DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE NCEA

- I

- 3833 1

www.epa.gov/iris 2

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# TOXICOLOGICAL REVIEW

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# OF

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# 1,4

- D ioxane

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### (CAS No. 123

- 91

- 1) 13

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### In Support of Summary Information on the 16



### Integrated Risk Information System (IRIS) 17

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## Ma y 2011 22

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NOTICE 27

28

This document is an Intera gency Science Consultation draft. This information is distributed 29

solely for the purpose of pre

- dissemination peer review under applicable information quality 30

guidelines. It has not been formally disseminated by EPA. It does not represent and should not 31

be construed to represent any Agency determination or policy. It is being circulated for review 32

of its technical accuracy and science policy implications. 33

34

35

36

37

38

U.S. Environmental Protection Agency 39

Washington, DC 40DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ii DISCLAIMER 1

2

This document is a preliminary draft for review purposes only. This information is 3

distributed solely for the purpose of pre

- dissemination peer review under application information 4

quality guidelines. It has not been formally disseminated by EPA. It does not represent and 5

should not be construed to represent any Agency determination or policy. Mention of trade 6

names or commercial products does not constitute endorsement or recommendation for use. 7DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE iii CONT ENTS

– TOXICOLOGICAL REVIEW OF 1,4

- DIOXANE 1

(CAS No. 123

- 91

- 1) 2

LIST OF TABLES

................................ ................................ ................................ ................... vii 3

LIST OF FIGURES

................................ ................................ ................................ ................ xiii 4

LIST OF ABBREV IATIONS AND ACRONYMS

................................ ............................... xviii 5

1. INTRODUCTION

................................ ................................ ................................ ................... 1 6

2. CHEMICAL AND PHYSICAL INFORMATION

................................ ................................ ... 3 7

3. TOXICOKINETICS

................................ ................................ ................................ ................ 6 8

3.1. ABSORPTION

................................ ................................ ................................ ............ 6 9

3.2. DISTRIBUTION

................................ ................................ ................................ ......... 7 10

3.3. METABOLISM

................................ ................................ ................................ ........... 8 11

3.4. ELIMINATION

................................ ................................ ................................ ......... 12 12

3.5. PHYSIOLOGIC ALLY BASED PHARMACOKINETIC MODELS

.......................... 13 13

3.5.1. Available Pharmacokinetic Data

................................ ................................ ........ 14 14

3.5.2. Published PBPK Models for 1,4

- Dioxane

................................ ........................... 16 15

3.5.2.1. Leung and Paustenbach

................................ ................................ ..................... 16 16

3. 5.2.2. Reitz et al.

................................ ................................ ................................ ......... 17 17

3.5.2.3. Fisher et al.

................................ ................................ ................................ ....... 18 18

3.5.2.4. S weeney et al.

................................ ................................ ................................ ... 18 19

3.5.3. Implementation of Published PBPK Models for 1,4

- Dioxane

............................. 19 20

3.6. RAT NASAL EXPOSURE VIA DRINKING WATER

................................ ............. 23 21

4. HAZARD IDENTIFICATION

................................ ................................ .............................. 24 22

4.1. STU DIES IN HUMANS

– EPIDEMIOLOGY, CASE REPORTS, CLINICAL 23

CONTROLS

................................ ................................ ................................ ......................... 24 24

4.1.1. Thiess et al.

................................ ................................ ................................ ........ 26 25

4.1.2. Buffler et al.

................................ ................................ ................................ ....... 27 26

4.2. SUBCH RONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 27

ANIMALS

- ORAL AND INHALATION

................................ ................................ ............ 28 28

4.2.1. Oral Toxicity

................................ ................................ ................................ ...... 28 29

4.2.1.1. Subchronic Oral Toxicity

................................ ................................ .................. 28 30

4.2.1.1.1. Stoner et al.

................................ ................................ ................................ 29 31

4.2.1.1. 2. Stott et al.

................................ ................................ ................................ ... 29 32

4.2.1.1.3. Kano et al.

................................ ................................ ................................ .. 29 33

4.2.1.1.4. Yamamoto et al.

................................ ................................ ......................... 34 34

4.2.1.2. Chronic Oral Toxicity and Carcinogenicity

................................ ....................... 35 35

4.2.1.2.1. Argus et al.

................................ ................................ ................................ . 35 36

4.2.1.2.2. Argus et al.; Hoch

- Ligeti et al.

................................ ................................ .... 36 37

4.2.1.2.3. Hoch

- Ligeti and Argus.

................................ ................................ .............. 37 38

4.2.1.2.4. Kociba et al.

................................ ................................ ............................... 38 39

4.2.1.2. 5. National Cancer Institute (NCI).

................................ ................................ . 40 40DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE iv 4.2.1.2.6. Kano et al.; Japan Bioassay Research Center; Yamazaki et al.

.................... 44 1

4.2.2. Inhalation Toxicity

................................ ................................ ............................. 56 2

4.2.2.1. Subchronic Inhalation Toxicity

................................ ................................ ......... 56 3

4.2.2.1.1. Fairley et al.

................................ ................................ ............................... 56 4

4.2.2. 1.2. Kasai et al.

................................ ................................ ................................ .. 56 5

4.2.2.2. Chronic Inhalation Toxicity and Carcinogenicity

................................ .............. 59 6

4.2.2.2.1. Torkelson et al.

................................ ................................ ........................... 59 7

4.2.2.2.2. Kasai et al.

................................ ................................ ................................ .. 60 8

4.2.3. Initiation/Promotion Studies

................................ ................................ ............... 63 9

4.2.3.1. Bull et al.

................................ ................................ ................................ .......... 63 10

4.2.3.2. Kin g et al.

................................ ................................ ................................ ......... 64 11

4.2.3.3. Lundberg et al.

................................ ................................ ................................ .. 65 12

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES

— ORAL AND INHALATION

. 65 13

4.3.1. Giavini et al.

................................ ................................ ................................ ...... 65 14

4.4. OTHER DURATION OR ENDPOINT

- SPECIFIC STUDIES

................................ ... 66 15

4.4.1. Acute and Short

- term Toxicity

................................ ................................ ........... 66 16

4.4.1.1. Oral Toxicity

................................ ................................ ................................ ..... 66 17

4.4.1.2. Inhalation Toxicity

................................ ................................ ............................ 66 18

4.4. 2. Neurotoxicity

................................ ................................ ................................ ..... 69 19

4.4.2.1. Frantik et al.

................................ ................................ ................................ ...... 69 20

4.4.2.2. Goldberg et al.

................................ ................................ ................................ .. 70 21

4.4.2.3. Kanada et al.

................................ ................................ ................................ ..... 70 22

4.4.2.4. Knoefel

................................ ................................ ................................ ............. 71 23

4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF 24

ACTION

................................ ................................ ................................ ............................... 71 25

4.5.1. Genotoxicity

................................ ................................ ................................ ...... 71 26

4.5.2. Mecha nistic Studies

................................ ................................ ........................... 80 27

4.5.2.1. Free Radical Generation

................................ ................................ .................... 80 28

4.5.2.2. Induction of Metabolism

................................ ................................ ................... 80 29

4.5.2.3. Mechanisms of Tumor Induction

................................ ................................ ....... 81 30

4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS

................................ ................ 83 31

4.6.1. Oral

................................ ................................ ................................ .................... 83 32

4.6.2. Inhalation

................................ ................................ ................................ ........... 86 33

4.6.3. Mode of Action Information

................................ ................................ .............. 89 34

4.7. EVALUATION OF CARCINOGENICITY

................................ ............................... 90 35

4.7.1. Summary of Overall Weight of Evidence

................................ ........................... 90 36

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

........................... 92 37

4.7.3. Mode of Action Information

................................ ................................ .............. 94 38

4.7.3.1. Identification of Key Events for Carcinogenicity

................................ ............... 94 39

4.7.3.1.1. Liver.

................................ ................................ ................................ ......... 94 40

4.7.3.1.2. Nasal cavity.

................................ ................................ ............................... 95 41

4.7.3.2. Strength, Consistency, Specificity of Association

................................ .............. 96 42

4.7.3.2.1. Liver.

................................ ................................ ................................ ......... 96 43

4.7.3.2.2. Nasal cavity.

................................ ................................ ............................... 96 44

4.7.3.3. Dose

- Response Relationship

................................ ................................ ............. 97 45

4.7.3.3.1. Liver.

................................ ................................ ................................ ......... 97 46DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE v 4.7.3.3.2. Nasal cavity.

................................ ................................ ............................... 99 1

4.7.3.4. Temporal Relationship

................................ ................................ .................... 101 2

4.7.3.4.1. Liver.

................................ ................................ ................................ ....... 101 3

4.7.3.4.2. Nasal cavity.

................................ ................................ ............................. 102 4

4.7.3.5. Biological Plausibility and Coherence

................................ ............................. 103 5

4.7.3.5.1. Liver.

................................ ................................ ................................ ....... 103 6

4.7.3.5.2. Nas al cavity.

................................ ................................ ............................. 103 7

4.7.3.6. Other Possible Modes of Action

................................ ................................ ...... 103 8

4.7.3.7. Conclusions About the Hypothesized Mode of Action

................................ ..... 104 9

4.7.3.7.1. Liver.

................................ ................................ ................................ ....... 104 10

4.7.3.7.2. Nasal cavity.

................................ ................................ ............................. 104 11

4.7.3. 8. Relevance of the Mode of Action to Humans

................................ .................. 104 12

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES

................................ .......... 105 13

5. DOSE

- RESPONSE ASSESSMENTS

................................ ................................ ................. 106 14

5. 1. ORAL REFERENCE DOSE (RfD)

................................ ................................ ......... 106 15

5.1.1. Choice of Principal Studies and Critical Effect with Rationale and Justification 16

106 17

5.1.2. Methods of Analysis

— Including Models (PBPK, BMD, etc.)

.......................... 107 18

5.1.3. RfD Derivation

- Including Application of Uncertainty Factors (UFs)

.............. 110 19

5.1.4. RfD Comparison Information

................................ ................................ ........... 111 20

5.1.5. Previous RfD Assessment

................................ ................................ ................ 115 21

5.2. INHALATION REFERENCE CONCENTRATION (RfC)

................................ ...... 115 22

5.2.1. Choice of Principal Studies and Critical Effect(s) with Rationale and Justification 23

................................ ................................ ................................ ........................ 115 24

5.2.2. Methods of Analysis

................................ ................................ ........................ 118 25

5.2. 3. Exposure Duration and Dosimetric Adjustments

................................ .............. 119 26

5.2.4. RfC Derivation

- Including Application of Uncertainty Factors (UFs)

............... 122 27

5.2.5. RfC Comparison Information

................................ ................................ ........... 123 28

5.2.6. Previous RfC Assessment

................................ ................................ ................ 123 29

5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE AND INHALATION 30

REFERENCE CONCENTRATION

................................ ................................ .................... 123 31

5.4. CANCER ASSESSMENT

................................ ................................ ....................... 125 32

5.4.1. Choice of Study/Data

– with Rationale and Justification

................................ .. 125 33

5.4.1.1. Oral Study/Data

................................ ................................ .............................. 125 34

5.4 .1.2. Inhalation Study/Data

................................ ................................ ...................... 127 35

5.4.2. Dose

- Response Data

................................ ................................ ........................ 128 36

5.4.2. 1. Oral Data

................................ ................................ ................................ ........ 128 37

5.4.2.2. Inhalation Data

................................ ................................ ................................ 129 38

5.4.3. Dose Adjustments and Extrapolation Method(s)

................................ ............... 130 39

5.4.3.1. Oral

................................ ................................ ................................ ................. 130 40

5.4.3.2 . Inhalatio n

................................ ................................ ................................ ........ 132 41

5.4.4. Oral Slope Factor and Inhalation Unit Risk

................................ ...................... 133 42

5.4.4.1. Oral Slope Factor

................................ ................................ ............................ 133 43

5.4. 4.2. Inhalation Unit Risk

................................ ................................ ........................ 135 44

5.4.5. Previous Cancer Assessment

................................ ................................ ............ 137 45

5.5. UNCERTAINTIES IN CANCER RISK VALUES

................................ .................. 137 46DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE vi 5.5.1. Sources of Uncertainty

................................ ................................ ..................... 138 1

5. 5.1.1. Choice of Low

- Dose Extrapolation Approach

................................ ................. 138 2

5.5.1.2. Dose Metric

................................ ................................ ................................ .... 139 3

5.5.1.3. Cross

- Species Scaling

................................ ................................ ..................... 139 4

5.5.1.4. Statistical Uncertainty at the POD

................................ ................................ ... 139 5

5.5.1.5. Bioassay Selection

................................ ................................ .......................... 140 6

5.5.1.6. Choice of Species/Gender

................................ ................................ ............... 140 7

5.5.1.7. Relevance to Humans

................................ ................................ ...................... 141 8

5.5.1.8. Human Population Variability

................................ ................................ ......... 14 1 9

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE 10

RESPONSE

................................ ................................ ................................ ............................ 143 11

6.1. HUM AN HAZARD POTENTIAL

................................ ................................ .......... 143 12

6.2. DOSE RESPONSE

................................ ................................ ................................ .. 145 13

6.2.1. Nonca ncer/Oral

................................ ................................ ................................ 145 14

6.2.2. Noncancer/Inhalation

................................ ................................ ....................... 145 15

6.2.3. Cancer

................................ ................................ ................................ ............. 145 16

6.2.3.1. Oral

................................ ................................ ................................ ................. 146 17

6.2.3.2. Inhalatio n

................................ ................................ ................................ ........ 146 18

6.2.3.3. Choice of Low

- Dose Extrapolation Approach

................................ ................. 146 19

6.2.3.4. Dose Metric

................................ ................................ ................................ .... 148 20

6.2.3.5. Cross

- Species Scaling

................................ ................................ ..................... 148 21

6.2.3.6. Statistical Uncertainty at the POD

................................ ................................ ... 148 22

6.2.3.7. Bioassay Selection

................................ ................................ .......................... 148 23

6.2. 3.8. Choice of Species/Gender

................................ ................................ ............... 149 24

6.2.3.9. Relevance to Humans

................................ ................................ ...................... 149 25

6.2.3.10. Human Population Variability

................................ ................................ ....... 149 26

7. REFERENCES

................................ ................................ ................................ ................... 150 27

APPENDIX A. SUMMAR Y OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS 28

AND DISPOSITION

................................ ................................ ................................ ............. A

- 1 29

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

- DIOXANE

......... B

- 1 30

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

- DIOXANE

....... C

- 1 31

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

- DIOXANE

...... D

- 1 32

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

- YEAR 33

1,4

- DIOXANE DRINKING WATER STUDY

................................ ................................ ....... E

- 1 34

APPENDIX F. DETAILS OF BMD ANALYSIS FOR INHALATION RfC FOR 1,4

- DIOXANE 35

................................ ................................ ................................ ................................ ............. F

- 13 36

APPENDIX G. DETAILS OF BMD ANALY S IS FOR INHALATION UNIT RISK FOR 37

1,4

- DIOXANE

................................ ................................ ................................ ...................... G

- 41 38DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE vii LIST OF TABLES

Table 2

- 1. Physical properties and chemical identity of 1,4

- dioxane

................................ .......... 4 1

Table 4

- 1. Incidence of histopathological lesions in F344/DuCrj rats exposed to 2

1,4

- dioxane in drinking water for 13 weeks

................................ ............................ 32 3

Table 4

- 2. Incidence of histopathological lesions in Crj:BDF1 mice exposed to 4

1,4

- dioxane in drinking water for 13 weeks

................................ ............................ 34 5

Table 4

- 3. Number of incipient liver tumors and hepatomas in male Sprague

- Dawley rats 6

exposed to 1,4

- dioxane in drinking water for 13 months

................................ ......... 37 7

Table 4

- 4. Incidence of liver and nasal tumors in male and female Sherman rats 8

(combined) treated with 1,4

- dioxane in the drinking water for 2 years

.................... 40 9

Table 4

- 5. Incidence of nonneoplastic lesions in Osborne

- Mendel rats exposed to 10

1,4

- dioxane in drinking water

................................ ................................ ................. 41 11

Table 4

- 6. Incidence of nasal cavity squamous cell carcinoma and liver hepatocellular 12

adenoma in Osborne

- Mendel rats exposed to 1,4

- dioxane in drinking water

........... 42 13

Table 4

- 7. Incidence of hepatocellular adenoma or carcinoma in B6C3F 1 mice exposed to 14

1,4

- dioxane in drinking water

................................ ................................ ................. 44 15

Table 4

- 8. Incidence of histopathological lesions in male F344/DuCrj rats exposed to 16

1,4

- dioxane in drinking water for 2 years

................................ ................................ 48 17

Table 4

- 9. Incidence of histopathological lesions in female F344/DuCrj rats exposed to 18

1,4

- dioxane in drinking water for 2 years

................................ ................................ 49 19

Table 4

- 10. Incidence of nasal cavity, peritoneum, and mammary gland tumors in 20

F344/DuCrj rats exposed to 1,4

- dioxane in drinkin g water for 2 years

.................... 51 21

Table 4

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

- dioxane in 22

drinking water for 2 year s

................................ ................................ ....................... 51 23

Table 4

- 12. Incidence of histopathological lesions in male Crj:BDF1 mice exposed to 24

1,4

- dioxane in drinking water for 2 years

................................ ................................ 53 25

Table 4

- 13. Incidence of histopathological lesions in female Crj:BDF1 mice exposed to 26

1,4

- dioxane in drinking water for 2 years

................................ ................................ 54 27

Table 4

- 14. Incidence of tumors in Crj:BDF1 mice exposed to 1,4

- dioxane in drinking 28

water for 2 years

................................ ................................ ................................ ..... 55 29

Table 4

- 16. Incidence of pre

- and nonneoplastic lesions in male F344/DuCrj rats exposed to 30

1,4

- dioxane vapor by whole

- body inhalation for 2 years.

................................ ........ 62 31

Table 4

- 17. Incidence of tumors in male F344/DuCrj rats exposed to 1,4

- dioxane vapor by 32

whole

- body inhalation for 2 years.

................................ ................................ .......... 63 33

Table 4

- 18. Acute and short

- term toxicity studies of 1,4

- dioxane

................................ ............... 67 34

Table 4

- 19. Genotoxicity studies of 1,4

- dioxane; in vitro

................................ ........................... 74 35

Table 4

- 20. Genotoxicity studies of 1,4

- dioxane; mammalian in vivo

................................ ........ 78 36

Table 4

- 21. Oral toxicity studies (n oncancer effects) for 1,4

- dioxane

................................ ......... 84 37

Table 4

- 22. Inhalation toxicity studies (noncancer effects) for 1,4

- dioxane

................................ 88 38

Table 4

- 23. Temporal sequence and dose

- response relationship for possible key events and 39

liver tumors in rats and mice

................................ ................................ ................... 97 40

Table 4

- 24. Temporal sequence and dose

- response relationship for possible key events and 41

nasal tumors in rats and mice.

................................ ................................ ............... 100 42

Table 5

- 1. Incidence of cortical tubule degeneration in Osborne

- Mendel rats exposed to 43

1,4

- dioxane in drinking water for 2 years

................................ .............................. 109 44DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE viii Table 5

- 2. BMD and BMDL values derived from BMD modeling of cortical tubule 1

degeneration in male and female Osborne

- Mendel rats exposed to 1,4

- dioxane 2

in drinking water for 2 years

................................ ................................ ................. 109 3

Table 5

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

- dioxane in 4

drinking water for 2 years a

................................ ................................ .................... 109 5

Table 5

- 4. BMD and BMDL values derived from BMD modeling of liver hyperplasia in 6

male and female F344/DuCrj rats exposed to 1,4

- dioxane in drinking water for 7

2 years

................................ ................................ ................................ .................. 110 8

Table 5

- 5. Incidences of nonneoplastic lesions resulting from chronic exposure (ppm) to 9

1,4

- dioxane considered for indentification of a critical effect.

............................... 118 10

Table 5

- 6. Duration adjusted POD estimates for best fitting BMDS models or 11

NOAEL/LOAEL from chronic exposure to 1,4

- dioxane

................................ ....... 119 12

Table 5

- 7. Incidence of liver, nasal cavity, peritoneal, and mammary gland tumors in rats 13

and mice exposed to 1,4

- dioxane in drinking water for 2 years (based on 14

survival to 12 months)

................................ ................................ .......................... 126 15

Table 5

- 8. Incidence of liver, nasal cavity, kidney, peritoneal, and mammary gland, 16

Zymbal gland, and subcutis tumors in rats exposed to 1,4

- dioxane vapors for 2 17

years.

................................ ................................ ................................ .................... 128 18

Table 5

- 9. Incidence of hepatocellular adenoma or carcinoma in rats and mice exposed to 19

1,4

- dioxane in drinking water for 2 years

................................ .............................. 129 20

Table 5

- 10. Incidence of tumors in F344 male rats exposed to 1,4

- dioxane for 104 weeks (6 21

hours/day, 5 days/week)

................................ ................................ ........................ 130 22

Table 5

- 11. Calculated HEDs for the tumor incidence data used for dose

- response 23

modeling

................................ ................................ ................................ .............. 131 24

Table 5

- 12. BMD HED and BMDL HED values from models fit to tumor incidence data for 25

rats and mice exposed to 1,4

- dioxane in drinking water for 2 years and 26

corresponding oral CSFs

................................ ................................ ....................... 134 27

Table 5

- 13. Dose

- response modeling summary results for male rat tumors associated with 28

inhalation exposure to 1,4

- dioxane for 2 years

................................ ...................... 136 29

Table 5

- 14. Summary of uncertainty in the 1,4

- dioxane cancer risk estimation

....................... 142 30

Table B

- 1. Human PBPK model parameter values for 1,4

- dioxane

................................ ....... B

- 11 31

Table B

- 2. PBPK metabolic and elimination parameter values resulting from re

- calibration 32

of the human model using alternative values for physiological flow rates a and 33

tissue:air partition coefficients

................................ ................................ ............ B

- 13 34

Table B

- 3. PBPK metabolic and elimination parameter values resulting from recalibration 35

of the human model using biologically plausible values for physiological flow 36

rates a and selected upper and lower boundary values for tissue:air partition 37

coefficients

................................ ................................ ................................ ......... B

- 20 38

Table C

- 1. Incidence of cortical tubule degeneration in Osborne

- Mendel rats exposed to 39

1,4

- dioxane in drinking water for 2 years

................................ .............................. C

- 1 40

Table C

- 2. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 41

incidence data for cortical tubule degeneration in male and female Osborne

42

Mendel rats (NCI, 1978) exposed to 1,4

- dioxane in drinking water

....................... C

- 2 43

Table C

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

- dioxane in 44

drinking water a

................................ ................................ ................................ ..... C

- 7 45DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ix Table C

- 4. Benchmark dose modeling results based on the incidence of liver hyperplasias 1

in male and female F344 rats exposed to 1,4

- dioxane in drinking water for 2 2

years

................................ ................................ ................................ ..................... C

- 8 3

Table D

- 1. Recommended models for rodents exposed to 1,4

- dioxane in drinking water 4

(Kano, et al., 2009)

................................ ................................ ............................... D

- 4 5

Table D

- 2. Data for hepatic adenomas and carcinomas in female F344 rats (Kano, et al., 6

2009)

................................ ................................ ................................ .................... D

- 5 7

Table D

- 3. BMDS dose

- response modeling results for the combined incidence of hepatic 8

adenomas and carcinomas in female F344 rats (Kano, et al., 2009)

....................... D

- 5 9

Table D

- 4. Data for hepatic adenomas and carcinomas in male F344 rats (Kano, et al., 10

2009)

................................ ................................ ................................ .................... D

- 8 11

Table D

- 5. BMDS dose

- response modeling results for the combined incidence of 12

adenomas and carcinomas in livers of male F344 rats (Kano, et al., 2009)

............ D

- 9 13

Table D

- 6. Data for significant tumors at other sites in male and female F344 rats (Kano, 14

et al., 2009)

................................ ................................ ................................ ......... D

- 14 15

Table D

- 7. BMDS dose

- response modeling results for the incidence of nasal cavity tumors 16

in female F344 rats a (Kano, et al., 2009)

................................ ............................. D

- 15 17

Table D

- 8. BMDS dose

- response modeling results for the incidence of nasal cavity tumors 18

in male F344 rats a (Kano, et al., 2009)

................................ ................................ D

- 18 19

Table D

- 9. BMDS dose

- response modeling results for the incidence of mammary gland 20

adenomas in female F344 rats (Kano, et al., 2009)

................................ .............. D

- 21 21

Table D

- 10. BMDS dose

- response modeling results for the incidence of peritoneal 22

mesotheliomas in male F344 rats (Kano, et al., 2009)

................................ ......... D

- 26 23

Table D

- 11. Data for hepatic adenomas and carcinomas in female BDF1 mice (Kano, et al., 24

2009)

................................ ................................ ................................ .................. D

- 31 25

Table D

- 12. BMDS dose

- response modeling results for the combined incidence of hepatic 26

adenomas and carcinomas in female BDF1 mice (Kano, et al., 2009)

.................. D

- 32 27

Table D

- 13. BMDS LogLogistic dose

- response modeling results using BMRs of 10, 30, 28

and 50% for the combined incidence of hepatic adenomas and carcinomas in 29

female BDF1 mice (Kano, et al., 2009).

................................ .............................. D

- 32 30

Table D

- 14. Data for hepatic adenomas and carcinomas in male BDF1 mice (Kano, et al., 31

2009)

................................ ................................ ................................ .................. D

- 41 32

Table D

- 15. BMDS dose

- response modeling results for the combined incidence of hepatic 33

adenomas and carcinomas in male BDF1 mic e (Kano, et al., 2009)

..................... D

- 42 34

Table D

- 16. Summary of BMDS dose

- response modeling estimates associated with liver 35

and nasal tumor incid ence data resulting from chronic oral exposure to 36

1,4

- dioxane in rats and mice

................................ ................................ ............... D

- 47 37

Table D

- 17. Incidence of hepatocellular carcinom a and nasal squamous cell carcinoma in 38

male and female Sherman rats (combined) (Kociba, et al., 1974) treated with 39

1,4

- dioxane in the drinking water for 2 years

................................ ...................... D

- 48 40

Table D

- 18. BMDS dose

- response modeling results for the incidence of hepatocellular 41

carcinoma in male and female Sherman rats (combined) (Kociba, et al., 1974) 42

exposed to 1,4

- dioxane in the drinking water for 2 years

................................ ..... D

- 49 43

Table D

- 19. BMDS dose

- response modeling results for the incidence of nasal squamous 44

cell carcinoma in male and female Sherman rats (combined) (Kociba, et al., 45

1974) exposed to 1,4

- dioxane in the drinking water for 2 years

........................... D

- 54 46DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE x Table D

- 20. Incidence of nasal cavity squamous cell carcinoma and hepatocellular 1

adenoma in Osborne

- Mendel rats (NCI, 1978) exposed to 1,4

- dioxane in the 2

drinking water

................................ ................................ ................................ .... D

- 57 3

Table D

- 21. BMDS dose

- response modeling results for the incidence of hepatocellular 4

adenoma in female Osborne

- Mendel rats (NCI, 1978) exposed to 1,4

- dioxane 5

in the drinking water for 2 years

................................ ................................ ......... D

- 58 6

Table D

- 22. BMDS dose

- response modeling results for the incidence of nasal cavity 7

squamous cell carcinoma in female Osborne

- Mendel rats (NCI, 1978) exposed 8

to 1,4

- dioxane in the drinking water for 2 years

................................ .................. D

- 63 9

Table D

- 23. BMDS dose

- response modeling results for the incidence of nasal cavity 10

sq uamous cell carcinoma in male Osborne

- Mendel rats (NCI, 1978) exposed to 11

1,4

- dioxane in the drinking water for 2 years

................................ ...................... D

- 68 12

Table D

- 24. Incidence of hepatocellular adenoma or carcinoma in male and female B6C3F 1 13

mice (NCI, 1978) exposed to 1,4

- dioxane in drinking water

................................ D

- 73 14

Table D

- 25. BMDS dose

- response modeling results for the combined incidence of 15

hepatocellular adenoma or carcinoma in female B6C3F 1 mice (NCI, 1978) 16

exposed to 1,4

- dioxane in the drinking water for 2 years

................................ ..... D

- 74 17

Table D

- 26. BMDS dose

- response modeling results for the combined incidence of 18

hepatocellular adenoma or carcinoma in male B6C3F 1 mice (NCI, 1978) 19

exposed to 1,4

- dioxane in drinking water

................................ ............................ D

- 77 20

Table E

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

- 21

year JBRC drinking water study in male F344 rats

................................ ................ E

- 2 22

Table E

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

- 23

year JBRC drinking water study in female F344 rats

................................ ............. E

- 3 24

Table E

- 3. Neoplastic lesions: Comparison of histological findings report ed for the 2

- year 25

JBRC drinking water study in male F344 rats

................................ ....................... E

- 5 26

Table E

- 4. Neoplastic lesions: Comparison of histological findings reported for the 2

- year 27

JBRC drinking water study in female F344 rats

................................ .................... E

- 6 28

Table E

- 5. Nonneoplastic lesions: Comparison of histolo gical findings reported for the 2

- 29

year JBRC drinking water study in male Crj:BDF1 mice

................................ ...... E

- 8 30

Table E

- 6. Nonneoplastic lesions: Compa rison of histological findings reported for the 31

2

- year JBRC drinking water study in female Crj:BDF1 mice

.............................. E

- 10 32

Table E

- 7. Neoplastic lesions: Comparison of histological findings reported for the 2

- year 33

JBRC drinking water study in male Crj:BDF1 mice

................................ ............ E

- 11 34

Table E

- 8. Neoplastic lesions: Comparison of histological findings reported for the 2

- year 35

JBRC drinking water study in female Crj:BDF1 mice

................................ ......... E

- 12 36

Table F

- 1. Incidence of centrilobular necrosis of the liver in F344/DuCrj rats exposed to 37

1,4

- dioxane via inhalation for 2 years.

................................ ................................ F

- 13 38

Table F

- 2. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 39

incidence data for centrilobular necrosis of the liver in male F344/DuCrj rats 40

exposed to 1,4

- dioxane vapors (Kasai, et al., 2009).

................................ ............ F

- 14 41

Table F

- 3. Incidence of spongiosis hepatis of the liver in F344/DuCrj rats exposed to 42

1,4

- dioxane via inhalation for 2 years.

................................ ................................ F

- 17 43

Table F

- 4. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 44

incidence data for spongiosis hepatis of the liver in male F344/DuCrj rats (NCI, 45

1978) exposed to 1,4

- dioxane vapors.

................................ ................................ . F

- 17 46DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xi Table F

- 5. Incidence of squamous cell metaplasia of the respiratory epithelium in 1

F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

..................... F

- 22 2

Table F

- 6. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 3

incidence data for squamous cell metaplasia of the respiratory epithelium in 4

male F344/DuCrj rats exposed to 1,4

- dioxane vapors (Kasai, et al., 2009).

......... F

- 22 5

Table F

- 7. Incidence of squamous cell hyperplasia of the respiratory epithelium in 6

F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

..................... F

- 25 7

Table F

- 8. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 8

incidence data for squamous cell hyperplasia of the respiratory epithelium in 9

male F344/DuCrj rats exposed to 1,4

- dioxane vapors (Kasai, et al., 2009).

........ F

- 25 10

Table F

- 9. Incidence of respiratory metaplasia of the olfactory epithelium in F344/DuCrj 11

rats exposed to 1,4

- dioxane via inhalation for 2 years.

................................ ........ F

- 28 12

Table F

- 10. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 13

incidence data for respiratory metaplasia of olfactory epithelium in male 14

F344/DuCrj rats (Kasai, et al., 2009) exposed to 1,4

- dioxane vapors.

.................. F

- 29 15

Table F

- 11. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 16

incidence data for respiratory metaplasia of olfactory epithelium with high dose 17

group dropped in male F344/DuCrj rats (Kasai, et al., 2009) exposed to 18

1,4

- dioxane vapors.

................................ ................................ ............................. F

- 29 19

Table F

- 12. Incidence of respiratory metaplasia of the olfactory epithelium in F344/DuCrj 20

rats exposed to 1,4

- dioxane via inhalation for 2 years.

................................ ........ F

- 32 21

Table F

- 13. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 22

incidence data for atrophy of olfactory epithelium in male F344/DuCrj rats 23

(Kasai, et al., 2009) exposed to 1,4

- dioxane vapors.

................................ ............ F

- 32 24

Table F

- 14. Incidence of hydropic change of the lamina propria in the nasal cavity of 25

F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

..................... F

- 35 26

Table F

- 15. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 27

incidence data for hydropic change of the lamina propria in the nasal cavity of 28

male F344/DuCrj rats exposed to 1,4

- dioxane vapors (Kasai, et al., 2009).

........ F

- 35 29

Table F

- 16. Incidence of sclerosis of the lamina propria in the nasal cavity of F344/DuCrj 30

rats exposed to 1,4

- dioxane via inhalation for 2 years.

................................ ........ F

- 38 31

Table F

- 17. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from models fit to 32

incidence data for sclerosis of the lamina propria in the nasal cavity of male 33

F344/DuCrj rats exposed to 1,4

- dioxane vapors (Kasai, et al., 2009).

................. F

- 38 34

Table G

- 1. Summary of BMC 10 and BMCL 10 model results for individual tumor types and 35

combined tumor analysis for male rats exposed to 1,4

- dioxane vapors (Kasai, et 36

al., 2009)

................................ ................................ ................................ ............ G

- 42 37

Table G

- 2. Incidence of tumors in male F344/DuCrj rats exposed to 1,4

- dioxane vapor by 38

whole

- body inhalation for 2 years.

................................ ................................ ...... G

- 43 39

Table G

- 3. BMDS Multistage cancer dose

- response modeling results for the incidence of 40

nasal squamous cell carcinomas in male rats exposed to 1,4

- dioxane vapors for 41

2

- years (Kasai, et al., 2009)

................................ ................................ ................ G

- 43 42

Table G

- 4. BMDS Multistage cancer dose

- response modeling results for the incidence of 43

either hepatocellular adenoma or carcinoma in male rats exposed to 1,4

- 44

dioxane vapors for 2

- years (Kasai, et al., 2009)

................................ ................... G

- 46 45DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xii Table G

- 5. BMDS Multistage cancer dose

- response modeling results for the incidence of 1

renal cell carcinomas and Zymbal gland adenomas in male rats exposed to 1,4

- 2

dioxane vapors for 2

- years (Kasai, et al., 2009)

................................ ................... G

- 48 3

Table G

- 6. B MDS Multistage cancer dose

- response modeling results for the incidence of 4

peritoneal mesothelioma in male rats exposed to 1,4

- dioxane vapors for 2

- years 5

(Kasai, et al., 2009)

................................ ................................ ............................. G

- 53 6

Table G

- 7. BMDS Multistage cancer dose

- response modeling results for the incidence of 7

mammary gland fibroadenoma in male rats exposed to 1,4

- dioxane vapors for 8

2

- years (Kasai, et al., 2009)

................................ ................................ ................ G

- 56 9

Table G

- 8. BMDS Multistage cancer dose

- response modeling results for the incidence of 10

subcutis f ibromas in male rats exposed to 1,4

- dioxane vapors for 2

- years 11

(Kasai, et al., 2009)

................................ ................................ ............................. G

- 58 12DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xiii LIST OF FIGURES

Figure 2

- 1. 1,4

- Dioxane chemical structure.

................................ ................................ ................ 3 1

Figure 3

- 1. Suggested metabolic pathways of 1,4

- dioxane in the rat.

................................ ........... 9 2

Figure 3

- 2. Plasma 1,4

- dioxane levels in rats following i.v. doses of 3

- 5,600 mg/kg.

................ 11 3

Figure 3

- 3. General PBPK model structure consisting of blood

- flow limited tissue 4

compartments connected via arterial and venous blood flows.

................................ . 14 5

Figure 4

- 1. A schematic representation of the possible key events in the delivery of 6

1,4

- dioxane to the liver and the hypothesized MOA(s) for liver carcinogenic ity.

..... 95 7

Figure 5

- 1. Potential points of departure (POD) for liver toxicity endpoints with 8

corresponding applied uncertainty factors and derived RfDs following oral 9

exposure to 1,4

- dioxane.

................................ ................................ ....................... 112 10

Figure 5

- 2. Potential points of departure (POD) for kidney toxicity e ndpoints with 11

corresponding applied uncertainty factors and derived RfDs following oral 12

exposure to 1,4

- dioxane.

................................ ................................ ....................... 113 13

Figure 5

- 3. P otential points of departure (POD) for nasal inflammation with corresponding 14

applied uncertainty factors and derived sample RfDs following oral exposure to 15

1,4

- dioxane.

................................ ................................ ................................ .......... 114 16

Figure 5

- 4. Potential points of departure (POD) for organ specific toxicity endpoints with 17

corresponding applied uncertainty factors and derived sample RfDs fo llowing 18

oral exposure to 1,4

- dioxane.

................................ ................................ ................ 115 19

Figure 5

- 5. Potential points of departure (POD) for candidate endpoints with corresponding 20

applied uncertainty factors and derived sample RfCs following inhalation 21

exposure to 1,4

- dioxane.

................................ ................................ ....................... 123 22

Figure B

- 1. Schematic repre sentation of empirical model for 1,4

- dioxane in rats.

................... B

- 3 23

Figure B

- 2. Schematic representation of empirical model for 1,4

- dioxane i n humans.

............ B

- 4 24

Figure B

- 3. Output of 1,4

- dioxane blood level data from the acslXtreme implementation 25

(left) and published (right) empirical rat model simulations of i.v. 26

administration experiments.

................................ ................................ .................. B

- 5 27

Figure B

- 4. Output of HEAA urine level data from acslXtreme implementation (left) and 28

published (right) empirical rat model simulations of i.v. administration 29

experiments.

................................ ................................ ................................ ......... B

- 6 30

Figure B

- 5. a cslXtreme predictions of blood 1,4

- dioxane and urine HEAA levels from the 31

empirical rat model simulations of a 6

- hour, 50

- ppm inhalation exposure.

............ B

- 7 32

Figure B

- 6. Output of 1,4

- dioxane blood level data from the acslXtreme implementation 33

(left) and published (right) empirical human model simulations of a 6

- hour, 50

- 34

ppm inhalation exposure.

................................ ................................ ...................... B

- 8 35

Figure B

- 7. Observations and acslXtreme predictions of cumulative HEAA in human urine 36

following a 6

- hour, 50

- ppm inhalation exposure.

................................ .................. B

- 9 37

Figure B

- 8. EPA

- modified Young et al. empirical model prediction (line) of plasma 1,4

- 38

dioxane levels in rats following exposure to 1,4

- dioxane for 13 weeks 39

compared to data from Kasai et al. (2008).

................................ ............................ B

- 9 40

Figure B

- 9. Predicted and observed blood 1,4

- dioxane concentrations (left) and urin ary 41

HEAA levels (right) following re

- calibration of the human PBPK model with 42

tissue:air partition coefficient values.

................................ ................................ .. B

- 13 43DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xiv Figure B

- 10. Predicted and observed blood 1,4

- dioxane concentrations (left) and urinary 1

HEAA levels (right) following re

- calibration of the human PBPK model with 2

tissue:air partition coefficient values.

................................ ................................ .. B

- 14 3

Figure B

- 11. Predicted and observed blood 1,4

- dioxane concentrations (left) and urinary 4

HEAA levels (right)

................................ ................................ ............................ B

- 15 5

Figure B

- 12. The highest seven sensitivity coefficients (and associated parameters) for 6

blood 1,4

- dioxane concentrations (CV) at 1 (left) and 4 (right) hours o f a 50

- 7

ppm inhalation exposure.

................................ ................................ .................... B

- 17 8

Figure B

- 13. Comparisons of the range of PBPK model predictions from upper and lower 9

boundari es on partition coefficients with empirical model predictions and 10

experimental observations for blood 1,4

- dioxane concentrations (left) and 11

urinary HEAA levels (right) from a 6

- hour, 50

- ppm inhalation exposure.

........... B

- 19 12

Figure B

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

boundaries on partition coefficients with empirical model predictions and 14

experimental observations for blood 1,4

- dioxane concentrations (left) and 15

urinary HEAA levels (right) from a 6

- hour, 50

- ppm inhalation exposure.

........... B

- 20 16

Figure B

- 15. Predictions of blood 1,4

- dioxane concentration following calibration of a 17

zero

- order metabolism rate constant, k LC , to the experimental data.

..................... B

- 21 18

Figure B

- 16. Predictions of blood 1,4

- dioxane concentration following calibration of a 19

zero

- order metabolism rate constant, k LC , to only the exposure phase of the 20

experimental data.

................................ ................................ ............................... B

- 22 21

Figure B

- 17. Predictions of blood 1,4

- dioxane concentration following simultaneous 22

calibration of a zero

- order metabolism rate constant, k LC , and slowly perfused 23

tissue:air partition coefficient to the experimental data.

................................ ....... B

- 23 24

Figure C

- 1. BMD Log

- probit model of cortical tubule degeneration incidence data for 25

male rats exposed to 1,4

- dioxane in drinking water for 2 years to support the 26

results in Table C

- 2.

................................ ................................ .............................. C

- 3 27

Figure C

- 2. BMD Weibull model of cortical tubule degeneration incidence data for female 28

rats exposed to 1,4

- dioxane in drinking water for 2 years to support th e results 29

in Table C

- 2.

................................ ................................ ................................ ......... C

- 5 30

Figure C

- 3. BMD gamma model of liver hyperplasia incidence data for F344 male rats 31

exposed to 1,4

- dioxa ne in drinking water for 2 years to support results 32

Table C

- 4.

................................ ................................ ................................ ............. C

- 9 33

Figure C

- 4. BMD multistage (2 degree) model of liver hyperplasi a incidence data for F344 34

male rats exposed to 1,4

- dioxane in drinking water for 2 years to support 35

results Table C

- 4.

................................ ................................ ................................ C

- 11 36

Figure C

- 5. BMD Weibull model of liver hyperplasia incidence data for F344 male rats 37

exposed to 1,4

- dioxane in drinking water for 2 years to support the results in 38

Table C

- 4.

................................ ................................ ................................ ........... C

- 13 39

Figure C

- 6. BMD quantal

- linear model of liver hyperplasia incidence data for F344 male 40

rats exposed to 1,4

- dioxane in drinking water for 2 years to support the results 41

in Table C

- 4.

................................ ................................ ................................ ....... C

- 15 42

Figure C

- 7. BMD log

- probit model of liver hyperplasia incidence data for F344 female 43

rats exposed to 1,4

- dioxane in drinking water for 2 years to support the results 44

in Table C

- 4.

................................ ................................ ................................ ....... C

- 17 45DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xv Figure D

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

adenomas and carcinom as in female F344 rats.

................................ ..................... D

- 6 2

Figure D

- 2. Probit BMD model for the combined incidence of hepatic adenomas and 3

carcinomas in male F344 rats.

................................ ................................ ............. D

- 10 4

Figure D

- 3. Multistage BMD model (3 degree) for the combined incidence of hepatic 5

adenomas and carcinomas in male F344 rats.

................................ ...................... D

- 12 6

Figure D

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

- 16 7

Figure D

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

... D

- 19 8

Figure D

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

... D

- 22 9

Figure D

- 7. Multistage BMD model (1 degree) for mammary gland adenomas in female 10

F344 rats.

................................ ................................ ................................ ............ D

- 24 11

Figu re D

- 8. Probit BMD model for peritoneal mesotheliomas in male F344 rats.

................... D

- 27 12

Figure D

- 9. Multistage BMD (2 degree) model for perito neal mesotheliomas in male F344 13

rats.

................................ ................................ ................................ .................... D

- 29 14

Figure D

- 10. LogLogistic BMD model for the combined incidence of hepatic adenomas 15

and carcinomas in female BDF1 mice with a BMR of 10%.

................................ D

- 33 16

Figure D

- 11. LogLogistic BMD model for the combined incidence of hepatic adenomas 17

and carcinomas in female BDF1 mice with a BMR of 30%.

................................ D

- 35 18

Figure D

- 12. LogLogistic BMD model for the combined incidence of hepatic adenomas 19

and carcinomas in female BDF1 mice with a BMR of 50%.

................................ D

- 37 20

Figure D

- 13. Multistage BMD model (1 degree) for the combined incidence of hepatic 21

adenomas and carcinomas in female BDF1 mice.

................................ ................ D

- 39 22

Figure D

- 14. LogLogistic BMD model for the combined incidence of hepatic adenomas 23

and carcinomas in male BDF1 mice.

................................ ................................ ... D

- 43 24

Figure D

- 15. Multistage BMD model (1 degree) for the combined incidence of hepatic 25

adenomas and carcinomas in male BDF1 mice.

................................ .................. D

- 45 26

Figure D

- 16. Probit BMD model for the incidence of hepatocellular carcinoma in male and 27

female Sherman rats exposed to 1,4

- dio xane in drinking water.

.......................... D

- 50 28

Figure D

- 17. Multistage BMD model (1 degree) for the incidence of hepatocellular 29

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

- dioxane in drinking 30

water.

................................ ................................ ................................ ................. D

- 52 31

Figure D

- 18. Multistage BMD model (3 degree) for the incidence o f nasal squamous cell 32

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

- dioxane in drinking 33

water.

................................ ................................ ................................ ................. D

- 55 34

Figure D

- 19. LogLogistic BMD model for the incidence of hepatocellular adenoma in 35

female Osborne

- Mendel rats exposed to 1,4

- dioxane in drinking water.

.............. D

- 59 36

Figure D

- 20. Multistage BMD model (1 degree) for the incidence of hepatocellular 37

adenoma in female Osborne

- Mendel rats exposed to 1,4

- dioxane in drinking 38

water.

................................ ................................ ................................ ................. D

- 61 39

Figure D

- 21. LogLogistic BMD model for the incidence of nasal cavity squamous cell 40

carcinoma in female Osborne

- Mendel rats exposed to 1,4

- dioxane in drinking 41

water.

................................ ................................ ................................ ................. D

- 64 42

Figure D

- 22. Multistage BMD model (1 degree) for the incidence of nasal cavity 43

squamous cell carcinoma in female Osborne

- Mendel rats exposed to 44

1,4

- dioxane in drinking water.

................................ ................................ ............ D

- 66 45DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xvi Figure D

- 23. LogLogistic BMD model for the incidence of nasal cavity squamous cell 1

carcinoma in male Osborne

- Mendel rats

................................ ............................. D

- 69 2

Figure D

- 24. Multistage BMD model (1 degree) for the incidence of nasal cavity 3

squamous cell carcinoma in male Osborne

- Me ndel rats

................................ ...... D

- 71 4

Figure D

- 25. Multistage BMD model (2 degree) for the incidence of hepatocellular 5

adenoma or carcinoma in female B6C3 F 1 mice

................................ ................... D

- 75 6

Figure D

- 26. Gamma BMD model for the incidence of hepatocellular adenoma or 7

carcinoma in male B6C3F 1 mice exposed to 1 ,4

- dioxane in drinking water.

........ D

- 78 8

Figure D

- 27. Multistage BMD model (2 degree) for the incidence of hepatocellular 9

adenoma or carcinoma in male B6C3F 1 mice exposed to 1,4

- dioxane in 10

drinking w ater.

................................ ................................ ................................ .... D

- 80 11

Figure F

- 1. BMD Dichotomous Hill model of centrilobular necrosis incidence data for 12

male rats exposed to 1,4

- dioxane va pors for 2 years to support the results in 13

Table F

- 2.

................................ ................................ ................................ ........... F

- 15 14

Figure F

- 2. BMD Dichotomous

- Hill model of spongiosis hepatis incidence data for male 15

rats exposed to 1,4

- dioxane vapors for 2 years to support the results in Table F

16

4.

................................ ................................ ................................ ........................ F

- 18 17

Figure F

- 3. BMD Log

- Logisti c model of spongiosis hepatis incidence data for male rats 18

exposed to 1,4

- dioxane vapors for 2 years to support the results in Table F

- 4.

..... F

- 20 19

Figure F

- 4. BMD Log

- probit model of squamous cell metaplasia of the respiratory 20

epithelium incidence data for male rats exposed to 1,4

- dioxane vapors for 2 21

years to support the results in Table F

- 6.

................................ ............................. F

- 23 22

Figure F

- 5. BMD Log

- probit model of squamous cell hyperplasia of the respiratory 23

epithelium incidence data for male rats exposed to 1,4

- dioxane vapors for 2 24

years to support the results in Table F

- 8.

................................ ............................. F

- 26 25

Figure F

- 6. BMD Gamma model of respiratory metaplasia of olfactory epithelium 26

incidence dat a for male rats exposed to 1,4

- dioxane vapors for 2 years to 27

support the results in Table F

- 11.

................................ ................................ ........ F

- 30 28

Figure F

- 7. BMD Log

- Logistic model of atrophy of olfactory epithelium incidence data 29

for male rats exposed to 1,4

- dioxane vapors for 2 years to support the results in 30

Table F

- 13.

................................ ................................ ................................ ......... F

- 33 31

Figure F

- 8. BMD Log

- logistic model of hydropic change of lamina propria (nasal cavity) 32

incidence data for male rats exposed to 1,4

- dioxane vapors for 2 years to 33

support the results in Table F

- 16.

................................ ................................ ........ F

- 36 34

Figure F

- 9. BMD Log

- logistic model of sclerosis of lamina propria (nasal cavity) 35

incidence data for male rats exposed to 1,4

- dioxane vapors for 2 years to 36

support the results in Table F

- 18.

................................ ................................ ........ F

- 40 37

Figure G

- 1. Multistage model (1 st

- degree) for male rat nasal squamous cell carcinomas.

....... G

- 44 38

Figure G

- 2. Multistage model (1 st

- degree) for male rat hepatocellular adenomas and 39

carcinomas.

................................ ................................ ................................ ......... G

- 46 40

Figure G

- 3. Multistage model (2 nd

- degree) for male rat renal cell carcinomas and Zymbal 41

gland adenomas.

................................ ................................ ................................ . G

- 49 42

Figure G

- 4. Multistage model (3 rd

- degree) for male rat renal cell carcinomas.

....................... G

- 51 43

Figure G

- 5. Multistage model (1 st

- degree) for male rat peritoneal mesotheliomas.

................. G

- 54 44

Figure G

- 6. Mult istage model (1 st

- degree) for male rat mammary gland fibroadenoma.

......... G

- 56 45DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xvii Figure G

- 7. Multistage model (1 st

- degree) for male rat subcutis fibroma (high dose 1

dropped).

................................ ................................ ................................ ............ G

- 59 2DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xviii LIST OF ABBREVIATIONS AND ACRONYMS

AIC Akaike‘s Information Criterion 1

ALP alkaline phosphatase 2

ALT alanine aminot ransferase 3

AST aspartate aminotransferase 4

ATSDR Agency for Toxic Substances and Disease Registry 5

BMC benchmark concentration 6

BMCL benchmark concentration, lower 95% confidence limit 7

BMCL 10 benchmark concentration, lower 95% confidence limit at 10% extra risk 8

BMD benchmark dose 9

BMD 10 benchmark dose at 10% extra risk 10

BMD 30 benchmark dose at 30% extra risk 11

BMD 50 benchmark dose at 50% extra risk 12

BMDL benchmark dose, lower 95% confidence limit 13

BMDL 10 benchmark dose, lower 95% confidence limit at 10% extra risk 14

BMDL 30 benchmark dose, lower 95% confidence limit at 30% extra risk 15

BMDL 50 benchmark dose, lower 95% confidence limit at 50% extra risk 16

BMDS Benchmark Dose Software 17

BMR benchmark response 18

Brd U 5

- bromo

- 2‘

- deoxyuridine 19

BUN blood urea nitrogen 20

BW (s) body weight (s) 21

CASE computer automated structure evaluator 22

CASRN Chemical Abstracts Service Registry Number 23

CHO Chinese hamster ovary (cells) 24

CI confidence interval(s) 25

CNS central nervous system 26

CPK creatinine phosphokinase 27

CREST antikinetochore 28

CSF cancer slope factor 29

CV concentration in venous blood 30

CYP450 cytochrome P450 31

DEN diethylnitrosamine 32

FISH fluorescence in situ hybridization 33

G

- 6

- Pase glucose

- 6

- phosphatase 34

GC gas chromatography 35

GGT γ

- glutamyl transpeptidase 36

GST

- P glutathione S

- transf erase placental form 37

HEAA β

- hydroxyethoxy acetic acid 38

HED(s) human equivalent dose(s) 39

HPLC high

- performance liquid chromatography 40

HSDB Hazardous Substances Data Bank 41

Hz Hertz 42

IARC International Agency for Research on Cancer 43

i.p. intraperitoneal 44DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xix i.v. intravenous 1

IRIS Integrated Risk Information System 2

JBRC Japan Bioassay Research Center 3

k

e 1st order elimination rate of 1,4

- dioxane 4

k INH 1st order 1,4

- dioxane inhalation rate constant 5

k LC 1st order , non

- saturable metabolism rate constant for 1,4

- dioxane in the liver 6

K

m Michaelis constant for metabolism of 1,4

- dioxane in the liver 7

k

me 1st order elimination rate of HEAA ( 1,4

- dioxane metabolite ) 8

k OC soil organic carbon

- water portioning coefficient 9

LAP leucine aminopeptidase 10

LD 50 median lethal dose 11

LDH lactate dehydrogenase 12

LOAEL lowest

- observed

- adverse

- effect

- level 13

MCH mean corpuscular hemoglobin 14

MCV mean corpuscular volume 15

MOA mode of action 16

MS mass spectrometry , multi

- stage 17

MTD maximum tolerated dose 18

MVK Moolgavkar

- Venzon

- Knudsen (mode l) 19

NCE normochromatic erythrocyte 20

NCI National Cancer Institute 21

ND no data , not detected 22

NE not estimated 23

NOAEL no

- observed

- adverse

- effect

- level 24

NRC National Research Council 25

NTP National Toxicology Program 26

OCT ornithine carbamyl transferase 27

ODC ornithine decarboxylase 28

OECD Organization for Economic Co

- operation and Development 29

PB blood:air partition coefficient 30

PBPK physiologically based pharmacokinetic 31

PC partition coefficient 32

PCB polychlorinated biphenyl 33

PCE polychromatic erythrocyte 34

PFA fat:air partition coefficient 35

PLA liver:air partition coefficient 36

POD point of departure 37

ppm parts per million 38

PRA rapidly perfused tissue:air partition coefficient 39

PSA slowly perfused tissue:air partition coefficient 40

QCC normalized cardiac output 41

Q PC normalized alveolar ventilation rate 42

RBC red blood cell 43

RfC inhalation reference concentration 44

RfD oral reference dose 45

SCE sister chromatid exchange 46DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xx SDH sorbitol dehydrogenase 1

SMR standardized mortality ratio 2

SRC Syracuse Research Corporation 3

T PA 12

- O

- tetradecanoylphorbol

- 13

- acetate 4

TWA time

- weighted average 5

UF uncertainty factor 6

UNEP United Nations Environment Programme 7

U.S. EPA U.S. Environmental Protection Agency 8

V volts 9

VAS visual analogue scale 10

V d volume of distribution 11

V

max maximal rate of metabolism 12

V

max C n ormalized maximal rate of metabolism of 1,4

- dioxane in liver 13

VOC(s) volatile organic compound ( s ) 14

WBC white blood cell 15

χ

2 Chi

- s quared 16DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xxi FOREWORD 1

The purpose of this Toxicological Review is to provide scientific support and rationale 2

for the hazard and dose

- response assessment in IRIS pertaining to chronic exposure to 3

1,4

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

nature of 1,4

- dioxane

. 5

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

Response , is to present the major conclusions reached in the derivation of the reference dose, 7

reference concentration, and cancer a ssessment, where applicable, and to characterize the overall 8

confidence in the quantitative and qualitative aspects of hazard and dose response by addressing 9

the quality of the data and related uncertainties. The discussion is intended to convey the 10

limit ations of the assessment and to aid and guide the risk assessor in the ensuing steps of the 11

risk assessment process. 12

For other general information about this assessment or other questions relating to IRIS, 13

the reader is referred to EPA‘s IRIS Hotline at (202) 566

- 1676 (phone), (202) 566

- 1749 (fax), or 14

hotline.iris@epa.gov (email address). 15

NOTE: New studies ( Kasai et al., 2009 ; Kasai et al., 2008 ) regarding the toxicity of 16

1,4

- dioxane through the inhalation route of exposure are available that were not included in the 17

1,4

- dioxane assessment that was posted on the IRIS database in 2010 ( U.S. EPA, 2010 )

. 18

These studies have been incorporated into the previously posted assessment for re view 19

( U.S. EPA, 2010 ) . Sections including new information can be identified by the red underlined 20

text in the document. The entire document is provided for complete ness. 21DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xxii AUTHORS, CONTRIBUTORS, AND REVIEWERS 1

CHEMICAL MANAGERS /AUTHORS 2

3

Patricia Gillespie, Ph.D. 4

National Center for Environmental Assessment 5

U.S. Environmental Protection Agency 6

Research Triangle Park, NC 7

8

Eva D. McLanahan , Ph.D. 9

Lieutenant Commander

, U.S. Public Health Service 10

National Center for Environmental Assessment 11

U.S. Environmental Protection Agency 12

Research Triangle Park, NC 13

14

Reeder Sams II , Ph.D. 15

National Center for Environmental Assessment 16

U.S. Environmental Protection Agency 17

Research Trian gle Park, NC 18

19

AUTHORS AND CONTRIBUTORS 20

21

J. Allen Davis, MSPH 22

National Center for Environmental Assessment 23

U.S. Environmental Protection Agency 24

Research Triangle Park, NC 25

26

Hisham El

- Masri , Ph.D. 27

National Health and Environmental Effects Research Laboratory 28

U.S. Environmental Protection Agency 29

Research Triangle Park, NC 30

31

Jeff S. Gift, Ph.D. 32

National Center for Environmental Assessment 33

U.S. Environmental Protection Agency 34

Research Triangle Park, NC 35

36

Karen Hogan 37

National Center for Environmental Assessment 38

U.S. Environmental Protection Agency 39

Washington, DC 40

41

Leonid Kopylev, Ph.D. 42

National Center for Environmental Assessment 43

U.S. Environmental Protection Agency 44

Washington, DC 45

46DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xxiii William Lefew, Ph.D. 1

National Health and Environmental Effects Research Laboratory 2

U.S. Environmental Protection Agency 3

Research Triangle Park, NC 4

5

Fernando Llados 6

Environmental Science Center 7

Syracuse Research Corporation 8

Syracuse, NY 9

10

Michael Lumpkin , Ph.D. 11

Environmental Science Center 12

Syracuse Research Corporation 13

Syracuse, NY 14

15

Allan Marcus , Ph.D. 16

National Center for Environmental Assessment 17

U.S. Environmental Protection Agency 18

Research Triangle Park, NC 19

20

Marc Odin , Ph.D. 21

Environmental Science Center 22

Syracuse Research Corporation 23

Syracuse, NY 24

25

Susan Rieth 26

National Center for Environmental Assessment 27

U.S. Environmental Protection Agency 28

Washington, DC 29

30

Andrew Rooney , Ph.D. * 31

National Center for Environmental Assessment 32

U.S. Environmental Protection Agency 33

Research Triangle Park, NC 34

* Currently at National Toxicology Program 35

National Institute of Environmental Health Sciences 36

Research Triangle Park, NC 37

38

Paul Schlosser , Ph.D. 39

National Center for Environmental Assessment 40

U. S. Environmental Protection Agency 41

Research Triangle Park, NC 42

43

John Stanek , Ph.D. 44

National Center for Environmental Assessment 45

U.S. Environmental Protection Agency 46

Research Triangle Park, NC 47DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xxiv Julie Stickney , Ph.D. 1

Environmental Science Center 2

Syracuse Research Corporation 3

Syracuse, NY 4

5

John Vandenberg , Ph.D. 6

National Center for Environmental Assessment 7

U.S. Environmental Protection Agency 8

Research Triangle Park, NC 9

10

Debra Walsh , M.S. 11

National Center for Environmental Assessment 12

U.S. Environmental Protection Agency 13

Research Triangle Park, NC 14

15

REVIEWERS 16

This document has been provided for review to EPA scientists, interagency reviewers 17

from other federal agencies and White House offices, and the public, and peer reviewed by 18

independent scientists e xternal to EPA. A summary and EPA‘s disposition of the comments 19

received from the independent external peer reviewers and from the public is included in 20

Appendix A. 21

22

INTERNAL EPA REVIEWERS (ORAL ASSESSMENT) 23

24

Anthony DeAngelo , Ph.D. 25

National Health and Environmental Effects Research Laboratory 26

Office of Research and Development 27

28

Nagu Keshava , Ph.D. 29

National Center for Environmental Assessment 30

Office of Research and Development 31

32

Jason Lambert , Ph.D. 33

National Center for Environmenta l Assessment 34

Office of Research and Development 35

36

Connie Meacham , M.S. 37

National Center for Environmental Assessment 38

Research Triangle Park, NC 39

40DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE xxv Douglas Wolf

, Ph.D. 1

National Health and Environmental Effects Research Laboratory 2

Office of Research and Development 3

4

EXTERNAL PEER REVIEWERS (ORAL ASSESSMENT) 5

6

George V. Alexeeff

, Ph.D., DABT 7

Office of Environmental Health Hazard Assessment (OEHHA) 8

California EPA 9

10

Bruce C. Allen, M.S. 11

Bruce Allen Consulting 12

13

James V. Bruckner, Ph.D. 14

Department of Pharmaceutical and Biomedical Sciences 15

College of Pharmacy 16

The University of Georgia 17

18

Harvey J. Clewell III, Ph.D., DABT 19

Center for Human Health Assessment 20

The Hamner Institutes for Health Sciences 21

22

Lena Ernstgård, Ph.D. 23

Institute of Environmental Medicine 24

Karolinska Institutet 25

26

Frederick J. Kaskel, M.D., Ph.D. 27

Children‘s Hospital at Montefiore 28

Albert Einstein College of Medicine of Yeshiva University 29

30

Kannan Krishnan, Ph.D., DABT 31

Inter

- University Toxicology Research Center (CIRTOX) 32

Université de Montréal 33

34

Ragubir P. Sharma, DVM, Ph.D. 35

Department of Physiology and Pharmacology 36

College of Veterinary Medicine ( retired ) 37

The University of Georgia 38

39

EXTERNAL PEER REVIEWERS (INHALATION ASSESSMENT) 40

TO BE DETERMINED 41

421

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

1. INTRODUCTION

This document presents background information and justification for the Integrated Risk 1

Information System (IRIS) Summary of the hazard and dose

- response assessment of 2

1,4

- dioxane . IRIS Summaries may include oral reference dose (RfD) and inhalation reference 3

concentration (RfC) values for chronic and subchronic exposure durations, and a carcinogenicity 4

assessment. 5

The RfD and RfC, if derived, provide quantitative informatio n for use in risk assessments 6

for health effects known or assumed to be produced through a nonlinear ( presumed threshold) 7

mode of action. The RfD (expressed in units of mg /kg

- day) is defined as an estimate (with 8

uncertainty spanning perhaps an order of ma gnitude) of a daily exposure to the human 9

population (including sensitive subgroups) that is likely to be without an appreciable risk of 10

deleterious effects during a lifetime. The inhalation RfC (expressed in units of mg /m 3 ) is 11

analogous to the oral RfD, but provides a continuous inhalation exposure estimate. The 12

inhalation RfC considers toxic effects for both the respiratory system (portal

- of

- entry) and for 13

effects peripheral to the respiratory system (extrarespiratory or systemic effects). Reference 14

va lues are generally derived for chronic exposures (up to a lifetime), but may also be derived for 15

acute (≤ 24 hour s), short

- term (>24 hour s up to 30 day s), and subchronic (>30 day s up to 10% of 16

lifetime) exposure durations, all of which are derived based on an assumption of continuous 17

exposure throughout the duration specified. Unless specified otherwise, the RfD and RfC are 18

derived for chronic exposure duration. 19

The carcinogenicity assessment provides information on the carcinogenic hazard 20

potential of the substance in question and quantitative estimates of risk from oral and inhalation 21

exposure may be derived. The information includes a weight

- of

- evidence judgment of the 22

likelihood that the agent is a human carcinogen and the conditions under which the ca rcinogenic 23

effects may be expressed. Quantitative risk estimates may be derived from the application of a 24

low

- dose extrapolation procedure. If derived, the oral slope factor is a plausible upper bound on 25

the estimate of risk per mg /kg

- day of oral exposur e. Similarly, a n inhalation unit risk is a 26

plausible upper bound on the estimate of risk per μg/m 3 air breathed. 27

Development of these hazard identification and dose

- response assessments for 28

1,4

- dioxane has followed the general guidelines for risk assessme nt as set forth by the National 29

Research Council ( NRC, 1983 ) . EPA guidelines and Risk Assessment Forum Technical Panel 30

Reports that may have been used in the development of this assessment include the following: 31

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 Ris k Information System (IRIS)

.2

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Guidelines for the Health Risk Assessment of Chemical Mixtures ( U.S. EPA, 1986c )

, Guidelines 1

for Mutagenicity Risk Assessment ( U.S. EPA, 1986b )

, Recommendations for and Documentation 2

of Biological Values for Use in Risk Assessment ( U.S. EPA, 1988 )

, G uidelines for 3

Developmental Toxicity Risk Assessment ( U.S. EPA , 1991 )

, Interim Policy for Particle Size and 4

Limit Concentration Issues in Inhalation Toxicity ( U.S. EPA, 1994a )

, Methods for Derivation of 5

Inhalation Reference Concentrations and Application of Inhalation Dosimetry ( U.S. EPA, 6

1994b )

, Use of the Benchmark Dose Approach in Health Ris k Assessment ( U.S. EPA, 1995 )

, 7

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

, Guidelines for 8

Neurotoxicity Risk Assessment ( U.S. EPA, 1998 )

, Science Policy Council Handbook : Risk 9

Characterization ( U.S. EPA, 2000b )

, Benchmark Dose Technical Guidance Document (External 10

Review Draft) ( U.S. EPA, 2000a )

, Supplementary Guidance for Conducting Health Risk 11

As sessment of Chemical Mixture s ( U.S. EPA, 2000c )

, A Review of the Reference Dose and 12

Reference Concentration Processes ( U.S. EPA, 2002a )

, Guidelines for Carcinogen Risk 13

Assessment ( U.S. EPA, 2005a )

, Supplemental Guidance for Assessing Susceptibility from Early

14

Life Exposure to Carcinogens ( U.S. EPA, 2005b )

, Sci ence Policy Council Handbook : Peer 15

Review ( U.S. EP A, 2006b ) , and A Framework for Assessing Health Risks of Environmental 16

Exposures to Children ( U.S. EPA, 2006a )

. 17

The literature search strategy employed for this compound was based on the Chemical 18

Abstracts Service Registry Number (CASRN) and at least one common name. Any p ertinent 19

scientific information submitted by the public to the IRIS Submission Desk was also considered 20

in the development of this document. The relevant literature was reviewed through September 21

2009 for the oral assessment and through March 2011 for the inhalation assessment. 223

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 2. CHEMICAL AND PHYSICA L INFORMATION

1,4

- D ioxane , a volatile organic compound (VOC), is a colorless liquid with a pleasant 1

odor ( Hawley & Lewis Rj Sr, 2001 ; Lewis, 2000 )

. Synonyms include diethylene ether, 2

1,4

- diethylene dioxide, diethylene oxide, dioxyethylene ether, and dioxane ( Hawley & Lewis 3

Rj Sr, 2001 ) . The chemical structure of 1,4

- dioxane is shown in Figure 2

- 1. Selected chemical 4

and physical properties of thi s substance are listed in Table 2

- 1 below: 5

Figure 2

- 1

. 1,4

- D ioxane 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 databas e of scientific literature used

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

and the Integrate d Risk Information System (IRIS)

.4

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 2

- 1. Physical properties and chemical identity of 1,4

- dioxane

CASRN: 123

- 91

- 1 ( CRC, 2000 )

Molecular weight: 88.10 ( The Merck Index: An Encyclopedi a of Chemicals,

Drugs, and Biologicals , 2001 )

Chemical formula: C 4 H 8 O 2 ( The Merck Index: An Encyclopedia of

Chemicals, Drugs, and Biologicals , 2001 )

Boiling point: 101.1°C ( The Merck Index: An Encyclopedia of

Chemical s, Drugs, and Biologicals , 2001 )

Melting point: 11.8°C ( CRC, 2000 )

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

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

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

Water solubility: Miscible with water ( Hawley & Lewi s Rj Sr, 2001 )

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

Log K

ow :

– 0.27 ( Hansch, Leo, & Hoekman, 1995 )

Henry‘s Law constant: 4.80 10

- 6 atm

- m 3 /molecule at 25°C ( Park, Hussam,

Couasnon, Fritz, & Carr, 1987 )

OH reaction rate constant: 1.09 10

- 11 cm 3 /molecule sec at 25°C ( Atkinson, 1989 )

K

oc : 17 (estimated using log K

ow ) ( ACS, 1990 )

Bioconcentration factor: 0.4 (estimated using log K

ow ) ( Meylan et al., 1999 )

Conversion factors (in air): 1 ppm = 3.6 mg /m 3 ; 1 mg /m 3 = 0.278 ppm

(25 o C and 1 atm) ( HSDB, 2007 )

1,4

- D ioxane is produced commercially through the dehydration and ring closure of 1

diethylene glycol ( Surprenant, 2002 ) . Concentrated sulfuric acid is used as a catalyst 2

( Surprenant, 2002 ) . This is a continuous distillation process with operating temperatures and 3

pressures of 130

– 200°C and 188

– 825 mmHg , respectively ( Surprenant, 2002 ) . During the years 4

1986 and 1990, the U.S. production of 1,4

- dioxane reported by manufacturers was within the 5

range of 10

– 50 million pounds ( U.S. EPA, 2002b ) . The production volume reported during the 6

years 1994, 1998, and 2002 was within the range of 7

1

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

. 8

Historically, 1,4

- dioxane has been used as a stabilizer for the solvent 1,1,1

- trichloro

9

ethane ( Surprenant, 2002 ) . However, this use is no longer expected to be important due to the 10

1990 Amendments to the Clean Air Act and the Montreal Protocol, which mandate the eventual 11

phase

- out of 1,1,1

- trichloroethane production in the U. S

. ( "Amendments to the Clean Air Act. 12

Sec. 604. Phase

- out of production and consumption of class I substances," 1990 ; ATSDR, 2007 ; 13

U.N. Environment Programme, 2000 )

. 1,4

- Dioxane is a contaminant of some ingredients used in 145

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE the manufacture of personal care products and cosmetics. 1,4

- D ioxane is also used as a solvent 1

for cellulosics, organic produc ts, lacquers, paints, varnishes, paint and varnish removers, resins, 2

oils, waxes, dyes, cements, fumigants, emulsions, and polishing compositions ( Hawley & Lewis 3

Rj Sr, 2001 ; IA RC, 1999 ; The Merck Index: An Encyclopedia of Chemicals, Drugs, and 4

Biologicals , 2001 )

. 1,4

- D ioxane has been used as a solvent in the formulat ion of inks, coatings, 5

and adhesives and in the extraction of animal and vege t able oil ( Surprenant, 2002 ) . Reaction 6

products of 1,4

- dioxane are used in the manufacture of insecticides, herbicides, plasticizers, and 7

monomers ( Surprenant, 2002 )

. 8

When 1,4

- dioxane enters the air, it will exist as a vapor, as indicated by its vapor pressure 9

( HSDB, 2007 ) . It is expected to be degraded in the atmosphere through photooxidation with 10

hydroxyl radicals ( HSDB, 2007 ; Surprenant, 2002 ) . The estimated half

- life for this reaction is 11

6.7 hour s ( HSDB, 2007 ) . It may also be broken down by reaction with nitrate radicals, although 12

this removal process is not expected to compete with hydroxyl radical photooxidation ( Grosjean, 13

1990 )

. 1,4

- D ioxane is not expected to undergo direct photolysis ( Wolfe & Jeffers, 2000 )

. 14

1,4

- D ioxane is primarily photooxidized to 2

- o xodioxane and through reactions with nitrogen 15

oxides (NO

x ) results in the formation of ethylene glycol diformate ( Platz, Sehested, Mogelberg, 16

Nielsen, & Wallington, 1997 )

. 1,4

- D ioxane is expected to be highly mobile in soil based on its 17

estimated K

oc and is expected to leach to lower soil horizons and groundwater ( ACS, 1990 ; 18

ATSDR, 2007 ) . This substance may volatilize from dry soil surfaces based on its vapor pressure 19

( HSDB, 2007 ) . The estimated bioconcentration factor value indicates that 1,4

- dioxane will not 20

bioconcentrate in aquatic or marine organisms ( Franke et al., 1994 ; Meylan, et al., 1999 )

. 21

1,4

- D ioxane is not expected to undergo hydrolysis or to biodegrade readily in the environment 22

( ATSDR, 2007 ; HSDB, 2007 ) . Therefore, volatilization is expected to be the dominant removal 23

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

- 6 24

atm

- m

3 /mole, the half

- life for volatilization of 1,4

- dioxane from a model river is 5 day s and that 25

from a model lake is 56 day s ( ACS, 1990 ; HSDB, 2007 ; Park, et al., 1987 )

. 1,4

- D ioxane may be 26

more persistent in groundwater w here volatilization is hindered. 27

Recent environmental monitoring data for 1,4

- dioxane are lacking. Existing data indicate 28

that 1,4

- dioxane may leach from hazardous waste sites into drinking water sources located 29

nearby ( Lesage, Jackson, Priddle, & Riemann, 1990 ; Yasuhara et al., 1997 ; Yasuhara, Tanaka, 30

Tanabe, Kawata, & Katami, 2003 )

. 1,4

- D ioxane has been detected in contaminated surface and 31

groundwater samples collected near hazardous waste sites and industrial facilities ( Derosa, 32

Wilbur, Holler, Richter, & Stevens, 1996 )

. 336

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

3. TOXICOKINETICS

Data for the toxicokinetics of 1,4

- dioxane in humans are very limited. However, 1

absorption, distribution, metabolism, and elimination of 1,4

- dioxane are well described in rats 2

exposed via the oral, inhalation, or intravenous (i.v.) routes

. 1,4

- D ioxane is extensively absorbed 3

and metabolized in h umans and rats . The metabolite most often measured and reported is 4

β

- h ydroxyethoxy acetic acid (HEAA), which is predominantly excreted in the urine ; however, 5

other metabolites have also been identified . Saturation of 1,4

- dioxane metabolism has been 6

obser ved in rats and would be expected in humans; however, human exposure levels associated 7

with nonlinear toxicokinetics are not known. 8

Important data elements that have contributed to our current understanding of the 9

toxicokinetics of 1,4

- dioxane are summari zed in the following sections. 10

3.1. ABSORPTION

Absorption of 1,4

- dioxane following inhalation exposure has been qualitatively 11

demonstrated in workers and volunteers. Workers exposed to a time

- weighted average (TWA) 12

of 1.6 parts per million ( ppm ) of 1,4

- dioxane in air for 7.5 hour s showed a HEAA/ 1,4

- dioxane 13

ratio of 118:1 in urine ( Young, Braun, Gehring, Horvath, & Daniel, 1976 ) . The authors assumed 14

lung absorption to be 100% and calculated an average absorbed dose of 0.37 mg /kg, although no 15

exhaled breath measurements were taken. In a study with four healthy male volunteers, Young 16

et al

. ( 1977 ) reported 6

- hour inhalation exposures of adult volunteers to 50 ppm of 1,4

- dioxane 17

in a chamber, followed by blood and urine analysis for 1,4

- dioxane and HEAA. The study 18

protocol was approved by a seven

- member Human Research Review Committee of the Dow 19

Chemical Co mpany, and written informed consent of study participants was obtained. At a 20

concentration of 50 ppm, uptake of 1,4

- dioxane into plasma was rapid and approached steady

21

state conditions by 6 hour s. The authors reported a calculated absorbed dose of 5.4 mg /kg. 22

However, the exposure chamber atmosphere was kept at a constant concentration of 50 ppm and 23

exhaled breath was not analyzed. Accordingly, gas uptake could not be measured. As a result, 24

the absorbed fraction of inhaled 1,4

- dioxane could not be accur ately determined in humans. Rats 25

inhaling 50 ppm for 6 hour s exhibited 1,4

- dioxane and HEAA in urine with an HEAA to 26

1,4

- dioxane ratio of over 3,100:1 ( J. D. Young, W. H. Braun, & P. J. Gehring, 1978a ; J. D. 27

Young, W. H. Braun, & P. J Gehring, 1978b ) . Plasma concentrations at the end of the 6

- hour 28

exposure period averaged 7.3 μg/mL. The authors calculated an absorbed 1,4

- dioxane dose of 29

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 da tabase of scientific literature used

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

and the Inte grated Risk Information System (IRIS)

.7

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 71.9 mg /kg; ho wever, the lack of exhaled breath data and dynamic exposure chamber precluded 1

the accurate determination of the absorbed fraction of inhaled 1,4

- dioxane

. 2

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

- dioxane

. 3

Gastrointestinal absorpti on was nearly complete in male Sprague Dawley rats orally dosed with 4

10

– 1

, 000 mg /kg of [ 14 C ]

- 1,4

- dioxane given as a single dose or as 17 consecutive daily doses 5

( Young, et al., 1978a ; Young, et al., 1978b )

. Cumulative recovery of radiolabel in the feces was 6

<1

– 2% of administered dose regardless of dose level or frequency. 7

No human data are available to evaluate the dermal absorption of 1, 4

- dioxane ; however, 8

Bronaugh ( 1982 ) reported an in vitro study in which 1,4

- dioxane penetrated excised human skin 9

10 times more under occ l uded conditions (3.2% of applied dose) than unocc l uded conditions 10

(0.3% of applied dose). [ 14 C ]

- 1,4

- D ioxane was dissolved in lotion, applied to the excised skin in 11

occluded and unoccluded diffusion cells, and absorption of the dose was recorded 205 m inutes 12

after application. Bronaugh ( 1982 ) also reported observing rapid evaporation, which further 13

decreased the small amount available for skin absorption. 14

Dermal absorption data in animals are also limited. Dermal absorption in animals was 15

reported to be low following exposure of forearm ski n of monkeys ( Marzulli, Anjo, & Maibach, 16

1981 ) . In this study, Rhesus monkeys were exposed to [ 14 C ]

- 1,4

- dioxane in me thanol or skin 17

lotion vehicle for 24 hour s (skin was uncovered/unoccluded). Only 2

– 3% of the original 18

radiolabel was cumulatively recovered in urine over a 5

- day period. 19

3.2. DISTRIBUTION

No data are available for the distribution of 1,4

- dioxane in human ti ssues. No data are 20

available for the distribution of 1,4

- dioxane in animals following oral or inhalation exposures. 21

Mikheev et al

. ( 1990 ) studied the distribution of [ 14 C ]

- 1,4

- dioxane in the blood, liver, 22

kidney, brain, and testes of rats (strain not reported) for u p to 6 hour s following intraperitoneal 23

(i.p.) injection of approximately one

- tenth the median lethal dose ( LD 50 ) (actual dose not 24

reported). While actual tissue concentrations were not reported, tissue:blood ratios were given 25

for each tissue at six time points ranging from 5 minutes to 6 hour s. The time to reach maximum 26

accumulation of radiolabel was shorter for l iver and kidney than for blood or the other tissues, 27

which the authors suggested was indicative of selective membrane transport. Tissue:blood ratios 28

were less than one for all tissues except testes, which had a ratio greater than one at the 6

- hour 29

time po int. The significance of these findings is questionable since the contribution of residual 30

blood in the tissues was unknown (though saline perfusion may serve to clear tissues of highly 31

water

- soluble 1,4

- dioxane ), the tissue concentrations of radiolabel w ere not reported, and data 32

were collected from so few time points. 33

Woo et al

. ( 1977 ) administered i.p. doses of [ 3 H]

- 1,4

- dioxane (5 mCi/kg body weight 34

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

- function oxidase 358

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE inducers (phenobarbital, 3

- methylcholanthrene, or polychlorinat ed biphenyls [PCBs]). Liver, 1

kidney, spleen, lung, colon, and skeletal muscle tissues were collected from 1, 2, 6, and 12 hour s 2

after dosing. Distribution was generally uniform across tissues, with blood concentrations higher 3

than tissues at all times ex cept for 1 hour post dosing, when kidney levels were approximately 4

20% higher than blood. Since tissues were not perfused prior to analysis, the contribution of 5

residual blood to radiolabel measurements is unknown, though loss of 1,4

- dioxane from tissues 6

would be unknown had saline perfusion been performed. Covalent binding reached peak 7

percentages at 6 hour s after dosing in liver (18.5%), spleen (22.6%), and colon (19.5%). At 8

16 hour s after dosing, peak covalent binding percentages were observed in whol e blood (3.1%), 9

kidney (9.5%), lung (11.2%), and skeletal muscle (11.2%). Within hepatocytes, radiolabel 10

distribution at 6 hour s after dosing was greatest in the cytosolic fraction (43.8%) followed by the 11

microsomal (27.9%), mitochondrial (16.6%), and nuc lear (11.7%) fractions. While little 12

covalent binding of radiolabel was measured in the hepatic cytosol (4.6%), greater binding was 13

observed at 16 hour s after dosing in the nuclear (64.8%), mitochondrial (45.7%), and 14

microsomal (33.4%) fractions. Pretrea tment with inducers of mixed

- function oxidase activity 15

did not significantly change the extent of covalent binding in subcellular fractions. 16

3.3. METABOLISM

The major product of 1,4

- dioxane metabolism appears to be HEAA, although there is 17

one report that ide ntified 1,4

- dioxane

- 2

- one as a major metabolite ( Woo, Arcos, et al., 1977 )

. 18

However, the presence of this compound in the sample was believed to result from the acidic 19

conditions (pH of 4.0

– 4.5) of the analytical procedures. The reversible conversion of HEAA and 20

p

- 1,4

- dioxane

- 2

- one is pH

- dependent ( Braun & Young, 1977 ) . Braun and Young ( 1977 ) 21

identified HE AA (85%) as the major metabolite, with most of the remaining dose excreted as 22

unchanged 1,4

- dioxane in the urine of Sprague Dawley rats dosed with 1

, 000 mg /kg of 23

uniformly labeled 1,4

- [ 14 C ]dioxane. In fact, toxicokinetic studies of 1,4

- dioxane in humans a nd 24

rats ( Young, et al., 1978a ; Young, et al., 1978b ; Young, et al., 1977 ) employed an analytical 25

technique that converted HEAA to the more volatile 1,4

- dioxan e

- 2

- one prior to gas 26

chromatography ( GC ) ; however, it is still unclear as to whether HEAA or 1,4

- dioxane

- 2

- one is 27

the major metabolite of 1,4

- dioxane

. 28

A proposed metabolic scheme for 1,4

- dioxane metabolism ( Woo, Arcos, et al., 1977 ) in 29

Sprague Dawley rats is shown in Figure 3

- 1. Oxid ation of 1,4

- dioxane to diethylene glycol 30

(pathway a), 1,4

- dioxane

- 2

- ol (pathway c), or directly to 1,4

- dioxane

- 2

- one (pathway b) could 31

result in the production of HEAA

. 1,4

- D ioxane oxidation appears to be cytochrome P450 32

(CYP450)

- mediated, as CYP450 induction with phenobarbital or Aroclor 1254 (a commercial 33

PCB mixture ) and suppression with 2,4

- dichloro

- 6

- phenylphenoxy ethylamine or cobaltous 34

chloride were effective in significantly increasing and decreasing, respectively, the appearance of 359

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE HEAA in the urine of male Sprague Dawley rats following 3 g/kg i

. p

. dose ( Woo, Argus, & 1

Arcos, 1977a

, 1978 )

. 1,4

- D ioxane itself induced CYP450

- mediated metabolism of several 2

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

- dioxane ( Mungikar 3

& Pawar, 1978 ) . Of the three possible pathways proposed in this scheme, oxidation to 4

diethylene glycol and HEAA appears to be the most likely, becaus e diethylene glycol was found 5

as a minor metabolite in Sprague Dawley rat urine following a single 1

, 000 mg /kg gavage dose 6

of 1,4

- dioxane ( Braun & Young, 1977 ) . Addition ally, i.p. injection of 100

– 400 mg /kg 7

diethylene glycol in Sprague Dawley rats resulted in urinary elimination of HEAA ( Woo, Argus, 8

& Arcos, 1977b )

. 9

Source: Adapted with permission f rom Elsevier Ltd.

, Woo et al

. ( 1977 ; 1977a )

.

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 propose d pathways do

not account for metabolite degradation to the labeled carbon dioxide ( CO 2 )

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 10

workers exposed to a TWA of 1.6 ppm of 1,4

- dioxane for 7.5 hour s, Young et al

. ( 1976 ) found 11

HEAA and 1,4

- dioxane in the worker‘s urine at a ratio of 118:1. Similarly, in adult male 12

volunteers exposed to 50 ppm for 6 hour s ( Young, et al., 1977 ) , over 99% of inhaled 1,4

- dioxane 13

(assuming negligible exhaled excretion) appeared in the urine as HEAA. The linear elimination 1410

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE of 1,4

- dioxane in both plasma and urine indicated that 1,4

- dioxane metabolism was a 1

nonsaturated, first

- order process at this exposure level. 2

Like humans, rats extensively metabolize inhaled 1,4

- dioxane , as HEAA content in urine 3

was over 3

, 000

- fold higher than that of 1,4

- dioxane following exposure to 50 ppm for 6 hour s 4

( Young, et al., 1978a ; Young, et al., 1978b )

. 1,4

- D ioxane metabolism in rats was a saturable 5

process, as exhibited by oral and i.v. exposures to various doses of [ 14 C ]

- 1,4

- dioxane ( Young, et 6

al., 1978a ; Young, et al., 1978b ) . Plasma data from Sprague Dawley rats given single i.v. doses 7

of 3, 10, 30, 100, 300, or 1

, 000 mg [ 14 C ]

- 1,4

- dioxane /kg demonstrated a dose

- related shift from 8

linear, first

- order to nonlinear, saturable metabolism of 1,4

- dioxane between plasma 1,4

- dioxane 9

levels of 30 and 100 μg/ mL ( Figure 3

- 2). Similarly, in rats given, via gavage in distilled water, 10

10, 100, or 1

, 000 mg [ 14 C ]

- 1,4

- dioxane /kg singly or 10 or 1

, 000 mg [ 14 C ]

- 1,4

- dioxane /kg in 11

17 daily doses, the percent urinary excretion of the r adiolabel decreased significantly with dose 12

while radiolabel in expired air increased. Specifically, with single [ 14 C ]

- 1,4

- dioxane /kg doses, 13

urinary radiolabel decreased from 99 to 76% and expired 1,4

- dioxane increased from <1 to 25% 14

as dose increased fro m 10 to 1

, 000 mg /kg. Likewise, with multiple daily doses 10 or 1

, 000 mg 15

[ 14 C ]

- 1,4

- dioxane /kg, urinary radiolabel decreased from 99 to 82% and expired 1,4

- dioxane 16

increased from 1 to 9% as dose increased. The differences between single and multiple doses in 17

urinary and expired radiolabel support the notion that 1,4

- dioxane may induce its own 18

metabolism. 19

Induction of 1,4

- dioxane metabolism is quantitatively illustrated by examining plasma 20

levels of the chemical in relationship to inhaled doses in a 13 week study by Kasai et al. ( 2008 )

. 21

In this study, male and female F344 rats were exposed daily to concentrations of 0 (control), 22

100, 200, 400, 1,600, and 3,200 ppm . Plasma levels of 1,4

- dioxane linearly increased with 23

increasing inhalation concentration, suggesting that metabolic saturation was not achieved during 24

the course of the experiments for plasma levels up to 730 and 1

, 054 μg/m L in male and femal e 25

rats, respectively, at the highest exposure concentration (3,200 ppm). In contrast, Young et al. 26

( 1978a ) single dose experiments showed possible saturatio n of metabolism at plasma levels of 27

100 μg/m L . Therefore, lack of the metabolic saturation of 1,4

- dioxane found in the Kasai et al. 28

( 2008 ) study is likely attributed to enhanced metabolism by the induction of P450 enzymes, 29

including CYP2E1, by 13 weeks of repeated inhalation exposure to 1,4

- dioxane at concentrations 30

up to 3,200 ppm ( Kasai, et al., 2008 )

. 31

3211

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Taylor and Francis, Young et al

. ( 1978a )

.

Figure 3

- 2. Plasma 1,4

- dioxane levels in rats following i.v. doses of

3

- 5

, 600 mg /kg [y

- axis is plasma concentration of 1,4

- dioxane (μg/mL) and x

axis is time (hr)]

1,4

- Dioxane has been shown to ind uce several isoforms of CYP450 in various tissues 1

following acute oral administration by gavage or drinking water ( Nannelli, De Rubertis, Longo, 2

& Gervasi, 2005 ) . Male Sprague Dawley rats were exposed to either 2

, 000 mg /kg 1,4

- dioxane 3

via gavage for 2 consecutive day s or by ingestion of a 1.5% 1,4

- dioxane drinking water solution 4

for 10 day s. Both exposures resulted in significantly increased CYP2B1/2, CYP2C11, and 5

CYP2E1 activities in hepatic microsomes. The gavage exposure alone resulted in increased 6

CYP3A activity. The increase in 2C11 activity was unexpected, as that isoform has been 7

observed to be under hormonal control and was typically suppressed in the presence of 2B1/2 8

and 2E1 induction. In the male rat, hepatic 2C11 induction is associated with masculine pulsatile 9

plasma profiles of growth hormone (compared to the constant plasm a levels in the female), 10

resulting in masculinization of hepatocyte function ( Waxman, Pampori, Ram, Agrawal, & 11

Shapiro, 1991 ) . The authors postulated that 1,4

- dioxane may alter plasma growth hormone 12

levels, resulting in the observed 2C11 induction. However, growth hormone induction of 2C11 1312

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE is primarily dependent on the duration between growth hormone pulses and secondarily on 1

growth hormone plasma levels ( Agrawal & Shapiro, 2000 ; Waxman, et al., 1991 )

. Thus, the 2

induction of 2C11 by 1,4

- dioxane may be mediated by changes in the time interval between 3

growth hormone pulses rather than changes in growth hormone levels. This may be 4

accomplished by 1,4

- dioxane temporarily influencing the presence of growth hormone cell 5

surface binding sites ( Agrawal & Shapiro, 2000 ) . However, no studies are available to confirm 6

the influence of 1,4

- dioxane on either growth hormone levels or changes in growth hormone 7

pulse interval. 8

In nasal and renal mucosal cell microsomes, CYP2E1 activity, but not CYP2B1/2 9

activity, was increased. Pulmonary mucosal CYP450 activity levels were not significantly 10

altered. Observed increases in 2E1 mRNA in rats exposed by gavage an d i.p. injection suggest 11

that 2E1 induction in kidney and nasal mucosa is controlled by a transcriptional activation of 12

2E1 genes. The lack of increased mRNA in hepatocytes suggests that induction is regulated via 13

a post

- transcriptional mechanism. Differ ences in 2E1 induction mechanisms in liver, kidney, 14

and nasal mucosa suggest that induction is controlled in a tissue

- specific manner. 15

3.4. ELIMINATION

In workers exposed to a TWA of 1.6 ppm for 7.5 hour s, 99% of 1,4

- dioxane eliminated in 16

urine was in the form of HEAA ( Young, et al., 1976 ) . The elimination h alf

- life was 59 minutes 17

in adult male volunteers exposed to 50 ppm 1,4

- dioxane for 6 hour s, with 90% of urinary 18

1,4

- dioxane and 47% of urinary HEAA excreted within 6 hour s of onset of exposure ( Young, et 19

al., 1977 ) . There are no data for 1,4

- dioxane elimination in humans from oral exposures. 20

Elimination of 1,4

- dioxane in rats ( Young, et al., 1978a ; Young, et al., 1978b ) was 21

primarily via urine. As comparably assessed in humans , the elimination half

- life in rats exposed 22

to 50 ppm 1,4

- dioxane for 6 hour s was calculated to be 1.01 hour s. In Sprague Dawley rats 23

given single daily doses of 10, 100, or 1

, 000 mg [ 14 C ]

- 1,4

- dioxane /kg or multiple doses of 10 or 24

1

, 000 mg [ 14 C ]

- 1,4

- dioxane /kg, urinary radiolabel ranged from 99% down to 76% of total 25

radiolabel. Fecal elimination was less than 2% for all doses. The effect of saturable metabolism 26

on expired 1,4

- dioxane was apparent, as expired 1,4

- dioxane in singly dosed rats increased with 27

dose from 0.4 to 25% while expired 14 CO 2 changed little (between 2 and 3%) across doses. The 28

same relationship was seen in Spra gue Dawley rats dosed i.v. with 10 or 1

, 000 mg 29

[ 14 C ]

- 1,4

- dioxane /kg. Higher levels of 14 CO 2 relative to 1,4

- dioxane were measured in expired 30

air of the 10 mg /kg group, while higher levels of expired 1,4

- dioxane relative to 14 CO 2 were 31

measured in the 1

, 000 mg /kg group. 3213

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 3.5. PHYSIOLOGICALLY BASE D PHARMACOKINETIC MODELS

Physiologically based pharmacokinetic models ( PBPK ) models have been developed for 1

1,4

- dioxane in rats ( Leung & Paustenbach, 1990 ; Reitz, McCroskey, Park, Andersen, & Gargas, 2

1990 ; Sweeney et al., 2008 )

, mice ( Sweeney, et al., 2008 )

, humans ( Leung & Paustenbach, 1990 ; 3

Reitz, et al., 1990 ; Sweeney, et al., 2008 )

, and lactating women ( Fisher, Mahle, Bankston, 4

Greene, & Gearhart, 1997 ) . Each of the models simulates the body as a series of compartments 5

representing tissues or tissue groups that receive blood from the central vascular compartment 6

( Figure 3

- 3) . Modeling was conducted under the premise that transfers of 1,4

- dioxane between 7

blood and tissues occur sufficiently fast to be effectively blood flow

- limited, which is consistent 8

with the available data ( Ramsey & Andersen, 1984 ) . Blood time course and metabolite 9

production data in rats and humans suggest that absorption and metabolism are accomplished 10

through common mechanisms in both species ( 1978a ; Young, et al., 1978b ; Young, et al., 1977 )

, 11

allowing identical model structures to be used for bot h species (and by extension, for mice as 12

well). In all three models, physiologically relevant, species

- specific parameter values for tissue 13

volume, blood flow, and metabolism and elimination are used. The models and supporting data 14

are reviewed below, fr om the perspective of assessing their utility for predicting internal 15

dosimetry and for cross

- species extrapolation of exposure

- response relationships for critical 16

neoplastic and nonneoplastic endpoints (also see Appendix B). 1714

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure 3

- 3. General PBPK model structure c onsisting 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.

