DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 NCEA-I-3833

2 www.epa.gov/iris

3

4

5

6

7 TOXICOLOGICAL REVIEW

8 

9 OF

10

11 1,4-Dioxane

12

13 (CAS No. 123-91-1)

14

15

16 In Support of Summary Information on the

17 Integrated Risk Information System (IRIS)

18

19

20

21

22 May 2011

23

24

25

26

27 NOTICE

28

29 This document is an Interagency Science Consultation draft. This information is distributed 

30 solely for the purpose of pre-dissemination peer review under applicable information quality 

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

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

33 of its technical accuracy and science policy implications.

34

35

36

37

38

39 U.S. Environmental Protection Agency

40 Washington, DC
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

ii

1 DISCLAIMER

2

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

4 distributed solely for the purpose of pre-dissemination peer review under application information 

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

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

7 names or commercial products does not constitute endorsement or recommendation for use.
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

iii

1 CONTENTS – TOXICOLOGICAL REVIEW OF 1,4-DIOXANE

2 (CAS No. 123-91-1)

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

4 LIST OF FIGURES ................................................................................................................ xiii

5 LIST OF ABBREVIATIONS AND ACRONYMS ............................................................... xviii

6 1. INTRODUCTION...................................................................................................................1

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

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

9 3.1. ABSORPTION............................................................................................................6

10 3.2. DISTRIBUTION.........................................................................................................7

11 3.3. METABOLISM...........................................................................................................8

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

13 3.5. PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELS..........................13

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

15 3.5.2. Published PBPK Models for 1,4-Dioxane...........................................................16

16 3.5.2.1. Leung and Paustenbach.....................................................................................16

17 3.5.2.2. Reitz et al..........................................................................................................17

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

19 3.5.2.4. Sweeney et al. ...................................................................................................18

20 3.5.3. Implementation of Published PBPK Models for 1,4-Dioxane .............................19

21 3.6. RAT NASAL EXPOSURE VIA DRINKING WATER .............................................23

22 4. HAZARD IDENTIFICATION..............................................................................................24

23 4.1. STUDIES IN HUMANS – EPIDEMIOLOGY, CASE REPORTS, CLINICAL 

24 CONTROLS .........................................................................................................................24

25 4.1.1. Thiess et al.........................................................................................................26

26 4.1.2. Buffler et al........................................................................................................27

27 4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

28 ANIMALS - ORAL AND INHALATION ............................................................................28

29 4.2.1. Oral Toxicity......................................................................................................28

30 4.2.1.1. Subchronic Oral Toxicity ..................................................................................28

31 4.2.1.1.1. Stoner et al. ................................................................................................29

32 4.2.1.1.2. Stott et al. ...................................................................................................29

33 4.2.1.1.3. Kano et al. ..................................................................................................29

34 4.2.1.1.4. Yamamoto et al. .........................................................................................34

35 4.2.1.2. Chronic Oral Toxicity and Carcinogenicity .......................................................35

36 4.2.1.2.1. Argus et al..................................................................................................35

37 4.2.1.2.2. Argus et al.; Hoch-Ligeti et al.....................................................................36

38 4.2.1.2.3. Hoch-Ligeti and Argus. ..............................................................................37

39 4.2.1.2.4. Kociba et al. ...............................................................................................38

40 4.2.1.2.5. National Cancer Institute (NCI)..................................................................40
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

iv

1 4.2.1.2.6. Kano et al.; Japan Bioassay Research Center; Yamazaki et al. ....................44

2 4.2.2. Inhalation Toxicity.............................................................................................56

3 4.2.2.1. Subchronic Inhalation Toxicity .........................................................................56

4 4.2.2.1.1. Fairley et al. ...............................................................................................56

5 4.2.2.1.2. Kasai et al...................................................................................................56

6 4.2.2.2. Chronic Inhalation Toxicity and Carcinogenicity ..............................................59

7 4.2.2.2.1. Torkelson et al............................................................................................59

8 4.2.2.2.2. Kasai et al...................................................................................................60

9 4.2.3. Initiation/Promotion Studies...............................................................................63

10 4.2.3.1. Bull et al. ..........................................................................................................63

11 4.2.3.2. King et al. .........................................................................................................64

12 4.2.3.3. Lundberg et al. ..................................................................................................65

13 4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND INHALATION.65

14 4.3.1. Giavini et al. ......................................................................................................65

15 4.4. OTHER DURATION OR ENDPOINT-SPECIFIC STUDIES ...................................66

16 4.4.1. Acute and Short-term Toxicity ...........................................................................66

17 4.4.1.1. Oral Toxicity.....................................................................................................66

18 4.4.1.2. Inhalation Toxicity............................................................................................66

19 4.4.2. Neurotoxicity .....................................................................................................69

20 4.4.2.1. Frantik et al.......................................................................................................69

21 4.4.2.2. Goldberg et al. ..................................................................................................70

22 4.4.2.3. Kanada et al. .....................................................................................................70

23 4.4.2.4. Knoefel.............................................................................................................71

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

25 ACTION ...............................................................................................................................71

26 4.5.1. Genotoxicity ......................................................................................................71

27 4.5.2. Mechanistic Studies ...........................................................................................80

28 4.5.2.1. Free Radical Generation....................................................................................80

29 4.5.2.2. Induction of Metabolism ...................................................................................80

30 4.5.2.3. Mechanisms of Tumor Induction.......................................................................81

31 4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS................................................83

32 4.6.1. Oral....................................................................................................................83

33 4.6.2. Inhalation...........................................................................................................86

34 4.6.3. Mode of Action Information ..............................................................................89

35 4.7. EVALUATION OF CARCINOGENICITY...............................................................90

36 4.7.1. Summary of Overall Weight of Evidence ...........................................................90

37 4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence ...........................92

38 4.7.3. Mode of Action Information ..............................................................................94

39 4.7.3.1. Identification of Key Events for Carcinogenicity...............................................94

40 4.7.3.1.1. Liver. .........................................................................................................94

41 4.7.3.1.2. Nasal cavity................................................................................................95

42 4.7.3.2. Strength, Consistency, Specificity of Association..............................................96

43 4.7.3.2.1. Liver. .........................................................................................................96

44 4.7.3.2.2. Nasal cavity................................................................................................96

45 4.7.3.3. Dose-Response Relationship .............................................................................97

46 4.7.3.3.1. Liver. .........................................................................................................97
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

v

1 4.7.3.3.2. Nasal cavity................................................................................................99

2 4.7.3.4. Temporal Relationship ....................................................................................101

3 4.7.3.4.1. Liver. .......................................................................................................101

4 4.7.3.4.2. Nasal cavity..............................................................................................102

5 4.7.3.5. Biological Plausibility and Coherence .............................................................103

6 4.7.3.5.1. Liver. .......................................................................................................103

7 4.7.3.5.2. Nasal cavity..............................................................................................103

8 4.7.3.6. Other Possible Modes of Action......................................................................103

9 4.7.3.7. Conclusions About the Hypothesized Mode of Action.....................................104

10 4.7.3.7.1. Liver. .......................................................................................................104

11 4.7.3.7.2. Nasal cavity..............................................................................................104

12 4.7.3.8. Relevance of the Mode of Action to Humans ..................................................104

13 4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES ..........................................105

14 5. DOSE-RESPONSE ASSESSMENTS .................................................................................106

15 5.1. ORAL REFERENCE DOSE (RfD) .........................................................................106

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

17 106

18 5.1.2. Methods of Analysis—Including Models (PBPK, BMD, etc.)..........................107

19 5.1.3. RfD Derivation - Including Application of Uncertainty Factors (UFs)..............110

20 5.1.4. RfD Comparison Information...........................................................................111

21 5.1.5. Previous RfD Assessment ................................................................................115

22 5.2. INHALATION REFERENCE CONCENTRATION (RfC)......................................115

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

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

25 5.2.2. Methods of Analysis ........................................................................................118

26 5.2.3. Exposure Duration and Dosimetric Adjustments ..............................................119

27 5.2.4. RfC Derivation- Including Application of Uncertainty Factors (UFs)...............122

28 5.2.5. RfC Comparison Information...........................................................................123

29 5.2.6. Previous RfC Assessment ................................................................................123

