported 0/50 0/50 0/50 0/50 

 Sacrificed 

animals Not reported Not reported Not reported 

 E-6 
 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

Rabdomyosarcoma All animals 0/50 0/50 0/50 0/50 Not reported 0/50 0/50 0/50 0/50 

 Sacrificed 

animals Not reported Not reported Not reported 

Esthesioneuroepithelio All animals 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 

ma 

 Sacrificed 

animals Not reported Not reported Not reported 

Liver 

All animals 1/50 0/50 5/50 38/50 1/50 0/50 5/50 38/50e,f 3/50 1/50 6/50 48/50e,f Hepatocellular 

adenoma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 0/50 0/50 10/50 1/50 0/50 0/50 10/50e,f 0/50 0/50 0/50 10/50e,f Hepatocellular 

carcinoma 

 Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported 1/50 0/50 5/50 40/50e,f 3/50 1/50 6/50 48/50e,f Hepatocellular 

adenoma or carcinoma 

Sacrificed 

animals Not reported Not reported Not reported 

Tumors at other sites 

Peritoneum All animals 1/50 0/50 0/50 0/50 Not reported 1/50 0/50 0/50 0/50 

mesothelioma 

Sacrificed 

animals Not reported Not reported Not reported 

Subcutis fibroma All animals 0/50 2/50 1/50 0/50 Not reported 0/50 2/50 1/50 0/50 

Sacrificed 

animals Not reported Not reported Not reported 

Mammary gland All animals 3/50 2/50 1/50 3/50 Not reported 3/50 2/50 1/50 3/50 

fibroadenoma 

Sacrificed 

animals Not reported Not reported Not reported 

All animals 6/50 7/50 10/50 16/50 6/50 7/50 10/50 16/50d,f 6/50 7/50 10/50 16/50d,f Mammary gland 

adenoma 

Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported Not reported 8/50 8/50 11/50 18/50d,f Mammary gland 

fibroadenoma 

or adenoma Sacrificed 

animals Not reported Not reported Not reported 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994). Drinking water concentrations of 1,4-dioxane were used to identify 

the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in 

this final document (U.S. EPA, 2010, 625580). d

p ≤ 0.05 by Fisher's Exact test. e

p ≤ 0.01 by Fisher's Exact test. f

Significantly increased by Peto test for trend p < 0.01. 

 E-7 
 

Table E-5. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in male Crj:BDF1 mice 

 Yamazaki et al. (1994) JBRC (1998)d Kano et al. (2009) 

 Drinking water concentration (ppm) 

0 500 2,000 8,000 0 500 2,000 8,000 0 500 2,000 8,000 

Calculated Dose (Intake [mg/kg-day])b,c 

 Not reported Control

0 

37-94

(66) 

144-358

(251) 

451-1086 

(768) 0 49±5 191±21 677±74

All 

animals Not reported 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50e

Nasal respiratory epithelium; 

nuclear enlargement Sacrificed 

animals Not reported 0/31 0/33 0/25 19/26e Not reported 

All 

animals Not reported 0/50 0/50 9/50 49/50 0/50 0/50 9/50e 49/50e

Nasal olfactory epithelium; 

nuclear enlargement Sacrificed 

animals Not reported 0/31 0/33 7/25e 26/26e Not reported 

All 

animals Not reported 0/50 0/50 1/50 48/50 Not reported Nasal olfactory epithelium; 

atrophy Sacrificed 

animals Not reported 0/31 0/33 0/25 26/26e Not reported 

All 

animals Not reported 1/50 2/50 1/50 25/50 Not reported 

Nasal cavity; inflammation 

Sacrificed 

animals Not reported 1/31 1/33 1/25 15/26e Not reported 

All 

animals Not reported 0/50 0/50 0/50 42/50 Not reported 

Tracheal epithelium; atrophy 

Sacrificed 

animals Not reported 0/31 0/33 0/25 24/26e Not reported 

All 

animals Not reported 0/50 0/50 0/50 17/50 Not reported Tracheal epithelium; nuclear 

enlargement Sacrificed 

animals Not reported 0/31 0/33 0/25 12/26e Not reported 

All 

animals Not reported 0/50 0/50 0/50 41/50 Not reported Bronhcial epithelium; nuclear 

enlargement Sacrificed 

animals Not reported 0/31 0/33 0/25 24/26e Not reported 

All 

animals Not reported 0/50 0/50 0/50 43/50 Not reported 

Bronchial epithelium; atrophy 

Sacrificed 

animals Not reported 0/31 0/33 0/25 26/26e Not reported 

All 

animals Not reported 1/50 0/50 0/50 27/50 Not reported Lung/bronchial; accumlation of 

foamy cells Sacrificed 

animals Not reported 1/31 0/33 0/25 22/26e Not reported 

All 

animals Not reported 2/50 3/50 4/50 16/50 Not reported 

Liver; angiectasis 

Sacrificed 

animals Not reported 2/31 2/33 3/25 8/26f Not reported 

 E-8 
 

 Yamazaki et al. (1994) JBRC (1998)d Kano et al. (2009) 