3.5.1. Available Pharmacokinetic Data

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

. 1

( 1978a ; 1978b ; 1977 ) , Mikheev et al. ( 1990 ) , and Woo et al. ( 1977 ; 1977b ) . Young et al. 2

( 1978a ; 1978b ) studied the disposition of radiolabel ed [ 14 C]

- 1,4

- dioxane in adult male 3

Sprague Dawley rats following i.v., inhalation, and single and multiple oral gavage exposures. 4

Plasma concentration

- time profiles were reported for i.v. doses of 3, 10, 30, 100, and 5

1,000 mg /kg. In addition, exhaled 14 C O 2 and urinary 1,4

- dioxane and HEAA profiles were 6

reported following i.v. doses of 10 and 1,000 mg /kg. The plasma 1,4

- dioxane concentration

- time 7

course, cumulative urinary 1,4

- dioxane and cumulative urinary HEAA concentrations were 8

reported following a 6

- hour inhalation exposure to 50 ppm. Following oral gavage doses of 10

– 9

1,000 mg /kg, percentages of total orally administered radiolabel were measured in urine, feces, 10

expired air, and the whole body. 11

Oral absorption of 1,4

- dioxane was extensive, as only approximately 1% of the 12

administered dose appeared in the feces within 72 hour s of dosing ( Young, et al., 1978a ) 13

( Young, et al., 1978b ) . Although it may be concluded that the rate of oral absorption was high 1415

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE enough to ensure nearly complete absorption by 72 hour s, a more quantitative estimate of the 1

rate of oral absorption is not possible due to the absence of plasma time course data by oral 2

exposure. 3

Saturable metabolism of 1,4

- dioxane was observed in rats exposed by either the i.v. or 4

oral routes ( Young, et al., 1978a ; Young, et al., 1978b ) . Elimination of 1,4

- dioxane from plasma 5

appeared to be linear following i.v. doses of 3

- 30 mg /kg, but was nonlinear following doses of 6

100

– 1,000 mg /kg. Accordingly, 10 mg /kg i.v. doses resulted in higher concen trations of 14 CO 2 7

(from metabolized 1,4

- dioxane) in expired air relative to unchanged 1,4

- dioxane, while 8

1,000 mg /kg i.v. doses resulted in higher concentrations of expired 1,4

- dioxane relative to 14 CO 2

. 9

Thus, at higher i.v. doses, a higher proportion of unmetabolized 1,4

- dioxane is available for 10

exhalation. Taken together, the i.v. plasma and expired air data from Young et al. ( 1978a ; 11

1978b ) corroborate previous studies describing the saturable nature of 1,4

- dioxane metabolism in 12

rats ( 1977 ; Woo, Argus, et al., 1977b ) and are useful for optimizing metabolic parameters (V

max 13

and K

m ) in a PBPK model. 14

Similarly, increasing single or multiple oral doses of 10

– 1,000 mg /kg resulted in 15

increasing perc entage of 1,4

- dioxane in exhaled air and decreasing percentage of radiolabel 16

(either as 1,4

- dioxane or a metabolite) in the urine, with significant differences in both metrics 17

being observed between doses of 10 and 100 mg /kg ( Young, et al., 1978a ; Young, et al., 1978b )

. 18

These data identify the region (10

– 100 mg /kg) in which oral exposures will result in nonlinear 19

metabolism of 1,4

- dioxane and can be used to test whether metabolic parameter value estimates 20

derived from i.v. dosing data are adequate for modeling oral exposures. 21

Post

- exposure plasma data from a single 6

- hour, 50 ppm inhalation exposure in rats were 22

reported ( Young, et al., 1978a ; Young, et al., 1978b ) . The observed linear elimination of 23

1,4

- dioxane after inhalation exposure suggests that, via this route, metabolism is in the linear 24

region at this exposure level. 25

The only human data adequate for use in PBPK model development ( Young, et al., 1977 ) 26

come from adult male volunteers exposed to 50 ppm 1,4

- dioxane for 6 hour s. Plasma 27

1,4

- dioxane and HEAA concentrations were measured both during and after the exposure period, 28

and urine concentrations were measured following exposure. Plasma levels of 1,4

- dioxane 29

approached steady

- state at 6 hour s. HEAA data were insufficient to describe the appea rance or 30

elimination of HEAA in plasma. Data on elimination of 1,4

- dioxane and HEAA in the urine up 31

to 24 hour s from the beginning of exposure were reported. At 6 hour s from onset of exposure, 32

approximately 90% and 47% of the cumulative (0

– 24 hour s) urinary 1,4

- dioxane and HEAA, 33

respectively, were measured in the urine. The ratio of HEAA to 1,4

- dioxane in urine 24 hour s 34

after onset of exposure was 192:1 (similar to the ratio of 118:1 observed by Young et al

. ( 1976 ) 35

in workers exposed to 1.6 ppm for 7.5 hour s), indicating extensive metabolism of 1,4

- dioxane 36

As with Sprague Dawley rats, the eliminat ion of 1,4

- dioxane from plasma was linear across all 3716

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE observations (6 hour s following end of exposure), suggesting that human metabolism of 1

1,4

- dioxane is linear for a 50 ppm inhalation exposure to steady

- state. Thus, estimation of 2

human V

max and K

m from t hese data will introduce uncertainty into internal dosimetry performed 3

in the nonlinear region of metabolism. 4

Further data were reported for the tissue distribution of 1,4

- dioxane in rats. Mikheev 5

et al

. ( 1990 ) administered i.p. doses of [ 14 C ]

- 1,4

- dioxane to whit e rats (strain not reported) and 6

reported time

- to

- peak blood, liver, kidney, and testes concentrations. They also reported ratios 7

of tissue to blood concentrations at various time points after dosing. Woo et al

. ( 1977 ; 1977b ) 8

administered i.p. doses of [ 14 C ]

- 1,4

- dioxane to Sprague Dawley rats and measured radioactivity 9

levels in urine. However, since i.p. dosing is not relevant to human exposures, these data are of 10

limited use for PBPK model development. 11

3.5.2. Published PBPK Models for 1,4

- D ioxane

3.5.2.1. Leung and Paustenbach

Leung and Paustenbach ( 1990 ) developed a PBPK model for 1,4

- dioxane and its primary 12

metabolite, HEAA, in rats and humans. The model, based on the structure of a PBPK model for 13

styrene ( Ramsey & Andersen, 1984 ) , consists of a central blood compartment and four tissue 14

compartments: liver, fat, slowly perfused tissues (mainly muscle and skin), and richly perfused 15

tissues (brain, kidney, and viscera other than the liver). Tissue volumes were calculated as 16

percentages of total BW , and blood flow rates to each compartment were calculated as 17

percentages of cardiac output. Equivalent cardiac output and alveol ar ventilation rates were 18

allometrically scaled to a power (0.74) of BW for each species. The concentration of 19

1,4

- dioxane in alveolar blood was assumed to be in equilibrium with alveolar air at a ratio equal 20

to the experimentally measured blood:air parti tion coefficient. Transfers of 1,4

- dioxane between 21

blood and tissues were assumed to be blood flow

- limited and to achieve rapid equilibrium 22

between blood and tissue, governed by tissue:blood equilibrium partition coefficients. The latter 23

were derived fro m the quotient of blood:air and tissue:air partition coefficients, which were 24

measured in vitro ( Leung & Paustenbach, 1990 ) for blood, liver, fat, and skeletal muscle (slowly 25

pe rfused tissue). Blood:air partition coefficients were measured for both humans and rats. Rat 26

tissue:air partition coefficients were used as surrogate values for humans, with the exception of 27

slowly perfused tissue:blood, which was estimated by optimizati on to the plasma time

- course 28

data. Portals of entry included i.v. infusion (over a period of 36 seconds) into the venous blood, 29

inhalation by diffusion from the alveolar air into the lung blood at the rate of alveolar ventilation, 30

and oral administration via zero

- order absorption from the gastrointestinal tract to the liver. 31

Elimination of 1,4

- dioxane was accomplished through pulmonary exhalation and saturable 32

hepatic metabolism. Urinary excretion of HEAA was assumed to be instantaneous with the 33

generati on of HEAA from the hepatic metabolism of 1,4

- dioxane

. 3417

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE The parameter values for hepatic metabolism of 1,4

- dioxane, V

max and K

m , were 1

optimized and validated against plasma and/or urine time course data for 1,4

- dioxane and HEAA 2

in rats following i.v. and inhalation exposures and humans following inhalation exposure ( 1978a ; 3

1978b ; Young, et a l., 1977 ) ; the exact data (i.e., i.v., inhalation, or both) u sed for the 4

optimization and calibration were not reported. Although the liver and fat were represented by 5

tissue

- specific compartments, no tissue

- specific concentration data were available for model 6

development, raising uncertainty as the model‘s ability to adequately predict exposure to these 7

tissues. The human inhalation exposure of 50 ppm for 6 hour s ( Young, et al., 1977 ) was 8

reported to be in the linear range for metabolism; thus, uncertainty exists in the ability of the 9

allometrically

- scaled value for the human metabolic V

max to accurately describe 1,4

- dioxane 10

metabolism from exposures resulting in metabolic sat uration. Nevertheless, these values resulted 11

in the model producing good fits to the data. For rats, the values for V

max had to be adjusted 12

upwards by a factor of 1.8 to reasonably simulate exposures greater than 300 mg /kg. The model 13

authors attributed this to metabolic enzyme induction by high doses of 1,4

- dioxane. 14

3.5.2.2. Reitz et al

.

Reitz et al

. ( 1990 ) deve loped a model for 1,4

- dioxane and HEAA in the mouse, rat, and 15

human. This model, also based on the styrene model of Ramsey and Andersen ( 1984 ) , included 16

a central blood compartment and comp artments for liver, fat, and rapidly and slowly perfused 17

tissues. Tissue volumes and blood flow rates were defined as percentages of total BW and 18

cardiac output, respectively. Physiological parameter values were similar to those used by 19

Andersen et al

. ( 1987 ) , except that flow rates for cardiac output and alveolar ventilation were 20

doubled in order to produce a better fit of the model to human blood level data ( Young, et al., 21

1977 ) . Portals of entry included i.v. injectio n into the venous blood, inhalation, oral bolus 22

dosing, and oral dosing via drinking water. Oral absorption of 1,4

- dioxane was simulated, in all 23

three species, as a first

- order transfer to liver (halftime approximately 8 minutes ). 24

Alveolar blood levels o f 1,4

- dioxane were assumed to be in equilibrium with alveolar air 25

at a ratio equal to the experimentally measured blood:air partition coefficient. Transfers of 26

1,4

- dioxane between blood and tissues were assumed to be blood flow

- limited and to achieve 27

rapi d equilibrium between blood and tissue, governed by tissue:blood equilibrium partition 28

coefficients. These coefficients were derived by dividing experimentally measured ( Leung & 29

Paustenbach, 1990 ) in vitro blood:air and tissue:air partition coefficients for blood, liver, fat. 30

Blood:air partition coefficients were measured for both humans and rats. The mouse blood:air 31

partition coefficient was different from rat or human value s; the source of the partition 32

coefficient for blood in mice was not reported. Rat tissue:air partition coefficients were used as 33

surrogate values for humans. Rat tissue partition coefficient values were the same values as used 34

in the Leung and Paustenba ch ( 1990 ) model (with the exception of slowly perfused tissues) and 35

were used in the models for all three species. The liver value was used for the rapidly perfused 3618

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE tissues, as well as slowly perfused ti ssues. Although slowly perfused tissue:air partition 1

coefficients for rats were measured, the authors suggested that 1,4

- dioxane in the muscle and air 2

may not have reached equilibrium in the highly gelatinous tissue homogenate ( Reitz, et al., 3

1990 ) . Substitution of the liver value provided much closer agreement to the plasma data than 4

when the muscle value was used. Further, doubling of the measured human blood:air partition 5

coefficient improved the fit of the model to the human blood level data compared to the fit 6

resulting from the measured value ( Reitz, et al., 1990 ) . The Reitz et al

. ( 1990 ) model simulated 7

three routes of 1,4

- dioxane elimination: pulmonary exhalation, hepatic metabolism to HEAA, 8

and urinary excretion of HEAA. The elimination of HEAA was modeled as a first

- order transfer 9

of 1,4

- dioxane metabolite to urine. 10

Values for the metabolic rate constants, V

max and K

m , were optimized to achieve 11

agreement with various observations. Reitz et al

. ( 1990 ) optimized values for human V

max and 12

K

m against the experimental human 1,4

- dioxane inhalation data ( Young, et al., 1977 ) . As noted 13

previously, because the human exposures were below the level needed to exhibit nonlinear 14

kinetics, uncertainty exists in the ability of the optimized value of V

max to simulate human 15

1,4

- dioxane metabolism above the concentration that would result in saturation of metabolism. 16

Rat metabolic rate constants were obtained by optimization to simulated data from a two 17

compartment empirical pharmacokinetic model, wh ich was fitted to i.v. exposure data ( Young, et 18

al., 1978a ; Young, et al., 1978b ) . As with the Leung and 19

The Leung and Paustenbach model ( 1990 ) and the Reitz et al

. ( 1990 ) model included 20

compartments for the liver and fat, although no tissue

- specif ic concentration data were available 21

to validate dosimetry for these organs. The derivations of human and rat HEAA elimination rate 22

constants were not reported. Since no pharmacokinetics data for 1,4

- dioxane in mice were 23

available, mouse metabolic rate constants were allometrically scaled from rat and human values. 24

3.5.2.3. Fisher et al

.

A PBPK model was developed by Fisher et al

. ( 1997 ) to simulate a variety of volatile 25

organic compounds (VOCs, including 1,4

- dioxane ) in lactating humans. This model was similar 26

in structure to those of Leung and Paustenbach ( 1990 ) and Reitz et al

. ( 1990 ) with the addition of 27

elimination of 1,4

- dioxane to breast milk. Experimental measur ements were made for blood:air 28

and milk:air partition coefficients. Other partition coefficient values were taken from Reitz et al

. 29

( 1990 ) . The model was not optimized, nor was performance tested against experimental 30

exposure data. Thus, the ability of the model to simulate 1,4

- dioxane exposure data is unknown. 31

3.5.2.4. Sweeney et al.

The Sweeney et al. ( 2008 ) model consisted of fat, liver, slowly perfused, and other well 32

perfused tissue compartments. Lung and stomach compartments were used to describe the route 33

of exposure, and an overall volume of distribution compartment was used for calculation of 34

urinary excretion levels of 1,4

- dioxane and HEAA. Blood, saline, and tissue to air partition 3519

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE coefficient values for 1,4

- dioxane were experimentally determined for rats and mice. Average 1

values of the rat and mouse partition coefficients were used for humans. M etabolic constants 2

(VmaxC and Km) for the rat were derived by optimization of data from an i.v. exposure of 1,000 3

mg/kg ( Young, et al., 1978a ) for inducible metabolism. For unind uced VmaxC estimation, data 4

generated by i.v. exposures to 3, 10, 30, and 100 mg/kg were used ( Young, et al., 1978a )

. 5

Sweeney et al. ( 2008 ) determined best fit values for VmaxC by fitting to blood data in the Young 6

et al. ( 1978a ) . The best fit VmaxC values were 7.5, 10.8, and 12.7 mg/hr

- kg 0.75 for i.v. doses of 3 7

to 100, 300, and 1,000 mg/kg, suggesting a gradual dose dependent increase in metabolic rate 8

over i.v. doses ranging from 3 to 1,000 mg/kg. Although the Sweeney et al. ( 2008 ) model 9

utilized two values for VmaxC (induced and uninduced), the PBPK model does not include a 10

dose

- dependent function description of the change of Vmax for i.v. doses between metabolic 11

induced and uninduced exposures. Mouse Vmax C and absorption constants were derived by 12

optimizing fits to the blood 1,4

- dioxane concentrations in mice administered nominal doses of 13

200 and 2,000 mg/kg 1,4

- dioxane via gavage in a water vehicle ( Young, et al., 1978a ) . The in 14

vitro Vmax values for rats and mice were scaled to estimate in vivo rates. The scaled and 15

optimized rat VmaxC values were very similar. The discrepancy between the scaled and 16

optimized mouse values was larger, which was attributed to possible induction in mice at the 17

lowest dose tested (200 mg/kg). The ratio of optimized/scaled values for the rat was used to 18

adjust the sca led human VmaxC and Km values to projected in vivo values. 19

The Sweeney et al. ( 2008 ) mo del outputs were compared, by visual inspection, with data 20

not used in fitting model parameters. The model predictions gave adequate match to the 1,4

- 21

dioxane exhalation data in rats after a 1,000 mg/kg i.v. dose. 1,4

- Dioxane exhalation was 22

overpredicted by a factor of about 3 after a 10 mg/kg i.v. dose. Similarly, the simulations of 23

exhaled 1,4

- dioxane after oral dosing were adequate at 1,000 mg/kg and 100 mg/kg (within 24

50%), but poor at 10 mg/kg (model over predicted by a factor of 5). The fit of the m odel to the 25

human data ( Young, et al., 1977 ) was problematic. Using physiological parameters of Brown et 26

al. ( 1997 ) and measured partitioning parameters ( Leung & Paustenbach, 1990 ; Sweeney, et al., 27

2008 ) with no meta bolism, measured blood 1,4

- dioxane concentrations reported by Young et al. 28

( 1977 ) could not be achieved unless the estimated exposur e concentration was increased by 2

- 29

fold. As expected, inclusion of any metabolism resulted in a decrease in predicted blood 30

concentrations. If estimated metabolism rates were used with the reported exposure 31

concentration, urinary metabolite excretion was also underpredicted ( Sweeney, et al., 2008 )

. 32

3.5.3. Implementation of Published PBPK Models for 1,4

- D ioxane

As previously described, several pharmacokinetic models have been developed to predict 33

the absorption, distribution, metabolism, and elimination of 1,4

- dioxane in rats and humans. 34

Single compartment, empirical models for rats ( Young, et al., 1978a ; Yo ung, et al., 1978b ) and 3520

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE humans ( Young, et al., 1977 ) were developed to predict blood levels of 1,4

- dioxane and urine 1

levels of the primary metabolite, HEAA. PBPK models that describe the kinetics of 1,4

- dioxane 2

using biologically realistic flow rates, tissue volumes, enzyme affinities, metabolic pr ocesses, 3

and elimination behaviors were also developed ( Fisher, et al., 1997 ; Leung & Paustenbach, 1990 ; 4

Reitz, et al., 1990 ; Sweeney, et al., 2008 )

. 5

In developing updated toxicity values for 1,4

- dioxane the available PBPK models were 6

evaluated for their ability to predict observations made in experimental studies o f rat and human 7

exposures to 1,4

- dioxane (Appendix B). The Reitz et al

. ( 1990 ) and Leung and Paustenbach 8

( 1990 ) PBPK models were both developed from a PBPK model of styrene ( Ramsey & Andersen, 9

1984 ) , with the ex ception of minor differences in the use of partition coefficients and biological 10

parameters. The model code for Leung and Paustenbach ( 1990 ) was unavailable in contrast to 11

Reitz et al

. ( 1990 ) . The model of Reitz et al

. ( 1990 ) was identified for further consideration to 12

assist in the derivation of toxicity values , and the Sweeney et al. ( 2008 ) PBPK model was also 13

evaluated

. 14

T he biological plausibility of parameter values in the Reitz et al. ( 1990 ) human model 15

were examined

. T he model published by Reitz et al. ( 1990 ) was able to predict the only 16

available human inhalation data (50 ppm 1,4

- dioxane for 6 hour s; Young et al

., ( 1977 ) ) by 17

increasing (i.e., approximately doubling) the parameter values for human alveolar ventilation ( 30 18

L/hour/kg 0.74 ) , cardiac output ( 30 L/hour/kg 0.74 ) , and the blood:air partition coefficient ( 3,650 ) 19

above the measured values of 13 L/minute/kg 0.74 ( Brown, et al., 1997 )

, 14 L/hour/kg 0.74 ( Brown, 20

et al., 1997 ) , and 1, 825 ( Leung & Paustenbach, 1990 ) , respectively . Furthermore, R eitz et al. 21

( 1990 ) replaced the measured value for the slowly perfused tissue:air partition coefficient ( i.e., 22

muscle

— value not reported in manuscript ) with the measured liver value ( 1,557 ) to improve the 23

fit. Analysis of the Young et al

. ( 1977 ) human data suggested that the apparent volume of 24

distribution ( V d ) for 1,4

- dioxane was approximately 10

- fold higher in rats than humans, 25

presumably due to species differences in tissue partitioning or other process not represented in 26

the model . Based upon these observations

, several model parameters (e.g., 27

metabolism/elimination parameters) were re

- calibrated using biologically plausible values for 28

flow rates and tissue:air partition coefficients. 29

Appendix B describes all activities that were conducted in the evaluation of the empirical 30

models and the re

- calibration and evaluation of the Reitz et al

. ( 1990 ) PBPK model to determine 31

the adequacy and preference for the potential use of the models

. 32

The evaluation consisted of implementation of the Young et al. ( 1978a ; 1978b ; 1977 ) 33

empirical rat an d human models using the acslXtreme simulation software, re

- calibration of the 34

Reitz et al. ( 1990 ) human PBPK model, and evaluation of the model parameters published by 35

Sweeney et al. ( 2008 )

. Using the model descriptions and equations given in Young et al. ( 1978a ; 36

1978b ; 1977 ) , model code was developed for the empirical models and executed, simulat ing the 3721

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE reported experimental conditions. The model output was then compared with the model output 1

reported in Young et al. ( 1978a ; 1978b ; 19 77 )

. 2

The PBPK model of Reitz et al

. ( 1990 ) was re

- calibrated using measured values for 3

cardiac and alveolar flow rates and tissue:air partition coefficients. The predictions of blood and 4

urine levels of 1,4

- dioxane and HEAA, respectively, from the re

- calibrated model were 5

compared with the empirical model predictions of the same dosimeters to determine whether the 6

re

- calibrated PBPK model could perform similarly to the empirical model. As part of the PBPK 7

model eva luation, EPA performed a sensitivity analysis to identify the model parameters having 8

the greatest influence on the primary dosimeter of interest, the blood level of 1,4

- dioxane

. 9

Variability data for the experimental measurements of the tissue:air partiti on coefficients were 10

incorporated to determine a range of model outputs bounded by biologically plausible values for 11

these parameters. Model parameters from Sweeney et al. ( 2008 ) were also tested to evaluate the 12

ability of the PBPK model to predict human data following exposure to 1,4

- dioxane. 13

The rat and human empirical models of Young et al. ( 1978a ; 1978b ; 1977 ) were 14

successfully implemented in acslXtreme and perform identically to the models reported in the 15

published papers (Figures B

- 3 through B

- 7 ) , with the exception of the lower predicted HEAA 16

concentrations and early appearance of the peak HEAA levels in rat urine. The early appearance 17

of peak HEAA levels cannot presently be explained, but may result from manipulations of k

me or 18

other parameters by Young et al. ( 1978a ; 1978b ) that were not reported. Th e lower predictions 19

of HEAA levels are likely due to reliance on a standard urine volume production rate in the 20

absence of measured (but unreported) urine volumes. While the human urinary HEAA 21

predictions were lower than observations, this is due to param eter fitting of Young et al. ( 1977 )

. 22

No model output was published in Young et al. ( 1977 ) for comparison. The empirical models 23

were modified to allow for user

- defined inhalation exposure levels. However, no modifications 24

were made to model oral exposures as ade quate data to parameterize such modifications do not 25

exist for rats or humans. Further evaluations of the Young et al. ( 1977 ) modifi ed model w ere 26

conducted against data from the Kasai et al. ( 2008 ) subchronic inhalation study. The results of 27

this evaluati on are shown in Appendix B (Figure B

- 8 ). It shows that the Young et al. ( 1977 ) 28

inhalation empirical model failed to provide an adeq uate simulation of the 13 week inhalation 29

exposure blood data of Kasai et al. ( 2008 )

. Since the Young et al. ( 1977 ) model consistently 30

overpredicted the Kasai et al. ( 2008 ) data, the lack of model fit is most likely due to the lack of 31

inclusion of other metabolic processes or parameters

. 32

Several procedures were applied to the Reitz et al. ( 1990 ) human PBPK model to 33

determine if an adequate fit of the model to the empirical model output or experimental 34

observations could be attained using biologically plausible values for the model parameters. The 35

re

- calibrated model predictions for blood 1,4

- dioxane levels do not come within 10

- fold of the 36

experimental values using measured tissue:air partition coefficients from Leung and Paustenbach 3722

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ( 1990 ) or Sweeney et al

. ( 2008 ) (Figures B

- 9 and B

- 10 ). The utilization of a slowly perfused 1

tissue:air partition coefficient 10

- fold lower than measured values produces exposure

- phase 2

predictions that are much closer to observations, but does not replicate the elimination kinetics 3

( Figure B

- 1 1 ). Recalibration of the model with upper bounds on the tissue:air partition 4

coefficients results in predictions that are still six

- to seven fold lower than empirical model 5

prediction or observations (Figures B

- 13 and B

- 14 ). Explorati on of the model space using an 6

assumption of zero

- order metabolism (valid for the 50 ppm inhalation exposure) showed that an 7

adequate fit to the exposure and elimination data can be achieved only when unrealistically low 8

values are assumed for the slowly p erfused tissue:air partition coefficient ( Figure B

- 17 ). 9

Artificially low values for the other tissue:air partition coefficients are not expected to improve 10

the model fit, as these parameters are shown in the sensitivity analysis to exert less influence on 11

blood 1,4

- dioxane than V

max C and K

m . In the absence of actual measurements for the human 12

slowly perfused tissue:air partition coefficient, high uncertainty exists for this model parameter 13

value. Differences in the ability of rat and human blood to bind 1,4

- dioxane may contribute to 14

the difference in V d . However, this is expected to be evident in very different values for rat and 15

human blood:air partition coefficients, which is not the case ( Table B

- 1). Therefore, some other, 16

as yet unknown, modificatio n to model structure may be necessary. 17

Similarly, Sweeney et al

. ( 2008 ) also evaluated the available PBPK models ( Leung & 18

Paustenbach, 1990 ; Reitz, et al., 1990 ) for 1,4

- dioxane . To address uncertainties and 19

deficiencies in these models, the investigators conducted studies to fill data gaps and reduce 20

uncertainties pertaining to the pharmacokinetics of 1,4

- dioxane and HEAA in rats, mice, and 21

humans. The following studies were p erformed: 22

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 admin istration 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 ) resulted in partition coefficients that 23

were consistent with previously measured values and those used in the Leung and Paustenbach 24

( 1990 ) model. Of noteworthy significance, the laboratory results of Sweeney et al. ( 2008 ) did 25

not confirm the human blood:air partition coefficient Reitz et al. ( 1990 ) reported. Furthermore, 26

Sweeney et al. ( 2008 ) estimated metabolic rate constants (V maxC and K

m ) within the range used in 27

the previous models ( Leung & Pa ustenbach, 1990 ; Reitz, et al., 1990 )

. Overall

, the Sweeney et 28

al. ( 2008 ) model utilized more rodent in vivo and in vitro data in model parameterization and 29

refinement; however, the model was still unable to adequately predict the human blood data from 30

Young et al. ( 1977 )

. 3123

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Updated PBPK models were developed based on these new data and data from previous 1

kinetic studies in rats, workers, and human volunteers reported by Young et al. ( 1978a ; 1978b ; 2

1976 ; 1977 ) . The optimized rate of metabolism for the mouse was significantly higher than the 3

value previously estimated. The optimized rat ki netic parameters were similar to those in the 4

1990 models. Of the two available human studies ( Young, et al., 1976 ; 1977 ) , model predictions 5

were consistent with one study, but did not fit the second as well. 6

3.6. RAT NASAL EXPOSURE VIA DRINKING WATER

Sweeney et al

. ( 2008 ) conducted a rat nasal exposure study to explore the potential for 7

direct contact of nasal tissues with 1,4

- dioxane

- containing drinking water under bioassay 8

conditions. Two groups of male Spragu e Dawley rats (5/group) received drinking water in 9

45

- mL drinking water bottles containing a fluorescent dye mixture (Cell Tracker 10

Red/FluoSpheres). The drinking water for one of these two groups also contained 0.5% 11

1,4

- dioxane , a concentration within the range used in chronic toxicity studies. A third group of 12

five rats received tap water alone (controls). Water was provided to the rats overnight. The next 13

morning, the water bottles were weighed to estimate the amounts of water consumed. Rats were 14

sac rificed and heads were split along the midline for evaluation by fluorescence microscopy. 15

One additional rat was dosed twice by gavage with 2 mL of drinking water containing 16

fluorescent dye (the second dose was 30 minutes after the first dose; total of 4 mL administered) 17

and sacrificed 5 hour s later to evaluate the potential for systemic delivery of fluorescent dye to 18

the nasal tissues. 19

The presence of the fluorescent dye mixture had no measurable impact on water 20

consumption; however, 0.5% 1,4

- dioxane reduced water consumption by an average of 62% of 21

controls following a single, overnight exposure. Fluorescent dye was detected in the oral cavity 22

and nasal airways of each animal exposed to the Cell Tracker Red/FluoSpheres mixture in their 23

drinking wate r, including numerous areas of the anterior third of the nose along the nasal 24

vestibule, maxillary turbinates, and dorsal nasoturbinates. Fluorescent dye was occasionally 25

detected in the ethmoid turbinate region and nasopharynx

. 1,4

- D ioxane had no effect on the 26

detection of the dye. Little or no fluorescence at the wavelength associated with the dye mixture 27

was detected in control animals or in the single animal that received the dye mixture by oral 28

gavage. The investigators concluded that the findings indicate rat nasal tissues are exposed by 29

direct contact with drinking water under bioassay conditions. 3024

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

4. HAZARD IDENTIFICATIO N

4.1. STUDIES IN HUMANS

– EPIDEMIOLOGY, CASE REPORTS, CLINICAL

CONTROLS

Case reports of acute occupational poisoning with 1,4

- dioxane indicated that exposure to 1

high concentrations resulted in liver, kidney, and central nervous system (CNS) toxicity ( Barber, 2

1934 ; Johnstone, 1959 )

. Barber ( 1934 ) descri bed four fatal cases of hemorrhagic nephritis and 3

centrilobular necrosis of the liver attributed to acute inhalation exposure to high (unspecified) 4

concentrations of 1,4

- dioxane. Death occurred within 5

– 8 day s of the onset of illness. Autopsy 5

findings su ggested that the kidney toxicity may have been responsible for lethality, while the 6

liver effects may have been compatible with recovery. Jaundice was not observed in subjects 7

and fatty change was not apparent in the liver. Johnstone ( 1959 ) presented the f atal case of one 8

worker exposed to high concentrations of 1,4

- dioxane through both inhalation and dermal 9

exposure for a 1 week exposure duration. Measured air concentrations in the work environment 10

of this subject were 208

– 650 ppm, with a mean value of 470 ppm. Clinical signs that were 11

observed following hospital admission included severe epigastric pain, renal failure, headache, 12

elevation in blood pressure, agitation and restlessness, and coma. Autopsy findings revealed 13

significant changes in the live r, kidney, and brain. These included centrilobular necrosis of the 14

liver and hemorrhagic necrosis of the kidney cortex. Perivascular widening was observed in the 15

brain with small foci of demyelination in several regions (e.g., cortex, basal nuclei). It was 16

suggested that these neurological changes may have been secondary to anoxia and cerebral 17

edema. 18

Several studies examined the effects of acute inhalation exposure in volunteers. In a 19

study performed at the Pittsburgh Experimental Station of the U.S. Bu reau of Mines, eye 20

irritation and a burning sensation in the nose and throat were reported in five men exposed to 21

5,500 ppm of 1,4

- dioxane vapor for 1 minute ( Yant, Schrenk, Waite, & Patty, 1930 ) . Slight 22

vertigo was also reported by three of these men. Exposure to 1,600 ppm of 1,4

- dioxane vapor 23

for 10 minutes resulted in similar symptoms with a reduced intensity of effect. In a study 24

conducted by the Government Experimental Establishment at Proton, England ( Fairley, Linton, 25

& Ford

- Moore, 1934 ) , four men were exposed to 1,000 ppm of 1,4

- dioxane for 5 minutes . Odor 26

was detected immediately and one volunteer noted a constriction in the throat. Exposu re of six 27

volunteers to 2,000 ppm for 3 minutes resulted in no symptoms of discomfort. Wirth and 28

Klimmer ( 1936 ) , of the Institute of Pharmacology, University of Wurzburg, reported slight 29

mucous membrane irritation in the nose and throat of several human subjects exposed to 30

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)

.2 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE concentrations greater than 280 ppm for several minutes. Exposure to approximately 1,400 ppm 1

for several minutes caused a prickling sensation in the nose and a dry and scratchy throat. 2

Silverman et al. ( 1946 ) exposed 12 male and 12 female subjects to varying air concentrations of 3

1,4

- dioxane for 15 minutes . A 200 ppm concentration was reported to be tolerable, while a 4

concentration of 300 ppm caused irritat ion to the eyes, nose, and throat. The study conducted by 5

Silverman et al. ( 1946 ) was conducted by the Department of Industrial Hygiene, Harvard School 6

of Public Health, and was sponsored and supported by a grant from the Shell Development 7

Company. These volunteer studies published in the 1930s and 1940s ( Fairley, et al. , 1934 ; 8

Silverman, et al., 1946 ; Wirth & Klimmer, 1936 ; Yant, et al., 1930 ) did not provide information 9

on the human subjects research ethics procedures undertaken in these s tudies; however, there is 10

no evidence that the conduct of the research was fundamentally unethical or significantly 11

deficient relative to the ethical standards prevailing at the time the research was conducted. 12

Young et al. ( 1977 ) exposed four healthy adult male volunteers to a 50

- ppm 13

concentration of 1,4

- dioxane for 6 hour s. The investigators reported that the protocol of this 14

study was approved by a seven

- member Human Research Review Committee of the Dow 15

Chemical Company and was followed rigorously. Perception of the odor of 1,4

- dioxane 16

appeared to diminish over time, with two of the four subjects reporting inability to detect the 17

o dor at the end of the exposure period. Eye irritation was the only clinical sign reported in this 18

study. The pharmacokinetics and metabolism of 1,4

- dioxane in humans were also evaluated in 19

this study (see Section 3.3). Clinical findings were not reporte d in four workers exposed in the 20

workplace to a TWA concentration of 1.6 ppm for 7.5 hour s ( Young, et al., 1976 )

. 21

Ernstgård et al. ( 2006 ) examined the acute effects of 1,4

- dioxane vapor in male and 22

female volunteers. The study protocol was approved by the Regional Ethics Review Board in 23

Stockh olm, and performed following informed consent and according to the Helsinki 24

declaration. In a screening study by these investigators, no self

- reported symptoms (based on a 25

visual analogue scale (VAS) that included ratings for discomfort in eyes, nose, and throat, 26

breathing difficulty, headache, fatigue, nausea, dizziness, or feeling of intoxication) were 27

observed at concentrations up to 20 ppm; this concentration was selected as a tentative no

28

observed

- adverse

- effect

- level (NOAEL) in the main study. In th e main study, six male and six 29

female healthy volunteers were exposed to 0 or 20 ppm 1,4

- dioxane, at rest, for 2 hour s. This 30

exposure did not significantly affect symptom VAS ratings, blink frequency, pulmonary function 31

or nasal swelling (measured before and at 0 and 3 hour s after exposure), or inflammatory 32

markers in the plasma (C

- reactive protein and interleukin

- 6) of the volunteers. Only ratings for 33

―solvent smell‖ were significantly increased during exposure. 34

Only two well documented epidemiology stud ies were available for occupational workers 35

exposed to 1,4

- dioxane ( Buffler, Wood, Suarez, & Kilian, 1978 ; Thiess, Tress, & Fleig, 1976 )

. 3626

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE These studies did not provide eviden ce of effects in humans; however, the cohort size and 1

number of reported cases were small. 2

4.1.1. Thiess et al.

A cross

- sectional survey was conducted by Thiess et al. ( 1976 ) in German workers 3

exposed to 1,4

- dioxane. The study evaluated health effects in 74 workers, including 24 who 4

were still actively employed in 1,4

- dioxane production at the time of the investigation, 5

23 previously exposed workers who were still employed by the manufacturer, and 27 retired or 6

deceased workers. The actively employed workers were between 32 and 62 years of age and had 7

been employed in 1,4

- dioxane production for 5

– 41 years. Former workers (age range not given) 8

had been exposed to 1,4

- dioxane for 3

– 38 years and retirees (age r ange not given) had been 9

exposed for 12

– 41 years. Air concentrations in the plant at the time of the study were 10

0.06

– 0.69 ppm. A simulation of previous exposure conditions (prior to 1969) resulted in air 11

measurements between 0.06 and 7.2 ppm. 12

Active a nd previously employed workers underwent a thorough clinical examination and 13

X

- ray, and hematological and serum biochemistry parameters were evaluated. The examination 14

did not indicate pathological findings for any of the workers and no indication of mali gnant 15

disease was noted. Hematology results were generally normal. Serum transaminase levels were 16

elevated in 16 of the 47 workers studied; however, this finding was consistent with chronic 17

consumption of more than 80 g of alcohol per day , as reported fo r these workers. No liver 18

enlargement or jaundice was found. Renal function tests and urinalysis were normal in exposed 19

workers. Medical records of the 27 retired workers (15 living at the time of the study) were 20

reviewed. No symptoms of liver or kidne y disease were reported and no cancer was detected. 21

Medical reasons for retirement did not appear related to 1,4

- dioxane exposure (e.g., emphysema, 22

arthritis). 23

Chromosome analysis was performed on six actively employed workers and six control 24

persons (not characterized). Lymphocyte cultures were prepared and chromosomal aberrations 25

were evaluated. No differences were noted in the percent of cells with gaps or other 26

chromosome aberrations. Mortality statistics were calculated for 74 workers of different ages 27

and varying exposure periods. The proportional contribution of each of the exposed workers to 28

the total time of observation was calculated as the sum of man

- years per 10

- year age group. 29

Each person contributed one man

- year per calendar year to the s pecific age group in which he 30

was included at the time. The expected number of deaths for this population was calculated from 31

the age

- specific mortality statistics for the German Federal Republic for the years 1970

– 1973. 32

From the total of 1,840.5 person

- years, 14.5 deaths were expected; however, only 12 deaths were 33

observed in exposed workers between 1964 and 1974. Two cases of cancer were reported, 34

including one case of lamellar epithelial carcinoma and one case of myelofibro sis leukemia. 3527

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE These cancers were not considered to be the cause of death in these cases and other severe 1

illnesses were present. Standardized mortality ratios (SMRs) for cancer did not significantly 2

differ from the control population (SMR for overall population = 0.83; SMR for 65

– 7 5

- year

- old 3

men = 1.61; confidence intervals (CIs) were not provided). 4

4.1.2. Buffler et al.

Buffler et al. ( 1978 ) conducted a mortality study on workers exposed to 1,4

- dioxane at a 5

chemical manufacturing facility in Texas. 1,4

- Dioxane exposure was known to occur in a 6

manufacturing area and in a processing unit locat ed 5 miles from the manufacturing plant. 7

Employees who worked between April 1, 1954, and June 30, 1975, were separated into two 8

cohorts based on at least 1 month of exposure in either the manufacturing plant (100 workers) or 9

the processing area (65 worker s). Company records and follow

- up techniques were used to 10

compile information on name, date of birth, gender, ethnicity, job assignment and duration, and 11

employment status at the time of the study. Date and cause of death were obtained from copies 12

of dea th certificates and autopsy reports (if available). Exposure levels for each job category 13

were estimated using the 1974 Threshold Limit Value for 1,4

- dioxane (i.e., 50 ppm) and 14

information from area and personal monitoring. Exposure levels were classifie d as low 15

(<25 ppm), intermediate (50

– 75 ppm), and high (>75 ppm). Monitoring was not conducted prior 16

to 1968 in the manufacturing areas or prior to 1974 in the processing area; however, the study 17

authors assumed that exposures would be comparable, conside ring that little change had been 18

made to the physical plant or the manufacturing process during that time. Exposure to 19

1,4

- dioxane was estimated to be below 25 ppm for all individuals in both cohorts. 20

Manufacturing area workers were exposed to several ot her additional chemicals and processing 21

area workers were exposed to vinyl chloride. 22

Seven deaths were identified in the manufacturing cohort and five deaths were noted for 23

the processing cohort. The average exposure duration was not greater for those wor kers who 24

died, as compared to those still living at the time of the study. Cancer was the underlying cause 25

of death for two cases from the manufacturing area (carcinoma of the stomach, alveolar cell 26

carcinoma) and one case from the processing area (malign ant mediastinal tumor). The workers 27

from the manufacturing area were exposed for 28 or 38 months and both had a positive smoking 28

history (>1 pack/day). Smoking history was not available for processing area workers. The 29

single case of cancer in this area occurred in a 21

- year

- old worker exposed to 1,4

- dioxane for 30

1 year. The mortality data for both industrial cohorts were compared to age

- race

- sex specific 31

death rates for Texas (1960

– 1969). Person

- years of observation contributed by workers were 32

determin ed over five age ranges with each worker contributing one person

- year for each year of 33

observation in a specific age group. The expected number of deaths was determined by applying 34

the Texas 1960

– 1969 death rate statistics to the number of person years ca lculated for each 3528

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE cohort. The observed and expected number of deaths for overall mortality (i.e., all causes) was 1

comparable for both the manufacturing area (7 observed versus 4.9 expected) and the processing 2

area (5 observed versus 4.9 expected). No sig nificant excess in cancer

- related deaths was 3

identified for both areas of the facility combined (3 observed versus 1.7 expected). A separate 4

analysis was performed to evaluate mortality in manufacturing area workers exposed to 5

1,4

- dioxane for more than 2 years. Six deaths occurred in this group as compared to 6

4.1 expected deaths. The use of a conditional Poisson distribution indicated no apparent excess 7

in mortality or death due to malignant neoplasms in this study. It is important to note that the 8

coho rts evaluated were limited in size. In addition, the mean exposure duration was less than 9

5 years (<2 years for 43% of workers) and the latency period for evaluation was less than 10

10 years for 59% of workers. The study authors recommended a follow

- up inv estigation to 11

allow for a longer latency period; however, no follow

- up study of these workers has been 12

published. 13

4.2. SUBCHRONIC AND CHRON IC STUDIES AND CANCE R BIOASSAYS IN

ANIMALS

- ORAL AND INHALATION

The majority of the subchronic and chronic studies conducted for 1,4

- dioxane were 14

drinking water studies. To date, there are only two subchronic inhalation studies ( Fairley, et al., 15

1934 ; Kasai, et al., 2008 ) and two chronic inhalation studies ( Kasai, et al., 2009 ; Torkelson, 16

Leong, Kociba, Richter, & Gehring, 1974 ) . The effects following oral and inhalation exposures 17

are described in detail below. 18

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% 19

1,4

- dioxane for up to 67 day s ( Fairley, et al., 1934 ) . Using reference BWs and drinking water 20

ingestion rates for rats and mice ( U.S. EPA, 1988 ) , it can be estimated that these rats and mice 21

received doses of approximately 1,900 and 3,3 00 mg /kg

- day, respectively. Gross pathology and 22

histopathology were evaluated in all animals. Five of the six rats in the study died or were 23

sacrificed in extremis prior to day 34 of the study. Mortality was lower in mice, with five of six 24

mice survivin g up to 60 day s. Kidney enlargement was noted in 5/6 rats and 2/5 mice. Renal 25

cortical degeneration was observed in all rats and 3/6 mice. Large areas of necrosis were 26

observed in the cortex, while cell degeneration in the medulla was slight or absent. Tubular casts 27

were observed and vascular congestion and hemorrhage were present throughout the kidney. 28

Hepatocellular degeneration with vascular congestion was also noted in five rats and three mice. 29

For this assessment, EPA identified the tested doses of 1,900 mg /kg

- day in rats and 3,300 mg /kg

- 3029

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE day in mice as the lowest

- observed

- adverse

- effect

- levels (LOAELs) for liver and kidney 1

degeneration in this study. 2

4.2.1.1.1. Stoner et al. 1,4

- Dioxane was evaluated by Stoner et al. ( 1986 ) for its ability to induce 3

lung adenoma formation in A/J mice. Six

- to 8

- week

- old male and female A/J mice 4

(16/sex

/group) were given 1,4

- dioxane by gavage or i.p. injection, 3 times/week for 8 weeks

. 5

Total cumulative dose levels were given as 24,000 mg /kg (oral), and 4,800, 12,000, or 6

24,000 mg /kg (i.p.). Average daily dose estimates were calculated to be 430 mg /kg

- day (oral), 7

and 86, 210, or 430 mg /kg

- day (i.p.) by assuming an exposure duration of 56 day s. The authors 8

indicated that i.p. doses represent the maximum tolerated dose (MTD), 0.5 times the MTD, and 9

0.2 times the MTD. Mice were killed 24 weeks after init iation of the bioassay, and lungs, liver, 10

kidney, spleen, intestines, stomach, thymus, salivary, and endocrine glands were examined for 11

gross lesions. Histopathology examination was performed if gross lesions were detected. 12

1,4

- Dioxane did not induce lun g tumors in male or female A/J mice in this study. 13

4.2.1.1.2. Stott et al. In the Stott et al. ( 1981 ) study, m ale Sprague Dawley rats (4

– 6/group) 14

were given average d oses of 0, 10, or 1,000 mg /kg

- day 1,4

- dioxane (>99% pure) in their 15

drinking water, 7 day s/week for 11 weeks . It should be noted that the methods description in this 16

report stated that the high dose was 100 mg /kg

- day, while the abstract, results, and discu ssion 17

sections indicated that the high dose was 1,000 mg /kg

- day. Rats were implanted with a [ 6

- 18

3 H]thymidine loaded osmotic pump 7 day s prior to sacrifice. Animals were sacrificed by 19

cervical dislocation and livers were removed, weighed, and prepared for histopathology 20

evaluation. [ 3 H]

- Thymidine incorporation was measured by liquid scintillation spectroscopy. 21

An increase in the liver to BW ratio was observed in rats from the high dose group 22

(assumed to be 1,000 mg /kg

- day). Histopathological alterations, characterized as minimal 23

centrilobular swelling, were also seen in rats from this dose group (incidence values were not 24

reported). Hepatic DNA synthesis, measured by [ 3 H]

- thymidine incorporation, was increased 25

1.5

- fold in high

- dose rats. No changes relative to control were observed for rats exposed to 26

10 mg /kg

- day. EPA found a NOAEL value of 10 mg /kg

- day and a LOAEL value of 27

1,000 mg /kg

- day for this study based on histopathological changes in the liver. 28

Stott et al. ( 1981 ) also performed several acute experiments designed to evaluate 29

potential mechanisms for the carcinogenicity of 1,4

- dioxane. These experiments are dis cussed 30

separately in Section 4.5.2 (Mechanistic Studies). 31

4.2.1.1.3. Kano et al. In the Kano et al. ( 2008 ) stud y, g roups of 6

- week

- old F344/DuCrj rats 32

(10/sex/group) and Crj:BDF1 mice (10/sex/group) were administered 1,4

- dioxane (>99% pure) 33

in the drinking water for 13 weeks . The animals were observed daily for clinical signs of 34

toxicity. Food consumption and BWs were measured once per week and water consumption was 3530

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE measured twice weekly. Food and water were available ad libitum. The concentrations of 1

1,4

- dioxane in the w ater for rats and mice were 0, 640, 1,600, 4,000, 10,000, or 25,000 ppm. 2

The investigators used data from water consumption and BW changes to calculate a daily intake 3

of 1,4

- dioxane by the male and female animals. Thus, male rats received doses of approx imately 4

0, 52, 126, 274, 657, and 1,554 mg 1,4

- dioxane/kg

- day and female rats received 0, 83, 185, 427, 5

756, and 1,614 mg /kg

- day. Male mice received 0, 86, 231, 585, 882, or 1,570 mg /kg

- day and 6

female mice received 0, 170, 387, 898, 1,620, or 2,669 mg /kg

- day. 7

No information was provided as to when the blood and urine samples were collected. 8

Hematology analysis included red blood cell (RBC) count, hemoglobin, hematocrit, mean 9

corpuscular volume (MCV), platelet count, white blood cell (WBC) count, and dif ferential 10

WBCs. Serum biochemistry included total protein, albumin, bilirubin, glucose, cholesterol, 11

triglyceride (rat only), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate 12

dehydrogenase (LDH), leucine aminopeptidase (LAP), alka line phosphatase (ALP), creatinine 13

phosphokinase (CPK) (rat only), urea nitrogen, creatinine (rat only), sodium, potassium, 14

chloride, calcium (rat only), and inorganic phosphorous (rat only). Urinalysis parameters were 15

pH, protein, glucose, ketone body, b ilirubin (rat only), occult blood, and urobilinogen. Organ 16

weights (brain, lung, liver, spleen, heart, adrenal, testis, ovary, and thymus) were measured, and 17

gross necropsy and histopathologic examination of tissues and organs were performed on all 18

animal s (skin, nasal cavity, trachea, lungs, bone marrow, lymph nodes, thymus, spleen, heart, 19

tongue, salivary glands, esophagus, stomach, small and large intestine, liver, pancreas, kidney, 20

urinary bladder, pituitary thyroid adrenal, testes, epididymis, seminal vesicle, prostate, ovary, 21

uterus, vagina, mammary gland, brain, spinal cord, sciatic nerve, eye, Harderian gland, muscle, 22

bone, and parathyroid). Dunnett‘s test and χ 2 test were used to assess the statistical significance 23

of changes in continuous and dis crete variables, respectively. 24

Clinical signs of toxicity in rats were not discussed in the study report. One female rat in 25

the high dose group (1,614 mg /kg

- day) group died, but cause and time of death were not 26

specified. Final BWs were reduced at the t wo highest dose levels in females (12 and 21%) and 27

males (7 and 21%), respectively. Food consumption was reduced 13% in females at 28

1,614 mg /kg

- day and 8% in 1,554 mg /kg

- day males. A dose

- related decrease in water 29

consumption was observed in male rats sta rting at 52 mg /kg

- day (15%) and in females starting at 30

185 mg /kg

- day (12%). Increases in RBCs, hemoglobin, hematocrit, and neutrophils, and a 31

decrease in lymphocytes were observed in males at 1554 mg /kg

- day. In females, MCV was 32

decreased at doses ≥ 756 m g /kg and platelets were decreased at 1,614 mg /kg

- day. With the 33

exception of the 30% increase in neutrophils in high

- dose male rats, hematological changes were 34

within 2

– 15% of control values. Total serum protein and albumin were significantly decreased 35

in males at doses ≥ 274 mg /kg

- day and in females at doses ≥ 427 mg /kg

- day. Additional 36

changes in high

- dose male and female rats included decreases in glucose, total cholesterol, 3731

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE triglycerides, and sodium (and calcium in females), and increases in ALT (males only), AST, 1

ALP, and LAP. Serum biochemistry parameters in treated rats did not differ more than twofold 2

from control values. Urine pH was decreased in males at ≥ 274 mg /kg

- day and in females at 3

≥ 756 mg /kg

- day. 4

Kidney weights were increased in females at ≥185 mg /kg

- day with a maximum increase 5

of 15% and 44% at 1,614 mg /kg

- day for absolute and relative kidney weight, respectively. No 6

organ weight changes were noted in male rats. Histopathology findings in rats that were related 7

to exposure included nuc lear enlargement of the respiratory epithelium, nuclear enlargement of 8

the olfactory epithelium, nuclear enlargement of the tracheal epithelium, hepatocyte swelling of 9

the centrilobular area of the liver, vacuolar changes in the liver, granular changes in the liver, 10

single cell necrosis in the liver, nuclear enlargement of the proximal tubule of the kidneys, 11

hydropic changes in the proximal tubule of the kidneys, and vacuolar changes in the brain. The 12

incidence data for histopathological lesions in rats ar e presented in Table 4

- 1. The effects that 13

occurred at the lowest doses were nuclear enlargement of the respiratory epithelium in the nasal 14

cavity and hepatocyte swelling in the central area of the liver in male rats. Based on these 15

histopathological fin dings the study authors identified the LOAEL as 126 mg /kg

- day and the 16

NOAEL as 52 mg /kg

- day. 1732

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 1. Incidence of histopathological lesions in F344/DuCrj rats

exposed to 1,4

- dioxane in drinking water for 13 weeks

Effect Male dose (mg/kg

- day) a

0 52 126 274 657 1,554

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 9/10 b 10/10 b 9/10 b 10/10 b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 10/10 b 9/10 b 10/10 b

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 10/10 b 10/10 b 10/10 b

Hepatocyte swelling 0/10 0/10 9/10 b 10/10 b 10/10 b 10/10 b

Vacuolic change; liver 0/10 0/10 0/10 0/10 10/10 b 10/10 b

Granular change; liver 0/10 0/10 0/10 5/10 c 2/10 10/10 b

Single cell necrosis; liver 0/10 0/10 0/10 5/10 c 2/10 10/10 b

Nuclear enlargement; renal proximal tubule 0/10 0/10 0/10 1/10 5/10 c 9/10 b

Hydropic change; renal proximal tubule 0/10 0/10 0/10 0/10 0/10 7/10 b

Vacuolic change; brain 0/10 0/10 0/10 0/10 0/10 10/10 b

Female dose (mg/kg

- day) a

0 83 185 427 756 1,614

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 5/10 c 10/10 b 10/10 b 8/9 b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 9/10 b 10/10 b 8/9 b

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 9/10 b 10/10 b 9/9 b

Hepatocyte swelling 0/10 0/10 0/10 0/10 9/10 b 9/9 b

Vacuolic change; liver 0/10 0/10 0/10 0/10 0/10 9/9 b

Granular change; liver 2/10 0/10 1/10 5/10 c 5/10 c 8/9 b

Single cell necrosis; liver 2/10 0/10 1/10 5/10 5/10 8/9 b

Nuclear enlargement; proximal tubule 0/10 0/10 0/10 0/10 8/10 b 9/9 b

Hydropic change; proximal tubule 0/10 0/10 0/10 0/10 0/10 5/9 c

Vacuolic change; brain 0/10 0/10 0/10 0/10 0/10 9/9 b

a Data are presented for sacrificed animals.

b p ≤ 0.01 by χ 2 test.

c p ≤ 0.05.

Source: Kano et al. ( 2008 )

Clinical signs of toxicity in mice were not discussed in the study report One male mouse 1

in the high

- dose grou p (1,570 mg /kg

- day) died, but no information was provided regarding cause 2

or time of death. Final BWs were decreased 29% in male mice at 1,570 mg /kg

- day, but changed 3

less than 10% relative to controls in the other male dose groups and in female mice. Foo d 4

consumption was not significantly reduced in any exposure group. Water consumption was 5

reduced 14

– 18% in male mice exposed to 86, 231, or 585 mg /kg

- day. Water consumption was 6

further decreased by 48 and 70% in male mice exposed to 882 and 1,570 mg /kg

- day, 7

respectively. Water consumption was also decreased 31 and 57% in female mice treated with 8

1,620 and 2,669 mg /kg

- day, respectively. An increase in MCV was observed in the two highest 9

dose groups in both male (882 and 1,570 mg /kg

- day) and female mice (1,620 and 10

2,669 mg /kg

- day). Increases in RBCs, hemoglobin, and hematocrit were also observed in high 1133

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE dose males (1

, 570 mg /kg

- day). Hematological changes were within 2

– 15% of control values. 1

Serum biochemistry changes in exposed mice included decreased total protein (at 2

1,570 mg /kg

- day in males, ≥1,620 mg /kg

- day in females), decreased glucose (at 3

1,570 mg /kg

- day in males, ≥1,620 mg /kg

- day in females), decreased albumin (at 4

1,570 mg /kg

- day in males, 2,669 mg / kg

- day in females), decreased total cholesterol 5

(≥ 585 mg /kg

- day in males, ≥1,620 mg /kg

- day in females), increased serum ALT (at 6

1,570 mg /kg

- day in males, ≥ 620 mg /kg

- day in females), increased AST (at 1,570 mg /kg

- day in 7

males, 2,669 mg /kg

- day in females), increased ALP (≥ 585 mg /kg

- day in m ales, 2,669 mg /kg

8

day in females), and increased LDH (in females only at doses ≥ 1,620 mg /kg

- day). With the 9

exception of a threefold increase in ALT in male and female mice, serum biochemistry 10

parameters in treated rats did not differ more than twofold fr om control values. Urinary pH was 11

decreased in males at ≥ 882 mg /kg

- day and in females at ≥ 1,620 mg /kg

- day. 12

Absolute and relative lung weights were increased in males at 1,570 mg /kg

- day and in 13

females at 1,620 and 2,669 mg /kg

- day. Absolute kidney weigh ts were also increased in females 14

at 1,620 and 2,669 mg /kg

- day and relative kidney weight was elevated at 2,669 mg /kg

- day. 15

Histopathology findings in mice that were related to exposure included nuclear enlargement of 16

the respiratory epithelium, nuclear en largement of the olfactory epithelium, eosinophilic change 17

in the olfactory epithelium, vacuolic change in the olfactory nerve, nuclear enlargement of the 18

tracheal epithelium, accumulation of foamy cells in the lung and bronchi, nuclear enlargement 19

and deg eneration of the bronchial epithelium, hepatocyte swelling of the centrilobular area of the 20

liver, and single cell necrosis in the liver. The incidence data for histopathological lesions in 21

mice are presented in Table 4

- 2. Based on the changes in the bro nchial epithelium in female 22

mice, the authors identified the dose level of 387 mg /kg

- day as the LOAEL for mice; the 23

NOAEL was 170 mg /kg

- day ( Kano, et al., 2008 )

. 2434

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 2. Incidence of histopathological lesions in Crj: BDF1 mice

exposed to 1,4

- dioxane in drinking water for 13 weeks

Effect Male dose (mg/kg

- day) a

0 86 231 585 882 1,570

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 0/10 2/10 5/10 b 0/9

Eosinophilic change; nasal respiratory epithelium 0/10 0/10 0/10 0/10 0/10 5/9 b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 9/10 c 10/10 c 9/9 c

Eosinophilic change; nasal olfactory epithelium 0/10 0/10 0/10 0/10 0/10 6/9 c

Vacuolic change; olfactory nerve 0/10 0/10 0/10 0/10 0/10 9/9 c

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 7/10 c 9/10 c 9/9 c

Accumulation of foamy cells; lung/bronchi 0/10 0/10 0/10 0/10 0/10 6/9 c

Nuclear enlargement; bronchial epithelium 0/10 0/10 0/10 9/10 c 9/10 c 9/9 c

Degeneration; bronchial epithelium 0/10 0/10 0/10 0/10 0/10 8/9 c

Hepatocyte swelling 0/10 0/10 0/10 10/10 c 10/10 c 9/9 c

Single cell necrosis; liver 0/10 0/10 0/10 5/10 b 10/10 c 9/9 c

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 7/10 c

Eosinophilic change; nasal respiratory epithelium 0/10 0/10 1/10 1/10 5/10 b 9/10 c

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 6/10 b 10/10 c 10/10 c

Eosinophilic change; nasal olfactory epithelium 0/10 0/10 0/10 1/10 c 6/10 b 6/10 b

Vacuolic change; olfactory nerve 0/10 0/10 0/10 0/10 2/10 8/10 c

Nuclear enlargement; tracheal epithelium 0/10 0/10 2/10 9/10 c 10/10 c 10/10 c

Accumulation of foamy cells; lung/bronchi 0/10 0/10 0/10 0/10 10/10 c 10/10 c

Nuclear enlargement; bronchial epithelium 0/10 0/10 10/10 c 10/10 c 10/10 c 10/10 c

Degeneration; bronchial epithelium 0/10 0/10 0/10 0/10 7/10 c 10/10 c

Hepatocyte swelling 0/10 1/10 1/10 10/10 c 10/10 c 9/10 b

Single cell necrosis; liver 0/10 0/10 0/10 7/10 c 10/10 c 9/10 c

a Data are presented for sacrificed animals.

b p ≤ 0.01 by χ 2 test.

c p ≤ 0.05.

Source: Kano et al ( 2008 )

.

4.2.1.1.4. Yamamoto et al. Studies ( Yamamoto et al., 1998 ; Yamamoto, Urano, & Nomura, 1

1998 ) in rasH2 transgenic mice carrying the human prototype c

- Ha

- ras gene have been 2

investigated as a bioassay model for rapid carcinogenicity testing. As part of vali dation studies 3

of this model, 1,4

- dioxane was one of many chemicals that were evaluated. RasH2 transgenic 4

mice were F1 offspring of transgenic male C57BLr6J and normal female BALB / cByJ mice. 5

CB6F 1 mice were used as a nontransgenic control. Seven

- to nin e

- week

- old mice (10

– 15/group) 635

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE were exposed to 0, 0.5, or 1% 1,4

- dioxane in drinking water for 26 weeks . An increase in lung 1

adenomas was observed in treated transgenic mice, as compared to treated nontransgenic mice. 2

The tumor incidence in transgenic ani mals, however, was not greater than that observed in 3

vehicle

- treated transgenic mouse controls. Further study details were not provided. 4

4.2.1.2. Chronic Oral Toxicity and Carcinogenicity

4.2.1.2.1. Argus et al. Twenty

- six adult male Wistar rats ( Argus, Arcos, & Hoch

- Ligeti, 1965 ) 5

weighing between 150 and 200 g were exposed to 1,4

- dioxane (purity not reported) in the 6

drinking water at a concentration of 1% for 64.5 weeks . A group of nine untreated rats served as 7

control. Food and water were available ad libitum. The drinking water intake for treated 8

animals was reported to be 30 mL/day, resulting in a dose/rat of 300 mg /day. Using a reference 9

BW of 0.462 kg for chronic exposure to male Wistar rats ( U.S. EPA, 1988 ) , it can be estimated 10

that these rats received daily doses of approximately 640 mg /kg

- day. All animals that died or 11

were killed during the study underwent a complete necropsy. A list of specific tissues examined 12

microscopically was not provided; however, it is apparent that the liver, kidneys, lungs, 13

lymphatic tissue, and spleen were examined. No statistical a nalysis of the results was conducted. 14

Six of the 26 treated rats developed hepatocellular carcinomas, and these rats had been 15

treated for an average of 452 day s (range, 448

– 455 day s). No liver tumors were observed in 16

control rats. In two rats that died a fter 21.5 weeks of treatment, histological changes appeared to 17

involve the entire liver. Groups of cells were found that had enlarged hyperchromic nuclei. Rats 18

that died or were killed at longer intervals showed similar changes, in addition to large cell s with 19

reduced cytoplasmic basophilia. Animals killed after 60 weeks of treatment showed small 20

neoplastic nodules or multifocal hepatocellular carcinomas. No cirrhosis was observed in this 21

study. Many rats had extensive changes in the kidneys often rese mbling glomerulonephritis, 22

however, incidence data was not reported for these findings. This effect progressed from 23

increased cellularity to thickening of the glomerular capsule followed by obliteration of the 24

glomeruli. One treated rat had an early tran sitional cell carcinoma in the kidney‘s pelvis; this rat 25

also had a large tumor in the liver. The lungs from many treated and control rats (incidence not 26

reported) showed severe bronchitis with epithelial hyperplasia and marked peribronchial 27

infiltration, as well as multiple abscesses. One rat treated with 1,4

- dioxane developed leukemia 28

with infiltration of all organs, particularly the liver and spleen, with large, round, isolated 29

neoplastic cells. In the liver, the distribution of cells in the sinusoids was suggestive of myeloid 30

leukemia. The dose of 640 mg /kg

- day tested in this study was a free

- standing LOAEL, 31

identified by EPA, for glomerulonephritis in the kidney and histological changes in the liver 32

(hepatocytes with enlarged hyperchromic nuclei, la rge cells with reduced cytoplasmic 33

basophilia). 3436

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.2.1.2.2. Argus et al.; Hoch

- Ligeti et al

. Five groups (28

- 32/dose group) of male 1

Sprague Dawley rats ( 2

- 3 months of age ) weighing 110

– 230 g at the beginning of the experiment 2

were administered 1,4

- dioxane (purity no t reported) in the drinking water for up to 13 month s at 3

concentrations of 0, 0.75, 1.0, 1.4, or 1.8% ( Argus, Sohal, Bryant, Hoch

- Ligeti, & Arcos, 1973 ; 4

Hoch

- Ligeti, Argus, & Arcos, 1970 ) . The drinking water intake was determine d for each group 5

over a 3

- day measurement period conducted at the beginning of the study and twice during the 6

study (weeks were not specified). The rats were killed with ether at 16 month s or earlier if nasal 7

tumors were clearly observable. Complete auto psies were apparently performed on all animals, 8

but only data from the nasal cavity and liver were presented and discussed. The nasal cavity was 9

studied histologically only from rats in which gross tumors in these locations were present; 10

therefore, early tumors may have been missed and pre

- neoplastic changes were not studied. No 11

statistical analysis of the results was conducted. Assuming a BW of 0.523 kg for an adult male 12

Sprague Dawley rat ( U.S. EPA, 1988 ) and a drinking water intake of 30 mL/day as reported by 13

the stud y authors, dose estimates were 0, 430, 574, 803, and 1,032 mg /kg

- day. The progression 14

of liver tumorigenesis was evaluated by an additional group of 10 male rats administered 1% 15

1,4

- dioxane in the drinking water (574 mg /kg

- day), 5 of which were sacrificed after 8 month s of 16

treatment and 5 were killed after 13 month s of treatment. Liver tissue from these rats and control 17

rats was processed for electron microscopy examination. 18

Nasal cavity tumors were observed upon gross examination in six rats (1/30 in t he 0.75% 19

group, 1/30 in the 1.0% group, 2/30 in the 1.4% group, and 2/30 in the 1.8% group). Gross 20

observation showed the tumors visible either at the tip of the nose, bulging out of the nasal 21

cavity, or on the back of the nose covered by intact or later ulcerated skin. As the tumors 22

obstructed the nasal passages, the rats had difficulty breathing and lost weight rapidly. No 23

neurological signs or compression of the brain were observed. In all cases, the tumors were 24

squamous cell carcinomas with marked k eratinization and formation of keratin pearls. Bony 25

structure was extensively destroyed in some animals with tumors, but there was no invasion into 26

the brain. In addition to the squamous carcinoma, two adenocarcinomatous areas were present. 27

One control rat had a small, firm, well

- circumscribed tumor on the back of the nose, which 28

proved to be subcutaneous fibroma. The latency period for tumor onset was 329

– 487 day s. 29

Evaluation of the latent periods and doses received did not suggest an inverse relation ship 30

between these two parameters. 31

Argus et al. ( 1973 ) studied the progression of liver tumorigenesis by electron microscopy 32

of liver tissues obtained following interim sacrifice at 8 and 13 month s of exposure (5 rats/group, 33

574 mg /kg

- day). The first change observed in the liver was an increase in the size of the nucleus 34

of the hepatocytes, mostly in the periportal area. Precancerous changes w ere characterized by 35

disorganization of the rough endoplasmic reticulum, an increase in smooth endoplasmic 36

reticulum, and a decrease in glycogen and increase in lipid droplets in hepatocytes. These 3737

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE changes increased in severity in the hepatocellular carci nomas in rats exposed to 1,4

- dioxane for 1

13 month s. 2

Three types of liver nodules were observed in exposed rats at 13

– 16 month s. The first 3

consisted of groups of cells with reduced cytoplasmic basophilia and a slightly nodular 4

appearance as viewed by light microscopy. The second type of circumscribed nodule was 5

described consisting of large cells, apparently filled and distended with fat. The third type of 6

nodule was described as finger

- like strands, 2

– 3 cells thick, of smaller hepatocytes with large 7

hype rchromic nuclei and dense cytoplasm. This third type of nodule was designated as an 8

incipient hepatoma, since it showed all the histological characteristics of a fully developed 9

hepatoma. All three types of nodules were generally present in the same live r. Cirrhosis of the 10

liver was not observed. The numbers of incipient liver tumors and hepatomas in rats from this 11

study (treated for 13 month s and observed at 13

– 16 month s) are presented in Table 4

- 3. 12

Table 4

- 3. Number of incipient liver tumors and hepat omas in male

Sprague

- Dawley rats exposed to 1,4

- dioxane in drinking water for

13 month s

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 2 8

– 3 2; incidence in

control rats was not reported; no statistical analysis of the results was conducted in the study.

Source: Argus et al. ( 1973 )

.

Treatment with all dose levels of 1,4

- dioxane induced marked kidney alterations, but 13

quantitative incidence data were not provided. Qualitatively, the changes indicated 14

glomerulonephritis and pyelonephritis, with characteristic epithelial proliferation of Bowman‘s 15

capsule, periglomerular fibrosis, and distension of tubules. No kidney tumors were found. No 16

tumors were found in the lungs. One rat at the 1.4% treatment level showed early peripheral 17

adenomatous chan ge of the alveolar epithelium and another rat in the same group showed 18

papillary hyperplasia of the bronchial epithelium. The lowest dose tested (430 mg /kg

- day) was 19

considered a LOAEL by EPA for hepatic and renal effects in this study. 20

4.2.1.2.3. Hoch

- Ligeti and

Argus

. Hoch

- Ligeti and Argus ( 1970 ) provided a brief account of 21

the results of exposure of guinea pigs to 1,4

- dioxane. A group of 22 male guinea pigs (neither 22

strain nor age provided) was administered 1,4

- dioxane (purity not provided) in the drinking 23

water fo r at least 23 month s and possibly up to 28 month s. The authors stated that the 24

concentration of 1,4

- dioxane was regulated so that normal growth of the guinea pigs was 2538

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE maintained, and varied 0.5

– 2% (no further information provided). The investigators furt her 1

stated that the amount of 1,4

- dioxane received by the guinea pigs over a 23

- month period was 2

588

– 635 g. Using a reference BW of 0.89 kg for male guinea pigs in a chronic study ( U.S. EPA, 3

1988 ) and assuming an exposure period of 700 day s (23 month s), the guinea pigs re ceived doses 4

between 944 and 1,019 mg 1,4

- dioxane/kg

- day. A group of ten untreated guinea pigs served as 5

controls. All animals were sacrificed within 28 month s, but the scope of the postmortem 6

examination was not provided. 7

Nine treated guinea pigs showe d peri

- or intrabronchial epithelial hyperplasia and nodular 8

mononuclear infiltration in the lungs. Also, two guinea pigs had carcinoma of the gallbladder, 9

three had early hepatomas, and one had an adenoma of the kidney. Among the controls, four 10

guinea p igs had peripheral mononuclear cell accumulation in the lungs, and only one had 11

hyperplasia of the bronchial epithelium. One control had formation of bone in the bronchus. No 12

further information was presented in the brief narrative of this study. Given the limited reporting 13

of the results, a NOAEL or LOAEL value was not provided for this study. 14

4.2.1.2.4. Kociba et al. Groups of 6

– 8

- week

- old Sherman rats (60/sex/dose level) were 15

administered 1,4

- dioxane (purity not reported) in the drinking water at levels of 0 ( controls), 16

0.01, 0.1, or 1.0% for up to 716 day s ( Kociba, McCollister, Park, Torkelson, & Gehring, 1974 )

. 17

The drinking water was prepared twice weekly during the first year of the study and weekly 18

during the second year of the study. Water samples were collected periodically and analyzed for 19

1,4

- dioxane content by routine gas liquid chromatography. Food and water were available ad 20

libitum. Rats were observed daily for clinical signs of toxicity, and BWs were measured twice 21

weekly during the first month , weekly during months 2

– 7, and biweekly thereafter. Water 22

consumption was record ed at three different time periods during the study: day s 1

– 113, 114

– 23

198, and 446

– 460. Blood samples were collected from a minimum of five male and five female 24

control and high

- dose rats during the 4th, 6th, 12th, and 18th month s of the study and at 25

term ination. Each sample was analyzed for packed cell volume, total erythrocyte count, 26

hemoglobin, and total and differential WBC counts. Additional endpoints evaluated included 27

organ weights (brain, liver, kidney, testes, spleen, and heart) and gross and mi croscopic 28

examination of major tissues and organs (brain, bone and bone marrow, ovaries, pituitary, uterus, 29

mesenteric lymph nodes, heart, liver, pancreas, spleen, stomach, prostate, colon, trachea, 30

duodenum, kidneys, esophagus, jejunum, testes, lungs, spi nal cord, adrenals, thyroid, 31

parathyroid, nasal turbinates, and urinary bladder). The number of rats with tumors, hepatic 32

tumors, hepatocellular carcinomas, and nasal carcinomas were analyzed for statistical 33

significance with Fisher‘s Exact test (one

- tail ed), comparing each treatment group against the 34

respective control group. Survival rates were compared using χ 2 Contingency Tables and 35

Fisher‘s Exact test. Student‘s test was used to compare hematological parameters, body and 36

organ weights, and water con sumption of each treatment group with the respective control group. 3739

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Male and female rats in the high

- dose group (1% in drinking water) consumed slightly 1

less water than controls. BW gain was depressed in the high

- dose groups relative to the other 2

groups a lmost from the beginning of the study (food consumption data were not provided). 3

Based on water consumption and BW data for specific exposure groups, Kociba et al. ( 1974 ) 4

calculated mean daily doses of 9.6, 94, and 1,015 mg /kg

- day for male rats and 19, 148, and 5

1,599 mg /kg

- day for female rats during day s 114

– 198 for the 0.01, 0.1, and 1.0% concentration 6

levels, respectively. Treatment with 1 ,4

- dioxane significantly increased mortality among high

7

dose males and females beginning at about 2

– 4 month s of treatment. These rats showed 8

degenerative changes in both the liver and kidneys. From the 5th month on, mortality rates of 9

control and treated groups were not different . There were no treatment

- related alterations in 10

hematological parameters. At termination, the only alteration in organ weights noted by the 11

authors was a significant increase in absolute and relative liver weights in male and f emale high

12

dose rats (data not shown). Histopathological lesions were restricted to the liver and kidney from 13

the mid

- and high

- dose groups and consisted of variable degrees of renal tubular epithelial and 14

hepatocellular degeneration and necrosis (no quan titative incidence data were provided). Rats 15

from these groups also showed evidence of hepatic regeneration, as indicated by hepatocellular 16

hyperplastic nodule formation and evidence of renal tubular epithelial regenerative activity 17

(observed after 2 year s of exposure). These changes were not seen in controls or in low

- dose 18

rats. The authors determined a LOAEL of 94 mg /kg

- day based on the liver and kidney effects in 19

male rats. The corresponding NOAEL value was 9.6 mg /kg

- day. 20

Histopathological examinati on of all the rats in the study revealed a total of 132 tumors in 21

114 rats. Treatment with 1% 1,4

- dioxane in the drinking water resulted in a significant increase 22

in the incidence of hepatic tumors (hepatocellular carcinomas in six males and four females) . In 23

addition, nasal carcinomas (squamous cell carcinoma of the nasal turbinates) occurred in one 24

high

- dose male and two high

- dose females. Since 128 out of 132 tumors occurred in rats from 25

the 12th to the 24th month , Kociba et al. ( 1974 ) assumed that the effective number of rats was 26

the number surviving at 12 month s, which was also when the first hepatic tumor was noticed. 27

The incidences o f liver and nasal tumors from Kociba et al. ( 1974 ) are presented in Table 4

- 4. 28

Tumors in other organs were not elevated when compared to control incidence and did not 29

appear to be related to 1,4

- dioxane administration. 3040

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 4. Incidence of liver and nasal tumors in male and female

Sherman rats (combined) treated with 1,4

- dio xane in the drinking water for

2 years

Dose in mg /kg

- day

(average of male

and female dose) Effective

number of

animals a Number of tumor

bearing animals Number of 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 12 b 10 c 3 d

a Rats surviving until 12 month s 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 )

.

The high

- dose level was the only dose that increased the formation of liver tumors over 1

control ( males 1,015 mg /kg

- day; females 1,599 mg /kg

- day ) and also cause d significant liver and 2

kidney toxicity in these animals. The mid

- dose group ( males 94 mg /kg

- day; females 148 mg /kg

3

day ) experienced hepatic and renal degeneratio n and necrosis, as well as regenerative 4

proliferation in hepatocytes and renal tubule epithelial cells. No increase in tumor formation was 5

seen in the mid

- dose group. No toxicity or tumor formation was observed in either sex in the 6

low

- dose (males 9.6 mg /kg

- day; females 19 mg /kg

- day) group of rats. 7

4.2.1.2.5. National Cancer Institute (NCI)

. Groups of Osborne

- Mendel rats (35/sex/dose) and 8

B6C3F 1 mice (50/sex/dose) were administered 1,4

- dioxane (≥ 99.95% pure) in the drinking 9

water for 110 or 90 weeks

, respectively, at levels of 0 (matched controls), 0.5, or 1% ( NCI, 10

1978 ) . Solutions of 1,4

- dioxane were prepared wi th tap water. The report indicated that at 11

105 weeks from the earliest starting date, a new necropsy protocol was instituted. This affected 12

the male controls and high

- dose rats, which were started a year later than the original groups of 13

rats and mice. Food and water were available ad libitum. Endpoints monitored in this bioassay 14

included clinical signs (twice daily), BWs (once every 2 weeks for the first 12 weeks and every 15

month during the rest of the study), food and water consumption (once per month in 20% of the 16

animals in each group during the second year of the study), and gross and microscopic 17

appearance of all major organs and tissues (mammary gland, trachea, lungs and bronchi, heart, 18

bone marrow, liver, bile duct, spleen, thymus, lymph nodes, sa livary gland, pancreas, kidney, 19

esophagus, thyroid, parathyroid, adrenal, gonads, brain, spinal cord, sciatic nerve, skeletal 20

muscle, stomach, duodenum, colon, urinary bladder, nasal septum, and skin). Based on the 21

measurements of water consumption and BW s, the investigators calculated average daily intakes 2241

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE of 1,4

- dioxane of 0, 240, and 530 mg /kg

- day in male rats, 0, 350, and 640 mg /kg

- day in female 1

rats, 0, 720, and 830 mg /kg

- day in male mice, and 0, 380, and 860 mg /kg

- day in female mice. 2

According to th e report, the doses of 1,4

- dioxane in high

- dose male mice were only slightly 3

higher than those of the low

- dose group due to decreased fluid consumption in high

- dose male 4

mice. 5

During the second year of the study, the BWs of high

- dose rats were lower than c ontrols, 6

those of low

- dose males were higher than controls, and those of low

- dose females were 7

comparable to controls. The fluctuations in the growth curves were attributed to mortality by the 8

investigators; quantitative analysis of BW changes was not don e. Mortality was significantly 9

increased in treated rats, beginning at approximately 1 year of study. Analysis of Kaplan

- Meier 10

curves (plots of the statistical estimates of the survival probability function) revealed significant 11

positive dose

- related tre nds ( p < 0.001, Tarone test). In male rats, 33/35 (94%) in the control 12

group, 26/35 (74%) in the mid

- dose group, and 33/35 (94%) in the high

- dose group were alive 13

on week 52 of the study. The corresponding numbers for females were 35/35 (100%), 30/35 14

(86 %), and 29/35 (83%). Nonneoplastic lesions associated with treatment with 1,4

- dioxane were 15

seen in the kidneys (males and females), liver (females only), and stomach (males only). Kidney 16

lesions consisted of vacuolar degeneration and/or focal tubular epi thelial regeneration in the 17

proximal cortical tubules and occasional hyaline casts. Elevated incidence of hepatocytomegaly 18

also occurred in treated female rats. Gastric ulcers occurred in treated males, but none were seen 19

in controls. The incidence of p neumonia was increased above controls in high

- dose female rats. 20

The incidence of nonneoplastic lesions in rats following drinking water exposure to 1,4

- dioxane 21

is presented in Table 4

- 5. EPA identified the LOAEL in rats from this study as 240 mg /kg

- day 22

f or increased incidence of gastric ulcer and cortical tubular degeneration in the kidney in males; 23

a NOAEL was not established. 24

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 0/31 a 20/31 b

(65%) 27/33 b

(82%) 0/31 a 0/34 10/32 b

(31%)

Hepatocytomegaly 5/31

(16%) 3/32

(9%) 11/33

(33%) 7/31 a

(23%) 11/33

(33%) 17/32 b

(53%)

Gastric ulcer 0/30 a 5/28 b

(18%) 5/30 b

(17%) 0/31 1/33

(3%) 1/30

(3%)

Pneumonia 8/30

(27%) 15/31

(48%) 14/33

(42%) 6/30 a

(20%) 5/34

(15%) 25/32 b

(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.42

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

Neoplasms associated with 1,4

- dioxane treatment were limited to the nasal cavity 1

(squamous cell carcinomas, adenocarcinomas, and one rhabdomyoma) in both sexes, liver 2

(hepatocellular adenomas) in females, and testis/epididymis (mesotheliomas) in males. The first 3

tumors were seen at week 52 in males and week 66 in females. The incidence of squamous cell 4

carcinomas in the nasal turbinates in male and female rats is presented in Table 4

- 6. Squamous 5

cell carcinomas were first seen on week 66 of the study. Morphologically, these tumors varied 6

from minimal foci of locally invasive squamous cell proliferation to advanced growths consisting 7

of extensive columns of epithelial cells projecting either into free spaces of the nasal cavity 8

and/or infiltrating into the submucosa. Adenocarcinomas of the nasal cavity were observed in 9

3 of 34 high

- dose male rats, 1 of 35 low

- dose female rats, and 1 of 35 high

- dose female rats. 10

The single rhabdomyoma (benign skeletal muscle tumor) was observed in the nasal cavity of a 11

male rat from the low

- dose group. A subsequent re

- examination of the nasal tissue sections by 12

Goldsworthy et al. ( 1991 ) concluded that the location of the tumors in the nasal apparatus was 13

consistent with the possibility that the nasal tumors resulted from inhalation of water droplets by 14

the rats (see Section 4.5.2 for more discussion of Goldsworthy et al. ( 1991 ) ). 15

Table 4

- 6. Incidence of nasal cavity squamous cell carcinoma and liver

hepatocellular adenoma in Osborne

- M endel rats exposed to 1,4

- dioxane in

drinking water

Males (mg/kg

- day) a

0 240 b 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 )

.

The incidence of hepatocellular adenomas in male and female rats is presented in Table 16

4

- 6. Hepatocellular adenomas were first observed in high

- dose females in week 70 of the study. 17

These tumors consisted of proliferating hepatic cells oriented as concen tric cords. Hepatic cell 18

size was variable; mitoses and necrosis were rare. Mesothelioma of the vaginal tunics of the 1943

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE testis/epididymis was seen in male rats (2/33, 4/33, and 5/34 in controls, low

- , and high

- dose 1

animals, respectively). The difference b etween the treated groups and controls was not 2

statistically significant. These tumors were characterized as rounded and papillary projections of 3

mesothelial cells, each supported by a core of fibrous tissue. Other reported neoplasms were 4

considered spon taneous lesions not related to treatment with 1,4

- dioxane. 5

In mice, mean BWs of high

- dose female mice were lower than controls during the second 6

year of the study, while those of low

- dose females were higher than controls. In males, mean 7

BWs of high

- dose animals were higher than controls during the second year of the study. 8

According to the investigators, these fluctuations could have been due to mortality; no 9

quantitative analysis of BWs was done. No other clinical signs were reported. Mortality was 10

si gnificantly increased in female mice ( p < 0.001, Tarone test), beginning at approximately 11

80 weeks on study. The numbers of female mice that survived to 91 weeks were 45/50 (90%) in 12

the control group, 39/50 (78%) in the low

- dose group, and 28/50 (56%) in the high

- dose group. 13

In males, at least 90% of the mice in each group were still alive at week 91. Nonneoplastic 14

lesions that increased significantly due to treatment with 1,4

- dioxane were pneumonia in males 15

and females and rhinitis in females. The inci dences of pneumonia were 1/49 (2%), 9/50 (18%), 16

and 17/47 (36%) in control, low

- dose, and high

- dose males, respectively; the corresponding 17

incidences in females were 2/50 (4%), 33/47 (70%), and 32/36 (89%). The incidences of rhinitis 18

in female mice were 0 /50, 7/48 (14%), and 8/39 (21%) in control, low

- dose, and high

- dose 19

groups, respectively. Pair

- wise comparisons of low

- dose and high

- dose incidences with controls 20

for incidences of pneumonia and rhinitis in females using Fisher‘s Exact test (done for this 21

review) yielded p

- values < 0.001 in all cases. Incidences of other lesions were considered to be 22

similar to those seen in aging mice. The authors stated that hepatocytomegaly was commonly 23

found in dosed mice, but the incidences were not significantly di fferent from controls and 24

showed no dose

- response trend. EPA concluded the LOAEL for 1,4

- dioxane in mice was 25

380 mg /kg

- day based on the increased incidence of pneumonia and rhinitis in female mice; a 26

NOAEL was not established in this study. 27

As shown in T able 4

- 7, treatment with 1,4

- dioxane significantly increased the incidence 28

of hepatocellular carcinomas or adenomas in male and female mice in a dose

- related manner. 29

Tumors were first observed on week 81 in high

- dose females and in week 58 in high

- dose ma les. 30

Tumors were characterized by parenchymal cells of irregular size and arrangement, and were 31

often hypertrophic with hyperchromatic nuclei. Mitoses were seldom seen. Neoplasms were 32

locally invasive within the liver, but metastasis to the lungs was ra rely observed. 3344

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 7. Incidence of hepatocellular adenoma or carcinoma in B6C3F 1 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 )

.

In addition to liver tumors, a variety of other benign and malignant neoplasms occurred. 1

However, the report ( NCI, 1978 ) indicated that each type had been encountered previously as a 2

spontaneous lesion in the B6C3F 1 mouse. The report further stated that the incidences of these 3

neoplasms were unr elated by type, site, group, or sex of the animal, and hence, not attributable to 4

exposure to 1,4

- dioxane. There were a few nasal adenocarcinomas (1/48 in low

- dose females 5

and 1/49 in high

- dose males) that arose from proliferating respiratory epithelium l ining of the 6

nasal turbinates. These growths extended into the nasal cavity, but there was minimal local 7

tissue infiltration. Nasal mucosal polyps were rarely observed. The polyps were derived from 8

mucus

- secreting epithelium and were otherwise unremarka ble. There was a significant negative 9

trend for alveolar/bronchiolar adenomas or carcinomas of the lung in male mice, such that the 10

incidence in the matched controls was higher than in the dosed groups. The report ( NCI, 1978 ) 11

indicated that the probable reason for this occurrence was that the dosed animals did not live as 12

long as the controls, thus diminishing the po ssibility of the development of tumors in the dosed 13

groups. 14

4.2.1.2.6. Kano et al. ; Japan Bioassay Research Center; Yamazaki et al. The Japan 15

Bioassay Research Center ( JBRC ) conducted a 2

- year drinking water study determining the 16

effects of 1,4

- dioxane on both sexes of rats and mice. The study results have been reported 17

several times: once as conference proceedings ( Yamazaki et al., 1994 ) , once as a laboratory 18

report ( JBRC, 1998 ) , and most recently as a peer

- reviewed manuscript ( Kano et al., 2009 ) . Dr. 19

Yamazaki also provided some detailed information ( Yamazaki, 2006 ) . Variations in the data 20

between these three reports were noted and included: (1) the level of detail on dose information 21

reported; (2) categories for incidence data reported (e.g., all animals or sacrificed animals); and 22

(3) analysis of non

- and neoplastic lesions. 2345

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE The 1,4

- dioxane dose information provided in the reports varied. Specifically, Yamazaki 1

et al. ( 1994 ) only included dr inking water concentrations for each dose group. In contrast, JBRC 2

( 1998 ) included drinking water concentrations (ppm), in addition using body weights and water 3

consumption measurements to calculate daily chemical intake (mg/kg

- day). JBRC ( 1998 ) 4

reported daily che mical intake for each dose group as a range. Thus, for the External Peer 5

Review draft of this Toxicological Review of 1,4

- Dioxane ( U.S. EPA, 2009b ) , the midpoint of 6

the range was used. Ka no et al. ( 2009 ) also reported a calculation of daily chemical intak e based 7

on body weight and water consumption measurements; however, for each dose group they 8

reported a mean and standard deviation estimate. Therefore, because the mean more accurately 9

represents the delivered dose than the midpoint of a range, the Kano et al. ( 2009 ) calculated 10

mean chemical intake (mg/kg

- day) is used fo r quantitative analysis of this data. 11

The categories for which incidence rates were described also varied among the reports. 12

Yamazaki et al. ( 1994 ) and Kano et al. ( 2009 ) reported histopathological results for all animals, 13

including dead and moribund animals; however, the detailed JBRC laboratory findings ( 1998 ) 14

included separate incidence reports for de ad and moribund animals, sacrificed animals, and all 15

animals. 16

Finally, the criteria used to evaluate some of the data were updated when JBRC published 17

the most recent manuscript by Kano et al. ( 2009 ) . The manuscript by Kano et al. ( 2009 ) stated 18

that the lesions diagnosed in the earlier reports ( JBRC, 1998 ; Yamazaki, et al., 1994 ) were re

19

examined and recategorized as appropriate according to current pathological diagnostic criteria 20

(see references in Kano et al. ( 2009 ) ). 21

Groups of F344/DuCrj rats (50/sex/dose level) were exposed to 1,4

- dioxane (>99% pure) 22

in the drinking water at levels of 0, 200, 1,000, or 5,000 ppm for 2 years. Groups of Crj: BDF1 23

mice (50/sex/dose level) were sim ilarly exposed in the drinking water to 0, 500, 2,000, or 24

8,000 ppm of 1,4

- dioxane. The high doses were selected based on results from the Kano et al. 25

( 2008 ) 13

- week drinking water study so as not to exceed the maximum tolerated dose (MTD) in 26

that study. Both rats and mice were 6 weeks old at the beginning of the study. Food and water 27

were available ad li bitum. The animals were observed daily for clinical signs of toxicity; and 28

BWs were measured once per week for 14 weeks and once every 2 weeks until the end of the 29

study. Food consumption was measured once a week for 14 weeks and once every 4 weeks for 30

t he remainder of the study. The investigators used data from water consumption and BW to 31

calculate an estimate of the daily intake of 1,4

- dioxane (mg/kg

- day) by male and female rats and 32

mice. Kano et al. ( 2009 ) reported a calculated mean ± standard deviation for the daily doses of 33

1,4

- dioxane for the duration of the study . Male rats received doses of approximately 0, 11±1, 34

55±3, or 274±18 mg /kg

- day and female rats received 0, 18±3, 83±14, or 429±69 mg /kg

- day. 35

Male mice received doses of 0, 49±5, 191±21, or 677±74 mg /kg

- day and female mice received 0, 36

66±10, 278±40, or 96 4±88 mg /kg

- day. For the remainder of this document, including the dose

- 3746

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE response analysis, the mean calculated intake values are used to identify dose groups. The Kano 1

et al. ( 2009 ) study was conducted in accordance with the Organization for Economic Co

2

operation and Development (OECD) Principles for Good Laboratory Practice (GLP). 3

No information was provided as to when urine samples were collected. Blood samples 4

were collected only at the end of the 2

- year study ( Yamazaki, 2006 )

. Hematology analysis 5

included RBCs, hemoglobin, hematocrit, MCV, platelets, WBCs and differential WBCs. Serum 6

biochemistry included total protein, albumin, bilirubin, glucose, cholesterol, triglyceride (rat 7

only), phospholipid, ALT, AST, LDH, LAP, ALP, γ

- glutamyl transpeptidase (GGT), CPK, urea 8

nitrogen, creatinin e (rat only), sodium, potassium, chloride, calcium, and inorganic phosphorous. 9

Urinalysis parameters were pH, protein, glucose, ketone body, bilirubin (rat only), occult blood, 10

and urobilinogen. Organ weights (brain, lung, liver, spleen, heart, adrenal, testis, ovary, and 11

thymus) were measured, and gross necropsy and histopathologic examination of tissues and 12

organs were performed on all animals (skin, nasal cavity, trachea, lungs, bone marrow, lymph 13

nodes, thymus, spleen, heart, tongue, salivary glands, esophagus, stomach, small and large 14

intestine, liver, pancreas, kidney, urinary bladder, pituitary, thyroid, adrenal, testes, epididymis, 15

seminal vesicle, prostate, ovary, uterus, vagina, mammary gland, brain, spinal cord, sciatic nerve, 16

eye, Harderian gla nd, muscle, bone, and parathyroid). Dunnett‘s test and χ 2 test were used to 17

assess the statistical significance of changes in continuous and discrete variables, respectively. 18

For rats, growth and mortality rates were reported in Kano et al. ( 2009 ) for the duration 19

of the study. Both male and female rats in the high dose g roups (274 and 429 mg /kg

- day, 20

respectively) exhibited slower growth rates and terminal body weights that were significantly 21

different (

p < 0.05) compared to controls. A statistically significant reduction in terminal BWs 22

was observed in high

- dose male rat s (5%, p < 0.01) and in high

- dose female rats (18%, p < 0.01) 23

( Kano, et al., 2009 ) . Food consumption was not significantly affected by treatment in male or 24

female rats; however, water consumption in female rats administered 18 mg /kg

- day was 25

significantly greater (p < 0.05) . 26

All control and exposed rats lived at least 12 month s following study initiation 27

( Yamazaki, 2006 ) ; however, survival at the end of the 2

- year study in the high dose group of 28

male and female rats (274 and 429 mg /kg

- day, respectively) was approximately 50%, which was 29

significantly different compared to controls. The investigators attributed these early deaths to the 30

increased incidence in nasal t umors and peritoneal mesotheliomas in male rats and nasal and 31

hepatic tumors in female rats. ( Yamazaki, 2006 )

. 32

Se veral hematological changes were noted in the JBRC report ( 1998 ) : Decreases in RBC 33

(male rats only), hemoglobin, hematocrit, and MCV; and increases in platelets in high

- dose 34

groups were observed ( JBRC, 1998 ) . These changes (except for MCV) also occurred in mid

35

dose males. With the exception of a 23% decrease in hemoglobin in high

- dose male rats and a 36

27% increase in platelets in high

- dose female rats, hematological changes were within 15% of 3747

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE control values. Significant changes in serum chemistry parameter s occurred only in high

- dose 1

rats (males: increased phospholipids, AST, ALT, LDH, ALP, GGT, CPK, potassium, and 2

inorganic phosphorus and decreased total protein, albumin, and glucose; females: increased total 3

bilirubin, cholesterol, phospholipids, AST, AL T, LDH, GGT, ALP, CPK, and potassium, and 4

decreased blood glucose) ( JBRC, 1998 ) . Increases in serum enzyme activities ranged from <2

- 5

to 17

- fold above control values, with the largest increases seen for ALT, AST, and GGT. Urine 6

pH was significantly de creased at 274 mg /kg

- day in male rats (not tested at other dose levels) 7

and at 83 and 429 mg /kg

- day in female rats ( JBRC, 1998 ) . Also, blood in the urine was seen in 8

female rats at 83 and 429 mg /kg

- day ( JBRC, 1998 ) . In male rats, relative liver weights were 9

increased at 55 and 274 mg /kg

- day ( Kano, e t al., 2009 ) . In female rats, relative liver weight was 10

increased at 429 mg /kg

- day ( Kano, et al., 2009 )

. 11

Microscopic examination of the tissues showed nonneoplastic alterations in the nasal 12

cavity, liver, and kidneys mainly in high

- dose rats and, in a few cases, in mid

- dose rats ( Table s 13

4

- 8 and 4

- 9). Alterations in high

- dose (274 mg /kg

- day) male rats consisted of nuclear 14

enlargement and metaplasia of the olfactory and respiratory epithelia, atrophy of the olfactory 15

epithelium, hydropic changes and sclerosis of the lamina propria, adhesion, and inflam mation. 16

In female rats, nuclear enlargement of the olfactory epithelium occurred at doses ≥ 83 mg /kg

17

day, and nuclear enlargement and metaplasia of the respiratory epithelium, squamous cell 18

hyperplasia, respiratory metaplasia of the olfactory epithelium, hydropic changes and sclerosis of 19

the lamina propria, adhesion, inflammation, and proliferation of the nasal gland occurred at 20

429 mg /kg

- day. Alterations were seen in the liver at ≥ 55 mg /kg

- day in male rats (spongiosis 21

hepatis, hyperplasia, and clear and mixed cell foci) and at 429 mg /kg

- day in female rats 22

(hyperplasia, spongiosis hepatis, cyst formation, and mixed cell foci). Nuclear enlargement of 23

the renal proximal tubule occurred in males at 274 mg /kg

- day and in females at ≥ 83 mg /kg

- day 24

( JBRC, 1998 )

. 2548

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 epithelium c 0/50 0/50 0/50 26/50 e

Squamous cell metaplasia; nasal respiratory epithelium c 0/50 0/50 0/50 31/50 e

Squamous cell hyperplasia; nasal respiratory epithelium c 0/50 0/50 0/50 2/50

Nuclear enlargement; nasal olfactory epithelium c 0/50 0/50 5/50 f 38/50 e

Respiratory metaplasia; nasal olfactory epithelium d 12/50 11/50 20/50 43/50

Atrophy; nasal olfactory epithelium d 0/50 0/50 0/50 36/50

Hydropic change; lamina propria d 0/50 0/50 0/50 46/50

Sclerosis; lamina propria d 0/50 0/50 1/50 44/50

Adhesion; nasal cavity d 0/50 0/50 0/50 48/50

Inflammation; nasal cavity d 0/50 0/50 0/50 13/50

Hyperplasia; liver d 3/50 2/50 10/50 24/50

Spongiosis hepatis; liver d 12/50 20/50 25/50 f 40/50

Clear cell foci; liver c 3/50 3/50 9/50 8/50

Acidophilic cell foci; liver c 12/50 8/50 7/50 5/50

Basophilic cell foci; liver c 7/50 11/50 8/50 16/50 f

Mixed

- cell foci; liver c 2/50 8/50 14/50 e 13/50 e

Nuclear enlargement; kidney proximal tubule d 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 )

.

c Data f rom Kano et al. ( 2009 )

. d Data from JBRC ( 1998 ) . JBRC did not report st atistical significance for the ―All animals‖ comparison.

e p < 0.01 b y χ

2 test.

f p < 0.05 b y χ

2 test

. Sources: Kano et al. ( 2009 ) and JBRC ( 1998 )

.49

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 epithelium c 0/50 0/50 0/50 13/50 e

Squamous cell metaplasia; nasal respiratory epithelium c 0/50 0/50 0/50 35/50 e

Squamous cell hyperplasia; nasal cavity c 0/50 0/50 0/50 5/50

Nuclear enlargement; nasal olfactory epithelium c 0/50 0/50 28/50 e 39/50

Respiratory metaplasia; nasal olfactory epithelium d 2/50 0/50 2/50 42/50

Atrophy; nasal olfactory epithelium d 0/50 0/50 1/50 40/50

Hydropic change; lamina propria d 0/50 0/50 0/50 46/50

Sclerosis; lamina propria d 0/50 0/50 0/50 48/50

Adhesion; nasal cavity d 0/50 0/50 0/50 46/50

Inflammation; nasal cavity d 0/50 0/50 1/50 15/50

Proliferation; nasal gland d 0/50 0/50 0/50 11/50

Hyperplasia; liver d 3/50 2/50 11/50 e 47/50

Spongiosis hepatis; liver d 0/50 0/50 1/50 20/50

Cyst formation; liver d 0/50 1/50 1/50 8/50

Acidophilic cell foci; liver c 1/50 1/50 1/50 1/50

Basophilic cell foci; liver c 23/50 27/50 31/50 8/50 e

Clear cell foci; liver c 1/50 1/50 5/50 4/50

Mixed

- cell foci; liver c 1/50 1/50 3/50 11/50 f

Nuclear enlargement; kidney proximal tubule d 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 )

.

c Data from Kano et al. ( 2009 )

. d Data from JBRC ( 1998 ) . JBRC did not report statistical significance for the ―All animals‖ comparison.

e p < 0.01 b y χ

2 test.

f p < 0.05 b y χ

2 test

.

Sources: Kano et al. ( 2009 ) and JBRC ( 1998 )

.

NOAEL and LOAEL values for rats in this study were identified by EPA as 55 and 1

274 mg /kg

- day, respectively, based on toxicity observed in nasal tissue of male rats (i.e., atrophy 2

of olfactory epithelium, adhesion, and inflammation). Metaplasia and hyperplasia of the nasal 3

epitheli um were also observed in high

- dose male and female rats. These effects are likely to be 4

associated with the formation of nasal cavity tumors in these dose groups. Nuclear enlargement 5

was observed in the nasal olfactory epithelium and the kidney proximal tubule at a dose of 6

83 mg /kg

- day in female rats; however, it is unclear whether these alterations represent adverse 7

toxicological effects. Hematological effects noted in male rats given 55 and 274 mg /kg

- day 8

(decreased RBCs, hemoglobin, hematocrit, increas ed platelets) were within 20% of control 9

values. In female rats decreases in hematological effects were observed in the high dose group 10

(429 mg /kg

- day). A reference range database for hematological effects in laboratory animals 1150

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ( Wolford et al., 1986 ) indicates that a 20% change in these parameters may fall within a normal 1

range (10th

– 90th percentile values) and may not represent a treatment

- related effect of concern. 2

Liver lesi ons were also seen at a dose of 55 mg /kg

- day in male rats; these changes are likely to 3

be associated with liver tumorigenesis. Clear and mixed

- cell foci are commonly considered 4

preneoplastic changes and would not be considered evidence of noncancer toxici ty. The nature 5

of spongiosis hepatis as a preneoplastic change is less well understood ( Bannasch, 2003 ; Karbe 6

& Kerlin, 2002 ; Stroebel, Mayer, Zerban, & Bannasch, 1995 ) . Spongiosis hepatis is a cyst

- like 7

lesion that arises from the perisinusoidal ( Ito ) cells (PSC) of the liver. It is commonly seen in 8

aging rats, but has been shown to increase in incidence following exposure to he patocarcinogens. 9

Spongiosis hepatis can be seen in combination with preneoplastic foci in the liver or with 10

hepatocellular adenoma or carcinoma and has been considered a preneoplastic lesion ( Bannasch, 11

2003 ; Stroebel, et al., 1995 ) . This change can also be associated with hepatocellular hypertrophy 12

and liver toxicity and has been regarded as a secondary effect of some liver carcinogens ( Karbe 13

& Kerlin, 2002 ) . In the case of the JBRC ( 1998 ) study, spongiosis hepatis was associated with 14

other preneoplastic changes in the liver (clear and mixed

- cell foci). No other lesions indicative 15

of liver toxi city were seen in this study; therefore, spongiosis hepatis was not considered 16

indicative of noncancer effects. Serum chemistry changes (increases in total protein, albumin, 17

and glucose; decreases in AST, ALT, LDH, and ALP, potassium, and inorganic phosph orous) 18

were observed in both male and female rats ( JBRC, 1998 ) in the high dose groups, 274 and 19

429 mg /kg

- day, respectively. These serum chemistry changes seen in terminal blood samples 20

from high

- dose male and female rats are likely related to tumor fo rmation in these dose groups. 21

Significantly increased incidences of liver tumors (adenomas and carcinomas) and tumors 22

of the nasal cavity occurred in high

- dose male and female rats ( Table s 4

- 10 and 4

- 11) treated 23

with 1,4

- dioxane for 2 years ( Kano, et al., 2009 ) . The first liver tumor was seen at 85 weeks in 24

high

- dose male rats and 73 weeks in high

- dose female rats (vs. 101

– 104 weeks in lower dose 25

groups and controls) ( Y amazaki, 2006 ) . In addition, a significant increase ( p ≤ 0.01, Fisher‘s 26

Exact test) in mesotheliomas of the peritoneum was seen in high

- dose males (28/50 versus 2/50 27

in controls). Mesotheliomas were the single largest cause of death among high

- dose m ale rats, 28

accounting for 12 of 28 pretermination deaths ( Yamazaki, 2006 ) . Also, in males, there were 29

increasing tr ends in mammary gland fibroadenoma and fibroma of the subcutis, both statistically 30

significant (

p < 0.01) by the Peto test of dose

- response trend. Females showed a significant 31

increasing trend in mammary gland adenomas ( p < 0.01 by Peto‘s test). The tumo r incidence 32

values presented in Tables 4

- 10 and 4

- 11 were not adjusted for survival. 3351

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 c avity

Squamous cell carcinoma 0/50 0/50 0/50 3/50 a 0/50 0/50 0/50 7/50 a,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 28/50 a,b 1/50 0/50 0/50 0/50

Mammary g land

Fibroadenoma 1/50 1/50 0/50 4/50 a 3/50 2/50 1/50 3/50

Adenoma 0/50 1/50 2/50 2/50 6/50 7/50 10/50 16/50 a,c

Either a denoma or f

ibroadenoma 1/50 2/50 2/50 6/50 a 8/50 8/50 11/50 18/50 a,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 )

.