30 5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE AND INHALATION 

31 REFERENCE CONCENTRATION....................................................................................123

32 5.4. CANCER ASSESSMENT.......................................................................................125

33 5.4.1. Choice of Study/Data – with Rationale and Justification ..................................125

34 5.4.1.1. Oral Study/Data ..............................................................................................125

35 5.4.1.2. Inhalation Study/Data......................................................................................127

36 5.4.2. Dose-Response Data ........................................................................................128

37 5.4.2.1. Oral Data ........................................................................................................128

38 5.4.2.2. Inhalation Data................................................................................................129

39 5.4.3. Dose Adjustments and Extrapolation Method(s)...............................................130

40 5.4.3.1. Oral.................................................................................................................130

41 5.4.3.2. Inhalation........................................................................................................132

42 5.4.4. Oral Slope Factor and Inhalation Unit Risk ......................................................133

43 5.4.4.1. Oral Slope Factor............................................................................................133

44 5.4.4.2. Inhalation Unit Risk ........................................................................................135

45 5.4.5. Previous Cancer Assessment............................................................................137

46 5.5. UNCERTAINTIES IN CANCER RISK VALUES ..................................................137
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

vi

1 5.5.1. Sources of Uncertainty.....................................................................................138

2 5.5.1.1. Choice of Low-Dose Extrapolation Approach .................................................138

3 5.5.1.2. Dose Metric ....................................................................................................139

4 5.5.1.3. Cross-Species Scaling .....................................................................................139

5 5.5.1.4. Statistical Uncertainty at the POD ...................................................................139

6 5.5.1.5. Bioassay Selection ..........................................................................................140

7 5.5.1.6. Choice of Species/Gender ...............................................................................140

8 5.5.1.7. Relevance to Humans......................................................................................141

9 5.5.1.8. Human Population Variability.........................................................................141

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

11 RESPONSE ............................................................................................................................143

12 6.1. HUMAN HAZARD POTENTIAL ..........................................................................143

13 6.2. DOSE RESPONSE..................................................................................................145

14 6.2.1. Noncancer/Oral................................................................................................145

15 6.2.2. Noncancer/Inhalation .......................................................................................145

16 6.2.3. Cancer .............................................................................................................145

17 6.2.3.1. Oral.................................................................................................................146

18 6.2.3.2. Inhalation........................................................................................................146

19 6.2.3.3. Choice of Low-Dose Extrapolation Approach .................................................146

20 6.2.3.4. Dose Metric ....................................................................................................148

21 6.2.3.5. Cross-Species Scaling .....................................................................................148

22 6.2.3.6. Statistical Uncertainty at the POD ...................................................................148

23 6.2.3.7. Bioassay Selection ..........................................................................................148

24 6.2.3.8. Choice of Species/Gender ...............................................................................149

25 6.2.3.9. Relevance to Humans......................................................................................149

26 6.2.3.10. Human Population Variability.......................................................................149

27 7. REFERENCES ...................................................................................................................150

28 APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS 

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

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

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

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

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

34 1,4-DIOXANE DRINKING WATER STUDY .......................................................................E-1

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

36 ............................................................................................................................................. F-13

37 APPENDIX G. DETAILS OF BMD ANALYSIS FOR INHALATION UNIT RISK FOR 

38 1,4-DIOXANE......................................................................................................................G-41
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

vii

LIST OF TABLES

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

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

3 1,4-dioxane in drinking water for 13 weeks ............................................................32

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

5 1,4-dioxane in drinking water for 13 weeks ............................................................34

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

7 exposed to 1,4-dioxane in drinking water for 13 months.........................................37

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

9 (combined) treated with 1,4-dioxane in the drinking water for 2 years ....................40

10 Table 4-5. Incidence of nonneoplastic lesions in Osborne-Mendel rats exposed to 

11 1,4-dioxane in drinking water .................................................................................41

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

13 adenoma in Osborne-Mendel rats exposed to 1,4-dioxane in drinking water ...........42

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

15 1,4-dioxane in drinking water .................................................................................44

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

17 1,4-dioxane in drinking water for 2 years................................................................48

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

19 1,4-dioxane in drinking water for 2 years................................................................49

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

21 F344/DuCrj rats exposed to 1,4-dioxane in drinking water for 2 years ....................51

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

23 drinking water for 2 years.......................................................................................51

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

25 1,4-dioxane in drinking water for 2 years................................................................53

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

27 1,4-dioxane in drinking water for 2 years................................................................54

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

29 water for 2 years.....................................................................................................55

30 Table 4-16. Incidence of pre-and nonneoplastic lesions in male F344/DuCrj rats exposed to 

31 1,4-dioxane vapor by whole-body inhalation for 2 years. ........................................62

32 Table 4-17. Incidence of tumors in male F344/DuCrj rats exposed to 1,4-dioxane vapor by 

33 whole-body inhalation for 2 years. ..........................................................................63

34 Table 4-18. Acute and short-term toxicity studies of 1,4-dioxane...............................................67

35 Table 4-19. Genotoxicity studies of 1,4-dioxane; in vitro...........................................................74

36 Table 4-20. Genotoxicity studies of 1,4-dioxane; mammalian in vivo ........................................78

37 Table 4-21. Oral toxicity studies (noncancer effects) for 1,4-dioxane.........................................84

38 Table 4-22. Inhalation toxicity studies (noncancer effects) for 1,4-dioxane ................................88

39 Table 4-23. Temporal sequence and dose-response relationship for possible key events and 

40 liver tumors in rats and mice ...................................................................................97

41 Table 4-24. Temporal sequence and dose-response relationship for possible key events and 

42 nasal tumors in rats and mice. ...............................................................................100

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

44 1,4-dioxane in drinking water for 2 years..............................................................109
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

viii

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

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

3 in drinking water for 2 years.................................................................................109

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

drinking water for 2 yearsa5 ....................................................................................109

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

7 male and female F344/DuCrj rats exposed to 1,4-dioxane in drinking water for 

8 2 years..................................................................................................................110

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

10 1,4-dioxane considered for indentification of a critical effect. ...............................118

11 Table 5-6. Duration adjusted POD estimates for best fitting BMDS models or 

12 NOAEL/LOAEL from chronic exposure to 1,4-dioxane .......................................119

13 Table 5-7. Incidence of liver, nasal cavity, peritoneal, and mammary gland tumors in rats 

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

15 survival to 12 months) ..........................................................................................126

16 Table 5-8. Incidence of liver, nasal cavity, kidney, peritoneal, and mammary gland, 

17 Zymbal gland, and subcutis tumors in rats exposed to 1,4-dioxane vapors for 2 

18 years. ....................................................................................................................128

19 Table 5-9. Incidence of hepatocellular adenoma or carcinoma in rats and mice exposed to 

20 1,4-dioxane in drinking water for 2 years..............................................................129

21 Table 5-10. Incidence of tumors in F344 male rats exposed to 1,4-dioxane for 104 weeks (6 

22 hours/day, 5 days/week)........................................................................................130

23 Table 5-11. Calculated HEDs for the tumor incidence data used for dose-response 

24 modeling ..............................................................................................................131

25 Table 5-12. BMD HED and BMDLHED values from models fit to tumor incidence data for 

26 rats and mice exposed to 1,4-dioxane in drinking water for 2 years and 

27 corresponding oral CSFs.......................................................................................134

28 Table 5-13. Dose-response modeling summary results for male rat tumors associated with 

29 inhalation exposure to 1,4-dioxane for 2 years ......................................................136

30 Table 5-14. Summary of uncertainty in the 1,4-dioxane cancer risk estimation.......................142

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

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

of the human model using alternative values for physiological flow ratesa33 and 

34 tissue:air partition coefficients............................................................................B-13

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

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

ratesa37 and selected upper and lower boundary values for tissue:air partition 

38 coefficients.........................................................................................................B-20

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

40 1,4-dioxane in drinking water for 2 years..............................................................C-1

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

42 incidence data for cortical tubule degeneration in male and female Osborne43 Mendel rats (NCI, 1978) exposed to 1,4-dioxane in drinking water.......................C-2

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

drinking watera45 .....................................................................................................C-7
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

ix

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

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

3 years.....................................................................................................................C-8

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

5 (Kano, et al., 2009)...............................................................................................D-4

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

7 2009)....................................................................................................................D-5