All 

animals Not reported 0/50 0/50 0/50 39/50 Not reported Kidney proximal tubule; 

nuclear enlargement Sacrificed 

animals Not reported 0/31 0/33 0/25 22/26e Not reported 

All 

animals Not reported 40/50 42/50 38/50 34/50 Not reported 

Testis; mineralization 

Sacrificed 

animals Not reported 28/31 30/33 24/25f 21/26f Not reported 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994). Drinking water concentrations of 1,4-dioxane were used to identify 

the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in 

this final document (U.S. EPA, 2010, 625580). d

JBRC did not report statistical significance for the “All animals” comparison. e

p ≤ 0.01 by χ2 test. f

p ≤ 0.05 by χ2 test. 

 E-9 
 

Table E-6. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in female Crj:BDF1 mice 

 Yamazaki et al. (1994)

a JBRC (1998)b Kano et al. (2009) 

 Drinking water concentration (ppm) 

 0 500 2,000 8,000 0 500 2,000 8,000 0 500 2,000 8,000 

Calculated Dose (Intake [mg/kg-day])b,c

Not reported Control

0 

45-

109

(77) 

192-

454 

(323) 

759-

1374 

(1066) 

0 66 ± 

10 

278 ± 

40 

964 ± 

88 

All animals Not reported 0/50 0/50 0/50 41/50 0/50 0/50 0/50 41/50e

Nasal respiratory 

epithelium; Nuclear 

enlargement Sacrificed 

animals Not reported 0/29 0/29 0/17 5/5e Not reported 

All animals Not reported 0/50 0/50 41/50 33/50 0/50 0/50 41/50e 33/50e

Nasal olfactory 

epithelium; Nuclear 

enlargement Sacrificed 

animals Not reported 0/29 0/29 17/17e 1/5 Not reported 

All animals Not reported 0/50 0/50 0/50 26/50 Not reported Nasal respiratory 

epithelium; Atrophy Sacrificed 

animals Not reported 0/29 0/29 0/17 1/5 Not reported 

All animals Not reported 0/50 0/50 1/50 42/50 Not reported Nasal olfactory 

epithelium; Atrophy Sacrificed 

animals Not reported 0/29 0/29 0/17 5/5e Not reported 

All animals Not reported 2/50 0/50 7/50 42/50 Not reported Nasal cavity; 

Inflammation Sacrificed 

animals Not reported 0/29 0/29 5/17e 5/5e Not reported 

All animals Not reported 0/50 0/50 2/50 49/50 Not reported Tracheal epithelium; 

Atrophy Sacrificed 

animals Not reported 0/29 0/29 1/17 5/5e Not reported 

All animals Not reported 0/50 1/50 22/50 48/50 Not reported Bronhcial epithelium; 

Nuclear enlargement Sacrificed 

animals Not reported 0/29 1/29 13/17e 5/5e Not reported 

All animals Not reported 0/50 0/50 7/50 50/50 Not reported Bronchial epithelium; 

Atrophy Sacrificed 

animals Not reported 0/29 0/29 3/17 5/5e Not reported 

All animals Not reported 0/50 1/50 4/50 45/50 Not reported Lung/bronchial; 

Accumlation of 

foamy cells Sacrificed 

animals Not reported 0/29 1/29 3/17 5/5e Not reported 

All animals Not reported 0/50 0/50 0/50 8/50 Not reported Kidney proximal 

tubule; Nuclear 

enlargement Sacrificed 

animals Not reported 0/29 0/29 0/17 0/5 Not reported 

a

Dose rates mg/kg-day]) were not provided in Yamazaki et al. (1994, 196120). Drinking water concentrations (ppm) of 1,4-dioxane 

were used to identify the dose groups. Statistical test results were not reported. 

b

Statistical analysis was not performed for data on 'All animals' in the JBRC (1998, 196240) report. c

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . d

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in 

this final document (U.S. EPA, 2010, 625580). e

p ≤ 0.01 by chi-square test. 