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 32/50 a,b 3/50 1/50 6/50 48/50 a,b

Hepatocellular carcinoma 0/50 0/50 0/50 14/50 a,b 0/50 0/50 0/50 10/50 a,b

Either a denoma or carcinoma 3/50 4/50 7/50 39/50 a,b 3/50 1/50 6/50 48/50 a,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 )

.

For mice, growth and mortality rates were reported in Kano et al. ( 2009 ) for the duration 1

of the study. Similar to rats, the growth rates of male and female mice were slower than controls 2

and terminal body weights wer e lower for the mid (p < 0.01 for males administered 191 mg /kg

3

day and p < 0.05 for females administered 278 mg /kg

- day) and high doses (p < 0.05 for males 4

and females administered 677 and 964 mg /kg

- day, respectively). There were no differences in 5

surviva l rates between control and treated male mice; however, survival rates were significantly 6

decreased compared to controls for female mice in the mid (278 mg /kg

- day, approximately 40% 7

survival) and high (964 mg /kg

- day, approximately 20% survival) dose groups . The study 852

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE authors attributed these early female mouse deaths to the significant incidence of hepatic tumors, 1

and Kano et al. ( 2009 ) reported tumor incidence for all animals in the study (N=50), including 2

animals that became moribund or died before the end of the study. Additional d ata on survival 3

rates of mice w ere pro vided in a personal communication from Dr. Yamazaki ( 2006 ) . Dr. 4

Yamazaki reported that the survival of mice was low in all male groups (31/50, 33/50, 25/50 and 5

26/50 in control, low

- , mid

- , and high

- dose groups, respectively) and particularly low in high

6

dose females (29/50, 29/50, 17/50, and 5/50 in control, low

- , mid

- , and high

- dose groups, 7

respectively). These deaths occurred primarily during the second year of the study. Survival at 8

12 month s in male mice was 50/50, 48/50, 50/50, and 48/50 in control, low

- , mid

- , and high

- dose 9

groups, respectively. Female mouse survival at 12 mon th s was 50/50, 50/50, 48/50, and 48/50 in 10

control, low

- , mid

- , and high

- dose groups, respectively ( Yamazaki, 2006 )

. Furthermore, these 11

deaths were primarily tumor related. Liver tumors were listed as the cause of death for 31 of the 12

45 pretermination deaths in high

- dose female Crj: BDF1 mice ( Yamazaki, 2006 )

. For mice, 13

growth and mortality rates were reported in Kano et al. ( 2009 ) for the duration of the study. 14

Similar to rats, the growth rates of male and female mice were slower than controls and terminal 15

body weights were lower for the mid (p < 0.01 for males administered 191 mg /kg

- day and p < 16

0.05 for females administered 278 mg /kg

- day) and high doses (p < 0.05 for males and females 17

administered 677 and 964 mg /kg

- day, respectively). 18

Food consumption was not significantly affected, but water consumption was reduced 19

26% in high

- dose male mice and 28% in high

- dose female mice. Final BWs were reduced 43% 20

in high

- dose male mice and 15 and 45% in mid

- and high

- dose female mice, respectively. Male 21

mice showed increases in RBC counts, hemoglobin, a nd hematocrit, whereas in female mice, 22

there was a decrease in platelets in mid

- and high

- dose rats. With the exception of a 60% 23

decrease in platelets in high

- dose female mice, hematological changes were within 15% of 24

control values. Serum AST, ALT, LDH, and ALP activities were significantly increased in mid

25

and high

- dose male mice, whereas LAP and CPK were increased only in high

- dose male mice. 26

AST, ALT, LDH, and ALP activities were increased in mid

- and high

- dose female mice, but 27

CPK activity was incr eased only in high

- dose female mice. Increases in serum enzyme activities 28

ranged from less than two

- to sevenfold above control values. Glucose and triglycerides were 29

decreased in high

- dose males and in mid

- and high

- dose females. High

- dose female mice also 30

showed decreases in serum phospholipid and albumin concentrations (not reported in males). 31

Blood calcium was lower in high

- dose females and was not reported in males. Urinary pH was 32

decreased in high

- dose males, whereas urinary protein, glucose, and occult blood were increased 33

in mid

- and high

- dose female mice. Relative and absolute lung weights were increased in high

34

dose males and in mid

- and high

- dose females ( JBRC, 1998 ) . Microscopic examination of the 35

tissues for nonneoplastic lesions sho wed significant alterations in the epithelium of the 36

respiratory tract, mainly in high

- dose animals, although some changes occurred in mid

- dose mice 3753

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE (Tables 4

- 12 and 4

- 13). Commonly seen alterations included nuclear enlargement, atrophy, and 1

inflammation of the epithelium. Other notable changes observed included nuclear enlargement 2

of the proximal tubule of the kidney and angiectasis in the liver in high

- dose male mice. 3

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 epithelium c 0/50 0/50 0/50 31/50 e

Nuclear enlargement; nasal olfactory epithelium c 0/50 0/50 9/50 e 49/50 e

Atrophy; nasal olfactory epithelium d 0/50 0/50 1/50 48/50

Inflammation; nasal cavity d 1/50 2/50 1/50 25/50

Atrophy; tracheal epithelium d 0/50 0/50 0/50 42/50

Nuclear enlargement; tracheal epithelium d 0/50 0/50 0/50 17/50

Nuclear enlargement; bronchial epithelium d 0/50 0/50 0/50 41/50

Atrophy; lung/bronchial epithelium d 0/50 0/50 0/50 43/50

Accumulation of foamy cells; lung d 1/50 0/50 0/50 27/50

Angiectasis; liver d 2/50 3/50 4/50 16/50

Nuclear enlargement; kidney proximal tubule d 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 )

.

c Data from Kano et al. ( 2009 )

. d Data from JBRC ( 1998 ) . JBRC did not report statistical significance for the ―All animals‖ comparison.

e p < 0.01 b y χ

2 test.

Source s : Kano et al. ( 2009 ) and JBRC ( 1998 )

.54

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 epithelium c 0/50 0/50 0/50 41/50 e

Nuclear enlargement; nasal olfactory epithelium c 0/50 0/50 41/50 e 33/50 e

Atrophy; nasal olfactory epithelium d 0/50 0/50 1/50 42/50

Inflammation; nasal cavity d 2/50 0/50 7/50 42/50

Atrophy; tracheal epithelium d 0/50 0/50 2/50 49/50

Nuclear enlargement; bronchial epithelium d 0/50 1/50 22/50 48/50

Atrophy; lung/bronchial epithelium d 0/50 0/50 7/50 50/50

Accumulation of foamy cells; lung d 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 )

.

c Data from Kano et al. ( 2009 )

. d Data from JBRC ( 1998 ) . JBRC did not report statistical significance for the ―All animals‖ comparison.

e p < 0.01 b y χ

2 test.

Source s : Kano et al. ( 2009 ) and JBRC ( 1998 )

.

NOAEL and LOAEL values for mice in this study were identified by EPA as 66 and 1

278 mg /kg

- day, respectively, based on nasal inflammation observed in female mice. Nuclear 2

enlargement of the nasal olfactory epithelium and bronchial epithelium was also observed at a 3

dose of 278 mg /kg

- day in female mice; however, it is unclear whether these alterations represent 4

adverse toxicological effects. The serum chemistry changes seen in terminal blood samples from 5

male and female mice (mid

- and high

- dose groups) are likely related to tumor formation in these 6

animals. Liver angiectasis, an abnormal dilatation and/or lengthening of a blood or lymphatic 7

vessel, was seen in male mice given 1,4

- dioxane at a dose of 677 mg /kg

- day. 8

Treatment with 1,4

- dioxane resulted in an increase in the format ion of liver tumors 9

(adenomas and carcinomas) in male and female mice. The incidence of hepatocellular adenoma 10

was statistically increased in male mice in the mid

- dose group only. The incidence of male mice 11

with hepatocellular carcinoma or either tumor t ype (adenoma or carcinoma) was increased in the 12

low, mid, and high

- dose groups. The appearance of the first liver tumor occurred in male mice at 13

64, 74, 63, and 59 weeks in the control, low

- mid

- , and high

- dose groups, respectively 14

( Yamazaki, 2006 ) . In female mice, increased incidence was observed for hepatocellular 15

carcinoma in all treatment groups, while an increas e in hepatocellular adenoma incidence was 16

only seen in the 66 and 278 mg /kg

- day dose groups ( Table 4

- 14). The appearance of the first 17

liver tumor in female mice occurred at 95, 79, 71, and 56 weeks in the control, low

- , mid

- , and 18

high

- dose groups, respect ively ( Yamazaki, 2006 ) . The tumor incidence data presented for male 19

and female mice in Table 4

- 14 are based on rea nalyzed sample data presented in Kano et al. 2055

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ( 2009 ) that included le sions in animals that became moribund or died prior to the completion of 1

the 2

- year study. 2

Katagiri et al. ( 1998 ) summarized the incidence of hepatocellular adeno mas and 3

carcinomas in control male and female BDF1 mice from ten 2

- year bioassays at the JBRC. For 4

female mice, out of 499 control mice, the incidence rates were 4.4% for hepatocellular adenomas 5

and 2.0% for hepatocellular carcinomas. Kano et al. ( 2009 ) reported a 10% incidence rate for 6

hepatocellular adenomas and a 0% incidence rate for hepatocellular carcinomas in control female 7

BDF1

. The background incidence rates for male BDF1 mice were 15% and 22.8% for 8

hepatocellular adenomas and carcinomas, respectively, out of 500 control mice in ten 2

- year 9

bioassays ( Katagiri, et al., 1998 ) . Background rates for B6C3F 1 mice evaluated by the National 10

Toxicology Program are similar (10.3% and 21.3% for hepatocel lular adenomas and carcinomas 11

in male mice, respectively; 4.0% and 4.1% for hepatocellular adenomas and carcinomas in 12

female mice, respectively) to the BDF1 mice background rates observed by JBRC ( Haseman, 13

Huff, & Boorman, 1984 ) . Thus , the BDF1 mouse is not particularly sensitive compared to the 14

commonly used B6C3F 1 strain and indicates that the results obtained by JBRC are reasonable. 15

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 23/50 a 11/50 5/50 31/50 a 20/50 a 3/ 50

Hepatocellular carcinoma 15/50 20/50 23/50 36/50 a,b 0/50 6/50 c 30/ 50 a 45/ 50 a,b

Either hepatocellular

adenoma or carcinoma 23/50 31/50 37/50 c 40/50 a,b 5/50 35/50 a 41/ 50 a 46/ 50 a,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 )

.

A weight of evidence evaluation of the carcinogenicity studies presented in Section 16

4.2.1.2 is located in Section 4.7 and Table 4

- 1 9

. 1756

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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/gro up) were exposed 1

to 1,000, 2,000, 5,000, or 10,000 ppm of 1,4

- dioxane vapor two

- times a day for 1.5 hour s 2

(3 hour s/day) for 5 day s/week and 1.5 hour s on the 6th day (16.5 hour s/week) ( Fairley, et al., 3

1934 ) . Animals were exposed until death occurred or were sacrificed at varying time periods. 4

At the 10,000 ppm concentration, onl y one animal (rat) survived a 7

- day exposure. The rest of 5

the animals (six guinea pigs, three mice, and two rats) died within the first five exposures. 6

Severe liver and kidney damage and acute vascular congestion of the lungs were observed in 7

these anima ls. Kidney damage was described as patchy degeneration of cortical tubules with 8

vascular congestion and hemorrhage. Liver lesions varied from cloudy hepatocyte swelling to 9

large areas of necrosis. At 5,000 ppm, mortality was observed in two mice and one guinea pig 10

following 15

– 34 exposures. The remaining animals were sacrificed following 49.5 hour s 11

(3 weeks ) of exposure (three rabbits) or 94.5 hour s (5 weeks ) of exposure (three guinea pigs). 12

Liver and kidney damage in both dead and surviving animals wa s similar to that described for 13

the 10,000 ppm concentration. Animals (four rabbits, four guinea pigs, six rats, and five mice) 14

were exposed to 2,000 ppm for 45

– 102 total exposure hour s (approximately 2

– 6 weeks ). Kidney 15

and liver damage was still apparen t in animals exposed to this concentration. Animals exposed 16

to 1,000 ppm were killed at intervals with the total exposure duration ranging between 78 and 17

202.5 hour s (approximately 4

– 12 weeks ). Cortical kidney degeneration and hepatocyte 18

degeneration and liver necrosis were observed in these animals (two rabbits, three guinea pigs, 19

three rats, and four mice). The low concentration of 1,000 ppm was identified by EPA as a 20

LOAEL for liver and kidney degeneration in rats, mice, rabbits, and guinea pigs in th is study. 21

4.2.2.1.2. Kasai et al. Male and female 6

- week

- old F344/DuCrj rats (10/sex/group) were 22

exposed to nominal concentrations of 0 (clean air), 100, 200, 400, 800, 1,600, 3,200, or 6,400 23

ppm (0, 360, 72 0 , 1,4 00 , 2, 900 , 5, 800 , 1 2000 , and 23,0 00 mg/m 3

, respectively) of vaporized 24

1,4

- dioxane (>99% pure) for 6 hours/day, 5 days/week, for 13 weeks in whole body inhalation 25

chambers (Kasai et al., 2008, 195044). Each inhalation chamber housed 20 individual cages for 26

10 males and 10 females. During exposure, the concentration of 1,4

- dioxane vapor was 27

determined every 15 minutes by gas chromatography. In addition, during exposure, animals 28

received food and water ad libitum and the following data were collected: 1) clinical signs and 29

mortality (daily); 2) BW an d food intake (weekly); 3) urinary parameters using Ames reagent 30

strips (measured during week 13 of the exposure); and 4) 1,4

- dioxane content in plasma from 31

three rats of both sexes (measured on the third day of exposure during weeks 12 and 13 at 1 hour 32

po stmortem). At the end of the 13 week exposure period or at the time of an animal‘s death 33

during exposure, all organs were collected, weighed, and evaluated for macroscopic lesions. 3457

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Histopathological evaluations of organs and tissues were conducted in acco rdance with the 1

OECD test guidelines, including all tissues of the respiratory tract . Hematological and clinical 2

chemistry parameters were also measured using blood collected from the abdominal aorta of rats 3

following an overnight fasting at the end of th e 13

- week exposure period. The measured 4

hematological and clinical chemistry parameters included: red blood cell count, hemoglobin, 5

hematocrit, MCV, AST, ALT, glucose, and triglyceride. Liver sections from male and female 6

rats exposed to 800, 1,600 and 3

, 200 ppm of 1,4

- dioxane were also analyzed for foci (in the 7

absence of tumor formation) by immunohistochemical expression of glutathione S

- transferase 8

placental form (GST

- P). Statistically significant differences between 1,4

- dioxane and clean air 9

exposed groups were determined using Dunnett‘s test or χ 2 test. A p

- value of 0.05 was 10

considered the threshold for significance. 11

All rats exposed to 6,400 ppm of 1,4

- dioxane died by the end of the first week of 12

exposure; the determined cause of death was renal failure and diagnosed as necrosis of the renal 13

tubules. At concentrations lower than 6,400 ppm, mortality was not observed and all exposed 14

rats were absent of clinical signs. Exposure

- related effects on final BWs, organ weights, 15

hematology parameters, and histopathological lesions were reported as compared to controls. 16

Terminal BWs were significantly decreased in both sexes at 200 ppm (males, 6%, p <0.05; 17

female, 7%, p <0.01) and 3,200 ppm (males, 7%, p <0.01; female, 10%, p <0.01); and 18

additionally in females at 800 ppm (6%, p <0.01) and 1,600 ppm (8%, p <0.01). Statistically 19

significant increases in several organ weights were observed, including liver (≥800 ppm, both 20

sexes, p≤ 0.01 ; 800 ppm, males, p≤ 0.05), kidney (3,200 ppm

, males, p≤ 0.01; ≥800 ppm

, 21

females, p≤ 0.01), and lung (≥1,600 ppm

, males, p≤ 0.01; ≥200 ppm

, females , p≤ 0.0 5 ; 400 22

ppm, female, p≤ 0.05). Changes in hematological parameters were observed at 3,200 ppm 23

including increased levels of hemoglobin ( both sexes, p≤ 0.05), ALT ( males, p≤ 0.05; female, p≤ 24

0.01), RBC ( both sexes, p≤ 0.01), AST ( both sexes, p≤ 0.01), hematocrit ( females, p≤ 0.5)

, and 25

MCV( both sexes, p≤ 0.1)

. In males only, at 3,200 ppm, decreased levels of glucose (p≤ 0.01) 26

and triglyceride (p≤ 0.05) were observed; and in females only, at 200 ppm, an increased AST 27

level in females (p≤ 0.05) was noted . At 3,200 ppm, in exposed male rats, urinary protein was 28

slightly decreased; however, this data was not shown in this study. In plasma, a linear increase 29

in 1,4

- dioxane levels was detected at exposure concentrations of 400 ppm and above in both 30

sexes, and the highest blood levels were observ ed in females. Exposure and/or sex

- related 31

histopathology findings included nuclear enlargement of the nasal respiratory, nasal olfactory, 32

tracheal, and bronchial epithelium; vacuolic change in the olfactory and bronchial epithelium; 33

atrophy of the nasal epithelium; hydropic change in the proximal tubules of the kidney; and 34

single

- cell necrosis and centrilobular swelling in the liver (Table 4

- 15). Severit y of these 35

histopatho lo gical lesions are noted in Table 4

- 15 as well. Further microscopic evaluation of liver 3658

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE tissue revealed GST

- P positive liver foci in both sexes at 3,200 ppm (3/10 males, 2/10 females) 1

and in females at 1,600 ppm (4/10) (Table 4

- 15). 2

The study authors determined nuclear enlargement in the respiratory epithelium as the 3

most sensitive lesion and a LOAEL value of 100 ppm was identified by the study authors based 4

on the incidence data of this lesion in both male and female rats. 5

Table 4

- 15. Incidence data of histopathological lesions in F344/DuCrj rats exposed 6

to 1,4

- dioxane vapor by wh ole

- body inhalation for 13 weeks. 7

8

Males

1,4

- dioxane vapor concentration (ppm) a

Effect b 0 (clean air) 100 200 400 800 1,600 3,200

Nuclear enlargement; nasal

respiratory epithelium 0/10 7/10 c

(7, 1+) 9/10 c

(9, 1+) 7/10 c

(7, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 2+) 10/10 c

(10, 2+)

Nuclear enlargement; nasal

olfactory epithelium 0/10 0/10 5/10

(5, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 2+) 10/10 c

(10, 2+)

Nuclear enlargement; tracheal

epithelium 0/10 0/10 0/10 0/10 1/10

(1, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 1+)

Nuclear enlargement;

bronchial epithelium 0/10 0/10 0/10 0/10 0/10 9/10 c

(9, 1+) 10/10 c

(10, 1+)

Vacuolic change; olfactory

epithelium 0/10 1/10

(1, 1+) 3/10

(3, 1+) 6/10 d

(6, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 1+)

Vacuolic change; bronchial

epithelium 0/10 0/10 0/10 0/10 4/10

(4, 1+) 6/10 d

(6, 1+) 6/10 d

(6, 1+)

Atrophy; olfactory epithelium e

- - - - - - - Hepatocyte centrilobular

swelling 0/10 0/10 0/10 0/10 0/10 1/10

(1, 1+) 10/10 c

(10, 1+)

Hepatocyte single

- cell necrosis 0/10 0/10 0/10 0/10 0/10 1/10

(1, 1+) 8/10 c

(8, 1+)

Hydropic change; renal

proximal tubule e - - - - - - -

Females

1,4

- dioxane vapor concentration (ppm) a

Effect b 0 (clean air) 100 200 400 800 1,600 3,200

Nuclear enlargement; nasal

respiratory epithelium 0/10 5/10 d

(5, 1+) 9/10 c

(9, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 1+) 10/10 c

(10, 2+) 10/10 c

(10, 2+)

Nuclear enlargement; nasal

olfactory epithelium 0/10 2/10

(2, 1+) 6/10 d

(6, 1+) 10/10 c

(9, 1+;

1, 2+) 10/10 c

(10, 1+) 10/10 c

(7, 1+;

3, 2+) 10/10 c

(10, 2+)

Nuclear enlargement; tracheal

epithelium 0/10 0/10 0/10 0/10 2/10

(2, 1+) 7/10 c

(7, 1+) 10/10 c

(10, 1+)

Nuclear enlargement;

bronchial epithelium 0/10 0/10 0/10 0/10 0/10 0/10 10/10 c

(10, 1+)

Vacuolic change; olfactory

epithelium 0/10 1/10

(1, 1+) 2/10

(2, 1+) 3/10

(3, 1+) 7/10 c

(7, 1+) 9/10 c

(9, 1+) 10/10 c

(10, 1+)

Vacuolic change; bronchial

epithelium 0/10 0/10 0/10 1/10

(1, 1+) 1/10

(1, 1+) 3/10

(3, 1+) 4/10

(4, 1+)

Atrophy; olfactory epithelium 0/10 0/10 2/10

(2, 1+) 3/10

(3, 1+) 5/10 d

(5, 1+) 5/10 d

(5, 1+) 4/10

(4, 1+)

Hepatocyte centrilobular

swelling 0/10 0/10 0/10 0/10 0/10 1/10

(1, 1+) 8/10 c

(8, 1+)59

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Hepatocyte single

- cell necrosis 0/10 0/10 0/10 0/10 0/10 0/10 3/10

(3, 1+)

Hydropic change; renal

proximal tubule 0/10 0/10 0/10 0/10 0/10 0/10 6/10 d

(6, 1+)

a Data are presented for sacrificed animals.

b Values listed are the number of animals with the indicated lesion. Values in parentheses , are the number

of lesion bearing animals for a given grade of lesion severity. Severity key: 1+, slight and , 2+, moderate.

c p ≤ 0.01 by χ 2 test.

d p ≤ 0.05 by χ 2 test.

e Data were not reported for male rats.

Source: Kasai et al. ( 2008 )

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

1,4

- dioxane vapors (99.9% pure) at a concentration of 0.4 mg /L (111 ppm), were carried out 2

7 hour s/day, 5 day s/week for 2 years ( Torkelson, et al., 1974 ) . The age of the animals at the 3

beginning of the study was not provided. The concentration of 1,4

- dioxane vapor during 4

exposures was determined with infrared analyzers. Food and water were available ad libitum 5

except during exposures. Endpoints examined included clinical signs, eye and nasal irritation, 6

skin condition, respiratory distress, and tumor formation. BWs were determined weekly. 7

Standard hematological parameters were determined on all surviving anim als after 16 and 8

23 month s of exposure. Blood collected at termination was used also for determination of 9

clinical chemistry parameters (serum AST and ALP activities, blood urea nitrogen [BUN], and 10

total protein). Liver, kidneys, and spleen were weighed and the major tissues and organs were 11

processed for microscopic examination (lungs, trachea, thoracic lymph nodes, heart, liver, 12

pancreas, stomach, intestine, spleen, thyroid, mesenteric lymph nodes, kidneys, urinary bladder, 13

pituitary, adrenals, testes, o varies, oviduct, uterus, mammary gland, lacrimal gland, lymph nodes, 14

brain, vagina, and bone marrow, and any abnormal growths). Nasal tissues were not obtained for 15

histopathological evaluation. Control and experimental groups were compared statistically using 16

Student‘s t test, Yates corrected χ 2 test, or Fisher‘s Exact test. 17

Exposure to 1,4

- dioxane vapors had no significant effect on mortality or BW gain and 18

induced no signs of eye or nasal irritation or respiratory distress. Slight, but statistically 19

si gnificant, changes in hematological and clinical chemistry parameters were within the normal 20

physiological limits and were considered to be of no toxicological importance by the 21

investigators. Altered hematological parameters included decreases in packed cell volume, RBC 22

count, and hemoglobin, and an increase in WBC count in male rats. Clinical chemistry changes 23

consisted of a slight decrease in both BUN (control

— 23 ± 9.9; 111

- ppm 1,4

- dioxane

— 19.8 ± 24

8.8) and ALP activity (control

— 34.4 ± 12.1; 111

- ppm 1,4

- dioxane

— 29.9 ± 9.2) and a small 25

increase in total protein (control

— 7.5 ± 0.37; 111

- ppm 1,4

- dioxane

— 7.9 ± 0.53) in male rats 26

(values are mean ± standard deviation). Organ weights were not significantly affected. 27

Microscopic examination of organs and tissu es did not reveal any treatment

- related effects. 2860

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Based on the lack of significant effects on several endpoints, EPA identified the exposure 1

concentration of 0.4 mg /L (111 ppm) as a free standing NOAEL. The true NOAEL was likely to 2

be higher. 3

Tumors, obse rved in all groups including controls, were characteristic of the rat strain 4

used and were considered unrelated to 1,4

- dioxane inhalation. The most common tumors were 5

reticulum cell sarcomas and mammary tumors. Using Fisher‘s Exact test and a significanc e level 6

of p < 0.05, no one type of tumor occurred more frequently in treated rats than in controls. No 7

hepatic or nasal cavity tumors were seen in any rat. 8

4.2.2.2.2. Kasai et al. Groups of male 6

- week

- old F344/DuCrj rats (50/group) weighing 120 ± 9

5g (mean ± SD) at the beginning of the study were exposed via inhalation to nominal 10

concentrations of 0 (clean air), 50, 250, and 1,250 ppm (0, 180, 90 0 , and 4,50 0 mg/m 3

, 11

respectively) of vaporized 1,4

- dioxane (>99% pure) for 6 hours/day, 5 days/week, for 104 weeks 12

(2 years) in whole body inhalation chambers ( K asai, et al., 2009 )

. Each inhalation chamber 13

housed male rats individually in stainless

- steel wire hanging cages. The authors stated female 14

counterparts were not exposed given data illustrating the absence of induced mesotheliomas 15

following exposure t o 1,4

- dioxane in drinking water ( Yamazaki, et al., 1994 ) . During exposure, 16

the concentration of 1,4

- dioxane vapor was determined every 15 minutes by gas chromatography 17

and animals received food and water ad libitum. In addition, during the 2

- year exposure period, 18

cl inical signs and mortality were recorded daily. BW and food intake were measured once 19

weekly for the first 14 weeks of exposure, and thereafter, every 4 weeks. At the end of the 2

- 20

year exposure period or at the time of an animal‘s death during exposure, all organs were 21

collect ed, weighed, and evaluated for macroscopic lesions. Additional examinations were 22

completed on rats sacrificed at the end of the 2

- year exposure period. Endpoints examined 23

included: 1) histopathological evaluations of organs and tis sues outlined in the OECD test 24

guideline which included all tissues of the respiratory tract; 2) mea surement of urinary 25

parameters using Ames reagent strips during the last week of the exposure period; and 3) 26

measurement of hematological parameters using blood collected from the abdominal aorta of rats 27

following an overnight fasting at the end of the 2

- year exposure period. Organs and tissues 28

collected for histopathological examination were fixed in 10% neutral buffered formalin with the 29

exception of nasal cavity samples. Nasal tissue was trimmed transversely at three levels after 30

decalcification and fixation in a formic acid

- forma lin solution. The levels were demarcated at 31

the following points: at the posterior edge of the upper incisor teeth (level 1), at the incisive 32

papilla (level 2), and at the anterior edge of the upper molar teeth (level 3). All tissue samples 33

were embedded in paraffin, and then sectioned (at 5 μm thickness) and stained with hematoxylin 34

and eosin (H&E). For measured hematological parameters, analyses included: red blood cell 35

count, hemoglobin, hematocrit, MCV, mean corpuscular hemoglobin (MCH), AST, ALT, ALP

, 36

and γ

- GTP. Dunnett‘s test, χ 2 test, and Fisher‘s exact test were used to determine statistical 3761

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE differences between 1,4

- dioxane exposed and clean air exposed group data. A p

- value of 0.05 1

was considered the threshold for significance. 2

Growth rates and s urvival rates were analyzed. Growth rates were not significantly 3

affected by 1,4

- dioxane exposures, but a decreasing trend in growth was observed during the 4

latter half of the 2

- year exposure period for all exposure doses (i.e., 50, 250, and 1

, 250 ppm)

. 5

S urvival rates were significantly decreased following 91 weeks of exposure to 1

, 250 ppm of 6

1,4

- dioxane. The authors attributed these deaths to increased incidences of peritoneal 7

mesotheliomas, but also noted that nasal tumors could be a contributing factor. Terminal 8

survival rates were 37/50, 37/50, 29/50, and 25/50 for 0, 50, 250, and 1,250 ppm exposed groups, 9

respectively. Statistically significant changes in body and organ weights were also observed. 10

Following exposure to 1,250 ppm of 1,4

- dioxane, term inal body weights of rats were 6% less 11

than the control (p≤ 0.05) and relative liver and lung weights of rats were 27% (p≤ 0.01), and 2% 12

greater than the control, respectively. It is of note that the observed change in terminal body 13

weight was not an effe ct of food consumption , which was determined to be unaltered by the 14

study authors. 15

Deformity in the nose was the only clinical sign reported in this study. This deformity 16

was seen at exposure weeks 74 and 79 in one rat each, exposed to 250 ppm and 1,250 ppm of 17

1,4

- dioxane, respectively. Both of these rats did not survive the 2

- year exposure with deaths 18

caused by malignant nasal tumors. Altered hematological parameters were observed with 19

significant changes at 1,250 ppm. Altered endpoints included decrea sed hemoglobin (p≤ 0.05), 20

MCV (p≤ 0.05), and MCH (p≤ 0.01) and increased AST (p≤ 0.01), ALT (p≤ 0.01), ALP (p≤ 21

0.01), and γ

- GTP (p≤ 0.01) levels. In addition, urine pH was decreased in 1,250 ppm exposed 22

rats (p≤ 0.05). 23

Histopathology findings of pre

- an d nonneoplastic lesions associated with 1,4

- dioxane 24

treatment were seen in the nasal cavity, liver, and kidneys (Table 4

- 16). At the highest 25

concentration of 1,250 ppm, all pre

- and nonneoplastic lesions were significantly increased, as 26

compared to contro ls, with the exception of clear and mixed cell foci in the liver. At the lowest 27

concentration of 50 ppm, n uclear enlargement of the respiratory epithelium was the most 28

sensitive lesion observed in the nasal cavity. Based on this finding

, the study authors identified a 29

LOAEL of 50 ppm in male rats. 30

Tumor development was observed in the nasal cavity (squamous cell carcinoma), liver 31

(hepatocellular adenoma and carcinoma), peritoneum (peritoneal mesothelioma ) , kidney (renal 32

cell carcinoma), mammary gland (fib roadenoma and adenoma), Zymbal gland (adenoma), and 33

subcutaneous tissue (subcutis fibroma). Tumor incidences with a dose

- dependent, statistically 34

significant positive trend (Peto‘s test) included nasal squamous cell carcinoma (p≤ 0.01), 35

hepatocellular adenoma (p≤ 0.01), peritoneal mesothelioma (p≤ 0.01), mammary gland 36

fibroadenoma (p≤ 0.05), and Zymbal gland adenoma (p≤ 0.01). Renal cell carcinoma was also 3762

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE identified as statistically sign ificant with a positive dose

- dependent trend (p≤ 0.01); however, no 1

tumor incidences were reported at 50 and 250 ppm. At 1,250 ppm, significant increases in nasal 2

squamous cell carcinoma, hepatocellular adenoma, and peritoneal mesothelioma were observed. 3

At 250 ppm, significant increases in peritoneum mesothelioma and subcutis fibroma were 4

observed. Table 4

- 17 presents a summary of tumor incidences found in this study. Further 5

characterizations of neoplasms revealed nasal squamous cell carcinoma occurred at the dorsal 6

area of the nose (levels 1

- 3) marked by keratinization and the progression of growth into 7

surrounding tissue. Peritoneal mesotheliomas were characterized by complex branching 8

structures originating from the mesothelium of the scrotal sac. I nvasive growth into surrounding 9

tissues was occasionally observed for peritoneal mesotheliomas. 10

Table 4

- 16. Incidence of pre

- and nonneoplastic lesions in male F344/DuCrj

rats exposed to 1,4

- dioxane vapor by whole

- body inhalation for 2 years.

Effect 1,4

- dioxane vapor concentration (ppm)

0 (clean air) 50 250 1,250

Nuclear enlargement; nasal respiratory epithelium 0/50 50/50 a 48/50 a 38/50 a

Squamous cell metaplasia; nasal respiratory epithelium 0/50 0/50 7/50 b 44/50 a

Squamous cell hyperplasia; nasal respiratory epithelium 0/50 0/50 1/50 10/50 a

Inflammation; nasal respiratory epithelium 13/50 9/50 7/50 39/50 a

Nuclear enlargement; nasal olfactory epithelium 0/50 48/50 a 48/50 a 45/50 a

Respiratory metaplasia; nasal olfactory epithelium 11/50 34/50 a 49/50 a 48/50 a

Atrophy; nasal olfactory epithelium 0/50 40/50 a 47/50 a 48/50 a

Inflammation; nasal olfactory epithelium 0/50 2/50 32/50 a 34/50 a

Hydropic change; lamina propria 0/50 2/50 36/50 a 49/50 a

Sclerosis; lamina propria 0/50 0/50 22/50 a 40/50 a

Proliferation; nasal gland 0/50 1/50 0/50 6/50 b

Nuclear enlargement; liver centrilobular 0/50 0/50 1/50 30/50 a

Necrosis; liver centrilobular 1/50 3/50 6/50 12/50 a

Spongiosis hepatis; liver 7/50 6/50 13/50 19/50 a

Clear cell foci; liver 15/50 17/50 20/50 23/50

Basophilic cell foci; liver 17/50 20/50 15/50 44/50 a

Acidophilic cell foci; liver 5/50 10/50 12/50 25/50 a

Mixed

- cell foci; liver 5/50 3/50 4/50 14/50

Nuclear enlargement; kidney proximal tubule 0/50 1/50 20/50 a 47/50 a

Hydropic change; kidney proximal tubule 0/50 0/50 5/50 6/50 a

a p≤ 0.01 by Fisher‘s exact test.

b p≤ 0.05 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.63

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 17. Incidence of tumors in male F344/DuCrj rats exposed to 1,4

- dioxane vapor by whole

- body inhalation for 2 years.

Effect 1,4

- dioxane vapor concentration (ppm)

0 (clean air) 50 250 1,250

Nasal squamous cell carcinoma 0/50 0/50 1/50 6/50 b,c

Hepatocellular adenoma 1/50 2/50 3/50 21/50 a,c

Hepatocellular carcinoma 0/50 0/50 1/50 2/50

Renal cell carcinoma 0/50 0/50 0/50 4/50

Peritoneal mesothelioma 2/50 4/50 14/50 a 41/50 a,c

Mammary gland fibroadenoma 1/50 2/50 3/50 5/50 d

Mammary gland adenoma 0/50 0/50 0/50 1/50

Zymbal gland adenoma 0/50 0/50 0/50 4/50 c

Subcutis fibroma 1/50 4/50 9/50 a 5/50

a p≤ 0.01 by Fisher‘s exact test.

b p≤ 0.05 by Fisher‘s exact test.

c p≤ 0.01 by Peto‘s test for dose

- related trend.

d p≤ 0.05 by Peto‘s test for dose

- related trend.

Source: Kasai et al. ( 2009 )

.

4.2.3. Initiation/Promotion Studies

4.2.3.1. Bull et al.

Bull et al. ( 1986 ) tested 1,4

- dioxane as a cancer initiator in mice using oral, 1

subcutaneous, and topical routes of exposure. A group of 40 female SENCAR mice (6

– 8 weeks 2

old) was administered a single dose of 1,000 mg /kg 1,4

- dioxane (purity >99%) by gavage, 3

subcutaneous injection, or topical administration (vehicle was not specified). A group of rats 4

was used as a vehicle control (number of animals not specifi ed). Food and water were provided 5

ad libitum. Two weeks after administration of 1,4

- dioxane, 12

- O

- tetradecanoylphorbol

- 13

- 6

acetate (TPA) (1.0 μg in 0.2 mL of acetone) was applied to the shaved back of mice 7

3 times/week for a period of 20 weeks . The yield of papillomas at 24 weeks was selected as a 8

potential predictor of carcinoma yields at 52 weeks following the start of the promotion 9

schedule. Acetone was used instead of TPA in an additional group of 20 mice in order to 10

determine whether a single dose o f 1,4

- dioxane could induce tumors in the absence of TPA 11

promotion. 12

1,4

- Dioxane did not increase the formation of papillomas compared to mice initiated with 13

vehicle and promoted with TPA, indicating lack of initiating activity under the conditions of the 14

st udy. Negative results were obtained for all three exposure routes. A single dose of 15

1,4

- dioxane did not induce tumors in the absence of TPA promotion. 1664

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.2.3.2. King et al.

1,4

- Dioxane was evaluated for complete carcinogenicity and tumor promotion activity in 1

mou se skin ( King, Shefner, & Bates, 1973 ) . In the complete carcinogenicity study, 0.2 mL of a 2

solution of 1,4

- dioxane (purity not specified) in acetone was applied to the shaved skin of the 3

back of Swiss Webster mice (30/sex) 3 times/week for 78 weeks . Acetone was applied to the 4

backs of control mice (30/sex) for the same time period. In the promotion study, each animal 5

was treated with 50 μg of dimethylbenzanthracene 1 week prior to the topical application of the 6

1,4

- dioxane solution described above (0.2 mL, 3 times/week, 78 weeks ) (30 mice/sex). Acetone 7

vehicle was used in negative control mice (30/sex). Croton oil was used as a positive control in 8

the promotion study (30/sex). Weekly counts of papillomas and suspect carcinomas were made 9

by gross examination. 1,4

- Dioxane was also administered in the drinking water (0.5 and 1%) to 10

groups of Osborne

- Mendel rats (35/sex/group) and B6C3F 1 mice for 42 weeks (control findings 11

were only reported for 34 weeks ). 12

1,4

- Dioxane was negative in the complete sk in carcinogenicity test using dermal 13

exposure. One treated female mouse had malignant lymphoma; however, no papillomas were 14

observed in male or female mice by 60 weeks . Neoplastic lesions of the skin, lungs, and kidney 15

were observed in mice given the pro motional treatment with 1,4

- dioxane. In addition, the 16

percentage of mice with skin tumors increased sharply after approximately 10 weeks of 17

promotion treatment. Significant mortality was observed when 1,4

- dioxane was administered as 18

a promoter (only 4 ma le and 5 female mice survived for 60 weeks ), but not as a complete 19

carcinogen (22 male and 25 female mice survived until 60 weeks ). The survival of acetone

20

treated control mice in the promotion study was not affected (29 male and 26 female mice 21

survived u ntil 60 weeks ); however, the mice treated with croton oil as a positive control 22

experienced significant mortality (0 male and 1 female mouse survived for 60 weeks ). The 23

incidence of mice with papillomas was similar for croton oil and 1,4

- dioxane; however, the 24

tumor multiplicity (i.e., number of tumors/mouse) was higher for the croton oil treatment. 25

Oral administration of 1,4

- dioxane in drinking water caused appreciable mortality in rats, 26

but not mice, and increased weight gain in surviving rats and male mi ce. Histopathological 27

lesions (i.e., unspecified liver and kidney effects) were also reported in exposed male and female 28

rats; however, no histopathological changes were indicated for mice. 29

1,4

- Dioxane was demonstrated to be a tumor promoter, but not a co mplete carcinogen in 30

mouse skin, in this study. Topical administration for 78 weeks following initiation with 31

dimethylbenzanthracene caused an increase in the incidence and multiplicity of skin tumors in 32

mice. Tumors were also observed at remote sites (i .e., kidney and lung), and survival was 33

affected. Topical application of 1,4

- dioxane for 60 weeks in the absence of the initiating 34

treatment produced no effects on skin tumor formation or mortality in mice. 3565

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.2.3.3. Lundberg et al.

Lundberg et al. ( 1987 ) eva luated the tumor promoting activity of 1,4

- dioxane in rat liver. 1

Male Sprague Dawley rats (8/dose group, 19 for control group) weighing 200 g underwent a 2

partial hepatectomy followed 24 hour s later by an i.p. injection of 30 mg /kg diethylnitrosamine 3

(DEN) (initiation treatment). 1,4

- Dioxane (99.5% pure with 25 ppm butylated hydroxytoluene 4

as a stabilizer) was then administered daily by gavage (in saline vehicle) at doses of 0, 100, or 5

1,000 mg /kg

- day, 5 day s/week for 7 weeks . Control rats were administered saline daily by 6

gavage, following DEN initiation. 1,4

- Dioxane was also administered to groups of rats that were 7

not given the DEN initiating treatment (saline used instead of DEN). Ten day s after the last 8

dose, animals w ere sacrificed and liver sections were stained for GGT. The number and total 9

volume of GGT

- positive foci were determined. 10

1,4

- Dioxane did not increase the number or volume of GGT

- foci in rats that were not 11

given the DEN initiation treatment. The high dos e of 1,4

- dioxane (1,000 mg /kg

- day) given as a 12

promoting treatment (i.e., following DEN injection) produced an increase in the number of 13

GGT

- positive foci and the total foci volume. Histopathological changes were noted in the livers 14

of high

- dose rats. Enl arged, foamy hepatocytes were observed in the midzonal region of the 15

liver, with the foamy appearance due to the presence of numerous fat

- containing cytoplasmic 16

vacuoles. These results suggest that cytotoxic doses of 1,4

- dioxane may be associated with 17

tum or promotion of 1,4

- dioxane in rat liver. 18

4.3. REPRODUCTIVE/DEVELOP MENTAL 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 19

(99% pure, 0.7% acetal) by gavage in water at concentrations of 0, 0.25, 0.5, or 1 mL/kg

- day, 20

corresponding to dose estimates of 0, 250, 500, or 1,000 mg /kg

- day (density of 1,4

- dioxane is 21

approximately 1.03 g/mL) ( Giavini, Vismara, & Broccia, 1985 ) . The chemical was administered 22

at a constant volume of 3 mL/kg on day s 6

– 15 of gestat ion. Food consumption was determined 23

daily and BWs were measured every 3 day s. The dams were sacrificed with chloroform on 24

gestation day 21 and the numbers of corpora lutea, implantations, resorptions, and live fetuses 25

were recorded. Fetuses were weighe d and examined for external malformations prior to the 26

evaluation of visceral and skeletal malformations (Wilson‘s free

- hand section method and 27

staining with Alizarin red) and a determination of the degree of ossification. 28

Maternal weight gain was reduced by 10% in the high

- dose group (1,000 mg /kg

- day). 29

Food consumption for this group was 5% lower during the dosing period, but exceeded control 30

levels for the remainder of the study. No change from control was observed in the number of 31

implantations, live f etuses, or resorptions; however, fetal birth weight was 5% lower in the 3266

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE highest dose group (

p < 0.01). 1,4

- Dioxane exposure did not increase the frequency of major 1

malformations or minor anomalies and variants. Ossification of the sternebrae was reduced in 2

the 1,000 mg /kg

- day dose group ( p < 0.05). The study authors suggested that the observed delay 3

in sternebrae ossification combined with the decrease in fetal birth weight indicated a 4

developmental delay related to 1,4

- dioxane treatment. NOAEL and LOAE L values of 500 and 5

1,000 mg /kg

- day were identified from this study by EPA and based on delayed ossification of 6

the sternebrae and reduced fetal BWs. 7

4.4. OTHER DURATION OR EN DPOINT

- SPECIFIC STUDIES

4.4.1. Acute and Short

- term Toxicity

The acute (≤ 24 hour s) and shor t

- term toxicity studies (<30 day s) of 1,4

- dioxane in 8

laboratory animals are summarized in Table 4

- 18 . Several exposure routes were employed in 9

these studies, including dermal application, drinking water exposure, gavage, vapor inhalation, 10

and i.v. or i.p. injection. 11

4.4.1.1. Oral Toxicity

Mortality was observed in many acute high

- dose studies, and LD50 values f or 12

1,4

- dioxane were calculated for rats, mice, and guinea pigs ( Laug, Calvery, Morris, & Woodard, 13

1939 ; Pozzani, Weil, & Carpenter, 1959 ; Smyth Hf Jr, Seaton, & Fischer, 1941 ) . Clinical signs 14

of CNS depression were observed, including staggered gait, narcosis, paralysis, coma, and death 15

( de Navasquez, 1935 ; Laug, et al., 1939 ; Nelson, 1951 ; Schrenk & Yant, 1936 ) . Severe liver and 16

kidney degeneration and necrosis were often seen in acute studies ( David, 1964 ; de Navasquez, 17

1935 ; JBRC, 1998 ; Kesten, Mulinos, & Pomerantz, 1939 ; Laug, et al., 1939 ; Schrenk & Yant, 18

1936 ) . JBRC ( 1998 ) additionally reported histopathological lesions in the nasal cavity and the 19

brain of rats following 2 weeks of exposure to 1,4

- dioxane in the drinking water. 20

4.4.1.2. Inhalation Toxicity

Acute and short

- term toxicity studies (all routes) are summarized in Table 4

- 18

. 21

Mortality occurred in many high

- concentration studies ( Nelson, 1951 ; Pozzani, et al., 1959 ; 22

Wirth & Klimme r, 1936 ) . Inhalation of 1,4

- dioxane cau sed eye and nasal irritation, altered 23

respiration, and pulmonary edema and congestion ( Yant, et al., 1930 ) . Clinical signs of CNS 24

depression were observed, including staggered gait, narcosis, paralysis, coma, and death ( Nelson, 25

1951 ; Wirth & Klimmer, 1936 ) . Liver and kidney degeneration and necrosis were also seen in 26

acute and short

- term inhalation studies ( Drew, Patel, & Lin, 1978 ; Fairley, et al., 1934 )

. 2767

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 18

. Acute and short

- term toxicity studies of 1,4

- dioxane

Animal Exposure route Test conditions Results Dose a Reference

Oral studies

Rat (inbred strain

and gender

unspecified) Oral via

drinking water 1

– 10 day s of

exposure Ultrastructural

changes in the

kidney, degenerative

nephrosis, hyaline

droplet accumulation,

crystal formation in

mitochondria 11,000 mg /kg

- day

(5%) David ( 1964 )

Rat (strain and

gender unspecified) Oral via

drinking water 5

– 12 day s of

exposure Extensive

degeneration of the

kidney, liver damage,

mortality in

8/10 animals by

12 day s 11,000 mg /kg

- day

(5%) Kesten et al.

( 1939 )

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 )

Female

Sprague Dawley rat Gavage 0, 168, 840, 2550,

or 4,200 mg

/kg by

gavage, 21 and

4 hour s prior to

sacrifice Increased ODC

activity, hepatic

CYP450 content, and

DNA single

- strand

breaks 840 mg /kg (ODC

activity only) Kitchin and

Brown ( 1990 )

Female Carworth

Farms

- Nelson rat Gavage Determination of a

single dose LD 50 Lethality LD 50 = 6,400 mg /kg

(14,200 ppm) Pozzani et al.

( 1959 )

Male Wistar rat,

guinea pig Gavage Single dose,

LD 50 determination Lethality LD 50 (mg/kg):

rat = 7,120

guinea pig = 3,150 Smyth et al.

( 1941 )

Rat, mouse, guinea

pig Gavage Single dose;

several dose

groups Clinical signs of CNS

depression, stomach

hemorrhage, kidney

enlargement, and

liver and kidney

degeneration LD 50 (mg/kg):

mouse = 5,900

rat = 5,400

guinea pig = 4,030 Laug et al.

( 1939 )

Rabbi t 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 )

Rat, rabbit Gavage Single dose;

mortality after

2 weeks Mortality and

narcosis 3,160 mg /kg Nelson

( 1951 )68

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Animal Exposure route Test conditions Results Dose a Reference

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 )

Dog Drinking water

ingestion 3

– 10 day s of

exposure Clinical signs of CNS

depression, and liver

and kidney

degeneration 11,000 mg /kg

- day

(5%) Schrenk and

Yant ( 1936 )

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 )

Rat Vapor

inhalation 5 hour s of

exposure Mortality and

narcosis 6,000 ppm Nelson

( 1951 )

Female Carworth

Farms

- Nelson rat Vapor

inhalation Determination of a

4

- hour inhalation

LC 50 Lethality LC 50 = 51.3 mg /L Pozzani et al.

( 1959 )

Mouse, cat Vapor

inhalation 8 hour s/day for

17 day s Paralysis and death 8,400 ppm Wirth and

Klimmer

( 1936 )

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 )

Rabbit, guinea pig,

rat, mouse Vapor

inhalation 3 hour s exposure,

for 5 day s;

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 )

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 )

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 )69

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Animal Exposure route Test conditions Results Dose a Reference

Female

Sprague Dawley rat i.p. injection Single dose;

LD 50 values

determined

24 hour s and

14 day s after

injection Increased serum SDH

activity at 1/16th of

the LD 50 dose; no

change at higher or

lower doses LD 50 (mg/kg):

24 hour s = 4,848

14 day s = 799 Lundberg et

al. ( 1986 )

CBA/J mouse i.p. injection Daily injection for

7 day s, 0, 0.1, 1, 5,

and 10% Slightly lower

lymphocyte response

to mitogens 2,000 mg /kg

- day

(10%) Thurman et

al. ( 1978 )

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 1

following high dose exposure to 1,4

- dioxane (see Sections 4.1 and 4.2.1.1). Neurological 2

symptoms were reported in the fatal case of a worker exposed to high concentratio ns of 3

1,4

- dioxane through both inhalation and dermal exposure ( Johnstone, 1959 ) . These symptoms 4

included headache, elevation in blood pressure, agitation and restlessness, and coma. Autopsy 5

findings demonstrated perivascular widening in the br ain, with small foci of demyelination in 6

several regions (e.g., cortex, basal nuclei). It was suggested that these neurological changes may 7

have been secondary to anoxia and cerebral edema. In laboratory animals, the neurological 8

effects of acute high

- do se exposure included staggered gait, narcosis, paralysis, coma, and death 9

( de Navasquez, 1935 ; Laug, et al., 1939 ; Nelson, 1951 ; Schrenk & Yant, 1936 ; Yant, et al., 10

1930 )

. The neurotoxicity of 1,4

- dioxane was further investigated in several studies described 11

below ( Frantik, Hornychova, & Horvath, 1994 ; Goldberg, Johnson, Pozzani, & Smyth, 1964 ; 12

Kanada, Miyagawa, Sa to, Hasegawa, & Honma, 1994 ; Knoefel, 1935 )

. 13

4.4.2.1. Frantik et al.

The acute neurotoxicity of 1,4

- dioxane was evaluated following a 4

- hour inhalation 14

exposure to male Wistar rats (four per dose group) and a 2

- hour inhalation exposure to female 15

H

- strain mice (eight per dose group) ( Frantik, et al., 1994 ) . Three exposure groups and a control 16

group were used in this study. Exposure concentrations were not specified, but apparently were 17

chosen from the lin ear portion of the concentration

- effect curve. The neurotoxicity endpoint 18

measured in this study was the inhibition of the propagation and maintenance of an electrically

19

evoked seizure discharge. This endpoint has been correlated with the behavioral effe cts and 20

narcosis that occur following acute exposure to higher concentrations of organic solvents. 21

Immediately following 1,4

- dioxane exposure, a short electrical impulse was applied through ear 22

electrodes (0.2 seconds, 50 hertz (Hz), 180 volts (V) in rats, 90 V in mice). Several time 23

characteristics of the response were recorded; the most sensitive and reproducible measures of 2470

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE chemically

- induced effects were determined to be the duration of tonic hind limb extension in 1

rats and the velocity of tonic extension in mice. 2

Linear regression analysis of the concentration

- effect data was used to calculate an 3

isoeffective air concentrat ion that corresponds to the concentration producing a 30% decrease in 4

the maximal response to an electrically

- evoked seizure. The isoeffective air concentrations for 5

1,4

- dioxane were 1,860 ± 200 ppm in rats and 2,400 ± 420 ppm in mice. A NOAEL value was 6

not identified from this study. 7

4.4.2.2. Goldberg et al.

Goldberg et al. ( 1964 ) evaluated the effect of solvent inhalation on pole climb 8

performance in rats. Female rats (Carworth Farms Elias strain) (eight per dose group) were 9

exposed to 0, 1,500, 3,000, or 6,000 ppm of 1,4

- dioxane in air for 4 hour s/day, 5 day s/weeks, for 10

10 exposure day s. Conditioned avoidance and escape behaviors were evaluated using a pole 11

climb methodology. Prior to exposure, rats were trained to respond to a buzze r or shock stimulus 12

by using avoidance/escape behavior within 2 seconds. Behavioral criteria were the abolishment 13

or significant deferment (>6 seconds) of the avoidance response (conditioned or buzzer response) 14

or the escape response (buzzer plus shock re sponse). Behavioral tests were administered on day 15

1, 2, 3, 4, 5, and 10 of the exposure period. Rat BWs were also measured on test day s. 16

1,4

- Dioxane exposure produced a dose

- related effect on conditioned avoidance behavior 17

in female rats, while escape behavior was generally not affected. In the 1,500 ppm group, only 18

one of eight rats had a decreased avoidance response, and this only occurred on day s 2 and 5 of 19

exposure. A larger number of rats exposed to 3,000 ppm (two or three of eight) experienced a 20

decrease in the avoidance response, and this response was observed on each day of the exposure 21

period. The maximal decrease in the avoidance response was observed in the 6,000 ppm group 22

during the first 2 day s of exposure (75

– 100% of the animals were inh ibited in this response). For 23

exposure day s 3

– 10, the percent of rats in the 6,000 ppm group with significant inhibition of the 24

avoidance response ranged from 37

– 62%. At the end of the exposure period (day 10), the BWs 25

for rats in the high exposure group were lower than controls. 26

4.4.2.3. Kanada et al.

Kanada et al. evaluated the effect of oral exposure to 1,4

- dioxane on the regional 27

neurochemistry of the rat brain ( Kanada, et al., 1994 )

. 1,4

- Dioxane was administered by gavage 28

to male Sprague Dawley rats (5/group) at a dose of 1,050 mg /kg, approximately equal to one

29

fourth the oral LD50. Rats were sacrificed by microwave irradiation to the head 2 hour s after 30

dosing, and brains were dissected into small brain areas. Each brain region was analyzed for the 31

content of biogenic amine neurotransmitters and their metabolites using high

- performance liquid 32

chromatography (HPLC) o r GC methods. 1,4

- Dioxane exposure was shown to reduce the 33

dopamine and serotonin content of the hypothalamus. The neurochemical profile of all other 34

brain regions in exposed rats was similar to control rats. 3571

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.4.2.4. Knoefel

The narcotic potency of 1,4

- dioxane was evaluated following i.p. injection in rats and 1

gavage administration in rabbits ( Knoefel, 1935 ) . Rats were given i.p. doses of 20, 30, or 2

50 mmol/kg. No narcotic effect was seen at the lowest dose; however, rats given 30 mmol/kg 3

were observed to sleep approximately 8

– 10 minutes . Rats given the high dose of 50 mmol/kg 4

died during the study. Rabbits were given 1,4

- dioxane at oral doses of 10, 20, 50, 75, or 5

100 mmol/kg. No effect on the normal erect animal posture was observed in rabbits treated with 6

less than 50 mmol/kg. At 5 0 and 75 mmol/kg, a semi

- erect or staggering posture was observed; 7

lethality occurred at both the 75 and 100 mmol/kg doses. 8

4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUP PORT OF THE MODE

OF ACTION

4.5.1. Genotoxicity

The genotoxicity data for 1,4

- dioxane are presente d in Table s 4

- 19 and 4

- 20 for in vitro 9

and in vivo tests, respectively

. 1,4

- Dioxane has been tested for genotoxic potential using in vitro 10

assay systems with prokaryotic organisms, non

- mammalian eukaryotic organisms, and 11

mammalian cells, and in vivo assay systems using several strains of rats and mice. In the large 12

majority of in vitro systems, 1,4

- dioxane was not genotoxic. Where a positive genotoxic 13

response was observed, it was generally observed in the presence of toxicity. Similarly, 14

1,4

- dioxane wa s not genotoxic in the majority of available in vivo studies. 1,4

- Dioxane did not 15

bind covalently to DNA in a single study with calf thymus DNA. Several investigators have 16

reported that 1,4

- dioxane caused increased DNA synthesis indicative of cell prolif eration. 17

Overall, the available literature indicates that 1,4

- dioxane is nongenotoxic or weakly genotoxic. 18

Negative findings were reported for mutagenicity in in vitro assays with the prokaryotic 19

organisms Salmonella typhimurium

, Escherichia coli , and Pho tobacterium phosphoreum 20

(Mutatox assay) ( Haworth, Lawlor, Mortelmans, Sp eck, & Zeiger, 1983 ; Hellmér & Bolcsfoldi, 21

1992 ; Khudoley, Mizgireuv, & Pliss, 1987 ; Kwan, Dutka, Rao, & Liu, 1990 ; Morita & Hayashi, 22

1998 ; Nestmann, Otson, Kowbel, Bothwell, & Harrington, 1984 ; Stott, et al. , 1981 ) . In in vitro 23

assays with nonmammalian eukaryotic organisms, negative results were obtained for the 24

induction of aneuploidy in yeast ( Saccharomyces ce revisiae ) and in the sex

- linked recessive 25

lethal test in Drosophila melanogaster ( Yoon, Mason, Valenc ia, Woodruff, & Zimmering, 1985 ; 26

Zimmermann, Mayer, Scheel, & Resnick, 1985 ) . In the presence of toxicity, positive results 27

were reported for meiotic nondisjunction in Drosophila ( Munoz & Barnett, 2002 )

. 28

The ability of 1,4

- dioxane to induce genotoxic effects in mammalian cells in vitro has 29

been examined in model test systems with and without exogenous metabolic activation and in 30

hepatocytes that retain their xenobiotic

- metabolizing capabilities. 1,4

- Dioxane was reported as 31

negative in the mouse lymphoma cell forward mutation assay ( McGregor et al., 1991 ; Morita & 3272

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Hayashi, 1998 )

. 1,4

- Dioxane did not produce chromosomal aberrations or micronucleus 1

formation in Chinese hamster ovary (CHO) cells ( Galloway et al., 1987 ; Morita & Hayashi, 2

1998 ) . Results were negative in one assay for sister chromatid exchange (SCE) in CHO ( Morita 3

& Hayashi, 1998 ) and were weakly positive in the absence of metabolic activation in another 4

( Galloway, et al., 1987 ) . In rat hepatocytes, 1,4

- dioxane exposure in vitro caused single

- strand 5

breaks in DNA at concentrations also toxic to the hepatocytes ( Sina, Bean, Dysart, Taylor, & 6

Bradley, 1983 ) and produced a positive genotoxic response in a cell transformation assay with 7

BALB/3T3 cells also in the presence of toxicity ( Sheu, Moreland, Lee, & Dunkel, 1988 )

. 8

1,4

- Dioxane was not genotoxic in the majority of a vailable in vivo mammalian assays. 9

Studies of micronucleus formation following in vivo exposure to 1,4

- dioxane produced mostly 10

negative results, including studies of bone marrow micronucleus formation in B6C3F 1 , BALB/c, 11

CBA, and C57BL6 mice ( McFee, Abbott, Gulati, & Shelby, 1994 ; Mirkova, 1994 ; Tinwell & 12

Ashby, 1994 ) and micronucleus formation in peripheral blood of CD1 mice ( Morita, 1994 ; 13

Morita & Hayashi, 1998 ) . Mirkova ( 1994 ) reported a dose

- related increase in the incidence of 14

bone marrow micronuclei in male and female C5 7BL6 mice 24 or 48 hour s after administration 15

of 1,4

- dioxane. At a sampling time of 24 hour s, a dose of 450 mg /kg produced no change 16

relative to control, while doses of 900, 1,800, and 3,600 mg /kg increased the incidence of bone 17

marrow micronuclei by appr oximately two

- , three

- , and fourfold, respectively. A dose of 18

5,000 mg /kg also increased the incidence of micronuclei by approximately fourfold at 48 hour s. 19

This compares with the negative results for BALB/c male mice tested in the same study at a dose 20

o f 5,000 mg /kg and sampling time of 24 hour s. Tinwell and Ashby ( 1994 ) could not explain the 21

difference in response in the mouse bone marrow micronucleus assay with C57BL6 mice 22

obtained in their laboratory (i.e., non

- significant 1.6

- fold increase over control) with the dose

23

related positive findings reported by Mirkova ( Mirkova, 1994 ) using the same mouse strain, 24

1,4

- dioxane dose (3,600 mg /kg) and sampling time (24 hour s). Morita and Hayashi ( 1998 ) 25

demonstrated an increase in micronucleus formation in hepatocytes following 1,4

- dioxane 26

dosing and partial hepatectomy to induce cellular mitosis. DNA single

- strand breaks were 27

demonstrated in hepatocytes following gavage exposure to female rats ( Kitchin & Brown, 1990 )

. 28

Roy et al. ( 2005 ) examined micronucleus formation in male CD1 mice exposed to 29

1,4

- dioxane to confirm the mixed findings from earlier mouse micronucleus stu dies and to 30

identify the origin of the induced micronuclei. Mice were administered 1,4

- dioxane by gavage at 31

doses of 0, 1,500, 2,500, and 3,500 mg /kg

- day for 5 day s. The mice were also implanted with 32

5

- bromo

- 2

- deoxyuridine (BrdU)

- releasing osmotic pumps to measure cell proliferation in the 33

liver and to increase the sensitivity of the hepatocyte assay. The frequency of micronuclei in the 34

bone marrow erythrocytes and in the proliferating BrdU

- labeled hepatocytes was determined 35

24 hour s after the final dose . Significant dose

- related increases in micronuclei were seen in the 36

bone

- marrow at all the tested doses (≥ 1,500 mg /kg

- day). In the high

- dose (3,500

- mg/kg) mice, 3773

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE the frequency of bone marrow erythrocyte micronuclei was about 10

- fold greater than the con trol 1

frequency. Significant dose

- related increases in micronuclei were also observed at the two 2

highest doses (≥ 2,500 mg /kg

- day) in the liver. Antikinetochore (CREST) staining or 3

pancentromeric fluorescence in situ hybridization (FISH) was used to deter mine the origin of the 4

induced micronuclei. The investigators determined that 80

– 90% of the micronuclei in both 5

tissues originated from chromosomal breakage; small increase in micronuclei originating from 6

chromosome loss was seen in hepatocytes. Dose

- rel ated statistically significant decreases in the 7

ratio of bone marrow polychromatic erythrocytes (PCE):normochromatic erythrocytes (NCE), an 8

indirect measure of bone marrow toxicity, were observed. Decreases in hepatocyte proliferation 9

were also observed. Based on these results, the authors concluded that at high doses 1,4

- dioxane 10

exerts genotoxic effects in both the mouse bone marrow and liver; the induced micronuclei are 11

formed primarily from chromosomal breakage; and 1,4

- dioxane can interfere with cell 12

proliferation in both the liver and bone marrow. The authors noted that reasons for the 13

discrepant micronucleus assay results among various investigators was unclear, but could be 14

related to the inherent variability present when detecting moderate to weak responses using small 15

numbers of animals, as well as differences in strain, dosing regimen, or scoring criteria. 16

1,4

- Dioxane did not affect in vitro or in vivo DNA repair in hepatocytes or in vivo DNA 17

repair in the nasal cavity ( Goldsworthy, et al., 1991 ; Stott, et al., 1981 ) , but increased hepatocyte 18

DNA synthesis indicative of cell proliferation in several in vivo studies ( Goldsworthy, et al., 19

1991 ; Miyagawa, Shirotori, Tsuchitani, & Yoshikawa, 1999 ; Stott, et al., 1981 ; Uno et al., 1994 )

. 20

1,4

- Dioxane caused a transient inhibition of RNA polymerase A and B in the rat liver ( Kurl, 21

Poellinger, Lund, & Gustafsson, 1981 ) , indicating a negative impact on the synthesis of 22

ribosomal and messenger RNA (DNA transcription). Intravenous administration of 1,4

- dioxane 23

at doses of 10 or 10 0 mg /rat produced inhibition of both polymerase enzymes, with a quicker and 24

more complete recovery of activity for RNA polymerase A, the polymerase for ribosomal RNA 25

synthesis. 26

1,4

- Dioxane did not covalently bind to DNA under in vitro study conditions ( Woo, 27

Argus, et al., 1977b ) . DNA alkylation was also not detected in the liver 4 hour s following a 28

single gavage exposure (1,000 mg /kg) in male Sprague Dawley rats ( Stott, et al., 1981 )

. 29

Rosenkranz and Klopman ( 1992 ) analyzed 1,4

- dioxane using the computer automated 30

structure evaluator (CASE) structure activity method to predict its potential genotoxicity and 31

carcinogenicity. The CASE analysis is based on information contained in the structures of 32

approximately 3,000 chemicals tested for endpoints related to mutagenic/genotoxic and 33

carcinogenic potential. CASE selects descriptors (activating [biophore] or inactivating 34

[biophobe] structural fragments) from a learning set of active and inactive mo lecules. Using the 35

CASE methodology, Rosenkranz and Klopman ( 1992 ) predicted that 1,4

- dioxane would be 36

inactive for mutagenicity in several in vitro systems, including Salmonella, induction of 3774

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE chromosomal aberrations in CHO cells, and unscheduled DNA synthesis in rat hepatocytes. 1

1,4

- Dioxane was predicted to induce SCE in cultured CHO cells, micro nuclei formation in rat 2

bone marrow, and carcinogenicity in rodents. 3

Gene expression profiling in cultured human hepatoma HepG2 cells was performed using 4

DNA microarrays to discriminate between genotoxic and other carcinogens ( van Delft et al., 5

2004 ) . Van Delft et al. ( 2004 ) examined this method using a training set of 16 treatments (nine 6

genotoxins and seven nongenotoxins) and a validation set (three and three), with discrimination 7

models based on Pearson correlation analyses for the 20 most discriminating genes. As reported 8

by the authors ( van Delft, et al., 2004 ) , the gene expression profile for 1,4

- dioxane indicated a 9

classification of this chemical as a ―nongenotoxic‖ carcinogen, and thus, 1,4

- dioxane was 10

included in the training set as a ―nongenotoxic‖ carcinogen. The accuracy for carcinogen 11

classification using this method ranged from 33 to 100%, depending on which chemical data sets 12

and gene expression signals were included in the analysis. 13

Table 4

- 19

. Genotoxicity studies of 1,4

- dioxane; in vitro

Test system Endpoint Test conditions Results a

Dose b Source Without

activation With

activation

Prokaryotic organisms in vitro

S. typhimurium

strains TA98, TA100,

TA1535, TA1537 Reverse

mutation Plate incorporation

assay – – 10,000 μg/plate Haworth et

al. ( 1983 )

S. typhimurium

strains TA98, TA100,

TA1530, TA1535,

TA1537 Reverse

mutation Plate incorporation

assay – – ND Khudoley et

al. ( 1987 )

S. typhimurium

strains TA98, TA100,

TA1535, TA1537 Reverse

mutation Plate incorporation

and preincubation

assays – – 5,000 μg/plate Morita and

Hayashi

( 1998 )

S. typ himurium

strains TA100,

TA1535 Reverse

mutation Preincubation

assay – – 103 mg Nestmann et

al. ( 1984 )

S. typhimurium

strains TA98, TA100,

TA1535, TA1537,

TA1538 Reverse

mutation Plate incorporation

assay – – 103 mg Stott et al.

( 1981 )

E. coli K

- 12

uvrB/recA DNA repair Host mediated

assay – – 1,150 mmol/L Hellmer and

Bolcsfoldi

( 1992 )

E. coli

WP2/WP2uvrA Reverse

mutation Plate incorporation

and preincubation

assays – – 5,000 μg/plate Morita and

Hayashi

( 1998 )

P. phosphoreum

M169 Mutagenicity,

DNA damage Mutatox assay

– ND ND Kwan et al.

( 1990 )75

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Test system Endpoint Test conditions Results a

Dose b Source Without

activation With

activation

Nonmammalian eukaryotic organisms in vitro

S. cerevisiae D61.M Aneuploidy Standard 16

- hour

incubation or cold

interruption

regimen – T ND 4.75% Zimmerman

et al. ( 1985 )

D. melanogaster Meiotic

nondisjunction Oocytes were

obtained for

evaluation 24 and

48 hour s after

mating +T c ND d 2% in sucrose

media Munoz and

Barnett

( 2002 )

D. melanogaster Sex

- linked

recessive lethal

test Exposure by

feeding and

injection – ND d 35,000 ppm in

feed, 7 day s or

50,000 ppm

(5% in water)

by injection Yoon et al.

( 1985 )

Mammalian cells in vitro

Rat hepatocytes DNA damage;

single

- strand

breaks measured

by alkaline

elution 3

- Hour exposure

to isolated primary

hepatocytes +T e ND d 0.3 mM Sina et al.

( 1983 )

Primary hepatocyte

culture from male

F344 rats DNA repair Autoradiography

– ND d 1 mM Goldsworthy

et al. ( 1991 )

L5178Y mouse

lymphoma cells Forward

mutation assay Thymidine kinase

mutagenicity assay

(trifluorothymidin

e resistance) – – 5,000 μg/mL McGregor et

al. ( 1991 )

L5178Y mouse

lymphoma cells Forward

mutation assay Thymidine kinase

mutagenicity assay

(trifluorothymidin

e resistance) – – T 5,000 μg/mL Morita and

Hayashi

( 1998 )

BALB/3T3 cells Cell

transformation 48

- Hour exposure

followed by

4 weeks

incubation; 13 day

exposure followed

by 2.5 weeks

incubation +T f ND d 0.5 mg /mL Sheu et al.

( 1988 )76

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Test system Endpoint Test conditions Results a

Dose b Source Without

activation With

activation

CHO cells SCE BrdU was added

2 hour s after

1,4

- dioxane

addition; chemical

treatment was

2 hour s with S9

and 25 hour s

without S9 ± g

– 10,520 μg/mL Galloway et

al. ( 1987 )

CHO cells Chromosomal

aberration Cells were

harvested 8

–

12 hour s or 18

–

26 hour s after

treatment (time of

first mitosis) – – 10,520 μg/mL Galloway et

al. ( 1987 )

CHO cells SCE 3 hour pulse

treatment;

followed by

continuous

treatment of BrdU

for 23 or 26 hour s – – 5,000 μg/mL Morita and

Hayashi

( 1998 )

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 hour s

following

exposure – – 5,000 μg/mL Morita and

Hayashi

( 1998 )

CHO cells Micronucleus

formation 5 hour pulse

treatment or

44 hour

continuous

treatment; cells

were harvested

42 hour s following

exposure – – 5,000 μg/mL Morita and

Hayashi

( 1998 )

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.

( 1977b )77

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Test system Endpoint Test conditions Results a

Dose b Source Without

activation With

activation

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 hour s 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 diff erent 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 hour s 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 hepato cyte micronuclei was observed in partially

hepatectomized mice 6 day s 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 day s/week).

g A dose

- related increase in the frequency of micron uclei was observed in proliferating cells with micronuclei at

2,500 and 3,500 mg /kg

- day, 5 day s/week. No increase in the frequency of micronuclei was seen in the non

proliferating cells.

h No increase in the hepatocyte labeling index was observed 24 or 48 h our s 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 o bserved 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 hour s following exposure to 0, 1,000, 1,500,

2,000, or 4,000 mg /kg. The incidence (%) of replicative DNA sy nthesis 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 hour s 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 hour s after administration of 2,000 mg /kg (threefold increase). Cell viability

for this group was 79%.

l Replicat ive 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.78

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 20

. Genotoxicity studies of 1,4

- dioxane; mammalian in vivo

Test system Endpoint Test Conditions Results a Dose b Source

Female

Sprague Dawley

Rat DNA damage;

single

- strand breaks

measured by alkaline

elution Two gavage doses given 21

and 4 hour s prior to

sacrifice + c 2,550 mg /kg Kitchin and

Brown

( 1990 )

Male

Sprague Dawley

Rat DNA alkylation in

hepatocytes Gavage; DNA isolation and

HPLC analysis 4 hour s after

dosing – 1,000 mg /kg Stott et al.

( 1981 )

Male

B6C3F 1

Mouse Micronucleus

formation in bone

marrow i.p. injection; analysis of

polychromatic erythrocytes

24 or 48 hour s after dosing – Single dose of

4,000 mg /kg;

3 daily doses of

2,000 McFee et al.

( 1994 )

Male and female

C57BL6

Mouse;

male BALB/c

Mouse Micronucleus

formation in bone

marrow Gavage; analysis of

polychromatic erythrocytes

24 or 48 hour s after dosing +

(C57BL6) d

– (BALB/c) 900 mg /kg

(C57BL6);

5,000 mg /kg

(BALB/c) Mirkova

( 1994 )

Male

CD1

Mouse Micronucleus

f ormation in

peripheral blood Two i.p. injections (1/day);

micronucleated

reticulocytes measured 24,

48, and 72 hour s after the

2nd dose – 3,200 mg /kg Morita

( 1994 )

Male

CD1

Mouse Micronucleus

formation in

hepatocytes Gavage, partial

hepatectomy 24 hour s after

dosing, hepatocytes

analyzed 5 day s after

hepatectomy + e 2,000 mg /kg Morita and

Hayashi

( 1998 )

Male

CD1

Mouse Micronucleus

formation in

peripheral blood Gavage, parti al

hepatectomy 24 hour s after

dosing, peripheral blood

obtained from tail vein

24 hour s after hepatectomy – 3,000 mg /kg Morita and

Hayashi

( 1998 )

Male

CBA and

C57BL6 Mouse Micronucleus

formation in bone

marrow Gavage; analysis of

polychromatic erythrocytes

from specimens prepared

24 hour s after dosing – 3,600 mg /kg Tinwell and

Ashby ( 1994 )

Male

CD1

Mouse Micronuclei

formation in bone

marrow Gavage; analysis for

micronucleated erythrocytes

24 hour s after dosing + f 1,500 mg /kg

- day

for 5 day s Roy et al.

( 2005 )

Male

CD1

Mouse Micronuclei

formation in

hepatocytes Gavage; analysis for

micronuclei 24 hour s after

dosing + g 2,500 mg /kg

- day

for 5 day s Roy et

al. ( 2005 )

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 )79

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Test system Endpoint Test Conditions Results a Dose b Source

Male

F344

Rat DNA repair in

hepatocytes

(autoradiography) Gavage and drinking water

exposure; thymidine

incorporation – 1,000 mg /kg for

2 or 12 hour s;

1,500 mg /kg

- day

for 2 weeks or

3,000 mg /kg

- day

for 1 week Goldsworthy

et al. ( 1991 )

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 day s +

1,000 mg /kg

gavage dose

12 hour s prior to

sacrifice Goldsworthy

et al. ( 1991 )

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 hour s;

1,500 mg /kg

- day

for 1 or 2 weeks Goldsworthy

et al. ( 1991 )

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 )

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 )

Male

F344

Rat DNA synthesis in

hepatocytes Gavage; thymidine and

BrdU incorporation + j 1,000 mg /kg Miyagawa

( 1999 )

Male

F344

Rat DNA synthesis in

hepatocytes Thymidine incorporation ± k 2,000 mg /kg Uno et al.

( 1994 )

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 )

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 hour s 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

C5 7BL6 mice 24 or 48 hour s 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

- , fo ur

- and fourfold, respectively.

e A dose

- related increase in the incidence of hepatocyte micronuclei was observed in partially

hepatectomized mice 6 day s after administration of 1,4

- dioxane. A dose of 1,000 mg /kg produced no

change relative to control, whi le 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 day s/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 day s/week. No increase in the frequency of micronuclei was seen in the non

proliferating cells.80

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE h No increase in the hepatocyte labeling index was observed 24 or 48 hour s 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 hour s follow ing 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 hour s 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 hour s after admini stration 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 ) investigated the effect of 1,4

- dioxane inhalation on free radical 1

processes in the rat ovary and brain. Female rats (6

– 9/group, unspecified strain) were exposed to 2

0, 10, or 100 mg /m 3 of 1,4

- dioxane vapor for 4 hour s/day, 5 day s/week, for 1 month . Rats were 3

sacrificed during the morning or evening following exposure and the ovaries and brain cortex 4

were removed and frozen. Tissue preparations were analyzed for catalase activity, glutathione 5

peroxidase activity, and protein peroxidation. Inhalation of 100 mg /m 3 of 1,4

- dioxane resulted in 6

a significant increase (p < 0.05) in glutath ione peroxidase activity, and activation of free radical 7

processes were apparent in both the rat ovary and brain cortex. No change in catalase activity or 8

protein peroxidation was observed at either concentration. A circadian rhythm for glutathione 9

perox idase activity was absent in control rats, but occurred in rat brain and ovary following 10

1,4

- dioxane exposure. 11

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 12

been shown to induce its own metabo lism ( Young, et al., 1978a ; Young, et al., 1978b ) . Nannelli 13

et al. ( 2005 ) (study details provided in Section 3.3) characterized the CYP450 isozymes that 14

were induced by 1,4

- dioxane in the liver, ki dney, and nasal mucosa of the rat. In the liver, the 15

activities of several CYP450 isozymes were increased (i.e., CYP2B1/2, CYP2E1, CYPC11); 16

however, only CYP2E1 was inducible in the kidney and nasal mucosa. CYP2E1 mRNA was 17

increased approximately two

- to threefold in the kidney and nasal mucosa, but mRNA levels 18

were not increased in the liver, suggesting that regulation of CYP2E1 is organ

- specific. 19

Induction of hepatic CYPB1/2 and CYP2E1 levels by phenobarbital or fasting did not increase 20

the liver toxic ity of 1,4

- dioxane, as measured by hepatic glutathione content or serum ALT 21

activity. This result suggested that highly reactive and toxic intermediates did not play a large 2281

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE role in the liver toxicity of 1,4

- dioxane, even under conditions where metabolism was enhanced. 1

This finding is similar to an earlier conclusion by Kociba et al. ( 1975 ) who evaluated toxicity 2

from a chronic drinking water study alongside data providing a pharmacokinetic profile for 3

1,4

- dioxane. Kociba et al. ( 1975 ) concluded that liver toxicity and eventual tumor formation 4

occurred only at doses where clearance pathways were saturated and elimination of 1,4

- dioxane 5

from the blood was reduced. Nannelli et al. ( 2005 ) further suggested that a sustained induction 6

of CYP2E1 may lead to generation of reactive oxygen species contributing to target organ 7

toxicity and regenerative cell pro liferation; however, no data were provided to support this 8

hypothesis. 9

4.5.2.3. Mechanisms of Tumor Induction

Several studies have been performed to evaluate potential mechanisms for the 10

carcinogenicity of 1,4

- dioxane ( Goldsworthy, et al., 1991 ; Kitch in & Brown, 1990 ; Stott, et al., 11

1981 ) . Stott et al. ( 1981 ) evaluated 1,4

- dioxane in several test systems, including salmonella 12

mutagenicity in vitro, rat hepatocyte DNA repair activity in vitro, DNA synthesis determination 13

in male Sprague Dawl ey rats following acute gavage dosing or an 11

- week drinking water 14

exposure (described in Section 4.2.1), and hepatocyte DNA alkylation and DNA repair following 15

a single gavage dose. This study used doses of 0, 10, 100, or 1,000 mg /kg

- day, with the highes t 16

dose considered to be a tumorigenic dose level. Liver histopathology and liver to BW ratios 17

were also evaluated in rats from acute gavage or repeated dose drinking water experiments. 18

The histopathology evaluation indicated that liver cytotoxicity (i.e., centrilobular 19

hepatocyte swelling) was present in rats from the 1,000 mg /kg

- day dose group that received 20

1,4

- dioxane in the drinking water for 11 weeks ( Stott, et al., 1981 ) . An increase in the liver to 21

BW ratio accompanied by an increase in hepatic DNA synthesis was also seen in this group of 22

animals. No effect on histopathology, liver weight, or DNA synthesis was observed in acutely 23

exposed rats or rats that were exposed to a lower dose of 10 mg /kg

- day for 11 weeks

. 24

1,4

- Dioxane produced negative findings in the remaining genotoxicity assays conducted as part 25

of this study (i.e., Salmonella mutagenicity, in vitro and in vivo rat hepatocyte DN A repair, and 26

DNA alkylation in rat liver). The study authors suggested that the observed lack of genotoxicity 27

at tumorigenic and cytotoxic dose levels indicates an epigenetic mechanism for 1,4

- dioxane 28

hepatocellular carcinoma in rats. 29

Goldsworthy et al. ( 1991 ) evaluated potential mechanisms for the nasal and liver 30

carcinogenicity of 1,4

- dioxane in the rat. DNA repair activity was evaluated as a measure of 31

DNA reactivity and DNA synthesis was measured as an indicator of cell proliferation or 32

promotional activity. In vitro DNA repair was evaluated in primary hepatocyte cultures from 33

control and 1,4

- dioxane

- treate d rats (1 or 2% in the drinking water for 1 week). DNA repair and 34

DNA synthesis were also measured in vivo following a single gavage dose of 1,000 mg /kg, a 35

drinking water exposure of 1% (1,500 mg /kg

- day) for 1 week, or a drinking water exposure of 3682

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 2% (3,0 00 mg /kg

- day) for 2 weeks . Liver to BW ratios and palmitoyl CoA oxidase activity were 1

measured in the rat liver to determine whether peroxisome proliferation played a role in the liver 2

carcinogenesis of 1,4

- dioxane. In vivo DNA repair was evaluated in ra t nasal epithelial cells 3

derived from either the nasoturbinate or the maxilloturbinate of 1,4

- dioxane

- treated rats. These 4

rats received 1% 1,4

- dioxane (1,500 mg /kg

- day) in the drinking water for 8 day s, followed by a 5

single gavage dose of 10, 100, or 1,00 0 mg /kg 12 hour s prior to sacrifice. Archived tissues from 6

the NCI ( 1978 ) bioassay were reexamined to determine the prima ry sites for tumor formation in 7

the nasal cavity following chronic exposure in rats. Histopathology and cell proliferation were 8

determined for specific sites in the nasal cavity that were related to tumor formation. This 9

evaluation was performed in rats that were exposed to drinking water containing 1% 1,4

- dioxane 10

(1,500 mg /kg

- day) for 2 weeks

. 11

1,4

- Dioxane and its metabolite 1,4

- dioxane

- 2

- one did not affect in vitro DNA repair in 12

primary hepatocyte cultures ( Goldsworthy, et al., 1991 ) . In vivo DNA repair was also unaffected 13

by acute gavage exposure or ingestion of 1,4

- dioxane in the drinki ng water for a 1

- or 2

- week 14

period. Hepatocyte cell proliferation was not affected by acute gavage exposure, but was 15

increased approximately twofold following a 1

– 2

- week drinking water exposure. A 5

- day 16

drinking water exposure to 1% 1,4

- dioxane (1,500 mg /kg

- day) did not increase the activity of 17

palmitoyl coenzyme A or the liver to BW ratio, suggesting that peroxisome proliferation did not 18

play a role in the hepatocarcinogenesis of 1,4

- dioxane. Nannelli et al. ( 2005 ) also reported a lack 19

of hepatic palmitoyl CoA induction following 10 day s of exposure to 1.5% 1,4

- dioxane in the 20

drinking water (2,100 mg /kg

- day). 21

Treatment of rats with 1% (1,500 mg /kg

- day) 1,4

- dioxane for 8 day s did not alter DNA 22

repair in nasal epit helial cells ( Goldsworthy, et al., 1991 ) . The addition of a single gavage dose 23

of up t o 1,000 mg /kg 12 hour s prior to sacrifice also did not induce DNA repair. Reexamination 24

of tissue sections from the NCI ( 197 8 ) bioassay suggested that the majority of nasal tumors were 25

located in the dorsal nasal septum or the nasoturbinate of the anterior portion of the dorsal 26

meatus ( Goldsworthy, et al., 1991 ) . No histopathological lesions were observed in nasal section 27

of rats exposed to drinking water containing 1% 1,4

- dioxane (1,500 mg /kg

- day) for 2 week s and 28

no increase was observed in cell proliferation at the sites of highest tumor formation in the nasal 29

cavity. 30

Female Sprague Dawley rats (three to nine per group) were given 0, 168, 840, 2,550, or 31

4,200 mg /kg 1,4

- dioxane (99% purity) by corn oil gavage in two doses at 21 and 4 hour s prior to 32

sacrifice ( Kitchin & Brown, 1990 ) . DNA damage (single

- strand breaks measured by alkaline 33

elution), ODC activity, reduced glutathione content, and CYP450 content were measured in the 34

liver. Serum ALT activity and liver histopathology were also evaluated. No changes were 35

observed in hep atic reduced glutathione content or ALT activity. Light microscopy revealed 36

minimal to mild vacuolar degeneration in the cytoplasm of hepatocytes from three of five rats 3783

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE from the 2,550 mg /kg dose group. No histopathological lesions were seen in any other dose 1

group, including rats given a higher dose of 4,200 mg /kg. 1,4

- Dioxane caused 43 and 50% 2

increases in DNA single

- strand breaks at dose levels of 2,550 and 4,200 mg /kg, respectively. 3

CYP450 content was also increased at the two highest dose levels (2 5 and 66% respectively). 4

ODC activity was increased approximately two

- , five

- , and eightfold above control values at 5

doses of 840, 2,550, and 4,200 mg /kg, respectively. The results of this study demonstrated that 6

hepatic DNA damage can occur in the absen ce of significant cytotoxicity. Parameters associated 7

with tumor promotion (i.e., ODC activity, CYP450 content) were also elevated, suggesting that 8

promotion may play a role in the carcinogenesis of 1,4

- dioxane. 9

4.6. SYNTHESIS OF MAJOR N ONCANCER EFFECTS

Liver and kidney toxicity were the primary noncancer health effects associated with 10

exposure to 1,4

- dioxane in humans and laboratory animals. Several fatal cases of hemorrhagic 11

nephritis and centrilobular necrosis of the liver were related to occupational expos ure (i.e., 12

inhalation and dermal contact) to 1,4

- dioxane ( Barber, 1934 ; Johnstone, 1959 ) . Neurological 13

changes were also reported in one case; including, headache, elevation in blood pressure, 14

agitation and restlessness, and coma ( Johnstone, 1959 ) . Perivascular wide ning was observed in 15

the brain of this worker, with small foci of demyelination in several regions (e.g., cortex, basal 16

nuclei). Liver and kidney degeneration and necrosis were observed in acute oral and inhalation 17

studies ( David, 1964 ; de Navasquez, 1935 ; Drew, et al., 1978 ; Fairley, et al., 1934 ; JBRC, 1998 ; 18

Kesten, et al., 1939 ; Laug, et al., 1939 ; Schrenk & Yant, 1936 ) . The results of subchronic and 19

chronic studies are discussed below. 20

4.6.1. Oral

Table 4

- 21 presents a summary of the noncancer results for the subchronic and chronic 21

oral studies of 1,4

- dioxane toxicity in experimental animals. Liver and kidney toxicity were the 22

primary noncancer health effects of oral exposure to 1,4

- dioxane in animals. Kidney damage at 23

high doses was characterized by degeneration of the cortical tubule cells, necrosis with 24

hemorrhage, and glomerulonephritis ( Argus, et al., 1965 ; Fairley, et al., 1934 ; Kociba, et al., 25

1974 ; NCI, 1978 ) . Renal cell degeneration generally began with cloudy swelling of cells in th e 26

cortex ( Fairley, et al., 1934 ) . Nuclear enlargement of proximal tubule ce lls was observed at 27

doses below those producing renal necrosis ( JBRC, 1998 ; Kano, et al., 2008 ) , but is of uncertain 28

toxicological significance. Th e lowest dose reported to produce kidney damage was 94 mg /kg

29

day, which produced renal degeneration and necrosis of tubule epithelial cells in male rats in the 30

Kociba et al. ( 1974 ) study. Cortical tubule degeneration was seen at higher doses in the NCI 31

( 1978 ) bioassay (240 mg /kg

- day, male rats), and glomerulonephritis was reported for rats given 32

doses of ≥ 430 mg /kg

- day ( Argus, et al., 1965 ; 1973 )

. 3384

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 21

. Oral toxicit y 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 /kg

day; mice 0 or

3,300 mg /kg

- day for

67 day s NA 1,900 rats

3,300 mice Renal cortical degeneration

and necrosis, hemorrhage;

hepatocellular degeneration Fairley et al.

( 1934 )

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 )

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 )

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 /kg

day for 13 weeks 170 387 Nuclear enlargement of

bronchial epithelium Kano et al.

( 2008 )

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 )

Male

Sprague Dawley

rats (30/group) 0, 430, 574, 803, or

1,032 mg /kg

- day for

13 month s NA 430 Hepatocytomegaly;

glomerulonephritis Argus et al.

( 1973 )

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 )

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 )

B6C3F 1 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 )

F344/DuCrj rat

(50/sex/dose

level) Males 0, 11, 55, or

274 mg /kg

- day; females

0, 18, 83, or 429 mg

/kg

day for 2 years 55 274 Atrophy of nasal olfactory

epithelium; nasal adhesion

and inflammation JBRC ( 1998 ) ;

Kano et al.

( 2009 )

F344/DuCrj rat

(50/sex/dose

level) Males 0, 11, 55, or

274 mg /kg

- day; females

0, 18, 83, or 429 mg

/kg

day for 2 years 11 55 Liver hyperplasia JBRC ( 19 98 ) ;

Kano et al.

( 2009 )85

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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

/kg

day for 2 years 55 274 Increases in serum liver

enzymes (GOT, GPT, LDH,

and ALP) JBRC ( 1998 ) ;

Kano et al.

( 2009 )

Crj: BDF1 mouse

(50/sex/dose

level) Males 0, 49, 191 or

677 mg /kg

- day; females

0, 66, 278, or 964 mg

/kg

day for 2 years 66 278 Nasal inflammation JBRC ( 1998 ) ;

Kano et al.

( 2009 )

Crj: BDF1 mouse

(50/sex/dose

level) Males 0, 49, 191 or

677 mg /kg

- day; females

0, 66, 278, or 964 mg

/kg

day for 2 years 49 191 Increases in serum liver

enzymes (GOT, GPT, LDH,

and ALP) JBRC ( 1998 ) ;

Kano et al.

( 2009 )

Developmental studies

Sprague Dawley

rat

(18

– 20/group) Pregnant dams 0, 250,

500, or 1,000 mg /kg

- day

on gestation day s 6

– 15 500 1,000 Delayed ossification of the

sternebrae and reduced fetal

BWs Giavani et al.

( 1985 )

Liver effects included degeneration and necrosis, hepatocyte swelling, cells with 1

hyperchromic nuclei, spongiosis hepatis, hyperplasia, and clear and mixed cell foci of the liver 2

( Argus, et al., 1965 ; Argus, et al., 1973 ; Fairley, et al., 1934 ; Kano, et al., 2 008 ; Kociba, et al., 3

1974 ; NCI, 1978 )

. Hepatocellular degeneration and necrosis were seen at high doses in a 4

subchronic study (1,900 mg /kg

- day in rats) ( Fairley, et al., 1934 ) and at lower doses in a chronic 5

study (94 mg /kg

- day, male rats) ( Kociba, et al., 1974 ) . Argus et al. ( 1973 ) described a 6

progression of preneoplastic effects in the liver of rats exposed to a dose of 575 mg /kg

- day. 7

Early changes (8 month s exposure) were described as an increased nuclear size of hepatocytes, 8

disorganization of the rough endoplasmic reticulum, an increase i n smooth endoplasmic 9

reticulum, a decrease in glycogen, an increase in lipid droplets in hepatocytes, and formation of 10

liver nodules. Spongiosis hepatis, hyperplasia, and clear and mixed

- cell foci were also observed 11

in the liver of rats (doses >55 mg /kg

- d ay in male rats) ( JBRC, 1998 ; Kano, et al., 2009 ) . Clear 12

and mixed

- cell foci are commonly considered preneoplastic changes and would not be 13

considered evidence of noncancer toxicity when observed in conjunction with tumor formation. 14

If exposure to 1,4

- d ioxane had not resulted in tumor formation, these lesions could represent 15

potential noncancer toxicity. The nature of spongiosis hepatis as a preneoplastic change is less 16

well understood ( Bannasch, 2003 ; Karbe & Kerlin, 2002 ; Stroebel, et al., 1995 ) . Spongiosis 17

hepatis is a cyst

- like lesion that arises from the perisinusoidal Ito cells of the liver. This change 18

is sometimes associated with hepatocellu lar hypertrophy and liver toxicity ( Karbe & K erlin, 19

2002 ) , but may also occur in combination with preneoplastic foci, or hepatocellular adenoma or 20

carcinoma ( Bannasch, 2003 ; Stroebel, et al., 1995 ) . In the case of the JBRC ( 1998 ) study, 21

spongiosis hepatis was associated with other preneoplastic c hanges in the liver (hyperplasia, 22

clear and mixed

- cell foci). No other lesions indicative of liver toxicity were seen in this study; 23

therefore, spongiosis hepatis was not considered indicative of noncancer effects. The activity of 2486

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE serum enzymes (i.e., AS T, ALT, LDH, and ALP) was increased in rats and mice exposed to 1

1,4

- dioxane, although only in groups with high incidence of liver tumors. Blood samples were 2

collected only at the end of the 2

- year study, so altered serum chemistry may be associated with 3

t he tumorigenic changes in the liver. 4

Hematological changes were reported in the JBRC ( 1998 ) study only. Mean doses are 5

reported based on information provided in Kano et al. ( 2009 ) . Observed increases in RBCs, 6

hematocrit, hemoglobin in high

- dose male mice (677 mg /kg

- day) may be related to lower 7

drinking water consumption (74 % of control drinking water intake). Hematological effects 8

noted in male rats given 55 mg /kg

- day (decreased RBCs, hemoglobin, hematocrit, increased 9

platelets) were within 20% of control values. A reference range database for hematological 10

effects in labo ratory animals ( Wolford, et al., 1986 ) indicates that a 20% change in these 11

parameters may fall within a normal range (10th

– 90th percentile values) and may not represent a 12

treatment

- re lated effect of concern. 13

Rhinitis and inflammation of the nasal cavity were reported in both the NCI ( 1978 ) (mice 14

only, dose ≥ 380 mg /kg

- day) and JBRC ( 1998 ) studies (≥ 274 mg /kg

- day in rats, >278 mg /kg

15

day in mice). The JBRC ( 1998 ) study also demonstrates atrophy of the nasal epithelium and 16

adhesion in rats and mice. Nasal inflammation may be a response to direct contact of the nasal 17

mucosa with drinking water containing 1,4

- dioxane ( Goldsworthy, et al., 1991 ; Sweeney, et al., 18

2008 ) or could result from systemic exposure. Regardless, inflammation may indicate toxicity 19

due to 1,4

- dioxane exposure. A significant increase in the incidence of pneumonia was reported 20

in mice from the NCI ( 1978 ) study. The significance of this effect is unclear, as it was not 21

observed in other studies that evaluated lung histopathology ( JBRC, 1998 ; Kano, et al., 2008 ; 22

Kociba, et al., 1974 ) . No studies were available regarding the potential for 1,4

- dioxane to cause 23

immunological effects. Metaplasia and hyperplasia of the nasal epithelium were also observed in 24

high

- dose male and female rats ( JBRC, 1998 ) ; h owever, these effects are likely to be associated 25

with the formation of nasal cavity tumors in these dose groups. Nuclear enlargement of the nasal 26

olfactory epithelium was observed at a dose of 83 mg /kg

- day in female rats ( Kano, et al., 2009 ) ; 27

however, it is unclear whether this alteration represents an adverse toxicological effect. Nuclear 28

enlargement of the tracheal and bronchial epithelium and an accumulation of foamy cells in the 29

lung were also seen in male and female mice give 1,4

- dioxane at doses of ≥ 278 mg /kg for 30

2 years ( JBRC, 1998 )

. 31

4.6.2. Inhalati on

Two subchronic ( Fairley, et al., 1934 ; Kasai, et al., 2008 ) and two chronic in halation 32

studies ( Kasai, et al., 2009 ; Torkelson, et al., 1974 ) were identified. Nasal, l iver, and kidney 33

toxicity were the primary noncancer health effects of inhalation expo sure to 1,4

- dioxane in 3487

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE animals. Table 4

- 22 presents a summary of the noncancer results for the subchronic and chronic 1

inhalation studies of 1,4

- dioxane toxicity in laboratory animals. 2

Of the inhalation studies, nasal tissue was only collected in rat studies conducted by 3

Kasai et al. ( 2009 ; 2008 )

. Damage to nasal tissue was reporte d frequently in these studies and 4

statistically significant observations were noted as low as 50 ppm. Nasal effects included 5

deformity of the nose and histopathological lesions characterized by enlarged epithelial nuclei 6

(respiratory epithelium, olfactory epithelium, trachea, and bronchus), atrophy (olfactory 7

epithelium), vacuolic change (olfactory epithelium and bronchial epithelium), squamous cell 8

metaplasia and hyperplasia (respiratory epithelium), respiratory metaplasia (olfactory 9

epithelium), inflamma tion (respiratory and olfactory epithelium), hydropic change (lamina 10

propria), and sclerosis (lamina propria). In both studies, a concentration

- dependent, statistically 11

significant change in enlarged nuclei of the respiratory epithelium was considered the most 12

severe nasal effect by the study authors; however, the toxicological significance of nuclear 13

enlargement is uncertain. 14

At high doses, liver damage was characterized by cell degeneration which varied from 15

swelling ( Fairley, et al., 1934 ; Kasai, et al., 2008 ) to necrosis ( Fairley, et a l., 1934 ; Kasai, et al., 16

2009 ; Kasai, et al., 2008 ) , spongiosis hepatis ( Kasai, et al., 2009 )

, nuclear enlargement of 17

centrilobular cells ( Kasai, et al., 2009 ) and basophilic and acidophilic cell foci ( Kasai, et al., 18

2009 )

. A ltered cell foci are commonly considered preneoplastic changes and would not be 19

considered evidence of noncancer toxicity when observed in conjunction with tumor formation 20

( Bannasch, Moore, Klimek, & Zerban, 1982 )

. Since exposure to 1,4

- dioxane resulted in tumor 21

formation, these lesions are not considered potential noncancer toxicity. 22

At concentrations ranging from 200 ppm to 3

, 200 ppm , altered liver enzymes (i.e., AST, 23

ALT, ALP, and γ

- GTP), increased liver weights, and induction of GST

- P was also observed 24

( Kasai, et al., 2009 ; Kasai, et al., 2008 )

. Changes in the activity of serum enzymes w ere mostly 25

observed in exposed rat groups of high 1,4

- dioxane concentration s ( Kasai, et al., 2009 ; Kasai, e t 26

al., 2008 )

. Induction of GST

- P positive hepatocytes were observed in female rats at 1

, 600 ppm 27

and male and female rats at 3

, 200 ppm following 13 weeks of exposure to 1,4

- dioxane. GST

- P 28

is considered a good enzymatic marker for early detection of chemical hepatocarcinogenesis 29

( Sato, 1989 )

. Although, GST

- P positive liver foci w ere not observed in the 2 year bioassay, th e 30

focally and proliferating GST

- P positive hepatocytes noted in the 13 week study suggests 31

eventual progression to hepatocellular tumors after 2 years of exposure and therefore would not 32

be a potential noncancer effect. 33

The lowest concentration reported to produce liver lesions was 1,250 ppm , character ized 34

by necrosis of centrilobular cells, spongiosis hepatis, and nuclear enlargement in the Kas ai et al. 35

( 2009 ) study. However, as previously stated, the toxicological significance of nuclear 3688

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE enlargement lesions is uncertain; and altered cell foci may not be a potential noncancer effect 1

given its observation in conjunction with tumor formation. 2

Kidney effects were reported less frequently in these inhalation studies and were 3

generally observed at higher exposure concentrations than nasal and liver effects

. Kidney 4

damage was described as patchy degeneration of cortical tubules with vascular congestion and 5

hemorrhage ( Fairley, et al., 1934 ) , hydropic change of proximal tubules ( Kasai, et al., 2009 ; 6

Kasai, et al., 2008 ) , and as nuclear enlargement of proximal tubules cells ( Kasai, et al., 2009 )

. 7

Changes in serum chemistry and urinalysis variables were also noted as evidence of renal 8

damage. In a 13 week inhalation study of male and female rats ( Kasai, et al., 2008 ) kidney 9

toxicity was only observed in female rats exposed to 3 ,200 ppm of 1,4

- dioxane (i.e. hydropic 10

change in the renal proximal tubules)

, which suggests a possible increased susceptibility of 11

female rats to renal damage following inhalation exposure to 1,4

- dioxane. 12

Other noted noncancer effects in laboratory animal s included acute vascular congestion 13

of the lungs ( Fairley, et al., 1934 ) ; change s in relative lung weight s ( Kasai, et al., 2008 ) ; and 14

decrease in body weight gain ( Kasai, et al., 2009 ; Kasai, et al., 2008 )

. Following a 13

- week 15

exposure, h igher 1,4

- dioxane plasma levels were found in female rats as compared to male rats 16

( Kasai, et al., 2008 )

. 1,4

- D ioxane was observed in plasma along with systemic effects following 17

subchronic inhalation e xposure to 1,4

- dioxane in rats. 18

Table 4

- 22

. Inhalation toxicity studies (noncancer effects) for 1,4

- dioxane

Species Dose/duration NOAEL

(ppm) LOAEL

(ppm) Effect Reference

Subchronic studies

Rat, mouse,

rabbit, and

guinea pig (3

- 6/species/group);

unknown strains 0, 1,000, 2,000, 5,000, or

10,000 ppm for 7 days.