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

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

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

11 2009)....................................................................................................................D-8

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

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

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

15 et al., 2009).........................................................................................................D-14

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

in female F344 ratsa17 (Kano, et al., 2009) .............................................................D-15

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

in male F344 ratsa19 (Kano, et al., 2009) ................................................................D-18

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

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

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

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

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

25 2009)..................................................................................................................D-31

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

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

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

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

30 female BDF1 mice (Kano, et al., 2009)...............................................................D-32

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

32 2009)..................................................................................................................D-41

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

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

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

36 and nasal tumor incidence data resulting from chronic oral exposure to 

37 1,4-dioxane in rats and mice ...............................................................................D-47

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

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

40 1,4-dioxane in the drinking water for 2 years......................................................D-48

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

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

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

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

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

46 1974) exposed to 1,4-dioxane in the drinking water for 2 years...........................D-54
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

x

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

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

3 drinking water ....................................................................................................D-57

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

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

6 in the drinking water for 2 years .........................................................................D-58

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

8 squamous cell carcinoma in female Osborne-Mendel rats (NCI, 1978) exposed 

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

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

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

12 1,4-dioxane in the drinking water for 2 years......................................................D-68

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

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

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

16 hepatocellular adenoma or carcinoma in female B6C3F1 mice (NCI, 1978) 

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

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

19 hepatocellular adenoma or carcinoma in male B6C3F1 mice (NCI, 1978) 

20 exposed to 1,4-dioxane in drinking water............................................................D-77

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

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

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

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

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

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

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

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

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

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

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

32 2-year JBRC drinking water study in female Crj:BDF1 mice .............................. E-10

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

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

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

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

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

38 1,4-dioxane via inhalation for 2 years. ................................................................ F-13

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

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

41 exposed to 1,4-dioxane vapors (Kasai, et al., 2009)............................................. F-14

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

43 1,4-dioxane via inhalation for 2 years. ................................................................ F-17

44 Table F-4. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

46 1978) exposed to 1,4-dioxane vapors. ................................................................. F-17
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xi

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

2 F344/DuCrj rats exposed to 1,4-dioxane via inhalation for 2 years...................... F-22

3 Table F-6. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

5 male F344/DuCrj rats exposed to 1,4-dioxane vapors (Kasai, et al., 2009). ......... F-22

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

7 F344/DuCrj rats exposed to 1,4-dioxane via inhalation for 2 years...................... F-25

8 Table F-8. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

10 male F344/DuCrj rats exposed to 1,4-dioxane vapors (Kasai, et al., 2009). ........ F-25

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

12 rats exposed to 1,4-dioxane via inhalation for 2 years. ........................................ F-28

13 Table F-10. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

14 incidence data for respiratory metaplasia of olfactory epithelium in male 

15 F344/DuCrj rats (Kasai, et al., 2009) exposed to 1,4-dioxane vapors................... F-29

16 Table F-11. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

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

19 1,4-dioxane vapors.............................................................................................. F-29

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

21 rats exposed to 1,4-dioxane via inhalation for 2 years. ........................................ F-32

22 Table F-13. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

24 (Kasai, et al., 2009) exposed to 1,4-dioxane vapors............................................. F-32

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

26 F344/DuCrj rats exposed to 1,4-dioxane via inhalation for 2 years...................... F-35

27 Table F-15. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

29 male F344/DuCrj rats exposed to 1,4-dioxane vapors (Kasai, et al., 2009). ........ F-35

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

31 rats exposed to 1,4-dioxane via inhalation for 2 years. ........................................ F-38

32 Table F-17. Goodness-of-fit statistics and BMD10 and BMDL10 values from models fit to 

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

34 F344/DuCrj rats exposed to 1,4-dioxane vapors (Kasai, et al., 2009).................. F-38

35 Table G-1. Summary of BMC10 and BMCL10 model results for individual tumor types and 

36 combined tumor analysis for male rats exposed to 1,4-dioxane vapors (Kasai, et 

37 al., 2009) ............................................................................................................G-42

38 Table G-2. Incidence of tumors in male F344/DuCrj rats exposed to 1,4-dioxane vapor by 

39 whole-body inhalation for 2 years. ......................................................................G-43

40 Table G-3. BMDS Multistage cancer dose-response modeling results for the incidence of 

41 nasal squamous cell carcinomas in male rats exposed to 1,4-dioxane vapors for 

42 2-years (Kasai, et al., 2009) ................................................................................G-43

43 Table G-4. BMDS Multistage cancer dose-response modeling results for the incidence of 

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

45 dioxane vapors for 2-years (Kasai, et al., 2009)...................................................G-46
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xii

1 Table G-5. BMDS Multistage cancer dose-response modeling results for the incidence of 

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

3 dioxane vapors for 2-years (Kasai, et al., 2009)...................................................G-48

4 Table G-6. BMDS Multistage cancer dose-response modeling results for the incidence of 

5 peritoneal mesothelioma in male rats exposed to 1,4-dioxane vapors for 2-years 

6 (Kasai, et al., 2009).............................................................................................G-53

7 Table G-7. BMDS Multistage cancer dose-response modeling results for the incidence of 

8 mammary gland fibroadenoma in male rats exposed to 1,4-dioxane vapors for 

9 2-years (Kasai, et al., 2009) ................................................................................G-56

10 Table G-8. BMDS Multistage cancer dose-response modeling results for the incidence of 

11 subcutis fibromas in male rats exposed to 1,4-dioxane vapors for 2-years 

12 (Kasai, et al., 2009).............................................................................................G-58
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xiii

LIST OF FIGURES

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

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

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

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

5 compartments connected via arterial and venous blood flows..................................14

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

7 1,4-dioxane to the liver and the hypothesized MOA(s) for liver carcinogenicity......95

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

9 corresponding applied uncertainty factors and derived RfDs following oral 

10 exposure to 1,4-dioxane. .......................................................................................112

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

12 corresponding applied uncertainty factors and derived RfDs following oral 

13 exposure to 1,4-dioxane. .......................................................................................113

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

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

16 1,4-dioxane...........................................................................................................114

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

18 corresponding applied uncertainty factors and derived sample RfDs following 

19 oral exposure to 1,4-dioxane. ................................................................................115

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

21 applied uncertainty factors and derived sample RfCs following inhalation 

22 exposure to 1,4-dioxane. .......................................................................................123

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

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

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

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

27 administration experiments. ..................................................................................B-5

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

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

30 experiments. .........................................................................................................B-6

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

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

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

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

35 ppm inhalation exposure. ......................................................................................B-8

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

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

38 Figure B-8. EPA-modified Young et al. empirical model prediction (line) of plasma 1,4-

39 dioxane levels in rats following exposure to 1,4-dioxane for 13 weeks 

40 compared to data from Kasai et al. (2008).............................................................B-9

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

42 HEAA levels (right) following re-calibration of the human PBPK model with 

43 tissue:air partition coefficient values. ..................................................................B-13
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xiv

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

2 HEAA levels (right) following re-calibration of the human PBPK model with 

3 tissue:air partition coefficient values. ..................................................................B-14

4 Figure B-11. Predicted and observed blood 1,4-dioxane concentrations (left) and urinary 

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

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

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

8 ppm inhalation exposure. ....................................................................................B-17

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

10 boundaries on partition coefficients with empirical model predictions and 

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

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

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

14 boundaries on partition coefficients with empirical model predictions and 

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

16 urinary HEAA levels (right) from a 6-hour, 50-ppm inhalation exposure. ...........B-20

17 Figure B-15. Predictions of blood 1,4-dioxane concentration following calibration of a 

18 zero-order metabolism rate constant, kLC, to the experimental data......................B-21

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

20 zero-order metabolism rate constant, kLC, to only the exposure phase of the 

21 experimental data................................................................................................B-22

22 Figure B-17. Predictions of blood 1,4-dioxane concentration following simultaneous 

23 calibration of a zero-order metabolism rate constant, kLC, and slowly perfused 

24 tissue:air partition coefficient to the experimental data........................................B-23

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

26 male rats exposed to 1,4-dioxane in drinking water for 2 years to support the 

27 results in Table C-2...............................................................................................C-3

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

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

30 in Table C-2..........................................................................................................C-5

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

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

33 Table C-4..............................................................................................................C-9