 E-10 
 

Table E-7. Neoplastic lesions: Comparison of histological findings reported 

for the 2-year JBRC drinking water study in male Crj:BDF1 mice 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

 Drinking water concentration (ppm) 

 0 500 2,000 8,000 0 500 2,000 8,000 0 500 2,000 8,000 

Calculated Dose (Intake [mg/kg-day])b,c

Not reported Control

0 

37-94

(66) 

144-

358 

(251) 

451-

1086 

(768) 

0 49±5 191±21 677±74

Nasal cavity 

All Animals 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 

Esthesioneuroepithelioma Sacrificed 

animals Not reported Not reported Not reported 

All Animals 0/50 0/50 0/50 0/50 Not reported 0/50 0/50 0/50 0/50 

Adenocarcinoma Sacrificed 

animals Not reported Not reported Not reported 

Liver 

All Animals 7/50 16/50 22/50 8/50 7/50 16/50 22/50e 8/50 9/50 17/50 23/50e 11/50 

Hepatocellular adenomas Sacrificed 

animals Not reported Not reported Not reported 

All Animals 15/50 20/50 23/50 36/50 15/50 20/50 23/50 36/50d,e 15/50 20/50 23/50 36/50e,f

Hepatocellular carcinomas Sacrificed 

animals Not reported Not reported Not reported 

All Animals Not reported 21/50 31/50 37/50 39/50d,e 23/50 31/50 37/50d 40/50e,f

Either adenoma 

or carcinoma Sacrificed 

animals Not reported Not reported Not reported 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994). Drinking water concentrations of 1,4-dioxane were used to 

identify the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used in 

this final document (U.S. EPA, 2010, 625580). d

p ≤ 0.05 by Fisher's Exact test. e

Significantly increased by Peto test for trend p < 0.01. 

f

p ≤ 0.01 by Fisher's Exact test. 

 E-11 
 

Table E-8. Neoplastic lesions: Comparison of histological findings reported 

for the 2-year JBRC drinking water study in female Crj:BDF1 mice 

 Yamazaki et al. (1994)a JBRC (1998) Kano et al. (2009) 

 Drinking water concentration (ppm) 

 0 500 2,000 8,000 0 500 2,000 8,000 0 500 2,000 8,000 

Calculated Dose (Intake [mg/kg-day])b,c

Not reported Control

0 

45-

109

(77) 

192-

454

(323) 

759-

1374

(1066) 

0 66 ± 

10 

278 ± 

40 

964 ± 

88 

Nasal Cavity 

All animals 0/50 0/50 0/50 0/50 Not reported 0/50 0/50 0/50 0/50 

Esthesioneruoepithelioma Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50 

Adenocarcinoma Sacrificed 

animals Not reported Not reported Not reported 

Liver 

All animals 4/50 30/50 20/50 2/50 4/50 30/50d 20/50d 2/50e 5/50 31/50d 20/50d 3/50 

Hepatocellular adenomas Sacrificed 

animals Not reported Not reported Not reported 

All animals 0/50 6/50 30/50 45/50 0/50 6/50f 30/50d 45/50d,g 0/50 6/50f 30/50d 45/50d,g

Hepatocellular carcinomas Sacrificed 

animals Not reported Not reported Not reported 

All animals Not reported 4/50 34/50d 41/50d 46/50d,g 5/50 35/50d 41/50d 46/50d,g

Either adenoma 

or carcinoma Sacrificed 

animals Not reported Not reported Not reported 

a

Dose rates (mg/kg-day) were not provided in Yamazaki et al. (1994, 196120). Drinking water concentrations (ppm) of 1,4-dioxane 

were used to identify the dose groups. Statistical test results were not reported. 

b

JBRC (1998, 196240) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in 

parentheses) was used in the external peer review draft of this document (U.S. EPA, 2009, 628630) . c

Kano et al. (2009, 594539) reported a mean intake dose for each group ± standard deviation. The mean shown in this table was used 

in this final document (U.S. EPA, 2010, 625580). d

p ≤ 0.01 by Fisher's Exact test. e

Significantly decreased by Cochran-Armitage test for trend p < 0.05 

f p ≤ 0.05 by Fisher's Exact test. g

Significantly increased by Peto test for trend p < 0.01 

 E-12