Days 1

- 5, two 1.5 hour

exposures; day 6, one 1.5

hour exposure; and day 7,

no exposure NA 1,000 Renal cortical degeneration

and hemorrhage;

hepatocellular degeneration

and necrosis Fairley et al.

( 1934 )

F344/DuCrj rat

(10/sex/group) 0, 100, 200, 400, 800,

1,600, 3,200, or 6,400

ppm 6 hours/day 5

days/week, for 13 weeks NA 100 Respiratory epithelium :

n uclear enlargement of

epithelial cells Kasai et al.

( 2008 )

Chronic studies

Wistar rat

(288/sex) 111 ppm for 7hours/day,

5days/week, for 2 years 111 (free

standing) NA No significant effects were

observed on BWs, survival,

organ weights, hematology,

clinical chemistry, or

histopathology Torkelson et

al. ( 1974 )

F344/DuCrj

male rat

(50/group) 0, 50, 250, or 1,250 ppm

for 6 hours/day, 5

days/week for 2 years N / A 50 Respiratory epithelium:

nuclear enlargement of

epithelial cells, atrophy, and

metaplasia Kasai et al.

( 2009 )

198 9

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.6.3. Mode of Action Information

The metabolism of 1,4

- dioxane in humans was extensive at low doses (<50 ppm). The 1

linear elimination of 1,4

- dioxane in both plasma and urine indicated that 1,4

- dioxane metabolism 2

was a nonsaturated, first

- order process at this exposure level ( 1976 ; Young, et al., 1977 ) . Like 3

humans, rats extens ively metabolized inhaled 1,4

- dioxane; however, plasma data from rats given 4

single i.v. doses of 3, 10, 30, 100, or 1,000 mg [ 14 C]

- 1,4

- dioxane/kg demonstrated a dose

- related 5

shift from linear, first

- order to nonlinear, saturable metabolism of 1,4

- dioxane ( Young, et al., 6

1978a ; Young, et al., 1978b )

. Conversely, using the Young et al. ( 1978a ; 1978b ) rat model, the 7

metabolism of 1,4

- dioxane in rats that were exposed to 400, 800, 1,600, and 3,200 ppm via 8

inhalation for 13 weeks could not be accuratel y depicted due to a lack of knowledge on needed 9

model parameters and biological processes (See Section 3.5.3 and Appendix B). Metabolism 10

may be induced following prolonged inhalation exposure to 1,4

- dioxane at concentrations up to 11

3,200 ppm (Appendix B )

. 12

1,4

- Dioxane oxidation appeared to be CYP450

- mediated, as CYP450 induction with 13

phenobarbital or Aroclor 1254 and suppression with 2,4

- dichloro

- 6

- phenylphenoxy ethylamine 14

or cobaltous chloride was effective in significantly increasing and decreasing, re spectively, the 15

appearance of HEAA in the urine of rats ( Woo, Argus, et al., 1977a ; Woo, et al., 1978 )

. 16

1,4

- Dioxane itself induced CYP450

- mediated metabolism of several barbiturates in Hindustan 17

mice given i.p. injections of 25 and 50 mg /kg of 1,4

- dioxane ( Mungikar & Pawar, 1978 ) . The 18

differences between single and multiple doses in urinary and expired radiolabel support the 19

notion that 1,4

- dioxane may induce its own metabolism. 1,4

- Dioxane has been shown to i nduce 20

several isoforms of CYP450 in various tissues following acute oral administration by gavage or 21

drinking water ( Nannelli, et al., 2005 ) . In the liver, the activity of several CYP450 isozymes was 22

increased (i.e., CYP2B1/2, CYP2E1, CYPC11); however, only CYP2E1 was inducible in the 23

kidney and nasal mucosa. CYP2E1 mRNA was increased approximately two

- to threefold in the 24

kidney and nasal mucosa, but mRNA levels were not increased in the liver, suggesting that 25

regulation of CYP2E1 was organ

- specific. 26

Nannelli et al. ( 2005 ) investigated the role of CYP450 isozymes in the liver toxicity of 27

1,4

- dioxane. Hepatic CYPB1/2 and CYP2E1 levels were induced by pheno barbital or fasting 28

and liver toxicity was measured as hepatic glutathione content or serum ALT activity. No 29

increase in glutathione content or ALT activity was observed, suggesting that highly reactive and 30

toxic intermediates did not play a large role in the liver toxicity of 1,4

- dioxane, even under 31

conditions where metabolism was enhanced. Pretreatment with inducers of mixed

- function 32

oxidases also did not significantly change the extent of covalent binding in subcellular fractions 33

( Woo, Argus, et al., 1977b ) . Covalent binding was measured in liver, kidney, spleen, lung, 34

colon, and skeletal muscle 1

– 12 hour s after i.p. dosing with 1,4

- dioxane. Covalent binding was 3590

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE highest in liver, spleen, and colon. Within he patocytes, 1,4

- dioxane distribution was greatest in 1

the cytosolic fraction, followed by the microsomal, mitochondrial, and nuclear fractions. 2

The absence of an increase in toxicity following an increase in metabolism suggests that 3

accumulation of the par ent compound may be related to 1,4

- dioxane toxicity. This hypothesis is 4

supported by a comparison of the pharmacokinetic profile of 1,4

- dioxane with the toxicology 5

data from a chronic drinking water study ( Kociba, et al., 1975 ) . This analysis indicated that liver 6

toxicity did not occur unless clearance pathways were saturated and elimination of 1,4

- dioxane 7

from the blood was reduced

. A dose

- dependent increase of 1,4

- dioxane accumulation in the 8

blood was seen, which correlated to the observed dose

- dependent increase in incidences of nasal, 9

liver, and kidney toxicities ( Kasai, et al., 2 008 )

. Alternative metabolic pathways (i.e., not 10

CYP450 mediated) may be present at high doses of 1,4

- dioxane; however, the available studies 11

have not characterized these pathways or identified any possible reactive intermediates. T hus, 12

t he mechanism b y which 1,4

- dioxane induces tissue damage is not known, nor is it known 13

whether the toxic moiety is 1,4

- dioxane or a transient or terminal metabolite. 14

4.7. EVALUATION OF CARCIN OGENICITY

4.7.1. Summary of Overall Weight of Evidence

Under the Guidelines for Carcinogen R isk Assessment ( U.S. EPA, 2005a )

, 1,4

- dioxane is 15

―likely to be carcinogenic to humans‖ based on evidence of carcinogenicity in several 2

- year 16

bioassays conducted in four strains of rats, two strains of mice, and in guinea pigs ( Argus, et al., 17

1965 ; Argus, et al., 1973 ; Hoch

- Ligeti & Argus, 1970 ; Hoch

- Ligeti, et al., 1970 ; JBRC, 1998 ; 18

Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ; Yamazaki, et al., 1994 )

. 19

Tissue sites where tumors have been observed in these laboratory animals due to exposure to 20

1,4

- dioxane include, peritoneal ( JBRC, 1998 ; Kan o, et al., 2009 ; Kasai, et al., 2009 ; Yamazaki, 21

et al., 1994 )

, mammary gland ( JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Yamazaki, et 22

al., 1994 ) , liver ( Kano, et al., 2009 ; Kasai, et al., 2009 ) , kidney ( Kasai, et al., 2009 )

, Zymbal 23

gland ( Kasai, et al., 2009 ) , subcutaneous ( Kasai, et al., 2009 )

, nasal tissue ( Argus, et al., 1973 ; 24

Hoch

- Ligeti, et al., 1970 ; JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 25

1974 ; NCI, 1978 ; Yamazaki, et al., 1994 )

, and lung ( Hoch

- Ligeti & Argus, 1970 )

. Studies in 26

humans are inconclusive regarding evidence for a causal link between occupational exposure to 27

1,4

- dioxane and increased risk for cancer; however, only two studies were available and these 28

were limited by small cohort size and a small number of reported cancer cases ( Buffler, et al., 29

1978 ; Thiess, et al., 1976 )

. 30

The available evidence is inadequate to establish a mode of action (MOA) by which 31

1,4

- dioxane induces liver tumors in rats and mice. A MOA hypothesis involving sustained 32

proliferation of spontaneously transformed liver cells has some support from data indicating that 33

1,4

- dioxane acts as a tumor promoter in mouse skin and rat liver bioassay s ( King, et al., 1973 ; 3491

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Lundberg, et al., 1987 ) . Dose

- response and temporal data support the occurrence of cell 1

proliferation and hyperplasia prior to the development of liver tumors ( JBRC, 1998 ; Kociba, et 2

al., 1974 ) in the rat model. However, the dose

- response relationship for induction of hepatic cell 3

proliferation has not been characterized, and it is unknown if it would reflect the dose

- resp onse 4

relationship for liver tumors in the 2

- year rat and mouse studies. Conflicting data from rat and 5

mouse bioassays ( JBRC, 1998 ; Kociba, et al., 1974 ) suggest that cytotoxicity may not be a 6

required precursor event for 1,4

- dioxane

- induced cell proliferation. Data regarding a plausible 7

dose response and temporal progression (see Table 4

- 21 ) from cytotoxicity and cell proliferation 8

to eventual liver tumor formation are not available. 9

For nasal tumors, a hypothesized MOA includes metabolic induction, cyto to xicity , and 10

regenerative cell proliferation

. T he induction of CYP450 has some support from data illustrating 11

that following acute oral administration of 1,4

- dioxane by gavage or drinking water, CYP2E1 12

was inducible in nasal mucosa ( Nannelli, et al., 2005 )

. CYP2E1 mRNA was increased 13

approximately two

- to threefold in nasal mucosa (and in the kidney, see section 3.3 ) in the 14

Nan n elli et al. ( 2005 ) study. The possibility of the parent compound as a factor in the 15

development of nasal tumors also has some support. Following a 13

- week inhalation study in 16

rats, a concentration

- dependent accumulation of 1,4

- dioxane in the blood was observed ( Kasai, 17

et al., 2008 ) . Studies have shown that water

- soluble, gaseous irritants cause nasal injuries such 18

as squamous cell carcinomas ( Morgan, Patterson, & Gross, 1986 )

. Similarly , 1,4

- dioxane, which 19

has been reported as a miscible compound ( Hawley & Lewis Rj Sr, 2001 )

, also caused nasal 20

injuries that were concentration

- d ependent, including nasal tumors ( Kasai, et al ., 2009 )

. While 21

cell proliferation was observed following 1,4

- dioxane exposure in both a 2

- year inhalation study 22

in male rats ( 1,250 ppm ) ( Kasai, et al., 2009 ) and a 2

- year drinking water study in male ( 274 23

mg/kg

- day ) and female rats ( 429 mg/kg

- day ) , no evidence of cytotoxicity in the nas al cavity was 24

observed ( Kasai, et al., 2009 ) ; t herefore

, cytotoxicity, as a key event

, is not supported. 25

The MOA by which 1,4

- dioxane produces liver, nasal, lung, peritoneal ( mesotheliomas ), 26

mammary gland

, Zymbal gland, and subcutis tumors is unknown, and the available data do not 27

support any hypothesized carcinogenic MOA for 1,4

- dioxane. 28

U.S. EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a ) indicate that 29

for tumors occurring at a site other than the initial point of contact, the weight of evidence for 30

carcinogenic potential may apply to all routes of exposure that have not been adequately tested at 31

sufficient doses. An exception occurs when there is convincing information (e.g., toxicokinetic 32

data) that absorption does not occur by other routes. Information availa ble on the carcinogenic 33

effects of 1,4

- dioxane via the oral route demonstrates that tumors occur in tissues remote from 34

the site of absorption. In addition, information on the carcinogenic effects of 1,4

- dioxane via the 35

inhalation route in animals also dem onstrates that tumors occur at tissue sites distant from the 36

portal of entry. Information on the carcinogenic effects of 1,4

- dioxane via the inhalation and 3792

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE dermal routes in humans and via the dermal route in animals is absent. Based on the observance 1

of s ystemic tumors following oral and inhalation exposure, it is assumed that an internal dose 2

will be achieved regardless of the route of exposure. Therefore, 1,4

- dioxane is ―likely to be 3

carcinogenic to humans‖ by all routes of exposure. 4

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, 5

the cohort size was limited and number of reported cases were of limited size was small ( Buffler, 6

et al., 1978 ; Thiess, et al., 1976 )

. 7

Several carcinogenicity bioassays have been conducted for 1,4

- dioxane in mice, rats, and 8

guinea pigs ( Argus, et al., 1965 ; Argus, et al., 1973 ; Hoch

- Ligeti & Argus, 1970 ; Hoch

- Ligeti, et 9

al., 1970 ; JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ; 10

Torkelson, et al., 1974 ; Yamazaki, et al., 1994 )

. Liver tumors have been observed following 11

drinking water exposure in male Wistar rats ( Argus, et al., 1965 ) , male guinea pigs ( Hoch

- Ligeti 12

& Argus, 1970 )

, male Sprague Dawley rats ( Argus, et al., 1973 ; Hoch

- Ligeti, et al., 1970 ) , male 13

and female Sherman rats ( Koc iba, et al., 1974 ) , female Osborne

- Mendel rats ( NCI, 1978 ) , male 14

and female F344/DuCrj rats ( JBRC, 1998 ; Kano, et al., 2009 ; Yamazaki, et al., 1994 ) , male and 15

fem ale B6C3F 1 mice ( NCI, 1978 ) , and male and female Crj: BDF1 mice ( JBRC, 1998 ; Kano, et 16

al., 2009 ; Yamazaki, et al., 1994 ) ; and follo wing inhalation exposure in male F344 rats ( Kasai, et 17

al., 2009 )

. In the earliest cancer bioassays, the liver tumors were described as hepatomas ( Argus, 18

et al., 1965 ; Argus, et al ., 1973 ; Hoch

- Ligeti & Argus, 1970 ; Hoch

- Ligeti, et al., 1970 ) ; however, 19

later studies made a distinction between hepatocellular carcinoma and hepatocellular adenoma 20

( JBRC, 1998 ; Kano, et al. , 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ; Yamazaki, 21

et al., 1994 )

. Both tumor types have been seen in rats and mice exposed to 1,4

- dioxane via 22

drinking water and inhalation

. Kociba et al. ( 1974 ) noted evidence of liver toxicity at or below 23

the dose levels that produced liver tumors but did not report incidence data for these effects. 24

Hepatocellular degeneration and necrosis were observed in the mid

- and high

- dose groups of 25

male and female Sherman rats exposed to 1,4

- dioxane, while tum ors were only observed at the 26

highest dose. Hepatic regeneration was indicated in the mid

- and high

- dose groups by the 27

formation of hepatocellular hyperplastic nodules. Kano et al., ( 2009 ) also provided evidence of 28

liver hyperplasia in male F344/DuCrj rats at a dose level below the dose that induced a 29

statistically sign ificant increase in tumor formation. Kasai et al. ( 2009 ) noted evidence of liver 30

toxicity and tumor incidences (i.e. hepatocellular adenoma) in male F344/DuCrj rats following 31

inhalation exposures to 1,250 ppm. Increased liver toxicities included hepatocellular necrosis, 32

spongiosis hepatis, and acidophilic and basophilic cell foci. 33

Nasal cavity tumors were also observed in Sprague Dawley rats ( Argus, et al., 1973 ; 34

Hoch

- Ligeti, et al., 1970 ) , Osborne

- Mendel rats ( NCI, 1978 ) , Sherman rats ( Kociba, et al., 3593

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1974 ) , and F344/DuCrj ra ts ( JBR C, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Yamazaki, et 1

al., 1994 )

. Most tumors were characterized as squamous cell carcinomas. Nasal tumors were 2

not elevated in B6C3F 1 or Crj: BDF1 mice. Kano et al. ( 2009 ) and Kasai et al. ( 2009 ) were the 3

only stud ies that eval uated nonneoplastic changes in nasal cavity tissue following prolonged 4

exposure to 1,4

- dioxane via oral and inhalation routes, respectively

. Histopathological lesions in 5

female F344/DuCrj rats were suggestive of toxicity and regeneration in this tissue (i .e., atrophy, 6

adhesion, inflammation, nuclear enlargement, and hyperplasia and metaplasia of respiratory and 7

olfactory epithelium). Some of these effects occurred at a lower dose (83 mg /kg

- day) than that 8

shown to produce nasal cavity tumors (429 mg /kg

- day ) in female rats. Re

- examination of tissue 9

sections from the NCI ( 1978 ) bioassay suggested that the majority of nasal tumors were located 10

in the dorsal nasal septum or the nasoturbinate of the anterior portion of the dorsal meatus. 11

Histopathological lesions in male F344/DuCrj rats following exposure to 1,4

- dioxane via 12

inhala tion were also suggestive of toxicity and regeneration in the nasal cavity (i.e. atrophy, 13

inflammation, nuclear enlargement, hyperplasia and metaplasia of the respiratory and olfactor y 14

epithelium, and inflammation). Some of these effects occurred at lower concentration s (50 ppm 15

and 250 ppm) than th ose shown to produce nasal cavity tumors (1,250 ppm) in male rats

. N asal 16

squamous cell carcinoma s were observed in the dorsal area of levels 1

- 3 of the nasal cavity and 17

w ere characterized as well

- differentiated and keratinized. In two cases, invasive growth into 18

adjacent tissue was noted, marked by carcinoma growth out of the nose and through a destroyed 19

nasal bone

. 20

Tumor initiation and promotion studies in mouse skin and rat liver suggested that 21

1,4

- dioxane doe s not initiate the carcinogenic process, but instead acts as a tumor promoter 22

( Bull, et al., 1986 ; King, et al., 1973 ; Lundberg, et al., 1987 ) (see Section 4.2.3). 23

In addition to the liver and nasal tumors observed in several studies, a statistically 24

significant increase in mesotheliomas of t he peritoneum was seen in male rats from the Kano et 25

al. ( 2009 ) stud y ( JBRC, 1998 ; Yamazaki, et al., 1994 ) and the Kasai et al. ( 2009 ) study

. Female 26

rats dosed with 429 mg /kg

- day in drinking water for 2 years also showed a statistically 27

significant increase in mammary gland adenomas ( JBRC, 1998 ; Kano, et al., 2009 ; Yamazaki, et 28

al., 1994 )

. In male rats, exposed via inhalation, a statistically significant positive trend of 29

mammary gland adenomas was observed by Kasai et al. ( 2009 ) . A statistically significant 30

increase and/or trend of subcutis fibroma, Z ymbal gland adenoma, and renal cell carcinoma 31

incidences was also observed in male rats exposed fo r 2 years via inhalation ( Kasai, et al., 2009 )

. 32

A significant increase in the incidence of these tumors was not observed in other chronic oral or 33

inhalation bioassays of 1,4

- dioxane ( Kociba, et al., 1974 ; NCI, 1978 ; Torkelson, et al., 1974 )

. 3494

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.7.3. Mode of Action Information

The MOA by which 1,4

- dioxane produces liver, nasal, peritoneal ( mesotheliomas ), 1

mammary gland

, Zymbal gland

, and subcu t is tumors is unknown, and the available data do not 2

support any hypothesized mode of carcinogenic action for 1,4

- dioxane. Available data also do 3

not clearly identify whether 1,4

- dioxane or one of its metabolites is responsible for the observed 4

effects. The hypothesized MOAs for 1,4

- dioxane carcinogenicity are discussed below within the 5

context of the modified Hill criteria of causality as recommended in the most recent Agency 6

guidelines ( U.S. EPA, 2005a ) . MOA analyses were not conducted for peritoneal

, mammary 7

gland

, Zymbal gland, or subcut i s tumors due to the absence of any chemical specific information 8

for these tumor types. 9

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 10

spontaneously transformed liver cells, resulting in t he eventual formation of liver tumors. 11

Precursor events in which 1,4

- dioxane may promote proliferation of transformed liver cells are 12

uncertain. One study suggests that induced liver cytotoxicity may be a key precursor event to 13

cell proliferation leading to the formation of liver tumors ( Kociba, et al., 1974 ) , however, this 14

study did not report incidence data for these effe cts. Other studies suggest that cell proliferation 15

can occur in the absence of liver cytotoxicity. Liver tumors were observed in female rats and 16

female mice in the absence of lesions indicative of cytotoxicity ( JBRC, 1998 ; Kano, et al., 2008 ; 17

NCI, 1978 )

. Figure 4

- 1 presents a schematic representation of possible key events in the MOA 18

for 1,4

- dioxane liver carcinogenicity. These include: (1) oxidation by CYP2E1 and CYP2B1/2 19

(i.e., detoxification pathway for 1,4

- dioxane), (2) saturation of metabolism/clearance leading to 20

accumulation of the parent 1,4

- dioxane, (3) liver damage followed by regenerative cell 21

proliferation, or (4) cell proliferation in the absence of cytotoxicity (i.e., mitogenesis), 22

(5) hyperpl asia, and (6) tumor formation. It is suggested that liver toxicity is related to the 23

accumulation of the parent compound following metabolic saturation at high doses ( Kociba, et 24

al., 1975 ) ; however, no in vivo or in vitro assays have examined the toxicity of metabolites 25

resulting from 1,4

- dioxane to suppo rt this hypothesis. Nan n elli et al. ( 2005 ) demonstrated that 26

an increase in the oxidative metabolism of 1,4

- dioxane via CYP450 induction using 27

phenobarbital or fasting does not result in an increase in liver toxicity. This result suggested that 28

highly reactive and toxic intermediates did not play a large role in the liver toxicity of 29

1,4

- dioxane, even under con ditions where metabolism was enhanced. Alternative metabolic 30

pathways (e.g., not CYP450 mediated) may be present at high doses of 1,4

- dioxane; although the 31

available studies have not characterized these pathways nor identified any possible reactive 32

interm ediates. Tumor promotion studies in mouse skin and rat liver suggest that 1,4

- dioxane 33

may enhance the growth of previously initiated cells ( King, et al., 1973 ; Lundberg , et al., 1987 )

. 3495

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE This is consistent with the in crease in hepatocyte cell proliferation observed in several studies 1

( Goldsworthy, et al., 1991 ; Miyagawa, et al., 1999 ; Stott, et al., 1981 ; Uno, et al., 1994 )

. These 2

mechanistic studies provide evidence of cell proliferation, but do not indicate whether 3

mitogenesis or cytotoxicity is responsible for increased cell turnover. 4

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 5

sustained proliferation of spontaneously transformed nasal epithelial cells, resulting in the 6

eventual formation of nasal cavity tumors. Cell proliferation was observed following 7

1,4

- dioxane exposure in both a 2

- year inhalation study in male rats (1,250 ppm) ( Kasai, et al., 8

2009 ) and a 2

- year drinking water study in male (274 mg/kg

- day) and female rats (429 mg/kg

9

day); however, no evidence of cytotoxicity in the nasal cavity was observed ( Kasai, et al., 2009 ) ; 10

t herefore, cytotoxicity as a key event is not supported. The Kasai et al. ( 2009 ; 2008 ) studies 11

suggest that nasal toxicity is related to the accumulation of the parent compound following 12

metabolic saturation at high doses; however no in vivo or in vitro assays have examined the 13

toxicity of metabolites resulting from 1,4

- dioxane to support this hypo th es is. Nannelli et al. 14

( 2005 ) demonstrated that CYP2E1 was inducible in nasal mucosa following acute oral 15

administration of 1,4

- dioxane by gavage or drinking water, which could potentially lead to an 16

increase in the oxidative metabolism of 1,4

- dioxane and nasal toxicity. However, Nannelli et al. 17

( 2005 ) did no t characterize this pathway nor identify any possible reactive intermediates or nasal 18

toxicities. 19

2096

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 1

subsequent reparative cell proliferation, as precursor events to liver tumor formation is 2

minimally supported by findings that nonneoplastic liver lesions occurred at exposure levels 3

low er than those resulting in significantly increased incidences of hepatocellular tumors ( Kociba, 4

et al., 1974 ) and the demo nstration of nonneoplastic liver lesions in subchronic ( Kano, et al., 5

2008 ) and acute and short

- term oral studies (see Table 4

- 18 ). Because the incidence of 6

nonneoplastic lesions was not reported by Kociba et al. ( 197 4 ) , it is difficult to know whether the 7

incidence of liver lesions increased with increasing 1,4

- dioxane concentration. Contradicting the 8

observations by Kociba et al. ( 1974 ) , liver tumors were observed in female rats and female mice 9

in the absence of lesions indicative of cytotoxicity ( JBRC, 1998 ; Kano, et al., 2008 ; NCI, 1978 )

. 10

This suggests that cytotoxicity may not be a requisite step in the MOA for liv er cancer. 11

Mechanistic and tumor promotion studies suggest that enhanced cell proliferation without 12

cytotoxicity may be a key event; however, data showing a plausible dose response and temporal 13

progression from cell proliferation to eventual liver tumor f ormation are not available (see 14

Sections 4.7.3.3 and 4.7.3.4). Mechanistic studies that demonstrated cell proliferation after 15

short

- term exposure did not evaluate liver cytotoxicity ( Goldsworthy, et al., 1991 ; Miyagawa, et 16

al., 1999 ; Uno, et al., 1994 )

. Studies have not investigated possible precursor events that may 17

lead to cell proliferation in the absence of cytotoxicity (i.e., genetic regulation of mitogenesis). 18

4.7.3.2.2. Nasal cavity

. Nasal cav ity tumors have been demonstrated in several rat strains 19

( JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ; Yamazaki, 20

et al., 1994 ) , but were not elevated in two strains of mice ( JBRC, 1998 ; Kano, et al., 2009 ; NCI, 21

1978 ; Yamazaki, et al., 1994 ) . Chronic irritation was indicated by the observation of rhinitis 22

and /or inflammation of the nasal cavity in rats from the JBRC ( 1998 ) and Kasai et al. ( 2009 ; 23

2008 ) studie s

. The Kasai et al. ( 2009 ; 2008 ) studies also showed atrophy of the nasal epithelium 24

in rats

, and the JRBC ( 1998 ) study also observed atrophy of the nasal epithelium as well as 25

adhesion in rats. Regeneration of the nasal epithelium is demonstrated by metaplasia and 26

hyperplasia observed in rats exposed to 1,4

- dioxane ( JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et 27

al., 2009 ; Yamazaki, et al., 1994 )

. Oxidation of 1,4

- dioxane metabolism by CYP450 is not 28

supported as a key event in the MOA of nasal tumors

. Nannelli et al. ( 2005 ) lacked details of 29

possible reactive intermediates and result ing nasal toxicity

. Accumulation of 1,4

- dioxane in 30

blood as a precursor event of nasal tumor formation is also not supported because the parent 31

compound 1,4

- dioxane was only measured in one subchronic study ( Kasai, et al., 2008 ) and in 32

this subchronic study no evidence of nasal cytotoxicity, cell proliferation, or incidence of nasal 33

tumors were reported. 34

3597

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.7.3.3. Dose

- Response Relationship

4.7.3.3.1. Liver

. Table 4

- 23 presents the temporal sequence and dose

- response relationship for 1

possible key events in the liver carcinogenesis of 1,4

- dioxane. Dose

- response information 2

provides some support for enhanced cell proliferation as a key event in the liver tumorigenesis of 3

1,4

- dioxane; however, the role of cytotoxicity as a required precursor event is not supported by 4

data from more than one study. Kociba et al. ( 1974 ) demonstrated that liver toxicity and 5

hepatocellular regeneration occurred at a lower dose level than tumor form ation. Hepatocellular 6

degeneration and necrosis were observed in the mid

- and high

- dose groups of Sherman rats 7

exposed to 1,4

- dioxane, although it is not possible to discern whether this effect was observed in 8

both genders due to the lack of incidence dat a ( Kociba, et al., 1974 ) . Hepatic tumors were only 9

observed at the highest dose ( Kociba, et al., 1974 ) . Hepatic regeneration was indicated in the 10

mid

- and high

- dose group by the formation of hepatocellular hyperplastic nodules. Liver 11

hyperpl asia was also seen in rats from the JBRC ( 1998 ) study, at or below the dose level that 12

resulted in tumor formation ( Kano, et al., 2009 ) ; however, hepatocellular degeneration and 13

necrosis were not observed. These results suggest that hepatic cell proliferation and hyperplasia 14

may occur in the absence of signific ant cytotoxicity. Liver angiectasis (i.e., dilation of blood or 15

lymphatic vessels) was observed in male mice at the same dose that produced liver tumors; 16

however, the relationship between this vascular abnormality and tumor formation is unclear. 17

Table 4

- 2 3

. Temporal sequence and dose

- response relationship for possible

key events and liver tumors in rats and mice

Dose (mg/kg

- day)

or Exposure

(ppm) Key event (time →)

Metabolism

1,4

- dioxane Liver damage Cell

proliferation Hyperplasia Adenomas

and/or

carcinomas

Kociba et al., ( 1974 )

— Sherman rats (male and female combined)

0 mg/kg

- day

— a

— a

— a

— a

— a

14 mg/kg

- day b

— a

— a

— a

— a

121 mg/kg

- day b c

— a c

— a

1,307 mg/kg

- day b c

— a c c

NCI, ( 1978 )

— female Osborne

- Mendel rats

0 mg/kg

- day

— a

— a

— a

— a

— a

350 mg/kg

- day b

— a

— a

— a c

640 mg/kg

- day b

— a

— a

— a c

NCI, ( 1978 )

— male B6C3F 1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

720 mg/kg

- day b

— a

— a

— a c

830 mg/kg

- day b

— a

— a

— a c

NCI, ( 1978 )

— female B6C3F 1 mice98

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Dose (mg/kg

- day)

or Exposure

(ppm) Key event (time →)

Metabolism

1,4

- dioxane Liver damage Cell

proliferation Hyperplasia Adenomas

and/or

carcinomas

0 mg/kg

- day

— a

— a

— a

— a

— a

380 mg/kg

- day b

— a

— a

— a c

860 mg/kg

- day b

— a

— a

— a c

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— male F344/DuCrj rats

0 mg/kg

- day

— a

— a

— a

— a

— a

11 mg/kg

- day b

— a

— a

— a

— a

55 mg/kg

- day b

— a

— a c ,e

— a

274 mg/kg

- day b c,d

— a c ,e c ,e

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— female F344/DuCrj rats

0 mg/kg

- day

— a

— a

— a

— a

— a

18 mg/kg

- day b

— a

— a

— a

— a

83 mg/kg

- day b

— a

— a

— a

— a

429 mg/kg

- day b

— a

— a c ,e c ,e

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— male Crj: BDF1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

49 mg/kg

- day b

— a

— a

— a c ,e

191 mg/kg

- day b

— a

— a

— a c ,e

677 mg/kg

- day b c,d

— a

— a c ,e

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— female Crj: BDF1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

66 mg/kg

- day b

— a

— a

— a c ,e

278 mg/kg

- day b

— a

— a

— a c ,e

964 mg/kg

- day b c,d

— a

— a c ,e

Kasai et al. ( 2008 )

— F344 rats (male and female combined)

0 ppm

— a

— a

— a

— a

— a

100 ppm

— a

— a

— a

— a

— a

200 ppm

— a

— a

— a

— a

— a

400 ppm

— a

— a

— a

— a

— a

800 ppm

— a

— a

— a

— a

— a

1,600 ppm

— a

— a

— a

— a

— a

3,200 ppm

— a f

— a

— a

— a

6,400 ppm

— a,g

— a,g

— a,g

— a,g

— a,g99

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Dose (mg/kg

- day)

or Exposure

(ppm) Key event (time →)

Metabolism

1,4

- dioxane Liver damage Cell

proliferation Hyperplasia Adenomas

and/or

carcinomas

Kasai et al., ( 2009 )

— male F344 rats

0 ppm

— a

— a

— a

— a

— a

50 ppm

— a

— a

— a

— a

— a

250 ppm

— a

— a

— a

— a

— a

1,250 ppm

— a h

— a

— a h

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/kg

day), and female mice (898 mg/kg

- day) exposed to 1,4

- dioxane in drinking water ( Kano, et al., 2008 )

.

e + Kano et al. ( 2009 ) reported incidence rates for hepatocellular adenomas and carcinomas; however, information

from JBRC ( 1998 ) on incidence of liver hyperplasia was used to create this table.

f + Kasai et al. ( 2008 ) reported significant incidence rates for single cell necrosis in female rats only (3200 ppm)

following a 2 year bioassay.

g All rats died during the first week of the 13

- week bioassay ( Kasai, et al., 2008 )

. h Kasai et al. ( 2009 ) reported incidence rates for centrilobular necrosis and hepatoc ellular adenomas in male rats

(1,250 ppm).

4.7.3.3.2. Nasal cavity

. Table 4

- 24 presents the temporal sequence and dose

- response 1

relationship for possible key events in the nasal tissue carcinogenesis of 1,4

- dioxane. Toxicity 2

and regeneration in nasal epithelium (i.e., atrophy, adhesion, inflammation, and hyperplasia and 3

metaplasia of respiratory and olfactory epithelium) was evident in one study at the same dose 4

levels that produced nasal cavity tumors ( JBRC, 1998 ; Kano, et al., 2009 )

. In another study, 5

dose

- response information provided some support for nasal toxicity and regeneration in nasal 6

epithelium occurring before tumor development ( Kasai, et al., 2009 ) . However, the role of 7

cytotoxicity as a required precursor event is not supported by data from any of the reviewed 8

studies. T he accumulation of parent 1,4

- dioxane as a key event has some support since 9

concentration

- dependent increases were noted for bot h 1,4

- dioxane in plasma and toxi cities 10

observed that are also other possible precursor events (i.e. regeneration in nasal 11

epithelium) ( Kasai, et al., 2008 )

. In a subsequent study by Kasai et al. ( 2009 ) some of these same 12

possible precursor events were observed at 50, 250, and 1,250 ppm with evidence of nasal 13

tumors at the highest concentration (1,250 ppm). 14100

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 4

- 24

. Temporal sequence and dose

- response relationship for possible

key events and nasal tumors in rats and mice.

Dose (mg/kg

- day)

or Exposure

(ppm) Key event (time →)

Metabolism

1,4

- dioxane Nasal

cytotoxicity Cell

proliferation Hyperplasia Adenomas

and/or

carcinomas

Kociba et al., ( 1974 )

— Sherman rats (male and female combined)

0 mg/kg

- day

— a

— a

— a

— a

— a

14 mg/kg

- day b

— a

— a

— a

— a

121 mg/kg

- day b

— a

— a

— a

— a

1,307 mg/kg

- day b

— a

— a

— a

— a

NCI, ( 1978 )

— female Osborne

- Mendel rats

0 mg/kg

- day

— a

— a

— a

— a

— a

350 mg/kg

- day b

— a

— a

— a

— a

640 mg/kg

- day b

— a

— a

— a

— a

NCI, ( 1978 )

— male B6C3F 1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

720 mg/kg

- day b

— a

— a

— a

— a

830 mg/kg

- day b

— a

— a

— a

— a

NCI, ( 1978 )

— female B6C3F 1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

380 mg/kg

- day b

— a

— a

— a

— a

860 mg/kg

- day b

— a

— a

— a

— a

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— male F344/DuCrj rats

0 mg/kg

- day

— a

— a

— a

— a

— a

11 mg/kg

- day b

— a

— a

— a

— a

55 mg/kg

- day b

— a

— a

— a

— a

274 mg/kg

- day b

— a

— a c,d c,d

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— female F344/DuCrj rats

0 mg/kg

- day

— a

— a

— a

— a

— a

18 mg/kg

- day b

— a

— a

— a

— a

83 mg/kg

- day b

— a

— a

— a

— a

429 mg/kg

- day b

— a

— a c,d c,d

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— male Crj:BDF1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

49 mg/kg

- day b

— a

— a

— a

— a

191 mg/kg

- day b

— a

— a

— a

— a

677 mg/kg

- day b

— a

— a

— a

— a101

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Dose (mg/kg

- day)

or Exposure

(ppm) Key event (time →)

Metabolism

1,4

- dioxane Nasal

cytotoxicity Cell

proliferation Hyperplasia Adenomas

and/or

carcinomas

Kano et al., ( 2009 ) ; JBRC, ( 1998 )

— female Crj:BDF1 mice

0 mg/kg

- day

— a

— a

— a

— a

— a

66 mg/kg

- day b

— a

— a

— a

— a

278 mg/kg

- day b

— a

— a

— a

— a

964 mg/kg

- day b

— a

— a

— a

— a

Kasai et al. ( 2008 )

— F344 rats (male and female combined)

0 ppm

— a

— a

— a

— a

— a

100 ppm b

— a

— a

— a

— a

200 ppm b

— a

— a

— a

— a

400 ppm + c

— a

— a

— a

— a

800 ppm + c

— a

— a

— a

— a

1600 ppm + c

— a

— a

— a

— a

3200 ppm + c

— a

— a

— a

— a

6400 ppm a, b, f

— a, f

— a, f

— a, f

— a, f

Kasai et al. ( 2009 )

— male F344 rats

0 ppm

— a

— a

— a

— a

— a

50 ppm b

— a

— a

— a

— a

250 ppm b

— a

— a

— a

— a

1,250 ppm b

— a

— c + e c

a

— No evidence demonstrating key event.

b + 1,4

- dioxane metabolism was not evaluated as part of the se studies . 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 + Kano et al. ( 2009 ) reported incidence rates for squamous cell hyperplasia (respiratory epithelium) and squamous

cell carcinomas (nasal cavity); however, information from JBRC ( 1998 ) on significant incidence of squamous cell

hyperplasia was used to create this table.

e +Kasai et al. ( 2009 ) reported incidence rates for squamous cell hyperp lasia in male rats (1,250 ppm) following a 2

year bioassay.

f + All rats died during the first week of the 13 week bioassay ( Kasai, et al., 2008 )

.

4.7.3.4. Temporal Relationship

4.7.3.4.1. Liver

. Available information regarding temporal relationships between the key event 1

(sustained proliferation of spontaneously transformed liver cells) and the eventual formation of 2

liver tumors is limited. A comparison of 13

- week and 2

- year studies conducted in F344/DuCrj 3

rats and Crj: BDF1 mice at the same laboratory revealed that tumorigenic doses of 1,4

- dioxane 4

produced liver toxicity by 13 weeks of exposure ( JBRC, 1998 ; Kano, e t al., 2009 ; Kano, et al., 5

2008 ) . Hepatocyte swelling of the centrilobular area of the liver, vacuolar changes in the liver, 6

granular changes in the liver, and single cell necrosis in the liver were observed in mice and rats 7102

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE given 1,4

- dioxane in the dri nking water for 13 weeks . Sustained liver damage may lead to 1

regenerative cell proliferation and tumor formation following chronic exposure. As discussed 2

above, histopathological evidence of regenerative cell proliferation has been seen following 3

long

- term exposure to 1,4

- dioxane ( JBRC, 1998 ; Kociba, et al., 1974 ) . Tumors occurred earlier 4

at high doses in both mice and rats from this study ( Yamazaki, 2006 ) ; however, temporal 5

information regarding hyperplasia or other possible key events was not available (i.e., int erim 6

blood samples not collected, interim sacrifices were not performed). Argus et al. ( 1973 ) studied 7

the progression of tumorigenesis by ele ctron microscopy of liver tissues obtained following 8

interim sacrifices at 8 and 13 month s of exposure (five rats/group, 574 mg /kg

- day). The first 9

change observed was an increase in the size of the nuclei of the hepatocytes, mostly in the 10

periportal area. Precancerous changes were characterized by disorganization of the rough 11

endoplasmic reticulum, increase in smooth endoplasmic reticulum, and decrease in glycogen and 12

increase in lipid droplets in hepatocytes. These changes increased in severity in the 13

hepatocellular carcinomas in rats exposed to 1,4

- dioxane for 13 month s. 14

Three types of liver nodules were observed in exposed ra ts at 13

– 16 month s. The first 15

consisted of groups of these cells with reduced cytoplasmic basophilia and a slightly nodular 16

appearance as viewed by light microscopy. The second type of nodule was described consisting 17

of large cells, apparently filled and distended with fat. The third type of nodule was described as 18

finger

- like strands, 2

– 3 cells thick, of smaller hepatocytes with large hyperchromic nuclei and 19

dense cytoplasm. This third type of nodule was designated as an incipient hepatoma, since it 20

sh owed all the histological characteristics of a fully developed hepatoma. All three types of 21

nodules were generally present in the same liver. 22

4.7.3.4.2. Nasal cavity

. No information was available regarding the temporal relationship 23

between toxicity in the nasal epithelium and the formation of nasal cavity tumors. A comparison 24

of 13

- week and 2

- year studies conducted in F344/DuCrj rats could not be conducted since the 25

tumorigenic concentration of 1,4

- dioxane was different from the concentration which produced 26

nasal toxicities by 13 weeks of exposure ( Kasai, et al., 2009 ; Kasai, et al., 2008 )

. In addition, 27

severity data w ere only provided in the shorter term study. Sustained nasal damage may lead to 28

regenerative cell proliferation and tumor formation following chronic exposure. As discussed 29

above (Section 4.2.2.2.1), histopathological evidence of regenerative cell prolifera tion has been 30

seen following long

- term exposure to 1,4

- dioxane ( Kasai, et al., 2009 ; Kasai, et al., 2008 )

, and 31

observations of nasal tumors were also noted at the highest exposure concentration. Other 32

incidences of nasal damage may hav e occurred before tumor formation; however, temporal 33

information regarding these events was not available (i.e., interim blood samples not collected, 34

interim sacrifices were not performed). 35103

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.7.3.5. Biological Plausibility and Coherence

4.7.3.5.1. Liver

. The hypothesis tha t sustained proliferation of spontaneously transformed liver 1

cells is a key event within a MOA is possible based on supporting evidence indicating that 2

1,4

- dioxane is a tumor promoter of mouse skin and rat liver tumors ( Bull, et al., 1986 ; King, et 3

al., 1973 ; Lundberg, et al., 1987 ) . Further support for this hypothesis is provided by studies 4

demonstrating that 1,4

- dioxane increased hepatocyte DNA synthesis, indicative of cell 5

proliferation ( Goldsworthy, et al., 1991 ; Miyagawa, et al., 1999 ; Stott, et al., 1981 ; Uno, et al., 6

1994 )

. In addition, the generally negative results for 1,4

- dioxane in a number of genotoxicity 7

assays indicates the carcinogenicity of 1,4

- dioxane may not be mediated by a mutagenic MOA. 8

The importance of cytotoxicity as a necessary precursor to sustained cell proliferation is 9

biologically plausible, but is not s upported by the dose

- response in the majority of studies of 10

1,4

- dioxane carcinogenicity. 11

4.7.3.5.2. Nasal cavity

. Sustained cell proliferation in response to cell death from toxicity may 12

be related to the formation of nasal cavity tumors; however, this MOA is also not established . 13

Nasal carcinogens are generally characterized as potent genotoxins ( Ashby, 1994 ) ; however, 14

other MOAs have been proposed for nasal carcinogens that induce effects through other 15

mechanisms ( Green et al., 2000 ; Kasper et al., 2007 )

. 16

The National Toxicological Program (NTP) database identified 12 chemicals from 17

approximately 500 bioassays as nasal carcinogens and 1,4

- dioxane was the only identified nasal 18

carcinogen that s howed little evidence of genotoxicity ( Haseman & Hailey, 1997 ) . Nasal tumors 19

were not observed in an inhalation study in Wistar rats exposed to 111 ppm for 5 day s/week for 20

2 years ( Torkelson, et al., 1974 )

. 21

4.7.3.6. Other Possible Modes of Action

An alternate MOA could be hypothesized that 1,4

- dioxane alters DNA, either directly or 22

indirectly, which causes mutations in critical genes fo r tumor initiation, such as oncogenes or 23

tumor suppressor genes. Following these events, tumor growth may be promoted by a number of 24

molecular processes leading to enhanced cell proliferation or inhibition of programmed cell 25

death. The results from in vi tro and in vivo assays do not provide overwhelming support for the 26

hypothesis of a genotoxic MOA for 1,4

- dioxane carcinogenicity. The genotoxicity data for 27

1,4

- dioxane were reviewed in Section 4.5.1 and were summarized in Table 4

- 19 . Negative 28

findings we re reported for mutagenicity in Salmonella typhimurium

, Escherichia coli , and 29

Photobacterium phosphoreum (Mutatox assay) ( Haworth, et al., 1983 ; Hellmér & Bolcsfoldi, 30

1992 ; Khudoley, et al., 1987 ; Kwan, et al., 1990 ; Morita & Hayashi, 1998 ; Nestmann, et al., 31

1984 ; Stott, et al., 1981 ) . Negative results were also indicated for the induction of aneuploidy in 32

yeast ( Saccharomyces cerevisiae ) and the sex

- linked recessive lethal test in Drosophila 33

melanogaster ( Zimmermann, et al., 1985 ) . In contrast, positive results were reported in assays 34104

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE for sister chromatid exchange ( Galloway, et al., 1987 ) , DNA damage ( Kitchin & Brown, 1990 )

, 1

and in in vivo micronucleus formation in bone marrow ( Mirkova, 1994 ; Roy, et al., 2005 ) , and 2

liver ( Morita & Hayashi, 1998 ; Roy, et al., 2005 ) . Lastly, in the presence of toxicity, positive 3

results were reported for meiotic nondisjunction in drosophila ( Munoz & Barnett, 2002 ) , DNA 4

damage ( Sina, et al., 1983 ) , and cell transformation ( Sheu, et al., 1988 )

. 5

Additionally, 1,4

- dioxane metabolism did not produce reactive intermediates that 6

covalently bound to DNA ( Stott, et al., 1981 ; Woo, Argus, et al., 1977b ) and DNA repair assays 7

were generally negative ( Goldswort hy, et al., 1991 ; Stott, et al., 1981 ) . No studies were 8

available to assess the ability of 1,4

- dioxane or its metaboli tes to induce oxidative damage to 9

DNA. 10

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 11

available evidence in support of any hypothetical mode of carcinogenic action for 1,4

- diox ane is 12

inconclusive. A MOA hypothesis involving 1,4

- dioxane induced cell proliferation is possible 13

but data are not available to support this hypothesis. Pharmacokinetic data suggest that 14

clearance pathways were saturable and target organ toxicity occur s after metabolic saturation. 15

Liver toxicity preceded tumor formation in one study ( Kociba, et al., 1974 ) and a regenerat ive 16

response to tissue injury was demonstrated by histopathology. Liver hyperplasia and tumor 17

formation have also been observed in the absence of cytotoxicity ( JBRC, 1998 ; Kano, et al., 18

2009 ) . Cell proliferation an d tumor promotion have been shown to occur after prolonged 19

exposure to 1,4

- dioxane ( Bull, et al., 1986 ; Goldsworthy, et al., 1991 ; King, et al., 1973 ; 20

Lundberg, et al., 1987 ; Miyagawa, et al., 1999 ; Stott, et al., 1981 ; Uno, et al., 1994 )

. 21

4.7.3.7.2. Nasal cavity

. The MOA for the formation of nasal cavity tumors is unknown, and 22

evidence in support of any hypothetical mode of carcinogenic action for 1,4

- dioxane is 23

inconclusive. A MOA hypothesis involving nasal damage, cell prolifer ation, and hyperplasia is 24

possible, but data are not available to support this hypothesis. One or more of these events is 25

missing from the studies that examine nasal effects after exposure to 1,4

- dioxane. Nasal cavity 26

tumors have been reported in the abs ence of cell proliferation ( Kasai, et al., 200 9 ) and 27

hyperplasia ( JBRC, 1998 ; Kano, et al., 2009 )

. 28

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 29

been discussed along with the supporting evidence for each. As was stated, the MOA by which 30

1,4

- dioxane produces liver, nasal, peritoneal, and mammary gland tumors is unknown. Some 31

mechanistic information is available to inform the MOA of the liver and nasal tumors but no 32

information exists to inform the MOA of the observed peritoneal or mammary gland tumors 33

( JBRC, 1998 ; Kano, et al., 2009 ; Yamazaki, et al., 1994 )

. 34105

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4.8. SUSCEPTIBL E POPULATIONS AND LI FE STAGES

There is no direct evidence to establish that certain populations and lifestages may be 1

susceptible to 1,4

- dioxane. Changes in susceptibility with lifestage as a function of the presence 2

of microsomal enzymes that metabolize and detoxify this compound (i.e., CYP2E1 present in 3

liver, kidney, and nasal mucosa can be hypothesized). Vieira et al. ( 1996 ) reported that large 4

increases in hepatic C YP2E1 protein occur postnatally between 1 and 3 month s in humans. 5

Adult hepatic concentrations of CYP2E1 are achieved sometime between 1 and 10 years. To the 6

extent that hepatic CYP2E1 levels are lower, children may be more susceptible to liver toxicity 7

from 1,4

- dioxane than adults. CYP2E1 has been shown to be inducible in the rat fetus. The 8

level of CYP2E1 protein was increased by 1.4

- fold in the maternal liver and 2.4

- fold in the fetal 9

liver following ethanol treatment, as compared to the untreated or pair

- fed groups ( Carpenter, 10

Lasker, & Raucy, 1996 ) . Pre

- and postnatal induction of microsomal enzymes resulting from 11

exposure to 1,4

- dioxane or other drugs or chemicals may reduce overall toxicity following 12

sustained exposur e to 1,4

- dioxane. 13

Genetic polymorphisms have been identified for the human CYP2E1 gene ( Hayashi, 14

Watanabe, & Kawajiri, 1991 ; Watanabe, Hayashi, & Kawajiri, 1994 ) and were considered to be 15

possible factors in the abnormal liver function seen in workers exposed to vinyl chloride ( Huang, 16

Huan g, Cheng, Wang, & Hsieh, 1997 ) . Individuals with a CYP2E1 genetic polymorphism 17

resulting in increased expression of this enzyme may be less susceptible to toxicity following 18

exposure to 1,4

- dioxane. 19

Gender differences were noted in subchronic and chron ic toxicity studies of 1,4

- dioxane 20

in mice and rats (see Sections 4.6 and 4.7). No consistent pattern of gender sensitivity was 21

identified across studies. In a 13 week inhalation study of male and female rats ( Kasai, et al., 22

2008 ) kidney toxicity was observed in female rats exposed to 3,200 ppm of 1,4

- dioxane (i.e. 23

hydropic change in the renal proximal tubule s)

, but not male rats, which suggests a possible 24

increased susceptibility of female rats to renal damage following inhalation exposure to 25

1,4

- dioxane. 26106

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 5. DOSE

- RESPONSE ASSESSMENTS

5.1. ORAL REFERENCE DOSE (R f D)

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 1

exposure to 1,4

- dioxane in humans and laboratory animals. Occupational exposure to 2

1,4

- dioxane has resulted in hemorrhagic nephritis and c entrilobular necrosis of the liver ( Barber, 3

1934 ; Johnstone, 1959 ) . In animals, liver and kidney degeneration and necrosis were observed 4

frequently in acute oral and inhalation studies ( David, 1964 ; de Navasquez, 1935 ; Drew, et al., 5

1978 ; Fairley, et al., 1934 ; JBRC, 1998 ; Kesten, et al., 1939 ; Laug, et al., 1939 ; Schrenk & Yant, 6

1936 ) . Liver and kidney effects were also obser ved following chronic oral exposure to 7

1,4

- dioxane in animals ( Argus, et al., 1965 ; Argus, et al., 1973 ; JBRC, 1998 ; Kano, et al., 2009 ; 8

Kociba, et al., 1974 ; NCI, 1978 ; Yamazaki, et al., 1994 ) (see Table 4

- 21 ). 9

Liver toxicity in the available chronic st udies was characterized by necrosis, spongiosis 10

hepatic, hyperplasia, cyst formation, clear foci, and mixed cell foci. Kociba et al. ( 1974 ) 11

demonstrated hepatocellular degeneration and necrosis at doses of 94 mg /kg

- day (LOAEL in 12

male rats) or greater. The NOAEL for liver toxicity was 9.6 mg /kg

- day and 19 mg /kg

- day in 13

male and female rats, respectively. No quantitative incidence data were pr ovided in this study. 14

Argus et al. ( 1973 ) described early preneoplastic changes in the liver and JBRC ( 1998 ) 15

demonstrated liver lesions that are primarily associated with the carcinogenic process. Clear and 16

mixed

- cell foci in the liver are commonly considered preneoplastic changes and would not be 17

considered evidence of noncancer toxicity. In the JBRC ( 1998 ) study, spongiosis hepatis was 18

associated with other preneoplastic changes in the liver (clear and mixed

- cell foci) and no other 19

lesions indicative of liver toxicity were seen. Spongiosis hepatis was therefore not considered 20

indicative of noncancer effects in th is study. The activity of serum enzymes (i.e., AST, ALT, 21

LDH, and ALP) was increased in mice and rats chronically exposed to 1,4

- dioxane ( JBRC, 22

1998 ) ; however, these increases were seen only at tumorigenic dose levels. Blood samples were 23

collected at study termination and elevated serum enzymes may reflect changes associated with 24

tumor formation. Histopathological evidence of liver toxicity was not seen in rats from the 25

JBRC ( 1998 ) study. The highest non

- tumorigenic dose levels for this study approximated the 26

LOAEL derived from the Kociba et al. ( 1974 ) study (94 and 148 mg /kg

- day for male and female 27

rats, respectively). 28

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)

.107

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Kidney damage in chron ic toxicity studies was characterized by degeneration of the 1

cortical tubule cells, necrosis with hemorrhage, and glomerulonephritis ( Argus, et al., 1965 ; 2

Argus, et al., 1973 ; Fairley, et al., 1934 ; Kociba, et al., 1974 ; NCI, 1978 ) . Kociba et al. ( 1974 ) 3

described renal tubule epithelial cell degeneration and necrosis at doses of 94 mg /kg

- day 4

(LOAEL in male rats) or greater, with a NOAEL of 9.6 mg /kg

- day. No quantitative incidence 5

data were provided in this study ( Kociba, et al., 1974 ) . Doses of ≥ 430 mg /kg

- day 1,4

- dioxane 6

induced marked kidney alterations ( Argus, et al., 1973 ) . The observed changes included 7

glomerulonephritis and pyelonephritis, with characteristic epithelial proliferation of Bowman‘s 8

capsule, periglomerular fibrosis, and distension of tubules . Quantitative incidence data were not 9

provided in this study. In the NCI ( 1978 ) study, kidney lesions in rats consisted of vacuolar 10

degeneration and/or focal tubular epithelial regeneration in the proximal cortical tubules and 11

occasional hyaline casts. Kidney toxicity was not seen in rats from the JBRC ( 1998 ) study at any 12

dose level (highest dose was 274 mg /kg

- day in male rats and 429 mg /kg

- day in female rats). 13

Kociba et al. ( 1974 ) was chosen as the principal study for derivation of the RfD because 14

the liver an d kidney effects in this study are considered adverse and represent the most sensitive 15

effects identified in the database (NOAEL 9.6 mg /kg

- day, LOAEL 94 mg /kg

- day in male rats). 16

Kociba et al. ( 1974 ) reported degenerative effects in the liver, while liver lesions reported in 17

other studies ( Argus, et al., 1973 ; JBRC, 1998 ) ap peared to be related to the carcinogenic 18

process. Kociba et al. ( 1974 ) also reported degenerative changes in the kidney. NCI ( 1978 ) and 19

Argus et al. ( 1973 ) provided supporting data for this endpoint; however, kidney toxicity was 20

observed in these studies at higher doses. JBRC ( 1998 ) reported nasal inflammation in rats 21

(NOAEL 55 mg /kg

- day, LOAEL 274 mg /kg

- day) and mice (NOAEL 66 mg /kg

- day, LOAEL 22

278 mg /kg

- day). 23

Even though the study reported by Kociba et al. ( 1974 ) had one noteworthy weakness, it 24

had several noted strengths

, includ ing : (1) two

- year study duration; (2) use of both male and 25

female rats and three dose levels, 10

- fold apart, plus a control group; (3) a sufficient number of 26

animals per dose group (60 animals/sex/dose group; and (4) the authors conducted a 27

comprehensive evalu ation of the animals including body weights and clinical observations, blood 28

samples, organ weights of all the major tissues, and a complete histopathological examination of 29

all rats. T he authors did not report individual incidence data that would have al lowed for a BMD 30

analysis of this robust dataset. 31

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 32

fit of the model to the empirical model output or experimental obse rvations could be attained 33

using biologically plausible values for the model parameters. The re

- calibrated model 34

predictions for blood 1,4

- dioxane levels did not come within 10

- fold of the experimental values 35108

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE using measured tissue:air partition coefficien ts of Leung and Paustenbach ( 1990 ) or Sweeney 1

et al. ( 2008 ) (Figures B

- 8 and B

- 9). The utilization of a slowly perfused tissue:air partition 2

coefficient 10

- fold lower than measured values produces exposure

- phase predictions that are 3

much closer to observations, but does not replicate the elimination kinetics ( Fig ure B

- 10). Re

4

calibration of the model with upper bounds on the tissue:air partition coefficients results in 5

predictions that are still six

- to sevenfold lower than empirical model prediction or observations 6

(Figures B

- 12 and B

- 13). Exploration of the mo del space using an assumption of zero

- order 7

metabolism (valid for the 50 ppm inhalation exposure) showed that an adequate fit to the 8

exposure and elimination data can be achieved only when unrealistically low values are assumed 9

for the slowly perfused tiss ue:air partition coefficient ( Figure B

- 16). Artificially low values for 10

the other tissue:air partition coefficients are not expected to improve the model fit, as these 11

parameters are shown in the sensitivity analysis to exert less influence on blood 1,4

- d ioxane than 12

V maxC and K

m . This suggests that the model structure is insufficient to capture the apparent 10

- 13

fold species difference in the blood 1,4

- dioxane between rats and humans. In the absence of 14

actual measurements for the human slowly perfused tiss ue:air partition coefficient, high 15

uncertainty exists for this model parameter value. Differences in the ability of rat and human 16

blood to bind 1,4

- dioxane may contribute to the difference in V d . However, this is expected to 17

be evident in very different values for rat and human blood:air partition coefficients, which is not 18

the case ( Table B

- 1). Therefore, some other, as yet unknown, modification to model structure 19

may be necessary. 20

Kociba et al. ( 1974 ) did not provide quantitative incidence or severity data for liver and 21

kidney degeneration and necrosis. Benchmark dose (BMD) modeling could not be performed 22

for this study and the NOAEL for liver and kidney degeneration (9.6 mg /kg

- day in male rats) 23

was used as the point of departure (POD) in deriving the RfD for 1,4

- dioxane. 24

Alternative PODs were calculated using incidence data reported for cortical tubule 25

degeneration in male and female rats ( NCI, 1978 ) and liver hyperplasia ( JBRC, 1998 ) . The 26

incidence data for cortical tubule cell degeneration in male and female rats exposed to 27

1,4

- dioxane in the drinking water for 2 years are presented in Table 5

- 1. Details of the BMD 28

analysis of these data are presented in Appendix C. Male rats were more sensitive to the kidney 29

effects of 1,4

- dioxane than females and the male rat data provided the lowest POD for cortical 30

tubule degeneration in the NCI ( 1978 ) study (BMDL 10 of 22.3 mg /kg

- day) ( Table 5

- 2). 31

Incidence data ( JBRC, 1998 ; Kano, et al., 2009 ) for liver hyperplasia in male and female rats 32

exposed to 1,4

- dioxane in the drinking water for 2 years are presented in Table 5

- 3. Details of 33

the BMD analysis of these data are presented in Appendix C. Male rats were more sensitive to 34

developing liver hyperplasia due to exposure to 1,4

- dioxane than females and the male rat data 35

provided the lowest POD for hyperplasia in the JBR C ( 1998 ) study (BMDL 10 of 23.8 mg /kg

36

day) ( Table 5

- 4). The BMDL 10 values of 22.3 mg /kg

- day and 23.8 mg /kg

- day from the NCI 37109

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ( 1978 ) and JBRC ( 1998 ) studies, respectively, are about double the NOAEL (9.6 mg /kg

- day) 1

observed by Kociba et al. ( 1974 )

. 2

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

0/31 a 20/31 b 27/33 b 0/31 a 0/34 10/32 b

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 )

.

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

BMD 10 (mg/kg

- day) BMDL 10 (mg/kg

- day)

Male rats 28.8 22.3

Female rats 596.4 452.4

Source: NCI ( 1978 )

.

Table 5

- 3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to

1,4

- dioxane in drinking water for 2 years a

Males (mg/kg

- day) Females (mg/kg

- day)

0 11 55 274 0 18 83 429

3/40 2/45 9/ 35 b 12/ 22 c 0/ 38 b 0/37 1/38 14/ 24 c

a Dose information from Kano et al. ( 2009 ) and incidence data for sacrificed animals from JBRC ( 1998 )

. 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 ) ; JBRC ( 1998 )

.110

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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

BMD 10 (mg/kg

- day) BMDL 10 (mg/kg

- day)

Male rats 35.9 23.8

Female rats 137.3 88.5

Source: Kano et al. ( 2009 ) ; JBRC ( 1998 )

.

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

1,4

- dioxane in the drinking water for 2 years ( Kociba, et al ., 1974 ) . The Kociba et al. ( 1974 ) 2

study was chosen as the principal study because it provides the most sensitive measure of 3

adverse eff

ects by 1,4

- dioxane. The incidence of liver and kidney lesions was not reported for 4

each dose group. Therefore, BMD modeling could not be used to derive a POD. The RfD for 5

1,4

- dioxane is derived by dividing the NOAEL of 9.6 mg /kg

- day ( Kociba, et al., 1974 ) by a 6

composite UF of 300, as follows: 7

RfD

= NOAEL / UF 8

= 9.6 mg /kg

- day / 300 9

= 0.03 or 3 × 10

– 2 mg /kg

- day 10

The composite UF of 300 includes factors of 10 for animal

- to

- human extrapolation and 11

for interindividual variability, and an UF of 3 for database deficiencies. 12

A default interspecies UF of 10 was used to account for pharmacokinetic and 13

pharmacodynamic differences across species. Existing PBPK models could not be used to derive 14

an oral RfD for 1,4

- dioxane ( Appendix B). 15

A default interindividual variability UF of 10 was used to account for variation in 16

sensitivity within human populations because there is limited information on the degree to which 17

humans of varying gender, age, health status, or genetic makeup might vary in the disposition of, 18

or response to, 1,4

- dioxane. 19

An UF of 3 for database deficiencies was applied due to the lack of a multigeneration 20

reproductive toxicity study. A single oral prenatal developmental toxicity study in rats was 21

available for 1,4

- dioxane ( Giavini, et al., 1985 ) . This developmental study indicates that the 22

developing fetus may be a target of toxicity. 23

An UF to e xtrapolate from a subchronic to a chronic exposure duration was not necessary 24

because the RfD was derived from a study using a chronic exposure protocol. 25

An UF to extrapolate from a LOAEL to a NOAEL was not necessary because the RfD 26

was based on a NOAEL. Kociba et al. ( 1974 ) was a well

- conducted, chronic drinking water 27111

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE study with an adequate number of animals. Histopathological examination w as performed for 1

many organs and tissues, but clinical chemistry analysis was not performed. NOAEL and 2

LOAEL values were derived by the study authors based on liver and kidney toxicity ; however 3

quantitative incidence data was not reported . Several additi onal oral studies (acute/short

- term, 4

subchronic, and chronic durations) were available that support liver and kidney toxicity as the 5

critical effect ( Argus, et al., 1973 ; JBRC, 1998 ; Kano, et al., 2008 ; NCI, 1978 ) ( Tables 4

- 15 and 6

4

- 17). Although degenerative liver and kidney toxicity was not observed in rats from the JBRC 7

( 1998 ) study at doses at or below the LOAEL in the Kociba et al. ( 1974 ) study, other endpoints 8

such as metaplasia and hyperplasia of the nasal epithelium, nuclear enlargement, and 9

hematological effects, were noted. 10

5.1.4. RfD Compariso n Information

PODs and sample oral RfDs based on selected studies included in Table 4

- 1 8 are arrayed 11

in Figures 5

- 1 to 5

- 3, and provide perspective on the RfD supported by Kociba et al. ( 1974 )

. 12

These figures should be interpreted with caution because the PODs across studies are not 13

necessarily comparable, nor is the confidence in the data sets from which the PODs were derived 14

the same. PODs in these figures may be based on a NOAEL, LOAEL, or BMDL (as indicated), 15

and the nature, severity, and incidence of effects occurring at a LOAEL are likely to vary. To 16

some extent, the confidence associated with the resulting sample RfD is reflected in the 17

magnitude of the total UF applied to the POD (i.e., the size of the bar); however, the text of 18

Sections 5.1.1 and 5.1.2 should be consulted for a more complete understanding of the issues 19

associated with each data set and the rationale for the sele ction of the critical effect and principal 20

study used to derive the RfD. 21

The predominant noncancer effect of chronic oral exposure to 1,4

- dioxane is 22

degenerative effects in the liver and kidney. Figure 5

- 1 provides a graphical display of effects 23

that were observed in the liver following chronic oral exposure to 1,4

- dioxane. Information 24

presented includes the PODs and UFs that could be considered in deriving the oral RfD. As 25

discussed in Sections 5.1.1 and 5.1.2, among those studies that demonstrated live r toxicity, the 26

study by Kociba et al. ( 1974 ) provided the data set most appropriate for deriving the RfD. For 27

degenerative liver effects r esulting from 1,4

- dioxane exposure, the Kociba et al. ( 1974 ) study 28

represents the most sensitive effect and dataset observed in a chronic bi oassay ( Figure 5

- 1). 29

Kidney toxicity as evidenced by glomerulonephritis ( Argus, et al., 1965 ; Argus, et al., 30

1973 ) and degeneration of the cortical tubule ( Kociba, et al., 1974 ; NCI, 1978 ) has also been 31

observed in response to chronic exposure to 1,4

- dioxane. As was discussed in Sections 5.1 and 32

5.2, degenerative effects were observed in the kidney at the same dose level as effects in the liver 33

( Kociba, et al., 1974 ) . A comparison of the a vailable datasets from which an RfD could 34

potentially be derived is presented in Figure 5

- 2. 35112

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Rhinitis and inflammation of the nasal cavity were reported in both the NCI ( 1978 ) (mice 1

only, dose ≥ 380 mg /kg

- day) and JBRC ( 1998 ) studies (≥ 274 mg /kg

- day in rats, >278 mg /kg

2

day in mice). JBRC ( 1998 ) reported nasal inflammation in rats (NOAEL 55 mg /kg

- day, LOAEL 3

274 mg /kg

- day) and mice (N OAEL 66 mg /kg

- day, LOAEL 278 mg /kg

- day). A comparison of 4

the available datasets from which an RfD could potentially be derived is presented in Figure 5

- 3. 5

Figure 5

- 4 displays PODs for the major targets of toxicity associated with oral exposure 6

to 1,4

- diox ane. Studies in experimental animals have also found that relatively high doses of 7

1,4

- dioxane (1,000 mg /kg

- day) during gestation can produce delayed ossification of the 8

sternebrae and reduced fetal BWs ( Giavini, et al., 1985 ) . This graphical display ( Figure 5

- 4) 9

compares organ specific t oxicity for 1,4

- dioxane, including a single developmental study. The 10

most sensitive measures of degenerative liver are and kidney effects. The sample RfDs for 11

degenerative liver and kidney effects are identical since they were derived from the same study 12

and dataset ( Kociba, et al., 1974 ) and are presented for completeness. 13

Figure 5

- 1. Potential p oints of departure (POD) for liver toxicity endpoints

with corresponding applied uncertainty factors and derived RfDs following

oral exposure to 1,4

- dioxane.113

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure 5

- 2. P otential p oints of departure (POD) for kidney toxicity endpoints

with correspondin g applied uncertainty factors and derived RfDs following

oral exposure to 1,4

- dioxane.114

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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.115

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 f

or 1,4

- dioxane was previously posted on the IRIS database in 1988. An 1

oral RfD was not developed as part of the 1988 assessment. 2

5.2. INHALATION REFERENCE CONCENTRATION (RFC)

5.2.1. Choice of Principal Studies and Critical Effect(s) with Rationale and Justification

T wo human studies of occupational exposure to 1,4

- dioxane have been published 3

( Buffler, et al., 1978 ; Thiess, et al., 1976 ) ; however, neither study provides sufficient in formation 4

and data to quantify subchronic or chronic noncancer effects. In each study, findings were 5

inconclusive and the cohort size and number of reported cases were limited ( Buffler, et al., 1978 ; 6

Thiess, et al., 1976 )

. 7

Four inhalation studies in animals we re identified in the literature; two

, 13

- week 8

subchronic studies in laboratory animals ( Fairley, et al., 1934 ; Kasai, et al., 2008 ) and two

, 2

- 9

year ch ronic studies in rats ( Kasai, et al., 2009 ; Torkelson, et al., 1974 )

. 10116

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE In the subchronic study by Fairley et al. ( 1934 ) rabbits, guinea pigs, rats, and mice 1

(3

- 6/species/group) were exposed to 1,000, 2,000, 5 ,000, or 10,000 ppm of 1,4

- dioxane vapor for 2

1.5 hours two times a day for 5 days, 1.5 hours for one day, and no exposure on the seventh day. 3

Animals were exposed until death occurred or were sacrificed after various durations of exposure 4

(3

- 202.5 hours). Detailed dose

- response information was not provided; however, severe liver 5

and kidney damage and acute vascular congestion of the lungs were observed at concentrations ≥ 6

1,000 ppm. Kidney damage was described as patchy degeneration of cortical tubules w ith 7

vascular congestion and hemorrhage. Liver lesions varied from cloudy hepatocyte swelling to 8

large areas of necrosis. In this study, a LOAEL of 1,000 ppm for liver and kidney degeneration 9

in rats, mice, rabbits, and guinea pigs was identified by the E PA. 10

In the subchronic study by Kasai et al. ( 2008 ) male and female rats (10/group/sex) were 11

exposed to 0, 100, 200, 400, 800, 1,600, 3,200, and 6,400 ppm of 1,4

- dioxane for 6 hours/day, 5 12

days/week for 13 weeks. This study observed a range of 1,4

- dioxane induced nonneoplastic 13

effects across several org an systems including the liver and respiratory tract (from the nose to the 14

bronchus regio n) in both sexes and the kidney in female s. Detailed dose

- response information 15

was provided, illustrating a concentration

- dependent increase of nuclear enlargement of nasal 16

(respiratory and olfactory)

, trachea, and bronchus epithelial cells (both sexes); vacuolic change 17

of nasal and bronchial epitheli al cells (both sexes) , necrosis and centrilobular swelling of 18

hepatocytes (both sexes) ; and hydropic change in the proximal tubules of the kidney (females). 19

The study authors determined nuclear enlargement of the nasal respiratory epithelium as the 20

most sensitive lesion and a LOAEL o f 100 ppm was identified based on this effect

. 21

Torkelson et al. ( 1974 ) performed a chronic inhalation study in which male and female 22

Wistar rats (288/sex) were exposed to 111 ppm 1,4

- dioxane vapor for 7 hours/day, 5 days/week 23

for 2 years. Control rats (192/sex) wer e exposed to filtered air. No significant effects were 24

observed on BWs, survival, organ weights, hematology, clinical chemistry, or histopathology. 25

A free standing NOAEL of 111 ppm was identified in this study by EPA

. 26

Kasai et al. ( 2009 ) reported data for groups of male F344 rats (50/group) exposed to 0, 27

50, 2 50, and 1,250 ppm of 1,4

- dioxane for 6 hours/day, 5 days/week, for 2 years. In contrast to 28

the subchronic Kasai et al. (2008) study , this 2

- year bioassay reported more nonneoplastic effects 29

in multiple organ systems

. A dditional noted incidences included: (1) inflammation of nasal 30

respiratory and olfactory epithelium, (2) squamous cell metaplasia and hyperplasia of nasal 31

respiratory epithelium, (3) atrophy and respiratory metaplasia of olfactory epithelium, (4) 32

hydropic change and sclerosis in lam ina propria of nasal cavity , (5) nuclear enlargement in 33

proximal tubules of kidney and in centrilobular of liver, (6) centrilobular necrosis in the liver, 34

and (7) spongiosis hepatis . Some of these histopathological lesions were significantly increased 35

com

pared to controls at the lowest exposure level (50 ppm), including nuclear enlargement of 36

respir atory and olfactory epithelium; and atrophy and respiratory metaplasia of olfactory 37117

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE epithelium. Many of these histopathological lesions were increased in a con centration

- dependent 1

manner. 2

Because Fairley et al. ( 1934 ) did not present the statistics of th e dose response data

, and 3

Torkelson et al. ( 1974 ) identified a free

- standing NOAEL only, neither study was sufficient to 4

characterize the inhalation risks of 1,4

- dioxane. A route extrapolation from oral toxicity data 5

was not performed because 1,4

- dioxane inhalation causes direct effects on the respirato ry tract 6

(i.e., respiratory irritation in humans, pulmonary congestion in animals) ( Fairley, et al., 1934 ; 7

Wirth & Klimmer, 1936 ; Yant, et al., 1930 ) , which would not be accounted for in a cross

- route 8

extrapolation. In addition, available kinetic model s are not suitable for this purpose (Appendix 9

B). 10

The chronic Kasai et al. ( 2009 ) study was selected as the principal study for the 11

derivation of the RfC. Based on the noncancer database for 1,4

- dioxane, this study demonstrated 12

exposure concentration

- related effects for histopathological lesions at lower doses as compared 13

to the subchronic Kasai et al. study ( 2008 ) . In addition, the Kasai et al. ( 2009 ) 2

- year bioassay 14

study utilized 50 animals per exposure group, a range of exposure concen trations which were 15

based on the results of the subchronic study ( 2008 ) and thoroughly examined toxicity of 1

- 16

4,dioxane in m ultiple organ systems. This 2

- year bioassay ( Kasai, et al., 2009 ) did not observe 17

effects in both sexes, but the use of only male rats was proposed by the study authors as justified 18

by data illustrating the absence of induced mesotheliomas in female rats following exposure to 19

1,4

- diox a ne in drinki ng water ( Yama zaki, et al., 1994 )

. 20

All systemic and portal

- of

- entry nonneoplastic lesions from the Kasai et al. ( 2009 ) study 21

that were statistically increased at the low

- or mid

- exposure concentration (50 or 250 ppm) 22

compared to controls, or the lesions that demonstrated a dose

- response relationship in the 23

absence of statis tical significance were considered candidates for the critical effect. The 24

candidate endpoints included centrilobular necrosis of the liver

, spongiosis hepatis , squamous 25

cell metaplasia of nasal respiratory epithelium , squamous cell hyperplasia of nasal respiratory 26

epithelium , respiratory metaplasia of nasal olfactory epithelium , sclerosis in lamina propria of 27

nasal cavity , and two degenerative nasal lesions, that is, atrophy of nasal olfactory epithelium 28

and hydropic change in the lamina propri a (Table 5

- 5 ). Despite statistical increases at the low

29

and mid exposure concentrations, incidences of nuclear enlargement of respiratory epithelium 30

(nasal cavity ), olfactory epithelium (nasal cavity), and proximal tubule (kidney) were not 31

considered can didates for the critical effect given that the toxicological significance of nuclear 32

enlargement is uncertain (See Section 4.6.2 and Table 4

- 22)

. 33118

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 5

- 5 . Incidences of nonneoplastic lesions resulting from chronic

exposure (ppm) to 1,4

- dioxane considere d for identification of a critical

effect.

Species/Strain Tissue Endpoint Concentration (ppm)

0 50 250 1250

Rat/ F344 (male) Liver Centrilobular necrosis 1/50 3/50 6/50 12/50 a

Spongiosis hepatis 7/50 6/50 13/50 19/50 a

Nasal Squamous cell metaplasia;

respiratory epithelium 0/50 0/50 7/50 b 44/50 a

Squamous cell hyperplasia;

respiratory epithelium 0/50 0/50 1/50 10/50 a

Respiratory metaplasia;

olfactory epithelium 11/50 34/50 a 49/50 a 48/50 a

Atrophy; olfactory epithelium 0/50 40/50 a 47/50 a 48/50 a

Hydropic change;

lamina propria 0/50 2/50 36/50 a 49/50 a

Sclerosis; lamina propria 0/50 0/50 22/50 a 40/50 a

a p≤ 0.01 by Fisher‘s exact test.

b p≤ 0.05 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

5.2.2. Methods of Analysis

Benchmark dose (BMD) modeling methodology ( U.S. EPA, 2000a ) was used to analyze 1

the candidate endpoints identified for 1,4

- dioxane. Use of BMD methods involves fitting 2

mathematical models to the observed dose

- response data and provides a BMD and its 95% lower 3

confidence limit (BMDL) associated with a predetermined benchmark response (BMR ). The 4

suitability of these methods to determine a POD is dependent on the nature of the toxicity 5

database for a specific chemical. For 1,4

- dioxane, the selected datasets in Table 5

- 5 were 6

analyzed using BMD modeling. Information regarding the degree of change in the selected 7

endpoints that is considered biologically significant was not available. Therefore, a BMR of 8

10% extra risk was selected under the assumption that it represents a mimimally biologically 9

significant response level ( U.S. EPA, 2000a )

. 10

BMD model results were inadequate (poo r fit and/or substantial model uncertainty

– see 11

Appendix F) for the following nasal lesions: atrophy (olfactory epithelium), respiratory 12

metaplasia (olfactory epithelium), and sclerosis (lamina propria). Considering the datasets for 13

atrophy and respirato ry metaplasia, in which the first non

- control dose had a response level 14

substantially above the desired BMR, the use of BMD methods included substantial model 15

uncertainty (Appendix F). The detailed results of the BMDS analysis are provided in Appendix 16119

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE F. Consequently, NOAELs and LOAELs were used as potential PODs for the endpoints not 1

suitable for BMD modeling. 2

5.2.3. Exposure Duration and Dosimetric Adjustments

Because an RfC is a measure that assumes continuous human exposure over a lifetime, 3

data derived from animal studies need to be adjusted to account for the noncontinuous exposure 4

protocols used in animal studies. In the Kasai et al. ( 2009 ) study, rats were exposed to 1,4

- 5

dioxane for 6 hours/day, 5 days/week for 2 years. Therefore, the duration

- adjusted PODs for 6

nasal and systemic lesions in rats were calculated as follows: 7

8

RfCs are typically expressed in units of mg/ m 3 ; so PODADJ (ppm) values were 9

converted using the chemical specific conversion factor of 1 ppm = 3.6 mg/m 3 for 1,4

- dioxane 10

(Table 2

- 1). The following calculation was used: 11

12

The calculated POD ADJ (mg/m 3 ) values for all considered en dpoints are presented in the 13

last column of Table 5

- 6. 14

Table 5

- 6 . Duration adjusted POD estimates for best fitting BMDS models or

NOAEL/LOAEL from chronic exposure to 1,4

- dioxane

Endpoint NOAEL a

(ppm) LOAEL b

(ppm) Model BMR BMD

(ppm) BMDL

(ppm) POD ADJ

(mg/m 3 )

Nasal Effects

Squamous cell

metaplasia; respiratory

epithelium 50 250 Log

- probit 10 218 160 103

Squamous cell

hyperplasia; respiratory

epithelium 250 1250 Log

- probit 10 756 561 361

Respiratory metaplasia;

olfactory epithelium -- 50

-- c

-- -- -- 32.2

Atrophy; olfactory

epithelium -- 50

-- c

-- -- -- 32.2

Hydropic change;

lamina propria 50 250 Log

- logistic 10 69 47 30.2

Sclerosis; lamina

propria 50 250

-- c

-- -- -- 32.2

Systemic Effects

Centrilobular necrosis;

Liver 250 1250 Dichotomous

Hill 10 220 60 38.6

Spongiosis hepatis;

Liver 250 1250 Log

- logistic d 10 314 172 11 1120

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE a NOAEL is identified as the highest tested exposure dose at which there is no statistically significant effect in the

exposed group as compared to control.

b LOAEL is identified as the lowest tested exposure dose at which there is a statistically significant effect in the

exposed group as compared to control.

c BMDS model results are not adequate for use to derive a POD. Therefore, NOAEL/LOAEL approach is

recommended t o determine a POD ADJ for these endpoints. BMDS analysis for these endpoints is included in

Appendix F.

d Dichotomous Hill model had lowest BMDL, but model output warned that the BMDL estimate was ―imprecise at

best‖.

Based on analysis of data in Table 5

- 5, hydropic change, atrophy, and respiratory 1

metaplasia were a considered for selection of the critical effect. Typically, chemical

- induced 2

nasal effects include atrophy and/or necrosis, cell proliferation/hyperplasia, and metaplasia 3

depending on the nature of the tissue damage and exposure ( Boorman, Morgan, & Uriah, 1990 ; 4

Gaskell, 1990 ; Harkema, Carey, & Wagner, 2006 ) . These effects are often accompanied by an 5

inflammatory response. BMD analysis indicated hydropic change of lamina propria was the 6

most sensitive endpoint. Hydropic change and atrophy were the two degenerative nasal lesions 7

observed (Table 5

- 5); however, because hydro pic change has a NOAEL (i.e., 50 ppm) and a 8

calculated BMDL (i.e., 47 ppm) at an exposure concentration equivalent to the LOAEL (i.e., 50 9

ppm) designated for other nasal lesions (i.e., atrophy and respiratory metaplasia), hydropic 10

change was not selected a s the critical effect. Therefore, in this assessment the LOAEL approach 11

is the preferred methodology for selection of the critical effect and POD. 12

Using the LOAEL approach, atrophy and respiratory metaplasia of the olfactory 13

epithelium are identified as the most sensitive endpoints with a POD ADJ of 32.2 mg/m 3 . Since 14

atrophy of the olfactory epithelium had an increased incidence rate at the LOAEL compared to 15

respiratory metaplasia and is likely to occur earlier in the continuum of pathological events 16

assoc iated with respiratory tract effects, it is selected as the critical effect in this assessment. 17

For the derivation of a RfC based upon an animal study, the selected POD must be 18

adjusted to reflect the human equivalent concentration (HEC)

. The HEC was calculated by the 19

application of the appropriate dosimetric adjustment factor (DAF), in accordance with the U.S. 20

EPA RfC methodology ( U.S. EPA, 1994b ) . DAFs are ratios of animal and human physiologic 21

parameters, and are dependent on the nature of the contaminant (particle or gas) and the target 22

site (e.g., respiratory tract or remote to the portal

- of

- entry) ( U.S. EPA, 1994b )

. 23

1,4

- Dioxane is miscible with water and has a high blood:air partition coefficient. 24

Typically, highly water

- soluble and directly reactive chemicals (i.e. Category 1 gases) partition 25

greatly into the upper respiratory tract, induce portal

- of

- entry effects, and do not accumulate 26

significantly in the blood. 1,4

- Dioxane induces both systemic and portal of entry effects and has 27

been measured in the blood after inhalation exposure ( Kasai, et al., 2008 ) . The observations of 28

systemic (i.e., nonrespiratory) effects and measured blood levels resulting from 1,4

- dioxane 29

exposure clearly indicate that this compound is absorbed into the bloodstream and distributed 30121

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE throughout the body. Furthermore, the lack of an anterior to poster ior gradien t for the nasal 1

effects induced by 1,4

- dioxane is not typical of chemicals which are predominantly directly 2

reactive. Thus, 1,4

- dioxane might be best described as a water

- soluble and non

- directly reactive 3

gas. Gases such as these are readily taken up int o respiratory tract tissues and can also diffuse 4

into the blood capillaries ( Medinsky & Bond, 2001 ) . The effects in the olfactory epithelium may 5

be the result of the metabolism of 1,4

- dioxane to an acid metabolite; however, for the reasons 6

stated above it is unclear whether or not these effects are solely the result of portal

- of

- entry or 7

systemic delivery. A similar pattern of systemic effects (i.e., respiratory tract effects) were 8

observed after oral exposure to 1,4

- dioxane . 9

Consequently, for dosimetric purposes, the human equivalent concentration (HEC) for 10

1,4

- dioxane was calculated by the application of the appropriate dosimetric adjustment factor 11

(DAF) for systemic acting gases (i.e. Category 3 gases), in accord ance with the U.S. EPA RfC 12

methodology ( U.S. EPA, 1994b ) as follows: 13

14

DAF = (Hb/g)A/(Hb/g)H 15

where: 16

(Hb/g) A = the animal blood:air partition coefficient =1861 ( Sweeney, et al., 2008 ) 17

(Hb/g) H = the human blood:air partition coefficient =1666 ( Sweeney, et al., 2008 ) 18

DAF = 1861/1666 19

DAF = 1.12 20

21

Given that the animal blood:air partition coefficient is higher than the human value 22

resulting in a DAF>1, a default value of 1 is substituted in accordance with the U.S. EPA RfC 23

methodology ( U.S. EPA, 1994b ) . Analysis of the existing inhalation dosimetry m odeling 24

database supports the application of a DAF of 1 to be appropriate ( U.S. EPA, 2009a )

. 25

Application of these models to gases that have similar physicochemical properties and induce 26

similar nasa l effects as 1,4

- dioxane estimate DAFs ≥ 1. 27

Utilizing a DAF of 1, the HEC for atrophy of the olfactory epithelium in male 28

F344/DuCrj rats is calculated as follows: 29

30

POD HEC (mg/m 3 ) = POD ADJ (mg/m 3 ) × DAF 31

= POD ADJ (mg/m 3 ) × 1.0 32

= 32.2 mg/m 3 × 1.0 33

= 32.2 mg/m 3 34

35

Therefore, the POD HEC of 32.2 mg/m 3 for the critical effect of atrophy of the olfactory 36

epithelium is used for the derivation of a RfC for 1,4

- dioxane. 37122

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 5.2.4. RfC Derivation

- Including Application of Uncertainty Factors (UFs)

The RfC of 3 × 10

– 2 mg/m 3 is based on atrophy of the olfactory epithelium in male rats 1

exposed to 1,4

- dioxane via inhalation for 2 years ( Kasai, et al., 2009 ) . The RfC for 1,4

- dioxane is 2

derived by dividing the POD HEC for 1,4

- dioxane by a composite UF of 1000. 3

4

RfC = POD HEC / UF 5

= 32.2 mg/m 3 / 1000 6

= 0.0322 or 3 × 10

– 2 mg/m 3 7

8

The composite UF of 1000 includes factors of 10 for LOAEL

- to

- NOAEL extrapolation 9

and for human interindividual variability, and factors of 3 w ere used for animal

- to

- human 10

extrapolation and for database deficiencies. 11

An UF of 10 was used to extrapolate from a LOAEL to a NOAEL given significant 12

incidence data reported at the lowest tested concentration for this endpoint. A NOAEL for 13

atrophy of the olfactory epithelium was not identified in this study. Adequate BMD model 14

estimates were not available for derivation of the RfC, and since a NOAEL was not identified for 15

atrophy of the olfactory epithelium, the LOAEL (lowest dose tested in the study by Kasai et al. 16

( 2009 ) ) was chosen as the POD. 17

A default interindividual variability UF of 10 was used to account for variation in 18

sensitivity within human populations beca use there is limited information on the degree to which 19

humans of varying gender, age, health status, or genetic makeup might vary in the disposition of, 20

or response to, 1,4

- dioxane. 21

An UF of 3 was used to for animal

- to

- human extrapolation to account for 22

p harmacodynamic differences between species. This uncertainty factor for animal

- to

- human 23

extrapolation is comprised of two separate and equal areas of uncertainty to account for 24

difference in the toxicokinetics and toxicodynamics of animals and humans. In this assessment, 25

the toxicokinetic uncertainty was accounted for by the calculation of a HEC by the application of 26

a dosimetric adjustment factor as outlined in the RfC methodology ( U.S. EPA, 1994b ) . As the 27

toxicokinetic differences are thus accounted for, only the toxicodynamic uncertainties remain, 28

and an UF of 3 is retained to account for this uncertainty. 29

An UF of 3 for database deficiencies was applied due to the lack of a multigeneration 30

reproductive toxicity study. The oral toxicity database included a single prenatal developmental 31

study that indicated the developing fetus may be a target of toxicity ( Giavini, et al., 1985 ) 32

An UF to extrapolate from a subchronic to a chronic exposure duration was not necessary 33

because the RfC was derived from a study using a chronic exposure protocol. 34123

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 5.2.5. RfC Comparison Information

Figure 5

- 5 presents PODs, applied UFs, and derived sample RfCs for possible endpoints 1

from the chronic inhalation Kasai et al. ( 2009 ) in male rats. The PODs are based on the BMDL 10 , 2

NOAEL, or LOAEL and appropriate unit conversion and duration and dosimetric adjustments 3

were applied before applications of uncertainty factors. 4

Figure 5

- 5 . Potential points of departure (POD) for candidate endpoints with

corresponding applied uncertainty factors and derived sample RfCs

following inhalation exposure to 1,4

- dioxane.

Source: Kasai et al. ( 2009 )

5.2.6. Previous RfC Assessment

An assessment for 1,4

- dioxan e was previously posted on the IRIS database in 1988 and 5

2010. An inhalation RfC was not developed as part of either the 1988 or 2010 assessment. 6

5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE AND INHALATION

REFERENCE CONCENTRAT ION

Risk assessments need to po rtray associated uncertainty. The following discussion 7

identifies uncertainties associated with the RfD and RfC for 1,4

- dioxane. As presented earlier in 8

this section ( see Sections 5.1.2

, 5.1.3 for the RfD and Sections 5.2.2, and 5.2.3 for the RfC ), the 9

uncertainty factor approach ( U.S. EPA, 1994b

, 2002a ) was used to derive the RfD and RfC for 10124

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1,4

- dioxane

. Using this approach, the POD was divided by a set of factors to account for 1

uncertainties associated with a number of steps in the analys is, including extrapolation from 2

LOAEL to NOAEL exposure and responses observed in animal bioassays to humans, a diverse 3

popu lation of varying susceptibilities, and to account for database deficiencies. Because 4

information specific to 1,4

- dioxane was unavailable to fully inform many of these extrapolations, 5

default factors were generally applied. 6

An adequate range of animal tox icology data are available for the hazard assessment of 7

1,4

- dioxane, as described throughout the previous section ( Section 4). The database of oral 8

toxicity studies includes chronic drinking water studies in rats and mice, multiple subchronic 9

drinking water studies conducted in rats and mice, and a developmental study in rats. Toxicity 10

associated with oral exposure to 1,4

- d ioxane is observed predominately in the liver and kidney. 11

The database of inhalation toxicity studies in animals includes two subchronic bioassay s in 12

rabbits, guinea pigs, mice, and rats, and two chronic inhalation bioassay s in rats. Toxicity 13

associated with inhalation exposure to 1,4

- dioxane was observed predominately in the liver and 14

nasal cavity. In addition to oral and inhalation data, there are PBPK models and genotoxicity 15

studies of 1,4

- dioxane. Critical data gaps have been identified and uncertai nties associated with 16

data deficiencies of 1,4

- dioxane are more fully discussed below. 17

Consideration of the available dose

- response data led to the selection of the two

- year 18

drinking water bioassay in Sherman rats ( Kociba, et al., 1974 ) as the principal study and 19

increased liver and kidney degeneration as the critical effects for deriving the RfD for 20

1,4

- dioxane. The dose

- re sponse relationship for oral exposure to 1,4

- dioxane and cortical tubule 21

degeneration in Osborne

- Mendel rats ( NCI, 197 8 ) was also suitable for deriving a RfD, but it is 22

associated with higher a POD and potential RfD compared to Kociba et al. ( 1974 )

. 23

The R fD was derived by applying UFs to a NOAEL for degenerative liver and kidney 24

effects. The incidence data for the observed effects were not reported in the principal study 25

( Kociba, et al., 1974 ) , precluding modeling of the dose

- response. However confidence in the 26

NOAEL can be derived from additional studies ( Argus, et al., 1965 ; Argus, et al., 1973 ; JBRC, 27

1998 ; NCI, 1978 ) that observed effects on the same organs at comparable dose levels and by the 28

BMDL generated by modeling o f the kidney dose

- response data from the chronic NCI ( 1978 ) 29

study. 30

The RfC was derived by applying UFs to a LOAEL for atro phy of the olfactory 31

epithelium. The incidence data for the observed effects were not appropriate for BMD modeling 32

for this endpoint (see Appendix F ) . The LOAEL for this effect was less than or equal to the 33

LOAEL or NOAEL for other effects observed in the same study. 34

Extrapolating from animals to humans embodies further issues and uncertainties. The 35

effect and the magnitude associated with the dose at the POD in rodents are extrapolated to 36

human response. Pharmacokinetic models are useful to examine s pecies differences in 37125

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE pharmacokinetic processing; however, it was determined that dosimetric adjustment using 1

pharmacokinetic modeling to reduce uncertainty following oral exposure to 1,4

- dioxane was not 2

supported. Insufficient information was available t o quantitatively assess toxicokinetic or 3

toxicodynamic differences between animals and humans, so a 10

- fold UF was used to account 4

for uncertainty in extrapolating from laboratory animals to humans in the derivation of the RfD. 5

A DAF was used to account f or pharmacokinetic differences between rodents and humans in the 6

derivation of the RfC; however, there was no information to inform pharmacodynamic 7

differences between species, so a reduced UF of 3 was used in derivation of the RfC to account 8

for these unc ertainties. 9

Heterogeneity among humans is another uncertainty associated with extrapolating doses 10

from animals to humans. Uncertainty related to human variation needs consideration. In the 11

absence of 1,4

- dioxane

- specific data on human variation, a factor of 10 was used to account for 12

uncertainty associated with human variation in the derivation of the RfD and RfC . Human 13

variation may be larger or smaller; however, 1,4

- dioxane

- specific data to examine the potential 14

magnitude of over

- or under

- estimation a re unavailable. 15

Uncertainties in the assessment of the health hazards of 1,4

- dioxane are associated with 16

deficiencies in reproductive toxicity information. The oral and inhalation database s lack a 17

multigeneration reproductive toxicity study. A single ora l prenatal developmental toxicity study 18

in rats was available for 1,4

- dioxane ( Giavini, et al., 1985 ) . This developmental study indicates 19

that the developing fetus may be a target of toxicity. The database of inhalation studies also 20

lacks a developmental toxicity stud y

. 21

5.4. CANCER ASSESSMENT

5.4.1. Choice of Study/Data

– with Rationale and Justification

5.4.1.1. Oral Study/Data

Three chronic drinking water bioassays provided incidence data for liver tumors in rats 22

and mice, and nasal cavity, peritoneal, and mammary gland tumors in rats only ( JBRC, 1998 ; 23

Kano, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ; Yamazaki, et al., 1994 )

. The dose

- response 24

data from each of these studies are summarized in Table 5

- 7 . With the exception of the NCI 25

( 1978 ) study, the incidence of nasal cavity tumors was generally lower than the incidence of liver 26

tumors in exposed rats. The Kano et al. ( 2009 ) drinking water study was chosen as the principal 27

study for de rivation of an oral cancer slope factor (CSF) for 1,4

- dioxane. This study used three 28

dose groups in addition to controls and characterized the dose

- response relationship at lower 29

exposure levels, as compared to the high doses employed in the NCI ( 1978 ) bioassay ( Table 5

- 30

7 ). The Kociba et al. ( 1974 ) study also used three dose groups and low exposures; however, the 31

study authors only reported the incidence of hepatocellular carcinoma, which may underestimate 32126

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE the combined incidence of rats with adenoma or carcinom a. In addition to increased incidence of 1

liver tumors, chosen as the most sensitive target organ for tumor formation, the Kano et al. 2

( 2009 ) study also noted increased incidence of peritoneal and mammary gland tumors. Nasal 3

cavity tumors were also seen in high

- dose male and female rats; however, the incidence of nasal 4

tu mors was much lower than the incidence of liver tumors in both rats and mice. 5

In a personal communication

, Dr. Yamazaki ( 2006 ) provided that the survival of mice 6

was low in all male groups (31/50, 33/50, 25/50 and 26/50 in control, low

- , mid

- , and high

- dose 7

groups, respectively) and particularly low in high

- dose females (29/50, 29/50, 17/50, and 5/50 in 8

control, low

- , mi d

- , and high

- dose groups, respectively). These deaths occurred primarily during 9

the second year of the study. Survival at 12 month s in male mice was 50/50, 48/50, 50/50, and 10

48/50 in control, low

- , mid

- , and high

- dose groups, respectively. Female mouse survival at 11

12 month s was 50/50, 50/50, 48/50, and 48/50 in control, low

- , mid

- , and high

- dose groups, 12

respectively ( Y amazaki, 2006 ) . Furthermore, these deaths were primarily tumor related. Liver 13

tumors were listed as the cause of death for 31 of the 45 pr e termination deaths in high

- dose 14

female Crj: BDF1 mice ( Yamazaki, 2006 ) . Thus, the high mortality rates in the female mice 15

were still considered to be relevant for this analysis. 16

Table 5

- 7 . Incidence of liver, nasal cavity, per itoneal, and mammary gland

tumors in rats and mice exposed to 1,4

- dioxane in drinking water for 2 years

(based on survival to 12 month s)

Study Species/strain/gender Animal dose

(mg/kg

- day) Tumor Incidence

Liver Nasal

cavity Peritoneal Mammary

gland

Kociba et al.