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

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

36 results Table C-4.................................................................................................C-11

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

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

39 Table C-4............................................................................................................C-13

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

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

42 in Table C-4........................................................................................................C-15

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

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

45 in Table C-4........................................................................................................C-17
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xv

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

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

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

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

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

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

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

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

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

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

11 F344 rats.............................................................................................................D-24

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

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

14 rats. ....................................................................................................................D-29

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

31 water. .................................................................................................................D-52

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

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

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

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

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

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

38 adenoma in female Osborne-Mendel rats exposed to 1,4-dioxane in drinking 

39 water. .................................................................................................................D-61

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

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

42 water. .................................................................................................................D-64

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

44 squamous cell carcinoma in female Osborne-Mendel rats exposed to 

45 1,4-dioxane in drinking water. ............................................................................D-66
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xvi

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

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

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

4 squamous cell carcinoma in male Osborne-Mendel rats......................................D-71

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

6 adenoma or carcinoma in female B6C3F1 mice...................................................D-75

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

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

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

10 adenoma or carcinoma in male B6C3F1 mice exposed to 1,4-dioxane in 

11 drinking water.....................................................................................................D-80

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

13 male rats exposed to 1,4-dioxane vapors for 2 years to support the results in 

14 Table F-2. ........................................................................................................... F-15

15 Figure F-2. BMD Dichotomous-Hill model of spongiosis hepatis incidence data for male 

16 rats exposed to 1,4-dioxane vapors for 2 years to support the results in Table F17 4. ........................................................................................................................ F-18

18 Figure F-3. BMD Log-Logistic model of spongiosis hepatis incidence data for male rats 

19 exposed to 1,4-dioxane vapors for 2 years to support the results in Table F-4...... F-20

20 Figure F-4. BMD Log-probit model of squamous cell metaplasia of the respiratory 

21 epithelium incidence data for male rats exposed to 1,4-dioxane vapors for 2 

22 years to support the results in Table F-6.............................................................. F-23

23 Figure F-5. BMD Log-probit model of squamous cell hyperplasia of the respiratory 

24 epithelium incidence data for male rats exposed to 1,4-dioxane vapors for 2 

25 years to support the results in Table F-8.............................................................. F-26

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

27 incidence data for male rats exposed to 1,4-dioxane vapors for 2 years to 

28 support the results in Table F-11......................................................................... F-30

29 Figure F-7. BMD Log-Logistic model of atrophy of olfactory epithelium incidence data 

30 for male rats exposed to 1,4-dioxane vapors for 2 years to support the results in 

31 Table F-13. ......................................................................................................... F-33

32 Figure F-8. BMD Log-logistic model of hydropic change of lamina propria (nasal cavity) 

33 incidence data for male rats exposed to 1,4-dioxane vapors for 2 years to 

34 support the results in Table F-16......................................................................... F-36

35 Figure F-9. BMD Log-logistic model of sclerosis of lamina propria (nasal cavity) 

36 incidence data for male rats exposed to 1,4-dioxane vapors for 2 years to 

37 support the results in Table F-18......................................................................... F-40

Figure G-1. Multistage model (1st 38 -degree) for male rat nasal squamous cell carcinomas........G-44

Figure G-2. Multistage model (1st 39 -degree) for male rat hepatocellular adenomas and 

40 carcinomas..........................................................................................................G-46

Figure G-3. Multistage model (2nd 41 -degree) for male rat renal cell carcinomas and Zymbal 

42 gland adenomas. .................................................................................................G-49

Figure G-4. Multistage model (3rd 43 -degree) for male rat renal cell carcinomas. .......................G-51

Figure G-5. Multistage model (1st 44 -degree) for male rat peritoneal mesotheliomas..................G-54

Figure G-6. Multistage model (1st 45 -degree) for male rat mammary gland fibroadenoma..........G-56
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xvii

Figure G-7. Multistage model (1st 1 -degree) for male rat subcutis fibroma (high dose 

2 dropped). ............................................................................................................G-59
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xviii

LIST OF ABBREVIATIONS AND ACRONYMS

1 AIC Akaike‘s Information Criterion

2 ALP alkaline phosphatase

3 ALT alanine aminotransferase

4 AST aspartate aminotransferase

5 ATSDR Agency for Toxic Substances and Disease Registry

6 BMC benchmark concentration

7 BMCL benchmark concentration, lower 95% confidence limit

8 BMCL10 benchmark concentration, lower 95% confidence limit at 10% extra risk

9 BMD benchmark dose

10 BMD10 benchmark dose at 10% extra risk

11 BMD30 benchmark dose at 30% extra risk

12 BMD50 benchmark dose at 50% extra risk

13 BMDL benchmark dose, lower 95% confidence limit

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

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

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

17 BMDS Benchmark Dose Software

18 BMR benchmark response

19 BrdU 5-bromo-2‘-deoxyuridine

20 BUN blood urea nitrogen

21 BW(s) body weight(s)

22 CASE computer automated structure evaluator

23 CASRN Chemical Abstracts Service Registry Number

24 CHO Chinese hamster ovary (cells)

25 CI confidence interval(s)

26 CNS central nervous system

27 CPK creatinine phosphokinase

28 CREST antikinetochore

29 CSF cancer slope factor

30 CV concentration in venous blood

31 CYP450 cytochrome P450

32 DEN diethylnitrosamine

33 FISH fluorescence in situ hybridization

34 G-6-Pase glucose-6-phosphatase

35 GC gas chromatography

36 GGT γ-glutamyl transpeptidase

37 GST-P glutathione S-transferase placental form

38 HEAA β-hydroxyethoxy acetic acid

39 HED(s) human equivalent dose(s)

40 HPLC high-performance liquid chromatography

41 HSDB Hazardous Substances Data Bank

42 Hz Hertz

43 IARC International Agency for Research on Cancer

44 i.p. intraperitoneal
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xix

1 i.v. intravenous

2 IRIS Integrated Risk Information System

3 JBRC Japan Bioassay Research Center

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

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

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

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

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

9 kOC soil organic carbon-water portioning coefficient

10 LAP leucine aminopeptidase

11 LD50 median lethal dose

12 LDH lactate dehydrogenase

13 LOAEL lowest-observed-adverse-effect-level

14 MCH mean corpuscular hemoglobin

15 MCV mean corpuscular volume

16 MOA mode of action

17 MS mass spectrometry, multi-stage

18 MTD maximum tolerated dose

19 MVK Moolgavkar-Venzon-Knudsen (model)

20 NCE normochromatic erythrocyte

21 NCI National Cancer Institute

22 ND no data, not detected

23 NE not estimated

24 NOAEL no-observed-adverse-effect-level

25 NRC National Research Council

26 NTP National Toxicology Program

27 OCT ornithine carbamyl transferase

28 ODC ornithine decarboxylase

29 OECD Organization for Economic Co-operation and Development

30 PB blood:air partition coefficient

31 PBPK physiologically based pharmacokinetic

32 PC partition coefficient

33 PCB polychlorinated biphenyl

34 PCE polychromatic erythrocyte

35 PFA fat:air partition coefficient

36 PLA liver:air partition coefficient

37 POD point of departure

38 ppm parts per million

39 PRA rapidly perfused tissue:air partition coefficient

40 PSA slowly perfused tissue:air partition coefficient

41 QCC normalized cardiac output

42 QPC normalized alveolar ventilation rate 

43 RBC red blood cell

44 RfC inhalation reference concentration

45 RfD oral reference dose

46 SCE sister chromatid exchange
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xx

1 SDH sorbitol dehydrogenase

2 SMR standardized mortality ratio

3 SRC Syracuse Research Corporation

4 TPA 12-O-tetradecanoylphorbol-13-acetate

5 TWA time-weighted average

6 UF uncertainty factor

7 UNEP United Nations Environment Programme

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

9 V volts

10 VAS visual analogue scale

11 Vd volume of distribution

12 Vmax maximal rate of metabolism

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

14 VOC(s) volatile organic compound(s)

15 WBC white blood cell

χ

2

16 Chi-squared
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xxi

1 FOREWORD

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

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

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

5 nature of 1,4-dioxane.

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

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

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

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

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

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

12 risk assessment process. 

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

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

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

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

17 1,4-dioxane through the inhalation route of exposure are available that were not included in the 

18 1,4-dioxane assessment that was posted on the IRIS database in 2010 (U.S. EPA, 2010).

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

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

21 text in the document. The entire document is provided for completeness.
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xxii

1 AUTHORS, CONTRIBUTORS, AND REVIEWERS

2 CHEMICAL MANAGERS/AUTHORS

3

4 Patricia Gillespie, Ph.D.

5 National Center for Environmental Assessment

6 U.S. Environmental Protection Agency

7 Research Triangle Park, NC

8

9 Eva D. McLanahan, Ph.D. 

10 Lieutenant Commander, U.S. Public Health Service

11 National Center for Environmental Assessment

12 U.S. Environmental Protection Agency

13 Research Triangle Park, NC

14

15 Reeder Sams II, Ph.D.

16 National Center for Environmental Assessment

17 U.S. Environmental Protection Agency

18 Research Triangle Park, NC 

19

20 AUTHORS AND CONTRIBUTORS

21

22 J. Allen Davis, MSPH

23 National Center for Environmental Assessment

24 U.S. Environmental Protection Agency

25 Research Triangle Park, NC

26

27 Hisham El-Masri, Ph.D.

28 National Health and Environmental Effects Research Laboratory 

29 U.S. Environmental Protection Agency

30 Research Triangle Park, NC 

31

32 Jeff S. Gift, Ph.D.

33 National Center for Environmental Assessment

34 U.S. Environmental Protection Agency

35 Research Triangle Park, NC

36

37 Karen Hogan

38 National Center for Environmental Assessment

39 U.S. Environmental Protection Agency

40 Washington, DC 

41

42 Leonid Kopylev, Ph.D.

43 National Center for Environmental Assessment

44 U.S. Environmental Protection Agency

45 Washington, DC

46
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xxiii

1 William Lefew, Ph.D.

2 National Health and Environmental Effects Research Laboratory 

3 U.S. Environmental Protection Agency

4 Research Triangle Park, NC 

5

6 Fernando Llados

7 Environmental Science Center

8 Syracuse Research Corporation

9 Syracuse, NY 

10

11 Michael Lumpkin, Ph.D.

12 Environmental Science Center

13 Syracuse Research Corporation

14 Syracuse, NY 

15

16 Allan Marcus, Ph.D.

17 National Center for Environmental Assessment

18 U.S. Environmental Protection Agency

19 Research Triangle Park, NC 

20

21 Marc Odin, Ph.D.

22 Environmental Science Center

23 Syracuse Research Corporation

24 Syracuse, NY 

25

26 Susan Rieth 

27 National Center for Environmental Assessment

28 U.S. Environmental Protection Agency

29 Washington, DC 

30

31 Andrew Rooney, Ph.D.*

32 National Center for Environmental Assessment

33 U.S. Environmental Protection Agency

34 Research Triangle Park, NC 

35 *Currently at National Toxicology Program 

36 National Institute of Environmental Health Sciences 

37 Research Triangle Park, NC

38

39 Paul Schlosser, Ph.D.

40 National Center for Environmental Assessment

41 U.S. Environmental Protection Agency

42 Research Triangle Park, NC 

43

44 John Stanek, Ph.D.

45 National Center for Environmental Assessment

46 U.S. Environmental Protection Agency

47 Research Triangle Park, NC
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xxiv

1 Julie Stickney, Ph.D.

2 Environmental Science Center

3 Syracuse Research Corporation

4 Syracuse, NY 

5

6 John Vandenberg, Ph.D.

7 National Center for Environmental Assessment

8 U.S. Environmental Protection Agency

9 Research Triangle Park, NC 

10

11 Debra Walsh, M.S.

12 National Center for Environmental Assessment

13 U.S. Environmental Protection Agency

14 Research Triangle Park, NC 

15

16 REVIEWERS

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

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

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

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

21 Appendix A.

22

23 INTERNAL EPA REVIEWERS (ORAL ASSESSMENT)

24

25 Anthony DeAngelo, Ph.D.

26 National Health and Environmental Effects Research Laboratory 

27 Office of Research and Development 

28

29 Nagu Keshava, Ph.D.

30 National Center for Environmental Assessment 

31 Office of Research and Development 

32

33 Jason Lambert, Ph.D.

34 National Center for Environmental Assessment 

35 Office of Research and Development 

36

37 Connie Meacham, M.S.

38 National Center for Environmental Assessment

39 Research Triangle Park, NC 

40
DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

xxv

1 Douglas Wolf, Ph.D.

2 National Health and Environmental Effects Research Laboratory 

3 Office of Research and Development 

4

5 EXTERNAL PEER REVIEWERS (ORAL ASSESSMENT)

6

7 George V. Alexeeff, Ph.D., DABT

8 Office of Environmental Health Hazard Assessment (OEHHA)

9 California EPA

10

11 Bruce C. Allen, M.S.

12 Bruce Allen Consulting

13

14 James V. Bruckner, Ph.D.

15 Department of Pharmaceutical and Biomedical Sciences

16 College of Pharmacy

17 The University of Georgia

18

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

20 Center for Human Health Assessment

21 The Hamner Institutes for Health Sciences

22

23 Lena Ernstgård, Ph.D.

24 Institute of Environmental Medicine

25 Karolinska Institutet

26

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

28 Children‘s Hospital at Montefiore

29 Albert Einstein College of Medicine of Yeshiva University

30

31 Kannan Krishnan, Ph.D., DABT

32 Inter-University Toxicology Research Center (CIRTOX)

33 Université de Montréal

34

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

36 Department of Physiology and Pharmacology

37 College of Veterinary Medicine (retired)

38 The University of Georgia

39

40 EXTERNAL PEER REVIEWERS (INHALATION ASSESSMENT)

41 TO BE DETERMINED

42
1

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1. INTRODUCTION

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

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

3 1,4-dioxane. IRIS Summaries may include oral reference dose (RfD) and inhalation reference 

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

5 assessment.

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

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

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

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

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

deleterious effects during a lifetime. The inhalation RfC (expressed in units of mg/m311 ) is 

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

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

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

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

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

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

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

19 derived for chronic exposure duration.

20 The carcinogenicity assessment provides information on the carcinogenic hazard 

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

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

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

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

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

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

plausible upper bound on the estimate of risk per μg/m327 air breathed.

28 Development of these hazard identification and dose-response assessments for 

29 1,4-dioxane has followed the general guidelines for risk assessment as set forth by the National 

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

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

 

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

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Guidelines for the Health Risk Assessment of Chemical Mixtures (U.S. EPA, 1986c), Guidelines 

2 for Mutagenicity Risk Assessment (U.S. EPA, 1986b), Recommendations for and Documentation 

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

4 Developmental Toxicity Risk Assessment (U.S. EPA, 1991), Interim Policy for Particle Size and 

5 Limit Concentration Issues in Inhalation Toxicity (U.S. EPA, 1994a), Methods for Derivation of 

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

7 1994b), Use of the Benchmark Dose Approach in Health Risk Assessment (U.S. EPA, 1995), 

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

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

10 Characterization (U.S. EPA, 2000b), Benchmark Dose Technical Guidance Document (External 

11 Review Draft) (U.S. EPA, 2000a), Supplementary Guidance for Conducting Health Risk 

12 Assessment of Chemical Mixtures (U.S. EPA, 2000c), A Review of the Reference Dose and 

13 Reference Concentration Processes (U.S. EPA, 2002a), Guidelines for Carcinogen Risk 

14 Assessment (U.S. EPA, 2005a), Supplemental Guidance for Assessing Susceptibility from Early15 Life Exposure to Carcinogens (U.S. EPA, 2005b), Science Policy Council Handbook: Peer 

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

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

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

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

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

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

22 2009 for the oral assessment and through March 2011 for the inhalation assessment. 
3

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

2. CHEMICAL AND PHYSICAL INFORMATION

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

2 odor (Hawley & Lewis Rj Sr, 2001; Lewis, 2000). Synonyms include diethylene ether, 

3 1,4-diethylene dioxide, diethylene oxide, dioxyethylene ether, and dioxane (Hawley & Lewis 

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

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

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

 

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

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

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

and the Integrated Risk Information System (IRIS).
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 Encyclopedia of Chemicals, 

Drugs, and Biologicals, 2001)

Chemical formula: C4H8O2 (The Merck Index: An Encyclopedia of 

Chemicals, Drugs, and Biologicals, 2001)

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

Chemicals, 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 & Lewis Rj Sr, 2001)

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

Log Kow: –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)

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

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

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

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

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

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

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

4 pressures of 130–200°C and 188–825 mmHg, respectively (Surprenant, 2002). During the years 

5 1986 and 1990, the U.S. production of 1,4-dioxane reported by manufacturers was within the 

6 range of 10–50 million pounds (U.S. EPA, 2002b). The production volume reported during the 

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

8 1–10 million pounds (U.S. EPA, 2002b). 