( 1974 ) Sherman rats, male

and female

combined a,b 0 1/106 h 0/106 h NA NA

14 0/110 0/110 NA NA

121 1/106 0/106 NA NA

1,307 10/66 i 3/66 NA NA

NCI ( 1978 ) Male Osborne

- Mendel

rats b 0 NA 0/33 h NA NA

240 NA 12/26 NA NA

530 NA 16/33 i NA NA

Female Osborne

Mendel rats b,c 0 0/31 h 0/34 h NA NA

350 10/30 i 10/30 i NA NA

640 11/29 i 8/29 i NA NA

Male B6C3F 1 mice d 0 8/49 h NA NA NA

720 19/50 i NA NA NA

830 28/47 i NA NA NA

Female B6C3F 1 mice d 0 0/50 h NA NA NA

380 21/48 i NA NA NA

860 35/37 i NA NA NA127

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Kano et al. ( 2009 ) Male F344/DuCrj

rats d,e,f,g 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

274 39/50 j,k 7/50 k 28/50 j,k 6/50 k

Female F344/DuCrj

rats d,e,f,g 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

429 48/50 j,k 8/50

j,k 0/50 18/50 i,k

Male Crj: BDF1 mice d 0 23/50 0/50 NA NA

49 31/50 0/50 NA NA

191 37/50 i 0/50 NA NA

677 40/50 j,k 1/50 NA NA

Female Crj: BDF1

mice d 0 5/50 0/50 NA NA

66 35/50 j 0/50 NA NA

278 41/50 j 0/50 NA NA

964 46/50 j,k 1/50 NA NA

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)

5.4.1.2. Inhalation Study/Data

Epidemiological studies of populations exposed to 1,4

- dioxane are not adequate for dose

1

response analysis and derivation of an inhalation unit risk (IUR)

. However, t wo chronic 2

inhalation studies in animals are available and were evaluated for the potential to estimate an 3

IUR (Table 5

- 8 ) . The chronic inhalation study conducted by Torkelson et al. ( 1974 ) in rats did 4

not find any treatment

- related tumors; however, only a single exposure concentration was used 5

(111 ppm 1,4

- dioxane vapor for 7 hours/day, 5 days/week for 2 years). A chronic bioassay of 6

1,4

- dioxane by the inhalation route reported by Kasai et al. ( 2009 ) provides data adequate for 7

dose

- response modeling and was subsequently chosen as the principal study for the derivation of 8

an IUR for 1,4

- dioxane. In this bioassay, groups of 50 male F344 rats were exposed to either 0, 9

50, 25 0 or 1,250 ppm 1,4

- dioxane, 6 hours/day, 5 days/week, for 2 years (104

- weeks). In male 10

F344 rats, 1,4

- d ioxane produced a statistically significant increase in incidence and/or a 11

statistically significant dose

- response trend for the following tumor types: hepato mas

, nasal 12

squamous cell carcinomas, renal cell carcinomas, peritoneal mesotheliomas, mammary gland 13128

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE fibroadenomas, Zymbal gland adenomas , and subcutis fibromas ( Kasai, et al., 2009 )

. It is 1

important to note that the incidence of adenomas and the incidence of carcinomas within a dose 2

grou p at a site or tissue (i.e., liver) in rodents are sometimes combined. This practice is based 3

upon the hypothesis that adenomas may develop into carcinomas if exposure at the same dose 4

was continued ( McConnell, Solleveld, Swenberg, & Boorman, 1986 ; U.S. EPA, 2005a )

. 5

Consistent with the oral cancer assessment (Appendix D), the incidence of hepatic adenomas and 6

carcinomas was summed without double

- counting

, to calculate the combined incidence of either 7

a hepatocellular carcinoma o r adenoma in rodents (See Table 5

- 8). 8

Table 5

- 8 . Incidence of liver, nasal cavity, kidney, peritoneal, and mammary

gland, Zymbal gland, and subcutis tumors in rats exposed to 1,4

- dioxane

vapors for 2 years.

Study Species/

strain/

gender Animal

Exposure

(ppm) Tumor Incidence

Liver c Nasal

cavity d Kidney e Peritoneal f Mammary

gland Zymbal

gland g Subcutis h

Torkelson

et al.

( 19 74 ) a Male

Wistar

rats 0 0/150 0/150 0/150 i NA NA NA 0/150

111 0/206 0/206 1/206 i NA NA NA 2/206

Female

Wistar

rats 0 0/139 0/139 1/139 j NA 11/139 k NA 0/139

111 0/217 0/217 0/217 j NA 29/217 k NA 0/217

Kasai et

al.

( 2009 ) b Male

F344

rats 0 1/50 0/50 0/50 2/50 1/50 l 0/50 1/50

50 2/50 0/50 0/50 4/50 2/50 l 0/50 4/50

250 4/50 1/50 0/50 14/50 n 3/50 l 0/50 9/50 n

1,250 22/50 6/50 m 4/50 41/50 n 5/50 l 4/50 5/50

a Incidence reported based on survival to 9 months.

b Incidence reported based on survival to 12 months.

c Incidence of hepatocellular adenoma or carcinoma. For Kasai et al. ( 2009 ) incidence data was p rovided via personal

communication from Dr. Tatsuya Kasai to Dr. Reeder Sams on 12/23/2008 ( 2008 )

. Statistics were not reported.

Individual inc idence rates for adenomas and carcinomas are in Table 5

- 10.

d Incidence of nasal squamous cell carcinoma.

e Incidence of renal cell carcinoma.

f Incidence of peritoneal mesothelioma.

g Incidence of Zymbal gland adenoma.

h Incidence of subcutis fibroma.

i Incidence of kidney fibroma.

j Incidence of kidney adenocarcinoma

k Incidence of mammary gland adenoma.

l Incidence of mammary gland fibroadenoma.

m T umor incidence significantly elevated compared with that in controls by Fisher‘s exact test ( p ≤ 0.05).

n Tumor incidence significantly elevated compared with that in controls by Fisher‘s exact test ( p ≤ 0.01).

NA = data are not available

5.4.2. Dose

- Response Data

5.4.2.1. Oral Data

Table 5

- 9 summarizes the incidence of hepatocellular adenoma or carcinoma in rats and 9

mice from the Kano et al. ( 2009 ) 2

- year drinking water study. There were statistically 10129

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE significant increasing trends in tumorigenic response for males and females of both species. The 1

dose

- response curve for female mice is steep, with 70% inciden ce of liver tumors occurring in 2

the low

- dose group (66 mg /kg

- day). Exposure to 1,4

- dioxane increased the incidence of these 3

tumors in a dose

- related manner. 4

A significant increase in the incidence of peritoneal mesothelioma was observed in high

5

dose male rats only (28/50 rats, Table 5

- 7 ). The incidence of peritoneal mesothelioma was lower 6

than the observed incidence of hepatocellular adenoma or carcinoma in male rats ( Table 5

- 9 ); 7

therefore, hepatocellular adenoma or carcinoma data were used to derive an o ral CSF for 8

1,4

- dioxane. 9

Table 5

- 9 . 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 tumors a

Male F344/DuCrj rats 0 3/50

11 4/50

55 7/50

274 39/50 b,c

Female F344/DuCrj rats 0 3/50

18 1/50

83 6/50

429 48/50 b,c

Male Crj:BDF1 mice 0 23/50

49 31/50

191 37/50 d

677 40/50 b,c

Female Crj:BDF1 mice 0 5/50

66 35/50 c

278 41/50 c

964 46/50 b,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 )

.

5.4.2.2. Inhalation Data

Multi

- tumor dose

- response modeling was performed for all tumor responses from the 10

Kasai et al. ( 2009 ) bioassay. Kasai et al. ( 2009 ) reported tumor incidence data for male F344 11

rats exposed via inhalation to 0, 50, 250, or 1,250 ppm 1,4

- dioxane for 6 hours/day, 5days/week, 12

for 2 years (104

- weeks). Statistically significant dose

- response trends for the incre ase in tumors 13130

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE with increasing dose was observed for the nasal cavity squamous cell carcinomas, hepatomas

, 1

renal cell carcinomas, peritoneal mesotheliomas, mammary gland fibroadenomas, and Zymbal 2

gland adenomas. Following 250 ppm 1,4

- dioxane exposure stati stically elevated tumor 3

incidences were found in two tissue types ( peritoneal mesothelioma and subcutis fibroma) 4

compared to controls. Tumor incidences following 1,250 ppm inhalation exposure to 1,4

- 5

dioxane were statistically elevated compared to controls in three tissues (nasal cavity squamous 6

cell carcinoma, hepatomas , and peritoneal mesothelioma). Incidence data for the tumor types 7

reported by Kasai et al. ( 2009 ) are summarized in Table 5

- 1 0

. 8

Table 5

- 1 0 . Incidence of tumors in F344 male rats exposed to 1,4

- dioxane for

104 weeks (6 hours/day, 5 d ays/week)

Tumor Type Animal Exposure (ppm)

0 50 250 1,250

Nasal cavity squamous cell carcinoma 0/50 0/50 1/50 6/50 a, b

Hepatocellular adenoma 1/50 2/50 3/50 21/50 a, c

Hepatocellular carcinoma 0/50 0/50 1/50 2/50

Hepatocellular adenoma or carcinoma e 1/50 2/50 4/50 22/50 a,c

Renal cell carcinoma 0/50 0/50 0/50 4/50 a

Peritoneal mesothelioma 2/50 4/50 14/50 c 41/50 a, c

Mammary gland fibroadenoma 1/50 2/50 3/50 5/50 d

Mammary gland adenoma 0/50 0/50 0/50 1/50

Zymbal gland adenoma 0/50 0/50 0/50 4/50 a

Subcutis fibroma 1/50 4/50 9/50 c 5/50

a Statistically significant trend for increased tumor incidence by Peto‘s test ( p ≤ 0.01).

b Tumor incidence significantly elevated compared with that in controls by Fisher‘s exact test ( p ≤ 0.05).

c Tumor incidence significantly elevated compared with that in controls by Fisher‘s exact test ( p ≤ 0.01).

d Statistically significant trend for increased tumor incidence by Peto‘s test ( p ≤ 0.05).

e Provided via personal communication from Dr. Tatsuya Kasai to Dr. Reeder Sams on 12/23/200 8 ( 2008 )

. Statistics were not reported for these data by study authors, so statistical analyses were conducted by EPA

.

Source: Kasai et al. ( 2009 ) and Kasai personal communication ( 2008 )

5.4.3. Dose Adjustments and Extrapolation Method(s)

5.4.3.1. Oral

Human equivalent doses (HEDs) were calculated from the administered animal doses 9

using a BW scaling factor (BW 0.75 ). This was accomplished using the following equation: 10

11

For all calculations , a human BW of 70 kg was used. HEDs for the principal study ( Kano, et al., 12

2009 ) are given in Table 5

- 1 1 . HEDs were also calculated for supporting studies ( Kociba, et al., 13

1974 ; NCI, 1978 ) and are also shown in Table 5

- 1 1

. 14131

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 5

- 1 1

. Calculated HEDs for the tumor incidence data used for dose

response modeling

Study Species/strain/gender Animal BW (g)

TWA Animal dose

(mg/kg

- day) HED

(mg/kg

- day) d

Kano et al. ( 2009 ) Male F344/DuCrj rats 432 a 11 3.1

432 a 81 23

432 a 398 112

Female F344/DuCrj rats 267 a 18 4.5

267 a 83 21

267 a 429 107

Male Crj: BDF1 mice 47.9 a 49 7.9

47.9 a 191 31

47.9 a 677 110

Female Crj: BDF1 mice 35.9 a 66 10

35.9 a 278 42

35.9 a 964 145

Kociba et al. ( 1974 ) Male and female (combined)

Sherman rats 325 b 14 3.7

325 b 121 32

285 c 1,307 330

NCI ( 1978 ) Male Osborne

- Mendel rats 470 b 240 69

470 b 530 152

Female Osborne

- Mendel rats 310 b 350 90

310 b 640 165

Male B6C3F 1 mice 32 b 720 105

32 b 830 121

Female B6C3F 1 mice 30 b 380 55

30 b 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 ) ; Kociba et al. ( 1974 ) ; and NCI ( 1978 )

.

The U.S. EPA Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a ) 1

recommend that the method used to characterize and quantify cancer risk from a chemical is 2

determined by what is known about the mode of action of the carcinog en and the shape of the 3

cancer dose

- response curve. The linear approach is recommended if the mode of action of 4

carcinogenicity is not understood ( U.S. EPA, 2005a ) . In the case of 1,4

- dioxane, the mode of 5

carcinogenic action for peritoneal, mammary, nasal, and liver tumors is unknown. Therefore, a 6

line ar low

- dose extrapolation approach was used to estimate human carcinogenic risk associated 7

with 1,4

- dioxane exposure. 8132

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE However, several of the external peer review panel members ( Appendix A: Summary of 1

External Peer Review and Public Comments and Dispositio n) recommended that the mode of 2

action data support the use of a nonlinear extrapolation approach to estimate human carcinogenic 3

risk associated with exposure to 1,4

- dioxane and that such an approach should be presented in 4

the Toxicological Review. As dis cussed in Section 4.7.3., numerous short

- term in vitro and a 5

few in vivo tests were nonpositive for 1,4

- dioxane

- induced genotoxicity. Results from two

- stage 6

mouse skin tumor bioassays demonstrated that 1,4

- dioxane does not initiate mouse skin tumors, 7

but it is a promoter of skin tumors initiated by DMBA ( King, et al., 1973 ) . These data suggest 8

that a potential mode of action for 1,4

- dioxane

- induced tumors may involve proliferation of cells 9

initiated spontaneously, or by some other agent, to become tumors ( Bull, et al., 1986 ; 10

Goldsworthy, et al., 1991 ; King, et al., 197 3 ; Lundberg, et al., 1987 ; Miyagawa, et al., 1999 ; 11

Stott, et al., 1981 ; Uno, et al., 1994 )

. However, key events related to the promotion of tumor 12

formation by 1,4

- dioxane are unknown. Therefore, under the U.S. EPA Guidelines for 13

Carcinogen Risk Assessment ( U.S. EPA, 2005a ) , EPA concluded that the available information 14

does not establish a plausible mode of action for 1,4

- dioxane and data are insufficient to establish 15

significant biological support for a nonlinear approach. EPA determined that there are no data 16

available to inform the low

- dose region of the dose response, and thus, a nonlinear approach was 17

not included. 18

Accordingly, the CSF for 1,4

- dioxane was derived via a linear extrapolation from the 19

POD calculated by curve fitting the experimental dose

- response data. Th e POD is the 95% 20

lower confidence limit on the dose associated with a benchmark response (BMR) near the lower 21

end of the observed data. The BMD modeling analysis used to estimate the POD is described in 22

detail in Appendix D and is summarized below in Sect ion 5.4.4. 23

Model estimates were derived for all available bioassays and tumor endpoints ( Appendix 24

D); however, the POD used to derive the CSF is based on the most sensitive species and target 25

organ in the principal study ( Kano, et al., 2009 )

. 26

The oral CSF was calculated using the following equation: 27

28

5.4.3.2. Inhalation

In accordance with the U.S. EPA ( 1994b ) RfC methodology, the HEC values for the 29

various tumors were calculated by the application of DAFs. As discussed in Section 5.2.3. since 30

1,4

- dioxane is miscible with water, has a high partition c oefficient, and systemic and portal of 31

entry effects are observed, a DAF of 1.0 was applied. The lifetime continuous inhalation risk for 32

humans is defined as the slope of the line from the POD, the lower 95% bound on the exposure 33

associated with a level o f extra risk near the low end of the data range. 34133

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE All PODs were converted to equivalent continuous exposure levels by multiplying by [(6 1

hours)/(24 hours)] × [(5 days)/(7 days)], or 0/178, under the assumption of equal cumulative 2

exposures leading to equiv alent outcomes. 3

Given the multiplicity of tumor sites, basing the IUR on one tumor site may 4

unde restimate the carcinogenic potential of 1,4

- dioxane. Simply pooling the counts of animals 5

with one or more tumors (i.e., counts of tumor bearing animals) would tend to underestimate the 6

overall risk when tumors are independent across sites and ignores pot ential differences in the 7

dose

- response relationships across the sites ( Bogen, 1990 ; Spurgeon, Hopkin, & Jones, 1994 )

. 8

NRC ( 1994 ) also noted that the assumption of independence across tumor types is not likely to 9

produce substantial error in the risk estimates unless tumors are known to be biologically 10

dependent. 11

Kopylev et al. ( 2009 ) describe a Markov Chain Monte Caro (MCMC) computational 12

approach to calculating the dose associated with a specified composite risk under assumption of 13

independence of tumors. The Guidelines for Carcinogen Risk Assessment recommend 14

calculation of an upper bound to account for uncertainty in the estimate ( U.S. EPA, 2005a ) . For 15

uncertainty characterization, MCMC methods have the adva ntage of providing information about 16

the full distribution of risk and/or benchmark dose, which can be used in generating a confidence 17

bound. This MCMC approach building on the re

- sampling approach recommend ed by Bogen 18

( 1990 ) , which also provides a distribution of the combined potency across sites. The Bayesian 19

MCMC computations were conducted using WinBugs ( Spiegelhalter, Thomas, & Best, 2003 ) 20

and additional details of this analysis are included in Appendix G

. In addition, the best fitting 21

BMDS multistage model wa s determined for each individual tumor type as shown in Section 22

5.4.4.2 and Appendix G. 23

IUR estimates based were calculated using the following equation: 24

IUR = BMR / HEC 25

5.4.4. Oral Slope Factor and Inhalation Unit Risk

5.4.4.1. Oral Slope Factor

The dichotomous models available in the Benchmark Dose Software (BMDS, version 26

2.1.1) were fit to the incidence data for ―either hepatocellular carcinoma or adenoma‖ in rats and 27

mice, as well as mammary and peritoneal tumors in rats exposed to 1,4

- dioxane in the drinking 28

water ( Kano, et al., 2009 ; Kociba, et al., 1974 ; NCI, 19 78 ) ( Table 5

- 7 ). Animal doses are used 29

for BMD modeling and HED BMD and BMDL values are calculated using the animal TWAs 30

( Table 5

- 12 ) and a human BW of 70kg. Doses associated with a BMR of 10% extra risk were 31

calculated. BMDs and BMDLs from all mode ls are reported, and the output and plots 32

corresponding to the best

- fitting model are shown ( Appendix D). When the best

- fitting model is 33

not a multistage model, the multistage model output and plot are also provided ( Appendix D). A 34134

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE summary of the BMDS mo del predictions for the Kano et al. ( 2009 ) , NCI ( 1978 ) , and Kociba 1

et al. ( 1974 ) studies is shown in Table 5

- 1 2

. 2

Table 5

- 1 2 . BMD HED and BMDL HED 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 BMD HED a

(mg/kg

- day) BMDL HED a

(mg/kg

day) Oral CSF

(mg/kg

- day) - 1

Kano et al.

( 2009 ) Male F344/DuCrj rats b Hepatocellular

adenoma or

carcinoma 17.43 14.33 7.0 x 10

- 3

Female F344/DuCrj rats c 19.84 14.43 6.9 x 10

- 3

Male Crj: BDF1 mice d 5.63 2.68 3.7 x 10

- 2

Female Crj: BDF1 mice d 0.83 0.55 0.18

Female Crj: BDF1 mice d, e 3.22 e 2.12 e 0.14

Female Crj: BDF1 mice d, f 7.51 f 4.95 f 0.10

Female F344/DuCrj rats g Nasal

squamous cell

carcinoma 94.84 70.23 1.4 x 10

- 3

Male F344/DuCrj rats g 91.97 68.85 1.5 x 10

- 3

Male F344/DuCrj rats b Peritoneal

mesothelioma 26.09 21.39 4.7 x 10

- 3

Female F344/DuCrj rats d Mammary

gland

adenoma 40.01 20.35 4.9 x 10

- 3

Kociba et al.

( 1974 ) Male and female (combi ned)

Sherman rats g Nasal

squamous cell

carcinomas 448.24 340.99 2.9 x 10

- 4

Male and female (combined)

Sherman rats b Hepatocellular

carcinoma 290.78 240.31 4.2 x 10

- 4

NCI ( 1978 ) Male Osborne Mendel rats d Nasal

squamous cell

carcinomas 16.10 10.66 9.4 x 10

- 3

Female Osborne Mendel rats d 40.07 25.82 3.9 x 10

- 3

Female Osborne Mendel rats d Hepatocellular

adenoma 28.75 18.68 5.4 x 10

- 3

Female B6C3F 1 mice c Hepatocellular

adenoma or

carcinoma 23.12 9.75 1.0 x 10

- 2

Male B6C3F 1 mice h 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.

The multistage model did not provide an adequate fit (as determined by AIC, p

- value 3

< 0.1, and χ 2 p > |0.1|) to the data for the incidence of hepatocellular adenoma or carcinoma in 4

female mice ( Appendix D). The high dose was dropped for the female mouse l iver tumor dataset 5

in an attempt to achieve an adequate fit; however, an adequate fit was still not achieved. 613 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Because the female mice were clearly the most sensitive group tested, other BMD models were 1

applied to the female mouse liver tumor dataset to ac hieve an adequate fit. The log

- logistic 2

model was the only model that provided adequate fit for this data set due to the steep rise in the 3

dose

- response curve (70% incidence at the low dose) followed by a plateau at near maximal 4

tumor incidence in the mid

- and high

- dose regions (82 and 92% incidence, respectively). The 5

predicted BMD 10 and BMDL 10 for the female mouse data are presented in Table 5

- 12 , as well as 6

BMD HED and BMDL HED values associated with BMRs of 30 and 50% . 7

The multistage model also did not provide an adequate fit to mammary tumor incidence 8

data for the female rat or male rat peritoneal tumors. The predicted BMD 10 and BMDL 10 for 9

female rat mammary tumors and male peritoneal tumors obtained from the log

- logistic and 10

probit models, respect ively, are presented in Table 5

- 1 2

. 11

A comparison of the model estimates derived for rats and mice from the Kano et al. 12

( 2009 ) , NCI ( 1978 ) , and Kociba et al. ( 1974 ) studies ( Table 5

- 1 2 ) indicates that female mice are 13

more sensitive to liver carcinogenicity induced by 1,4

- dioxane compared to other species or 14

tumor types. The BMDL 50 HED for the female mouse data was chosen as the POD and the CSF of 15

0.10 (mg/kg

- day)

- 1 was calculated as follows: 16

17

Calculation of a CSF for 1,4

- dioxane is based upon the dose

- response data for the most 18

sensitive species and gender. 19

5.4.4.2. Inhalation Unit Risk

I nhalation unit risk estimates were base d on the multiple carcinogenic effects of 20

1,4

- dioxane observed in rats via the inhalation route. 21

The multistage cancer models available in the Benchmark Dose Software (BMDS, 22

version 2.1.1) were fit to the incidence data for each tumor type observed in rats exposed to 23

1,4

- dioxane via inhalation ( Kasai, et al., 2009 ) to determine the degree (e.g., 1 st , 2 nd , or 3 rd ) of the 24

multistage model that best fit the data (details in Appendix G). A Bayesian MCMC analysis was 25

performed using WinBUGS to calculate the total tumor risk. For comparative purposes only, a 26

total tumor analysis was also performed with the BMDS (version 2.2Beta) MSCombo model and 27

yielded similar results (See Appendix G). MSCombo is a new addition to BMDS that allows for 28

multi

- tumor analysis. A summary of the BMDS model predictions for the Kasai et al. ( 2009 ) 29

study is shown in Table 5

- 1 3 . Animal exposure concentrations were used for BMD modeling 30

and continuous human equivalent exposures were calculated by adjusting for duration of 31

exposure (Table 5

- 1 3 ) and applying an appropriate DAF (see Section 5.2.3)

. In accordance with 32

the U.S. EPA ( 2005a ) Cancer Guidelines, the BMCL 10 (lower bound on the concentration 33

estimated to produce a 10% increase in tumor incidence over background) was estimated for the 34

dichotomous incidence data and the result s of the model that best characterized the cancer 35136

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE incidences were selected. BMCs and BMCLs from all models are reported, and the output and 1

plots corresponding to the best

- fitting model are shown (Appendix G). 2

The IUR estimates are provided in Table 5

- 1 3 . Human equivalent risks estimated from 3

the individual rat tumor sites ranged from 1. 5 × 10

- 7 to 2.4 × 10

- 6 (μg/m 3 )

- 1 (or rounded to one 4

significant figure, 2 × 10

- 7 to 2 × 10

- 6 (μg/m 3 )

- 1 ). The highest IUR (2.4 × 10

- 6 (μg/m 3 )

- 1 ) 5

corresponded to peritoneal mesotheliomas in male rats, and the lowest IUR (1. 5 × 10

- 7 (μg/m 3 )

- 1 ) 6

corresponded to renal cell carcinoma and Zymbal gland adenomas in male rats. 7

Table 5

- 1 3 . Dose

- response modeling summary results for male rat tumors

associated with inhalatio n exposure to 1,4

- dioxane for 2 years

Tumor Type a Multistage

Model

Degree b Point of Departure c

IUR

Estimate e

(μg/m 3 ) - 1 Bioassay Exposure

Concentration (ppm) HEC

(mg/m 3 ) d

BMC 10 BMCL 10 BMC 10 BMCL 10 Nasal cavity squamous cell

carcinoma 1 1107 629.9 712.3 405.3 2.5 × 10

- 7

Hepatocellular adenoma or

carcinoma 1 252.8 182.3 162.7 117.3 8.5 × 10

- 7

Renal cell carcinoma 3 1355 1016 872 653.7 1.5 × 10

- 7

Peritoneal mesothelioma 1 82.21 64.38 52.89 41.42 2.4 × 10

- 6

Mammary gland

fibroadenoma 1 1635 703.0 1052 452.4 2.2 × 10

- 7

Zymbal gland adenoma 3 1355 1016 872 653.7 1.5 × 10

- 7

Subcutis fibroma 1 141.8 81.91 91.21 52.70 1.9 × 10

- 6

Bayesian Total Tumor Analysis f 39.2 31.4 25.2 20.2 5.0 × 10

- 6

a Tumor incidence data from Kasai et al. ( 2009 )

. b Best

- fitting multistage model degree ( p >0.1, lowest AIC). See Appendix G for modeling details.

c BMC = Concentration at specified extra risk (benchmark dose); BMCL = 95% lower bound on concentration at

specified extra risk.

d Human continuous equivalent estimated by multiplying exposures by [ (6 hours)/(24 ho urs) × (5 days)/(7 days) x

molecular weight of 1,4

- dioxane]/ 24.45

.

e The inhalation unit risk (μg/m 3 )

- 1 was derived from the BMCL 10 , the 95% lower bound on the concentration

associated with a 10% extra cancer risk. Specifically, by dividing the BMR (0.10) by the BMCL 10 . Thus,

representing an upper bound, continuous lifetime exposure estimate of cancer potency.

f Results in this table are from the Bayesian analysis using WinBUGS. Additionally, for comparative purposes only,

t otal tumor analysis was performed with the draft BMDS (version 2.2Beta) MS C ombo model and yielded similar

results (See Appendix G)

.

Given the multiplicity of tumor sites, basing the inhalation unit risk on one tumor site 8

may underestimate the carcinogen ic potential of 1,4

- dioxane. Consistent with recommendations 9

of the NRC ( 1994 ) and the current Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 10

2005a ) for the assessment of total risk, and upper bound risk for all tumor sites in male F344 rats 11

was estimated. This estimate of total risk describes the risk of developing any combination of 12

the tumor types considered, not just the risk of developing all simultaneously. As shown in 13

Table 5

- 1 3 , the resulting total inhalation unit risk for all tumor types for male F344 rats was 5 × 14

10

- 6 (μg/m 3 )

- 1 . Overall, the consideration of the other tumor sites a pproximately doubled the unit 15137

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE risk compared to the highest unit risk associated wit h any individual tumor type, 2 × 10

- 6 1

(μg/m

3 )

- 1 for male peritoneal mesotheliomas. 2

The HEC BMCL 10 for the male rat combined tumor estimate was chosen as the POD and 3

the IUR of 5 × 10

- 6 (μg/m 3 )

- 1 was calculated as follows: 4

5

Based on the analysis discussed above, the recommended upper bound estimate on 6

human extra ca n cer risk from continuous lifetime exposure to 1,4

- dioxane is 5 × 10

- 6 ( μg/m 3 )

- 1

. 7

The recommended unit risk estimate reflects the exposure

- response relationships for the multiple 8

tumor sites in male F344 rats. 9

5.4.5. Previous Cancer Assessment

A previous cancer assessment was posted for 1,4

- dioxane on IRIS in 1988. 1,4

- Dioxane 10

was classified as a Group B2 Carcinogen (probable human carcinogen; sufficient evidence from 11

animal studies and inadequate eviden ce or no data from human epidemiology studies ( U.S. EPA, 12

1986a ) ) based on the induction of nasal cavity and liver carcinomas in multiple st rains of rats, 13

liver carcinomas in mice, and gall bladder carcinomas in guinea pigs. An oral CSF of 0.011 14

(mg/kg

- day)

- 1 was derived from the tumor incidence data for nasal squamous cell carcinoma in 15

male rats exposed to 1,4

- dioxane in drinking water for 2 years ( NCI, 1978 ) . The linearized 16

multistage extra risk procedure was used for linear low dose extrapolation. An inhalation unit 17

risk was not previously derived. 18

5.5. UNCERTAINTIES IN CAN CER RISK VALUES

As in most risk assessments, extrapolation of study data to estimate potential risks to 19

human populations from exposure to 1,4

- dioxane has engendered some uncertainty in the results. 20

Several types of uncertainty may be considered quantitatively, but other important uncertainties 21

cannot be considered quantitatively. Thus an overall integrated quantitative uncertainty analysis 22

is not presented. In addition, the use of th e assumptions, particularly those underlying the 23

Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a ) is explained and the decision 24

concerning the preferred approach is given and justified. Principal uncertainties are summarized 25

below and in Table 5

- 14

. 26138

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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

1,4

- dioxane, or any chemical, ranges from linear to nonlinear, but is dependent upon a plausible 2

MOA(s) for the observed tumors. The M OA is a key consideration in clarifying how risks 3

should be estimated for low

- dose exposure. Exposure to 1,4

- dioxane has been observed in 4

animal models to induce multiple tumor types, including liver adenomas and carcinomas, nasal 5

carcinomas, mammary aden omas and fibroadenomas, and mesotheliomas of the peritoneal cavity 6

( JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ) . MOA 7

information that is available for the carcinogenicit y of 1,4

- dioxane has largely focused on liver 8

adenomas and carcinomas, with little or no MOA information available for the remaining tumor 9

types. In Section 4.7.3, hypothesized MOAs were explored for 1,4

- dioxane. Information that 10

would provide sufficient support for any MOA is not available. In the absence of a MOA(s) for 11

the observed tumor types, a linear low

- dose extrapolation approach was used to estimate human 12

carcinogenic risk associated with 1,4

- dioxane exposure. 13

It is not possible to predict how additional MOA information would impact the dose

14

response assessment for 1,4

- dioxane because of the variety of tumors observed and the lack of 15

data on how 1,4

- dioxane or a metabolite thereof, interacts with cells starting the progression to 16

the observed t umors. 17

In general, the Agency has preferred to use the multistage model for analyses of tumor 18

incidence and related endpoints because they have a generic biological motivation based on 19

long

- established mathematical models such as the Moolgavkar

- Venzon

- Knud sen (MVK) model. 20

The MVK model does not necessarily characterize all modes of tumor formation, but it is 21

a starting point for most investigations and, much more often than not, has provided at least an 22

adequate description of tumor incidence data. 23

The mu ltistage cancer model provide d good fits for the tumor incidence data following a 24

2

- year inhalation exposure to 1,4

- dioxane by male rats ( Kasai, et al., 2009 )

. However, in the 25

studies evaluated for the oral cancer assessment ( Kano, et al., 2009 ; Kociba, et al., 1974 ; NCI, 26

1978 ) , the multistage model provided good descriptions of the incidence of a few tumor types in 27

male (nasal cavity) and female (hepatocellular and nasal cavity) rats and in male mice 28

(hepatocellular) exposed to 1,4

- dioxane ( Appendix D for details). T he multistage model did not 29

provide an adequate fit for the fe male mouse liver tumor dataset based upon the following ( U.S. 30

EPA, 2000a ) : 31

Goodness

- of

- fit p

- value was not greater than 0.10;

Akaike‘s Information Criterion (AIC) was larger than other acceptable models;139

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Data deviated from the fitted model, as measured by th eir χ 2 residuals (values were

greater than an absolute value of one).

BMDS software typically implements the guidance in the external peer review draft 1

BMD technical guidance document ( U.S. EPA, 2000a ) by imposing constraints on the values of 2

certain parameters of the models. When these constrain ts were imposed, the multistage model 3

and most other models did not fit the incidence data for female mouse liver adenomas or 4

carcinomas. 5

The log

- logistic model was selected because it provides an adequate fit for the female 6

mouse data ( Kano, et al., 2009 ) . A BMR of 50% was used because it is proximate to the 7

response at the lowest dose tested and the BMDL 50 HED was derived by applying appropriate 8

parameter constraints, consistent with recommended use of BMDS in the BMD technical 9

guidance document ( U.S. EPA, 2000a )

. 10

The human equivalent oral CSFs estimated from tumor datasets with statistically 11

si gnificant increases ranged from 4.2 × 10

- 4 to 0.18 per mg /kg

- day ( Table 5

- 1 2 ), a range of about 12

three orders of magnitude, with the extremes coming from the combined male and female rat 13

data for hepatocellular carcinomas ( Kociba, et al., 1974 ) and the female mouse combined liver 14

adenoma and carcinomas ( Kano, et al., 2009 )

. 15

5.5.1.2. Dose Metric

1,4

- Dioxane is known to be metabolized in vivo. However, it is unknown whether a 16

metab olite or the parent compound, or some combination of parent compound and metabolites, is 17

responsible for the observed toxicity. If the actual carcinogenic moiety is proportional to 18

administered exposure, then use of administered exposure as the dose metri c is the least biased 19

choice. On the other hand, if this is not the correct dose metric, then the impact on the CSF is 20

unknown. 21

5.5.1.3. Cross

- Species Scaling

For the oral cancer assessment, an adjustment for cross

- species scaling (BW 0.75 ) was 22

applied to address toxicological equivalence of internal doses between each rodent species and 23

humans, consistent with the 2005 Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 24

2005a ) . It is assumed that equal risks result from equivalent constant lifetime exposures. 25

Differences in the anatomy of the upper respiratory tract and resulting differences in 26

absorption or in local respiratory system effects are sources of uncertainty in the inhalation 27

cancer assessment. 28

5.5.1.4. Statistical Uncertainty at the POD

Parameter uncertainty can be assessed through confidence intervals. Each description of 29

parameter uncertainty assumes that the underlying model and associated assumptions are valid. 30

For the log

- logistic model applied to the female mouse data following oral exposure , there is a 31140

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE reasonably small degree of uncertainty at th e 10% excess incidence level (the POD for linear 1

low

- dose extrapolation). For the multistage model applied for the male rat inhalation dataset, 2

there is a reasonable small degree of uncertainty at the 10% extra risk level (the POD for linear 3

low

- dose extr apolation). 4

5.5.1.5. Bioassay Selection

The study by Kano et al. ( 2009 ) w as used for development of an oral CSF. This was a 5

well

- designed study, conducted in both sexes in two species (rats and mice) with a sufficient 6

number (N=50) of animals per dose group. The number of test animals allocated among three 7

dose levels and an untreated control group was adequate, with examination of appropriate 8

toxicological endpoints in both sexes of rats and mice. Alternative bioassays ( Kociba, et al., 9

1974 ; NCI, 1978 ) were available and were fu lly considered for the derivation of the oral CSF. 10

The study by Kasai et al. ( 2009 ) was used for derivation of an inhalation unit risk. This 11

was a well

- designed and peer reviewed study, conducted in male rats with a sufficient number 12

(N=50) of animals per dose group. Three dose lev els plus an untreated control group were 13

examined following exposure to 1,4

- dioxane via inhalation for 2 years. Other bioassays ( Kasai, 14

et al., 2008 ; Torkelson, et al., 1974 ) were availabl e and were considered for the derivation of the 15

inhalation unit risk. 16

5.5.1.6. Choice of Species/Gender

The oral CSF for 1,4

- dioxane was quantified using the tumor incidence data for the 17

female mouse, which was shown to be more sensitive than male mice or either sex of rats to the 18

carcinogenicity of 1,4

- dioxane. While all data, both species and sexes reported from the Kano 19

et al. ( 2009 ) study, were suitable for deriving an oral CSF, the female mouse data represented the 20

most sensitive indicator of carcinogenicity in the rodent model. The lowest exposure level 21

(66 mg /kg

- day or 10 mg /kg

- day [HED]) resulted in a considerable and significant increase in 22

combined liver adenomas and carcinomas observed . Additional testing of doses within the range 23

of control and the lowest dose (66 mg /kg

- d ay or 10 mg /kg

- day [HED]) could refine and reduce 24

uncertainty for the oral CSF. 25

A personal communication from Dr. Yamazaki ( 2006 ) provided that the survival of mice 26

was particularly low in high

- dose females (29/50, 29/50, 17/50, and 5/50 in control, low

- , mid

- , 27

and high

- dose groups, respectively). These deaths occurred primarily during the second year of 28

the study. Female mous e survival at 12 month s was 50/50, 50/50, 48/50, and 48/50 in control, 29

low

- , mid

- , and high

- dose groups, respectively ( Yamazaki, 2006 ) . Furthermore, these deaths 30

were primarily tumor related. Liver tumors were listed as the cause of dea th for 1/21, 2/21, 8/33, 31

and 31/ 45 of the pretermination deaths in control, low

- , mid

- and, high

- dose female Crj: BDF1 32

mice ( Yamazaki, 2006 ) . T herefore, because a number of the deaths in female mice were 33

attributed to liver tumors, this e ndpoint and species was still considered to be relevant for this 34

analysis; however, the high mortality rat e does contribute uncertainty

. 35141

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Additionally, the incidence of hepatocellular adenomas and carcinomas in historical 1

controls was evaluated with the dat a from Kano et al. ( 2009 ) . Katagiri et al. ( 1998 ) summarized 2

the incidence of hepatocellular adenomas and carcinomas in control male and female BDF1 mice 3

from ten 2

- year bioassays at the JBRC. For female mice, out of 499 control mice, the incidence 4

rates were 4.4% for hepatocellular adenomas and 2.0% for hepatocellular carcinomas. Kano et 5

al. ( 2009 ) reported a 10% incidence rate for hepatocellular adenomas and a 0% incidence rate for 6

hepatocellular carcinomas in control female BDF1 . These incidence rates are near the historical 7

control values a nd thus are appropriate for consideration in this assessment

. 8

Male F344 rat data were used to estimate risk following inhalation of 1,4

- dioxane. Kasai 9

et al. ( 2008 ) showed that male rats were more sensitive than female rats to the effects of 1,4

- 10

dioxane following inhalation; therefore, male rats were chosen to be studies in the 2

- year 11

bioassay conducted by the same laboratory ( Kasai, et al., 2009 )

. 12

5.5.1.7. Relevance to Humans

The derivation of the oral CSF is derived using the tumor incidence in the liver of female 13

mice. A thorough review of the available toxicological data available for 1,4

- dioxane provides 14

no scientific justification to propose that the liver adenomas and carcinomas observed in animal 15

models due to exposure to 1,4

- dioxane are not relevant to humans. As such, liver adenomas and 16

carcinomas were considered relevant to humans due to exposure to 1,4

- dioxane. 17

The derivation of the inhalation unit risk is base d on the tumor incidence at multiple sites 18

in male rats. There is no information on 1,4

- dioxane to indicate that the observed rodent tumors 19

are not relevant to humans. Further, no data exist to guide quantitative adjustment for 20

differences in sensitivity among rodents and humans. 21

5.5.1.8. Human Population Variability

The extent of inter

- individual variability in 1,4

- dioxane metabolism has not been 22

characterized. A separate issue is that the human variability in response to 1,4

- dioxane is also 23

unknown. Data exp loring whether there is differential sensitivity to 1,4

- dioxane carcinogenicity 24

across life stages are unavailable. This lack of understanding about potential differences in 25

metabolism and susceptibility across exposed human populations thus represents a source of 26

uncertainty. Also, the lack of information linking a MOA for 1,4

- dioxane to the observed 27

carcinogenicity is a source of uncertainty. 28142

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table 5

- 1 4 . Summary of uncertainty in the 1,4

- dioxane cancer risk

estimation

Consideration/

approach Potential Impact 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,

for OSF;

Bayesian

multistage

modeling for

IUR; 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

Gu idelines 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 BW 0.67 )] BW 0.75 (default

approach) There are no data to support alternatives. BW 0.75

scaling was used to calculate equivalent

cumulative exposures for estimating equivalent

human risks. PBPK modeling was conducted but

not deemed sui table for interspecies extrapolation.

Bioassay Alternatives could ↑

or ↓ cancer potency

by an unknown

extent OSF ( Kano, et al.,

2009 ) ; IUR

( Kasai, et al.,

2009 ) Alternative bioassays were available and

considered for derivation of oral CSF and

inhalation UR.

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 Mouse liver

adenomas and

carcinomas are

relevant to

humans (basis for

OSF). Rat tumors

at multiple sites

are relevant to

humans (basis for

IUR) 1,4

- dioxane is a multi

- site carcinogen in rodents

and the MOA(s) is unknown; carcinogenicity

observed in the rodent st udies 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.143

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE

RESPONSE

6.1. HUMAN HAZARD POTENTI AL

1,4

- Dioxane is absorbed rapidly following oral and inhalation exposure, with much less 1

absorption occurring from the dermal route. 1,4

- Dioxane is primarily metabolized to HEAA, 2

which is excreted in the urine. Liver

, kidney , and nasal toxicity are the primary noncancer health 3

effects associated with exposure to 1,4

- dioxane in humans and laboratory animals. Several fatal 4

cases of hemorrhagic nephritis and centrilobular necrosis of the liver were related to 5

occupational exposure (i.e., i nhalation and dermal contact) to 1,4

- dioxane ( Barber, 1934 ; 6

Johnstone, 1959 ) . Neurological changes were also reported in one case, including headache, 7

elevation in blood pressure, agitation and restlessness, and coma ( Johnstone, 1959 ) . Perivascular 8

widening was obse rved in the brain of this worker, with small foci of demyelination in several 9

regions (e.g., cortex, basal nuclei). Severe liver and kidney degeneration and necrosis were 10

observed frequently in acute oral and inhalation studies (≥ 1,000 mg /kg

- day oral, ≥ 1,000 ppm 11

inhalation) ( David, 1964 ; de Navasquez, 1935 ; Drew, et al., 1978 ; Fairley, et al., 1934 ; JBRC, 12

1998 ; Kesten, et al., 1939 ; Laug , et al., 1939 ; Schrenk & Yant, 1936 )

. 13

Liver and kidney toxicity were the primary noncancer health effects of subchronic and 14

chronic oral exposure to 1,4

- dioxane in animals. Hepatocellular degeneration and necrosis were 15

obs erved ( Kociba, et al., 1974 ) and preneoplastic changes were noted in the liver following 16

chronic administration of 1,4

- dio xane in drinking water ( Argus, et al., 1973 ; JBRC, 1998 ; Kano, 17

et al., 2009 ) . Liver and kidney toxicity appear to be related to saturation of clearance pathways 18

and an increase in the 1,4

- dioxane concen tration in the blood ( Kociba, et al., 1974 ) . Kidney 19

damage was characterized by degeneration of the cortical tubule cells , necrosis with hemorrhage, 20

and glomerulonephritis ( Argus, et al., 1965 ; Argus, e t al., 1973 ; Fairley, et al., 1934 ; Kociba, et 21

al., 1974 ; NCI, 1978 )

. In chronic inhalation studies conducted in rats, nasal and liver toxicity 22

were the primary noncancer health effects. Degeneration of nasal tissue (i.e. metaplasia, 23

hyperplasia, atrophy, hydropic change, and vacu olic change ) and preneoplastic cell proliferation 24

were observed in the nasal cavity following 2 years of 1,4

- dioxane exposure via inhalation 25

( Kasai, et al., 2009 )

. Liver toxicity was described as necrosis of the centrilobular region and 26

preneoplastic changes were noted as well. 27

Several carcinogenicity bioassays have been conducted for 1,4

- dioxane in mice, rats, and 28

guinea pigs ( Argus, et al., 1965 ; Argus, et al., 1973 ; Hoch

- Ligeti & Argus, 1970 ; Hoch

- Ligeti, et 29

al., 1970 ; JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 ; 30

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)

.144

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Torkelson, et al., 1974 )

. Liver tumors (hepatocellular adenomas and carcinomas) have been 1

observed following drinking water exposure in several species and stra ins of rats, mice, and 2

guinea pigs and following inhalation exposure in rats

. Nasal (squamous cell carcinomas), 3

peritoneal, mammary

, Zymbal gland, and subcutaneous tumors were also observed in rats, but 4

were not seen in mice. With the exception of the NCI ( 1978 ) study, the incidence o f nasal cavity 5

tumors was generally lower than that of tumors observed in other tissues of the same study 6

population. 7

Under the Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a )

, 1,4

- dioxane i s 8

―likely to be carcinogenic to humans‖ based on evidence of multiple tissue carcinogenicity in 9

several 2

- year bioassays conducted in three strains of rats, two strains of mice, and in guinea pigs 10

( Argus, et al., 1965 ; Argus, et al., 1973 ; Hoch

- Ligeti & Argus, 1970 ; Hoch

- Ligeti, et al., 1970 ; 11

JBRC, 1998 ; Kano, et al., 2009 ; Kasai, et al., 2009 ; Kociba, et al., 1974 ; NCI, 1978 )

. Stud ies in 12

humans found no conclusive evidence for a causal link between occupational exposure to 13

1,4

- dioxane and increased risk for cancer; however, only two studies were available and these 14

were limited by small cohort size and a small number of reported can cer cases ( Buffler, et al., 15

1978 ; Thiess, et al., 1976 )

. 16

The available evidence is inadequate to estab lish a MOA by which 1,4

- dioxane induces 17

tumors in rats and mice. The genotoxicity data for 1,4

- dioxane is generally characterized as 18

negative, although several studies may suggest the possibility of genotoxic effects ( Galloway, et 19

al., 1987 ; Kitchin & Brown, 1990 ; Mirkova, 1994 ; Morita & Hayashi, 1998 ; Roy, et al., 2005 )

. 20

A MOA hypothesis for liver tumors involving sustained proliferation of spontaneously 21

transformed liver cells has some support by evidence that suggests 1,4

- dioxane is a tumor 22

promoter in mouse skin and rat liver bioassays ( Ki ng, et al., 1973 ; Lundberg, et al., 1987 ) . Some 23

dose

- response and temporal evidence support the occurrence of cell proliferation and hyperplasia 24

prior to the development of liver tumors ( JBRC, 1998 ; Kociba, et al., 1974 ) . However, the dose

25

response relationship for the induction of hepatic cell proliferation has not been characterized, 26

and it is unknown if it would reflect the dose

- response relationship for liver tumors in the 2

- year 27

rat and mouse studies. Conflicting data from rat and mouse bioassays ( JBRC, 1998 ; Kociba, et 28

al., 1974 ) suggest that cytotoxicity is not a required precursor event for 1,4

- dioxa ne

- induced cell 29

proliferation. Liver tumors were observed in female rats and female mice in the absence of 30

lesions indicative of cytotoxicity ( JBRC, 1998 ; Kano, et al., 2009 ; NCI, 1978 ) . Da ta regarding a 31

plausible dose response and temporal progression from cytotoxicity to cell proliferation and 32

eventual liver tumor formation are not available. Hypothesized MOAs by which 1,4

- dioxane 33

induces tumors in other organ systems such as the respirato ry system are uncertain (See Section 34

4.7.3). 35145

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 1

exposed to 1,4

- dioxane in the drinking water for 2 years ( Kociba, et al., 1974 ) . This study was 2

chosen as the principal study because it provides the most sensitive measure of adverse effects 3

by 1,4

- dioxane. The inci dence of liver and kidney lesions was not reported for each dose group. 4

Therefore, BMD modeling could not be used to derive a POD. Instead, the RfD is derived by 5

dividing the NOAEL of 9.6 mg /kg

- day by a composite UF of 300 (factors of 10 for animal

- to

6

hu man extrapolation and interindividual variability, and an UF of 3 for database deficiencies). 7

Information was unavailable to quantitatively assess toxicokinetic or toxicodynamic differences 8

between animals and humans and the potential variability in human susceptibility; thus, the 9

interspecies and intraspecies uncertainty factors of 10 were applied. In addition, a threefold 10

database uncertainty factor was applied due to the lack of information addressing the potential 11

reproductive toxicity associated with 1,4

- dioxane. 12

The overall confidence in the RfD is medium. Confidence in the principal study ( Kociba, 13

et al., 1974 ) is medium. Confidence in the database is medium due to the lack of a 14

multigeneration reproductive toxicity study. Reflecting medium confidence in the principal 15

study and medium confidence in the database, confidence in the RfD is medium. 16

6.2.2. Noncancer/Inhala tion

The RfC of 3 × 10

- 2 mg/m 3 was derived based on olfactory epithelium atrophy in rats 17

exposed for 2 years to 1,4

- dioxane via inhalation ( Kasai, et al., 2009 ) . This study was chosen as 18

the principal study because it provides the adequate study design and most sensitive measure of 19

adverse effects by 1,4

- dioxane. The POD was derived using the LOAEL for olfactory atrophy in 20

male rats from the Kasai et al. ( 2009 ) study. A composite UF of 1 00 0 was applied, consisting 21

of factors of 10 for a LOAEL

- to NOAEL extrapolation and for interindividual variability, and 3 22

fo r animal

- to

- human extrapolation and for database deficiencies. 23

The overall confidence in the RfC is medium. Confidence in the principal study ( Kasai, 24

et al., 2009 ) is medium. Confidence in the database is medium due to the lack of supporting 25

studies and a multigeneration reproductive toxicity study. Reflecting medium confidence in th e 26

principal study and medium confidence in the database, the confidence in the RfC is medium. 27

6.2.3. Cancer

Under EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a )

, 28

1,4

- dioxane is ―likely to be carcinogenic to humans‖ by all routes of exposure. This descriptor is 29

based on evidence of carcinogen icity from animal studies. 30146

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 6.2.3.1. Oral

An oral CSF for 1,4

- dioxane of 0.10 (mg/kg

- day)

- 1 was based on liver tumors in female 1

mice from a chronic study ( Kano, et al., 2009 ) . The available data indicate that the MOA(s) by 2

which 1,4

- dioxane induces peritoneal, mammary, or nasal tumors in rats and liver tumors in r ats 3

and mice is unknown (see Section 4.7.3 for a more detailed discussion of 1,4

- dioxane‘s 4

hypothesized MOAs). Therefore, based on the U.S. EPA ‘s Guidelines for Carcinogen Risk 5

Assessment ( U.S. EPA, 2005a ) , a linear low dose extrapolation was used. The POD was 6

calculated by curve fitting the animal expe rimental dose

- response data from the range of 7

observation and converting it to a HED (BMDL 50 HED of 4.95 mg /kg

- day). 8

The uncertainties associated with the quantitation of the oral CSF are discussed below. 9

6.2.3.2. Inhalation

An inhalation unit risk (IUR) for 1,4

- dioxane of 5 x 10

- 6 ( μ g/m 3 )

- 1 was based on a chronic 10

inhalation study conducted by Kasai et al. ( 2009 ) , Statistically significant increases in tumor 11

incidence and positive dose

- response trends were observed at multiple sites in the male rat 12

including the nasal cavity (squamous cell carcinoma), liver (adenoma), peritoneal 13

(mesothelioma), and the subcutis (fibroma). Statistically significant dose

- response trends were 14

also observed in the kidney (carcinoma), mammary gland (fibroadenoma), and the Zymbal gland 15

(adenoma). The available data indicate that the MOA(s) by which 1,4

- dioxane induces tumors in 16

rats is unknown (see Section 4.7.3 for a more detailed discussion of 1,4

- dioxane‘s hypothesized 17

MOAs). Therefore, based on the U.S. EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. 18

EPA, 2005a ) , a linear low dose extrapolation was used. A Bayesian approach (see Section 19

5. 4.3.2 and Appendix G for details) was used to calculate the POD for the total tumor risk 20

following inhalation of 1,4

- dioxane. The POD was calculated by curve fitting the animal 21

experimental dose

- response data from the range of observation a nd converting it to a continuous 22

human equivalent exposure. 23

The uncertainties associated with the quantitation of the IUR are discussed below. 24

6.2.3.3. Choice of Low

- Dose Extrapolation Approach

The range of possibilities for the low

- dose extrapolation of tumor ri sk for exposure to 25

1,4

- dioxane, or any chemical, ranges from linear to nonlinear, but is dependent upon a plausible 26

MOA(s) for the observed tumors. The MOA is a key consideration in clarifying how risks 27

should be estimated for low

- dose exposure. Exposur e to 1,4

- dioxane has been observed in 28

animal models to induce multiple tumor types, including liver adenomas and carcinomas, nasal 29

carcinomas, mammary adenomas and fibroadenomas, and mesotheliomas of the peritoneal cavity 30

( Kano, et al., 2009 ) . MOA information that is available for the carcinogenicity of 1, 4

- dioxane 31

has largely focused on liver adenomas and carcinomas, with little or no MOA information 32

available for the remaining tumor types. In Section 4.7.3, hypothesized MOAs were explored 33

for 1,4

- dioxane. Data are not available to support a carcinogeni c MOA for 1,4

- dioxane. In the 34147

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE absence of a MOA(s) for the observed tumor types associated with exposure to 1,4

- dioxane, a 1

linear low

- dose extrapolation approach was used to estimate human carcinogenic risk associated 2

with 1,4

- dioxane exposure. 3

In genera l, the Agency has preferred to use the multistage model for analyses of tumor 4

incidence and related endpoints because they have a generic biological motivation based on 5

long

- established mathematical models such as the MVK model. The MVK model does not 6

nec essarily characterize all modes of tumor formation, but it is a starting point for most 7

investigations and, much more often than not, has provided at least an adequate description of 8

tumor incidence data. 9

The multistage cancer model did provide good fits f or the tumor incidence data following 10

a 2

- year inhalation exposure to 1,4

- dioxane by male rats ( Kasai, et al., 2009 ) . However, in the 11

studies evaluated for the oral cancer assessment ( Kano, et al., 2009 ; Kociba, et al., 1974 ; NCI, 12

1978 ) the multistage model provided good descriptions of the incidence of a few tumor types in 13

male (nasal cavity) and female (hepatocel lular and nasal cavity) rats and in male mice 14

(hepatocellular) exposed to 1,4

- dioxane (see Appendix D for details). However, the multistage 15

model did not provide an adequate fit for female mouse liver tumor dataset based upon the 16

following ( U.S. EPA, 2000a ) : 17

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 18

document ( U.S. EPA, 2000a ) by imposing constraints on the values of certain parameters of the 19

models. When these constraints were imposed, the multistage model and most other models did 20

not fit the incidence data for fe male mouse liver adenomas or carcinomas. 21

The log

- logistic model was selected because it provides an adequate fit for the female 22

mouse data ( Kano, et al., 2009 ) . A BMR of 50% was used because it is proximate to the 23

response at the lowest dose tested and the BMDL 50 was derived by applying appropriate 24

paramet er constraints, consistent with recommended use of BMDS in the BMD technical 25

guidance document ( U.S. EPA, 2000a )

. 26

The human equivalent oral CSF estimated from liver tumor datasets with statistically 27

significant increases ranged from 4.2 × 10

- 4 to 1.0 × 10

- 1 per mg /kg

- day, a range of about three 28

or ders of magnitude, with the extremes coming from the combined male and female data for 29

hepatocellular carcinomas ( Kociba, et al., 1974 ) and the female mouse liver adenoma and 30

carcinoma dataset ( Kano, et al., 2009 )

. 31148

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 6.2.3.4. Dose Metric

1,4

- Dioxane is known to be metabolized in vivo. However, evidence does not exist to 1

determine whether the parent compound, metabolite(s), or a combination of the parent compound 2

and metabolites is responsible for the observed toxicity following exposure to 1,4

- dioxane. If the 3

actual carcinogenic moiety is proportional to administered exposure, then use of administered 4

exposure as the dose metric is the least biased choice. On the other hand, if this is not the correct 5

dose metric, then the impact on the CSF is unknown. 6

6.2.3.5. Cross

- Species Scaling

For the oral cancer assessment , an adjustment for cross

- species scaling (BW 0.75 ) was 7

applied to address toxicological equivalence of internal doses between each rodent species and 8

humans, consistent with the Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a ) . It is 9

assumed that equal risks result from equivalent constant lifetime exposures. 10

Differences in the anatomy of the upper respiratory tract and resulting differences in 11

absorption or in loca l respiratory system effects are sources of uncertainty in the inhalation 12

cancer assessment. 13

6.2.3.6. Statistical Uncertainty at the POD

Parameter uncertainty can be assessed through confidence intervals. Each description of 14

parameter uncertainty assumes that t he underlying model and associated assumptions are valid. 15

For the log

- logistic model applied to the female mouse data following oral exposure , there is a 16

reasonably small degree of uncertainty at the 50% excess incidence level (the POD for linear 17

low

- dose extrapolation). For the multistage model applied for the male rat inhalation dataset, 18

there is a reasonable small degree of uncertainty at t he 10% extra risk level (the POD for linear 19

low

- dose extrapolation). 20

6.2.3.7. Bioassay Selection

The study by Kano et al. ( 2009 ) was used for development of an oral CSF. This was a 21

well

- designed study, conducted in both sexes in two species (rats and mice) with a sufficient 22

number (N=50) of animals per dose group. The number o f test animals allocated among three 23

dose levels and an untreated control group was adequate, with examination of appropriate 24

toxicological endpoints in both sexes of rats and mice. Alternative bioassays ( Kociba, et al., 25

1974 ; NCI, 1978 ) were available and were fully considered for the derivation of the oral CSF. 26

The study by Kasai et al. ( 2009 ) was used for derivation of an inhalation unit risk. This 27

was a well

- designed and peer reviewed study, conducted in male rats with a sufficient number 28

(N=50) of animals per dose group. Three dose levels plus an untreated control group were 29

examined following exposure to 1,4

- dioxane via inhalation for 2 years. Other bioassays ( Kasai, 30

et al., 2008 ; Torkelson, et al., 1974 ) were available and were fully considered for the derivation 31

of the inhalation unit risk. 32149

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 6.2.3.8. Choice of Species/Gender

The oral CSF for 1,4

- dioxane was derived using the tumor incidence data for the female 1

mouse, which was thought to be more sensitive than male mice or either sex of rats to the 2

carcinogenicity of 1,4

- dioxane. While all data, from both species and sexes reported from the 3

Kano et al. ( 2009 ) study, were suitable for deriving an oral CSF, the female mouse data 4

represented the most sensitive indicator of carcinogenicity in the rodent model. T he lowest 5

exposure level (66 mg /kg

- day [animal dose] or 10 mg /kg

- day [HED]) observed a considerable 6

and significant increase in combined liver adenomas and carcinomas. Additional testing of doses 7

within the range of control and the lowest dose (66 mg /kg

- d ay [animal dose] or 10 mg /kg

- day 8

[HED]) could refine and reduce uncertainty for the oral CSF. 9

Male F344 rat data were used to estimate risk following inhalation of 1,4

- dioxane. Kasai 10

et al. ( 2008 ) showed that male rats were more sensitive than female rats to the effects of 1,4

- 11

dioxane following inhalation; therefore, male rats were chosen to be studie d in the 2

- year 12

bioassay conducted by the same laboratory ( Kasai, et al., 2009 )

. 13

6.2.3.9. Relevance to Humans

The oral CSF was derived using the tumor incidence in the liver of female mice. A 14

thorough review of the available toxicological data available for 1,4

- dioxane provides no 15

scientific justification to prop ose that the liver adenomas and carcinomas observed in animal 16

models following exposure to 1,4

- dioxane are not plausible in humans. Liver adenomas and 17

carcinomas were considered plausible outcome s in humans due to exposure to 1,4

- dioxane. 18

The derivation of the inhalation unit risk is based on the tumor incidence at multiple sites 19

in male rats. There is no information on 1,4

- dioxane to indicate that the observed rodent tumors 20

are not relevant to humans. Further, no data exist to guide quantitative adjust ment for 21

differences in sensitivity among rodents and humans. 22

6.2.3.10. Human Population Variability

The extent of inter

- individual variability in 1,4

- dioxane metabolism has not been 23

characterized. A separate issue is that the human variability in response to 1, 4

- dioxane is also 24

unknown. Data exploring whether there is differential sensitivity to 1,4

- dioxane carcinogenicity 25

across life stages is unavailable. This lack of understanding about potential differences in 26

metabolism and susceptibility across exposed h uman populations thus represents a source of 27

uncertainty. Also, the lack of information linking a MOA for 1,4

- dioxane to the observed 28

carcinogenicity is a source of uncertainty. 29150

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

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. 4

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27A

- 1

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC

COMMENTS AND DISPOSITION

Note: The comments and responses in this appendix were in regards to the oral 1

assessment previously reviewed. A summary of external peer review and public comments and 2

disposition following review of the inhalation assessment for 1,4

- dioxane will be included wh en 3

they become available. 4

The Toxicological Review of 1,4

- Dioxane has undergone formal external peer review 5

performed by scientists in accordance with EPA guidance on peer review ( U.S. EPA, 2000b

, 6

2006b ) . The external peer reviewers were tasked with providing written answers to general 7

questions on the overall assessment and on chemical

- specific questions in areas of scientific 8

controversy or uncertainty. A summary of significant comments made by the external reviewers 9

and EPA‘s responses to these comments arranged by charge question follow. In many cases the 10

comments of the individual reviewers have been synthesized and paraphrased for development of 11

Appendix A. The majority of the specific observations (in addition to EPA‘s charge questions) 12

made by the peer reviewers were incorporated into the document and are not discussed further in 13

this Appendix. Public comments that were received are summarized and addressed fo llowing the 14

peer

- reviewers‘ comments and disposition. 15

A.1. EXTERNAL PEER REVIEW PANEL COMMENTS

The reviewers made several editorial suggestions to clarify portions of the text. These 16

changes were incorporated in the document as appropriate and are not discuss ed further. 17

In addition, the external peer reviewers commented on decisions and analyses in the 18

Toxicological Review of 1,4

- Dioxane under multiple charge questions, and these comments were 19

organized and summarized under the most appropriate charge questio n. 20

A.1.1. General Charge Questions

1. Is the Toxicological Review logical, clear and concise? Has EPA accurately, clearly and 21

objectively represented and synthesized the scientific evidence for noncancer and cancer 22

hazards? 23

Comment : All reviewers found the Toxicological Review to be logical, clear, and concise. 24

One reviewer remarked that it was an accurate, open

- minded and balanced analysis of the 25

literature. Most reviewers found that the scientific evidence was presented objectively 26

and transparently; how ever, one reviewer suggested two things to improve the objectivity 27

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

- 2

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE and transparency (1) provide a clear description of the mode of action and how it feeds 1

into the choice of the extrapolation for the cancer endpoint and (2) provide a presentation 2

of the ou tcome if internal dose was used in the cancer and noncancer assessments. 3

One reviewer commented that conclusions could not be evaluated in a few places 4

where dose information was not provided ( Section s 3.2, 3.3 and 4.5.2.2). The same 5

reviewer found the M OA schematics, key event temporal sequence/dose

- response table, 6

and the POD plots to be very helpful in following the logic employed in the assessment. 7

8

Response : The mode of action analysis and how conclusions from that analysis fed into 9

the choice of ex trapolation method for the cancer assessment are discussed further under 10

charge questions C2 and C5. Because of the decision not to utilize the PBPK models, 11

internal doses were not calculated and thus were not included as alternatives to using the 12

externa l dose as the POD for the cancer and noncancer assessments. 13

In the sections noted by the reviewer (3.2, 3.3, and 4.5.2.2) dose information was 14

added as available. In Section 3.2, Mikheev et al. ( 1990 ) did not report actual doses, 15

which is noted in this section. All other dose information in this section was found to be 16

present after further review by the Agency. In Section 3.3, dose information for Woo 17

et al. ( 1977a ; 1978 ) was added to the paragraph. In S ection 4.5.2.2, study details for 18

Nannelli et al. ( 2005 ) were provided earlier in S ection 3.3 and a statement referring the 19

reade r to this section was added. 20

21

2. Please identify any additional studies that should be considered in the assessment of the 22

noncancer and cancer health effects of 1,4

- dioxane. 23

Comment : Five reviewers stated they were unaware of any additional studies available to 24

add to the oral toxicity evaluation of 1,4

- dioxane. These reviewers also acknowledged 25

the Kasai et al. ( 2009 ; 2008 ) publications that may be of use to derive toxicity values 26

following inhalation of 1,4

- dioxane. 27

a. Kasai T; Saito H; Senoh Y; et al. ( 2008 ) Thirteen

- week inhalation toxicity of 28

1,4

- dioxane in rats. Inhal Toxicol 20: 961

- 971. 29

b. Kasai T; Kano Y; Umeda T; et al. ( 2009 ) Two

- year inhalation study of 30

carcinogenicity and chronic toxicity of 1,4

- dioxane in male rats. Inhal Toxicol in 31

press

. 32

Other references suggested by reviewers include: 33

c. California Department of Health Services (1989) Risk Specific Intake Levels for 34

the Proposition 65 Carcinogen 1, 4

- dioxane. Reproductive and Cancer Hazard 35

Assessment Section. Office of Environmental Health Hazard Assessment 36A

- 3

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE d. National Research Council ( 2009 ) Science and Decisions: Advancing Risk 1

Assessment. Committee on Improving Risk Analysis Approaches Used by the 2

U.S. EPA. Washington, D.C., National Academy Press. 3

e. ATSDR ( 2007 ) Toxicological Profile for 1,4

- dioxane. Agency for Toxic 4

Substances and Disease Registry. Atlanta, GA. 5

f. Stickney JA; Sager SL; Clarkson JR; et al. ( 2003 ) An updated evaluation of the 6

carcinogenic potential of 1,4

- dioxane. Regul Toxicol Pharmacol 38: 183

- 195. 7

g. Yam amoto S; Ohsawa M; Nishizawa T; et al

. ( 2000 ) Long

- term toxicology 8

study of 1,4

- dioxane in R344 r ats by multiple

- route exposure (drinking water and 9

inhalation). J Toxicol Sci 25: 347. 10

11

Response : The references a

- b above will be evaluated for derivation of an RfC and IUR, 12

which will follow as an update to this oral assessment. References c and e note d above 13

were considered during development of this assessment as to the value they added to the 14

cancer and noncancer analyses. Reference g listed above is an abstract from conference 15

proceedings from the 27 th Annual Meeting of the Japanese Society of Toxi cology; 16

abstracts are not generally considered in the development of an IRIS assessment. 17

Reference d reviews EPA‘s current risk assessment procedures and provides no specific 18

information regarding 1,4

- dioxane. The Stickney et al. ( 2003 ) reference was a review 19

article and no new data were presented, thus it was not referenced in this Toxicological 20

Review but the data were considered during the development of this assessment. 21

Following external peer review (as noted above) Kano et al. ( 2009 ) was added to 22

the assessment, which was an update and peer

- reviewed published manuscript of the 23

JBRC ( 1998 ) report. 24

25

3. Please discuss research that you think would be likely to increase confidence in the database 26

for future assessments of 1,4

- dioxane. 27

Comment : All reviewers provided suggestions for additional research that would 28

strengthen the assessment and reduce uncerta inty in several areas. The following is a 29

brief list of questions that were identified that could benefit from further research. What 30

are the mechanisms responsible for the acute and chronic nephrotoxicity? Is the acute 31

kidney injury (AKI) multifactorial? Are there both tubular and glomerular/vascular 32

toxicities that result in cortical tubule degeneration and evidence for glomerulonephritis ? 33

What are the functional correlates of the histologic changes in terms of assessment of 34

renal function? What is the e xposure in utero and risk to the fetus and newborn? What are 35

the concentrations in breast milk following maternal exposure to 1,4

- dioxane? What is 36

the risk for use of contaminated drinking water to reconstitute infant formula? What are 37A

- 4

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE the exposures during early human development? What is the pharmacokinetic and 1

metabolic profile of 1,4

- dioxane during development? What are the susceptible 2

populations (e.g., individuals with decreased renal function or chronic renal disease, 3

obese individuals, gender, age)? 4

Additional suggestions for future research include: evaluation of potential 5

epigenetic mechanisms of carcinogenicity, additional information on sources of exposure 6

and biological concentrations as well as human toxicokinetic data for derivation of 7

paramet er to refine PBPK model, studies to determine toxic moiety, focused studies to 8

inform mode of action, additional inhalation studies and a multigeneration reproductive 9

toxicity study. 10

One reviewer suggested additional analyses of the existing data includin g a 11

combined analysis of the multiple datasets and outcomes for cancer and non

- cancer 12

endpoints, evaluation of the dose metrics relevant to the MOA to improve confidence in 13

extrapolation approach and uncertainty factors, and complete a Bayesian analysis of 14

human pharmacokinetic data to estimate human variability in key determinants of 15

toxicity (e.g., metabolic rates and partition coefficients). 16

17

Response : A number of research suggestions were provided for further research that may 18

enhance future health asse ssments of 1,4

- dioxane. Regarding the suggested additional 19

analyses for the existing data, EPA did not identify a MOA in this assessment, thus 20

combined analysis of the cancer and non

- cancer endpoints as well as application of 21

various dose metrics to a MOA is not applicable. Because the human PBPK model was 22

not implemented in this assessment for oral exposure to 1,4

- dioxane a Bayesian analysis 23

was not completed. No additional changes to the Toxicological Review of 1,4

- Dioxane 24

were made in response to thes e research recommendations. 25

26

4. Please comment on the identification and characterization of sources of uncertainty in 27

Sections 5 and 6 of the assessment document. Please comment on whether the key sources of 28

uncertainty have been adequately discussed. Have t he choices and assumptions made in the 29

discussion of uncertainty been transparently and objectively described? Has the impact of the 30

uncertainty on the assessment been transparently and objectively described? 31

Comment : Six reviewers stated Sections 5 and 6 adequately discussed and characterized 32

uncertainty, in a succinct, and transparent manner. One reviewer suggested adding 33

additional discussion of uncertainty relating to the critical study used in the cancer 34

assessment and another reviewer suggested addin g more discussion around the 35

uncertainty of the toxic moiety. 36A

- 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE One reviewer made specific comments on uncertainty surrounding the Kociba et 1

al. ( 1974 ) study as used for derivation of the RfD, choice of the non

- cancer dose metric, 2

and use of a 10%BMR as the basis for the CSF derivation. These comments and 3

responses are summarized below under their appropriate charge question. 4

5

Response : The m ajority of the reviewers thought the amount of uncertainty discussion 6

was appropriate. Since the external review, Kano et al. ( 2009 ) was published and this 7

assessment was updated accordingly (previously JBRC ( 1998 ) . It is assumed the 8

uncertainty referred to by the reviewer was addressed by the published Kano et al. ( 2009 ) 9

paper. 10

Clarification regarding the uncertainty surrounding th e identification of the toxic 11

moiety was added to Section 4.6.3 stating that the mechanism by which 1,4

- dioxane 12

induces tissue damage is not known, nor is it known whether the toxic moiety is 13

1,4

- dioxane or a metabolite of 1,4

- dioxane. Additional text was added to Section 4.7.3 14

clarifying that available data also do not clearly identify whether 1,4

- dioxane or one of its 15

metabolites is responsible for the observed effects. The impact of the lack of evidence to 16

clearly identify a toxic moiety related to 1,4

- dioxane exposure was summarized in 17

Section s 5.5.1.2 and 6.2.3.2. 18

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, 19

et al., 1974 ) in rats and mice. Please comment on whether the selection of this study as the 20

principal study has been scientifically justified. Has the selection of this study be en 21

transparently and objectively described in the document? Are the criteria and rationale for 22

this selection transparently and objectively described in the document? Please identify and 23

provide the rationale for any other studies that should be selected a s the principal study. 24

Comment : Seven of the reviewers agreed that the use of the Kociba et al. ( 1974 ) study 25

was the best choice for the pri ncipal study. 26

One reviewer stated that Kociba et al. ( 1974 ) was not the best choice because it 27

reported only NOAEL and LOAELs without provi ding incidence data for the endpoints. 28

This reviewer also stated that the study should not have been selected based on sensitivity 29

of the endpoints, but rather study design and adequacy of reporting of the study results. 30

Additionally, this reviewer sugge sted a better principal study would be either the NCI 31

( 1978 ) or JBRC ( 1998 ) study. 32

33

Response : The reviewer is correct that Ko ciba et al. ( 1974 ) did not provide incidence 34

data; however, Kociba et al. ( 1974 ) identified a NOAEL (9.6 mg /kg

- day) and LOAEL 35

(94 mg /kg

- day) within the text of the manuscript. Kociba et al. ( 1974 ) was a well 36A

- 6

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE conducted chronic bioassay (four dose levels, including controls, with 60 rats/sex/group) 1

and seven of the peer reviewers found this study to be appropriate as the basis for the 2

RfD. Further support for the sel ection of the Kociba et al. ( 1974 ) as the principal study 3

comes from comparison of the liver and kidney toxicity data reported by JBRC ( 1998 ) 4

and NCI ( 1978 ) , which was presented in Section 5.1. The effects reported by JBRC 5

( 1998 ) and NCI ( 1978 ) were consistent with what was observed by Kociba et al. ( 1974 ) 6

and within a similar dose range. Derivation of an RfD from these datasets resulted in a 7

similar value ( Section 5.1.). 8

9

2. Degenerative liver and kidney effects were selected as the critical effect. Please comment on 10

whether the rationale for the selection of this critical effect has been scientifically justified. 11

Are the criteria and rationale for this selection transparently and objectively described in the 12

document? Please provide a detailed explanation. Please comment on whether EPA‘s 13

rationale regarding adversity of the critical effect for the RfD has been adequately and 14

transparently described and is scientifically supported by the available data. Please identify 15

and provide the rationale for any other endpoints that should be considered in the selection of 16

the critical effect. 17

Comment : Five of the reviewers agreed with the selection of liver and kidney effects as 18

the critical effect. One of these reviewers suggested analyzing all datasets following dos e 19

adjustment (e.g., body weight scaling or PBPK model based) to provide a better rationale 20

for selection of a critical effect. 21

One reviewer stated that 1,4

- dioxane causing liver and kidney organ specific 22

effects is logical; however, with regards to nephrot oxicity, the models and limited human 23

data have not addressed the mechanisms of injury or the clinical correlates to the 24

histologic data. Also, advances in the field of biomarkers have not yet been used for the 25

study of 1,4

- dioxane. 26

One reviewer found the selection of these endpoints to be  ̳without merit‘ because 27

of the lack of incidence data to justify the NOAEL and LOAEL values identified in the 28

study. This reviewer suggested selecting the most sensitive endpoint(s) from the NCI 29

( NCI, 1978 ) or JBRC ( 1998 ) studies for the basis of the RfD, but did not provide a 30

suggestion as to what effect should be selected. 31

32

Response : The liver and kidney effects from Kociba et al. ( 1974 ) was supported as the 33

critical effect by most of the reviewers. PBPK model adjustment was not performed 34

because the PBPK model was found to be inadequate for use in the assessment. EPA 35

acknowledges that neither the mechanisms of injury nor the clinical correlates to 36A

- 7

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE histologic data exist for 1,4

- dioxane. This type of information could improve future 1

health assessments of 1,4

- dioxane. 2

As stated above, Kociba et al. ( 1974 ) identifie d a NOAEL (9.6 mg /kg

- day) and 3

LOAEL (94 mg /kg

- day) within the text of the manuscript and was a well conducted 4

chronic bioassay (four dose levels, including controls, with 60 rats/sex/group). 5

6

3. Kociba et al. ( 1974 ) derived a NOAEL based upon the observation of degenerative liver and 7

kidney effects and these data were utilized to derive the point of departure (POD) for the 8

RfD. Please provide co mments with regard to whether the NOAEL approach is the best 9

approach for determining the POD. Has the approach been appropriately conducted and 10

objectively and transparently described? Please identify and provide rationales for any 11

alternative approaches for the determination of the POD and discuss whether such 12

approaches are preferred to EPA‘s approach. 13

Comment : Seven reviewers agreed with the NOAEL approach described in the 14

document. One of these reviewers also questioned whether any attempt was made to 15

―semi

- qualitatively represent the histopathological observations to facilitate a quantitative 16

analysis‖. 17

One reviewer stated that data were not used to derive the POD, but rather a claim 18

by the authors of Kociba et al. ( 1974 ) of the NOAEL and LOAEL for the endpoints. This 19

reviewer preferred the use of a BMD approach for which data include the reported 20

incidence rather than a study reported NOAEL or LOAEL. 21

22

Response : The suggestion to ―semi

- qualitatively represent the histopathological 23

observations to facilitate a quantitative analysis‖ was not incorporated into the document 24

because it is unclear how this would be conducted since Kociba et al

. ( 1974 ) did not 25

provide incidence data and the reviewer did not illustrate their suggested approach. See 26

responses to B1 and B2 regarding the NOAEL and LOAEL approach. The Agency 27

agrees that a Benchmark Dose approach is preferred over the use of a NOAEL or 28

LOAEL for the POD if suitable data (e.g., reflecting the most sensitive sex, species, and 29

endpoint identified) are available for modelin g and, if suitable data are not available, then 30

NOAEL and LOAEL values are utilized. In this case, the data were not suitable for 31

BMD modeling and the LOAEL or NOAEL approach was used. 32

33

4. EPA evaluated the PBPK and empirical models available to describe ki netics following 34

inhalation of 1,4

- dioxane ( Reitz, et al., 1990 ; Young, et al., 1978a ; Young, et al., 1978b ; 35

Young, et al., 1977 ) . EPA concluded that the use of existing, revised, and recalibrated PBPK 36

models for 1,4

- dioxane were not superior to default approaches for the dose

- extrapolation 37A

- 8

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE between species. Please comment on whether EPA‘s rationale regarding the decision to not 1

utilize existing or revised PBPK models has been adequately and transparently described and 2

is supported by the available data. Please identify and provide the rationale for any 3

altern ative approaches that should be considered or preferred to the approach presented in the 4

toxicological review. 5

Comment : Six reviewers found the decision not to utilize the available PBPK models to 6

be appropriate and supported by available data. One of thes e reviewers suggested 7

presenting as part of the uncertainty evaluation an adjustment of the experimental doses 8

based on metabolic saturation. Another reviewer stated Appendix B was hard to follow 9

and that the main document should include a more complete d escription of the model 10

refinement effort performed by Sweeney et al. ( 2008 )

. 11

Two revie wers noted a complete evaluation of the models was evident; one of the 12

reviewers questioned the decision not to use the models on the basis that they were 13

unable to fit the human blood PK data for 1,4

- dioxane. This reviewer suggested the rat 14

model might f it the human blood PK data, thus raising concern in the reliance on the 15

human blood PK data to evaluate the PBPK model for 1,4

- dioxane. Instead, the reviewer 16

suggested the human urinary metabolite data may be sufficient to give confidence in the 17

model. On e other reviewer also questioned the accuracy of the available human data. 18

One reviewer commented that the rationale for not using the PBPK model to extrapolate 19

from high to low dose was questioned. In addition, the reviewer suggested that two 20

aspects of the model code for Reitz et al. ( 1990 ) need to be verified: 21

a. In the document, KLC is defined as a first

- o rder rate constant and is scaled by 22

BW 0.7 . This is inconsistent when multiplied by concentration does not result 23

in units of mg /hr. However, if the parameter is actually considered a 24

clearance constant (zero

- order rate constant) then the scaling rule use d, as well 25

as the interpretations provided, would be acceptable. 26

b. It is unclear as to why AM is calculated on the basis of RAM and not RMEX. 27

RMEX seems to represent the amount metabolized per unit time. 28

29

Response : The USEPA performed a rigorous evaluation of the PBPK models available 30

for 1,4

- dioxane. This effort was extensively described in Section 3.5 and in Appendix B. 31

In short, several procedures were applied to the human PBPK model to determine if an 32

adequate fit of the model to the empirical model ou tput or experimental observations 33

could be attained using biologically plausible values for the model parameters. The re

34

calibrated model predictions for blood 1,4

- dioxane levels did not come within 10

- fold of 35

the experimental values using measured tissue :air partition coefficients of ( Leung & 36

Paustenbach, 1990 ) or ( Sweeney, et al., 2008 ) (Figures B

- 8 and B

- 9). The utilization of a 37A

- 9

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE slowly perfused tissue:air partition coefficient 10

- fold lower than measured values 1

produces exposure

- phase predictions that are much closer to observations, but does not 2

replicate the elimination kinetics ( Figure B

- 10). Re

- calibration of the model with upper 3

bounds on the tissue:air partition coefficients results in predictions that are still six

- to 4

sevenfold lower than empirical model prediction or observations (Figures B

- 12 and B

5

13). Exploration of the model space using an assumption of first

- order metabolism (valid 6

for the 50 ppm inhalation exposure) showed that an adequate fit to the exposure and 7

elimina tion data can be achieved only when unrealistically low values are assumed for 8

the slowly perfused tissue:air partition coefficient ( Figure B

- 16). Artificially low values 9

for the other tissue:air partition coefficients are not expected to improve the mode l fit, as 10

these parameters are shown in the sensitivity analysis to exert less influence on blood 11

1,4

- dioxane than V

max C and K

m . In the absence of actual measurements for the human 12

slowly perfused tissue:air partition coefficient, high uncertainty exists for this model 13

parameter value. Differences in the ability of rat and human blood to bind 1,4

- dioxane 14

may contribute to the difference in V d . However, this is expected to be evident in very 15

different values for rat and human blood:air partition coefficie nts, which is not the case 16

( Table B

- 1). Therefore, some other, as yet unknown, modification to model structure 17

may be necessary. 18

The results of USEPA‘s model evaluation were confirmed by other investigators 19

( Sweeney, et al., 2008 ) . Sweeney et al. ( 2008 ) concluded that the available PBPK model 20

with refinements resulted in an under

- prediction of human blood levels for 1,4

- dioxane 21

by six

- to seven fold. It i s anticipated that the high uncertainty in predictions of the 22

PBPK model for 1,4

- dioxane would not result in a more accurate derivation of human 23

health toxicity values. 24

Because it is unknown whether the parent or the metabolite is the toxic moiety, 25

analyses were not conducted to adjust the experimental doses on the basis of metabolic 26

saturation. 27

The discussion of Sweeney et al. ( 2008 ) was expanded in the main document in 28

Section 3.5.3. In the absence of evidence to the contrary, the Agency cannot discount the 29

human blood kinetic data published by Young et al. ( 1977 ) . Even though the PBPK 30

model provided satisfactory fits to the rodent kinetic data, it was not used to extrapolate 31

from high dose to low dose in the a nimal because an internal dose metric was not 32

identified and external doses were utilized in derivation of the toxicity values. 33

KLC was implemented by USEPA during the evaluation of the model and should 34

have been described as a clearance constant (zero

- ord er rate constant) with units of 35

L/hr/kg 0.70 . These corrections have been made in the document; however, this does not 36A

- 10

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE impact the model predictions because it was in reference to the terminology used to 1

describe this constant. 2

The reviewer is correct that RMEX is the rate of metabolism of 1,4

- dioxane per 3

unit time; however an amount of 1,4

- dioxane metabolized was not calculated in the Reitz 4

et al. ( 1990 ) model code. Thus, AM is the amount of the metabolite (i.e., HEAA) in the 5

body rather than the amount metabolized of 1,4

- dioxane. RAM was published by Reitz 6

et al. ( 1990 ) as equation 2 for the change in the amount of metabolite in the body per unit 7

time. AMEX is the amount of the me tabolite excreted in the urine. While the variables 8

used are confusing, the code describes the metabolism of 1,4

- dioxane as published in the 9

manuscripts. The comments in the model code were updated to make this description 10

more clear ( Appendix B). 11

12

5. Pleas e comment on the selection of the uncertainty factors applied to the POD for the 13

derivation of the RfD. For instance, are they scientifically justified and transparently and 14

objectively described in the document? If changes to the selected uncertainty fact ors are 15

proposed, please identify and provide a rationale(s). Please comment specifically on the 16

following uncertainty factors: 17

An interspecies uncertainty factor of 10 was used to account for uncertainties in 18

extrapolating from laboratory animals to human s because a PBPK model to support 19

interspecies extrapolation was not suitable. 20

An intraspecies (human variability) uncertainty factor of 10 was applied in deriving the 21

RfD because the available information on the variability in human response to 22

1,4

- dioxan e is considered insufficient to move away from the default uncertainty factor 23

of 10. 24

A database uncertainty factor of 3 was used to account for lack of adequate 25

reproductive toxicity data for 1,4

- dioxane, and in particular absence of a 26

multigeneration repr oductive toxicity study. Has the rationale for the selection of these 27

uncertainty factors been transparently and objectively described in the document? 28

Please comment on whether the application of these uncertainty factors has been 29

scientifically justified

. 30

31

Comment : 32

One reviewer noted the uncertainty factors appear to be the standard default choices and 33

had no alternatives to suggest. 34

o Five reviewers agreed that the use of an uncertainty factor of 10 for the interspecies 35

extrapolation is fully supportable. One reviewer suggested using BW 3/4 scaling 36

rather than an uncertainty factor of 10 for animal to human extrapolation. Along 37A

- 11

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE the same lines, one reviewer suggested a steady

- state quantitative analysis to 1

determine the importance of pulmonary clearance and hepatic clearance and stated 2

that if hepatic clearance scales to body surface and pulmonary clearance is 3

negligible, then an adjusted uncertainty factor based on body surface scaling would 4

be more appropriate. 5

o Seven reviewers stated that the uncertainty f actor of 10 for interindividual 6

variability (intraspecies) is fully supportable. 7

o Six reviewers commented that the uncertainty factor of 3 for database deficiencies 8

is fully justifiable. One reviewer suggested adding text to clearly articulate the 9

science p olicy for the use of a factor of 3 for database deficiencies. 10

11

Response : The preferred approach to interspecies scaling is the use of a PBPK model; 12

however, the PBPK models available for 1,4

- dioxane are not suitable for use in this 13

health assessment as outlined elsewhere. Another approach that has been commonly 14

implemented in the cancer assessments is the use of body weight scaling based on body 15

surface area (BW 3/4 scaling). It is not standard practice to apply BW 3/4 scaling in 16

noncancer assessments at this time

. The current default approach used by the Agency 17

when PBPK models are not available for extrapolation is the application of an UF A of 10, 18

which was implemented in this assessment. 19

The absence of a multigenerational reproductive study is why the uncertainty 20

factor for database deficiencies (UFD) was retained; however, it was reduced from 10 to 21

3. In the text in Section 5.1.3 text was included to clearly state that because of the 22

absence of a multigenerational reproductive study for 1,4

- dioxa ne an uncertainty factor of 23

3 was used for database deficiencies. No other changes regarding the use of the 24

uncertainty factors were made to the document. 25

A.1.3. Carcinogenicity of 1,4

- dioxane

1. Under the EPA‘s 2005 Guidelines for Carcinogen Risk Assessment 26

(www. epa.gov/iris/backgr

- d.htm), the Agency concluded that 1,4

- dioxane is likely to be 27

carcinogenic to humans. Please comment on the cancer weight of evidence characterization. 28

Has the scientific justification for the weight of evidence descriptor been sufficie ntly, 29

transparently and objectively described? Do the available data for both liver tumors in rats 30

and mice and nasal, mammary, and peritoneal tumors in rats support the conclusion that 31

1,4

- dioxane is a likely human carcinogen? 32

Comment : All reviewers agree d with the Agency‘s conclusion that 1,4

- dioxane is ― likely 33

to be carcinogenic to humans ‖ . However, two reviewers also thought 1,4

- dioxane could 34

be categorized as a potential human carcinogen, since low

- dose environmental exposures 35

would be unlikely to res ult in cancer. One reviewer also suggested providing a brief 36A

- 12

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE recapitulation of the guidance provided by the 2005 Guidelines for Carcinogen Risk 1

Assessment regarding classification of a compound as likely to be carcinogenic to 2

humans and how a chemical fal ls into this category. 3

4

Response : The document includes a weight

- of

- evidence approach to categorize the 5

carcinogenic potential of 1,4

- dioxane. This was included in Section 4.7.1 based upon 6

U.S. EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a )

. 1,4

- Dioxane 7

can be described as likely to be carcinogenic to humans based on evidence of liver 8

carcinogenicity in several 2

- year bioassays conducted in three strains of rats, two strains 9

of mice, and in guinea pigs. Additionally, tumors in other organs and ti ssues have been 10

observed in rats due to exposure to 1,4

- dioxane. 11

12

2. Evidence indicating the mode of action of carcinogenicity of 1,4

- dioxane was considered. 13

Several hypothesized MOAs were evaluated within the Toxicological Review and EPA 14

reached the conclu sion that a MOA(s) could not be supported for any tumor types observed 15

in animal models. Please comment on whether the weight of the scientific evidence supports 16

this conclusion. Please comment on whether the rationale for this conclusion has been 17

transpar ently and objectively described. Please comment on data available for 1,4

- dioxane 18

that may provide significant biological support for a MOA beyond what has been described 19

in the Toxicological Review. Considerations should include the scientific support reg arding 20

the plausibility for the hypothesized MOA(s), and the characterization of uncertainty 21

regarding the MOA(s). 22

Comment : Three reviewers commented that the weight of evidence clearly supported the 23

conclusion that a mode of action could not be identified for any of the tumor sites. One 24

reviewer commented that there is inadequate evidence to support a specific MOA with 25

any confidence and low

- dose linear extrapolation is necessary ; this reviewer also pointed 26

out that EPA should not rule out a metabolite as the toxic moiety. 27

One reviewer stated this was outside of his/her area of expertise but indicated that 28

the discussion was too superficial and suggested adding statements as to what the Agency 29

would consider essential information to make a determination about a MOA. 30

Two reviewers commented that even though the MOA for 1,4

- dioxane is not clear 31

there is substantial evidence that the MOA is non

- genotoxic

. O ne of these reviewer s also 32

suggested that a nonlinear cancer risk assessment model should be utilized

. 33

One reviewer suggested adding more text to the summary statement to fully 34

reflect the available MOA information which should be tied to the conclusion and choice 35

of an extrapolation model. 36

37A

- 13

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Response : The Agency agrees with the reviewer not to rule out a toxic metabolite as the 1

toxic moiety. In Section 5.5.1.2 text is included relating that there is not enough 2

information to determine whether the parent compound, its metabolite (s) , or a 3

combination is responsible for the observed toxicities following e xposure to 1,4

- dioxane. 4

It is not feasible to describe the exact data that would be necessary to conclude 5

that a particular MOA was operating to induce the tumors observed following 6

1,4

- dioxane exposure. In general, the data would fit the general criteri a described in the 7

U.S. EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a )

. For 8

1,4

- dioxane, several MOA hypotheses have been proposed and are explored for the 9

observed liver tumors in Section 4.7.3. This analysis represents the extent to which data 10

could provide support for any particular MOA. 11

One reviewer suggested that the evidence indicating that 1,4

- dioxane is not 12

genotoxic supports a nonlinear approach to low

- dose extrapolation. In accordance with 13

the U.S. EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a ) , the 14

absence of evidence for genotoxicity does not invoke the use of nonlinear low

- dose 15

extrapolation, nor does it define a MOA. A nonlinear low

- dose extrapolation can be 16

utilized when a MOA supporting a nonlinear dose response is identified. For 1,4

- dioxane 17

this is not the case; a cancer MOA for any of the tumor types observed in animal models 18

has not been elucidated. Therefore, as concluded in the Toxicological Review, the 19

application of a nonlinear low

- dose extrapolation approach was not supported. 20

Additional text has been added to Section 5.4.3.2 to relay the fact that several 21

reviewers recommended that the MOA data support the use of a nonlinear extrapolation 22

approach to estimate human carcinogenic risk associated with exposure to 1,4

- dioxane 23

and that such an approach should be presented in the Toxicological R eview. Additional 24

text has also been added to the summary statement in Section 6.2.3 stating that the weight 25

of evidence is inadequate to establish a MOA(s) by which 1,4

- dioxane induces peritoneal, 26

mammary, or nasal tumors in rats and liver tumors in rats and mice (see Section 4.7.3 for 27

a more detailed discussion of 1,4

- dioxane‘s hypothesized MOAs). 28

29

3. A two

- year drinking water cancer bioassay ( JBRC, 1998 ) was selected as the principal study 30

for the development of an oral slope factor (OSF). Please comment on the appropriateness of 31

the selection of the principal study. Has the rationale for this choice been transparently and 32

objectively described? 33

Comment : 34

Seven reviewers agreed with the choice of the JBRC ( 1998 ) study as the principal 35

study for the dev elopment of an OSF. However, two reviewers that agreed with the 36

choice of JBRC ( 1998 ) also commented on the description and evaluation of the study. 37A

- 14

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE One reviewer commented the evaluation of the study should be separated from the 1

evaluation/selection of endpoints within the study. The other reviewer suggested that 2

details on the following aspects should be added to improve transparency of the study: 3

(1) rationale for selection of doses; (2) temporal information on body weight for 4

individual treatment gro ups; (3) temporal information on mortality rates; and (4) dosing 5

details. 6

One reviewer thought that the complete rationale for selection of the JBRC ( 1998 ) 7

study was not provided because there was no indication of whether the study was 8

conducted under GLP cond itions, and the study was not peer reviewed or published. This 9

reviewer noted the NCI ( 1978 ) study was not appropriate fo r use, but that the Kociba et 10

al. ( 1974 ) study may have resulted in a lower POD had they employed both sexes of mice 11

and combined benign and malignant tumors. 12

13

Response : Since the External Peer Review draft of the Toxicological Review of 14

1,4

- Dioxane was released ( U.S. EPA, 2009b ) , the cancer portion of the study conducted 15

by th e JBRC laboratory was published in the peer

- reviewed literature as Kano et al. 16

( 2009 ) . This manuscript was reviewed by EPA

. EPA determined that the data published 17

by Kano et al. ( 2009 ) should be included in the assessment of 1,4

- dioxane for several 18

reasons: (1) w hile the JBRC ( 1998 ) was a detailed laboratory report, it was not peer

19

reviewed; (2) the JBRC improved the diagnosis of pre

- and neoplastic lesions in the liver 20

according to the current diagnostic criteria and submitted the manuscript based on this 21

updated data; (3) the Kano et al. ( 2009 ) peer

- reviewed manuscript included additional 22

information such as body weight growth curves and means and standard deviations of 23

estimated dose for both rats and m ice of both sexes. Th us, the Toxicological Review was 24

updated to reflect the inclusion of the data from Kano et al. ( 2009 ) , and Appendix E was 25

added for a clear and transparent display of the data included in the multiple reports. 26

In response to the peer reviewers, d ose information was updated throughout the 27

assessment an d are also provided in detail in Section 4.2.1.2.6, along with temporal 28

information on body weights and mortality. T ext was also added to Section 4.2.1.2.6 29

regarding the choice of high dose selection as included in the Kano et al. ( 2009 ) 30

manuscript. Additional discussion regarding the mortality rates was also added to 31

Section 5.4.1 in selection of the critical study for the oral cancer assessment. 32

Documentation that the study was conducted in accordance with Organization for 33

Economic Co

- operation and Development (OECD) P rinciples of Good Laboratory 34

Practice (GLP) is provided in the manuscript ( Kano, et al., 2009 ) and this was also added 35

to the text in Section 4.2.1.2.6

. 36

37A

- 15

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 4. Combined liver tumors (adenomas and carcinomas) in female Cjr: BDF 1 mice from the JBRC 1

( 1998 ) study were chosen as the most sensitive species and gender for th e derivation of the 2

final OSF. Please comment on the appropriateness of the selections of species and gender. 3

Please comment on whether the rationale for these selections is scientifically justified. Has 4

the rationale for these choices been transparently a nd objectively described? 5

Comment : Six reviewers agreed the female Cjr: BDF 1 mice should be used for the 6

derivation of the OSF. Five of these reviewers agreed with the rationale for the selection 7

of the female Cjr: BDF 1 mouse as the most sensitive gender an d species. However, one 8

reviewer suggested that the specific rationale (i.e., that the final OSF is determined by 9

selecting the gender/species that gives the greatest OSF value) be stated clearly in a 10

paragraph separate from the other considerations of st udy selection. 11

One reviewer was unsure of both the scientific justification for combining benign 12

and malignant liver tumors, as well as the background incidence of the observed liver 13

tumors in historical control Cjr: BDF 1 male and female mice. 14

One reviewer commented that the scientific basis for the selection of female 15

Cjr: BDF 1 mice was unclear. This reviewer thought that the rationale for the choice of 16

this strain/sex compared to all others was not clearly articulated. 17

18

Response : Using the approach desc ribed in the Guidelines for Carcinogen Risk 19

Assessment ( U.S. EPA, 2005a ) studies were first evaluated based on their quality and 20

suitability for inclusion in the assessment. Once the studies were found to be of sufficient 21

quality for inclusion in the assessment, the dose

- response analysis was performed with 22

the goal of determ ining the most appropriate endpoint and species for use in the 23

derivation of an OSF. These topics are discussed in detail in Section 4.7 and 5.4. 24

Benign and malignant tumors that arise from the same cell type (e.g., 25

hepatocellular) may be combined to mor e clearly identify the weight of evidence for a 26

chemical. This is in accordance with the US EPA‘s 2005 Guidelines for Carcinogen Risk 27

Assessment as referenced in the Toxicological Review. In the absence of a MOA (MOA 28

analysis described in detail in Sectio n 4.7.) for 1,4

- dioxane carcinogenicity, it is not 29

possible to determine which species may more closely resemble humans. Text in Section 30

5.4.4 indicates that the c alculation of an OSF for 1,4

- dioxane is based upon the dose

31

response data for the most sensit ive species and gender

. 32

33

5. Has the scientific justification for deriving a quantitative cancer assessment been 34

transparently and objectively described? Regarding liver cancer, a linear low

- dose 35

extrapolation approach was utilized to derive the OSF. Please p rovide detailed comments on 36

whether this approach to dose

- response assessment is scientifically sound, appropriately 37A

- 16

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE conducted, and objectively and transparently described in the document. Please identify and 1

provide the rationale for any alternative appro aches for the determination of the OSF and 2

discuss whether such approaches are preferred to EPA‘s approach. 3

Comment : Four reviewers agreed with the approach for the dose

- response assessment. 4

One reviewer commented that even if a nongenotoxic MOA were ide ntified for 5

1,4

- dioxane it may not be best evaluated by threshold modeling. One reviewer 6

commented the use of the female mouse data provided an appropriate health protective 7

and scientifically valid approach. 8

One reviewer commented that the basic adjustments and extrapolation method for 9

derivation of the OSF were clearly and adequately described, but disagreed with the 10

linear low

- dose extrapolation. This reviewer suggested that the lack of certainty regarding 11

t he MOA was not a sufficient cause to default to a linear extrapolation. Another reviewer 12

commented that the rationale for a linear low

- dose extrapolation to derive the OSF was 13

not clear, but may be in accordance with current Agency policy in the absence of a 14

known MOA. This reviewer also commented that 1,4

- dioxane appears to be non

15

genotoxic and nonlinear models should be tested on the available data to determine if 16

they provide a better fit and are more appropriate. 17

One reviewer thought that the justifica tion for a linear extrapolation was not 18

clearly provided and that a disconnect between the MOA summary and the choice of a 19

linear extrapolation model existed. In addition, this reviewer commented that the 20

pharmacokinetic information did not support the us e of a linear extrapolation approach, 21

but rather use of animal PBPK models to extrapolate from high to low dose that would 22

result in a mixture of linear and nonlinear extrapolation models was warranted. 23

One reviewer suggested consideration of an integrated assessment of the cancer 24

and noncancer endpoints; however, if linear low

- dose extrapolation remains the approach 25

of choice by the Agency, then the effect of choosing BMRs other than 10% was 26

recommended to at least be included in the uncertainty discussion . Using BMRs lower 27

than 10% may allow for the identification of a risk level for which the low

- dose slope is 28

 ̳best‘ estimated. 29

30

Response : The EPA conducted a cancer MOA analysis evaluating all of the 31

available data for 1,4

- dioxane. Application of the f ramework in the USEPA‘s Guidelines 32

for Carcinogen Risk Assessment ( 2005a ) demonstrates that the available evidence to 33

support any hypothesized MOA for 1,4

- dioxane

- induced tumors does not exist. In the 34

absence of a MOA, the USEPA‘s Guidelines for Carcinogen Risk Assessment ( 2005a ) 35

indicate that a low dose linear extrapolation should be utilize d for dose response analysis 36

(see Section 5.4). Some of the potential uncertainty associated with this conclusion was 37A

- 17

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE characterized in Section 5.5. Note that there is no scientific basis to indicate that in the 1

absence of evidence for genotoxicity a nonl inear low

- dose extrapolation should be used. 2

As concluded in the Toxicological Review, the application of a nonlinear low

- dose 3

extrapolation approach was not supported. 4

With regards to the PBPK model available for 1,4

- dioxane, it is clear that there 5

curre ntly exist deficiencies within the model and as such, the model was not utilized for 6

interspecies extrapolation. Given the deficiencies and uncertainty in the 1,4

- dioxane 7

model it also does not provide support for a MOA. 8

Lastly, in the absence of a MOA for 1,4

- dioxane carcinogenicity it is not possible 9

to harmonize the cancer and noncancer effects to assess the risk of health effects due to 10

exposure. However, the choice of the BMDL 10 ,which was more than 15

- fold lower than 11

the response at the lowest dose (66 mg /kg

- day), was reconsidered in response to a public 12

comment . BMDs and BMDLs were calculated using a BMR of 30 and 50% extra risk 13

(BMD 30 , BMDL 30 , BMD 50 , and BMDL 50 ). A BMR of 50% was used as it resulted in a 14

BMDL closest to the response level at the lowest dose tested in the bioassay. 15

A.2. PUBLIC COMMENTS

Comments on the Toxicological Review of 1,4

- Dioxane submitted by the public are summarized 16

below in the following categories: Oral reference dose for 1,4

- dioxane, c arcinogenicity of 17

1,4

- dioxane, PBPK modeling, and other comments. 18

A.2.1. Oral reference dose (RfD) for 1,4

- dioxane

Comment : An UF for database deficiencies is not necessary because of considerable 19

evidence showing no reproductive or developmental effects from 1,4

- dioxane exposure. 20

21

Response : Due to the lack of a multigenerational reproductive study for 1,4

- dioxane an 22

UF of 3 was retained for database deficiencies. Without clear evidence showing a lack of 23

reproductive or developmental effects in a multigenerational reproductive study, there is 24

sti ll uncertainty in this area. 25

26

A.2.2. Carcinogenicity of 1,4

- dioxane

Comment : Using liver tumors as the basis for the oral CSF is more appropriate than 27

nasal tumors (1988 IRIS assessment of 1,4

- dioxane); however, t he use of mouse liver 28

tumor data is inappropriate because it is inconsistent with other liver models both 29

quantitatively and in the dose

- response pattern. High mortality rates in the study are also 30

a limitation. Liver tumor data from rats should be used instead, which represents a better 31

animal model for 1,4

- dioxane carcinogenicity assessment. 32A

- 18

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

Response : Even though the dose

- response is different for mice and rats, the female mice 2

were considered to be appropriate for the carcinogenicity assessment for s everal reasons. 3

The female mouse liver tumors from the Kano et al. ( 200 9 ) report were found to be the 4

most sensitive species and endpoint. Section 4.2.1.2.6 was updated to include additional 5

information on mortality rates. The majority of the animals lived past 52 weeks (only 4 6

females died prior to 52 weeks , 2 in each th e mid

- and high

- dose groups). The cause of 7

death in the female mice that died between 1 and 2 years was attributed to liver tumors. 8

9

Comment : The OSF was based on the most sensitive group, Crj: BDF 1 mice; however 10

BDF 1 mice have a high background rate of liver tumors. The incidence of liver tumors in 11

historical controls for this gender/species should be considered in the assessment. 12

Sensitivity of the test species/gender as well as other criteria should be considered i n the 13

selection of the appropriate study, including internal and external validity as outlined in 14

Lewandowski and Rhomberg ( 2005 )

. The female Crj: BDF 1 mice had a low survival rat e 15

that should be considered in the selection of the animal model for 1,4

- dioxane 16

carcinogenicity. 17

18

Response : Katagiri et al. ( 1998 ) summarized the incidence of h epatocellular adenomas 19

and carcinomas in control male and female BDF 1 mice from ten 2

- year bioassays at the 20

JBRC. For female mice, out of 499 control mice, the incidence rates were 4.4% for 21

hepatocellular adenomas and 2.0% for hepatocellular carcinomas. Kano et al. ( 2009 ) 22

reported a 10% incidence rate for hepatocellular adenomas and a 0% incidence rate for 23

hepatocellular carcinomas in control female BDF 1 . These incidence rates are near the 24

historical control values and thus are appropriate for consideration in this assessment. 25

Additional text regarding these historical controls was added to the study description in 26

Section 4.2.1.2.6. 27

28

Comment : Low

- dose linear extrapolation for the oral CSF is not appropriate nor justified 29

by the data. The weight of evidence supports a threshold ( nonlinear ) MOA when 30

metabolic pathway is saturated at high doses. Nonlinear extrapolations should be 31

evaluated and presented for 1,4

- dioxane. Oral CSFs should be derived and presented 32

using both the BW 3/4 scaling as well as available PBPK models to extrapolate across 33

species. 34

35

Response : The absence of evidence for genotoxicity/mutagenicity does not indicate the 36

use of nonlinear low

- dose extrapolation. For 1,4

- dioxane, a MOA to explain the 37A

- 19

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE induction of tumors does not exist so the nature of the low

- dose region of the dose

1

response is unknown. The oral CSF for 1,4

- dioxane was derived using BW 3/4 scaling for 2

interspecies extrapolation. The PBPK and empirical models available for 1,4

- dioxane 3

were evaluated and found not to be adequate for use in this assessment , described in 4

detail in Appendix B

. 5

6

Comment: The POD for the BDF 1 female mouse is 15

- fold lower than the lowest dose 7

in the bioassay, thus the POD is far below the lower limit of the data and does not follow 8

the U.S. EPA‘s Guidelines for Carcinogen Risk Assessment ( U.S. EPA, 2005a )

. 9

10

Response : The comment is correct that the animal B MDL 10 was more than 15

- fold 11

lower than the response at the lowest dose (66 mg /kg

- day) in the bioassay. BMDs and 12

BMDLs were calculated using a BMR of 30 and 50% extra risk (BMD 30 , BMDL 30 , 13

BMD 50 , and BMDL 50 ). A BMR of 50% was chosen as it resulted in a BMD L closest to 14

the response level at the lowest dose tested in the bioassay. 15

16

Comment : The geometric mean of the oral cancer slope factors (as done with B[a]P & 17

DDT) should have been used instead of relying on the female BDF 1 mouse data, since a 18

MOA coul d not be determined for 1,4

- dioxane

. 19

20

Response : In accordance with the BMD technical guidance document ( U.S. EPA, 2000a )

, 21

averaging tumor incidence is not a standard or default approach. Averaging the tumor 22

incidence response diminishes the effect seen in the sensitive species/gender. 23

24

Comment : EPA should c ritically reexamine the choice of JBRC ( 1998 ) as the principal 25

study since it has not been published or peer

- reviewed. A transcript of e

- mail 26

correspondence should be provided

. 27

28

Response : JBRC ( 1998 ) was published as conference proceedings as Yamazaki et al. 29

( 1994 ) and recently in t he peer

- reviewed literature as Kano et al. ( 2009 ) . Additional study 30

information was also gathered from the authors ( Yamazaki, 2006 ) and is available upon 31

request from the IRIS Hotline. The peer

- reviewed and published data from Kano et al. 32

( 2009 ) was incorporated into the final version of the Toxicological Review of 33

1,4

- Dioxane. 34

35

Comment : The WOE does not support a cancer descriptor of likely to be carcinogenic to 36

humans determination, but rather suggesti ve human carcinogen at the high dose levels 37A

- 20

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE used in rodent studies seems more appropriate for the following reasons: 1) lack of 1

conclusive human epidemiological data; 2) 1,4

- dioxane is not mutagenic; and 3) evidence 2

at high doses it would act via cell prol iferation MOA. 3

4

Response: A cancer c lassification of ― likely

, ” based on evidence of liver carcinogenicity 5

in several two

- year bioassays conducted in three strains of rats, two strains of mice, and 6

in guinea pigs was chosen . Also, mesotheliomas of the peri toneum, mammary, and nasal 7

tumors have been observed in rats. The Agency agrees that human epidemiological 8

studies are inconclusive. The evidence at any dose is insufficient to determine a MOA. 9

10

A.2.3. PBPK Model ing

Comment : EPA s hould have used and considered PBPK models to derive the oral 11

toxicity values (rat to human extrapolation) rather than relying on a default method

. The 12

draft did not consider the Sweeney et al. ( 2008 ) model. The PBPK model should be used 13

for both noncancer and cancer dose extrapolation. 14

15

Response : The Agency evaluated the Sweeney et al. ( 2008 ) publication and this was 16

included in Appendix B of the document. Text was added to the main document in 17

Section 3.5.2.4 and 3.5.3 regarding the evaluation of Sweeney et al. ( 2008 )

. This model 18

was determined not to be appropriate for interspecies extrapolation. Additionally, see 19

response to the external peer review panel comment B4. 20

21

Comment : EPA should use the modified inhalation inputs used in the Reitz et al. ( 1990 ) 22

model and the updated input parameters provided in Sweeney et al. ( 2008 ) and add a 23

compartment for the kidney 24

25

Response : See response to previous comment regarding evaluation of Sweene y et al. 26

( 2008 ) . Modification of the model to add a kidney compartment is not within t he scope 27

of this assessment. 28

A.2.4. Other Comments

Comment: EPA should consider the Kasai et al. ( 2009 ; 2008 ) studies for inhalation and 29

MOA relevance. 30

31

Response: The 13 week and 2

- year inhalation studies by Kas a i et al. ( 2009 ; 2008 ) were 32

published late in the development stage of this assessment. The IR IS Program will 33A

- 21

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE evaluate these recently published 1,4

- dioxane inhalation data for the potential to derive 1

an RfC in a separate assessment. 2

3

Comment : 1,4

- Dioxane is not intentionally added to cosmetics and personal care 4

products

– correct sentence on page 4. 5

6

Response : This oversight was corrected in the document

. 7B

- 1

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX B. EVALUATION OF EXISTING PBPK MODELS FOR 1,4

- DIOXANE

B.1. BACKGROUND

Several pharmacokinetic models have been developed to predict the absorption, 1

distribution, met abolism, and elimination of 1,4

- dioxane in rats and humans. Single 2

compartment, empirical models for rats ( Young, et al., 1978a ; Young, et al., 1978b ) and humans 3

( Young, et al., 1977 ) were developed to predict blood levels of 1,4

- dioxane and urine levels of 4

the primary metabolite, β

- hydroxyethoxy acetic acid (HEAA). Physiologically based 5

pharmacokinetic (PBPK) models that describe the kinetics of 1,4

- dioxane using biologically 6

realistic flow rates, tissue volumes and affinities, metabolic processes, and elimination behaviors, 7

were also developed ( Fisher, et al., 1997 ; Leung & Paustenbach, 1990 ; Reitz, et al., 1990 )

. 8

In developing updated toxicity values for 1,4

- dioxane, the available PBPK models were 9

evaluated for their abil ity to predict observations made in experimental studies of rat and human 10

exposures to 1,4

- dioxane. The model of Reitz et al. ( 1990 ) was identified for further 11

consideration to assist in the derivation of toxicity values. Issues related to the biological 12

plausibility of parameter values in the Reitz et al. ( 1990 ) human model were identified. The 13

model was able to predict the only available human inhalation data set ( Young, et al., 1977 ) by 14

increasing (i.e., doubling) parameter values for human alveolar ventilation, cardiac output, and 15

the blood:air partition coefficient a bove the measured values. Furthermore, the measured value 16

for the slowly perfused tissue:air partition coefficient (i.e., muscle) was replaced with the 17

measured liver value to improve the fit. Analysis of the Young et al. ( 1977 ) human data 18

suggested that the apparent volume of distribution (V d ) for 1,4

- dioxane was approximately 10

- 19

fold higher in rats than humans, presumably due to sp ecies differences in tissue partitioning or 20

other process not represented in the model. Subsequent exercising of the model demonstrated 21

that selecting a human slowly perfused tissue:air partition coefficient much lower than the 22

measured rat value resulted in better agreement between model predictions of 1,4

- dioxane in 23

blood and experimental observations. Based upon these observations, several model parameters 24

(e.g., metabolism/elimination parameters) were re

- calibrated using biologically plausible values 25

for flow rates and tissue:air partition coefficients. 26

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

- 2

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE This appendix describes activities conducted in the evaluation of the empirical models 1

( Young, et al., 1978a ; Young, et al., 1978b ; Young, et al., 1977 ) , and re

- calibration and 2

exercising of the Reitz et al. ( 1990 ) PBPK model, and evaluation of the Sweeney et al. ( 2008 ) 3

model to determine the potential utility of the PBPK models for 1,4

- dioxane for interspecies and 4

route

- to

- route extrapolation. 5

B.2. SCOPE

The scope of this effort consisted of implementation of the Young et al. ( 1978a ; 1978b ; 6

1977 ) empirical rat and human models using the acslXtreme simulation software, re

- calibration 7

of the Reitz et al. ( 1990 ) human PBPK model, and evaluation of model parameters published by 8

Sweeney et al. ( 2008 ) . Using the model descriptions and equations given in Young et al. ( 1978a ; 9

1978b ; 1977 )

, model code was developed for the empiri cal models and executed, simulating the 10

reported experimental conditions. The model output was then compared with the model output 11

reported in Young et al. ( 1978a ; 1978b ; 1977 )

. 12

The PBPK model of Reitz et al. ( 1990 ) was re

- calibrated using measured values for 13

cardiac and alveolar flow rates and ti ssue:air partition coefficients. The predictions of blood and 14

urine levels of 1,4

- dioxane and HEAA, respectively, from the re

- calibrated model were 15

compared with the empirical model predictions of the same dosimeters to determine whether the 16

re

- calibrated PBPK model could perform similarly to the empirical model. As part of the PBPK 17

model evaluation, EPA performed a sensitivity analysis to identify the model parameters having 18

the greatest influence on the primary dosimeter of interest, the blood level of 1,4

- dioxane. 19

Variability data for the experimental measurements of the tissue:air partition coefficients were 20

incorporated to determine a range of model outputs bounded by biologically plausible values for 21

these parameters. Model parameters from Sweeney et al. ( 2008 ) were also tested to evaluate the 22

ability of the PBPK model to predict hum an data following exposure to 1,4

- dioxane. 23

B.3. IMPLEMENTATION OF TH E EMPIRICAL MODELS I N acsl X treme

The empirical models of Young et al. ( 1978a ; 1978b ; 1977 ) for 1,4

- dioxane in rats and 24

humans were reproduced using acslXtreme, version 2.3 (Aegis Technologies, Huntsville, AL). 25

Model code files were developed using the equations described in the published papers. 26

Additional files containing experiment

- specific information (i.e., BWs, exposure levels, and 27

duration) we re also generated. 28

B.3.1. Model Descriptions

The empirical model of Young et al. ( 1978a ; 1978b ) for 1,4

- dioxane in rats is shown in 29

Figure B

- 1. This is a single

- compartment model that describes the absorption and metabolism 30

kinetics of 1,4

- dioxane in blood and urine. No info rmation is reported describing pulmonary 31B

- 3

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE absorption or intravenous ( i.v.) injection/infusion of 1,4

- dioxane. The metabolism of 1

1,4

- dioxane and subsequent appearance of HEAA is described by Michaelis

- Menten kinetics 2

governed by a maximum rate (V

max , μg/mL

- hour) and affinity constant (K

m , μg/mL) . Both 3

1,4

- dioxane and HEAA are eliminated via the first

- order elimination rate constants, k

e and k

me , 4

respectively (hour

- 1 ) by which 35% of 1,4

- dioxane and 100% of HEAA appear in the urine, 5

while 65% of 1,4

- dioxane is exhal ed. Blood concentration of 1,4

- dioxane is determined by 6

dividing the instantaneous amount of 1,4

- dioxane in blood by a V d of 301 mL/kg BW. 7

Source: Used with permission from Taylor & Francis, Young et al. ( 1978a ; 1978b )

.

Figure B

- 1. Schematic representa tio n of empirical model for 1,4

- dioxane in

rats.

Figure B

- 2 illustra

tes the empirical model for 1,4

- dioxane in humans as described in 8

Young et al. ( 1977 ) . Like the rat model, the human model predicts blood 1,4

- dioxane and 9

urinary 1,4

- dioxane and HEAA levels using a single

- compartment structure. However, the 10

metabolism of 1,4

- dioxane to HEAA in humans is modeled as a first

- order process governed by 11

a rate constant, K M (hour

- 1 ). Urinary deposition of 1,4

- dioxane and HEAA is described using the 12

first order rate constants, k e(diox) and k me(HEAA) , respectively. Pulmonary absorption is described 13

by a fixed rate of 76.1 mg /hour (k INH ). Blood concentrat ions of 1,4

- dioxane and HEAA are 14

calculated as instantaneous amount (mg) divided by V d(diox) or V d(HEAA) , respectively (104 and 15

480 mL/kg BW, respectively). 16B

- 4

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Taylor & Francis, Young et al. ( 1977 )

.

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 1

modifications arose in some cases from incomplete reporting of the Young et al. ( 1978a ; 1978b ; 2

1977 ) studies and in other cases from the desire to add capabilities to the mo dels to assist in the 3

derivation of toxicity values. 4

For the rat model, no information was given by Young et al. ( 1978a ; 1978b ) regarding 5

the parameterization of pulmonary absorption (or exhalation) or i.v. administration of 6

1,4

- dioxane. Therefore, additional parameters were added to simulate these processes in the 7

simplest form. To replicate 1,4

- dioxane inhalation, a first

- order rate constant, k INH (hour

- 1 ), was 8

introduced. k INH was multiplied by the inhalation concentration and the respiratory minute 9

volume of 0.238 L/minute ( Young, et al., 1978a ; 1978b ) . The value for k INH was estimated by 10

optimization against the blood time course data of Young et al. ( 1978a ; 1978b ) . Intravenous 11

(i.v.) administration was modeled as instantaneous appearance of the full dos e at the start of the 12

simulation. Rat urinary HEAA data were reported by Young et al. ( 1978a ; 1978b ) in units of 13

concentration. To simulate urinary HEAA concentration, an estimate of urine volume was 14

required. Since observed urinary volumes were not reported by Young et al. ( 1978a ; 1978b ) , a 15

standard rat urine production rate of 0.00145 L/hour was used. 16

For humans, Young et al. ( 1977 ) used a fixed 1,4

- dioxane inhalation uptake rate of 17

76.1 mg /hour, which corresponded to observations during a 50 ppm exposure. In order to 18

facilitate user

- specified inhalation concentrations, pulmonary absorption was modeled. The 19

modeling was performed identically to the rat mode l, but using a human minute volume of 20

7 L/minute. Urinary HEAA data were reported by Young et al. ( 1977 ) as a cumulative amount 21

(mg ) of HEAA. Cumulative amount of HEAA in the urine is readily calculated from the rate of 22B

- 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE transfer of HEAA from plasma to urine, so no modification was necessary to simulate this dose 1

metric for humans. 2

Neither empirical model of Young et al. ( 1978a ; 1978b ; 1977 ) described oral uptake of 3

1,4

- dioxane. Adequate data to estimate oral absorption parameters are not available for either 4

rats or humans; therefore, neither empirical model was modified to include oral u ptake. 5

B.3.3. Results

The acslXtreme implementation of the Young et al. ( 1978a ; 1978b ) rat em pirical model 6

simulates the 1,4

- dioxane blood levels from the i.v. experiments identically to the model output 7

reported in the published pape r ( Figure B

- 3). However, the acslXtreme version predicts urinary 8

HEAA concentrations in rats that are approximately threefold lower and reach a maximum 9

sooner than the predicted levels reported in the paper ( Figure B

- 4). These discrepancies may be 10

due, a

t least in part, to the reliance in the acslXtreme implementation on a constant, standard, 11

urine volume rather than experimental measurements, which may have been different from the 12

assumed value and may have varied over time. Unreported model parameters (e.g., lag times for 13

appearance of excreted HEAA in bladder urine) may also contribute to the discrepancy. 14

Source: Used with permission from Taylor & Francis, Young et al. ( 1978a ; 1978b )

.

Figure B

- 3. Output of 1,4

- dioxane blood level data from the acslXtreme

implem entation (left) and published (right) empirical rat model simulations

of i.v. administration experiments.B

- 6

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Us ed with p ermission from Taylor & Francis, Y oung et al. ( 1978a ; 1978b )

.

Figure B

- 4. Output of HEAA urine le vel data from acslXtreme

implementation (left) and published (right) empirical rat model simulations

of i.v. administration experiments.

The Young et al. ( 1978a ; 1978b ) report did not provide model predictions for the 50

- ppm 1

inhalation experiment. However, the acslXtre me im plementation produces blood 1,4

- dioxane 2

predictions that are quite similar to the reported observations ( Figure B

- 5). As with the urine 3

data from the i.v. experiment, the acslXtreme

- predicted urinary HEAA concentrations are 4

approximately threefold lo wer than the observations, presumably for the same reasons discussed 5

above for the i.v. predictions. 6B

- 7

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Taylor & Francis, Young et al. ( 1978a ; 1978b )

.

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 1

acslXtreme predictions of the blood 1,4

- dioxane observations are identical to the predictions 2

reported in Young et al. ( 1977 ) ( Figure B

- 6). Limited blood HEAA data were reported, and the 3

specimen analysis was highly problematic (e.g., an analytical interference was sometimes present 4

from which HEAA could not be separated). For this reason, You ng et al. ( 1977 ) did not compare 5

predictions of the blood HEAA data to observations in their manuscript. 6B

- 8

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permi ssion from Taylor & Francis, Young et al. ( 1978a ; 1978b )

.

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 ) , and no 1

analytical problems for these data were reporte d. Nevertheless, model predictions for urinary 2

HEAA were not presented in the manuscript. The acslXtreme prediction of the HEAA kinetics 3

profile is similar to the observations, although predicted values are approximately 1.5

- to 2

- fold 4

lower than the obs erved values ( Figure B

- 7). Unlike urinary HEAA observations in the rat, 5

human observations were reported as cumulative amount produced, negating the need for urine 6

volume data. Therefore, discrepancies between model predictions and experimental observati ons 7

for humans cannot be attributed to uncertainties in urine volumes in the subjects . Further 8

evaluation of the Young et al. ( 1977 ) empirical model was conducted against subchronic 9

inhalation exposure data reported by Kasai et al. ( 2008 ) . In the experime ntal study, male and 10

female F344 rats were exposed to 0, 100, 200, 400, 800, 1,600, 3,200, or 6,400ppm 1,4

- dioxane 11

in a 13

- week inhalation study. The simulations of the Young et al. ( 1977 ) model did not provide 12

an adequate fit (Figure B

- 8 ) for the measured plasma levels at each exposure level of 1,4

- dioxane 13

as reported by Kasai et al. ( 2008 )

. 14

15B

- 9

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Taylor & Francis, Young et al. ( 1977 )

.

Figure B

- 7. Observations and acslXtreme predictions of cumulative HEAA

in human urine following a 6

- hour, 50

- ppm inhalation exposure.

Figure B

- 8. EPA

- modified Young et al. empirical model prediction (line) of

pla sma 1,4

- dioxane levels in rats following exposure to 1,4

- dioxane for 13

weeks compared to data from Kasai et al. ( 2008 )

.

B.3.4. Conclusions for Empirical Model Implementation

The empirical models described by Young et al. ( 1978a ; 1978b ; 1977 ) for rats and 1

humans were implemented using acslXtreme. The models were modified to allow for us er

2

defined inhalation levels by addition of a first

- order rate constant for pulmonary uptake of 3B

- 10

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1,4

- dioxane, fitted to the inhalation data. No modifications were made for oral absorption as 1

adequate data are not available for parameter estimation. The ac slXtreme predictions of 2

1,4

- dioxane in the blood are identical to the published predictions for simulations of 6

- hour, 50

- 3

ppm inhalation exposures in rats and humans and 3 to 1,000 mg /kg i.v. doses in rats (Figures B

4

3, B

- 5, and B

- 6). However, the acslXt reme version predicts lower urinary HEAA concentrations 5

in rats appearing earlier than either the Young et al. ( 1978a ; 1978b ) model predictions or the 6

experimental observations. The lower predicted urinary HEAA levels in the acslXtreme 7

implementation for rats is likely due to use of default values for urine volume in the absence of 8

measured volumes. The reason for differences in time

- to

- peak levels is unknown, but may be 9

the result of an unreported adjustment by Young et al. ( 1978a ; 1978b ) in model parameter 10

values. Additionally, the modified Young et al. ( 1978a ; 1978b ; 1977 ) model failed to provide 11

adequate fit to blood data reported following su bchronic inhalation of 1,4

- dioxane in rats ( Kasai, 12

et al., 2008 )

. For humans, Young et al. ( 1977 ) did not report model predictions of urinary HEAA 13

levels. The urinary HEAA levels predicted by acslXtreme were low relative to the observati ons. 14

However, unlike the situation in rats, these data are not dependent on unreported urine volumes 15

(observations were reported as cumulative HEAA amount rather than HEAA concentration), but 16

reflect the model parameter values reported by Young et al. ( 1977 ) . Presently, there is no 17

explanation for the lack of fit of the reported urinary HEAA elimination rate constant to the 18

observati ons. 19

B.4. INITIAL RE

- CALIBRATION OF THE P BPK MODEL

Concern regarding adjustments made to some of the parameter values in Reitz et al. 20

( 1990 ) prompted a re

- calibration of the Reitz et al. ( 1990 ) human PBPK model usin g more 21

biologically plausible values for all measured parameter values. Reitz et al. ( 1990 ) doubled the 22

measured physiological flows and blood:air partition coefficient and substituted the slowly

23

perfused tissue:air partition coefficient with the liver:air value in order to attain an adequate fit to 24

the observations. This approach increases uncertainty in t hese parameter values, and in the 25

utilization of the model for cross

- species dose extrapolation. Therefore, the model was re

26

calibrated using parameter values that are more biologically plausible to determine whether an 27

adequate fit of the model to the av ailable data can be attained. 28

B.4.1. Sources of Values for Flow Rates

The cardiac output of 30 L/hour/kg 0.74 ( Table B

- 1) reported by Reitz et al. ( Reitz, et al., 29

1990 ) is approximately double the mean resting value of 14 L/hour/kg 0.74 reported in the widely 30

accepted compendium of Brown et al. ( 1997 )

. R esting cardiac output was reported to be 5.2 31

L/minute (or 14 L/hour/kg 0.74 ), while strenuous exercise resulted in a flow of 9.9 L/minute (or 26 32

L/hour/kg 0.74 ) ( Brown, et al., 1997 ) . Brown et al. ( 1997 ) also ci te the ICRP ( 1975 ) as having a 33B

- 11

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE mean respiratory minute volum e of 7.5 L/minute, which results in an alveolar ventilation rate of 1

5 L/minute (assuming 33% lung dead space), or 13 L/minute/kg 0.74 . Again, this is roughly half 2

the value of 30 L/hour/kg 0.74 employed for this parameter by Reitz et al. ( 1990 ) . Young et al. 3

( 1977 ) reported that the human subjects exposed to 50 ppm for 6 hour s were resting inside a 4

walk

- in exposure chamber. Thus, use of cardiac output and alveolar ventilation rates of 30 5

L/hour/kg 0.74 is not consistent with the experimental conditions being simulated. 6

Table B

- 1. Human PBPK model parameter values for 1,4

- dioxane

Parameter Reitz et al. ( 1990 ) Leung and

Paustenbach ( 1990 ) Sweeney et al.

( 2008 ) EPA c

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 ± 739 b 1,557

Rapidly perfused tissue:air (PRA) 1,557

-- -- 1,557

Slowly perfused tissue:air (PSA) 1,557 997 ± 254 1,348 ± 290 b 166

Metabolic Constants

Maximum rate for 1,4

- dioxane

metabolism (V maxC ) d 6.35

-- -- 5.49

Metabolic affinity constant (K

m ) e 3.00

-- -- 9.8

HEAA urinary elimination rate

constant (k

me ) f 0.56

-- -- 0.44

a L/hour/kg BW 0.74

b Measurement for rat tissue

c Biologically plausible values utilized by EPA in this assessment

d mg/hour/kg BW 0.75

e mg/L

f hour

- 1

Examination of the experimental data of Young et al. ( 1977 ) yields an estimated alveolar 7

ventilation to be 7 L/minute (or 16 L/hour/kg 0.74 ) for volunteers having a mean BW of 84 kg

. 8

This rate is based on the Young et al. ( 1977 ) estimate of 76.1 mg /hour for 1,4

- dioxane uptake. 9

Based on these findings, the cardiac output and alveolar ventilation rates of 17.0 and 17.7 10

L/hour/kg 0.74 were b iologically plausible for the experimental subjects. These rate estimates are 11

based on calculations made using empirical data and are consistent with standard human values 12

and the experimental conditions (i.e., subject exertion level) reported by Young et al. ( 1977 )

. 13

Therefore, these flow values were chosen for the model re

- calibration. 14B

- 12

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE B.4.2. Sources of Values for Partition Coefficients

T wo data sources are available for the tissue:air equilibrium partition coefficients for 1

1,4

- dioxane: Leung and Paustenbach ( 1990 ) and Sweeney et al. ( 2008 ) . Both investigators 2

report mean values and standard deviations for human blood:air, rat liver:air, and rat muscle:air 3

(e.g., slowly p erfused tissue:air), while Leung and Paustenbach et al. ( 1990 ) also reported values 4

for rat fat:air ( Table B

- 1). 5

B.4.3. Calibration Method

The PBPK model was twice re

- calibrated using the physiological flow valu es suggested 6

values (current EPA assessment, see Table B

- 1) and the partition coefficients of Leung and 7

Paustenbach ( 1990 ) and Sweeney et al. ( 2008 ) separately. For each calibration, the metabolic 8

parameters V

max C and K

m , were simultaneously fit (using the parameter estimation tool provide d 9

in the acslXtreme software) to the output of 1,4

- dioxane blood concentrations generated by the 10

acslXtreme implementation of the Young et al. ( 1977 ) empirical human model for a 6 hour

, 11

50 ppm inhalation exposure. Subsequently, the HEAA urinary elimination rate constant, k

me , 12

was fitted to the urine HEAA predictions from the empirical model. The empirical model 13

predictions, rather th an experimental observations, were used to provide a more robust data set 14

for model fitting, as the empirical model simulation provided 240 data points (one prediction 15

every 0.1 hour ) compared with hour ly experimental observations, and to avoid introducing error 16

by calibrating the model to data digitally captured from Young et al. ( 1977 )

. 17

B.4.4. Results

Results of the model re

- calibration are provided in Table B

- 2. The re

- calibrated values 18

for V

max C and k

me associated with the Leung and Paustenbach ( 1990 ) or Sweeney et al. ( 2008 ) 19

tissue:air partition coefficients are very similar. However, the fitted value for K

m using the 20

Sweeney et al. ( 2008 ) partition coefficients is far lower (0.0001 mg /L) than that resulting from 21

use of the Leung and Paustenbach ( 1990 ) partition coefficients (2.5 mg /L). This appears to be 22

due to the higher slowly perfused tissue:air partition coefficient determined by Sweeney et al. 23

( 2008 ) (1,348 vs. 997), resulting in a higher apparent V d than if the Leung and Paustenbach 24

( 1990 ) value is used. Thus, the optimization algorithm selects a low K

m , artificially saturating 25

metabolism in an effort to drive predicted blood 1,4

- dioxane levels closer to the empirical model 26

output. Saturation of metabolism during a 50 ppm inhalation exposure is inconsistent with the 27

observed kinetics. 28B

- 13

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table B

- 2. PBPK metabolic and elimination parameter values resulting

from re

- calibration of the human model using alternative values for

physiological flow rates a and tissue:air partition co efficients

Source of Partition Coefficients Leung and Paustenbach ( 1990 ) Sweeney et al. ( 2008 )

Maximum rate for 1,4

- dioxane metabolism (V maxC ) b 16.9 20.36

Metabolic affinity constant (K

m ) c 2.5 0.0001

HEAA urinary elimination rate constant (k

me ) d 0.18 0.17

a Cardiac output = 17.0 L/hour/kg BW 0.74 , alveolar ventilation = 17.7 L/hour/kg BW 0.74

b mg/hour/kg BW 0.75

c mg/L

d hour

- 1

Plots of predicted and experimentally observed blood 1,4

- dioxane and urinary HEAA 1

levels are shown in Figure B

- 9 . Neither re

- calibration resulted in an adequate fit to the blood 2

1,4

- dioxane data from the empirical model output or the experimental observations. Re

3

calibration using either the Leung and Paustenbach ( 1 990 ) or Sweeney et al. ( 2008 ) partition 4

coefficients resulted in blood 1,4

- dioxane p redictions that were at least 10

- fold lower than 5

empirical model predictions or observations. 6

Source: Used with permission from Elsevier, Ltd., Leung and Paustenbach ( 1990 )

.

Figure B

- 9 . P redicted an d 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 k

me resulted in HEAA levels in urine that were very similar to the 7

empirical model output (compare Figures B

- 7, B

- 9 , and B

- 10 ), which was not surprising, given 8

the fitting of a single parameter to the data. 9B

- 14

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission of Oxford Journals, Sweeney et al. ( 2008 )

.

Figure B

- 10 . P redicted and observed blood 1,4

- dioxane concentra tions (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 B

1

1) parameters are shown in F igure B

- 11 . These outputs rely on a very low value for the slowly 2

perfused tissue:air partition coefficient (166) that is six

- to eightfold lower than the measured 3

values reported in Leung and Paustenbach ( 1990 ) and Sweeney et al. ( 2008 ) , and 10

- fold lower 4

than the value used by Reitz et al. ( 1990 ) . While the predicted maximum blood 1,4

- di oxane 5

levels are much closer to the observations, the elimination kinetics are markedly different, 6

producing higher predicted elimination rates compared to observations during the post

- exposure 7

phase of the experiment. 8B

- 15

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure B

- 11 . P redicted and observe d 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 1

values for cardiac output and alveolar ventilation ( Young, et al., 1977 ) and measured mean 2

tissue:air 1,4

- dioxane partition coefficients reported by Leung and Paustenbach ( 1990 ) or 3

Sweeney et al. ( 2008 ) . T he resulting predictions of 1,4

- dioxane in blood following a 6

- hour, 50

- 4

ppm inhalation exposure were 10

- fold (or more) lower than either the observations or the 5

empirical model predictions, while the predictions of urinary HEAA by the PBPK and empirical 6

models were similar to each other, but lower than observed values (Figures B

- 9 and B

- 10 ). 7

Output from the model using bi ologically plausible parameter values ( Table B

- 1), Figure B

- 11 8

shows that application of a value for the slowly perfused tissue:air partition coefficient, which is 9

10

- fold lower than the measured value reported by Leung and Paustenbach ( 1990 ) , results in 10

closer agreement of the predictions to observations during the exposure phase, but not during the 11

elimination phase. Thus, model re

- calibration using experiment

- specific flow rates and mean 12

measured parti tion coefficients does not result in an adequate fit of the PBPK model to the 13

available data. 14

The Sweeney et al. ( 2008 ) PBPK model consisted of compartments for fat, liver, slowly 15

perfused, and other well perfused tissues. Lung and stomach compartments were used to 16

describe the route of exposure, and an overall volume of distribution compa rtment was used for 17

calculation of urinary excretion levels of 1,4

- dioxane and its metabolite, HEAA. Metabolic 18

constants (VmaxC and Km) for the rat PBPK model were derived by optimization data from an 19

i.v. exposure of 1,000 mg/kg data ( Young, et al., 1978a ; Young, et al., 1978b ) for induced 20

metabolism. For uninduced metabolism data generated by i.v. exposures to 3, 10, 30, and 100 21B

- 16

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE mg/kg were used ( Young, et al., 1978a ; Young, et al., 1978b ) . Da ta generated from the 300 1

mg/kg i.v. exposure was not used to estimate VmaxC and Km. The best fitting values for VmaxC 2

to estimate the blood data from the Young et al. ( 1978a ; 1978b ) study using the Sweeney et al. 3

( 2008 ) model resulted in VmaxC values of 12.7, 10.8, 7.4 mg/kg

- hr; suggesting a gradual dose 4

dependent increase in metabolic rate with dose. These estimates were for a range of doses 5

between 3 and 1,000 mg/kg i.v. dose. Although the Sweeney et al. ( 2008 ) model utilized two 6

values for VmaxC (induced and uninduced) , the PBPK model does not inclu de dose

- dependent 7

function description of the change of Vmax for i.v. doses between 100 and 1,000 mg/kg. PBPK 8

model outputs were compared with other data not used in fitting model parameters by visual 9

inspection. The model predictions gave adequate match to the 1,4

- dioxane exhalation data after a 10

1,000 mg/kg i.v. dose. 1,4

- Dioxane exhalation was overpredicted by a factor of about 3 for the 11

10 mg/kg i.v. dose. Similarly, the simulations of exhaled 1,4

- dioxane after oral dosing were 12

adequate at 1,000 mg/kg, and 100 mg/kg (within 50%), but poor at 10 mg/kg (model 13

overpredicted by a factor of five). The fit of the model to the human data ( Young, et al., 1977 ) 14

was also problematic ( Sweeney, et al., 2008 ) . Using physiological parameters of Brown et al. 15

( 1997 ) and measured partitioning parameters ( L eung & Paustenbach, 1990 ; Sweeney, et al., 16

2008 ) with no metabolism, measured blood 1,4

- dioxane concentrations reported by Young et al. 17

( 1977 ) could not be achieved unless the estimated exposure concentration was increased from 53 18

to 100 ppm. Inclusion of any metabolism necessarily decreased predicted blood concentrations. 19

If estimated metabolism rates were used with the reported exposure concentration, urinary 20

metabolite excretion was underpredicted ( Sweeney, et al., 2008 ) . Thus, the models were 21

inadequate to use for rat to human extrapolation. 22

B.4.6. SENSITIVITY ANALYSIS

A sensitivity analysis of the Reitz et al. ( 1990 ) model was performed to determine which 23

PBPK model parameters exert the greatest influence on the outcome of dosimeters of interest

— 24

in this case, the concentration of 1,4

- dioxane in blood. Knowledge of model sensitivity is useful 25

for guiding the choice of parameter values to minimize model uncertainty. 26

B.4.7. Method

A univariate sensitivity analysis was performed on all of the model parameter s for two 27

endpoints: blood 1,4

- dioxane concentrations after 1 and 4 hour s of exposure. These time points 28

were chosen to assess sensitivity during periods of rapid uptake (1 hour ) and as the model 29

approached steady state (4 hour s) for blood 1,4

- dioxane. Model parameters were perturbated 1% 30

above and below no minal values and sensitivity coefficients were calculated as follows: 31B

- 17

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE where x is the model parameter, f(x) is the output variable, Δx is the perturbation of the 1

parameter from the nominal value, and f‘(x) is the sensitivity coefficie nt. The sensitivity 2

coefficients were scaled to the nominal value of x and f(x) to eliminate the potential effect of 3

units of expression. As a result, the sensitivity coefficient is a measure of the propo rtional 4

change in the blood 1,4

- dioxane concentrat ion produced by a proportional change in the 5

parameter value, with a maximum value of 1. 6

B.4.8. Results

The sensitivity coefficients for the seven most influential model parameters at 1 and 7

4 hour s of exposure are shown in Figure B

- 1 2 . The three parameters wit h the highest sensitivity 8

coefficients in descending order are alveolar ventilation (QPC) (1.0), the blood:air partition 9

coefficient (PB) (0.65), and the slowly perfused tissue:air partition coefficient (PSA) (0.51). Not 10

surprisingly, these were the param eters that were doubled or given surrogate values in the Reitz 11

et al. ( 1990 ) model in order to achieve an adequate fit to the data. Because of the large influence 12

of these parameters on the model, it is important to assign values to these parameters in which 13

high confidence is placed, in order to reduce model uncertainty. 14

Figure B

- 1 2 . The highest seven se nsitivity coefficients (and assoc iated

parameters) for blood 1,4

- dioxane concentrations (CV) at 1 (left) and 4

(right) hour s of a 50

- ppm inhalation exposure.

B.5. PBPK MODEL EXERCISES USING BIOLOGICALLY P LAUSIBLE PARAMETER

BOUNDARIES

The PBPK model includes num erous physiological parameters whose values are typically 15

taken from experimental observations. In particular, values for the flow rates (cardiac output and 16

alveolar ventilation) and tissue:air partition coefficients (i.e., mean and standard deviations) a re 17

available from multiple sources as means and variances. The PBPK model was exercised by 18B

- 18

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE varying the partition coefficients over the range of biological plausibility (parameter mean ± 1

2 standard deviations), re

- calibrating the metabolism and elimination parameters, and exploring 2

t he resulting range of blood 1,4

- dioxane concentration time course predictions. Cardiac output 3

and alveolar ventilation were not varied because the experiment

- specific values used did not 4

include any measure of inter

- individual variation. 5

B.5.1. Observations Regarding the Volume of Distribution

Young et al. ( 1978a ; 1978b ) used experimental observations to estimate a V d for 6

1,4

- dioxane in rats of 301 mL, or 1,204 mL/kg BW. For humans, the V d was estimated to be 7

104 m

L/kg BW ( Young, et al., 1977 ) . It is possible that a very large volume of the slowly 8

perfused tissues in the body of rats and humans may be a significant contributor to the estimated 9

10

- fold difference in distribution volumes for the two species. This raises doubt regarding the 10

appropriateness of using the measured rat slowly perfused tissue:air partition coefficient as a 11

surrogate values for humans in the PBPK model. 12

B.5.2. Defining Boundaries for Parameter Values

Given the possible 10

- fold species differences in the apparent V d for 1,4

- dioxane in rats 13

and humans, boundary values for the partition coefficients were chosen to exercise the PBPK 14

model across its performance range to either minimize or maximize the simulated V d . This was 15

accomplished by defining biologically plausible values for the partition coefficients as the 16

mean ± 2 standard deviations of the measured va lues. Thus, to minimize the simulated V d for 17

1,4

- dioxane, the selected blood:air partition coefficient was chosen to be the mean + 2 standard 18

deviations, while all of the other tissue:air partition coefficients were chosen to be the mean

– 2 19

standard devi ations. This created cond itions that would sequester 1,4

- dioxane in the blood, away 20

from other tissues. To maximize the simulated 1,4

- dioxane V d , the opposite selections were 21

made: blood and other tissue:air partition coefficients were chosen as the mea n

– 2 standard 22

deviations and mean + 2 standard deviations, respectively. Subsequently, V

max C , K

m , and k

me 23

were optimized to the empirical model output data as described in Section B.4.3. This procedure 24

was performed for both the Leung and Paustenbach ( 1990 ) and Sweeney et al. ( 2008 ) partition 25

coefficients ( Table B

- 1). The two predicted time courses resulting from the re

- calibrated model 26

with partition coefficients chosen to minimize or maximize the 1,4

- dioxane V d represent the 27

range of model performance as bounded by biologically pla usible parameter values. 28

B.5.3. Results

The predicted time courses for a 6

- hour, 50

- ppm inhalation exposure for the re

- calibrated 29

human PBPK model with mean (central tendency) and ± 2 standard deviations from the mean 30

values for partition coefficients are shown i n Figure B

- 1 3 for the Leung and Paustenbach ( 1990 ) 31

values and Figure B

- 1 4 for the Sweeney et al. ( 2008 ) values. The resulting fitted values for 32B

- 19

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE V

max C , K

m , and k

me , are given in Table B

- 3. By bounding the tissue:air partition coefficients with 1

upper and lower limits on biologically plausib le values from Leung and Paustenbach ( 1990 ) or 2

Sweeney et al. ( 2008 ) , the model predictions are still at least six

- to sevenfold lower than either 3

the empirical model output or the experimental observations. The range of possible urinary 4

HEAA predictions brackets the prediction of the empirical model, but this agreement i s not 5

surprising, as the cumulative rate of excretion depends only on the rate of metabolism of 6

1,4

- dioxane, and not on the apparent V d for 1,4

- dioxane. These data show that the PBPK model 7

cannot adequately reproduce the predictions of blood 1,4

- dioxane c oncentrations of the Young 8

et al. ( 1977 ) human empirical model or the experimental observations when constrained by 9

biologically pla usible values for physiological flow rates and tissue:air partition coefficients. 10

Source: Used with permission of Elsevier, Ltd., Leung and Paustenbach ( 1990 )

Figure B

- 1 3 . Comparisons of the range o f 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 e xposure.B

- 20

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission of Oxford Journals, Sweeney et al. ( 2008 ) ; Used with

permission of Taylor & Francis, Young et al. ( 1977 )

.

Figure B

- 1 4 . 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.

Table B

- 3. PBPK metabolic and elimination parameter values resulting

from recalibration of the human model using biologically plausible values for

physiological flow rates a and selected upper and lower boundary values for

tissue:air partition coefficients

Source of partition coefficients Leung and Paus t enbach ( 1990 ) Sweeney et al. ( 2008 )

For maximal V d For minimal V d For maximal V d For minimal V d

Maximum rate for 1,4

- dioxane

metabolism ( V

max C ) b 14.95 18.24 17.37 21.75

Metabolic dissociation constant

( K

m ) c 5.97 0.0001 4.88 0.0001

HEAA urinary elimination rate

constant ( k

me ) d 0.18 0.17 0.26 0.19

a Cardiac output = 17.0 L/hour/kg BW 0.74, alveolar ventilation = 17.7 L/hour/kg BW 0.74

b mg/hour/kg BW 0.75

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. 1

( 1977 ) when parameterized by biologically plausi ble values, an exercise was performed to 2

explore alternative parameters and values capable of producing an adequate fit of the data. Since 3B

- 21

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE the metabolism of 1,4

- dioxane appears to be linear in humans for a 50

- ppm exposure ( Young, et 1

al., 1977 ) , the parameters V

max C and K

m were replaced by a zero

- order, non

- saturable metabolism 2

rate constant, k LC . This rate constant w as fitted to the experimental blood 1,4

- dioxane data using 3

partition coefficient values of Sweeney et al. ( 2008 ) to minimize the V d (i.e., maximize the blood 4

1,4

- dioxane levels). The resulting model predictions are shown in Figure B

- 1 5 . As before, the 5

maximum blood 1,4

- dioxane levels were approximately sevenfold lower than the observed 6

values. 7

Figure B

- 1 5 . Predictions of blood 1,4

- dioxane concentration following

calibration of a zero

- order metabolism rate constant, k LC , to the

experimental data.

A re

- calibration was performed using only the data from the exposure phase of the 8

experime nt, such that the elimination data did not influence the initial metabolism and tissue 9

distribution. The model predictions from this exercise are shown in Figure B

- 1 6 . These 10

predictions are more similar to the observations made during the exposure phase of the 11

experiment; however, this is achieved at greatly reduced elimination rate (compare Figures B

- 1 1 12

and B

- 1 6 ). 13B

- 22

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure B

- 1 6 . Predictions of blood 1,4

- dioxane concentration following

calibration of a zero

- order metabolism rate constant, k LC , to only the

exposure phase of the experimental data.

Finally, the model was re

- calibrated by simultaneously fitting k LC and the slowly 1

perfused tissue:air partition coefficient to the experimental data with no bounds on possible 2

values (except that they be non

- zer o). The fitted slowly perfused tissue:air partition coefficient 3

was an extremely low (and biologically unlikely) value of 0.0001. The resulting model 4

predictions, however, were closer to the observations than even the empirical model predictions 5

( Figure B

- 1 7 ). These exercises show that better fits to the observed blood 1,4

- dioxane kinetics 6

are achieved only when parameter values are adjusted in a way that corresponds to a substantial 7

decrease in apparent V d of 1,4

- dioxane in the human, relative to the ra t (e.g., decreasing the 8

slowly perfused tissue:air partition coefficient to extremely low values, relative to observations). 9

Downward adjustment of the elimination parameters (e.g., decreasing k LC ) increases the 10

predicted blood concentrations of 1,4

- dioxa ne, achieving better agreement with observations 11

during the exposure phase of the experiment; however, it results in unacceptably slow 12

elimination kinetics, relative to observations following cessation of exposure. These 13

observations suggest that some oth er process not captured in the present PBPK model structure is 14

responsible for the species differences in 1,4

- dioxane V d and the inability to reproduce the 15

human experimental inhalation data with biologically plausible parameter values. 16B

- 23

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure B

- 1 7 . Pre dictions of blood 1,4

- dioxane concentration following

simultaneous calibration of a zero

- order metabolism rate constant, k LC , and

slowly perfused tissue:air partition coefficient to the experimental data.

B.6. CONCLUSIONS

The rat and human empirical models of Y oung et al. ( 1978a ; 1978b ; 1977 ) were 1

successfully implemented in acslXtreme and perform identically to the models reported in the 2

published papers (Figures 3

- 3 through 3

- 6), with the excepti on of the lower predicted HEAA 3

concentrations and early appearance of the peak HEAA levels in rat urine. The early appearance 4

of peak HEAA levels cannot presently be explained, but may result from manipulations of k

me or 5

other parameters by Young et al. ( 1978a ; 1978b ) t hat were not reported. The lower predictions 6

of HEAA levels are likely due to reliance on a standard urine volume production rate in the 7

absence of measured (but unreported) urine volumes. While the human urinary HEAA 8

predictions were lower than observat ions, this is due to parameter fitting of Young et al. ( 1977 )

. 9

No model output was published in Young et al. ( 1977 ) for comparison. The empirical models 10

were modified to allow for user

- defined inhalation exposure levels. However, no modifications 11

were made to m odel oral exposures because adequate data to parameterize such modifications do 12

not exist for rats or humans. The inhalation Young et al. ( 1977 ) model failed to provide adequate 13

fits to the subchronic exposure plasma levels of 1,4

- dioxane in rats using the data from the Kasai 14

et al. ( 2008 ) study. 15

Several procedures were applied to the human PBPK model to determine if an adequate 16

fit of the model to the empirical model output or experimental observations could be attained 17

using biologically plausible values for the model parameters. The re

- calibrated model 18

predictions for blood 1,4

- dioxane levels do not come within 10

- fold of the experimental values 19B

- 24

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE using measured tissue:air partition coefficients from Leung and Paustenbach ( 1990 ) or Sweeney 1

et al. ( 2008 ) (Figures B

- 9 and B

- 10 ). Use of a slo wly perfused tissue:air partition coefficient 10

- 2

fold lower than measured values produces exposure

- phase predictions that are much closer to 3

observations, but does not replicate the elimination kinetics ( Figure B

- 11 ). Re

- calibration of the 4

model with uppe r bounds on the tissue:air partition coefficients results in predictions that are still 5

six

- to sevenfold lower than empirical model prediction or observations (Figures B

- 13 and B

- 14 ). 6

Exploration of the model space using an assumption of first

- order metabolism (valid for the 50

- 7

ppm inhalation exposure) showed that an adequate fit to the exposure and elimination data can 8

be achieved only when unrealistically low values are assumed for the slowly perfused tissue:air 9

partition coefficient ( Figure B

- 17 ). Artificially low values for the other tissue:air partition 10

coefficients are not expected to improve the model fit, because the sensitivity analysis to exert 11

less influence on blood 1,4

- dioxane than V

max C and K

m . This suggests that the model structure is 12

insufficient to capture the apparent 10

- fold species difference in the blood 1,4

- dioxane V d 13

between rats and humans. In the absence of actual measurements for the human slowly perfused 14

tissue:air partition coefficient, high uncertainty exists for this mod el parameter value. 15

Differences in the ability of rat and human blood to bind 1,4

- dioxane may contribute to the 16

difference in V d . However, this is expected to be evident in very different values for rat and 17

human blood:air partition coefficients, which i s not the case ( Table B

- 1). Therefore, some other, 18

as yet unknown, modification to model structure may be necessary. Sweeney et al. ( 2008 ) PBPK 19

model provided an overall improvement on previous models; however, the Sweeney et al. ( 2008 ) 20

inhalation model predictions of animal and human data were problematic. 21B

- 25

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE B.7. acsl X treme CODE FOR THE YOUNG E T AL. EMPIRCAL MODEL F OR

1,4

- DIOXANE IN RATS

PROGRAM: Young ( 1978a ) rat.csl 1

!

----------------------------------------------------------------- 2

! Created by Michael Lumpkin, Syracuse Research Corporation, 08/06 3

! This program implements the 1

- compartment empirical model for 1,4

- d ioxane 4

! in rats, developed by Young et al. 1978a, b. Program was modified to run 5

! in ACSL Xtreme and to include user

- defined i.v. and inhalation concentrations 6

!(MLumpkin, 08/06) 7

!

----------------------------------------------------------------- 8

9

INITIA L 10

11

!*****Timing and Integration Commands***** 12

ALGORITHM IALG=2 !Gear integration algorithm for stiff systems 13

!MERROR %%%%=0.01 !Relative error for lead in plasma 14

NSTEPS NSTP=1000 !Number of integration steps per communication interval 15

CINTERVAL CINT=0.1 ! Communication interval 16

CONSTANT TSTART=0. ! Start of simulation (hr) 17

CONSTANT TSTOP=70. !End of simulation (hr) 18

19

!*****MODEL PARAMETERS***** 20

CONSTANT BW=0.215 !Body weight (kg) 21

CONSTANT MINVOL=0.238 !respiratory minute volume (L/min) estimated from Young e t al. 22

(1978) 23

CONSTANT IVDOSE = 0. !IV dose (mg/kg)! 24

CONSTANT CONC = 0. !inhalation concentration (ppm) 25

26

CONSTANT MOLWT=88.105 !mol weight of 1,4

- dioxane 27

CONSTANT TCHNG=6.0 !Exposure pulse 1 width (hr) 28

CONSTANT TDUR=24.0 !Exposure duration (hr) 29

CONSTANT TCHNG2=120.0 !Exposure pulse 2 width (hr) 30

CONSTANT TDUR2=168.0 !Exposure duration 2 (hr) 31

32

CONSTANT Vmax=4.008 !(mcg/mL/hr) 33

CONSTANT Km=6.308 !(mcg/mL) 34

CONSTANT Kinh=0.43 !pulmonary absorption constant (/hr) 35

CONSTANT Ke=0.0149 !(/hr) 36

CONSTANT Kme=0.2593 !(/hr) 37

CONSTANT Vd=0.3014 !(L) 38

39

IV = IVDOSE*BW 40

AmDIOXi=IV 41

42

END !Of Initial Section 43

44

DYNAMIC 45B

- 26

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE DERIVATIVE 1

2

!*** Dioxane inhalation concentration *** 3

CIZONE=PULSE(0.0, TDUR, TCHNG) * PULSE(0.0, TDUR2, TCHNG2) 4

!First pulse is hour s /day, second pulse is hour s/week 5

CI=CONC*CIZONE*MOLWT/24450. !Convert to mg /L 6

7

!*** Dioxane metabolism/1st order elimination *** 8

dAmDIOX=(Kinh*CI*(MINVOL*60))

- ((Vmax*(AmDIOX))/(Km+(AmDIOX)))

- 9

(Ke*(AmDIOX)) 10

AmDIOX=INTEG(dAmDIOX,AmDIOXi) 11

ConcDIOX=AmDIOX/Vd !plasma dioxane concentration (mcg/mL) 12

AUCDIOX=INTEG(ConcDIOX,0) !plasma dioxane AUC 13

14

!*** HEAA production and 1st order metabolism *** 15

dAmHEAA=((Vmax*(AmDIOX))/(Km+(AmDIOX)))

- (Kme*(AmHEAA)) 16

AmHEAA=INTEG(dAmHEAA,0.) 17

ConcHEAA=AmHEAA/Vd !plasma HEAA concentration 18

19

!*** 1st order dioxane elimination to urine *** 20

dAmDIOXu=(Ke*(AmDIOX))*0.35 21

AmDIOXu=INTEG(dAmDIOXu,0.) 22

ConcDIOXu=Ke*AmDIOX*0.35/1.45e

- 3 !urine production approx 1.45e

- 3 L/hr in SD rats 23

24

!*** 1st order dioxane exhaled *** 25

dAmDIOXex=(Ke*(AmDI OX))*0.65 26

AmDIOXex=INTEG(dAmDIOXex,0.) 27

28

!*** 1st order HEAA elimination to urine *** 29

dAmHEAAu=(Kme*(AmHEAA)) 30

AmHEAAu=INTEG(dAmHEAAu,0.) 31

ConcHEAAu=Kme*AmHEAA/1.45e

- 3 !urine production approx 1.45e

- 3 L/hr in SD rats 32

33

END !of Derivative Section 34

35

DISCRETE 36

37

END !of Discrete Section 38

39

TERMT (T .GT. TSTOP) 40

41

END !of Dynamic Section 42

43

TERMINAL 44

45

END !of Terminal Section 46

47

END !of Program 48B

- 27

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE B.8. acsl X treme CODE FOR THE YOUNG E T AL. EMPIRICAL MODEL FOR

1,4

- DIOXANE IN HUMANS

PROGRAM: Young ( 1977 ) human.csl 1

!

----------------------------------------------------------------- 2

! Created by Michael Lumpkin, Syracuse Research Corporation, 01/06 3

! This program implements the 1

- compartment model for 1,4

- dioxane in humans, 4

! developed by Young et al., 1977. Program was modified to run 5

! in acslXtreme (MLumpkin, 08/06) 6

!

----------------------------------------------------------------- 7

8

INITIAL 9

10

!*****Timin g and Integration Commands***** 11

ALGORITHM IALG=2 !Gear integration algorithm for stiff systems 12

!MERROR %%%%=0.01 !Relative error for lead in plasma 13

NSTEPS NSTP=1000 !Number of integration steps per communication interval 14

CINTERVAL CINT=0.1 !Communication interval 15

CONSTANT TSTART=0. ! Start of simulation (hr) 16

CONSTANT TSTOP=120. !End of simulation (hr) 17

18

!*****MODEL PARAMETERS***** 19

!CONSTANT DATA=1 !Optimization dataset 20

CONSTANT MOLWT=88.105 !mol weight for 1,4

- dioxane 21

CONSTANT DOSE=0. !Dose (mg/kg 22

CONSTANT CONC=0. ! Inhalation concentration (ppm) 23

CONSTANT BW=84.1 !Body weight (kg) 24

CONSTANT MINVOL=7.0 !pulmonary minute volume (L/min) 25

CONSTANT F=1.0 !Fraction of dose absorbed 26

CONSTANT kinh=1.06 !Rate constant for inhalation (mg/hr); optimized by MH L 27

CONSTANT ke=0.0033 !Rate constant for dioxane elim to urine (hr

- 1) 28

CONSTANT km=0.7096 !Rate constant for metab of dioxane to HEAA (hr

- 1) 29

CONSTANT kme=0.2593 !Rate constant for transfer from rapid to blood (hr

- 1) 30

CONSTANT VdDkg=0.104 !Volume of distributi on for dioxane (L/kg BW) 31

32

CONSTANT VdMkg=0.480 !Volume of distribution for HEAA (L/kg BW) 33

CONSTANT OStart=0. !Time of first oral dose (hr) 34

CONSTANT OPeriod=120. !Oral Dose pulse period (hr) 35

CONSTANT OWidth=1. !Width (gavage/drink time) of oral dose (hr) 36

37

C ONSTANT IStart=0. !Time of inhalation onset (hr) 38

CONSTANT IPeriod=120. !Inhalation pulse period (hr) 39

CONSTANT IWidth=6. !Width (duration) of inhalation exposure (hr) 40

41

END !Of Initial Section 42

43

DYNAMIC 44

45

DERIVATIVE 46B

- 2 8

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ! VARIABLES and DEFINED VALUES** *** 1

VdD =BW*VdDkg !Volume of distribution for dioxane 2

VdM=BW*VdMkg !Volume of distribution for HEAA 3

4

InhalePulse=PULSE(IStart,IPeriod,IWidth) 5

Inhale=CONC*InhalePulse*MOLWT/24450. ! Convert to mg /L 6

7

!*****DIFFERENTIAL EQUATIONS FOR COMPARTMENTS  8

9

!** * Dioxane in the body (plasma) *** 10

dAMTbD=(Kinh*Inhale*(MINVOL*60))

- (AMTbD*km)

- (AMTbD*ke) 11

AMTbD=INTEG(dAMTbD,0.) 12

CbD=AMTbD/VdD 13

AUCbD=INTEG(CbD,0) 14

15

!*** HEAA in the body (plasma)*** 16

dAMTbM=AMTbD*km

- AMTbM*kme 17

AMTbM=INTEG(dAMTbM,0.) 18

CbM=AMTbM/VdM 19

20

!*** Cumulative Diox ane in the urine *** 21

dAMTuD=(AMTbD*ke) 22

AMTuD=INTEG(dAMTuD,0.) 23

24

!*** Cumulative HEAA in the urine *** 25

dAMTuM=(AMTbM*kme) 26

AMTuM=INTEG(dAMTuM,0.) 27

28

END !Of Derivative Section 29

30

DISCRETE 31

32

END !of Discrete Section 33

34

TERMT (T .GT. TSTOP) 35

36

END !Of Dynamic Section 37

38

TERMINAL 39

40

END !of Terminal Section 41

42

END !of Program 43B

- 29

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE B.9. acsl X treme CODE FOR THE REITZ E T AL. PBPK MODEL FOR 1,4

- DIOXANE

( Reitz, et al., 1990 ) 1

PROGRAM: DIOXANE.CSL (Used in Risk Estimation Procedures) 2

!Added a venous blood compartment and 1st order elim of metab.' 3

!Mass Balance Checked OK for Inhal, IV, Oral, and Water RHR' 4

!Defined Dose Surrogates for Risk Assessment 01/04/89' 5

!Modified the Inhal Route to use PULSE for exposure conditions' 6

!Modifications by GLDiamond, Aug2004, marked as !** 7

! 8

!Metabolism of dioxane modified by MLumpkin, Oct2006, to include 1st order 9

!or saturable kinetics. For 1st order, set VmaxC=0; for M

- Menten, set KlC=0. 10

! 11

INITIAL 12

13

INTEGER I 14

I=1 15

! ARRAY TDATA(20) ! CONSTANT TDATA=999, 19*1.0E

- 6 !** 16

CONSTANT BW = 0.40 !'Body weight (kg)' 17

CONSTANT QPC = 15. !'Alveolar ventilation rate (l/hr)' 18

CONSTANT QCC = 15. !'Cardiac output (l/hr)' 19

20

!Flows to Tissue Compartments' 21

CONSTANT QLC = 0.25 !'Fractional blood flow to liver' 22

CONSTANT QFC = 0.05 !'Fracti onal blood flow to fat' 23

CONSTANT QSC = 0.18 !'Fractional blood flow to slow' 24

QRC = 1.0

- (QFC + QSC + QLC) 25

CONSTANT SPDC = 1.0 ! diffusion constant for slowly perfused tissues 26

27

!Volumes of Tissue/Blood Compartments' 28

CONSTANT VLC = 0.04 !'Fraction liver tissue' 29

CONSTANT VFC = 0.07 !'Fraction fat tissue' 30

CONSTANT VRC = 0.05 !'Fraction Rapidly Perf tissue' 31

CONSTANT VBC = 0.05 !'Fraction as Blood' 32

VSC = 0.91

- (VLC + VFC + VRC + VBC) 33

34

!Partiti on Coefficients' 35

CONSTANT PLA = 1557. !'Liver/air partition coefficient' 36

CONSTANT PFA = 851. !'Fat/air partition coefficient' 37

CONSTANT PSA = 2065. !'Muscle/air (Slow Perf) partition' 38

CONSTANT PRA = 1557. !'Richly perfused tissue/ai r partition' 39

CONSTANT PB = 1850. !'Blood/air partition coefficient' 40

41

!Other Compound Specific Parameters' 42

CONSTANT MW = 88.1 !'Molecular weight (g/mol)' 43

CONSTANT KLC = 12.0 ! temp zero

- order metab constant 44

CONSTANT VMAXC = 13.8 !'Maximum Velocity of Metabol.' 45

CONSTANT KM = 29.4 !'Michaelis Menten Constant' 46

CONSTANT ORAL = 0.0 !'Oral Bolus Dose (mg/kg)' 47B

- 30

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE CONSTANT KA = 5.0 !'Oral uptake rate (/hr)' 1

CONSTANT WATER = 0.0 !'Conc in Water (mg/liter, ppm)' 2

CONSTANT WDOSE=0.0 !Water dose (mg/kg/day) ** 3

CONSTANT IV = 0.0 !'IV dose (mg/kg)' 4

CONSTANT CONC = 0.0 !'Inhaled concentration (ppm)' 5

CONSTANT KME = 0.276 !'Urinary Elim constant for met (hr

- 1)' 6

7

!Timing commands' 8

CONSTANT T STOP = 50 !'Length of experiment (hrs)' 9

CONSTANT TCHNG = 6 !'Length of inhalation exposure (hrs)' 10

CINTERVAL CINT=0.1 11

CONSTANT WIDD=24. !** 12

CONSTANT PERD=24. !** 13

CONSTANT PERW=168. !** 14

CONSTANT WIDW=168. !** 15

CONSTANT DAT=0.017 !* * 16

17

!Scaled parameters calculated in this section of Program' 18

QC=QCC*BW**0.74 19

QP=QPC*BW**0.74 20

QL=QLC*QC 21

QF=QFC*QC 22

QS=QSC*QC 23

QR=QRC*QC 24

VL=VLC*BW 25

VF=VFC*BW 26

VS=VSC*BW 27

VR=VRC*BW 28

VB=VBC*BW 29

PL=PLA/PB 30

PR=PRA/PB 31

PS=PSA/PB 32

PF=PFA/PB 33

KL = KLC*bw**0.7 ! Zero

- order metab constant 34

VMAX = VMAXC*BW**0.7 35

DOSE = ORAL*BW !'Initial Amount in Stomach' 36

AB0 = IV*BW !'Initial Amount in Blood' 37

!DRINK = 0.102*BW**0.7*WATER/24 !'Input from water (mg/hr)' !** 38

!DRINKA = 0.102*BW**0.7*WATER/DAT !'Input from water (mg/hr)' !** 39

DRINKA=WDOSE*BW/DAT 40

CV = AB0/VB !'Initialize CV' 41

42

END !'End of INITIAL' 43

44

DYNAMIC 45

46

ALGORITHM IALG = 2 !'Gear method for stiff systems' 47

TERMT ( T .GE. TSTOP ) 48B

- 31

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE CR = AR/VR 1

CS = AS/VS 2

CF = AF/VF 3

BODY = AL + AR + AS + AF + AB + TUMMY 4

BURDEN = AM + BODY 5

TMASS = BURDEN + AX + AMEX 6

7

!Calculate the Interval Excretion Data here:' 8

! DAX = AMEX

- AMEX2 9

! IF ( DOSE .LE. 0.0 .AND. IV .LE. 0.0 ) GO TO SKIP1 10

! PCTAX = 100*(AX

- AX2)/(DOSE + IV*BW) 11

! PCTMX = 100*(AMEX

- AMEX2)/(DOSE + IV*BW) 12

! SKIP1.. CONTINUE 13

! IF ( T .LT. TDATA(I) .OR. I .GE. 20 ) GO TO SKIP 14

! AX2=AX 15

! AMEX2=AMEX 16

! I=I+1 17

! SKIP.. CONTINUE 18

19

!DISCRETE EXPOSE 20

! CIZONE = 1.0 ! CALL LOGD(.TRUE.) Turns on inhalation exposure? 21

!END 22

!DISCRETE CLEAR 23

! CIZONE = 0.0 ! CALL LOGD(.TRUE.) 24

!END 25

26

DERIVATIVE 27

28

!Use Zero

- Crossing Form of DISCRETE Function Here' 29

! SCHEDULE command must be in DERIVATIVE section' 30

! DAILY = PULSE ( 0.0, PER1, TCHNG ) 31

! WEEKLY = PULSE ( 0.0, PER2, LEN2 ) 32

! SWITCHY = DAILY * WEEKLY 33

!SCHEDULE EXPOSE .XP. SWITCHY

- 0.995 34

!SCHEDULE CLEAR .XN. SWITCHY

- 0.005 35

36

DAILY=PULSE(0.0,PERD,WIDD) 37

WEEKLY=PULSE(0.0,PERW,WIDW) 38

SWITCHY = DAILY * WEEKLY 39

40

!********** ************Modified Here for Wong*****************' 41

CI = CONC * MW / 24451.0 * SWITCHY!** 42

43

!CA = Concentration in arterial blood (mg/l)' 44

CA = (QC*CV+QP*CI)/(QC+(QP/PB)) 45

CX = CA/PB 46

47

DRINK=DRINKA*SWITCHY !** 48B

- 32

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

!TUMMY = Amount in stomach' 2

RTUMMY =

- KA*TUMMY 3

TUMMY = INTEG(RTUMMY,DOSE) 4

!RAX = Rate of Elimination in Exhaled air' 5

RAX = QP*CX 6

AX = INTEG(RAX, 0.0) 7

8

!AS = Amount in slowly perfused tissues (mg)' 9

RAS = SPDC*(CA

- CVS) !now governed by diffusion

- limited constant, SPDC, instead of QS 10

AS = INTEG(RAS,0.) 11

CVS = AS/(VS*PS) 12

13

!AR = Amount in rapidly perfused tissues (mg)' 14

RAR = QR*(CA

- CVR) 15

AR = INTEG(RAR,0.) 16

CVR = AR/(VR*PR) 17

18

!AF = Amount in fat tissue (mg)' 19

RAF = QF*(CA

- CVF) 20

AF = INTEG(RAF,0.) 21

CVF = AF/(VF*PF) 22

23

!AL = Amount in liver tissue (mg)' 24

RAL = QL*(CA

- CVL)

- KL*CVL

- VMAX*CVL/(KM+CVL) + KA*TUMMY + DRINK 25

AL = INTEG(RA L,0.) 26

CVL = AL/(VL*PL) 27

28

!Metabolism comments updated by EDM on 2/1/10 29

!AM = Amount metabolized (mg)' 30

RMEX = (KL*CVL)+(VMAX*CVL/(KM+CVL)) !Rate of 1,4

- dioxane metabolism 31

RAM = (KL*CVL)+(VMAX*CVL)/(KM+CVL)

- KME*AM !Rate of change of metabolite 32

in body 33

34

AM = INTEG(RAM, 0.0) !'Amt Metabolite in body 35

CAM = AM/BW !'Conc Metabolite in body' 36

AMEX = INTEG(KME*AM, 0.0) !'Amt Metabolite Excreted via urine' 37

38

!AB = Amount in Venous Blood' 39

RAB = QF*CVF + QL*CVL + QS*CVS + QR*CVR

- QC*CV 40

AB = INTEG(RAB, AB0) 41

CV = AB/VB 42

AUCV = INTEG(CV, 0.0) 43

44

!Possible Dose Surrogates for Risk Assessment Defined Here' 45

46

CEX = 0.667*CX + 0.333*CI !'Conc in Exhal Air' 47

AVECON = PLA * (CEX+CI)/2 !'Ave Conc in Nose Tissue' 48B

- 33

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE AUCCON = INTEG(AVECON, 0.0) !'Area under Curve (Nose)' 1

2

AUCMET = INTEG(CAM, 0.0) !'Area under Curve (Metab)' 3

4

CL = AL/VL !'Conc Liver Tissue' 5

AUCL = INTEG(CL, 0.0) !'Area under Curve (Liver)' 6

AAUCL=AUCL/TIME 7

8

! Dose Surrogates are Average Area under Time/Conc Curve per 24 hrs' 9

IF (T .GT. 0) TIME=T 10

day S = TIME/24.0 11

NOSE = AUCCON/DAYS !'Nasal Turbinates' 12

LIVER = AUCL/DAYS !'Liver Tissues' 13

METAB = AUCMET/DAYS !'Stable Metabolite' 14

15

END !'End of dynamic' 16

17

END ! End of TERMINAL 18

19

END !'End of PROGRAM 20C

- 1

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX C. DETAILS OF BMD ANALYSIS FOR O RAL RfD FOR 1,4

- DIOXANE

C.1. CORTICAL TUBULE DEGE NERATION

All available dichotomous models in the Benchmark Dose Software (version 2.1.1) were 1

fit to the incidence data shown in Table C

- 1, for cortical tubule degeneration in male and female 2

Osborne

- Mendel rats exposed to 1,4

- dioxane in the drinking water ( NCI, 1978 ) . Doses 3

associated with a BMR of a 10% extra risk were calculated. 4

Table C

- 1. Incidence of cortical tubule degeneration in Osborne

- Mendel rats

exposed to 1,4

- dioxane in drinking water for 2 year s

Males (mg/kg

- day) Females (mg/kg

- day)

0 240 530 0 350 640

0/31 a 20/31 b

(65%) 27/33 b

(82%) 0/31 a 0/34 10/32 b

(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 )

.

As assessed by the χ 2 goodness

- of

- fit test, several models in the software provided 5

adequate fits to the data for the incidence of cortical tubule degeneration in male and female rats 6

(χ

2 p ≥ 0.1) ( Table C

- 2). Comparing across models, a better fit is indicated by a lower AIC 7

value ( U.S. EPA, 2000a ) . As assessed by Akaike‘s Information Criterion (AIC), the log

- probit 8

model provided the best fit to the cortical tubule degeneration incidence data for male rats 9

( Table C

- 2, Figure C

- 1) and could be use d to derive a POD of 38.5 mg /k g

- day for this endpoint. 10

The Weibull model provided the best fit to the data for female rats ( Table C

- 2, Figure C

- 5) and 11

could be used to derive a POD of 452.4 mg /kg

- day for this endpoint. For those models that 12

exhibit adequ ate fit, models with the lower AIC values are preferred. Differences in AIC values 13

of less than 1 are generally not considered important. BMDS modeling results for all 14

dichotomous models are shown in Table C

- 2. 15

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 Assessment s (ISA)

and the Integrated Risk Information System (IRIS)C

- 2

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table C

- 2. Goodness

- of

- fit statistics an d BMD 10 and BMDL 10 values from

models fit to incidence data for cortical tubule degeneration in male and

female Osborne

- Mendel rats ( NCI, 1978 ) exposed to 1,4

- dioxane in drinking

water

1

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(mg/kg

- day) BMDL 10

(mg/kg

- day)

Male

Gamma

b 74.458 0.6514 0 28.80 22.27

Logistic 89.0147 0.0011

- 1.902 88.48 65.84

Log

- logistic c 75.6174 1 0 20.85 8.59

Log

- probit c 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

Weibull b 74.458 0.6514 0 28.80 22.27

Quantal

- Linear 74.458 0.6514 0 28.80 22.27

Female

Gamma

b 41.9712 0.945 0.064 524.73 437.08

Logistic 43.7495 0.9996 0 617.44 471.92

Log

- logistic c 41.7501 0.9999 0 591.82 447.21

Log

- probit c 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

Weibull b 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 )

.C

- 3

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

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.

==================================================================== 1

Probit Model. (Version: 3.1; Date: 05/16/2008) 2

Input Data File: C: \ 14DBMDS \ lnp_nci_mrat_cortdeg_Lnp

- BMR10

- restrict.(d) 3

Gnuplot Plotting File: C: \ 14DBMDS \ lnp_nci_mrat_cortdeg_Lnp

- BMR10

- restrict.plt 4

Mon Feb 01 14:49:17 2010 5

==================================================================== 6

BMDS Model Run 7

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 8

The form of the probability function is: 9

10

P[response] = Background + (1

- Background) * CumNorm(I ntercept+Slope*Log(Dose)), 11

12

where CumNorm(.) is the cumulative normal distribution function 13

14

Dependent variable = Effect 15

Independent variable = Dose 16

Slope parameter is restricted as slope >= 1 17

18

Total number of observations = 3 19

Total numbe r of records with missing values = 0 20

Maximum number of iterations = 250 21

Relative Function Convergence has been set to: 1e

- 008 22

Parameter Convergence has been set to: 1e

- 008 23C

- 4

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE User has chosen the log transformed model 1

2

3

Default In itial (and Specified) Parameter Values 4

background = 0 5

intercept =

- 5.14038 6

slope = 1 7

8

9

Asymptotic Correlation Matrix of Parameter Estimates 10

(*** The model parameter(s)

- background

- slope have been estimated at a boundary 11

point, or have been specified by the user, and do not appear in the correlation 12

matrix) 13

14

intercept 15

intercept 1 16

17

18

Parameter Estimate s 19

20

95.0% Wald Confidence Interval 21

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22

background 0 NA 23

intercept

- 5.22131 0.172 682

- 5.55976

- 4.88286 24

slope 1 NA 25

26

NA

- Indicates that this parameter has hit a bound implied by some inequality 27

constraint and thus has no standard error. 28

29

30

31

Analysis of Devian ce Table 32

33

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 34

Full model

- 35.8087 3 35

Fitted model

- 36.084 1 0.550629 2 0.7593 36

Reduced model

- 65.8437 1 60.07 2 <.0001 37

38

AIC: 74.168 39

40

41

Goodness of Fit 42

Scaled 43

Dose Est._Prob. Expected Observed Size Residual 44

------------------------------------------------------------------------ 45

0.0000 0.0000 0.000 0.000 31 0.000 46

240.0000 0.6023 18.672 20.000 31 0.487 47

530.0000 0.8535 28.166 27.000 33

- 0.574 48

49

Chi^2 = 0.57 d.f. = 2 P

- value = 0.7532 50

51

52

Benchmark Dose Computation 53

Specified effect = 0.1 54

Risk Type = Extra ri sk 55

Confidence level = 0.95 56

BMD = 51.4062 57

BMDL = 38.5284 58C

- 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1 978 )

.

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.

=============================================================== ===== 1

Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 2

Input Data File: Z: \ 14Dioxane \ BMDS \ wei_nci_frat_cortdeg_Wei

- BMR10

- Restrict.(d) 3

Gnuplot Plotting File: Z: \ 14Dioxane \ BMDS \ wei_nci_frat_cortdeg_Wei

- BMR10

- Restrict.plt 4

Fri Dec 04 14:20:41 2009 5

==================================================================== 6

BMDS Model Run 7

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 8

The form of the probability function is: 9

10

P[response] = background + ( 1

- background)*[1

- EXP(

- slope*dose^power)] 11

12

Dependent variable = Effect 13

Independent variable = Dose 14

Power parameter is restricted as power >=1 15

16

Total number of observations = 3 17

Total number of records with missing values = 0 18

Maximum number of iterations = 250 19

Relative Function Convergence has been set to: 1e

- 008 20

Parameter Convergence has been set to: 1e

- 008 21

22

23

24C

- 6

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial (and Specified) Parameter Values 1

Background = 0.015625 2

Slope = 1.55776e

- 010 3

Power = 3.33993 4

5

6

Asymptotic Correlation Matrix of Parameter Estimates 7

(*** The model parameter(s)

- Background

- Power have been estimated at a boundary 8

point, or have been specified by the user, and do not appear in the correlation 9

matrix) 10

11

Slope 12

Slope

- 1.$ 13

14

Parameter Estimates 15

95.0% Wald Confidence Interval 16

Vari able Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 17

Background 0 NA 18

Slope 1.15454e

- 051 1.#QNAN 1.#QNAN 1.#QNAN 19

Power 18 NA 20

21

NA

- Indicates that this parameter has hit a bound implied by some inequality 22

constraint and thus has no standard error. 23

24

Analysis of Deviance Table 25

26

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 27

Full model

- 19.8748 3 28

Fitted model

- 19.875 1 0.000487728 2 0.9998 29

Reduced model

- 32.1871 1 24.6247 2 <.0001 30

31

AIC: 41.75 32

33

34

Goodness of Fit 35

Scaled 36

Dose Est._Prob. Expected Observed Size Residual 37

------------------------------------------------------------------------ 38

0.0000 0.0000 0.000 0.000 31 0.000 39

350.0000 0.0000 0.000 0.000 34

- 0.016 40

640.0000 0.3125 9.999 10.000 32 0.000 41

42

Chi^2 = 0.00 d.f. = 2 P

- value = 0.9999 43

44

45

Benchmark Dose Computation 46

Specified effect = 0.1 47

Risk Type = Extra risk 48

Confidence level = 0.95 49

BMD = 596.445 50

BMDL = 452.359 51C

- 7

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE C.2. LIVER HYPERPLASIA

All available dichoto mous models in the Benchmark Dose Software (version 2.1.1) were 1

fit to the incidence data shown in Table C

- 3, for liver hyperplasia in male and female 2

F344/DuCrj rats exposed to 1,4

- dioxane in the drinking water ( JBRC, 1998 ; Kano, et al., 2009 )

. 3

Benchmark doses associated with a BMR of a 10% extra risk were calculated. 4

Table C

- 3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to

1,4

- dioxane in drinking water a

Males (mg/kg

- day) Females (mg/kg

- day)

0 11 55 274 0 18 83 429

3/40 2/45 9/35 a 12/22 c 2 /38 b 2 /37 9 /38 24 /24 c

a Dose information from Kano et al. ( 2009 ) and incidence data from sacrificed animals from JBRC ( 1998 )

. 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 ) ; JBRC ( 1998 )

.

For incidence of liver hyperplasia in F344 male rats, the logistic, pr obit, and 5

dichotomous

- Hill models all exhibited a statistically significant lack of fit (i.e., 2 p

- value < 0.1; 6

see Table C

- 4), and thus should not be considered further for identification of a POD. All of the 7

remaining models exhibited adequate fit, but the AIC values for the gamma, multistage, quantal

8

linear, and Weibull models were lower than the AIC values for the log

- logistic and log

- probit 9

models. Finally, the AIC values for gamma, multistage, quantal

- linear, and Weibull models in 10

Table C

- 4 are equ ivalent and, in this case, essentially represent the same model. Therefore, 11

consistent with the external review draft Benchmark Dose Technical Guidance ( U.S. EPA, 12

2000a ) , any of them with equal AIC values (gamma, multistage, quantal

- linear, or Weibull) 13

could be used to identify a POD for this end point of 23.8 mg /kg

- day. 14

For liver hyperplasias in F344 female rats exposed to 1,4

- dioxane, the quantal

- linear and 15

dichotomous

- Hill models did not result in a good fit (i.e., 2 p

- value < 0.1; See Table C

- 4 ). The 16

multistage (3

- degree) model had the lowest AIC value and was selected as the best

- fitting model. 17

Therefore, consistent with the B MD t echnical g uidance document ( U.S. EPA, 2000a ) , the 18

BMDL from the multistage (3

- degree) model was selected to yield a POD for this endpoint of 19

27.1 mg /kg

- day. 20C

- 8

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table C

- 4. Benchmark dose modeling result s 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

- value a Scaled

Residual of

Interest BMD 10

(mg/kg

- day) BMDL 10

(mg/kg

- day)

Male

Gamma

b 114.172 0.3421 0.886 35.90 23.81

Logistic 117.047 0.0706 1.869 83.56 63.29

Log

- logistic c 115.772 0.1848 0.681 33.39 16.96

Log

- probit c 115.57 0.1431 1.472 54.91 37.05

Multistage d

(2 degree) 114.172 0.3421 0.886 35.90 23.81

Probit 116.668 0.0859 1.804 76.69 58.57

Weibull b 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 NC e

- 0.2398 32.01 14.84

Female

Gamma

b 78.8357 0.9783 0 70.78 40.51

Logistic 77.0274 0.9174

- 0.016 54.66 41.11

Log

- logistic c 78.8357 0.9781 0 77.72 51.21

Log

- probit c 78.8357 0.9781 0 74.64 50.97

Multistage d

(2 degree) 76.9718 0.9563

- 0.107 56.06 31.17

Multistage d

(3 degree) 76.8351 0.9999 0 65.28 27.08

Probit 77.0308 0.9095 0.017 52.53 38.44

Weibull b 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 NC e 0 NC e NC e

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 ) ; JBRC ( 1998 )

.C

- 9

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 suppor t

results Table C

- 4.

==================================================================== 1

Gamma Model. (Version: 2.13; Date: 05/16/2008) 2

Input Data File: Z: \ 14Dioxane \ BMDS \ gam_jbrc1998_mrat_liver_hyper_Gam

- BMR10

- 3

Restrict.(d) 4

Gnuplot Plotting File: Z: \ 14Dioxane \ BMDS \ gam_jbrc1998_mrat_liver_hyper_Gam

- BMR10

- 5

Restrict.plt 6

Fri Dec 04 14:35:02 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~ 10

The form of the probability function is: 11

12

P[response]= background+(1

- background)*CumGamma[slope*dose,power], 13

where CumGamma(.) is the cummulative Gamma distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Pow er parameter is restricted as power >=1 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22

Relative Function Convergence has been set to: 1e

- 008 23C

- 10

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Parameter Convergence has been set to: 1e

- 008 1

2

3

Default Initial (and Specified) Parameter Values 4

Background = 0.0853659 5

Slope = 0.00479329 6

Power = 1.3 7

8

9

Asymptotic Correlation Matrix of Parameter Estimates 10

(*** The model parameter(s)

- Power have been estimated at a boundary point, or have 11

been specified by the user, and do not appear in the correlation matrix ) 12

13

Background Sl ope 14

Background 1

- 0.36 15

Slope

- 0.36 1 16

17

Parameter Estimates 18

95.0% Wald Confidence Interval 19

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 20

Background 0.0569658 0.0278487 0.00238329 0.111548 21

Slope 0.00293446 0.000814441 0.00133818 0.00453073 22

Power 1 N A 23

24

NA

- Indicates that this parameter has hit a bound implied by some inequality 25

constraint and thus has no standard error. 26

27

Analysis of Deviance Table 28

29

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 30

Full model

- 53.9471 4 31

Fitted model

- 55.0858 2 2.27725 2 0.3203 32

Reduced model

- 67.6005 1 27.3066 3 <.0001 33

34

AIC: 114.172 35

36

37

Goodness of Fit 38

Scaled 39

Dose Est._Prob. Expected Observed Size Residual 40

-------------------------------------------------------- ---------------- 41

0.0000 0.0570 2.279 3.000 40 0.492 42

11.0000 0.0869 3.911 2.000 45

- 1.011 43

55.0000 0.1975 6.913 9.000 35 0.886 44

274.0000 0.5780 12.715 12.000 22

- 0.309 45

46

Chi^2 = 2.15 d.f. = 2 P

- value = 0.3421 47

48

49

Benchmark Dose Computation 50

Specified effect = 0.1 51

Risk Type = Extra risk 52

Confidence level = 0.95 53

BMD = 35.9046 54

BMDL = 23.8065 55C

- 11

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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.

==================================================================== 1

Multistage Model. (Version: 3.0; Date: 05/16/2008) 2

Input Data File: Z: \ 14Dioxane \ BMDS \ mst_jbrc1998_mrat_liver_hyper_Mst

- BMR10

- 3

restrict.(d) 4

Gnuplot Plotting File: Z: \ 14Dioxane \ BMDS \ m st_jbrc1998_mrat_liver_hyper_Mst

- BMR10

- 5

Restrict.plt 6

Fri Dec 04 14:35:06 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

19

Total numb er of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 3 22

Total number of specified parameters = 0 23

Degree of polynomial = 2 24

25

26C

- 12

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Maximum number of iterations = 250 1

Relative Function Convergence has be en set to: 1e

- 008 2

Parameter Convergence has been set to: 1e

- 008 3

4

5

6

Default Initial Parameter Values 7

Background = 0.0750872 8

Beta(1) = 0.00263797 9

Beta(2) = 0 10

11

12

Asymptotic Correlation Matrix of Parameter Estimates 13

(*** The model parameter(s)

- Beta(2) have been estimated at a boundary point, or have 14

been specified by the user, and do not appear in the correlation matrix) 15

16

Background Beta(1) 17

Background 1

- 0.49 18

Beta(1)

- 0.49 1 19

20

21

Parameter Estimates 22

95.0% Wald Confidence Interval 23

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24

Background 0.0569658 * * * 25

Beta(1) 0.00293446 * * * 26

Beta(2) 0 * * * 27

28

*

- Indicates that this value is not calculated. 29

30

31

32

Analysis of Deviance Table 33

34

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 35

Full model

- 53.9471 4 36

Fitted model

- 55.0858 2 2.27725 2 0.3203 37

Reduced model

- 67.6005 1 27.3066 3 <.0001 38

39

AIC: 114.172 40

41

42

Goodness of Fit 43

Scaled 44

Dose Est._Prob. Expected Observed Size Residual 45

-------------------------------------------------------- ---------------- 46

0.0000 0.0570 2.279 3.000 40 0.492 47

11.0000 0.0869 3.911 2.000 45

- 1.011 48

55.0000 0.1975 6.913 9.000 35 0.886 49

274.0000 0.5780 12.715 12.000 22

- 0.309 50

51

Chi^2 = 2.15 d.f. = 2 P

- value = 0.3421 52

53

54

Benchmark Dose Computation 55

Specified effect = 0.1 56

Risk Type = Extra risk 57

Confidence level = 0.95 58

BMD = 35.9046 59

BMDL = 23.8065 60

BMDU = 82.1206 61

62

Taken together, (23.8065, 82.1206) is a 90% two

- sided confidence interval for the BMD 63C

- 13

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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.

==================================================================== 1

Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 2

Input Data File: Z: \ 14Dioxane \ BMDS \ wei_jbrc1998_mrat_liver_hyper_Wei

- BMR10

- 3

Restrict.(d) 4

Gnuplot Plotting File: Z: \ 14Dioxane \ BMDS \ wei_jbrc1998_mrat_liver_hyper_Wei

- BMR10

- 5

Restrict.plt 6

Fri Dec 04 14:35:08 2009 7

======================================== ============================ 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = background + (1

- background)*[1

- EXP(

- slope*dose^power)] 13

14

Dependent variabl e = Effect 15

Independent variable = Dose 16

Power parameter is restricted as power >=1 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Maximum number of iterations = 250 21

Relative Function Convergence has been set to: 1e

- 008 22

Parameter Convergence has been set to: 1e

- 008 23

24

25

26C

- 14

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial (and Specified) Parameter Values 1

Background = 0.0853659 2

Slope = 0.00253609 3

Power = 1 4

5

6

Asymptotic Correlation Matrix of Parameter Estimates 7

( ** The model parameter(s)

- Power have been estimated at a boundary point, or have 8

been specified by the user, and do not appear in the correlation matrix ) 9

10

Background Slope 11

Background 1

- 0.36 12

Slope

- 0.36 1 13

14

15

Parameter Estimates 16

95.0% Wald Confidence Interval 17

Variab le Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 18

Background 0.0569661 0.0278498 0.00238155 0.111551 19

Slope 0.00293445 0.000814445 0.00133816 0.00453073 20

Po wer 1 NA 21

22

NA

- Indicates that this parameter has hit a bound implied by some inequality 23

constraint and thus has no standard error. 24

25

26

Analysis of Deviance Table 27

28

Model Log(likelihood) # Param 's Deviance Test d.f. P

- value 29

Full model

- 53.9471 4 30

Fitted model

- 55.0858 2 2.27725 2 0.3203 31

Reduced model

- 67.6005 1 27.3066 3 <.0001 32

33

AIC: 114.172 34

35

36

Goodness of Fit 37

Scaled 38

Dose Est._Prob. Expected Observed Size Residual 39

------------------------------------------------------------------------ 40

0.0000 0.0570 2.279 3.000 40 0.492 41

11.0000 0.0869 3.911 2.000 45

- 1.011 42

55.0000 0.1975 6.913 9.000 35 0.886 43

274.0000 0.5780 12.715 12.000 22

- 0.309 44

45

Chi^2 = 2.15 d.f. = 2 P

- value = 0.3421 46

47

48

Benchmark Dose Computation 49

Specified effect = 0.1 50

Risk Type = Extra risk 51

Confidence level = 0.95 52

BMD = 35.9047 53

BMDL = 23.8065 54C

- 15

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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

su pport the results in Table C

- 4.

==================================================================== 1

Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 2

Input Data File: Z: \ 14Dioxane \ BMDS \ qln_jbrc1998_mrat_liver_hyper_Qln

- BMR10.(d ) 3

Gnuplot Plotting File: Z: \ 14Dioxane \ BMDS \ qln_jbrc1998_mrat_liver_hyper_Qln

- BMR10.plt 4

Fri Dec 04 14:35:09 2009 5

==================================================================== 6

BMDS Model Run 7

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 8

The form of the probability function is: 9

10

P[response] = background + (1

- background)*[1

- EXP(

- slope*dose)] 11

12

13

Dependent variable = Effect 14

Independent variable = Dose 15

16

Total number of observations = 4 17

Total number of records with missing values = 0 18

Maximum number of iterations = 250 19

Relative Function Convergence has been set to: 1e

- 008 20

Parameter Convergence has been set to: 1e

- 008 21

22

Default Initial (and Specified) Parameter Values 23

Background = 0.0853659 24

Slope = 0.00253609 25

Power = 1 Specified 26C

- 16

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlation Matrix of Parameter Estimates 1

(** * The model parameter(s)

- Power have been estimated at a boundary point, or have 2

been specified by the user, and do not appear in the correlation matrix) 3

4

Background Slope 5

Background 1

- 0.36 6

Slope

- 0.36 1 7

8

9

10

Parameter Estimates 11

95.0% Wald Confidence Interval 12

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 13

Background 0.0569665 0.02785 0.00238157 0.111551 14

Slope 0.00293447 0.000814452 0.00133818 0.00453077 15

16

17

18

Analysis of Deviance Table 19

20

Model Log(likelihood) # Param's Dev iance Test d.f. P

- value 21

Full model

- 53.9471 4 22

Fitted model

- 55.0858 2 2.27725 2 0.3203 23

Reduced model

- 67.6005 1 27.3066 3 <.0001 24

25

AIC: 114.1 72 26

27

28

Goodness of Fit 29

Scaled 30

Dose Est._Prob. Expected Observed Size Residual 31

--------------------------------------------------- --------------------- 32

0.0000 0.0570 2.279 3.000 40 0.492 33

11.0000 0.0869 3.911 2.000 45

- 1.011 34

55.0000 0.1975 6.913 9.000 35 0.886 35

274.0000 0.5780 12.716 12.000 22

- 0.309 36

37

Chi^2 = 2.15 d.f. = 2 P

- value = 0.3421 38

39

40

Benchmark Dose Computation 41

Specified effect = 0.1 42

Risk Type = Extra risk 43

Confidence level = 0.95 44

BMD = 35.9044 45

BMDL = 23.8065 46C

- 17

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: JBRC ( 1998 )

.

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

.