9 Historically, 1,4-dioxane has been used as a stabilizer for the solvent 1,1,1-trichloro10 ethane (Surprenant, 2002). However, this use is no longer expected to be important due to the 

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

12 phase-out of 1,1,1-trichloroethane production in the U.S. ("Amendments to the Clean Air Act. 

13 Sec. 604. Phase-out of production and consumption of class I substances," 1990; ATSDR, 2007; 

14 U.N. Environment Programme, 2000). 1,4-Dioxane is a contaminant of some ingredients used in 
5

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 the manufacture of personal care products and cosmetics. 1,4-Dioxane is also used as a solvent 

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

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

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

5 Biologicals, 2001). 1,4-Dioxane has been used as a solvent in the formulation of inks, coatings, 

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

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

8 monomers (Surprenant, 2002).

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

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

11 hydroxyl radicals (HSDB, 2007; Surprenant, 2002). The estimated half-life for this reaction is 

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

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

14 1990). 1,4-Dioxane is not expected to undergo direct photolysis (Wolfe & Jeffers, 2000). 

15 1,4-Dioxane is primarily photooxidized to 2-oxodioxane and through reactions with nitrogen 

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

17 Nielsen, & Wallington, 1997). 1,4-Dioxane is expected to be highly mobile in soil based on its 

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

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

20 (HSDB, 2007). The estimated bioconcentration factor value indicates that 1,4-dioxane will not 

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

22 1,4-Dioxane is not expected to undergo hydrolysis or to biodegrade readily in the environment 

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

process for moist soil and surface water. Based on a Henry's Law constant of 4.8×10-624

atm-m

3

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

26 from a model lake is 56 days (ACS, 1990; HSDB, 2007; Park, et al., 1987). 1,4-Dioxane may be 

27 more persistent in groundwater where volatilization is hindered.

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

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

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

31 Tanabe, Kawata, & Katami, 2003). 1,4-Dioxane has been detected in contaminated surface and 

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

33 Wilbur, Holler, Richter, & Stevens, 1996). 
6

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

3. TOXICOKINETICS

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

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

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

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

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

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

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

8 with nonlinear toxicokinetics are not known. 

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

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

3.1. ABSORPTION

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

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

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

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

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

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

17 et al. (1977) reported 6-hour inhalation exposures of adult volunteers to 50 ppm of 1,4-dioxane

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

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

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

21 concentration of 50 ppm, uptake of 1,4-dioxane into plasma was rapid and approached steady22 state conditions by 6 hours. The authors reported a calculated absorbed dose of 5.4 mg/kg. 

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

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

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

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

27 1,4-dioxane ratio of over 3,100:1 (J. D. Young, W. H. Braun, & P. J. Gehring, 1978a; J. D. 

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

29 exposure period averaged 7.3 μg/mL. The authors calculated an absorbed 1,4-dioxane dose of 

 

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).
7

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 71.9 mg/kg; however, the lack of exhaled breath data and dynamic exposure chamber precluded 

2 the accurate determination of the absorbed fraction of inhaled 1,4-dioxane.

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

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

10–1,000 mg/kg of [14 5 C]-1,4-dioxane given as a single dose or as 17 consecutive daily doses 

6 (Young, et al., 1978a; Young, et al., 1978b). Cumulative recovery of radiolabel in the feces was 

7 <1–2% of administered dose regardless of dose level or frequency. 

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

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

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

(0.3% of applied dose). [14 11 C]-1,4-Dioxane was dissolved in lotion, applied to the excised skin in 

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

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

14 decreased the small amount available for skin absorption. 

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

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

1981). In this study, Rhesus monkeys were exposed to [14 17 C]-1,4-dioxane in methanol or skin 

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

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

3.2. DISTRIBUTION 

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

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

Mikheev et al. (1990) studied the distribution of [14 22 C]-1,4-dioxane in the blood, liver, 

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

24 (i.p.) injection of approximately one-tenth the median lethal dose (LD50) (actual dose not 

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

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

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

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

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

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

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

32 water-soluble 1,4-dioxane), the tissue concentrations of radiolabel were not reported, and data 

33 were collected from so few time points.

Woo et al. (1977) administered i.p. doses of [334 H]-1,4-dioxane (5 mCi/kg body weight 

35 [BW]) to male Sprague Dawley rats with and without pretreatment using mixed-function oxidase 
8

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

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

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

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

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

6 residual blood to radiolabel measurements is unknown, though loss of 1,4-dioxane from tissues 

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

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

9 16 hours after dosing, peak covalent binding percentages were observed in whole blood (3.1%), 

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

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

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

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

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

15 microsomal (33.4%) fractions. Pretreatment with inducers of mixed-function oxidase activity 

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

3.3. METABOLISM 

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

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

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

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

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

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

23 unchanged 1,4-dioxane in the urine of Sprague Dawley rats dosed with 1,000 mg/kg of 

uniformly labeled 1,4-[

14 24 C]dioxane. In fact, toxicokinetic studies of 1,4-dioxane in humans and 

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

26 technique that converted HEAA to the more volatile 1,4-dioxane-2-one prior to gas 

27 chromatography (GC); however, it is still unclear as to whether HEAA or 1,4-dioxane-2-one is 

28 the major metabolite of 1,4-dioxane.

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

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

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

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

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

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

35 chloride were effective in significantly increasing and decreasing, respectively, the appearance of 
9

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 HEAA in the urine of male Sprague Dawley rats following 3 g/kg i.p. dose (Woo, Argus, & 

2 Arcos, 1977a, 1978). 1,4-Dioxane itself induced CYP450-mediated metabolism of several 

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

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

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

6 as a minor metabolite in Sprague Dawley rat urine following a single 1,000 mg/kg gavage dose 

7 of 1,4-dioxane (Braun & Young, 1977). Additionally, i.p. injection of 100–400 mg/kg 

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

9 & Arcos, 1977b). 

Source: Adapted with permission from 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 proposed pathways do 

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

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

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

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

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

13 volunteers exposed to 50 ppm for 6 hours (Young, et al., 1977), over 99% of inhaled 1,4-dioxane

14 (assuming negligible exhaled excretion) appeared in the urine as HEAA. The linear elimination 
10

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

2 nonsaturated, first-order process at this exposure level.

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

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

5 (Young, et al., 1978a; Young, et al., 1978b). 1,4-Dioxane metabolism in rats was a saturable 

process, as exhibited by oral and i.v. exposures to various doses of [14 6 C]-1,4-dioxane (Young, et 

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

of 3, 10, 30, 100, 300, or 1,000 mg [

14 8 C]-1,4-dioxane/kg demonstrated a dose-related shift from 

9 linear, first-order to nonlinear, saturable metabolism of 1,4-dioxane between plasma 1,4-dioxane

10 levels of 30 and 100 μg/mL (Figure 3-2). Similarly, in rats given, via gavage in distilled water, 

10, 100, or 1,000 mg [

14C]-1,4-dioxane/kg singly or 10 or 1,000 mg [14 11 C]-1,4-dioxane/kg in 

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

while radiolabel in expired air increased. Specifically, with single [14 13 C]-1,4-dioxane/kg doses, 

14 urinary radiolabel decreased from 99 to 76% and expired 1,4-dioxane increased from <1 to 25% 

15 as dose increased from 10 to 1,000 mg/kg. Likewise, with multiple daily doses 10 or 1,000 mg

[

14 16 C]-1,4-dioxane/kg, urinary radiolabel decreased from 99 to 82% and expired 1,4-dioxane

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

18 urinary and expired radiolabel support the notion that 1,4-dioxane may induce its own 

19 metabolism.