==================================================================== 1

Multistage Model. (Version: 3.0; Date: 05/16/2008) 2

Input Data File: H: \ 14Dioxane \ BMDS \ mst_jbrc1998_frat_liver_hyper_Mst

- BMR10

- Restrict

3

3deg.(d) 4

Gnuplot Plotting File: H: \ 14Dioxane \ BMDS \ mst_jbrc1998_frat_liver_hyper_Mst

- BMR10

- 5

Restrict

- 3deg.plt 6

Fri May 21 10:30:14 2010 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2

- 13

beta3*dose^3)] 14

15

The parameter betas are restricted to be positive 16

17

Dependent variable = Effect 18

Independent variable = Dose 19

20

Total number of observations = 4 21

Total number of records with missing values = 0 22

Total number of parameters in model = 4 23C

- 18

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Total number of specified parameters = 0 1

Degree of polynomial = 3 2

3

Maximum number of iterations = 250 4

Relative Function Convergence has been set to: 1e

- 008 5

Parameter Convergence has been set to: 1e

- 008 6

7

Default Initial Parameter Values 8

Background = 0 9

Beta(1) = 0 10

Beta(2) = 0 11

Beta(3) = 1.2696e+012 12

13

Asymptotic Correlation Matrix of Parameter Estimates 14

15

(*** The model parameter(s)

- Beta(1),

- Beta(2) have been estimated at a boundary 16

point, or have b een specified by the user, and do not appear in the correlation 17

matrix) 18

19

Background Beta(3) 20

Background 1

- 0.55 21

Beta(3)

- 0.55 1 22

23

24

Parameter Estimates 25

26

95.0% Wald Confidence Interval 27

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 28

Background 0.0523101 * * * 29

Beta(1 ) 0 * * * 30

Beta(2) 0 * * * 31

Beta(3) 3.78712e

- 007 * * * 32

33

*

- Indicates that this value is not calculated. 34

35

36

Analysis of Deviance Table 37

38

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 39

Full model

- 36.4175 4 40

Fitted model

- 36.4175 2 0.00016582 2 0.9999 41

Reduced model

- 79.9164 1 86.9979 3 <.0001 42

43

AIC: 76.8351 44

45

Goodness of Fit 46

Scaled 47

Dos e Est._Prob. Expected Observed Size Residual 48

------------------------------------------------------------------------ 49

0.0000 0.0523 1.988 2.000 38 0.009 50

18.0000 0.0544 2.013 2.000 37

- 0.009 51

83.0000 0.2368 8.999 9.000 38 0.000 52

429.0000 1.0000 24.000 24.000 24 0.000 53

54

Chi^2 = 0.00 d.f. = 2 P

- value = 0.9999 55

56

Benchmark Dose Computation 57

Specified effect = 0.1 58

Risk Type = Extra risk 59

Confidence level = 0.95 60

BMD = 65.2814 61

BMDL = 27.0766 62

BMDU = 91.3457 63

64

Taken to gether, (27.0766, 91.3457) is a 90% two

- sided confidence interval for the BMD 65D

- 1

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX D. DETAILS OF BMD ANALYSIS FOR OR AL CSF FOR 1,4

- DIOXANE

Dichotomous models available in the Benchmark Dose Software (BMDS) (version 2.1.1) 1

were fit to the incidence data for hepatocellular carcinoma and/or adenoma for mice and rats, as 2

well as nasal cavity tumors, peritoneal mesotheliomas, and mammary gland ade nomas in rats 3

exposed to 1,4

- dioxane in the drinking water. Doses associated with a benchmark response 4

(BMR) of a 10% extra risk were calculated. BMD 10 and BMDL 10 values from the best fitting 5

model, determined by adequate global

- fit (χ 2 p ≥ 0.1) and AI C values, are reported for each 6

endpoint ( U.S . EPA, 2000a ) . If the multistage cancer model is not the best fitting model for a 7

particular endpoint, the best

- fitting multistage cancer model for that endpoint is also presented as 8

a point of comparison. 9

A summary of the model predictions for the K ano et al. ( 2009 ) study are shown in 10

Table D

- 1. The data and BMD modeling results are presented separately for each dataset as 11

follows: 12

Hepatic adenomas and carcinomas in female F344 rats (Tables D

- 2 and D

- 3; Figure D

- 1) 13

Hepatic adenomas and carcinomas in male F344 rats (Tables D

- 4 and D

- 5; Figures D

- 2 14

and D

- 3) 15

Signific ant tumor incidence data at sites other than the liver (i.e., nasal cavity, mammary 16

gland, and peritoneal) in male and female F344 rats ( Table D

- 6) 17

o Nasal cavity tumors in female F344 rats ( Table D

- 7; Figure D

- 4) 18

o Nasal cavity tumors in male F344 rats ( Table D

- 8; Figure D

- 5) 19

o Mammary gland adenomas in female F344 rats ( Table D

- 9; Figures D

- 6 and D

- 7) 20

o Peritoneal mesotheliomas in male F344 rats ( Table D

- 10; Figures D

- 8 and D

- 9) 21

Hepatic adenomas and carcinomas in female BDF 1 mice (Tables D

- 11, D

- 12, and D

- 13; 22

Fig ures D

- 10, D

- 11, D

- 12, and D

- 13) 23

Hepatic adenomas and carcinomas in male BDF 1 mice (Tables D

- 14 and D

- 15; Figures 24

D

- 14 and D

- 15) 25

Data and BMD modeling results from the additional chronic bioassays ( Kociba, et al., 1974 ; 26

NCI, 1978 ) were evaluated for comparison with the data from Kano et al. ( 2009 ) . These results 27

are presented as follows: 28

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

(Health and Environmental Research Online) a t 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 Assess ments (ISA)

and the Integrated Risk Information System (IRIS)D

- 2

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Summary of BMDS dose

- response modeling estimates associated with liver and nasal 1

tumor incidence data resulting from chronic oral exposure to 1,4

- dioxane in rats and mice 2

( Table D

- 16) 3

Incidence of hepatocellular carcinoma and nasal squamous cell carcinoma in male and 4

female Sherman rats (combined) ( Kociba, e t al., 1974 ) treated with 1,4

- dioxane in the 5

drinking water for 2 years ( Table D

- 17) 6

o BMDS dose

- response modeling results for incidence of hepatocellular carcinoma in 7

male and female Sherman rats (combined) ( Kociba, et al., 1974 ) exposed to 8

1,4

- dioxane in drinking water for 2 years ( Table D

- 18; Figures D

- 16 and D

- 17) 9

o BMDS dose

- response modeling results for incidence of nasa l squamous cell 10

carcinoma in male and female Sherman rats (combined) ( Kociba, et al., 1974 ) 11

exposed to 1,4

- dioxane in the drinking water for 2 years ( Table D

- 19; Figure D

- 18) 12

Incidence of nasal cavity squamous cell carcinoma and hepatocellular adenoma in 13

Osborne

- Mendel rats ( NCI, 1978 ) exposed to 1,4

- dioxane in the drinking water ( Table D

14

20) 15

o BMDS dose

- response modeling results for incidence of hepatocellular adenoma in 16

female Osborne

- Mendel rats ( NCI, 1978 ) exposed to 1,4

- dioxane in the drinking 17

water for 2 years ( Table D

- 21; Figures D

- 19 and D

- 20) 18

o BMDS dose

- response modeling results for incidence of nasal cavity squamous cell 19

carcinoma in female Osborne

- Mendel rats ( NCI, 1978 ) exposed to 1,4

- dioxane in the 20

drink ing water for 2 years ( Table D

- 22; Figures D

- 21 and D

- 22) 21

o BMDS dose

- response modeling results for incidence of nasal cavity squamous cell 22

carcinoma in male Osborne

- Mendel rats ( NCI, 1978 ) exposed to 1,4

- dioxane in the 23

drinking water for 2 years ( Table D

- 23; Figures D

- 23 and D

- 24) 24

Incidence of hepatocellular adenoma or carcinoma in male and female B6C3F 1 mice 25

( NCI, 1978 ) exposed to 1,4

- dioxane in drinking water ( Table D

- 24) 26

o BMDS dose

- response modeling results for the combined incidence of hepatocellular 27

adenoma or carcinoma in female B6C3F 1 mice ( NCI, 1978 ) exposed to 1,4

- dioxane in 28

the dr inking water for 2 years ( Table D

- 25; Figure D

- 25) 29

o BMDS dose

- response modeling results for incidence of combined hepatocellular 30

adenoma or carcinoma in male B6C3F 1 mice ( NCI, 1978 ) exposed to 1,4

- dioxane in 31

the drinking water for 2 years ( Table D

- 26; Figures D

- 26 and D

- 27). 32

D.1. GENERAL ISSUES AND A PPROACHES TO BMDS MO DELING

D.1.1. Combining Data on Adenomas and Carcinomas

The in cidence of adenomas and the incidence of carcinomas within a dose group at a site 33

or tissue in rodents are sometimes combined. This practice is based upon the hypothesis that 34D

- 3

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE adenomas may develop into carcinomas if exposure at the same dose was continued ( McConnell, 1

et al., 1986 ; U.S. EPA, 2005a ) . The incidence at high doses of both tumors in rat and mouse 2

liver is high in the key study ( Kano, et al., 2009 ) . The incidence of hepatic adenomas and 3

carci nomas was summed without double

- counting them so as to calculate the combined 4

incidence of either a hepatic carcinoma or a hepatic adenoma in rodents. 5

The variable N is used to denote the total number of animals tested in the dose group. 6

The variable Y is used here to denote the number of rodents within a dose group that have 7

characteristic X, and the notation Y(X) is used to identify the number with a specific 8

characteristic X. Modeling was performed on the adenomas and carcinomas separately and the 9

fo llowing combinations of tumor types: 10

Y(adenomas) = number of animals with adenomas, whether or not carcinomas are 11

present; 12

Y(carcinomas) = number of animals with carcinomas, whether or not adenomas are also 13

present; 14

Y(either adenomas or carcinomas) = numbe r of animals with adenomas or carcinomas, 15

not both = Y(adenomas) + Y(carcinomas)

– Y(both adenomas and carcinomas); 16

Y(neither adenomas nor carcinomas) = number of animals with no adenomas and no 17

carcinomas = N

- Y(either adenomas or carcinomas). 18

D.1.2. Model Se lection Criteria

Multiple models were fit to each dataset. The model selection criteria used in the B MD 19

t echnical g uidance d ocument ( U.S. EPA, 2000a ) were applied as follows: 20

p

- value for goodness

- of

- fit > 0.10 21

AIC smaller than other acceptable models 22

χ

2 residuals as small as possible 23

No systemati c patterns of deviation of model from data 24

Additional criteria were applied to eliminate implausible dose

- response functions: 25

Monotonic dose

- response functions, e.g. no negative coefficients of polynomials in MS 26

models 27

No infinitely steep dose

- response functions near 0 (control dose), achieved by requiring 28

the estimated parameters ―power‖ in the Weibull and Gamma models and ―slope‖ in the 29

log

- logistic model to have values ≥ 1. 30

Because no single set of criteria covers all contingencies, an extended list of preferred models are 31

presented below in Table D

- 1. 32D

- 4

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.1.3. Summary

The BMDS models recommended to calculate rodent BMD and BMDL values and 1

corresponding human BMD HED and BMDL HED values are summarized in Table D

- 1. 2

Table D

- 1. Recommended models for rodents exposed to 1,4

- dioxane in

drinking water ( Kano, et al., 2009 )

Endpoint Model

selection

criterion Model Type AIC p

- value BMD a

mg/kg

day BMDL a

mg/kg

day BMD HED a

mg/kg

day BMDL HE

D a

mg/kg

day

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

Meso

thelioma 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

Hepatic

Tumors Lowest

AIC LogLogistic 176.214 0.1421 5.54 3.66 0.83 0.55

BMR 50% LogLogistic 176.214 0.1421 49.88 b 32.93 b 7.51 b 4.95 b

Male BDF1 Mouse

Hepatic

Tumors Lowest

AIC Log

Logistic 248.839 0.3461 34.78 16.60 5.63 2.68

3

a Values for BMR 10% unless otherwise noted. 4

b BMR 50%. 5

D.2. FEMALE F344 RATS: H EPATIC CARCINOMAS AN D ADENOMAS

The incidence data for hepatic carcinomas and adenomas in female F344 rats ( Kano, et 6

al., 2009 ) are shown in Table D

- 2. 7D

- 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 2. Data for hepatic adenomas and carcinomas in female F344 rats

( Kano, et al., 2009 )

Tumor type Dose (mg/kg

- day)

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 )

.

Note that the incidence of rats with adenomas, with carcinomas, and with either 1

aden omas or carcinomas are monotone non

- decreasing functions of dose except for 3 female rats 2

in the control group. These data therefore appear to be appropriate for dose

- response modeling 3

using BMDS. 4

The results of the BMDS modeling for the entire suite of models are presented in 5

Table D

- 3. 6

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 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit b 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 NC d NC d NC d 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

- 6

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission of Elsevier , Ltd

., Kano et al. ( 2009 )

.

Figure D

- 1. Multistage BMD model (2 degree) for the combined incidence of

hepatic adenomas and carcinomas in female F344 rats.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxan e \ BMDS \ msc_kano2009_frat_hepato_adcar_Msc

3

BMR10

- 2poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_frat_hepato_adcar_Msc

- BMR10

- 2poly.plt 6

Mon Oct 26 08:20:52 2009 7

=============================================================== ===== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2)] 13

14

The parameter betas are restricted to b e positive 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 3 22

Total number of specified parameters = 0 23

Degree of polynomial = 2 24

25

Maximum number of iterations = 250 26

Relative Function Convergence has been set to: 1e

- 008 27

Parameter Convergence has been set to: 1e

- 008 28

29

Default Initial Parameter Values 30

Background = 0.0281572 31D

- 7

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Beta(1) = 0 1

Beta(2) = 1.73306e

- 005 2

3

Asymptotic Correlation Matrix of Parameter Estimates ( *** The model parameter(s)

- 4

Beta(1)have been estimated at a boundary point, or have been specified by the user, 5

and do not appear in the correlation matrix ) 6

7

Background Beta(2) 8

Background 1

- 0.2 9

Beta(2)

- 0.2 1 10

11

Parameter Estimates 12

95.0% Wald Confidence Interval 13

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

Background 0.036277 3 * * * 15

Beta(1) 0 * * * 16

Beta(2) 1.65328e

- 005 * * * 17

18

*

- Indicates that this value is not calculated. 19

20

21

Analysis of Deviance Table 22

23

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 24

Full model

- 42.9938 4 25

Fitted model

- 43.7949 2 1.60218 2 0.4488 26

Reduc ed model

- 120.43 1 154.873 3 <.0001 27

28

AIC: 91.5898 29

30

Goodness of Fit 31

Scaled 32

Dose Est._Prob. Expected Observed Size Residual 33

------------------------------------------------------------------------ 34

0.0000 0.0363 1.814 3.000 50 0.897 35

18.0000 0.0414 2.071 1.000 50

- 0.760 36

83.0000 0.1400 7.001 6.000 50

- 0.408 37

429.0000 0.9540 47.701 48.000 50 0.202 38

39

Chi^2 = 1.59 d.f. = 2 P

- value = 0.4516 40

41

Benchmark Dose Computation 42

43

Specified effect = 0.1 44

Risk Type = Extra risk 45

Confidence level = 0.95 46

BMD = 79.8299 47

BMDL = 58.085 48

BMDU = 94.0205 49

50

Taken together, (58.085 , 94.0205) is a 90% two

- sided confidence interval for the BMD 51

52

Multistage Cancer Slope Factor = 0.00172161 53D

- 8

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.3. MALE F344 RATS: HEP ATIC CARCINOMAS AND ADENOMAS

The data for hepatic adenomas and carcinomas in male F344 rats ( Kano, et al., 2009 ) are 1

shown in Table D

- 4. 2

Table D

- 4. Data for hepatic adenomas and carcinomas in male F344 rats

( Kano, et al., 2009 )

Tumor type Dose (mg/kg

- day)

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 )

. 3

Note that the incidence of rats with hepatic adenomas, carcinomas, and with either 4

adenomas or carcinomas are monotone non

- decreasing functions of dose. These data therefore 5

appear to be appropriate for dose

- response modeling using BMDS. 6

The results of the BMDS modeling for the entire suite of models tested u sing the data for 7

hepatic adenomas and carcinomas for male F344 rats are presented in Table D

- 5. 8D

- 9

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit b 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

Probit c 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 NC d NC d NC d 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

- 10

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elservier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 2. Probit BMD model for the combined incidence of hepatic

adenomas and carcinomas in male F344 rats.

==================================================================== 1

Probit Model. (Version: 3.1; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ pro_kano2009_mrat_hepato_adcar_Prb

3

BMR10.(d) 4

Gnupl ot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ pro_kano2009_mrat_hepato_adcar_Prb

- BMR10.plt 6

Mon Oct 26 08:32:08 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

P[response] = CumNorm(Intercept+Slope*Dose), 13

where CumNorm(.) is the cumulative normal distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is not restricted 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22

Relative Function Convergence has been set to: 1e

- 008 23

Parameter Convergence has been set to: 1e

- 008 24

25

26

Default Initial (and Speci fied) Parameter Values 27

background = 0 Specified 28

intercept =

- 1.51718 29

slope = 0.00831843 30

31D

- 11

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlation Matrix of Parameter Estimates 1

( *** The model parameter(s)

- background have been estimated at a boundary point, or 2

have bee n specified by the user, and do not appear in the correlation matrix ) 3

4

intercept slope 5

intercept 1

- 0.69 6

slope

- 0.69 1 7

8

9

Parameter Estimates 10

95.0% Wald Confidence Interval 11

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 12

intercept 1.53138 0.160195

- 1.84535

- 1.2174 13

slope 0.00840347 0.000976752 0.00648907 0.0103179 14

15

16

Analysis of Deviance Table 17

18

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 19

Full model

- 71.8804 4 20

Fitted model

- 71.8937 2 0.0265818 2 0.9868 21

Reduced model

- 115.644 1 87.528 3 <.0001 22

23

AIC: 147.787 24

25

26

Goodness of Fit 27

Scaled 28

Do se Est._Prob. Expected Observed Size Residual 29

------------------------------------------------------------------------ 30

0.0000 0.0628 3.142 3.000 50

- 0.083 31

11.0000 0.0751 3.754 4.00 0 50 0.132 32

55.0000 0.1425 7.125 7.000 50

- 0.050 33

274.0000 0.7797 38.985 39.000 50 0.005 34

35

Chi^2 = 0.03 d.f. = 2 P

- value = 0.9867 36

37

Benchmark Dose Computation 38

39

Specified effect = 0.1 40

Risk Type = Extra risk 41

Confidence level = 0.95 42

BMD = 62.1952 43

BMDL = 51.1158 44

45D

- 12

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elservier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 3. Multistage BMD model (3 degree) for the combined incidence of

he patic adenomas and carcinomas in male F344 rats.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mrat_hepato_adcar_Msc

3

BMR10

- 3poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mrat_hepato_adcar_Msc

- BMR10

- 3poly.plt 6

Mon Oct 26 08:32:08 2009 7

==================== ================================================ 8

9

BMDS Model Run 10

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11

12

The form of the probability function is: P[response] = background + (1

- background)*[1

- 13

EXP(

- beta1*dose^1

- beta2*dose^2

- beta3*dose^3)] 14

15

The parameter betas are restricted to be positive 16

17

Dependent variable = Effect 18

Independent variable = Dose 19

20

Total number of observations = 4 21

Total number of records with missing values = 0 22

Total number of parameters in model = 4 23

Total number of specified parameters = 0 24

Degree of polynomial = 3 25

26

Maximum number of iterations = 250 27

Relative Function Convergence has been set to: 1e

- 008 28

Parameter Convergence has been set to: 1e

- 008 29

30

Default Initial Parameter Values 31D

- 13

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Background = 0.062382 2 1

Beta(1) = 0.00142752 2

Beta(2) = 0 3

Beta(3) = 5.14597e

- 008 4

Asymptotic Correlation Matrix of Parameter Estimates 5

( *** The model parameter(s)

- Beta(2)have been estimated at a boundary point, or have 6

been specified by the user, and do not appear in the correlation matrix ) 7

8

Background Beta(1) Beta(3) 9

Background 1

- 0.67 0.58 10

Beta(1)

- 0.67 1

- 0.95 11

Beta(3) 0.58

- 0.95 1 12

13

14

Parameter Estimates 15

16

95.0% Wald Confidence Interval 17

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 18

Background 0.0619918 * * * 19

Beta(1) 0.001449 * * * 20

Beta(2) 0 * * * 21

Beta(3) 5.11829e

- 008 * * * 22

23

*

- Indicates that this value is not calculated. 24

25

26

27

Analysis of Deviance Table 28

29

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 30

Full model

- 71.8804 4 31

Fitted model

- 71.8858 3 0.0107754 1 0.9173 32

Reduced model

- 115.644 1 87.528 3 <.0001 33

34

AIC: 149.772 35

36

37

Goodness of Fit 38

Scal ed 39

Dose Est._Prob. Expected Observed Size Residual 40

------------------------------------------------------------------------ 41

0.0000 0.0620 3.100 3.000 50

- 0.058 42

11.0000 0.0769 3.84 4 4.000 50 0.083 43

55.0000 0.1412 7.059 7.000 50

- 0.024 44

274.0000 0.7799 38.997 39.000 50 0.001 45

46

Chi^2 = 0.01 d.f. = 1 P

- value = 0.9171 47

48

49

Benchmark Dose Computation 50

51

Specified effect = 0.1 52

Risk Type = Extra risk 53

Confidence level = 0.95 54

BMD = 63.6179 55

BMDL = 27.4913 56

BMDU = 123.443 57

58

Taken together, (2 7.4913, 123.443) is a 90% two

- sided confidence interval for the BMD 59

60

Multistage Cancer Slope Factor = 0.00363752 61D

- 14

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.4. F344 RATS: TUMORS A T OTHER SITES

The data for tumors at sites other than the liver in male and female F344 rats ( Kano, et 1

al., 2009 ) are shown in Table D

- 6. Note that the incidence of rats with these endpoints are 2

monotone non

- decreasing functions (except female peritoneal mesotheliomas). These data 3

therefore appear to be appropriate for dose

- response modeling using BMDS. 4

Table D

- 6. Data for significant tumors at other sites in male and fe male F344

rats ( Kano, et al., 2009 )

Tumor site and t ype Dose (mg/kg

- day)

Female Male

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 )

.

The results of the BMDS modeling for the entire suite of models are presented in Tables 5

D

- 7 through Table D

- 10 for tumors in the nasal cavity, mammary gland, and peritoneal cavity. 6D

- 15

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 7. BMDS dose

- response modeling results for the incidence of nasal

cavity tumors in female F344 rats a ( Kano , et al., 2009 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2b BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit c 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

- 16

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 4. Multistage BMD model (3 degree) for nasal cavity tumors in

female F344 rats.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 0 5/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_frat_nasal_car_Msc

3

BMR10

- 3poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_frat_nasal_car_Msc

- BMR10

- 3poly.plt 6

Mon Oct 26 08:28:58 2009 7

============== ====================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: P[response] = background + (1

- 11

background)*[1

- EXP(

- beta1*dose^1

- beta2* dose^2

- beta3*dose^3)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Total number of observations = 4 18

Total number of records with missing values = 0 19

Total number of parameters in model = 4 20

Total number of specified parameters = 0 21

Degree of polynomial = 3 22

23

Maximum number of iterations = 250 24

Relative Function Convergence has been set to: 1e

- 008 25

Parameter Convergence has been set to: 1e

- 008 26

27

Default Initial Parameter Values 28

Background = 0 29

Beta(1) = 0 30

Beta(2) = 0 31

Beta(3) = 1.91485e

- 009 32D

- 17

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlation Matrix of Parameter Estimates 1

( *** The model parameter(s)

- Background

- Beta(1)

- Beta(2) 2

have been estimated at a boundary point, or have been specified by the user, 3

and do not appear in the correlation matrix ) 4

5

Beta(3) 6

Beta(3) 1 7

8

Parameter Estimates 9

10

95.0% Wald Confidence Interval 11

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 12

Background 0 * * * 13

Beta(1) 0 * * * 14

Beta(2) 0 * * * 15

Beta(3) 1.89531e

- 009 * * * 16

17

*

- Indicates that this value is not calculated. 18

19

20

Analysis of Deviance Table 21

22

Model Log(likelihood) # P aram's Deviance Test d.f. P

- value 23

Full model

- 20.2482 4 24

Fitted model

- 20.3031 1 0.109908 3 0.9906 25

Reduced model

- 30.3429 1 20.1894 3 0.0001551 26

27

AIC: 42.6063 28

29

30

Goodness of Fit 31

Scaled 32

Dose Est._Prob. Expected Observed Size Residual 33

--------------------------------------- --------------------------------- 34

0.0000 0.0000 0.000 0.000 50 0.000 35

18.0000 0.0000 0.001 0.000 50

- 0.024 36

83.0000 0.0011 0.054 0.000 50

- 0.233 37

429.000 0 0.1390 6.949 7.000 50 0.021 38

39

Chi^2 = 0.06 d.f. = 3 P

- value = 0.9966 40

41

42

Benchmark Dose Computation 43

44

Specified effect = 0.1 45

Risk Type = Extra risk 46

Confidence level = 0.95 47

BMD = 381.651 48

BMDL = 282.609 49

BMDU = 500.178 50

51

Taken together, (282.609, 500.178) is a 90% two

- sided confidence interval for the BMD 52

53

Multistage Cancer Slope Factor = 0.000353846 54D

- 18

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 8. BMDS dose

- response modeling results for the incidence of nasal

cavity tumors in male F344 rats a ( Kano, et al., 2009 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2b BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit c 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

- 19

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permis s ion from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 5. Multistage BMD model (3 degree) for nasal cavity tumors in

male F344 rats.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mrat_nasal_car_Msc

3

BMR10

- 3poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mrat_nasal_car_Msc

- BMR10

- 3poly.plt 6

Mon Oct 26 08:34:20 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: P[response] = background + (1

- background)*[1

- 11

EXP(

- beta1*dose^1

- beta2*dose^2

- beta3*dose^3)] 12

13

The parameter betas are restricted to be positive 14

15

De pendent variable = Effect 16

Independent variable = Dose 17

Total number of observations = 4 18

Total number of records with missing values = 0 19

Total number of parameters in model = 4 20

Total number of specified parameters = 0 21

Degree of polynomial = 3 22

23

Maximum number of iterations = 250 24

Relative Function Convergence has been set to: 1e

- 008 25

Parameter Convergence has been set to: 1e

- 008 26

27

Default Initial Parameter Values 28

Background = 0 29D

- 20

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Beta(1) = 0 1

Beta(2) = 0 2

Beta(3) = 3.01594e

- 009 3

4

5

As ymptotic Correlation Matrix of Parameter Estimates 6

7

( *** The model parameter(s)

- Background

- Beta(1)

- Beta(2) 8

have been estimated at a boundary point, or have been specified by the user, 9

and do not appear in the correlation matrix ) 10

11

Beta(3) 12

Beta(3) 1 13

14

15

Parameter Estimates 16

17

95.0% Wald Confidence Interval 18

Variable Estimate Std. Err. Lower Conf. Limit Uppe r Conf. Limit 19

Background 0 * * * 20

Beta(1) 0 * * * 21

Beta(2) 0 * * * 22

Beta(3) 2. 98283e

- 009 * * * 23

24

*

- Indicates that this value is not calculated. 25

26

27

28

Analysis of Deviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 11.3484 4 32

Fitted model

- 11.3735 1 0.0502337 3 0.9971 33

Reduced model

- 15.5765 1 8.45625 3 0.03747 34

35

AIC: 24.747 36

37

38

Goodness of Fit 39

Scaled 40

Dose Est._Prob. Expected Observed Size Residual 41

-------------------------------------------------------- ---------------- 42

0.0000 0.0000 0.000 0.000 50 0.000 43

11.0000 0.0000 0.000 0.000 50

- 0.014 44

55.0000 0.0005 0.025 0.000 50

- 0.158 45

274.0000 0.0595 2.976 3.000 50 0.015 46

47

Chi^2 = 0.03 d.f. = 3 P

- value = 0.9989 48

49

50

Benchmark Dose Computation 51

52

Specified effect = 0.1 53

Risk Type = Extra risk 54

Confidence level = 0.95 55

BMD = 328.108 56

BMDL = 245.634 57

BMDU = 1268.48 58

59

Taken together, (245.634, 1268.48) is a 90% two

- sided confidence interval for the BMD 60

61

Multistage Cancer Slope Factor = 0.00040711 62D

- 21

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 9. BMDS dose

- response modeling results for the incidence of

mammary gland adenomas in female F344 rats ( Kano, et al., 2009 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogLogistic b 194.151 0.8874 161.01 81.91 0.406 40.01 20.35

LogProbit c 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 NC d 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

- 22

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Use with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 6. LogLogistic BMD model for mammary gland adenomas in

female F344 rats.

==================================================================== 1

Logistic Model. (Version: 2.12; D ate: 05/16/2008) 2

Input Data File: C: \ 14DBMDS \ lnl_kano2009_frat_mamm_ad_Lnl

- BMR10

- Restrict.(d) 3

Gnuplot Plotting File: C: \ 14DBMDS \ lnl_kano2009_frat_mamm_ad_Lnl

- BMR10

- Restrict.plt 4

Mon Feb 01 11:31:31 2010 5

========================================== ========================== 6

BMDS Model Run 7

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 8

The form of the probability function is: 9

10

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 11

12

Dependent variable = Effect 13

Independent variable = Dose 14

Slope parameter is restricted as slope >= 1 15

16

Total number of observations = 4 17

Total number of records with missing values = 0 18

Maximum number of iterations = 250 19

Relative Function Convergence has been set to: 1e

- 008 20

Parameter Convergence has been set to: 1e

- 008 21

22

User has chosen the log transformed model 23

24

Default Initial Parameter Values 25

background = 0.12 26

in tercept =

- 7.06982 27

slope = 1 28

Asymptotic Correlation Matrix of Parameter Estimates 29D

- 23

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

( *** The model parameter(s)

- slope have been estimated at a boundary point, or have 2

been specified by the user, and do not appear in the correlation matrix ) 3

4

background intercept 5

background 1

- 0.53 6

intercept

- 0.53 1 7

8

Parameter Estimates 9

10

95.0% Wald Confidence Interval 11

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 12

background 0.130936 * * * 13

intercep t

- 7.2787 * * * 14

slope 1 * * * 15

16

*

- Indicates that this value is not calculated. 17

18

19

20

Analysis of Deviance Table 21

22

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 23

Full model

- 94.958 4 24

Fitted model

- 95.0757 2 0.235347 2 0.889 25

Reduced model

- 98.6785 1 7.4409 3 0.0591 26

27

AIC: 194.151 28

29

30

Goodness of Fit 31

Scaled 32

Dose Est._Prob. Expected Observed Size Residual 33

------- ----------------------------------------------------------------- 34

0.0000 0.1309 6.547 6.000 50

- 0.229 35

18.0000 0.1416 7.080 7.000 50

- 0.032 36

83.0000 0.1780 8.901 10.000 50 0.406 37

429.0000 0.3294 16.472 16.000 50

- 0.142 38

39

Chi^2 = 0.24 d.f. = 2 P

- value = 0.8874 40

41

42

Benchmark Dose Computation 43

Specified effect = 0.1 44

Risk Type = Extra risk 45

Confidence level = 0.95 46

BMD = 161.012 47

BMDL = 81.9107 48D

- 24

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 7. Multistage BMD model (1 degree) for mammary gland

adenomas in female F344 rats.

=============== ===================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_frat_mamm_ad_Msc

- BMR10

- 3

1poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 1 4Dioxane \ BMDS \ msc_kano2009_frat_mamm_ad_Msc

- BMR10

- 1poly.plt 6

Mon Oct 26 08:27:02 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 2 22

Total number of specified parameters = 0 23

Degree of polynomial = 1 24

25

Maximum number of iterations = 250 26

Relative Function Convergence has been set to: 1e

- 008 27

Parameter Converge nce has been set to: 1e

- 008 28

29

Default Initial Parameter Values 30

Background = 0.136033 31

Beta(1) = 0.000570906 32D

- 25

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlation Matrix of Parameter Estimates 1

2

Background Beta(1) 3

Background 1

- 0.58 4

Beta(1)

- 0.5 8 1 5

6

7

Parameter Estimates 8

9

95.0% Wald Confidence Interval 10

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 11

Background .133161 * * * 12

Beta(1) 0.000596394 * * * 13

14

*

- Indicates that this value is not calculated. 15

16

17

18

Analysis of Deviance Table 19

20

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 21

Full model

- 94.958 4 22

Fitted model

- 95.111 2 0.305898 2 0.8582 23

Reduced model

- 98.6785 1 7.4409 3 0.0591 24

25

AIC: 194.222 26

27

28

Goodness of Fit 29

Scaled 30

Dose Est._Prob. Expected Observed Size Residual 31

---------------------------------------------- -------------------------- 32

0.0000 0.1332 6.658 6.000 50

- 0.274 33

18.0000 0.1424 7.121 7.000 50

- 0.049 34

83.0000 0.1750 8.751 10.000 50 0.465 35

429.0000 0 .3288 16.442 16.000 50

- 0.133 36

37

Chi^2 = 0.31 d.f. = 2 P

- value = 0.8559 38

39

40

Benchmark Dose Computation 41

42

Specified effect = 0.1 43

Risk Type = Extra risk 44

Confidence level = 0.95 45

BMD = 176.663 46

BMDL = 99.1337 47

BMDU = 501.523 48

49

Taken together, (99.1337, 501.523) is a 90% two

- sided confidence interval for the BMD 50

51

Multistage Cancer Slope Factor = 0.00100874 52D

- 26

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 10. BMDS do se

- response modeling results for the incidence of

peritoneal mesotheliomas in male F344 rats ( Kano, et al., 2009 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit b 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

Probit c 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 NC d NC d NC d 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

- 27

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 8

. Probit BMD model for peritoneal mesotheliomas in male F344

rats.

==================================================================== 1

Probit Model. (Version: 3.1; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCE A_HPAG \ 14Dioxane \ BMDS \ pro_kano2009_mrat_peri_meso_Prb

3

BMR10.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ pro_kano2009_mrat_peri_meso_Prb

- BMR10.plt 6

Mon Oct 26 08:41:29 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: P[response] = CumNorm(Intercept+Slope*Dose), 12

where CumNor m(.) is the cumulative normal distribution function 13

14

Dependent variable = Effect 15

Independent variable = Dose 16

Slope parameter is not restricted 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Maximum number of iterations = 250 21

Relative Function Convergence has been set to: 1e

- 008 22

Parameter Convergence has been set to: 1e

- 008 23

24

Default Initial (and Specified) Parameter Values 25

background = 0 Specified 26

intercept =

- 1.73485 27

slope = 0.00692801 28

29

Asymptotic Corr elation Matrix of Parameter Estimates 30D

- 28

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ( *** The model parameter(s)

- background have been estimated at a boundary point, or 1

have been specified by the user, and do not appear in the correlation matrix ) 2

3

intercept slope 4

intercept 1

- 0.75 5

slope

- 0.75 1 6

7

Parameter Estimates 8

95.0% Wald Confidence Interval 9

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 10

intercept

- 1.73734 0.18348

- 2.09695

- 1.37772 11

slope 0.00691646 0.000974372 0.00500672 0.00882619 12

13

Analysis of Deviance Table 14

Model Log(likelihood) # Param 's Deviance Test d.f. P

- value 15

Full model

- 67.3451 4 16

Fitted model

- 67.4344 2 0.178619 2 0.9146 17

Reduced model

- 95.7782 1 56.8663 3 <.0001 18

AIC: 138.869 19

20

Goodness of Fit 21

Scaled 22

Dose Est._Prob. Expected Observed Size Residual 23

---------------------------------------------- -------------------------- 24

0.0000 0.0412 2.058 2.000 50

- 0.041 25

11.0000 0.0483 2.417 2.000 50

- 0.275 26

55.0000 0.0874 4.370 5.000 50 0.315 27

274.0000 0 .5627 28.134 28.000 50

- 0.038 28

29

Chi^2 = 0.18 d.f. = 2 P

- value = 0.9148 30

Benchmark Dose Computation 31

Specified effect = 0.1 32

Risk Type = Extra risk 33

Confidence level = 0.95 34

BMD = 93.0615 35

BMDL = 76.3242 36

37

38D

- 29

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 9. Multistage BMD (2 degree) model for peritoneal

mesotheliomas in male F344 rats.

==================================================================== 1

Multistage Cancer M odel. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mrat_peri_meso_Msc

3

BMR10

- 2poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mrat_peri_meso_Msc

- BMR10

- 2poly.plt 6

Mon Oct 26 08:41:28 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

13

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2)] 14

15

The parameter betas are restricted to be positive 16

17

18

Dependent variable = Effect 19

Independent variable = Dose 20

21

Total number of observations = 4 22

Total number of records with missing values = 0 23

Total number of parameters in model = 3 24

Total number of specified parameters = 0 25

Degree of polynomial = 2 26

27

Maximum number of iterations = 250 28

Relative Function Convergence has been set to: 1e

- 008 29

Parameter Convergence has been set to: 1e

- 008 30

31D

- 30

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default In itial Parameter Values 1

Background = 0.0358706 2

Beta(1) = 0.000816174 3

Beta(2) = 7.47062e

- 006 4

5

6

Asymptotic Correlation Matrix of Parameter Estimates 7

8

Background Beta(1) Beta(2) 9

Background 1

- 0.67 0.59 10

Bet a(1)

- 0.67 1

- 0.98 11

Beta(2) 0.59

- 0.98 1 12

13

Parameter Estimates 14

95.0% Wald Confidence Interval 15

Variable Estimate Std. Err. Lower Conf. L imit Upper Conf. Limit 16

Background 0.0366063 * * * 17

Beta(1) 0.000757836 * * * 18

Beta(2) 7.6893e

- 006 * * * 19

20

*

- Indicates that this value is not calculated. 21

22

Analysis of Deviance Table 23

24

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 25

Full model

- 67.3451 4 26

Fitted model

- 67.3733 3 0.056567 1 0.812 27

Reduced model

- 95.7782 1 56.8663 3 <.0001 28

29

AIC: 140.747 30

31

32

Goodness of Fit 33

Scaled 34

Dose Est._Prob. Expected Observed Size Residual 35

------------------------------------------------------------------------ 36

0.0000 0.0366 1.830 2.000 50 0.128 37

11.0000 0.0455 2.275 2.000 50

- 0.186 38

55.0000 0.0972 4.859 5.000 50 0.067 39

274.0000 0.5605 28.027 28.000 50

- 0.008 40

41

Chi^2 = 0.06 d.f. = 1 P

- value = 0.8135 42

43

44

Benchmark Dose Computation 45

46

Specified effect = 0.1 47

Risk Type = Extra risk 48

Confidence level = 0.95 49

BMD = 77.7277 50

BMDL = 35.4296 51

BMDU = 118.349 52

53

Taken together, (35.4296, 118.349) is a 90% two

- sided confidence interval for the BMD 54

55

Multistage Cancer Slope Factor = 0.0028225 56D

- 31

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.5. FEMALE BDF 1 MICE: HEPATIC CARCI NOMAS AND ADENOMAS

Data for female BDF 1 mouse hepatic carcinomas and adenomas are shown in Table D

1

11. N ote that the incidence of carcinomas and the incidence of either adenomas or carcinomas 2

are monotone non

- decreasing functions of dose. These data therefore appear to be appropriate 3

for dose

- response modeling using BMDS. However, the incidence of adenoma s clearly reaches 4

a peak value at 66 mg /kg

- day and then decreases sharply with increasing dose. This cannot be 5

modeled by a multistage model using only non

- negative coefficients. To some extent the 6

incidence of ―either adenomas or carcinomas‖ retains so me of the inverted

- U shaped dose

7

response of the adenomas, which dominate based on their high incidence at the lowest dose 8

groups (66 and 278 mg /kg

- day), thus is not well characterized by any multistage model. 9

Table D

- 11. Data for hepatic adenomas and carc inomas in female BDF 1 mice

( Kano, et al., 2009 )

Tumo r type Dose (mg/kg

- day)

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 )

.

The r esults of the BMDS modeling for the entire suite of models for hepatic adenomas 10

and carcinomas in female BDF 1 mice are presented in Table D

- 12. The multistage models did 11

not provide reasonable fits to the incidence data for hepatocellular adenoma or carci noma in 12

female BDF 1 mice. The log

- logistic model provided the best

- fit to the data as indicated by the 13

AIC and p

- value as was chosen as the best

- fitting model to carry forward in the analysis; 14

however, this model resulted in a BMDL 10 much lower than the r esponse level at the lowest dose 15

in the study ( Kano, et al., 2009 ) . Thus, the log

- logistic model was run for BMRs of 30 and 50%. 16

The output from these models are shown in Figures D

- 11 and D

- 12. A summary of the BMD 17

results for BMRs of 10, 30, and 50% are shown in Table D

- 13. Using a higher BMR resulted in 18

BMDLs closer to the lowest observed response data, and a BMR of 50% was chosen to carry 19

forward in the analysis. 20

The graphical output from fitting these models suggested that a simpler model obtained 21

by dropping the data point for the highest dose (964 mg /kg

- day) might also be adequate. This 22

was tested and the results did not affect the choice of the model, nor significantly affect the 23

resulting BMDs and BMDLs. 24D

- 32

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 12. BMDS dose

- response modeling results for the combined

incidence of hepatic adenomas and carcinomas in female BDF 1 mice ( Kano,

et al., 2009 )

1

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogLogistic b 176.214 0.1421 5.54 3.66

- 0.121 0.83 0.55

LogProbit c 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 NC d NC d NC d 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 BDF 1 mice ( Kano, et al., 2009 )

.

BMR AIC p

- value BMD

mg/kg

- day BMDL

mg/kg

- day χ 2a BMD HED mg/kg

- day BMDL HED

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

- 33

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 10. LogLogistic BMD model for the combined incidence of hepatic

adenomas and carcinomas in female BDF 1 mice with a BMR of 10%.

==================================================================== 1

Logistic Model. (Version: 2.12; Date: 05/16/2008) 2

Input Data File: 3

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_fmouse_hepato_adcar_Lnl

- BMR10

- 4

Restrict.(d) 5

Gnuplot Plotting File: 6

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_fmouse_hepato_adcar_Lnl

- BMR 10

- 7

Restrict.plt 8

Wed May 12 11:26:35 2010 9

==================================================================== 10

BMDS Model Run 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12

The form of the probability function is: 13

P[ response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is restricted as slope >= 1 18

19

Total number of observations = 4 20

Total number of records with mis sing values = 0 21

Maximum number of iterations = 250 22D

- 34

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Relative Function Convergence has been set to: 1e

- 008 1

Parameter Convergence has been set to: 1e

- 008 2

3

User has chosen the log transformed model 4

5

Default Initial Parameter Value s 6

background = 0.1 7

intercept =

- 4.33618 8

slope = 1 9

10

Asymptotic Correlation Matrix of Parameter Estimates 11

(*** The model parameter(s)

- slope have been estimated at a boundary point, or have 12

been specified by the user, and do not appear in the correlation matrix ) 13

14

background intercept 15

background 1

- 0.32 16

intercept

- 0.32 1 17

18

Parameter Estimates 19

20

95.0% Wald Confidence Interval 21

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22

background 0.105265 * * * 23

intercept

- 3.90961 * * * 24

slope 1 * * * 25

26

*

- Indicates that this value is not calculated. 27

28

Analysis of D eviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 84.3055 4 32

Fitted model

- 86.107 2 3.6029 2 0.1651 33

Reduced model

- 131.248 1 93.8853 3 <.0001 34

35

AIC: 176.214 36

37

38

Goodness of Fit 39

Scaled 40

Dose Est._Prob. Expected Observed Size Residual 41

------------------------------------------------------------------------ 42

0.0000 0.1053 5.263 5.000 50

- 0.121 43

66.0000 0.6149 30.743 35.000 50 1.237 44

278.0000 0.8639 43.194 41.000 50

- 0.905 45

964.0000 0.9560 47.799 46.000 50

- 1.240 46

47

Chi^2 = 3.90 d.f. = 2 P

- value = 0.1421 48

49

50

Benchmark Dose Computa tion 51

Specified effect = 0.1 52

Risk Type = Extra risk 53

Confidence level = 0.95 54

BMD = 5.54218 55

BMDL = 3.65848 56

57D

- 35

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 11. LogLogistic BMD model for the combined incidence of hepatic

adenomas and carcinomas in female BDF 1 mice with a BMR of 30%.

==================================================================== 1

Logistic Model. (Version: 2.12; Date: 05/16/2008) 2

Input Data F ile: 3

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_fmouse_hepato_adcar_Lnl

- BMR30

- 4

Restrict.(d) 5

Gnuplot Plotting File: 6

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_fmouse_hepato_adcar_Lnl

- BMR30

- 7

Restrict.plt 8

Wed May 12 11:26:36 2010 9

==================================================================== 10

BMDS Model Run 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12

The form of the probability function is: 13

P[response] = background+(1

- background)/[1+EXP(

- inte rcept

- slope*Log(dose))] 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is restricted as slope >= 1 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22

Relative Function Convergence has been set to: 1e

- 008 23

Parameter Convergence has been set to: 1e

- 008 24D

- 36

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE User has chosen the log transformed model 1

2

Default Initial Parameter Values 3

background = 0.1 4

intercept =

- 4.33618 5

slope = 1 6

7

Asymptotic Correlation Matrix of Parameter Estimates 8

(*** The model parameter(s)

- slope have been estimated at a boundary point, or have 9

been specifi ed by the user, and do not appear in the correlation matrix) 10

11

background intercept 12

background 1

- 0.32 13

intercept

- 0.32 1 14

15

Parameter Estimates 16

17

95.0% Wald Confidence Interval 18

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 19

background 0.105265 * * * 20

intercept

- 3.90961 * * * 21

slope 1 * * * 22

23

*

- Indicates that this value is not calculated. 24

25

26

Analysis of Deviance Table 27

28

M odel Log(likelihood) # Param's Deviance Test d.f. P

- value 29

Full model

- 84.3055 4 30

Fitted model

- 86.107 2 3.6029 2 0.1651 31

Reduced model

- 131.248 1 93.8853 3 <.0001 32

33

AIC: 176.214 34

35

36

Goodness of Fit 37

Scaled 38

Dose Est._Prob. Expected Observed Size Residual 39

---------- -------------------------------------------------------------- 40

0.0000 0.1053 5.263 5.000 50

- 0.121 41

66.0000 0.6149 30.743 35.000 50 1.237 42

278.0000 0.8639 43.194 41.000 50

- 0.905 43

964.0000 0.9560 47.799 46.000 50

- 1.240 44

45

Chi^2 = 3.90 d.f. = 2 P

- value = 0.1421 46

47

48

Benchmark Dose Computation 49

Specified effect = 0.3 50

Risk Type = Extra risk 51

Confidence level = 0.95 52

BMD = 21.377 53

BMDL = 14.1113 54D

- 37

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 12. LogLogistic BMD model for the combined incidence of hepatic

adenomas and carcinomas in female BDF 1 mice with a BMR of 50%.

==================================================================== 1

Logistic Model. (Version: 2.12; Date: 05/16/2008) 2

Input Data File: 3

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_fmouse_hepato_adcar_Lnl

- BMR50

- 4

Restrict.(d) 5

Gnuplot Plotting File: 6

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_fmouse_hepato_adcar_Lnl

- BMR50

- 7

Restrict.plt 8

Wed May 12 11:26:36 2010 9

==================================================================== 10

BMDS Model Run 11

~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12

The form of the probability function is: 13

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is restricted as slope >= 1 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22D

- 38

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Relative Function Convergence has been set to: 1e

- 008 1

Parameter Convergence h as been set to: 1e

- 008 2

3

User has chosen the log transformed model 4

5

Default Initial Parameter Values 6

background = 0.1 7

intercept =

- 4.33618 8

slope = 1 9

10

Asymptotic Correlation Matrix of Parameter Estimates 11

(*** The model parameter(s)

- slope have been estimated at a boundary point, or have 12

been specified by the user, and do not appear in the correlation matrix) 13

14

background intercept 15

background 1

- 0.32 16

intercept

- 0.32 1 17

18

Parameter Estimates 19

20

95.0% Wald Confidence Interval 21

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22

background 0.105265 * * * 23

intercept

- 3.90961 * * * 24

slope 1 * * * 25

26

*

- Indicates that this value is not calculated. 27

28

Analysis of Deviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 84.3055 4 32

Fitted model

- 86.107 2 3.6029 2 0.1651 33

Reduced model

- 131.248 1 93.8853 3 <.0001 34

35

AIC: 176.214 36

37

Good ness of Fit 38

Scaled 39

Dose Est._Prob. Expected Observed Size Residual 40

------------------------------------------------------------------------ 41

0.0000 0.1053 5.263 5.000 50

- 0.121 42

66.0000 0.6149 30.743 35.000 50 1.237 43

278.0000 0.8639 43.194 41.000 50

- 0.905 44

964.0000 0.9560 47.799 46.000 50

- 1.240 45

46

Chi^2 = 3.90 d.f. = 2 P

- value = 0.1421 47

48

49

Benchmark Dose Computation 50

Specified effect = 0.5 51

Risk Type = Extra risk 52

Confidence level = 0.95 53

BMD = 49.8797 54

BMDL = 32.9263 55D

- 39

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 13. Multistage BMD model (1 degree) for the combined incidence of

hepatic adenomas and carcinomas in female BDF 1 mice.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: 3

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_fmouse_hepato_adcar_Msc

- BMR10

- 1poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_fmouse_hepato_adcar_M sc

- BMR10

- 1poly.plt 6

Wed May 12 11:26:31 2010 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Total number of parameters in model = 2 21

Total number of specified parameters = 0 22

Degree of polynomial = 1 23

24D

- 40

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Maximum number of iterations = 250 1

Relative Function Convergence has been set to: 1e

- 008 2

Param eter Convergence has been set to: 1e

- 008 3

4

Default Initial Parameter Values 5

Background = 0.51713 6

Beta(1) = 0.00201669 7

8

Asymptotic Correlation Matrix of Parameter Estimates 9

10

Background Beta(1) 11

Background 1

- 0.65 12

Beta(1)

- 0.65 1 13

14

Parameter Estimates 15

16

95.0% Wald Confidence Interval 17

Variab le Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 18

Background 0.265826 * * * 19

Beta(1) 0.00398627 * * * 20

21

*

- Indicates that thi s value is not calculated. 22

23

Analysis of Deviance Table 24

25

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 26

Full model

- 84.3055 4 27

Fitted model

- 99.6653 2 30.7195 2 2.1346928e

- 007 28

Reduced model

- 131.248 1 93.8853 3 <.0001 29

30

AIC: 203.331 31

32

Goodness of Fit 33

Scaled 34

Dose Est._Prob. Expected Observed Size Residual 35

------------------------------------------------------------------------ 36

0.0000 0.2658 13.291 5.00 0 50

- 2.654 37

66.0000 0.4357 21.783 35.000 50 3.770 38

278.0000 0.7576 37.880 41.000 50 1.030 39

964.0000 0.9843 49.213 46.000 50

- 3.651 40

41

Chi^2 = 35.65 d.f. = 2 P

- value = 0.0000 42

43

44

Benchmark Dose Computation 45

Specified effect = 0.1 46

47

Risk Type = Extra risk 48

Confidence level = 0.95 49

BMD = 26.4309 50

BMDL = 19.5045 51

BMDU = 37.5583 52

53

Taken together, (19.5045, 37.5583) is a 90% two

- sided confidence interval for the BMD 54

55

Multistage Cancer Slope Factor = 0.00512702 56D

- 41

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.6. MALE BDF 1 MICE: HEPATIC CARCI NOMAS AND ADENOMAS

Data for hepatic carcinomas and adeno mas in male BDF 1 mice ( Kano, et al., 2009 ) are 1

shown in Table D

- 14. Note that the incidence of carcinomas and the incidence of either 2

adenomas or carcinomas are monotone non

- decreasing functions of dose. These data therefore 3

appear to be appropriate for dose

- response modeling using BMDS. However, the in cidence of 4

adenomas clearly reaches a peak value at 191 mg /kg

- day and then decreases sharply with 5

increasing dose. This cannot be modeled by a multistage model using only non

- negative 6

coefficients. To some extent the incidence of ―either adenomas or car cinomas or both‖ retains 7

some of the inverted

- U shaped dose

- response of the adenomas, which dominate based on their 8

high incidence at the lowest dose groups (49 and 191 mg /kg

- day), thus is not well characterized 9

by any multistage model. 10

Table D

- 14. Data fo r hepatic adenomas and carcinomas in male BDF 1 mice

( Ka no, et al., 2009 )

Tumor type Dose (mg/kg

- day)

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 )

.

The results of the BMDS modeling for the entire suite of models for hepatic adenomas 11

and carcinomas in male BDF 1 mice are presented in Table D

- 15. 12D

- 42

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 15. BMDS dose

- response modeling results for the combined

incidence of hepatic adenomas and carcinomas in male BDF 1 mice ( Kano, et

al., 2009 )

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogLogistic b 248.839 0.3461 34.78 16.60 0.656 5.63 2.68

LogProbit c 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 NC d 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

- 43

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 14. LogLogistic BMD model for the combined incidence of hepatic

adenomas and carcinomas in male BDF 1 mice.

==================================================================== 1

Logistic Model. (Version: 2.12; Date: 05/16/2008) 2

Input Data File: 3

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_mmouse_hepato_adcar_Lnl

- BMR10

- 4

Restrict.(d) 5

Gnuplot Plotting File: 6

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_kano2009_mmouse_hepato_adcar_Lnl

- BMR10

- 7

Restrict.plt 8

Thu Nov 12 09:09:36 2009 9

==================================================================== 10

BMDS Model Run 11

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~ 12

The form of the probability function is: 13

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is restricted as slope >= 1 18

19

Total number of obser vations = 4 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22

Relative Function Convergence has been set to: 1e

- 008 23

Parameter Convergence has been set to: 1e

- 008 24

25

User has chosen the log transformed model 26

27D

- 44

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial Parameter Values 1

background = 0.46 2

intercept =

- 5.58909 3

slope = 1 4

Asymptotic Correlation Matrix of Parameter Estimates 5

6

( *** The model parameter(s)

- slope have been estimated at a boundary point, or have 7

been specified by the user, and do not appear in the correlation matrix ) 8

9

background intercept 10

background 1

- 0.69 11

intercept

- 0.69 1 12

13

14

Parameter Estimates 15

16

95.0% Wald Confidence Interval 17

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 18

background 0.507468 * * * 19

intercept

- 5.74623 * * * 20

slope 1 * * * 21

22

*

- Indicates that this value is not calculated. 23

24

25

Analysis of Deviance Table 26

27

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 28

Full model

- 121.373 4 29

Fitted model

- 122.419 2 2.09225 2 0.3513 30

Reduc ed model

- 128.859 1 14.9718 3 0.001841 31

32

AIC: 248.839 33

34

35

Goodness of Fit 36

Scaled 37

Dose Est._Prob. Expected Observed Size Residual 38

------------------------------------------------------------------------ 39

0.0000 0.5075 25.373 23.000 50

- 0.671 40

49.0000 0.5741 28.707 31.000 50 0.656 41

191.0000 0.6941 34.706 37.000 50 0.704 42

677.0000 0.8443 42.214 40.000 50

- 0.863 43

44

Chi^2 = 2.12 d.f. = 2 P

- value = 0.3461 45

46

47

Benchmark Dose Computation 48

Specified effect = 0.1 49

Risk Type = Extra risk 50

Confidence level = 0.95 51

BMD = 34.7787 52

BMDL = 16.5976 53D

- 45

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Else vier, Ltd., Kano et al. ( 2009 )

.

Figure D

- 15. Multistage BMD model (1 degree) for the combined incidence of

hepatic adenomas and carcinomas in male BDF 1 mice.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: 3

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mmouse_hepato_adcar_Msc

- BMR10

- 1poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kano2009_mmouse_hepato_adcar_Msc

- BMR10

- 1poly.plt 6

Mon Oct 26 08:30:50 2009 7

================ ==================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 2 22

Total number of specified param eters = 0 23

Degree of polynomial = 1 24

25

Maximum number of iterations = 250 26

Relative Function Convergence has been set to: 1e

- 008 27

Parameter Convergence has been set to: 1e

- 008 28

29D

- 46

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial Parameter Values 1

Background = 0.573756 2

Beta(1) = 0.00123152 3

4

Asymptotic Correlation Matrix of Parameter Estimates 5

Background Beta(1) 6

Background 1

- 0.58 7

Beta(1)

- 0.58 1 8

9

10

Parameter Estimates 11

12

95.0% Wald Confidence Interval 13

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

Background 0.545889 * * * 15

Beta(1) 0.00148414 * * * 16

17

*

- Indicates that this value is not calculated. 18

19

20

21

Analysis of Deviance Table 22

23

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 24

Fu ll model

- 121.373 4 25

Fitted model

- 123.275 2 3.80413 2 0.1493 26

Reduced model

- 128.859 1 14.9718 3 0.001841 27

28

AIC: 250.551 29

30

31

Goodness of Fit 32

Scaled 33

Dose Est._Prob. Expected Observed Size Residual 34

------------------------------------------------------------------------ 35

0.0000 0.5459 27.294 23.000 50

- 1.220 36

49.0000 0.5777 28.887 31.000 50 0.605 37

191.0000 0.6580 32.899 37.000 50 1.223 38

677.0000 0.8337 41.687 40.000 50

- 0.641 39

40

Chi^2 = 3.76 d.f. = 2 P

- value = 0.1527 41

42

43

Benchmark Dose Computation 44

45

Specified effect = 0.1 46

Risk Type = Extra risk 47

Confidence level = 0.95 48

BMD = 70.9911 49

BMDL = 44.0047 50

BMDU = 150.117 51

52

Taken together, (44.0047, 150.117) is a 90% two

- sided confidence interval for the BMD 53

54

Multistage Cancer Slope Factor = 0.00227248 55D

- 47

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.7. BMD MODELING RESULTS FROM ADDITIONAL CHRO NIC BIOASSA YS

Data and BMDS modeling results for the additional chronic bioassays ( Kociba, et al.

, 1

1974 ; NCI, 1978 ) were evaluated for comparison with the Kano et al. ( 2009 ) study. These 2

results are presented in the following sections. 3

The BMDS dose

- response modeling estimates and HED s that resulted are presented in 4

detail in the following sections and a summary is provided in Table D

- 16. 5

Table D

- 16. Summary of BMDS dose

- response modeling estimates associated

with liver and nasal tumor incidence data resulting from chronic oral

exposur e to 1,4

- dioxane in rats and mice

Endpoint Model

selection

criterion Model

Type AIC p

value BMD 10 mg/kg

day BMDL 10

mg/kg

day BMD 10 HED

mg/kg

day BMDL 10 HED

mg/kg

- day

Kociba et al., ( 1974 )

Male and Female (combined) Sherman Rats

Hepatic

Tumors a Lowest

AIC Probit 84.3126 0.606 1113.94 920.62 290.78 240.31

Nasal

Cavity

Tumors b Lowest

AIC Multistage

(3 degree) 26.4156 0.9999 1717.16 1306.29 448.24 340.99

NCI, ( 1978 )

Female Osborne

- Mendel Rats

Hepatic

Tumors c Lowest

AIC LogLogistic 84.2821 0.7333 111.46 72.41 28.75 18.68

Nasal

Cavity

Tumors b Lowest

AIC LogLogistic 84.2235 0.2486 155.32 100.08 40.07 25.82

NCI, ( 1978 )

Male Osborne

- Mendel Rats

Nasal

Cavity

Tumors b Lowest

AIC LogLogistic 92.7669 0.7809 56.26 37.26 16.10 10.66

NCI, ( 1978 )

Female B6C3F 1 Mice

Hepatic

Tumors d Lowest

AIC,

Multistage

model Multistage

(2 degree) 85.3511 1 160.68 67.76 23.12 9.75

NCI, ( 1978 )

Male B6C3F 1 Mice

Hepatic

Tumors d 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

- 48

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.7.1. Hepatocellular Carcinoma and Nasal Squamous Cell Carcinoma ( Kociba, et al.,

1974 )

The incidence data for hepatocellular carcinoma and nasal squamous cell carcinoma are 1

presented in Table D

- 17. The predicted BMD 10 HED and BMDL 10 HED values are also presented in 2

Tables D

- 18 and D

- 19 for hepatocellular carcinomas and nasal squamous cell carcinomas, 3

respectively. 4

Table D

- 17. Incidence of hepatocellular carcinoma and nasal squamous cell

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

treated with 1,4

- dioxane in the drinking water for 2 years

Animal Dose (mg/kg

- day)

(average of ma le and female dose) Incidence of hepatocellular

carcinoma a Incidence of nasal

squamous cell carcinoma a

0 1/106 b 0/106 c

14 0/110 0/110

121 1/106 0/106

1307 10/66 d 3/66 d

a Rats surviving until 12 month s 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 )

.D

- 49

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 ) exposed to 1,4

- dioxane in the drinking water for 2 years

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit b 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

Probit c 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 NC d NC d NC d 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

- 50

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kociba et al. ( 1974 )

.

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.

==================================================================== 1

Probit Model. (Version: 3.1; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ pro_kociba_mf _rat_hepato_car_Prb

3

BMR10.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ pro_kociba_mf_rat_hepato_car_Prb

- BMR10.plt 6

Tue Oct 27 12:54:14 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

P[response] = CumNorm(Intercept+Slope*Dose),where CumNorm(.) is the cumulative normal 13

distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is not restricted 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22

Relative Function Convergence has been set to: 1e

- 008 23

Parameter Convergence has been set to: 1e

- 008 24

25

Initial (and Specified) Parameter Values 26

background = 0 Specified 27

intercept =

- 2.62034 28D

- 51

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE slope = 0.0012323 1

Asymptotic Correlation Matrix of Parameter Estimates 2

( *** The model parameter(s)

- background have been estimated at a bou ndary point, or 3

have been specified by the user, and do not appear in the correlation matrix ) 4

5

intercept slope 6

intercept 1

- 0.82 7

slope

- 0.82 1 8

9

10

Parameter Estimates 11

12

95.0% Wald Confidence Interval 13

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

intercept

- 2.55961 0.261184

- 3.07152

- 2.0477 15

slope 0.00117105 0.000249508 0.000682022 0.00166008 16

17

18

Analysis of Deviance Table 19

20

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 21

Full model

- 39.3891 4 22

Fitted model

- 40.1563 2 1.53445 2 0.4643 23

Reduced model

- 53.5257 1 28.2732 3 <.0001 24

25

AIC: 84.3126 26

27

28

Goodness of Fit 29

Scaled 30

Dose Est._Prob. Expected Observed Size Residual 31

------------------------------------------------------------------------ 32

0.0000 0.0052 0.555 1.000 106 0.598 33

14.00 00 0.0055 0.604 0.000 110

- 0.779 34

121.0000 0.0078 0.827 1.000 106 0.191 35

1307.0000 0.1517 10.014 10.000 66

- 0.005 36

37

Chi^2 = 1.00 d.f. = 2 P

- value = 0.606 0 38

39

40

Benchmark Dose Computation 41

42

Specified effect = 0.1 43

Risk Type = Extra risk 44

Confidence level = 0.95 45

BMD = 1113.94 46

BMDL = 920.616 47D

- 52

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: Used with permission from Elsevier, Ltd., Kociba et al. ( 1974 )

.

Figure D

- 17. Multistage BMD model (1 degree) for the incidence of

hepatocell ular carcinoma in male and female Sherman rats exposed to

1,4

- dioxane in drinking water.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kociba_mf_rat_hepato_car_Msc

3

BMR10

- 1poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kociba_mf_rat_hepato_car_Msc

- BMR10

- 1poly.plt 6

Tue Oct 27 12:54:10 2009 7

======================== ============================================ 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

13

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 14

15

The parameter betas are restricted to be positive 16

17

Dependent variable = Effect 18

Independent variable = Dose 19

20

Total number of observations = 4 21

total number of records with missing values = 0 22

Total number of parameters in model = 2 23

Total number of specified parameters = 0 24

Degree of polynomial = 1 25

26

Maximum number of iterations = 250 27

Relative Function Convergence has been set to: 1e

- 008 28

Parameter Convergence has been set to: 1e

- 008 29D

- 53

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial Parameter Values 1

Background = 0.000925988 2

Beta(1) = 0.000124518 3

4

5

Asymptot ic Correlation Matrix of Parameter Estimates 6

Background Beta(1) 7

Background 1

- 0.44 8

Beta(1)

- 0.44 1 9

10

11

Parameter Estimates 12

13

95.0% Wald Confidence Interval 14

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 15

Background 0.0038683 * * * 16

Beta(1) 0.000112071 * * * 17

18

*

- Indicates that this value is not calculated. 19

20

21

Analysis of Deviance Table 22

23

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 24

Full model

- 39.3891 4 25

Fitted model

- 40.5594 2 2.34056 2 0.3103 26

Reduced model

- 53.5257 1 28.2732 3 <.0001 27

28

AIC: 85.1187 29

30

31

Goodness of Fit 32

Scaled 33

Dose Est._Prob. Expected Observed Size Residual 34

------------------------------------------------------------------------ 35

0.0000 0.0039 0.410 1.000 106 0.923 36

14.0000 0.0054 0.597 0.000 110

- 0.775 37

121.0000 0.0173 1.832 1.000 106

- 0.620 38

1307.0000 0.1396 9.213 10.000 66 0.279 39

40

Chi^2 = 1.92 d.f. = 2 P

- value = 0.3838 41

42

43

Benchmark Dose Computation 44

45

Specified effect = 0.1 46

Risk Type = Extra risk 47

Confidence level = 0.95 48

BMD = 940.124 49

BMDL = 583.576 50

BMDU = 1685.88 51

52

Taken together, (583.576, 1685.88) is a 90% two

- sided confidence interval for the BMD 53

54

Multistage Cancer Slope Factor = 0.000171357 55D

- 54

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 19. BMDS dose

- response modeling results for the incidence of nasal

squamous ce ll carcinoma in male and female Sherman rats (combined)

( Kociba, et al., 1974 ) exposed to 1,4

- dioxane in the drinking wat er for 2 years

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit b 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

- 55

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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.

1

==================================================================== 2

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 3

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kociba_mf_rat_nasal_car_Msc

4

BMR10

- 3poly.(d) 5

Gnuplot Plotting File: 6

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_kociba_mf_rat_nasal_car_Msc

- BMR10

- 3 poly.plt 7

Tue Oct 27 07:25:02 2009 8

==================================================================== 9

BMDS Model Run 10

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11

12

The form of the probability function is: 13

14

P[response] = backgr ound + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2

- 15

beta3*dose^3)] 16

17

The parameter betas are restricted to be positive 18

19

Dependent variable = Effect 20

Independent variable = Dose 21

22

Total number of observations = 4 23

Total number of records with missing values = 0 24

Total number of parameters in model = 4 25

Total number of specified parameters = 0 26

Degree of polynomial = 3 27

28D

- 56

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Maximum number of iterations = 250 1

Relative Function Convergence has been set to: 1e

- 008 2

Parameter Convergence has been set to: 1e

- 008 3

Default I nitial Parameter Values 4

Background = 0 5

Beta(1) = 0 6

Beta(2) = 0 7

Beta(3) = 2.08414e

- 011 8

9

10

Asymptotic Correlation Matrix of Parameter Estimates 11

12

( *** The model parameter(s)

- Background

- Beta(1)

- Beta(2) 13

have been estimated at a boundary point, or have been specified by the user, 14

and do not appear in the correlation matrix ) 15

16

Beta(3) 17

Beta(3) 1 18

19

20

Parameter Estimates 21

22

95.0% Wald Confidence Interval 23

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 24

Background 0 * * * 25

Beta(1) 0 * * * 26

Beta(2) 0 * * * 27

Beta(3) 2.08088e

- 011 * * * 28

29

*

- Indicates that this value is not calcula ted. 30

31

32

33

Analysis of Deviance Table 34

35

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 36

Full model

- 12.2039 4 37

Fitted model

- 12.2078 1 0.00783284 3 0.9998 38

Reduced model

- 17.5756 1 10.7433 3 0.0132 39

40

AIC: 26.4156 41

42

43

Goodness of Fit 44

Scaled 45

Dose Est._Prob. Expected Observed Size Residual 46

------------------------------------------------------------------------ 47

0.0000 0.0000 0.000 0.000 106 0.000 48

14.0000 0.0000 0.000 0.000 110

- 0.003 49

121.0000 0.0000 0.004 0.000 106

- 0.063 50

1307.0000 0.0454 2.996 3.000 66 0.002 51

52

Chi^2 = 0.00 d.f. = 3 P

- value = 0.9999 53

54

55

Benchmark Dose Computa tion 56

57

Specified effect = 0.1 58

Risk Type = Extra risk 59

Confidence level = 0.95 60

BMD = 1717.16 61

BMDL = 1306.29 62

BMDU = 8354.46 63

64

Taken together, (1306.29, 8354.46) is a 90% two

- sided confidence interval for the BMD 65

66D

- 57

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Multistage Cancer Slope Factor = 7.65529e

- 005 1

D.7.2. Nasal Cavity Squamous Cell Carcinoma and Liver Hepatocellular Adenoma in

Osborne

- Mendel Rats ( NCI, 1978 )

The incidence data for hepatocellular adenoma (female rats) and nasal squamous cell 2

carcinoma (male and female rats) are presented in Table D

- 20. The log

- logistic model 3

adeq uately fit both the male and female rat nasal squamous cell carcinoma data, as well as 4

female hepatocellular adenoma incidence data. For all endpoints and genders evaluated in this 5

section, compared to the multistage models, the log

- logistic model had a h igher p

- value, as well 6

as both a lower AIC and lower BMDL. The results of the BMDS modeling for the entire suite of 7

models are presented in Tables D

- 21 through D

- 23. 8

Table D

- 20. Incidence of nasal cavity squamous cell carcinoma and

hepatocellular adenoma in Osborne

- Mendel rats ( NCI, 1978 ) exposed to

1,4

- dioxane in the drinking water

Male rat Animal Dose (mg/kg

- day) a

0 240 b 530

Nasal cavity squamous cell carcinoma 0/33 c 12/26 d 16/33 d

Female rat Animal Dose (mg/kg

- day) a

0 350 640

Nasal cavity squamous cell carcinoma 0/34 c 10/30 d 8/29 d

Hepatocellular adenoma 0/31 c 10/30 d 11/29 d

a Tumor incidence values were adjusted for mortality ( NCI, 1978 )

. b Group not included in statistical analysis by NCI ( 1978 ) because the dose group was started a year earlier

without approp riate controls.

c p ≤ 0.001; positive dose

- related trend (Cochran

- Armitage test).

d p ≤ 0.001; Fisher‘s Exact test.

Source: NCI ( 1978 )

.D

- 58

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 21. BMDS dose

- response modeling results for the incidence of

hepatocellular adenoma in female Osborne

- Mendel rats ( NCI, 1978 ) exposed

to 1,4

- dioxane in the drinking water for 2 years

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogLogistic b 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

- 59

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

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.

================================================= =================== 1

Logistic Model. (Version: 2.12; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_nci_frat_hepato_ad_Lnl

- BMR10

- 3

Restrict.(d) 4

Gnuplot Plotting File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_nci_frat_hepato_ad_Lnl

5

BM R10

- Restrict.plt 6

Tue Oct 27 07:32:13 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 12

13

Dependent variable = Effect 14

Independent variable = Dose 15

Slope parameter is restricted as slope >= 1 16

17

Total number of observations = 3 18

Total number of records with missing values = 0 19

Maximum number of iterations = 250 20

Relative Function Convergence has been set to: 1e

- 008 21

Parameter Convergence has been set to: 1e

- 008 22

23

User has chosen the log transformed model 24

25

Default Initial Parameter Values 26

background = 0 27

intercept =

- 6.62889 28

s lope = 1 29D

- 60

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

Asymptotic Correlation Matrix of Parameter Estimates 2

3

( *** The model parameter(s)

- background

- slope have been estimated at a boundary 4

point, or have been specified by the user, and do not appear in the correlation 5

matrix) 6

7

intercept 8

intercept 1 9

10

Parameter Estimates 11

12

95.0% Wald Confidence Interval 13

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

background 0 * * * 15

intercept

- 6.91086 * * * 16

slope 1 * * * 17

18

*

- Indicates that this value is not calculated. 19

20

21

Analysis of Deviance Table 22

23

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 24

Full model

- 40.8343 3 25

Fitted model

- 41.141 1 0.613564 2 0.7358 26

Re duced model

- 50.4308 1 19.1932 2 <.0001 27

28

AIC: 84.2821 29

30

31

Goodness of Fit 32

Scaled 33

Dose Est._Prob. Expected Observed Size Residual 34

------------------------------------------------------------------------ 35

0.0000 0.0000 0.000 0.000 31 0.000 36

350.0000 0.2587 8.536 10.000 33 0.582 37

640.0000 0.3895 12.464 11.000 32

- 0.531 38

39

Chi^2 = 0.62 d.f. = 2 P

- value = 0.7333 40

41

42

Benchmark Dose Computation 43

44

Specified effect = 0.1 45

Risk Type = Extra r isk 46

Confidence level = 0.95 47

BMD = 111.457 48

BMDL = 72.4092 49D

- 61

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1 978 )

.

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.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_frat_hepato_ad_Msc

- BMR10

- 3

1poly.(d) 4

Gnuplot Plotting File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_frat_hepato_ad_Msc

5

BMR10

- 1poly.plt 6

T ue Oct 27 07:32:16 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

13

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 14

15

The parameter betas are restricted to be positive 16

17

Dependent variable = Effect 18

Independent variable = Dose 19

20

Total number of observations = 3 21

Total number of records with missing values = 0 22

Total number of parameters in model = 2 23

Total number of specified parameters = 0 24

Degree of polynomial = 1 25

26

Maximum number of iterations = 250 27

Relative Function Convergence has been set to: 1e

- 008 28

Parameter Convergence has been set to: 1e

- 008 29

30D

- 62

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

Default Initial Paramete r Values 2

Background = 0.0385912 3

Beta(1) = 0.000670869 4

Asymptotic Correlation Matrix of Parameter Estimates 5

6

( *** The model parameter(s)

- Background have been estimated at a boundary point, or 7

have been specified by the user, and do not appear in the correlation matrix) 8

9

Beta(1) 10

Beta(1) 1 11

12

13

14

Parameter Estimates 15

16

95.0% Wald Confidence Interval 17

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Lim it 18

Background 0 * * * 19

Beta(1) 0.00079602 * * * 20

21

*

- Indicates that this value is not calculated. 22

23

24

25

Analysis of Deviance Tab le 26

27

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 28

Full model

- 40.8343 3 29

Fitted model

- 41.3486 1 1.02868 2 0.5979 30

Reduced model

- 50.4308 1 19.1932 2 <.0001 31

32

AIC: 84.6972 33

34

35

Goodness of Fit 36

Scaled 37

Dose Est._Prob. Expected Observed Size Residual 38

------------------------------------------------------------------------ 39

0.0000 0.0000 0.000 0.000 31 0.000 40

350.0000 0.2432 8.024 10.000 33 0.802 41

640.0000 0.3992 12.774 11.000 32

- 0.640 42

43

Chi^2 = 1.05 d.f. = 2 P

- value = 0.5908 44

45

46

Benchmark Dose Computation 47

48

Specified effect = 0.1 49

Risk Type = Extra risk 50

Confidence level = 0.95 51

BMD = 132.359 52

BMDL = 94.0591 53

BMDU = 194.33 54

55

Taken together, (94.0591, 194.33 ) is a 90% two

- sided confidence interval for the BMD 56

57

Multistage Cancer Slope Factor = 0.00106316 58D

- 63

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 22. BMDS dose

- response modeling results for the incidence of nasal

cavity squamous cell carcinoma in female Osborne

- Mendel rats ( NCI, 1978 )

exposed to 1,4

- diox ane in the drinking water for 2 years

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogLogistic b 84.2235 0.2486 155.32 100.08 0 40.07 25.82

LogProbit c 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

- 64

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 19 78 )

.

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.

==================================================================== 1

Logistic Mod el. (Version: 2.12; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_nci_frat_nasal_car_Lnl

- BMR10

- 3

Restrict.(d) 4

Gnuplot Plotting File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_nci_frat_nasal_car_Lnl

5

BMR10

- Restrict.plt 6

Tue Oct 27 07:30:09 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

13

P[response] = background+(1

- background)/ [1+EXP(

- intercept

- slope*Log(dose))] 14

15

16

Dependent variable = Effect 17

Independent variable = Dose 18

Slope parameter is restricted as slope >= 1 19

20

Total number of observations = 3 21

Total number of records with missing values = 0 22

Maximum number of iterations = 250 23

R elative Function Convergence has been set to: 1e

- 008 24

Parameter Convergence has been set to: 1e

- 008 25

26

27D

- 65

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE User has chosen the log transformed model 1

2

3

Default Initial Parameter Values 4

background = 0 5

intercept =

- 6.64005 6

slope = 1 7

8

9

Asymptotic Correlation Matrix of Parameter Estimates 10

( *** The model parameter(s)

- background

- slope have been estimated at a boundary 11

point, or have been specified by the user, and do not appear in the correlation 12

matrix) 13

14

intercept 15

intercept 1 16

17

18

Parameter Estimates 19

20

95.0% Wald Confidence Interval 21

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22

background 0 * * * 23

intercept

- 7.24274 * * * 24

slope 1 * * * 25

26

*

- Indicates that this value is not calculated. 27

28

Analysis of Deviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 39.7535 3 32

Fitted model

- 41.1117 1 2.71651 2 0.2571 33

Reduced model

- 47. 9161 1 16.3252 2 0.0002851 34

35

AIC: 84.2235 36

37

Goodness of Fit 38

Scaled 39

Dose Est._Prob. Expected Observed Size Residual 40

------------------------------------------------------------------------ 41

0.0000 0.0000 0.000 0.000 34 0.000 42

350.0000 0.2002 7.008 10.000 35 1.264 43

640.0000 0.3140 10.992 8.000 35

- 1.090 44

45

Chi^2 = 2.78 d.f. = 2 P

- value = 0.2486 46

47

48

Benchmark Dose Computation 49

50

Specified effect = 0.1 51

Risk Type = Extra r isk 52

Confidence level = 0.95 53

BMD = 155.324 54

BMDL = 100.081 55D

- 66

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 197 8 )

.

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.

==================================================================== 1

Mul tistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_frat_nasal_car_Msc

- BMR10

- 3

1poly.(d) 4

Gnuplot Plotting File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_frat_nasal_car_Msc

5

BMR10

- 1poly.plt 6

Tue Oct 27 07:30:12 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- backgr ound)*[1

- EXP(

- beta1*dose^1)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

18

Total number of observations = 3 19

Total number of records with missing values = 0 20

Total number of parameters in model = 2 21

Total number of specified parameters = 0 22

Degree of polynomial = 1 23

24

Maximum number of iterations = 250 25

Relative Function Convergence has been set to: 1e

- 008 26

Parameter Convergence has been set to: 1e

- 008 27

28D

- 67

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial Parameter Values 1

Background = 0.0569154 2

Beta(1) = 0.00042443 3

4

Asymptotic Correlation Matrix of Parameter Estimates 5

( *** The model parameter(s)

- Background have been estimated at a boundary point, or 6

have been specified by the user, and do not appear in the correlation matrix) 7

8

Beta(1) 9

Beta(1) 1 10

11

Parameter Estimates 12

13

95.0% Wald Confidence Interval 14

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 15

Background 0 * * * 16

Beta(1) 0.000597685 * * * 17

18

*

- Indicates that this value is not calculated. 19

20

Analysis of Deviance Table 21

22

Model Log (likelihood) # Param's Deviance Test d.f. P

- value 23

Full model

- 39.7535 3 24

Fitted model

- 41.3998 1 3.29259 2 0.1928 25

Reduced model

- 47.9161 1 16.3252 2 0.0002851 26

27

AIC: 84.7996 28

29

Goodness of Fit 30

Scaled 31

Dose Est._Prob. Expected Observed Size Residual 32

----------------------- ------------------------------------------------- 33

0.0000 0.0000 0.000 0.000 34 0.000 34

350.0000 0.1888 6.607 10.000 35 1.466 35

640.0000 0.3179 11.125 8.000 35

- 1.134 36

37

Chi^2 = 3.44 d.f. = 2 P

- value = 0.1795 38

39

Benchmark Dose Computation 40

Specified effect = 0.1 41

Risk Type = Extra risk 42

Confidence level = 0. 95 43

BMD = 176.281 44

BMDL = 122.274 45

BMDU = 271.474 46

47

Taken together, (122.274, 271.474) is a 90% two

- sided confidence interval for the BMD 48

49

Multistage Cancer Slope Factor = 0.000817837 50D

- 68

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 23. BMD S dose

- response modeling results for the incidence of nasal

cavity squamous cell carcinoma in male Osborne

- Mendel rats ( NCI, 1978 )

exposed to 1,4

- dioxane in the drinking water for 2 years

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogLogistic b 92.7669 0.7809 56.26 37.26 0 16.10 10.66

LogProbit c 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

- 69

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

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.

==================================================================== 1

Logistic Model. (Version: 2.12; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ lnl_nci_mrat_nasal_car_Lnl

- BMR10

- 3

Restrict.(d) 4

Gnuplot Plotting File: L: \ Priv \ NCEA_ HPAG \ 14Dioxane \ BMDS \ lnl_nci_mrat_nasal_car_Lnl

5

BMR10

- Restrict.plt 6

Tue Oct 27 07:27:57 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 13

14

Dependent variable = Effect 15

Independent variable = Dose 16

Slope parameter is restricted as slope >= 1 17

18

Total number of observations = 3 19

Tot al number of records with missing values = 0 20

Maximum number of iterations = 250 21

Relative Function Convergence has been set to: 1e

- 008 22

Parameter Convergence has been set to: 1e

- 008 23

24

User has chosen the log transformed model 25

26D

- 70

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial Parameter Values 1

background = 0 2

intercept =

- 6.08408 3

slope = 1 4

5

Asymptotic Correlation Matrix of Parameter Estimates 6

( *** The model parameter(s)

- background

- slope have been estimated at a boundary 7

point, or have been specified by the user, and do n ot appear in the correlation 8

matrix) 9

10

intercept 11

intercept 1 12

13

Parameter Estimates 14

15

95.0% Wald Confidence Interval 16

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 17

background 0 * * * 18

intercept

- 6.2272 * * * 19

slope 1 * * * 20

21

*

- Ind icates that this value is not calculated. 22

23

Analysis of Deviance Table 24

25

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 26

Full model

- 45.139 3 27

Fitted model

- 45.3835 1 0.488858 2 0.7832 28

Reduced model

- 59.2953 1 28.3126 2 <.0001 29

30

AIC: 92.7669 31

32

Goodness of Fit 33

Sc aled 34

Dose Est._Prob. Expected Observed Size Residual 35

------------------------------------------------------------------------ 36

0.0000 0.0000 0.000 0.000 33 0.000 37

240.0000 0.3216 10. 612 12.000 33 0.517 38

530.0000 0.5114 17.388 16.000 34

- 0.476 39

40

Chi^2 = 0.49 d.f. = 2 P

- value = 0.7809 41

Benchmark Dose Computation 42

43

Specified effect = 0.1 44

Risk Type = Extra risk 45

Confidence level = 0.95 46

BMD = 56.2596 47

BMDL = 37.256 48D

- 71

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

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.

======================================= ============================= 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_mrat_nasal_car_Msc

- BMR10

- 3

1poly.(d) 4

Gnuplot Plotting File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_mrat_nasal_car_Msc

5

BMR10

- 1poly.plt 6

Tue Oct 27 07:28:00 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

18

Total number of observations = 3 19

Total number of records with missing values = 0 20

Total number of parameters in model = 2 21

Total number of specified parameters = 0 22

Degree of polynomial = 1 23

24

Maximum number of iterations = 250 25

Relative Function Convergence has been set to: 1e

- 008 26

Parameter Convergence has been set to: 1e

- 008 27

Default Initial Parameter Values 28D

- 72

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Background = 0.0578996 1

Beta(1) = 0.00118058 2

3

Asymptotic Correlation Matrix of Parameter Estimates 4

( *** The model parameter(s)

- Background have been estimated at a boundary point, or 5

have been specified by the user, and do not appear in the correlation matrix) 6

7

Beta(1) 8

Beta(1) 1 9

10

Parameter Estimates 11

12

95.0% Wald Confidence Interval 13

Variable Estim ate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

Background 0 * * * 15

Beta(1) 0.00142499 * * * 16

17

*

- Indicates that this value is not calculated. 18

19

Analysis of Deviance Table 20

21

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 22

Full model

- 45.139 3 23

Fitted model

- 45.8002 1 1.32238 2 0 .5162 24

Reduced model

- 59.2953 1 28.3126 2 <.0001 25

26

AIC: 93.6005 27

28

Goodness of Fit 29

Scaled 30

Dose Est._Prob. Expected Observed Size Residual 31

------------------------------------------------------------------------ 32

0.0000 0.0000 0.000 0.000 33

- 0.000 33

240.0000 0.2896 9.558 12.000 33 0.937 34

530.0000 0.5301 18.024 16.000 34

- 0.695 35

36

Chi^2 = 1.36 d.f. = 2 P

- value = 0.5063 37

38

Benchmark Dose Computation 39

Specified effect = 0.1 40

Risk Type = Extra risk 41

Confidence level = 0.95 42

BMD = 73.9379 43

BMDL = 54.7238 44

BMDU = 103.07 45

46

Taken together, (54.7238, 103.07 ) is a 90% two

- sided confidence interval for the BMD 47

48

Multistage Cancer Slope Factor = 0.00182736 49D

- 73

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE D.7.3. Hepatocellular Adenoma or Carcinoma in B6C3F 1 Mice ( NCI, 1978 )

The incidence data for hepatocellular ad enoma or carcinoma in male and female 1

mice are presented in Table D

- 24. The 2

- degree polynomial model (betas restricted ≥ 0) 2

was the lowest degree polynomial that provided an adequate fit to the female mouse data 3

( Figure D

- 25), while the gamma model pro vided the best fit to the male mouse data 4

( Figure D

- 26). The results of the BMDS modeling for the entire suite of models are 5

presented in Tables D

- 25 and D

- 26 for the female and male data, respectively. 6

Table D

- 24. Incidence of hepatocellular adenoma or carcinoma in male and

female B6C3F 1 mice ( NCI, 1978 ) exposed to 1,4

- dioxane in drinking water

Male mouse Animal Dos e (mg/kg

- day) a Female mouse Animal Dose (mg/kg

- day) a

0 720 830 0 380 860

8/49 b 19/50 d 28/47 c 0/50 b 21/48 c 35/37 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 )

.D

- 74

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 25. BMDS dose

- response modeling results for the combined

incidence of hepatocellular adenoma or carcinoma in female B6C3F 1 mice

( NCI, 1978 ) exposed to 1,4

- dioxane in the drinking water for 2 years

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 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

LogProbit b 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

- 75

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

Figure D

- 25. Multistage BMD model (2 d egree) for the incidence of

hepatocellular adenoma or carcinoma in female B6C3F 1 mice exposed to

1,4

- dioxane in drinking water.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_fmouse_hepato_adcar_Msc

3

BMR10

- 2poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_fmouse_hepato_adcar_Msc

- BMR10

- 2poly.plt 6

Tue Oct 27 07:36:26 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~ 10

11

The form of the probability function is: 12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

19

Total number of ob servations = 3 20

Total number of records with missing values = 0 21

Total number of parameters in model = 3 22

Total number of specified parameters = 0 23

Degree of polynomial = 2 24

25

26

Maximum number of iterations = 250 27

Relative Function Convergence has been set to: 1e

- 008 28D

- 76

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Parameter Convergence has been set to: 1e

- 008 1

2

Default Initial Parameter Values 3

Background = 0 4

Beta(1) = 2.68591e

- 005 5

Beta(2) = 3.91383e

- 006 6

7

8

Asymptotic Correlation Matrix of Parameter Estimates 9

( *** The model parameter(s)

- Background have been estimated at a boundary point, or 10

have been specified by the user, and do not appear in the correlation matrix) 11

12

Beta(1) Beta(2) 13

Beta(1) 1

- 0.92 14

Beta(2)

- 0.92 1 15

16

17

Parameter Estimates 18

19

95.0% Wald Confidence Interval 20

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 21

Background 0 * * * 22

Beta(1) 2.686e

- 005 * * * 23

Beta(2) 3.91382e

- 006 * * * 24

25

*

- Indicates that this value is not calculated. 26

27

28

Analysis of Deviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 40.6756 3 32

Fitted model

- 40.6756 2 3.20014e

- 010 1 1 33

Reduced model

- 91.606 1 101.861 2 <.0001 34

35

AIC: 85.3511 36

37

Goodness of Fit 38

Scaled 39

Dose Est._ Prob. Expected Observed Size Residual 40

------------------------------------------------------------------------ 41

0.0000 0.0000 0.000 0.000 50 0.000 42

380.0000 0.4375 21.000 21.000 4 8 0.000 43

860.0000 0.9459 35.000 35.000 37 0.000 44

45

Chi^2 = 0.00 d.f. = 1 P

- value = 1.0000 46

47

48

Benchmark Dose Computation 49

Specified effect = 0.1 50

Risk Type = Extra risk 51

Confidence leve l = 0.95 52

BMD = 160.678 53

BMDL = 67.7635 54

BMDU = 186.587 55

56

Taken together, (67.7635, 186.587) is a 90% two

- sided confidence interval for the BMD 57

58

Multistage Cancer Slope Factor = 0.00147572 59D

- 77

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table D

- 26. BMDS dose

- response modeling results for the combined

incidence of hepatocellular adenoma or carcinoma in male B6C3F 1 mice

( NCI, 1978 ) exposed to 1,4

- dioxane in drinking water

Model AIC p

- value BMD 10 mg/kg

- day BMDL 10

mg/kg

- day χ 2a BMD 10 HED mg/kg

- day BMDL 10 HED

mg/kg

- day

Gamma

b 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 NC c 622.39 283.04 0 91.01 41.39

LogProbit d 179.443 NC c 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 NC c 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

- 78

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

Figure D

- 26. Gamma BMD model for the incidence of hepatocellular

adenoma or carcinoma in male B6C3F 1 mice exposed to 1,4

- dioxane in

drinking water.

==================================================================== 1

Gamma Model. (Version: 2.13; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ gam_nci_mmouse_hepato_adcar_Gam

3

BMR10

- Restrict.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ gam_nci_mmouse_hepato_adcar_Gam

- BMR10

- Restrict.plt 6

Tue Oct 27 07:34:35 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~ 10

11

The form of the probability function is: 12

P[response]= background+(1

- background)*CumGamma[slope*dose,power], 13

where CumGamma(.) is the cummulative Gamma distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Power paramete r is restricted as power >=1 18

19

Total number of observations = 3 20

Total number of records with missing values = 0 21

Maximum number of iterations = 250 22

Relative Function Convergence has been set to: 1e

- 008 23

Parameter Convergence has been set to: 1e

- 008 24

25

Default I nitial (and Specified) Parameter Values 26

Background = 0.17 27

Slope = 0.000671886 28

Power = 1.3 29

30D

- 79

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlation Matrix of Parameter Estimates 1

( *** The model parameter(s)

- Power have been estimated at a boundary point, or h ave 2

been specified by the user, and do not appear in the correlation matrix) 3

4

Background Slope 5

Background 1

- 0.52 6

Slope

- 0.52 1 7

8

Parameter Estimates 9

95.0% Wald Confidence Interval 10

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 11

Background 0.160326 0.0510618 0.060247 0.260405 12

Slope 0.0213093 0.000971596 0.019405 0.0232136 13

Power 18 NA 14

15

NA

- Indicates that this parameter has hit a bound implied by some inequality 16

constraint and thus has no standard error. 17

18

Analysis of Deviance Table 19

20

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 21

Full model

- 86.7213 3 22

Fitted model

- 86.7693 2 0.096042 1 0.7566 23

Reduced model

- 96.715 1 19.9875 2 <.0001 24

25

AIC: 177.539 26

27

Goodness of Fit 28

Scaled 29

Dose Est._Prob. Expect ed Observed Size Residual 30

------------------------------------------------------------------------ 31

0.0000 0.1603 7.856 8.000 49 0.056 32

720.0000 0.3961 19.806 19.000 50

- 0.233 33

830.0000 0.5817 27.339 28.000 47 0.196 34

35

Chi^2 = 0.10 d.f. = 1 P

- value = 0.7571 36

Benchmark Dose Computation 37

Specified effect = 0.1 38

Risk Type = Extra risk 39

Confidence level = 0.95 40

BMD = 601.692 41

BMDL = 243.917 42D

- 80

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Source: NCI ( 1978 )

.

Figure D

- 27. Multistage BMD mode l (2 degree) for the incidence of

hepatocellular adenoma or carcinoma in male B6C3F 1 mice exposed to

1,4

- dioxane in drinking water

.

==================================================================== 1

Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 2

Input Data File: L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_mmouse_hepato_adcar_Msc

3

BMR10

- 2poly.(d) 4

Gnuplot Plotting File: 5

L: \ Priv \ NCEA_HPAG \ 14Dioxane \ BMDS \ msc_nci_mmouse_hepato_adcar_Msc

- BMR10

- 2 poly.plt 6

Tue Oct 27 07:34:42 2009 7

==================================================================== 8

BMDS Model Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: P[response] = backgroun d + (1

- background)*[1

- 12

EXP(

- beta1*dose^1

- beta2*dose^2)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

19

Total number of observations = 3 20

Total number of records with missing values = 0 21

Total number of parameters in model = 3 22

Total number of specified parameters = 0 23

Degree of polynomial = 2 24

Maximum number of iterations = 250 25

Relative Function Convergence has been set to: 1e

- 008 26

Parameter Convergence has been set to: 1e

- 008 27D

- 81

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Default Initial Param eter Values 1

Background = 0.131156 2

Beta(1) = 0 3

Beta(2) = 9.44437e

- 007 4

5

Asymptotic Correlation Matrix of Parameter Estimates 6

( *** The model parameter(s)

- Beta(1) have been estimated at a boundary point, or have 7

been specified by the user , and do not appear in the correlation matrix) 8

9

Background Beta(2) 10

Background 1

- 0.72 11

Beta(2)

- 0.72 1 12

13

14

Parameter Estimates 15

16

95.0% Wald Confidence Int erval 17

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 18

Background 0.1568 * * * 19

Beta(1) 0 * * * 20

Beta(2) 8.38821e

- 007 * * * 21

22

*

- Indicates that this value is not calculated. 23

24

25

26

Analysis of Deviance Table 27

28

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 29

Full mode l

- 86.7213 3 30

Fitted model

- 87.7413 2 2.04001 1 0.1532 31

Reduced model

- 96.715 1 19.9875 2 <.0001 32

33

AIC: 179.483 34

35

36

Go odness of Fit 37

Scaled 38

Dose Est._Prob. Expected Observed Size Residual 39

------------------------------------------------------------------------ 40

0.0000 0.15 68 7.683 8.000 49 0.124 41

720.0000 0.4541 22.707 19.000 50

- 1.053 42

830.0000 0.5269 24.764 28.000 47 0.946 43

44

Chi^2 = 2.02 d.f. = 1 P

- value = 0.1554 45

46

47

Benchmark Dose Computation 48

49

Specified effect = 0.1 50

Risk Type = Extra risk 51

Confidence level = 0.95 52

BMD = 354.409 53

BMDL = 126.241 54

BMDU = 447.476 55

56

Taken together, (1 26.241, 447.476) is a 90% two

- sided confidence interval for the BMD 57

58

Multistage Cancer Slope Factor = 0.000792138 59E

- 1

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX E. COMPARISON OF SEVERAL DATA REPORTS FOR THE J BRC

2

- Y EAR 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

, 1

the JBRC conducted a 2

- year drinking water study on the effects of 1,4

- dioxane in both sexes of 2

rats and mice. The results from this study have been reported three times, once as conference 3

proceedings ( Yamazaki, et al., 1994 ) , once as a detailed laboratory report ( JBRC, 1998 ) , and 4

once as a published manuscript ( Kano, et al., 2009 ) . After the External Peer Review draft of the 5

Toxic ological Review of 1,4

- Dioxane ( U.S. EPA, 2009b ) had been released, the Kano et al. 6

( 2009 ) manuscript was published; thus, minor changes to the Toxicological Review of 7

1,4

- Dioxane occurred. 8

The purpose of this appendix is to provide a clear and transparent comparison of the 9

reporting of this 2

- year 1,4

- dioxane drinking water study. The variations included: (1) the level 10

of detail on dose information reported; (2) categories for incidence dat a reported (e.g., all 11

animals or sacrificed animals); and (3) analysis of non

- and neoplastic lesions. Even though the 12

data contained in the reports varied, the differences were minor and did not did not significantly 13

affect the qualitative or quantitativ e cancer assessment

. 14

Tables contained within this appendix provide a comparison of the variations in the 15

reported data ( JBRC, 1998 ; K ano, et al., 2009 ; Yamazaki, et al., 1994 ) . Tables E

- 1 and E

- 2 16

show the histological nonneoplastic findings provided for male and female F344 rats, 17

respectively. Tables E

- 3 and E

- 4 show the histological neoplasti c findings provided for male 18

and female F344 rats, respectively. Tables E

- 5 and E

- 6 show the histological nonneoplastic 19

findings provided for male and female F344 rats, respectively. Tables E

- 7 and E

- 8 show the 20

histological neoplastic findings provided for male and female Crj: BDF 1 mice, respectively. 21

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

(Health and Environmental Research Onli ne) 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 A ssessments (ISA)

and the Integrated Risk Information System (IRIS)E

- 2

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table E

- 1. N onneoplastic 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

N asal respiratory epithelium ;

n uclear enlargement All animals Not reported 0/50 0/50 0/50 26/50 0/50 0/50 0/50 26/50 e

Sacrificed

animals Not reported 0/40 0/45 0/35 12/2 2 e Not reported

Nasal respiratory epithelium;

s quamous cell metaplasia All animals 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50 e

Sacrificed

animals Not reported 0/40 0/45 0/35 15/22 e Not reported

Nasal respiratory epithelium;

s quamous cell hyperplasia 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

Sacrificed

animals Not reported 0/40 0/45 0/35 1/22 Not reported

Nasal gland;

p roliferation All animals 0/50 0/50 0/50 5/50 Not reported Not reported

Sacrificed

animals Not reported Not reported Not reported

Nasal olfactory epithelium;

n uclear enlargement All animals Not reported 0/50 0/50 5/50 38/50 0/50 0/50 5/50 38/50 e

Sacrificed

animals Not reported 0/40 0/45 4/35 20/22 e Not reported

Nasal olfactory epithelium;

r espiratory metaplasia All animals Not reported 12/50 11/50 20/50 43/50 Not reported

Sacrificed

animals Not reported 10/40 11/45 17/35 22/22 e Not reported

N asal olfactory epithelium ; atrophy All animals Not reported 0/50 0/50 0/50 36/50 Not reported

Sacrificed

animals Not reported 0/40 0/45 0/35 17/22 e Not reported

L amina propria ; hydropic change All animals Not reported 0/50 0/50 0/50 46/50 Not reported

Sacrificed

animals Not reported 0/40 0/45 0/35 20/22 e Not reported

L amina propria ; sclerosis All animals Not reported 0/50 0/50 1/50 44/50 Not reported

Sacrificed

animals Not reported 0/40 0/45 1/35 20/22 e Not reported

N asal cavity ; adhesion All animals Not reported 0/50 0/50 0/50 48/50 Not reported

Sacrificed

animals Not reported 0/40 0/45 0/35 21/22 e Not reported

N asal cavity ; inflammation All animals Not reported 0/50 0/50 0/50 13/50 Not reported

Sacrificed

animals Not reported 0/40 0/45 0/35 7/22 e Not reported

Hyperplasia;

liver All animals 3/50 2/10 10/50 24/50 3/50 2/50 10/50 24/50 Not reported

Sacrificed

animals Not reported 3/40 2/45 9/35f 12/22 e Not reportedE

- 3

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Yamazaki et al. (1994) a JBRC (1998) Kano et al. (2009)

Spongiosis hepatis; liver All animals 12/50 20/50 25/50 40/50 12/50 20/50 25/50 40/50 Not reported

Sacrificed

animals Not reported 12/40 20/45 21/35 f 21/22 e Not reported

Clear cell foci;

liver All animals Not reported 3/50 3/50 9/50 8/50 3/50 3/50 9/50 8/50

Sacrificed

animals Not reported 3/40 3/45 9/35 f 7/22 e Not reported

Acidophilic cell foci; liver All animals Not reported Not reported 12/50 8/50 7/50 5/50

Sac rificed

animals Not reported Not reported Not reported

Basophilic cell foci; liver All animals Not reported 7/50 11/50 6/50 16/50 7/50 11/50 8/50 16/50 f

Sacrificed

animals Not reported 7/40 11/45 6/35 8/22 f Not reported

Mixed

- cell foci;

liver All animals Not reported 2/50 8/50 14/50 13/50 2/50 8/50 14/50e 13/50 e

Sacrificed

animals Not reported 2/40 8/45 14/35 e 22/22 e Not reported

Nuclear enlargement; kidney proximal

tubule All animals Not reported 0/50 0/50 0/50 50/50 Not reported

Sacrificed

animals Not reported 0/40 0/45 0/35 22/22 e 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 ( 19 98 ) 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, 2009b )

.

c Kano et al. ( 2009 ) reported a mean intake dos e for each group ± standard deviation. The mean shown in this table was used in this

final document ( U.S. EPA, 2010 )

. 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. N onneoplastic 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

N asal respiratory epithelium ; nuclear enlargement All animals Not reported 0/50 0/50 0/50 13/50 0/50 0/50 0/50 13/50 e

Sacrificed

animals Not reported 0 /38 0/37 0/38 7/24 e Not reported

Nasal respiratory epithelium;

s quamous cell metaplasia All animals 0/50 0/50 0/50 35/50 0/50 0/50 0/50 35/50 0/50 0/50 0/50 35/50 e

Sacrificed

animals Not reported 0/38 0/37 0/38 18/24 e Not reported

N asal respiratory epithelium ; squamous cell hyperplasia 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

Sacrificed

animals Not reported 0/38 0/37 0/38 4/24 f Not reported

N asal gland ; All animals 0/50 0/50 0/50 11/50 0/50 0/50 0/50 11/50 Not reportedE

- 4

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

Yamazaki et al. (1994) a JBRC (1998) Kano et al. (2009)

proliferation Sacrificed

animals Not reported 0/38 0/37 0 /38 8/24 e Not reported

N asal olfactory epithelium ; nuclear enlargement All animals Not reported 0/50 0/50 28/50 39/50 0/50 0/50 28/50 e 39/50 e

Sacrificed

animals Not reported 0/38 0/37 24/38 e 22/24 e Not reported

N asal olfactory epithelium ; respiratory metaplasia All animals Not reported 2/50 0/50 2/50 42/50 Not reported

Sacrificed

animals Not reported 1/38 0/37 1/38 24/24 e Not reported

N asal olfactory epithelium ; atrophy All animals Not reported 0/50 0/50 1/50 40/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 1/38 22/24 e Not reported

Lam ina propria ; hydropic change All animals Not reported 0/50 0/50 0/50 46/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 0/38 23/24 e Not reported

L amina propria ; slerosis All animals Not reported 0/50 0/50 0/50 48/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 0/38 23/24 e Not reported

N asal cavity ; adhesion All animals Not reported 0/50 0/50 0/50 46/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 0/38 24/24 e Not reported

N asal cavity ; inflammation All animals Not reported 0/50 0/50 1/50 15/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 1/38 7/24 e Not reported

L iver ; hyperplasia All animals 3/50 2/50 11/50 47/50 3/50 2/50 11/50 47/50 Not reported

Sacrificed

animals Not reported 2/38 2/37 9/38 24/24 e Not reported

L iver ; spongiosis hepatis All animals 0/50 0/50 1/50 20/50 0/50 0/50 1/50 20/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 1/38 14/24 e Not reported

L iver ; cyst formation All animals Not reported 0/50 1/50 1/50 8/50 Not reported

Sacrificed

animals Not reported 0/38 1/37 0/38 5/24 f Not reported

L iver ; clear cell foci All animals Not reported Not reported 1/50 1/50 5/50 4/50

S acrificed

animals Not reported Not reported Not reported

L iver ; acidophilic

cell foci All animals Not reported Not reported 1/50 1/50 1/50 1/50

Sacrific ed

animals Not reported Not reported Not reported

Liver; basophilic

cell foci All animals Not reported Not reported 23/50 27/50 31/50 8/50 e

Sacrific ed

animals Not reported Not reported Not reported

Li ver ; mixed

- cell

foci All animals Not reported 1/50 1/50 3/50 11/50 1/50 1/50 3/50 11/50 f

Sacrificed

animals Not reported 1/38 1/37 3/38 7/24 f Not reported

K idney proximal

tubule ; nuclear enlargement All animals Not reported 0/50 0/50 6/50 39/50 Not reported

Sacrificed

animals Not reported 0/38 0/37 6/38 22/24 e Not reportedE

- 5

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

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 gro ups. Statistical test results were not reported.

b JBRC ( 1998 ) 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, 2009b )

.

c Kano et al. ( 2009 ) 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 )

. 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. N eoplastic 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

Squamous cell carcinoma All

animals 0/50 0/50 0/50 3/50 0/50 0/50 0/50 3/50 e 0/50 0/50 0/50 3/50 e

Sacrificed

animals Not reported Not reported Not reported

Sarcoma NOS 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

Sacrificed

animals Not reported Not reported Not reported

Rabdomyosarcoma 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

Sacrificed

animals Not reported Not reported Not reported

Esthesioneuroepithelioma 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

Sacrificed

animals Not reported Not reported Not reported

Liver

Hepatocellular adenoma All

animals 0/50 2/50 4/50 24/50 0/50 2/50 4/49 24/50 d,e 3/50 4/50 7/50 32/50 d,e

Sacrificed

animals Not reported Not reported Not reported

Hepatocellular carcinoma All

animals 0/50 0/50 0/50 14/50 0/50 0/50 0/49 14/50 d,e 0/50 0/50 0/50 14/50 d,e

Sacrificed

animals Not reported Not reported Not reportedE

- 6

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

Yamazaki et al. (1994) a JBRC (1998) Kano et al. (2009)

Hepatocellular adenoma

or carcinoma All

animals Not reported 0/50 2/50 4/49 33/50 d,e 3/50 4/50 7/50 39/50 d,e

Sacrificed

animals Not reported Not reported Not reported

Tumors at other sites

Peritoneum

mesothelioma All

animals 2/50 2/50 5/50 28/50 2/50 2/50 5/50 28/50 d,e 2/50 2/50 5/50 28/50 d,e

Sacrificed

animals Not reported Not reported Not reported

Subcutis fibroma All

animals 5/50 3/50 5/50 12/50 5/50 3/50 5/50 12/50 e 5/50 3/50 5/50 12/50 e

Sacrificed

animals Not reported Not reported Not reported

Mammary gland

fibroadenoma All

animals 1/50 1/50 0/50 4/50 1/50 1/50 0/50 4/50 e 1/50 1/50 0/50 4/50 e

Sacrificed

animals Not reported Not reported Not reported

Mammary gland

adenoma All

animals 0/50 0/50 0/50 0/50 Not reported 0/50 1/50 2/50 2/50

Sacrificed

animals Not reported Not reported Not reported

Mammary gland

fibroadenoma

or adenoma All

animals Not reported Not reported 1/50 2/50 2/50 6/50 e

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 ) 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, 2009b )

.

c Kano et al. ( 2009 ) 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 )

. d p ≤ 0.01 by Fisher's Exact test.

e Significantly increased by Peto test for trend p < 0.01.

Table E

- 4. N eoplastic 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

Squamous cell

carcinoma All animals 0/50 0/50 0/50 7/50 0/50 0/50 0/50 7/50 d,f 0/50 0/50 0/50 7/50 e,f

Sacrificed

animals Not reported Not reported Not reportedE

- 7

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

Yamazaki et al. (1994) a JBRC (1998) Kano et al. (2009)

Sarcoma NO S 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

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

ma 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

Sacrificed

animals Not reported Not reported Not reported

Liver

Hepatocellular

adenoma All animals 1/50 0/50 5/50 38/50 1/50 0/50 5/50 38/50 e,f 3/50 1/50 6/50 48/50 e,f

Sacrificed

animals Not reported Not reported Not reported

Hepatocellular

carcinoma All animals 0/50 0/50 0/50 10/50 1/50 0/50 0/50 10/50 e,f 0/50 0/50 0/50 10/50 e,f

Sacrificed

animals Not reported Not reported Not reported

Hepatocellular

adenoma or carcinoma All animals Not reported 1/50 0/50 5/50 40/50 e,f 3/50 1/50 6/50 48/50 e,f

Sacrificed

animals Not reported Not reported Not reported

Tumors at other sites

Peritoneum

mesothelioma All animals 1/50 0/50 0/50 0/50 Not reported 1/50 0/50 0/50 0/50

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

fibroadenoma All animals 3/50 2/50 1/50 3/50 Not reported 3/50 2/50 1/50 3/50

Sacrificed

animals Not reported Not reported Not reported

Mammary gland

adenoma All animals 6/50 7/50 10/50 16/50 6/50 7/50 10/50 16/50 d,f 6/50 7/50 10/50 16/50 d,f

Sacrificed

animals Not reported Not reported Not reported

Mammary gland

fibroadenoma

or adenoma All animals Not reported Not reported 8/50 8/50 11/50 18/50 d,f

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 ) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in

parentheses) was used in the exter nal peer review draft of this document ( U.S. EPA, 2009b )

.

c Kano et al. ( 2009 ) 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 )

. 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

- 8

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table E

- 5. N onneoplastic lesions: Comparison of histological findings

reported for the 2

- year JBRC drinking water study in male Crj: BDF 1 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

N asal respiratory epithelium ; nuclear enlargement All

animals Not reported 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50 e

Sacrificed

animals Not reported 0/31 0/33 0/25 19/26 e Not reported

N asal olfactory epithelium ; nuclear enlargement All

animals Not reported 0/50 0/50 9/50 49/50 0/50 0/50 9/50 e 49/50 e

Sacrificed

animals Not reported 0/31 0/33 7/25 e 26/26 e Not reported

N asal olfactory epithelium ; atrophy All

animals Not reported 0/50 0/50 1/50 48/50 Not reported

Sacrificed

animals Not reported 0/31 0/33 0/25 26/26 e Not reported

N asal cavity ; inflammation All

animals Not reported 1/50 2/50 1/50 25/50 Not reported

Sacrificed

animals Not reported 1/31 1/33 1/25 15/26 e Not reported

T racheal epithelium ; atrophy All

animals Not reported 0/50 0/50 0/50 42/50 Not reported

Sacrificed

animal s Not reported 0/31 0/33 0/25 24/26 e Not reported

T racheal epithelium ; nuclear enlargement All

animals Not reported 0/50 0/50 0/50 17/50 Not reported

Sacrificed

animals Not reported 0/31 0/33 0/25 12/26 e Not reported

B ronhcial epithelium ; nuclear enlargement All

animals Not reported 0/50 0/50 0/50 41/50 Not reported

Sacrificed

animals Not reported 0/31 0/33 0/25 24/26 e Not reported

B ronchial epithelium ; atrophy All

animals Not reported 0/50 0/50 0/50 43/50 Not reported

Sacrificed

animals Not reported 0/31 0/33 0/25 26/26 e Not reported

L ung/bronchial ; accumlation of foamy cells All

animals Not reported 1/50 0/50 0/50 27/50 Not reported

Sacrificed

an imals Not reported 1/31 0/33 0/25 22/26 e Not reported

Liver ; angiectasis All

animals Not reported 2/50 3/50 4/50 16/50 Not reported

Sacrificed

animals Not reported 2/31 2/33 3/25 8/26 f Not reportedE

- 9

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

Yamazaki et al. (1994) JBRC (1998) d Kano et al. (2009)

K idney proximal tubule ; nuclear enlargement All

animals Not reported 0/50 0/50 0/50 39/50 Not reported

Sacrificed

animals Not reported 0/31 0/33 0/25 22/26 e Not reported

T estis ; mineralization All

animals Not reported 40/50 42/50 38/50 34/50 Not reported

Sacrificed

animals Not reported 28/31 30/33 24/25 f 21/26 f 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 ) 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, 2009b )

.

c Kano et al. ( 2009 ) 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 )

. 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.

1E

- 10

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table E

- 6. Nonneoplastic lesions: Comparison of histological findings

reported for the 2

- year JBRC drinking water study in female Crj: BDF 1 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

Nasal respiratory epithelium; Nuclear enlargement All animals Not reported 0/50 0/50 0/50 41/50 0/50 0/50 0/50 41/50 e

Sacrificed

animals Not reported 0/29 0/29 0/17 5/5 e Not reported

Nasal olfactory epithelium; Nuclear enlargement All animals Not reported 0/50 0/50 41/50 33/50 0/50 0/50 41/50 e 33/50 e

Sacrificed

animals Not reported 0/29 0/29 17/17 e 1/5 Not reported

Nasal respiratory epithelium; Atrophy All animals Not reported 0/50 0/50 0/50 26/50 Not reported

Sacrificed

animals Not reported 0/29 0/29 0/17 1/5 Not reported

Nasal olfactory epithelium; Atrophy All animals Not reported 0/50 0/50 1/50 42/50 Not reported

Sacrificed

animals Not reported 0/29 0/29 0/17 5/5 e Not reported

Nasal cavity;

Inflammation All animals Not reported 2/50 0/50 7/50 42/50 Not reported

Sacrificed

animals Not reported 0/29 0/29 5/17 e 5/5 e Not reported

Tracheal epithelium; Atrophy All animals Not reported 0/50 0/50 2/50 49/50 Not reported

Sacrificed

animals Not reported 0/29 0/29 1/17 5/5 e Not reported

Bronhcial epithelium; Nuclear enlargement All animals Not reported 0/50 1/50 22/50 48/50 Not reported

Sacrificed

animals Not reported 0/29 1/29 13/17 e 5/5 e Not reported

Bronchial epithelium; Atrophy All animals Not reported 0/50 0/50 7/50 50/50 Not reported

Sacrificed

animals Not reported 0/29 0/29 3/17 5/5 e Not reported

Lung/bronchial;

Accumlation of foamy cells All animals Not reported 0/50 1/50 4/50 45/50 Not reported

Sacrificed

animals Not reported 0/29 1/29 3/17 5/5 e Not reported

Kidney proximal tubule; Nuclear enlargement All animals Not reported 0/50 0/50 0/50 8/50 Not reported

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 ) . 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 ) report.

c JBRC ( 1998 ) 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, 2009b )

. d Kano et al. ( 2009 ) 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 )

.

e p ≤ 0.01 by chi

- square test.E

- 11

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table E

- 7. N eoplastic lesions: C omparison of histological findings reported

for the 2

- year JBRC drinking water study in male Crj: BDF 1 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 r eported Control

0 37

- 94 (66) 144

- 358 (251) 451

- 1086 (768) 0 49±5 191±21 677±74

Nasal cavity

Esthesioneuroepithelioma 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

Sacrificed

animals Not reported Not reported Not reported

Adenocarcinoma 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

Liver

Hepatocellular adenomas All Animals 7/50 16/50 22/50 8/50 7/50 16/50 22/50 e 8/50 9/50 17/50 23/50 e 11/50

Sacrificed

animals Not reported Not reported Not reported

Hepatocellular carcinomas All Animals 15/50 20/50 23/50 36/50 15/50 20/50 23/50 36/50 d,e 15/50 20/50 23/50 36/50 e,f

Sacrificed

animals Not reported Not reported Not reported

Either adenoma

or carcinoma All Animals Not reported 21/50 31/50 37/50 39/50 d,e 23/50 31/50 37/50 d 40/50 e,f

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 ) reported an estimated chemical intake range (of doses) for the animals; and the midpoint of the range (shown in

parentheses) was used in the exter nal peer review draft of this document ( U.S. EPA, 2009b )

.

c Kano et al. ( 2009 ) 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 )

. 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.

1F

- 12

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table E

- 8. Neoplastic lesions: Comparison of histological findings reported

for the 2

- year JBRC drinking water study in female Crj: BDF 1 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

Esthesioneruoepithelioma 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

Adenocarcinoma 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

Sacrificed

animals Not reported Not reported Not reported

Liver

Hepatocellular adenomas All animals 4/50 30/50 20/50 2/50 4/50 30/50 d 20/50 d 2/50 e 5/50 31/50 d 20/50 d 3/50

Sacrificed

animals Not reported Not reported Not reported

Hepatocellular carcinomas All animals 0/50 6/50 30/50 45/50 0/50 6/50 f 30/50 d 45/50 d,g 0/50 6/50 f 30/50 d 45/50 d,g

Sacrificed

animals Not reported Not reported Not reported

Either adenoma

or carcinoma All animals Not reported 4/50 34/50 d 41/50 d 46/50 d,g 5/50 35/50 d 41/50 d 46/50 d,g

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 (ppm) of 1,4

- dioxane were used to

identify the dose groups. Statistical test results were not reported.

b JBRC ( 1998 ) 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, 2009b )

.

c Kano et al. ( 2009 ) 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, 20 10 )

. 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 < 0.01F

- 13

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX F. DETAILS OF BMD ANALYSIS FOR INHALATION RfC FOR

1,4

- DIOXANE

F.1. CENTRILOBULAR NECROS IS OF THE LIVER

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 1

fit to the incidence data shown in Table F

- 1, for centrilobular necrosis of the liver in male 2

F344/DuCrj rats exposed to 1,4

- d ioxane vapors for 2 years ( Kasai, et al., 2009 ) . Doses 3

associated with a BMR of a 10% extra risk were calculated. 4

Table F

- 1. Incidence of centrilobular necrosis of the liver in F344/DuCrj rats

exposed to 1,4

- dioxane via inhalation for 2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

1/50

(2%) 3/50

(6%) 6/50

(12%) 12/50 a

(24%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

. 5

As assessed by the χ 2 goodness

- of

- fit test, several models in the software provided 6

adequate fits to the incidence data of centrilobular necrosis of the liver in male rats (χ 2 p ≥ 0.1) 7

(Table F

- 2). Comparing across adequately fitting models, the BMDL estimates were not within 8

threefold difference of each other. Therefore, i n accordance with EPA BMD technical guidance 9

( U.S. EPA, 2000a ) , the adequately fitting model that resulted in the lowest BMDL was selected 10

as appropriate for derivin g a POD which was the Dichotomous

- Hill model. BMDS modeling 11

results for all dichotomous models are shown in Table F

- 2 and the model plot (Figure F

- 1) and 12

output for the selected Dichotomous

- Hill model l are included immediately after the table. 13

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 Scie nce Assessments (ISA)

and the Integrated Risk Information System (IRIS)F

- 14

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 2. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for centrilobular necrosis of the liver in male

F344/DuCrj rats exposed to 1,4

- dioxane vapors ( Kasai, et al., 2009 )

.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 129.692 0.5099 0.786 502.444 308.113

Logistic 131.043 0.2794

- 0.142 794.87 609.269

Log

- logistic c 129.465 0.568 0.676 453.169 258.687

Log

- probit c 132.067 0.1645

- 0.175 801.17 539.489

Multistage

(2 degree) d 129.692 0.5099 0.786 502.445 308.112

Probit 130.889 0.2992

- 0.167 756.192 567.169

Weibull b 129.692 0.5099 0.786 502.461 308.113

Quantal

- Linear 129.692 0.5099 0.786 502.461 308.113

Dichotomous

Hill c, e 130.404 0.7459

- 0.179 219.51 59.5598

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 Bold indicates best

- fit model based on lowest BMDL.

Source: Kasai et al. ( 2009 )

.F

- 15

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure F

- 1. BMD Dichotomous Hill model of centrilobular necrosis

incidence data for male rats exposed to 1,4

- dioxane vapors for 2 years to

support the results in Table F

- 2.

==================================================================== 1

Dichotomous Hill Model. (Version: 1.2; Date: 12/11/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/dhl_Centr_necrosis_liver_Dhl

- BMR10

- Restrict.(d) 4

Gn uplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/dhl_Centr_necrosis_liver_Dhl

- BMR10

- Restrict.plt 6

Wed Jan 12 16:34:41 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = v*g +(v

- v*g)/[1+EXP(

- intercept

- slope*Log(dose))] 13

where: 0 <= g < 1, 0 < v <= 1 14

v is the maximum probability of response predicted by the model, 15

and v*g is the background estimate of that probability. 16

17

Dependent variable = Effect 18

Independent variable = Dose 19

Slope parameter is restricted as slope >= 1 20

21

Total number of observations = 4 22

Total number of records with missing values = 0 23

Maximum number of iterations = 250 24

Relative Function Convergence has been set to: 1e

- 008 25

Parameter Convergence has been set to: 1e

- 008 26

27

Default Initial Parameter Values 28

v =

- 9999 29

g =

- 9999 30

intercept =

- 8.08245 31

slope = 1 32

33

34F

- 16

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlati on Matrix of Parameter Estimates 1

(*** The model parameter(s)

– slope have been estimated at a boundary point, or have 2

been specified by the user, and do not appear in the correlation matrix) 3

4

v g intercept 5

v 1

- 0.25

- 0.89 6

g

- 0.25 1 0.016 7

intercept

- 0.89 0.016 1 8

9

10

Parameter Estimates 11

12

95.0% Wald Confidence Interval 13

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

v 0.311077 0.156196 0.00493876 0.617216 15

g 0.0709966 0.0662298

- 0.0588115 0.200805 16

intercept

- 6.06188 1.34538

- 8.69878

- 3.42498 17

slope 1 NA 18

19

NA

- Indicates that this parameter has hi t a bound implied by some inequality 20

constraint and thus has no standard error. 21

22

23

Analysis of Deviance Table 24

25

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 26

Full model

- 62.1506 4 27

F itted model

- 62.2022 3 0.103279 1 0.7479 28

Reduced model

- 69.3031 1 14.305 3 0.002518 29

30

AIC: 130.404 31

32

Goodness of Fit 33

Scaled 34

Dose Est._Prob. Expected Observed Size Residual 35

------------------------------------------------------------------------ 36

0.0000 0.0221 1.104 1.000 50

- 0.100 37

50.0000 0.0522 2.612 3.000 50 0.247 38

250.0000 0.1285 6.423 6.000 50

- 0.179 39

1250.0000 0.2372 11.861 12.000 50 0.046 40

41

Chi^2 = 0.10 d.f. = 1 P

- value = 0.7459 42

43

44

Benchmark Dose Computation 45

Specified effect = 0.1 46

Risk Type = Extra risk 47

Confidence level = 0.95 48

BMD = 219.51 49

BMDL = 59.5598 50

F.2. S PONGIOSIS HEPATIS

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 51

fit to the incidence data shown in Table F

- 3, for spongiosis hepatis of the liver in male 52

F344/DuCrj rats exposed to 1,4

- dioxane vapors for 2 years ( Kasai, et al., 2009 )

. Doses 53

associated with a BMR of a 10% extra risk were calculated. 54F

- 17

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 3. Incidence of spongiosis hepatis of the liver in F344/DuCrj rats

exposed to 1,4

- dioxane via inhalation for 2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

7/50

(14%) 6/50

(12%) 13/50

(26%) 19/50 a

(38%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

As assessed by the χ 2 goodness

- of

- fit test, several models in the software provided 1

adequate fits to the incidence data of spongiosis of the liver in male rats (χ 2 p ≥ 0.1) (Table F

- 4). 2

BMDL estimates for all adequately fitting models were not within threefold difference of each other 3

( U.S. EPA, 2000a ) . Therefore, i n accordance with EPA BMD technical guidance ( U.S. EPA, 4

2000a ) , the adequately fitting model that resulted in the lowest BMDL was selected as 5

appropriate for deriving a POD which was the Dichotomous

- Hill model. However, the 6

Dichotomous

- Hi ll model, warned that the BMDL estimate was ―imprecise at best‖ (see Figure F

7

2 and subsequent textual model output). Comparing across all models (excluding the 8

dichotomous

- hill model), a better fit is indicated by a lower AIC value since the BMDL estimat es 9

for all appropriately fitting models were within threefold difference of each other ( U.S. EPA, 10

2000a ) . As assessed by the AIC, the log

- logistic model provided the best fit to the spongiosis 11

incidence data for male rats (Table F

- 4, Figure F

- 3and subsequent textual model output) and 12

could be used to derive a POD for this endpoint. 13

Table F

- 4. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for spongiosis hepatis of the liver in male

F344/DuCrj rats ( NCI, 1978 ) exposed to 1,4

- dioxane vapors.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 206.472 0.4482 1.031 369.422 224.993

Logistic 207.141 0.3159 1.242 537.295 392.318

Log

- logistic c, f 206.229 0.5102 0.912 314.34 172.092

Log

- probit c 208.147 0.1825 1.536 633.557 414.718

Multistage

(2 degree) d 206.472 0.4482 1.031 369.422 224.993

Probit 207.06 0.3292 1.223 515.483 371.644

Weibull b 206.472 0.4482 1.031 369.422 224.993

Quantal

- Linear 206.472 0.4482 1.031 369.422 224.993

Dichotomous

Hill c, e 206.364 0.4671 1.031 289.919 59.69F

- 18

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 Model output warned that the BMDL estimate was ―impre cise at best‖.

f Bold indicates best

- fit model based on lowest AIC.

Source: Kasai et al. ( 2009 )

.

1

Figure F

- 2. BMD Dichotomous

- Hill model of spongiosis hepatis incidence

data for male rats exposed to 1,4

- dioxane vapors for 2 years to support the

results in Table F

- 4.

==================================================================== 2

Dichotomous Hill Model. (Version: 1.2; Date: 12/11/2009) 3

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 4

files/dhl_spong_hepa_liver_Dhl

- BMR10

- Restrict.(d) 5

Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 6

files/dhl_spong_hepa_liver_Dhl

- BMR10

- Restrict.plt 7

Wed Jan 12 16:52:46 2011 8

==================================================================== 9

BMDS_Model_Run 10

~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 11

The form of the probability function is: 12

13

P[response] = v*g +(v

- v*g)/[1+EXP(

- intercept

- slope*Log(dose))] 14

where: 0 <= g < 1, 0 < v <= 1 15

v is the maximum probability of response p redicted by the model, 16

and v*g is the background estimate of that probability. 17

18

Dependent variable = Effect 19

Independent variable = Dose 20

Slope parameter is restricted as slope >= 1 21

22

Total number of observations = 4 23F

- 19

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Total number of records with missing values = 0 1

Maximum number of iterations = 250 2

Relative Function Convergence has been set to: 1e

- 008 3

Parameter Convergence has been set to: 1e

- 008 4

5

Default Initial Parameter Values 6

v =

- 9999 7

g =

- 9999 8

intercept =

- 8.74962 9

slope = 1.13892 10

11

Asymptotic Correlation Matrix of Parameter Estimates 12

(** * The model parameter(s)

- v

- slope have been estimated at a boundary point, or have 13

been specified by the user, and do not appear in the correlation matrix ) 14

15

g intercept 16

g 1

- 0.53 17

intercept

- 0.53 1 18

19

Parameter Estimates 20

21

95.0% Wald Confidence Interval 22

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23

v 1 NA 24

g 0.125 0.0332679 0.0597961 0.190204 25

intercept

- 7.86683 0.396424

- 8.6438

- 7.08985 26

slope 1 NA 27

28

NA

- Indicat es that this parameter has hit a bound implied by some inequality 29

constraint and thus has no standard error. 30

31

Analysis of Deviance Table 32

33

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 34

Full model

- 100.45 4 35

Fitted model

- 101.182 2 1.46273 2 0.4813 36

Reduced model

- 106.633 1 12.3646 3 0.006233 37

38

AIC: 206.364 39

40

Goodness of Fit 41

Scaled 42

Dose Est._Prob. Expected Observed Size Residual 43

------------------------------------------------------------------------ 44

0 .0000 0.1250 6.250 7.000 50 0.321 45

50.0000 0.1415 7.073 6.000 50

- 0.435 46

250.0000 0.2015 10.075 13.000 50 1.031 47

1250.0000 0.4084 20.420 19.000 50

- 0.409 48

49

Chi^2 = 1.52 d.f. = 2 P

- value = 0.4671 50

51

52

Benchmark Dose Computation 53

Specified effect = 0.1 54

Risk Type = Extra risk 55

Confidence level = 0.95 56

BMD = 289.919 57

58

Warning: BMDL computation is at best imprecise for these data 59

BMDL = 59.69 60

61

62F

- 20

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure F

- 3. BMD Log

- Logistic model of spongiosis hepatis incidence data for

male rats exposed to 1,4

- dioxane vapors for 2 years to support the results in

Table F

- 4.

==================================================================== 1

Logistic Model. (Version: 2.13; Date: 10/28/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/lnl_spong_hepa_liver_Lnl

- BMR10

- Restrict.(d) 4

Gn uplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/lnl_spong_hepa_liver_Lnl

- BMR10

- Restrict.plt 6

Wed Jan 12 16:52:44 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

T he form of the probability function is: 11

12

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 13

14

Dependent variable = Effect 15

Independent variable = Dose 16

Slope paramete r is restricted as slope >= 1 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Maximum number of iterations = 250 21

Relative Function Convergence has been set to: 1e

- 008 22

Parameter Convergence has been set to: 1 e

- 008 23

24

User has chosen the log transformed model 25

26

Default Initial Parameter Values 27

background = 0.14 28

intercept =

- 8.74962 29

slope = 1.13892 30

31F

- 21

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Asymptotic Correlation Matrix of Parameter Estimates 1

(*** The model parameter(s)

- slope have been estimated at a boundary point, or have 2

been specified by the user, and do not appear in the correlation matrix) 3

4

background interce pt 5

background 1

- 0.54 6

intercept

- 0.54 1 7

8

Parameter Estimates 9

95.0% Wald Confidence Interval 10

Variable Estimate Std. Er r. Lower Conf. Limit Upper Conf. Limit 11

background 0.13769 * * * 12

intercept

- 7.9477 * * * 13

slope 1 * * * 14

15

*

- Indicates that this value is not calculated. 16

17

18

Analysis of Deviance Table 19

20

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 21

Full model

- 100.45 4 22

Fitted mode l

- 101.115 2 1.3283 2 0.5147 23

Reduced model

- 106.633 1 12.3646 3 0.006233 24

25

AIC: 206.229 26

27

28

Goodness of Fit 29

Scaled 30

Dose Est._Prob. Expected Observed Size Residual 31

------------------------------------------------------------------------ 32

0.0000 0.1377 6.885 7.000 50 0.047 33

50.0000 0.1527 7.633 6.000 50

- 0.642 34

250.0000 0.2077 10.385 13.000 50 0.912 35

1250.0000 0.4019 20.097 19.000 50

- 0.316 36

37

Chi^2 = 1.35 d.f. = 2 P

- value = 0.5102 38

39

40

Benchmark Dose Computation 41

Specified effect = 0.1 42

Risk Type = Extra risk 43

Confidence level = 0.95 44

BMD = 314.34 45

BMDL = 172.092 46

F.3. SQUAMOU S CELL METAPLASIA

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 47

fit to the incidence data shown in Table F

- 5, for squamous cell metaplasia of the respiratory 48

epithelium in male F344/DuCrj rats exposed to 1,4

- dioxane v apors for 2 years ( NCI, 1978 )

. 49

Doses associated with a BMR of a 10% extra risk were calculated. 50F

- 22

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 5. Incide nce of squamous cell metaplasia of the respiratory

epithelium in F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for

2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

0/50 0/50 7/50 b

(14%) 44/50 a

(88%)

a p≤ 0.01 by Fisher‘s exact test.

b p≤ 0.05 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

For incidence of squamous cell metaplasia in F344/DuCrj male rats, the logistic and 1

probit models all exhibited a statistically significant lack of fit (i.e., 2 p

- value < 0.1; see 2

Table F

- 6), and thus should not be considered further for identification of a POD. All of the 3

remaining models exhibited adequate fit. The BMDL estimates for all appropriately fitting models 4

were within threefold difference of each other, indica ting that BMDL selection should be made based 5

on model fit ( U.S. EPA, 2000a ) . As assessed by the AIC, the Log

- probit model provided the best 6

fit to the squamous cell metaplasia data for male rats (Table F

- 6, Figure F

- 4 ), and could be used 7

to derive a POD for th is endpoint. 8

Table F

- 6. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for squamous cell metaplasia of the respiratory

epithelium in male F344/DuCrj rats exposed to 1,4

- dioxane vapors ( Kasai, et

al., 2009 )

.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 81.687 0.8682 0.24 218.38 150.329

Logistic 89.4148 0.0464 1.806 370.443 288.535

Log

- logistic c 81.5252 0.9142 0.131 218.218 158.293

Log

- probit c, e 81.23 0.9894 0.032 217.79 159.619

Multistage

(2 degree) d 82.6875 0.6188 0.605 231.294 141.025

Probit 87.9361 0.0779 1.681 337.732 268.424

Weibull b 82.1236 0.7679 0.33 218.435 145.383

Quantal

- Linear 92.9215 0.0198

- 1.76 87.682 68.8015

Dichotomous

Hill c 83.1888 0.9995 0 240.867 161.945F

- 23

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 Bold indicates best

- fit model based on lowest AIC.

Source: Kasai et al. ( 2009 )

.

Figure F

- 4. BMD Log

- probit model of squamous cell metaplasia of the

respiratory epithelium incidence data for male rats exposed to 1,4

- dioxane

vapors for 2 years to support the results in Table F

- 6.

==================================================================== 1

Probit Model. (Version: 3.2; Date: 10/28/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/lnp_squ_cell_meta_re_Lnp

- BMR10

- Restrict.(d) 4

Gnuplot Plottin g File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/lnp_squ_cell_meta_re_Lnp

- BMR10

- Restrict.plt 6

Thu Jan 13 13:11:09 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = Background + (1

- Background) * CumNorm(Intercept+Slope*Log(Dose)), 13

where CumNorm(.) is the cumulative normal distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is restricted as slope >= 1 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21F

- 24

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Maximum number of iterations = 250 1

Relative Function Convergence has been set to: 1e

- 008 2

Parameter Convergence has been set to: 1e

- 008 3

4

User has chosen the log transformed model 5

6

Default Initial (and Specified) Parameter Values 7

background = 0 8

intercept =

- 6.76507 9

slope = 1.09006 10

11

Asymptotic Correlation Matrix of Parameter Estimates 12

(*** The model parameter(s)

- background have been estimated at a boundary point, or 13

have been specified by the user, and do not appear in the correlation matrix) 14

15

intercept slope 16

intercept 1

- 0.99 17

slope

- 0.99 1 18

19

Parameter Estimates 20

21

95.0% Wald Confidence Interval 22

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23

background 0 NA 24

intercept

- 8.86173 1.2 226

- 11.258

- 6.46548 25

slope 1.40803 0.193057 1.02965 1.78642 26

27

NA

- Indicates that this parameter has hit a bound implied by some inequality 28

constraint and thus has no standard error. 29

30

Analysis of Deviance Table 31

32

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 33

Full model

- 38.5944 4 34

Fitted model

- 38.615 2 0.041197 2 0.9796 35

Reduced m odel

- 113.552 1 149.916 3 <.0001 36

37

AIC: 81.23 38

39

Goodness of Fit 40

Scaled 41

Dose Est._Prob. Ex pected Observed Size Residual 42

------------------------------------------------------------------------ 43

0.0000 0.0000 0.000 0.000 50 0.000 44

50.0000 0.0004 0.020 0.000 50

- 0. 141 45

250.0000 0.1384 6.922 7.000 50 0.032 46

1250.0000 0.8808 44.038 44.000 50

- 0.017 47

48

Chi^2 = 0.02 d.f. = 2 P

- value = 0.9894 49

50

51

Benchmark Dose Computation 52

Specified effect = 0.1 53

Risk Type = Extra risk 54

Confidence level = 0.95 55

BMD = 217.79 56

BMDL = 159.619 57

F.4. SQUAMOUS CELL HYPERP LASIA

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) wer e 58

fit to the incidence data shown in Table F

- 7, for squamous cell hyperplasia of the respiratory 59F

- 25

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE epithelium in male F344/DuCrj rats exposed to 1,4

- dioxane vapors for 2 years ( NCI, 1978 )

. 1

Doses associated with a BMR of a 10% extra risk were calculated. 2

Table F

- 7. Incidence of squamous cell hyperplasia of the respiratory

epithelium in F344/DuCrj rats exposed to 1,4

- dio xane via inhalation for

2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

0/50 0/50 1/50

(2%) 10/50 a

(20%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

For incidence of squamous cell hyperplasia in F344/DuCrj male rats, the logistic, probit, 3

and quantal

- linear models all exhibited a statistically significant lack of fit (i.e., 2 p

- value < 0.1; 4

see Table F

- 8 ), and thus should not be considered further for identification of a POD. All of the 5

remai ning models exhibited adequate fit. The BMDL estimates for all appropriately fitting models 6

were within threefold difference of each other, indicating that BMDL selection should be made based 7

on model fit ( U.S. EPA, 2000a ) . As assessed by the AIC, the Log

- probit model provided the best 8

fit to the squamous cell hyperplasia data for male rats (Table F

- 8, Figure F

- 5 and subsequent 9

textual model output), and could be used to derive a POD for this endpoint. 10

Table F

- 8. Goodn ess

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for squamous cell hyperplasia of the respiratory

epithelium in male F344/DuCrj rats exposed to 1,4

- dioxane vapors ( Kasai, et

al., 2009 )

.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 81.687 0.8682 0.24 218.38 150.329

Logistic 89.4148 0.0464 1.806 370.443 288.535

Log

- logistic c 81.5252 0.9142 0.131 218.218 158.293

Log

- probit c, e 81.23 0.9894 0.032 217.79 159.619

Multistage

(2 degree) d 82.6875 0.6188 0.605 231.294 141.025

Probit 87.9361 0.0779 1.681 337.732 268.424

Weibull b 82.1236 0.7679 0.33 218.435 145.383

Quantal

- Linear 92.9215 0.0198

- 1.76 87.682 68.8015

Dichotomous

Hill c 83.1888 0.9995 0 240.867 161.945F

- 26

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 Bold indicates best

- fit model based on lowest AIC.

Source: Kasai et al. ( 2009 )

.

Figure F

- 5. BMD Log

- probit model of squamous cell hyperplasia of the

respiratory epithelium incidence data for male rats exposed to 1,4

- dioxane

vapors for 2 years to support the results in Table F

- 8.

==================================================================== 1

Probit Model. (Version: 3.2; Date: 10/28/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/lnp_squ_cell_hyper_re_Lnp

- BMR10

- Restrict.(d) 4

Gnuplot Plotti ng File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/lnp_squ_cell_hyper_re_Lnp

- BMR10

- Restrict.plt 6

Thu Jan 13 13:25:05 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = Background + (1

- Background) * CumNorm(Intercept+Slope*Log(Dose)), 13

where CumNorm(.) is the cumulative normal distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Slope parameter is restricted as slope >= 1 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21F

- 27

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Maximum number of iterations = 250 1

Relative Function Convergence has been set to: 1e

- 008 2

Parameter Convergence has been set to: 1e

- 008 3

4

User has chosen the log transformed model 5

6

Default Initial (and Specified) Parameter Values 7

background = 0 8

intercept =

- 7.75604 9

slope = 1 10

11

Asymptotic Correlation Matrix of Parameter Estimates 12

(*** The model parameter(s)

- background

- slope have been estimated at a boundary 13

point, or have been spec ified by the user, and do not appear in the correlation 14

matrix) 15

16

intercept 17

intercept 1 18

19

Parameter Estimates 20

21

95.0% Wald Confidence Interval 22

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 23

background 0 NA 24

intercept

- 7.90911 0.186242

- 8.27414

- 7.54408 25

slope 1 NA 26

27

NA

- Indicates that this parameter has hit a bound implied by some inequality 28

constraint and thus has no standard error. 29

30

Analysis of Deviance Table 31

32

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 33

Full model

- 29.9221 4 34

Fitted model

- 30.2589 1 0.673572 3 0.8794 35

Reduced model

- 42.5964 1 25.3487 3 <.0001 36

37

AIC: 62.5177 38

39

Goodness of Fit 40

Scaled 41

Dose Est._Prob. Expected Observed Size Residual 42

------------------------------------------------------------------------ 43

0 .0000 0.0000 0.000 0.000 50 0.000 44

50.0000 0.0000 0.002 0.000 50

- 0.040 45

250.0000 0.0085 0.424 1.000 50 0.889 46

1250.0000 0.2182 10.911 10.000 50

- 0.312 47

48

Chi^2 = 0.89 d.f. = 3 P

- value = 0.8282 49

50

51

Benchmark Dose Computation 52

Specified effect = 0.1 53

Risk Type = Extra risk 54

Confidence level = 0.95 55

BMD = 755.635 56

BMDL = 560.86 57

F.5. RESPIRATORY METAPLAS IA

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 58

fit to the incidence data shown in Table F

- 9, for respiratory metaplasia of the olfactory 59F

- 28

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE epithelium in male F344 /DuCrj rats exposed to 1,4

- dioxane vapors for 2 years ( NCI, 1978 )

. 1

Doses associated with a BMR of a 10% extra risk were calculated. 2

Table F

- 9. Incidence of respiratory metaplasia of the olfactory epithelium in

F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

11/50

(22%) 34/50

(68%) 49/50 a

(98%) 48/50 a

(96%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

As assessed by the χ 2 goodness

- of

- fit test, no models in the software provided adequate 3

fits to the data for the incidence of respiratory metaplasia of the olfactory epithelium in male rats 4

(χ

2 p ≥ 0.1) (Table F

- 10). However, given that first non

- control dose had a response level 5

substantially above the desired BMR (i.e. 10%), the use of BMD methods included substantial 6

model uncertainty . The model uncertainty associated with this dataset is related to low

- dose 7

extrapolation and consistent with BMD technical guidance document (USEPA, 2000), all 8

available dichotomous models in the Benchmark Dose Software (version 2.1.2) were fit to the 9

incidence data shown in Table F

- 9 with the highest dose group omitted. As ass essed by the χ 2 10

goodness

- of

- fit test , the logistic, log

- logistic, log

- probit, and probit models all exhibited a 11

statistically significant lack of fit (i.e., 2 p

- value < 0.1;See Table F

- 11), and thus should not be 12

considered further for identification of a POD. The BMDL estimates for all appropriately fitting 13

models were within threefold difference of each other, indicating that BMDL selection should be 14

made based on model fit ( U.S. EPA, 2000a ) . The AIC values for gamma, multistage, quantal

15

linear, and Weibull models in Table F

- 11 are equivalent and the lowest and, in this case, 16

essentially represent the same model. Therefore, consistent with the external review draft 17

Benchmark Dose Technical Guidance ( U.S. EPA, 2000a ) , any of them with equal AIC values 18

(gamma, multistage, quantal

- linear, or Weibull) could be used to identify a POD for t his 19

endpoint. The model plot for the gamma model (Figure F

- 6) and output are included immediately 20

after the table. 21

22F

- 29

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 10. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for respiratory metaplasia of olfactory

epithelium in male F344/DuCrj rats ( Kasai, et al., 2009 ) exposed to

1,4

- dioxane vapors.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 179.68 0

- 2.07 17.4082 12.3829

Logistic 191.339 0 1.788 34.2946 24.5917

Log

- logistic c 152.72 0.0285 0.039 4.05465 1.90233

Log

- probit c 161.267 0

- 0.39 14.3669 10.3023

Multistage

(2 degree) d 179.68 0

- 2.07 17.4082 12.3829

Probit 198.785 0 1.479 61.4378 45.9091

Weibull b 179.68 0

- 2.07 17.4082 12.3829

Quantal

- Linear 179.68 0

- 2.07 17.4082 12.3829

Dichotomous

Hill c 150.466 NA 0 38.8552 31.4727

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: Kasai et al. ( 2009 )

.

Table F

- 11. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for respiratory metaplasia of olfactory

epithelium with high dose group dropped in male F344/DuCrj rats ( Kasai, et

al., 2009 ) exposed to 1,4

- dioxane vapors.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma b, e 129.463 0.5815

- 0.106 6.46848 4.73742

Logistic 133.583 0.0119

- 1.031 12.5197 9.34421

Log

- logistic c 131.182 NA 0 14.2075 3.77044

Log

- probit c 131.182 NA 0 12.2114 7.80131

Multistage

(2 degree) d, e 129.463 0.5815

- 0.106 6.46847 4.73742

Probit 136.121 0.0066

- 1.511 15.2883 11.6855

Weibull b 129.463 0.5815

- 0.106 6.46847 4.73742

Quantal

- Linear e 129.463 0.5815

- 0.106 6.46847 4.73742F

- 30

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 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 Bold indicates best

- fit models based on lowest AIC.

Source: Kasai et al. ( 2009 )

.

Figure F

- 6. BMD Gamma model of respiratory metaplasia of olfactory

epithelium incidence data for male rats exposed to 1,4

- dioxane vapors for 2

years to support the results in Table F

- 11.

==================================================================== 1

Gamma Model. (Version : 2.15; Date: 10/28/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/gam_resp_meta_no high dose_Gam

- BMR10

- Restrict.(d) 4

Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/gam_resp_meta_no high dose_Gam

- BMR10

- Restrict.plt 6

Thu Jan 13 16:24:15 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability functio n is: 11

12

P[response]= background+(1

- background)*CumGamma[slope*dose,power], 13

where CumGamma(.) is the cummulative Gamma distribution function 14

15

Dependent variable = Effect 16

Independent variable = Dose 17

Power parameter is restricted as power >=1 18

19

Total number of observations = 3 20

Total number of records with missing values = 0 21F

- 31

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Maximum number of iterations = 250 1

Relative Function Convergence has been set to: 1e

- 008 2

Parameter Convergence has been set to: 1e

- 008 3

4

Defaul t Initial (and Specified) Parameter Values 5

Background = 0.230769 6

Slope = 0.022439 7

Power = 1.3 8

9

Asymptotic Correlation Matrix of Parameter Estimates 10

( *** The model parameter(s)

- Power have been estimated at a boundary point, or have 11

been specified by the user, and do not appear in the correlation matrix) 12

13

Background Slope 14

Background 1

- 0.33 15

Slope

- 0.33 1 16

17

Parameter Estimates 18

19

95.0% Wald Confidence Interval 20

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 21

Background 0.226249 0.0588535 0.110898 0.3416 22

Slope 0.0162883 0.00320976 0.00999729 0.0225793 23

Power 1 NA 24

25

NA

- Indicates that this parameter has hit a bound implied by some inequality 26

constraint and thus has no standard error. 27

28

Analysis of Deviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 62.5908 3 32

Fitted model

- 62.7313 2 0.280907 1 0.5961 33

Reduced model

- 99.1059 1 73.0301 2 <.0001 34

35

AIC: 129.463 36

37

Goodness of Fit 38

Scaled 39

Dose Est._Prob. Expected Observed Size Residual 40

------------------------------------------------------------------------ 41

0.0000 0.2262 11.312 11.000 50

- 0.106 42

50.0000 0.6573 32.865 34.000 50 0.338 43

250.0000 0.9868 49.341 49.000 50

- 0.422 44

45

Chi^2 = 0.30 d.f. = 1 P

- value = 0.5815 46

47

Benchmark Dose Computation 48

Specified effect = 0.1 49

Risk Type = Extra risk 50

Confidence level = 0.95 51

BMD = 6.46848 52

BMDL = 4.73742 53

F.6. ATROPHY

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 54

fit to the incidence d ata shown in Table F

- 12, for atrophy of the olfactory epithelium in male 55

F344/DuCrj rats exposed to 1,4

- dioxane vapors for 2 years ( Kasai, et al., 2009 ) . Doses 56

associated with a BMR of a 10% extra risk were calculated. 57F

- 32

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 12. Incidence of respiratory metaplasia of the olfactory epithelium

i n F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

0/50 40/50 a

(80%) 47/50 a

(94%) 48/50 a

(96%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

As assessed by the χ 2 goodness

- of

- fit test, the gamma, logistic, log

- probit, multistage, 1

probit, Weibull, and quantal

- linear models all exhibited a statistically significant lack of fit (i.e., 2

2 p

- value < 0.1;See Table F

- 13), and thus should not be considered further for iden tification of a 3

POD. The BMDL estimates for all appropriately fitting models were within threefold difference of 4

each other, indicating that BMDL selection should be made based on model fit ( U.S. EPA, 2000a )

. 5

As assessed by the AIC, the Log

- logistic model provided the best fit to the atrophy data for male 6

rats (Table F

- 13, Figure F

- 7), and could be used to derive a POD for this endpoint. However, 7

given that first non

- control dose had a response level substa ntially above the desired BMR (i.e. 8

10%), the use of BMD methods included substantial model uncertainty. 9

Table F

- 13. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for atrophy of olfactory epithelium in male

F34 4/DuCrj rats ( Kasai, et al., 2009 ) exposed to 1,4

- dioxane vapors.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 159.444 0 0 9.93187 8.14152

Logistic 190.692 0 4.342 33.9373 25.4454

Log

- logistic c 93.9074 0.3023 0 1.67195 1.01633

Log

- probit c 117.337 0 0 9.42745 7.20318

Multistage

(2 degree) d 159.444 0 0 9.9319 8.14152

Probit 200.626 0 3.943 61.9146 47.107

Weibull b 159.444 0 0 9.9319 8.14152

Quantal

- Linear 159.444 0 0 9.9319 8.14152

Dichotomous

Hill c 95.5314 1 0 2.93951 0.544697

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 Bold indicates best

- fit model based on lowest AIC.

Source: Kasai et al. ( 2009 )

.F

- 33

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure F

- 7. BMD Log

- Logistic model of atrophy of olfactory epithelium

incidence data for male rats exposed to 1,4

- dioxane vapors for 2 years to

support the results in Table F

- 13.

==================================================================== 1

Logistic Model. (Version: 2.13; Date: 10/28/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/lnl_atrophy_Lnl

- BMR10

- Restrict.(d) 4

Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/lnl_atrophy_Lnl

- BMR10

- Restrict.plt 6

Fri Jan 14 09:53:22 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~ 10

11

The form of the probability function is: 12

P[response] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 13

14

Dependent variable = Effect 15

Independent variable = Dose 16

Slope parameter is restricted as slope >= 1 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Maximum number of iterations = 250 21

Relative Function Convergence has been set to: 1e

- 008 22

Parameter Convergence has been set to: 1e

- 008 23

24

User has chosen the log transformed model 25

26

Default Initial Parameter Values 27

background = 0 28

intercept =

- 3.48908 29

slope = 1 30

31

Asymptotic Correlation Matrix of Parameter Estimates 32F

- 34

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE (*** The model parameter(s)

- background

- slope have been estimated at a boundary 1

point, or have been specified by the user, and do not appear in the correlation 2

matrix) 3

4

intercep t 5

intercept 1 6

7

Parameter Estimates 8

95.0% Wald Confidence Interval 9

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 10

backg round 0 * * * 11

intercept

- 2.71122 * * * 12

slope 1 * * * 13

14

*

- Indicates that this value is not calculated. 15

16

Analysis of Deviance Table 17

18

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 19

Full model

- 44.7657 4 20

Fitted model

- 45.9537 1 2.37596 3 0.4981 21

Reduced model

- 126.116 1 162.701 3 <.0001 22

23

AIC: 93.9074 24

25

Goodness of Fit 26

Scaled 27

Dose Est._Prob. Expected Observed Size Residual 28

------------------------------------------------------------------------ 29

0.0000 0.0000 0.000 0.000 50 0.000 30

50.0000 0.7687 38.433 40.000 50 0.525 31

250.0000 0.9432 47.161 47.000 50

- 0.099 32

1250.0000 0.9881 49.405 48.000 50

- 1.833 33

34

Chi^2 = 3.65 d.f. = 3 P

- value = 0.3023 35

36

Benchmark Dose Computat ion 37

Specified effect = 0.1 38

Risk Type = Extra risk 39

Confidence level = 0.95 40

BMD = 1.67195 41

BMDL = 1.01633 42

F.7. HYPDROPIC CHANGE

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 43

fit to the incidence data shown in Table F

- 14, for hydropic change of the lamina propria in the 44

nasal cavity of male F344/DuCrj rats exposed to 1,4

- dioxane vapors for 2 years ( Kasai, et al., 45

2009 ) . Doses associated with a BMR of a 10% extra risk were calculated. 46

47F

- 35

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 14. Incidence of hydropic change of the lamina propria in the nasal

cavity of F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

0/50 2/50

(4%) 36/50 a

(72%) 49/50 a

(98%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al., ( 2009 )

.

For incidence of hydropic change of the lamina propria in F344/DuCrj male rats, the 1

gamma, logistic, multistage, probit, Weibull, and quantal

- linear models all exhibited a 2

statistically significant lack of fit (i.e., 2 p

- value < 0.1; see Table F

- 16), an d thus should not be 3

considered further for identification of a POD. The BMDL estimates for all appropriately fitting 4

models were within threefold difference of each other, indicating that BMDL selection should be 5

made based on model fit ( U.S. EPA, 2000a ) . As assessed by the AIC, the Log

- logisti c model 6

provided the best fit to the hydropic change of the lamina propria data for male rats (Table F

- 15, 7

Figure F

- 8 and subsequent text output), and could be used to derive a POD of for this endpoint. 8

Table F

- 15. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for hydropic change of the lamina propria in the

nasal cavity of male F344/DuCrj rats exposed to 1,4

- dioxane vapors ( Kasai,

et al., 2009 )

.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 98.3441 0.0002

- 1.321 51.979 28.7632

Logistic 117.957 0

- 1.143 89.2909 70.6131

Log

- logistic c 90.5388 0.6819

- 0.333 68.5266 46.7808

Log

- probit c 91.5881 0.3458

- 0.538 63.0852 44.5657

Multistage

(2 degree) d 99.3482 0.0256

- 2.411 28.7899 22.6831

Probit 136.585 0

- 2.099 92.6118 74.3784

Weibull b 100.225 0.0033

- 1.899 39.1371 23.9762

Quantal

- Linear 99.3482 0.0256

- 2.411 28.7899 22.6831

Dichotomous

Hill c 91.8937 1 0 73.1032 49.2687

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 Bold indicates best

- fit model based on lowest AIC.

Source: Kasai et al. ( 2009 )

.F

- 36

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure F

- 8. BMD Log

- logistic model of hydropic change of lamina propria

(nasal cavity) incidence data for male rats exposed to 1,4

- dioxane vapors for

2 years to support the results in Table F

- 16.

==================================================================== 1

Logist ic Model. (Version: 2.13; Date: 10/28/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/lnl_hydrpic_Lnl

- BMR10

- Restrict.(d) 4

Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/lnl_hydrpic_Lnl

- BMR1 0

- Restrict.plt 6

Fri Jan 14 10:30:47 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[r esponse] = background+(1

- background)/[1+EXP(

- intercept

- slope*Log(dose))] 12

13

Dependent variable = Effect 14

Independent variable = Dose 15

Slope parameter is restricted as slope >= 1 16

17

Total number of observations = 4 18

Total number of records with missing values = 0 19

Maximum number of iterations = 250 20

Relative Function Convergence has been set to: 1e

- 008 21

Parameter Convergence has been set to: 1e

- 008 22

23

User has chosen the log transformed model 24

25

Default Initial Parameter Values 26

background = 0 27

intercept =

- 11.5745 28

slope = 2.19638 29

30

Asymptotic Correlation Matrix of Parameter Estimates 31F

- 37

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE (*** The mo del parameter(s)

- background have been estimated at a boundary point, or 1

have been specified by the user, and do not appear in the correlation matrix) 2

3

intercept slope 4

intercept 1

- 0.99 5

slope

- 0.99 1 6

7

Parameter Estimates 8

9

95.0% Wald Confidence Interval 10

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 11

background 0 * * * 12

intercept

- 12.1316 * * * 13

slope 2.3501 * * * 14

15

*

- Indicates that this value is not calculated. 16

17

Analysis of Deviance Table 18

19

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 20

Full model

- 42.9468 4 21

Fitted model

- 43.2694 2 0.645129 2 0.7243 22

Red uced model

- 136.935 1 187.976 3 <.0001 23

24

AIC: 90.5388 25

26

Goodness of Fit 27

Scaled 28

Dose Est._Prob. Expected Observed Size Residual 29

------------------------------------------------------------------------ 30

0.0000 0.0000 0.000 0.000 50 0.000 31

50.0000 0.0503 2.515 2.000 50

- 0.333 32

250.0000 0.6994 34.969 36.000 50 0.318 33

1250.0000 0.9903 49.515 49.000 50

- 0.744 34

35

Chi^2 = 0.77 d.f. = 2 P

- value = 0.6819 36

37

38

Benchmark Dose Computation 39

Specified effect = 0.1 40

Risk Type = Extra risk 41

Confidence level = 0.95 42

BMD = 68.5266 43

BMDL = 46.7808 44

F.8. SCLEROSIS

All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 45

fit to t he incidence data shown in Table F

- 16, for sclerosis of the lamina propria in the nasal 46

cavity of male F344/DuCrj rats exposed to 1,4

- dioxane vapors for 2 years ( Kasai, et al., 2009 )

. 47

Doses associated with a BMR of a 10% extra risk were calculated. 48F

- 38

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table F

- 16. Incidence of sclerosis of the lamina propria in the nasal cavity of

F344/DuCrj rats exposed to 1,4

- dioxane via inhalation for 2 years.

1,4

- dioxane vapor concentration (ppm)

0 50 250 1

, 250

0/50 0/50 22/50 a

(44%) 40/50 a

(80%)

a p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. ( 2009 )

.

As assessed by the χ 2 goodness

- of

- fit test , all models with the exception of the 1

dichotomous

- hill model, exhibited a statistically significant lack of fit (i.e., 2 p

- value < 0.1;See 2

Table F

- 17), and thus should not be considered further for identification o f a POD. Since the 3

dichotomous

- hill model provided the only fit to the sclerosis of the lamina propria data for male 4

rats as assessed by the χ 2 goodness

- of

- fit test (Table F

- 17, Figure F

- 9 and subsequent text 5

output), it could be considered to derive a PO D for this endpoint; however, the model output 6

warned that the BMDL estimate was ―imprecise at best‖. 7

Table F

- 17. Goodness

- of

- fit statistics and BMD 10 and BMDL 10 values from

models fit to incidence data for sclerosis of the lamina propria in the nasal

c avity of male F344/DuCrj rats exposed to 1,4

- dioxane vapors ( Kasai, et al.,

2009 )

.

Model AIC p

- value a Scaled

Residual of

Interest BMD 10

(ppm) BMDL 10

(ppm)

Male

Gamma

b 134.416 0.0123

- 1.89 75.4489 57.6938

Logistic 161.562 0 4.542 244.217 196.446

Log

- logistic c 130.24 0.0683

- 1.579 86.3863 52.4762

Log

- probit c 127.784 0.0829

- 0.995 109.558 88.1232

Multistage

(2 degree) d 132.436 0.0356

- 1.949 71.9719 57.6471

Probit 159.896 0 4.619 231.856 191.419

Weibull b 132.436 0.0356

- 1.949 71.9719 57.6471

Quantal

- Linear 132.436 0.0356

- 1.949 71.9719 57.6471

Dichotomous

Hill c, e 124.633 0.9994 0 206.74 167.46

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 Model output warned that the BMDL estimate was ―impre cise at best‖.

Source: Kasai et al. ( 2009 )

.

8F

- 39

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ==================================================================== 1

Dichotomous Hill Model. (Version: 1.2; Date: 12/11/2009) 2

Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 3

files/dhl_sclerosis_Dhl

- BMR10

- Restrict.(d) 4

Gnuplot Plott ing File: C:/Documents and Settings/pgillesp/Desktop/BMDS 5

files/dhl_sclerosis_Dhl

- BMR10

- Restrict.plt 6

Fri Jan 14 10:53:28 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = v*g +(v

- v*g)/[1+EXP(

- intercept

- slope*Log(dose))] 12

where: 0 <= g < 1, 0 < v <= 1 13

v is the maximum probability of response predicted by th e model, 14

and v*g is the background estimate of that probability. 15

16

Dependent variable = Effect 17

Independent variable = Dose 18

Slope parameter is restricted as slope >= 1 19

20

Total number of observations = 4 21

Total number of records with missing values = 0 22

Maximum number of iterations = 250 23

Relative Function Convergence has been set to: 1e

- 008 24

Parameter Convergence has been set to: 1e

- 008 25

26

Default Initial Parameter Values 27

v =

- 9999 28

g =

- 9999 29

intercept =

- 11.4511 30

slope = 1.86444 31

32

Asymptotic Correlation Matrix of Parameter Estimates 33

(*** The m odel parameter(s)

- g have been estimated at a boundary point, or have been 34

specified by the user, and do not appear in the correlation matrix) 35

36

v intercept slope 37

v 1 0.00074

- 0.00078 38

intercept 0.00074 1

- 1 39

slope

- 0.00078

- 1 1 40

41

Parameter Estimates 42

43

95.0% Wald Confidence Interval 44

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 45

v 0.8 0.0565686 0.689128 0.910872 46

g 0 NA 47

intercept

- 62.1804 41 33.38

- 8163.46 8039.1 48

slope 11.2979 748.603

- 1455.94 1478.53 49

50

NA

- Indicates that this parameter has hit a bound implied by some inequality 51

constraint and thus has no standard error. 52

53

54

Analysis of Deviance Table 55

56

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 57

Full model

- 59.3166 4 58

Fitted model

- 59.3166 3 1.23973e

- 006 1 0.9991 59

Reduce d model

- 123.82 1 129.007 3 <.0001 60

61

AIC: 124.633 62

63

Goodness of Fit 64

Scaled 65

Dose Est._Prob. Expected Observed Size Residual 66F

- 40

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ------------------------------------------------------------------------ 1

0.0000 0.0000 0.000 0.000 50 0.000 2

50.0000 0.0000 0.000 0.000 50

- 0.001 3

250.0000 0.4400 22.000 22.000 50 0.000 4

1250.0000 0.8000 40.000 40.000 50

- 0.000 5

6

Chi^2 = 0.00 d.f. = 1 P

- value = 0.9994 7

8

Benchmark Dose Computation 9

Specified effect = 0.1 10

Risk Type = Extra risk 11

Confidence level = 0.95 12

BMD = 206.74 13

14

Warning: BMDL computation is at best imprecise for these data 15

BMDL = 167.46 16

Figure F

- 9. BMD Log

- logistic mo del of sclerosis of lamina propria (nasal

cavity) incidence data for male rats exposed to 1,4

- dioxane vapors for 2 years

to support the results in Table F

- 18.G

- 41

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE APPENDIX G. DETAILS OF BMD ANALYSIS FOR INHALATION UNIT RISK FOR

1,4

- DIOXANE

Multistage cancer models available in the Benchmark Dose Software (BMDS) (version 1

2.2beta) were fit to the incidence data for hepatocellular carcinoma and/or adenoma, nasal cavity 2

squamous cell carcinoma, renal cell carcinoma, peritoneal mesothelioma, and mammary gland 3

fibroadenom a, Zymbal gland adenoma, and subcutis fibroma in rats exposed to 1,4

- dioxane 4

vapors for 2 years ( Kasai, et al., 2009 ) . Concentrations associated with a benchmark response 5

(BMR) of a 10% extra risk were calculated. BMC 10 and BMCL 10 values from the best fitting 6

model, determined by adequate global

- fit (χ 2 p ≥ 0.1) and AIC values, are reported for each 7

endpoint ( U.S. EPA, 2000a ) . Given the multiplicity of tumor sites, basing the IUR on one tumor 8

site will underestimate the carcinogenic potential of 1,4

- dioxane. A Bayesian analysis was 9

performed using WinBUGS ( ( Spiegelhalter, et al., 2003 ) , freeware developed by the MRC 10

Biostatistical Unit, Cambridge, United Kingdom (available at http://www.mrc

11

bsu.cam.ac.uk/bugs/winbugs/contents.shtml )) and reported in detail in Sectio n G.3. In addition, 12

the combined tumor analysis was also performed using the beta version of the BMDS MSCombo 13

model (BMDS Version 2.2beta) and is included in Section G.4. The results of both analyses 14

were very similar. 15

A summary of the BMDS model predict ions for the Kasai et al. ( 2009 ) study are shown 16

in Table G

- 1. 17

G.1. GENERAL ISSUES AND A PPROACHES TO BMDS AN D MULTITUMOR

MODELING

G.1.1. Combining Data tumor types

The incidence of adenomas and the incidence of carcinomas within a dose group at a site 18

or tissue in rodents are sometimes combined. This practice is based upon the hypothesis that 19

adenomas may develop into carcinomas if exposure at the same dose was continued ( McConnell, 20

et al., 1986 ; U.S. EPA, 2005a ) . In the same manner and was done for the oral cancer assessment 21

(Appendix D), the incidence of hepatic adenomas and carcinomas was summed without double

22

counting them so as to calculate the combined incidence of either a hepatic carcinoma or a 23

hepatic adenoma in roden ts. 24

The remaining of the tumor types were assumed to occur independently. 25

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

(Health and Environmental Res earch 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)G

- 42

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE G.1.2. Summary

The BMDS models recommended to calculate rodent BMC 10 and BMCL 10 values for 1

individual tumor types and combined tumor analysis are summarized in Table G

- 1. The first 2

orde r multistage models for most tumor types were selected because they resulted in the lowest 3

AIC values; however, for renal cell carcinoma and Zymbal gland adenoma, the lowest AIC 4

model was not the first order model. In BMDS, the third order model resulted in the lowest AIC 5

(1 st , 2 nd , and 3 rd degree models were evaluated); however, using the MCMC approach in 6

WinBUGS, the third order multistage model did not converge while the second order model did 7

converge. Thus, for renal cell carcinoma and Zymbal gland adenoma, the second order 8

multistage model was used in both the MCMC (WinBugs) approach and the BMDS (Version 2.2 9

beta) MSCombo approach for direct comparison of results. These results are shown below in 10

Table G

- 1. 11

Table G

- 1. Summary of BMC 10 and BMCL 10 model results for individual

tumor ty pes and combined tumor analysis for male rats exposed to

1,4

- dioxane vapors ( Kasai, et al., 2009 )

Endpoint Multistage

Model

Degree AIC p

- value χ 2

Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

Nasal squamous cell

carcinoma First 49.03 0.9607 0.176 1107.04 629.95

Hepatocellular

adenoma/carcinoma First 127.9 0.6928

- 0.763 252.80 182.26

Renal cell carcinoma Third 29.99 0.9984 0.017 1355.16 16.15

Peritoneal mesothelioma First 155.4 0.8509

- 0.204 82.21 64.38

Mammary gland

fibroadenoma First 86.29 0.7904

- 0.149 1635.46 703.03

Zymbal gland adenoma Third 29.99 0.9984 0.017 1355.16 16.15

Subcutis fibroma a First 89.2 0.5245 0.537 141.762 81.9117

WinBUGS multitumor analysis b 39.2 31.4

BMDS Version 2.2beta MSCombo 40.4 30.3

a High

- dose dropped. See Section G.2.6 for details.

b In MCMC approach, the simulations for the four

- parameter third order multistage model did not converge for renal

cell carcinomas and Zymbal gland adenomas. Second order multistage model was used instead.

G.2. BMDS MODEL OUTPUT FO R MULTISTAGE CANCER MODELS FOR

INIDIVIDUAL TUMOR TY PE S

For tumor incidence data reported in the Kasai et al. ( 2009 ) 2

- year inhalation bioassay, 12

multistage cancer models of 1, 2, and 3 degrees were implemented BMDS (Version 2.2Beta). 13

Incidence data used for BMD analysis are shown in Table G

- 2. Tumor incidence for mammary 14

gland adenoma was excluded from this analysis since only 1 tumor of this type was found across 15

all doses. 16G

- 43

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table G

- 2. Incidence of tumors in male F344/DuCrj rats exposed to 1,4

- dioxane vapor by whole

- body inhalation for 2 years.

Effect 1,4

- dioxane vapor concentration (ppm)

0 (clean air) 50 250 1,250

Nasal squamous cell carcinoma 0/50 0/50 1/50 6/50 b,c

Hepatocellular adenoma 1/50 2/50 3/50 21/50 a,c

Hepatocellular carcinoma 0/50 0/50 1/50 2/50

Hepatocellular adenoma or carcinoma 1/50 2/50 4/50 22/50 a,c

Renal cell carcinoma 0/50 0/50 0/50 4/50 c

Peritoneal mesothelioma 2/50 4/50 14/50 a 41/50 a,c

Mammary gland fibroadenoma 1/50 2/50 3/50 5/50 d

Zymbal gland adenoma 0/50 0/50 0/50 4/50 c

Subcutis fibroma 1/50 4/50 9/50 a 5/50

a p≤ 0.01 by Fisher‘s exact test.

b p≤ 0.05 by Fisher‘s exact test.

c p≤ 0.01 by Peto‘s test for dose

- related trend.

d p≤ 0.05 by Peto‘s test for dose

- related trend.

e Provided via personal communication from Dr. Tatsuya Kasai to Dr. Reeder Sams on 12/23/2008

( 2008 ) . Statistics w ere not reported for these data by study authors, so statistical analyses were

conducted by EPA.

Source: Kasai et al. ( 2009 ) and Kasai personal communication ( 2008 )

G.2.1. Nasal Squamous Cell Carcinoma

The incidence data for nasal squamous cell carcinoma were monotonic non

- decreasing 1

functions of dose; therefore, these data appear to be appropriate for dose

- response modeling 2

using BMDS. The results of the BMDS modeling fo r the multistage cancer model for 1 st , 2 nd

, 3

and 3 rd

- degree polynomials are shown in Table G

- 3. The 1 st

- degree polynomial was the best 4

fitting model based on AIC. The plot (Figure G

- 1) and model output for the 1 st

- degree model are 5

shown below. 6

Table G

- 3. BMDS Multistage cancer dose

- response modeling results for the

incidence of nasal squamous cell carcinomas in male rats exposed to 1,4

- dioxane vapors for 2

- years ( Kasai, et al., 2009 )

Polynomial Degree AIC p

- value χ 2 Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

First b 49.0308 0.9607 0.176 1107.04 629.95

Second 50.8278 0.9087

- 0.021 1086.94 642.43

Third 50.8278 0.9087

- 0.021 1086.94 642.43

a Best

- fitting model based on AIC.

7

8G

- 44

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure G

- 1. Multistage model (1 st

- degree) for male rat nasal squamous cell

carcinomas.

==================================================================== 1

MS_COMBO. (Version: 1.4; Date: 10/20/2010) 2

Input Data File: C: \ Documents and 3

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.(d) 4

Gnuplot Plotting File: C: \ Documents and 5

Setti ngs \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.plt 6

Wed Nov 17 10:57:55 2010 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of th e probability function is: 11

12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = EFFECT 17

Independent variable = DOSE 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 2 22

Total number of specified parameters = 0 23

Degree of polynomial = 1 24

25

Maximum number of iterations = 250 26G

- 45

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Relative Function Convergence has been set to: 1e

- 008 1

Param eter Convergence has been set to: 1e

- 008 2

3

4

Default Initial Parameter Values 5

Background = 0 6

Beta(1) = 0.000104666 7

8

Asymptotic Correlation Matrix of Parameter Estimates 9

( ***The model parameter(s)

- Background have been estimated at a boundary point, or 10

have been specified by the user, and do not appear in the correlation matrix ) 11

12

Beta(1) 13

Beta(1) 1 14

15

Parameter Estimates 16

95.0% Wald Confidence Interval 17

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 18

Background 0 * * * 19

Beta(1) 9.51733e

- 005 * * * 20

21

*

- Indicates that this value is not calculated. 22

23

Analysis of Deviance Table 24

25

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 26

Full model

- 23.2482 4 27

Fitted model

- 23.5154 1 0.534383 3 0.9113 28

Reduced model

- 30.3429 1 14.1894 3 0.002658 29

30

AI C: 49.0308 31

32

Log

- likelihood Constant 20.493267595834471 33

34

35

Goodness of Fit 36

Scaled 37

Dose Est._Prob. Expected Observed Size Residual 38

------------------------------------------------------------------------ 39

0.0000 0.0000 0.000 0 50 0.000 40

50.0000 0.0047 0.237 0 50

- 0.488 41

250.0000 0.0235 1.176 1 50

- 0.164 42

1250.0000 0.1122 5.608 6 50 0.176 43

44

Chi^2 = 0.30 d.f. = 3 P

- value = 0.9607 45

46

47

Benchmark Dose Computation 48

49

Specified effect = 0.1 50

Risk Type = Extra risk 51

Confidence level = 0.95 52

BMD = 1107.04 53

BMDL = 629.948 54

BMDU = 2215.11 55

56

Taken together, (629.948, 2215.11) is a 90% two

- sided confidence interval for the BMD 57

G.2.2. Hepatocellular Adenoma and Carcinoma

The incidence data for the occurrence of either hepatocellular adenoma or carcinoma 58

were combined for this analysis as explained in G.1.1. The incidence data were monotonic non

59

decreasing functions of dose; th erefore, these data appear to be appropriate for dose

- response 60G

- 46

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE modeling using BMDS. The results of the BMDS modeling for the multistage cancer model for 1

1 st , 2 nd , and 3 rd

- degree polynomials are shown in Table G

- 4. The 1 st

- degree polynomial was the 2

best f

itting model based on AIC. The plot (Figure G

- 2) and model output for the 1 st

- degree 3

model are shown below. 4

Table G

- 4. BMDS Multistage cancer dose

- response modeling results for the

incidence of either hepatocellular adenoma or carcinoma in male rats

expos ed to 1,4

- dioxane vapors for 2

- years ( Kasai, e t al., 2009 )

Polynomial Degree AIC p

- value χ 2 Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

First a 127.86 0.6928

- 0.763 252.80 182.26

Second 129.157 0.7636

- 0.094 377.16 190.28

Third 129.131 0.8

- 0.068 397.426 190.609

a Best

- fitting model based on AIC.

Figure G

- 2

. Multistage model (1 st

- degree) for male rat hepatocellular

adenomas and carcinomas.

5G

- 47

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE ==================================================================== 1

MS_COMBO. (Version: 1.4; Date: 10/20/2010) 2

Input Data File: C: \ Documents and 3

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.(d) 4

Gnuplot Plotting File: C: \ Documents and 5

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.plt 6

Wed Nov 17 10:57:55 2010 7

============================== ====================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = EFFECT 16

Independent variable = DOSE 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Total number of parameters in model = 2 21

Total number o f specified parameters = 0 22

Degree of polynomial = 1 23

24

Maximum number of iterations = 250 25

Relative Function Convergence has been set to: 1e

- 008 26

Parameter Convergence has been set to: 1e

- 008 27

28

Default Initial Parameter Values 29

Background = 0.00480969 30

Beta(1) = 0.0004548 31

32

Asymptotic Correlation Matrix of Parameter Estimates 33

34

Background Beta(1) 35

Background 1

- 0.53 36

Beta(1)

- 0.53 1 37

38

Parameter Estimates 39

40

95.0% Wald Confidence Interval 41

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 42

Background 0.0170678 * * * 43

Beta(1) 0.000416776 * * * 44

45

*

- Indicates that this value is not calculated. 46

47

Analysis of Deviance Table 48

49

Model Log(like lihood) # Param's Deviance Test d.f. P

- value 50

Full model

- 61.5341 4 51

Fitted model

- 61.9302 2 0.792109 2 0.673 52

Reduced model

- 82.7874 1 42.5066 3 <.0001 53

54

AIC: 127.86 55

56

Log

- likelihood Constant 55.486699676972215 57

58

Goodness of Fit 59

Scaled 60

Dose Est._Prob. Expected Observ ed Size Residual 61

------------------------------------------------------------------------ 62

0.0000 0.0171 0.853 1 50 0.160 63

50.0000 0.0373 1.867 2 50 0.099 64

250.0000 0.1143 5.716 4 50

- 0.763 65

1250.0000 0.4162 20.810 22 50 0.342 66G

- 48

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Chi^2 = 0.73 d.f. = 2 P

- value = 0.6928 1

2

3

Benchmark Dose Computation 4

5

Specified effect = 0.1 6

Risk Type = Extra risk 7

Confidence level = 0.95 8

BMD = 252.799 9

BMDL = 182.256 10

BMDU = 371.457 11

12

Taken together, (182.256, 371.457) is a 90% two

- sided confidence interval for the B MD 13

14

G.2.3. Renal Cell Carcinoma and Zymbal Gland Adenoma

The incidence data for renal cell carcinomas and Zymbal gland adenomas were the same. 15

These data were monotonic non

- decreasing functions of dose; therefore, these data appear to be 16

appropriate for dose

- res ponse modeling using BMDS. The results of the BMDS modeling for 17

the multistage cancer model for 1 st , 2 nd , and 3 rd

- degree polynomials are shown in Table G

- 5. The 18

3 rd

- degree polynomial was the best fitting model based on AIC; however, when conducting the 19

m ultitumor analysis, WinBUGS was unable to converge using the 3 rd degree model. Thus, the 20

2 nd degree model was used in the multitumor analyses. The plots (Figure G

- 3 and G

- 4) and 21

model outputs for both the 2 nd and 3 rd

- degree models are shown below. 22

Table G

- 5. BMDS Multistage cancer dose

- response modeling results for the

incidence of renal cell carcinomas and Zymbal gland adenomas in male rats

exposed to 1,4

- dioxane vapors for 2

- years ( Kasai, et al., 2009 )

Polynomial Degree AIC p

- value χ 2 Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

First 31.6629 0.8004 0.446 1974.78 957.63

Second 30.2165 0.9817 0.085 1435.28 999.44

Third a 29.9439 0.9984 0.017 1355.16 1016.15

a Best

- fitting model based on AIC.G

- 49

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure G

- 3. Multistage model (2 nd

- degree) for male rat renal cell carcinomas

and Zymbal gland adenomas.

==================================================================== 1

Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2

Input Data File: C:/Documents and 3

Settings/emclanah/Desktop/BMD_14D_Cancer/Data/msc_Kasai2009_renal_Msc2

- BMR10.(d) 4

Gnuplot Plotting File: C:/Documents and 5

Settings/emclanah/Desktop/BMD_14D_Cancer/Data/msc_Kasai2009_renal_Msc2

- BMR10.plt 6

Thu Feb 10 10:17:39 2011 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

12

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = EFFECT 17

Independent variable = DOSE 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 3 22

Total number of specified parameters = 0 23

Degree of polynomial = 2 24

25

Maximum number of iterations = 250 26G

- 50

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Relative Function Convergence has been set to: 1e

- 008 1

Parameter Convergence has been set to: 1e

- 008 2

3

Default Initial Parameter Values 4

Background = 0 5

Beta(1) = 0 6

Beta(2) = 5.40386e

- 008 7

8

Asymptotic Correlation Matrix of Parameter Estimates 9

(*** The model parameter(s)

- Background

- Beta(1) have been estimated at a boundary 10

point, or have been specified b y the user, and do not appear in the correlation 11

matrix) 12

13

Beta(2) 14

Beta(2) 1 15

16

Parameter Estimates 17

95.0% Wald Confidence Interval 18

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 19

Background 0 * * * 20

Beta(1) 0 * * * 21

Beta(2) 5.11454e

- 008 * * * 22

23

*

- Indicates that this value is not calculated. 24

25

Analysis of Deviance Table 26

27

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 28

Full model

- 13.9385 4 29

Fitted model

- 14.1082 1 0.339554 3 0.9524 30

Reduced model

- 19.6078 1 11.3387 3 0.01003 31

32

AIC: 30.2165 33

34

Goodness of Fit 35

Scaled 36

Dose Est._Prob. Expected Observed Size Residual 37

------------------------------------------------------------------------ 38

0 .0000 0.0000 0.000 0.000 50 0.000 39

50.0000 0.0001 0.006 0.000 50

- 0.080 40

250.0000 0.0032 0.160 0.000 50

- 0.400 41

1250.0000 0.0768 3.840 4.000 50 0.085 42

43

Chi^2 = 0.17 d.f. = 3 P

- value = 0.9817 44

45

Benchmark Dose Computation 46

Specified effect = 0.1 47

Risk Type = Extra risk 48

Confidence level = 0.95 49

BMD = 1435.28 50

BMDL = 999.44 51

52

BMDU = 3666.87 53

54

Taken together, (999.44 , 3666.87) is a 90% two

- sided confidence interval for the BMD 55

56

Multistage Cancer Slope Factor = 0.000100056 57G

- 51

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure G

- 4. Multistage model (3 rd

- degree) for male rat renal cell carcinomas.

==================================================================== 1

MS_COMBO. (Version: 1.4; Date: 10/20/2010) 2

Input Data File: C: \ Documents and 3

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.(d) 4

Gnuplot Plott ing File: C: \ Documents and 5

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.plt 6

Wed Nov 17 10:57:55 2010 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1

- beta2*dose^2

- 12

beta3*dose^3)] 13

14

The parameter betas are restricted to be positive 15

16

Dependent variable = EFFECT 17

Independent variable = DOSE 18

19

Total number of observations = 4 20

Total number of records with missing values = 0 21

Total number of parameters in model = 4 22

Total number of specified parameters = 0 23

Degree of polynomial = 3 24

25

Maximum number of iterations = 250 26

Relative Function Convergence has been set to: 1e

- 008 27G

- 52

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Parameter Convergence has been set to: 1e

- 008 1

2

Default Initial Parameter Values 3

Background = 0 4

Beta(1) = 0 5

Beta(2) = 0 6

Beta(3) = 4.2804e

- 011 7

8

9

Asymptotic Correlation Matrix of Parameter Estimates 10

(*** The model parameter(s)

- Background

- Beta(1)

- Beta(2) have been estimated at a 11

boundary point , or have been specified by the user, and do not appear in the 12

correlation matrix) 13

14

Beta(3) 15

Beta(3) 1 16

17

Parameter Estimates 18

19

95.0% Wald Confid ence Interval 20

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 21

Background 0 * * * 22

Beta(1) 0 * * * 23

Beta(2) 0 * * * 24

Beta(3) 4.23353e

- 011 * * * 25

26

*

- Indicates that this value is not calculated. 27

28

Analysis of Deviance Table 29

30

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 31

Full model

- 13.9385 4 32

Fitted model

- 13.9719 1 0.0669578 3 0.9955 33

Reduced model

- 19.6078 1 11.3387 3 0.01003 34

35

AIC: 29.9439 36

37

Log

- likelihood Constant 12.347138085809094 38

39

40

Goodness of Fit 41

Scaled 42

Dose Est ._Prob. Expected Observed Size Residual 43

------------------------------------------------------------------------ 44

0.0000 0.0000 0.000 0 50 0.000 45

50.0000 0.0000 0.000 0 50

- 0.016 46

250.0000 0.0007 0.033 0 50

- 0.182 47

1250.0000 0.0794 3.968 4 50 0.017 48

49

Chi^2 = 0.03 d.f. = 3 P

- value = 0.9984 50

51

52

Benchmark Dose Computation 53

Specified effect = 0.1 54

Risk Type = Extra risk 55

Confidence level = 0.95 56

BMD = 1355.16 57

BMDL = 1016.15 58

BMDU = 3393.6 59

60

Taken together, (1016.15, 3393.6 ) is a 90% two

- sided confi dence interval for the BMD 61G

- 53

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE G.2.4. Peritoneal Mesothelioma

The incidence data for peritoneal mesotheliomas were monotonic non

- decreasing 1

functions of dose; therefore, these data appear to be appropriate for dose

- response modeling 2

using BMDS. The results of the BM DS modeling for the multistage cancer model for 1 st , 2 nd

, 3

and 3 rd

- degree polynomials are shown in Table G

- 6. The 1 st

- degree polynomial was the best 4

fitting model based on AIC. The plot (Figure G

- 5) and model output for the 1 st

- degree model are 5

shown belo w. 6

Table G

- 6. BMDS Multistage cancer dose

- response modeling results for the

incidence of peritoneal mesothelioma in male rats exposed to 1,4

- dioxane

vapors for 2

- years ( Kasai, et al., 2009 )

Polynomial Degree AIC p

- value χ 2 Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

First a 155.433 0.8509

- 0.204 82.21 64.38

Second 157.168 0.8053

- 0.204 96.23 65.15

Third 157.168 0.8053 0 96.23 65.15

a Best

- fitting model based on AIC.G

- 54

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure G

- 5. Multistage model (1 st

- degree) for male rat peritoneal

mesotheliomas.

==================================================================== 1

MS_COMBO. (Version: 1.4; Date: 10/20/2010) 2

Input Data File: C: \ Documents and 3

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.(d) 4

Gnuplot Plotting File: C: \ Documents and 5

S ettings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.plt 6

Wed Nov 17 10:57:55 2010 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = EFFECT 16

Independent variable = DOSE 17

18

Total number of observations = 4 19

Total number of records with missing values = 0 20

Total number of parameters in model = 2 21

Total number of specified parameters = 0 22

Degree of polynomial = 1 23

Maximum number of iterations = 250 24

Relative Function Convergence has been set to: 1e

- 008 25

Parame ter Convergence has been set to: 1e

- 008 26G

- 55

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

Default Initial Parameter Values 2

Background = 0.0172414 3

Beta(1) = 0.00135351 4

5

Asymptotic Correlation Matrix of Parameter Estimates 6

7

Background Beta(1) 8

Background 1

- 0.45 9

Beta(1)

- 0.45 1 10

11

Parameter Estimates 12

95.0% Wald Confidence Interval 13

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 14

Background 0.033631 * * * 15

Beta(1) 0.00128167 * * * 16

17

*

- Indicates that this value is not calculated. 18

19

Analysis of Deviance Table 20

21

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 22

Full model

- 75.553 4 23

Fitted model

- 75.7165 2 0.326905 2 0.8492 24

Reduced model

- 123.008 1 94.9105 3 <.0001 25

26

AIC: 155.433 27

28

Log

- likelihood Constant 68.666413125908832 29

30

Goodness of Fit 31

Scaled 32

Dose Est._Prob. Expected Observed Size Residual 33

------------------------------------------------------------------------ 34

0.0000 0.0336 1.682 2 50 0.250 35

50.0000 0.0936 4.681 4 50

- 0.331 36

250.0000 0.2986 14.928 14 50

- 0.287 37

1250.0000 0.8053 40.265 41 50 0.263 38

39

Chi^2 = 0.32 d. f. = 2 P

- value = 0.8509 40

41

Benchmark Dose Computation 42

Specified effect = 0.1 43

Risk Type = Extra risk 44

Confidence level = 0.95 45

BMD = 82.2057 46

BMDL = 64.3808 47

BMDU = 107.497 48

49

Taken together, (64.3808, 107.497) is a 90% two

- sided confidence interval for the BMD 50

G.2.5. Mammary Gland Fibroadenoma

The incidence data for mammary gland fibroadenomas were monotonic non

- decreasing 51

functions of dose; therefor e, these data appear to be appropriate for dose

- response modeling 52

using BMDS. The results of the BMDS modeling for the multistage cancer model for 1 st , 2 nd

, 53

and 3 rd

- degree polynomials are shown in Table G

- 7. Since quadratic and cubic terms of the 54

multist age models evaluated resulted in the estimates on the boundary, i.e. equal to 0, the 1 st

- 55

degree polynomial was selected based on model parsimony. The plot (Figure G

- 6) and model 56

output for the 1 st

- degree model are shown below. 57G

- 56

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Table G

- 7. BMDS Multistage c ancer dose

- response modeling results for the

incidence of mammary gland fibroadenoma in male rats exposed to 1,4

- dioxane vapors for 2

- years ( Kasai, et al., 2009 )

Polynomial Degree AIC p

- value χ 2 Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

First a 86.29 0.7904

- 0.149 1635.46 703.03

Second 86.29 0.7904

- 0.149 1635.46 703.03

Third 86.29 0.7904

- 0.149 1635.46 703.03

a All model fits were equivalent based on AIC. Selected 1 st

- degree model based on parsimony.

1

Figure G

- 6. Multistage model (1 st

- degree) for male rat mammary gland

fibroadenoma.

==================================================================== 2

MS_COMBO. (Version: 1.4; Date: 10/20/2010) 3

Input Data File: C: \ Documents and 4

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.(d) 5

Gnuplot Plotting File: C: \ Documents and 6

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.plt 7

Wed Nov 17 10:57:55 2010 8

==================================================================== 9G

- 57

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE BMDS_Model_Run 1

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2

The form of the probability function is: 3

P[response] = background + (1

- background)*[1

- EXP(

- beta1*dose^1)] 4

5

The parameter betas are restricted to be positive 6

7

Dependent variable = EFFECT 8

Independent variable = DOSE 9

10

Total number of observations = 4 11

Total number of records with missing values = 0 12

Total number of parameters in model = 2 13

Total number of specified parameters = 0 14

Degree of polynomial = 1 15

16

Maximum number of iterations = 250 17

Relative Function Convergence has been set to: 1e

- 008 18

Param eter Convergence has been set to: 1e

- 008 19

20

Default Initial Parameter Values 21

Background = 0.0335609 22

Beta(1) = 5.91694e

- 005 23

24

Asymptotic Correlation Matrix of Parameter Estimates 25

26

Background Beta(1) 27

Background 1

- 0.61 28

Beta(1)

- 0.61 1 29

30

Parameter Estimates 31

32

95.0% Wald Confidence Interval 33

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 34

Background 0.0315836 * * * 35

Beta(1) 6.44224e

- 005 * * * 36

37

*

- Indicates that this value is not calculated. 38

39

40

Analysis of Deviance Table 41

42

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 43

Full model

- 40.9017 4 44

Fitted model

- 41.145 2 0. 486662 2 0.784 45

Reduced model

- 42.5964 1 3.3895 3 0.3354 46

47

AIC: 86.29 48

49

Log

- likelihood Constant 35.472345543489602 50

51

Goodness of Fit 52

Scaled 53

Dose Est._Prob. Expected Observed Size Residual 54

------------------------------------------------------------------------ 55

0.0000 0.0316 1.579 1 50

- 0.468 56

50.0000 0.0347 1.735 2 50 0.205 57

250.0000 0.0471 2.353 3 50 0.432 58

1250.0000 0.1065 5.326 5 50

- 0.149 59

60

Chi^2 = 0.47 d.f. = 2 P

- value = 0.7904 61

62

63

Benchmark Dose Computation 64

Specified effect = 0.1 65

Risk Type = Extra risk 66G

- 58

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Confidence level = 0.95 1

BMD = 1635.46 2

BMDL = 703.034 3

BMDU = 1.9523e+009 4

5

Taken together, (703.034, 1.9523e+009) is a 90% two

- sided confidence interval for the 6

BMD 7

G.2.6. Subcutis Fibroma

The incidence data for subcutis fibroma were monotonic non

- decreasing functions of 8

dose for the control (0 ppm), l ow (50 ppm), and mid

- dose (250 ppm); however, the incidence 9

rate at the high dose (1,250 ppm) was lower than observed at the mid

- dose. No BMDS model 10

had reasonable fit to the data without dropping the high dose. The results of the BMDS 11

modeling for the multistage cancer model for 1 st , 2 nd , and 3 rd

- degree polynomials with the high 12

dose dropped are shown in Table G

- 8. Since quadratic and cubic terms of multistage models 13

evaluated resulted in the estimates on the boundary, i.e. equal to 0, , the 1 st

- degre e polynomial 14

was selected based on model parsimony. The plot (Figure G

- 7) and model output for the 1 st

- 15

degree model are shown below. 16

Table G

- 8. BMDS Multistage cancer dose

- response modeling results for the

incidence of subcutis fibromas in male rats expo sed to 1,4

- dioxane vapors for

2

- years ( Kasai, et al., 2009 )

Polynomial Degree AIC p

- value χ 2 Residual

of Interest BMC 10

(ppm) BMCL 10

(ppm)

First a 89.2094 0.5245 0.537 141.76 81.92

Second 89.2094 0.5245 0.537 141.76 81.92

Third 89.2094 0.5245 0.537 141.76 81.92

a All model fits were equivalent based on AIC. Selected 1 st

- degree model based on parsimony.G

- 59

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Figure G

- 7. Multistage model (1 st

- degree) for male rat subcutis fibroma (high

dose dropped).

=================================================================== 1

MS_COMBO. (Version: 1.4; Date: 10/20/2010) 2

Input Data File: C: \ Documents and 3

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.(d) 4

Gnuplot Plotting File: C: \ Documents and 5

Settings \ emclanah \ Desktop \ BMD_14D_Cancer \ Data \ New.plt 6

Wed Nov 17 10:57:55 2010 7

==================================================================== 8

BMDS_Model_Run 9

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10

The form of the probability function is: 11

P[response] = background + (1

- back ground)*[1

- EXP(

- beta1*dose^1)] 12

13

The parameter betas are restricted to be positive 14

15

Dependent variable = EFFECT 16

Independent variable = DOSE 17

18

Total number of observations = 3 19

Total number of records with missing values = 0 20

Total number of parameters in model = 2 21

Total number of specified parameters = 0 22

Degree of polynomial = 1 23

24

Maximum number of iterations = 250 25

Relative Function Convergence has been set to: 1e

- 008 26G

- 60

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE Parameter Convergence has been set to: 1e

- 008 1

2

Default Initial Parameter Values 3

Background = 0.0327631 4

Beta(1) = 0.000673665 5

6

7

Asymptotic Correlation Matrix of Parameter Estimates 8

9

Background Beta(1) 10

Background 1

- 0.68 11

Beta(1)

- 0.68 1 12

13

Parameter Estimates 14

15

95.0% Wald Confidence Interval 16

Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 17

Background 0.0262054 * * * 18

Beta(1) 0.00074322 * * * 19

20

*

- Indicates that this value is not calculated. 21

22

Analysis of Deviance Table 23

24

Model Log(likelihood) # Param's Deviance Test d.f. P

- value 25

Full model

- 42.4101 3 26

Fitted model

- 42.6047 2 0.3 89155 1 0.5327 27

Reduced model

- 46.5274 1 8.23466 2 0.01629 28

29

AIC: 89.2094 30

31

Log

- likelihood Constant 37.900888781466982 32

33

Goodness of Fit 34

Scaled 35

Dose Est._Prob. Expected Observed Size Residual 36

------------------------------------------------------------------------ 37

0.0000 0.0262 1.310 1 50

- 0.275 38

50.0000 0.0617 3.086 4 50 0.537 39

250.0000 0.1913 9.566 9 50

- 0.204 40

Chi^2 = 0.41 d.f. = 1 P

- value = 0.5245 41

42

43

Benchmark Dose Computation 44

Specified effect = 0.1 45

Risk Type = Extra risk 46

Confidence level = 0.95 47

BMD = 141.762 48

BMDL = 81.9117 49

BMDU = 364.364 50

51

Taken together, (81 .9117, 364.364) is a 90% two

- sided confidence interval for the BMD 52

G.3. MULTITUMOR ANALYSIS USING BAYESIAN METHO DS

Given the multiplicity of tumor sites, basing the IUR on one tumor site will 53

underestimate the carcinogenic potential of 1,4

- dioxane. Simply pool ing the counts of animals 54

with one or more tumors (i.e., counts of tumor bearing animals) would tend to underestimate the 55

overall risk when tumors are independent across sites and ignores potential differences in the 56

dose

- response relationships across the sites ( Bogen, 1990 ; Spurgeon, et al., 1994 ) . NRC ( 1994 ) 57G

- 61

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE also noted that the assumption of independence acros s tumor types is not likely to produce 1

substantial error in the risk estimates unless tumors are known to be biologically dependent. 2

Kopylev et al. ( 2009 ) describe a Markov Chain Monte Caro (MCMC) computational 3

approach to calculating the dose associated with a specified composite risk under assumption of 4

independence of tumors. The current Guidelines for Carcinogen Risk Assessment recommend 5

calculation of an upper bound to account for uncertainty in the estimate ( U.S. EPA, 2005a ) . For 6

uncertainty characterization, MCMC methods have the advantage of providing information about 7

the full distribution of risk and/or benchmark dose, which can be used in generating a confidence 8

bound. This MCMC approach build ing on the re

- sampling approach recommended by Bogen 9

( 1990 ) , and also provides a distribution of the combined potency across sites. 10

For individual tumor data modeled using the multistage model: 11

P(d | q ) = 1

- exp[

- (q 0 + q 1 d + q 2 d 2 + ... + q k d

k )] , q i ≥0 12

the model for the combined tumor risk is still multistage, with a functional form that has 13

the sum of stage

- specific multistage coefficients as the corresponding multistage coefficient; 14

P

c (d | q ) = 1

- exp[

- (q Σ 0i + q Σ 1i d + q

Σ 2i d 2 + ... + q

Σ ki d k )]

, 15

The res ulting equation for fixed extra risk (BMR) is polynomial in dose (when logarithms 16

of both sides are taken) and can be straightforwardly solved for a combined BMC. Computation 17

of the confidence bound on combined risk BMC can be accomplished via likelihood methods 18

(BMDS

- MSCOMBO), re

- sampling (bootstrap) or Bayesian methods. 19

The MCMC computations were conducted using WinBUGS ( Spiegelhalter, et al., 20

2003 ) (freeware developed by the MRC Biostatistical Unit, Cambridge, United Kingdom, 21

available at http://www.mrc

- bsu.cam.ac.uk/bugs/winbugs/contents.shtml ). 22

In a Bayesian analysis, the choice of the appropriate prior is important. In the examples 23

developed by Kopylev et al. ( 2009 ) , a diffuse (i.e., high variance or low tolerance) Gaussian 24

prior restric ted to be nonnegative was used; such diffuse priors performed reasonably well. 25

The mean and the 5 th percentile of the posterior distribution of combined BMC provide 26

estimates of the mean BMC and the lower bound on the BMC (BMCL), respectively, for the 27

co mbined tumor risk. 28

The values calculated using this method were: mean BMC 10 39.2ppm, and BMCL 10 29

31.4. 30

G.4. MULTITUMOR ANALYSIS USING BMDS MSCOMBO ( BETA)

The combined tumor analysis was also performed with beta version of the MSCombo model in 31

BMDS (Version 2.2beta). The model resulted in similar results to the Bayesian method and 32

model output is shown below for the combined calculation. 33

34

**** Start of combined BMD and BMDL Calculations.**** 35

Combined Log

- Likelihood

- 277.79874987953076 36

Combined Log

- likelihood Constant 246.62591390071873 37

38G

- 62

DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE 1

Benchmark Dose Computation 2

Specified effect = 0.1 3

Risk Type = Extra risk 4

Confidence level = 0.95 5

BMD = 40.4937 6

BMDL = 32.331 7

8

9