20 Induction of 1,4-dioxane metabolism is quantitatively illustrated by examining plasma 

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

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

23 100, 200, 400, 1,600, and 3,200 ppm. Plasma levels of 1,4-dioxane linearly increased with 

24 increasing inhalation concentration, suggesting that metabolic saturation was not achieved during 

25 the course of the experiments for plasma levels up to 730 and 1,054 μg/mL in male and female

26 rats, respectively, at the highest exposure concentration (3,200 ppm). In contrast, Young et al. 

27 (1978a) single dose experiments showed possible saturation of metabolism at plasma levels of 

28 100 μg/mL. Therefore, lack of the metabolic saturation of 1,4-dioxane found in the Kasai et al. 

29 (2008) study is likely attributed to enhanced metabolism by the induction of P450 enzymes, 

30 including CYP2E1, by 13 weeks of repeated inhalation exposure to 1,4-dioxane at concentrations 

31 up to 3,200 ppm (Kasai, et al., 2008).

32
11

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 xaxis is time (hr)]

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

2 following acute oral administration by gavage or drinking water (Nannelli, De Rubertis, Longo, 

3 & Gervasi, 2005). Male Sprague Dawley rats were exposed to either 2,000 mg/kg 1,4-dioxane

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

5 for 10 days. Both exposures resulted in significantly increased CYP2B1/2, CYP2C11, and 

6 CYP2E1 activities in hepatic microsomes. The gavage exposure alone resulted in increased 

7 CYP3A activity. The increase in 2C11 activity was unexpected, as that isoform has been 

8 observed to be under hormonal control and was typically suppressed in the presence of 2B1/2 

9 and 2E1 induction. In the male rat, hepatic 2C11 induction is associated with masculine pulsatile 

10 plasma profiles of growth hormone (compared to the constant plasma levels in the female), 

11 resulting in masculinization of hepatocyte function (Waxman, Pampori, Ram, Agrawal, & 

12 Shapiro, 1991). The authors postulated that 1,4-dioxane may alter plasma growth hormone 

13 levels, resulting in the observed 2C11 induction. However, growth hormone induction of 2C11 
12

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 is primarily dependent on the duration between growth hormone pulses and secondarily on 

2 growth hormone plasma levels (Agrawal & Shapiro, 2000; Waxman, et al., 1991). Thus, the 

3 induction of 2C11 by 1,4-dioxane may be mediated by changes in the time interval between 

4 growth hormone pulses rather than changes in growth hormone levels. This may be 

5 accomplished by 1,4-dioxane temporarily influencing the presence of growth hormone cell 

6 surface binding sites (Agrawal & Shapiro, 2000). However, no studies are available to confirm 

7 the influence of 1,4-dioxane on either growth hormone levels or changes in growth hormone

8 pulse interval. 

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

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

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

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

13 2E1 genes. The lack of increased mRNA in hepatocytes suggests that induction is regulated via 

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

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

3.4. ELIMINATION

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

17 urine was in the form of HEAA (Young, et al., 1976). The elimination half-life was 59 minutes

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

19 1,4-dioxane and 47% of urinary HEAA excreted within 6 hours of onset of exposure (Young, et 

20 al., 1977). There are no data for 1,4-dioxane elimination in humans from oral exposures.

21 Elimination of 1,4-dioxane in rats (Young, et al., 1978a; Young, et al., 1978b) was 

22 primarily via urine. As comparably assessed in humans, the elimination half-life in rats exposed 

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

given single daily doses of 10, 100, or 1,000 mg [

14 24 C]-1,4-dioxane/kg or multiple doses of 10 or 

1,000 mg [

14 25 C]-1,4-dioxane/kg, urinary radiolabel ranged from 99% down to 76% of total 

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

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

dose from 0.4 to 25% while expired 14 28 CO2 changed little (between 2 and 3%) across doses. The 

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

[

14C]-1,4-dioxane/kg. Higher levels of 14 30 CO2 relative to 1,4-dioxane were measured in expired 

air of the 10 mg/kg group, while higher levels of expired 1,4-dioxane relative to 14 31 CO2 were 

32 measured in the 1,000 mg/kg group.
13

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

3.5. PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELS

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

2 1,4-dioxane in rats (Leung & Paustenbach, 1990; Reitz, McCroskey, Park, Andersen, & Gargas, 

3 1990; Sweeney et al., 2008), mice (Sweeney, et al., 2008), humans (Leung & Paustenbach, 1990; 

4 Reitz, et al., 1990; Sweeney, et al., 2008), and lactating women (Fisher, Mahle, Bankston, 

5 Greene, & Gearhart, 1997). Each of the models simulates the body as a series of compartments 

6 representing tissues or tissue groups that receive blood from the central vascular compartment 

7 (Figure 3-3). Modeling was conducted under the premise that transfers of 1,4-dioxane between 

8 blood and tissues occur sufficiently fast to be effectively blood flow-limited, which is consistent 

9 with the available data (Ramsey & Andersen, 1984). Blood time course and metabolite 

10 production data in rats and humans suggest that absorption and metabolism are accomplished 

11 through common mechanisms in both species (1978a; Young, et al., 1978b; Young, et al., 1977), 

12 allowing identical model structures to be used for both species (and by extension, for mice as 

13 well). In all three models, physiologically relevant, species-specific parameter values for tissue 

14 volume, blood flow, and metabolism and elimination are used. The models and supporting data 

15 are reviewed below, from the perspective of assessing their utility for predicting internal 

16 dosimetry and for cross-species extrapolation of exposure-response relationships for critical 

17 neoplastic and nonneoplastic endpoints (also see Appendix B).
14

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

limited tissue compartments connected via arterial and venous blood flows.

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

inhaled and intravenously infused chemicals enter directly into the arterial and 

venous blood pools, respectively.

3.5.1. Available Pharmacokinetic Data

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

2 (1978a; 1978b; 1977), Mikheev et al. (1990), and Woo et al. (1977; 1977b). Young et al. 

(1978a; 1978b) studied the disposition of radiolabeled [14 3 C]-1,4-dioxane in adult male 

4 Sprague Dawley rats following i.v., inhalation, and single and multiple oral gavage exposures. 

5 Plasma concentration-time profiles were reported for i.v. doses of 3, 10, 30, 100, and 

1,000 mg/kg. In addition, exhaled 14 6 CO2 and urinary 1,4-dioxane and HEAA profiles were 

7 reported following i.v. doses of 10 and 1,000 mg/kg. The plasma 1,4-dioxane concentration-time 

8 course, cumulative urinary 1,4-dioxane and cumulative urinary HEAA concentrations were 

9 reported following a 6-hour inhalation exposure to 50 ppm. Following oral gavage doses of 10–

10 1,000 mg/kg, percentages of total orally administered radiolabel were measured in urine, feces, 

11 expired air, and the whole body.

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

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

14 (Young, et al., 1978b). Although it may be concluded that the rate of oral absorption was high 
15

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

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

3 exposure.

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

5 oral routes (Young, et al., 1978a; Young, et al., 1978b). Elimination of 1,4-dioxane from plasma 

6 appeared to be linear following i.v. doses of 3-30 mg/kg, but was nonlinear following doses of 

100–1,000 mg/kg. Accordingly, 10 mg/kg i.v. doses resulted in higher concentrations of 14 7 CO2

8 (from metabolized 1,4-dioxane) in expired air relative to unchanged 1,4-dioxane, while 

1,000 mg/kg i.v. doses resulted in higher concentrations of expired 1,4-dioxane relative to 14 9 CO2. 

10 Thus, at higher i.v. doses, a higher proportion of unmetabolized 1,4-dioxane is available for 

11 exhalation. Taken together, the i.v. plasma and expired air data from Young et al. (1978a; 

12 1978b) corroborate previous studies describing the saturable nature of 1,4-dioxane metabolism in 

13 rats (1977; Woo, Argus, et al., 1977b) and are useful for optimizing metabolic parameters (Vmax

14 and Km) in a PBPK model. 

15 Similarly, increasing single or multiple oral doses of 10–1,000 mg/kg resulted in 

16 increasing percentage of 1,4-dioxane in exhaled air and decreasing percentage of radiolabel 

17 (either as 1,4-dioxane or a metabolite) in the urine, with significant differences in both metrics 

18 being observed between doses of 10 and 100 mg/kg (Young, et al., 1978a; Young, et al., 1978b). 

19 These data identify the region (10–100 mg/kg) in which oral exposures will result in nonlinear 

20 metabolism of 1,4-dioxane and can be used to test whether metabolic parameter value estimates 

21 derived from i.v. dosing data are adequate for modeling oral exposures. 

22 Post-exposure plasma data from a single 6-hour, 50 ppm inhalation exposure in rats were 

23 reported (Young, et al., 1978a; Young, et al., 1978b). The observed linear elimination of 

24 1,4-dioxane after inhalation exposure suggests that, via this route, metabolism is in the linear 

25 region at this exposure level.

26 The only human data adequate for use in PBPK model development (Young, et al., 1977)

27 come from adult male volunteers exposed to 50 ppm 1,4-dioxane for 6 hours. Plasma 

28 1,4-dioxane and HEAA concentrations were measured both during and after the exposure period, 

29 and urine concentrations were measured following exposure. Plasma levels of 1,4-dioxane

30 approached steady-state at 6 hours. HEAA data were insufficient to describe the appearance or 

31 elimination of HEAA in plasma. Data on elimination of 1,4-dioxane and HEAA in the urine up 

32 to 24 hours from the beginning of exposure were reported. At 6 hours from onset of exposure, 

33 approximately 90% and 47% of the cumulative (0–24 hours) urinary 1,4-dioxane and HEAA, 

34 respectively, were measured in the urine. The ratio of HEAA to 1,4-dioxane in urine 24 hours 

35 after onset of exposure was 192:1 (similar to the ratio of 118:1 observed by Young et al. (1976)

36 in workers exposed to 1.6 ppm for 7.5 hours), indicating extensive metabolism of 1,4-dioxane 

37 As with Sprague Dawley rats, the elimination of 1,4-dioxane from plasma was linear across all 
16

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 observations (6 hours following end of exposure), suggesting that human metabolism of 

2 1,4-dioxane is linear for a 50 ppm inhalation exposure to steady-state. Thus, estimation of 

3 human Vmax and Km from these data will introduce uncertainty into internal dosimetry performed 

4 in the nonlinear region of metabolism. 

5 Further data were reported for the tissue distribution of 1,4-dioxane in rats. Mikheev 

et al. (1990) administered i.p. doses of [

14 6 C]-1,4-dioxane to white rats (strain not reported) and 

7 reported time-to-peak blood, liver, kidney, and testes concentrations. They also reported ratios 

8 of tissue to blood concentrations at various time points after dosing. Woo et al. (1977; 1977b)

administered i.p. doses of [

14 9 C]-1,4-dioxane to Sprague Dawley rats and measured radioactivity 

10 levels in urine. However, since i.p. dosing is not relevant to human exposures, these data are of 

11 limited use for PBPK model development.

3.5.2. Published PBPK Models for 1,4-Dioxane

3.5.2.1. Leung and Paustenbach 

12 Leung and Paustenbach (1990) developed a PBPK model for 1,4-dioxane and its primary 

13 metabolite, HEAA, in rats and humans. The model, based on the structure of a PBPK model for 

14 styrene (Ramsey & Andersen, 1984), consists of a central blood compartment and four tissue 

15 compartments: liver, fat, slowly perfused tissues (mainly muscle and skin), and richly perfused 

16 tissues (brain, kidney, and viscera other than the liver). Tissue volumes were calculated as 

17 percentages of total BW, and blood flow rates to each compartment were calculated as 

18 percentages of cardiac output. Equivalent cardiac output and alveolar ventilation rates were 

19 allometrically scaled to a power (0.74) of BW for each species. The concentration of 

20 1,4-dioxane in alveolar blood was assumed to be in equilibrium with alveolar air at a ratio equal 

21 to the experimentally measured blood:air partition coefficient. Transfers of 1,4-dioxane between 

22 blood and tissues were assumed to be blood flow-limited and to achieve rapid equilibrium 

23 between blood and tissue, governed by tissue:blood equilibrium partition coefficients. The latter 

24 were derived from the quotient of blood:air and tissue:air partition coefficients, which were 

25 measured in vitro (Leung & Paustenbach, 1990) for blood, liver, fat, and skeletal muscle (slowly 

26 perfused tissue). Blood:air partition coefficients were measured for both humans and rats. Rat 

27 tissue:air partition coefficients were used as surrogate values for humans, with the exception of 

28 slowly perfused tissue:blood, which was estimated by optimization to the plasma time-course 

29 data. Portals of entry included i.v. infusion (over a period of 36 seconds) into the venous blood, 

30 inhalation by diffusion from the alveolar air into the lung blood at the rate of alveolar ventilation, 

31 and oral administration via zero-order absorption from the gastrointestinal tract to the liver. 

32 Elimination of 1,4-dioxane was accomplished through pulmonary exhalation and saturable 

33 hepatic metabolism. Urinary excretion of HEAA was assumed to be instantaneous with the 

34 generation of HEAA from the hepatic metabolism of 1,4-dioxane.
17

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 The parameter values for hepatic metabolism of 1,4-dioxane, Vmax and Km, were 

2 optimized and validated against plasma and/or urine time course data for 1,4-dioxane and HEAA 

3 in rats following i.v. and inhalation exposures and humans following inhalation exposure (1978a; 

4 1978b; Young, et al., 1977); the exact data (i.e., i.v., inhalation, or both) used for the 

5 optimization and calibration were not reported. Although the liver and fat were represented by 

6 tissue-specific compartments, no tissue-specific concentration data were available for model 

7 development, raising uncertainty as the model‘s ability to adequately predict exposure to these 

8 tissues. The human inhalation exposure of 50 ppm for 6 hours (Young, et al., 1977) was 

9 reported to be in the linear range for metabolism; thus, uncertainty exists in the ability of the 

10 allometrically-scaled value for the human metabolic Vmax to accurately describe 1,4-dioxane 

11 metabolism from exposures resulting in metabolic saturation. Nevertheless, these values resulted 

12 in the model producing good fits to the data. For rats, the values for Vmax had to be adjusted 

13 upwards by a factor of 1.8 to reasonably simulate exposures greater than 300 mg/kg. The model 

14 authors attributed this to metabolic enzyme induction by high doses of 1,4-dioxane.

3.5.2.2. Reitz et al. 

15 Reitz et al. (1990) developed a model for 1,4-dioxane and HEAA in the mouse, rat, and 

16 human. This model, also based on the styrene model of Ramsey and Andersen (1984), included 

17 a central blood compartment and compartments for liver, fat, and rapidly and slowly perfused 

18 tissues. Tissue volumes and blood flow rates were defined as percentages of total BW and 

19 cardiac output, respectively. Physiological parameter values were similar to those used by 

20 Andersen et al. (1987), except that flow rates for cardiac output and alveolar ventilation were 

21 doubled in order to produce a better fit of the model to human blood level data (Young, et al., 

22 1977). Portals of entry included i.v. injection into the venous blood, inhalation, oral bolus 

23 dosing, and oral dosing via drinking water. Oral absorption of 1,4-dioxane was simulated, in all 

24 three species, as a first-order transfer to liver (halftime approximately 8 minutes). 

25 Alveolar blood levels of 1,4-dioxane were assumed to be in equilibrium with alveolar air 

26 at a ratio equal to the experimentally measured blood:air partition coefficient. Transfers of 

27 1,4-dioxane between blood and tissues were assumed to be blood flow-limited and to achieve 

28 rapid equilibrium between blood and tissue, governed by tissue:blood equilibrium partition 

29 coefficients. These coefficients were derived by dividing experimentally measured (Leung & 

30 Paustenbach, 1990) in vitro blood:air and tissue:air partition coefficients for blood, liver, fat. 

31 Blood:air partition coefficients were measured for both humans and rats. The mouse blood:air 

32 partition coefficient was different from rat or human values; the source of the partition 

33 coefficient for blood in mice was not reported. Rat tissue:air partition coefficients were used as 

34 surrogate values for humans. Rat tissue partition coefficient values were the same values as used 

35 in the Leung and Paustenbach (1990) model (with the exception of slowly perfused tissues) and 

36 were used in the models for all three species. The liver value was used for the rapidly perfused 
18

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 tissues, as well as slowly perfused tissues. Although slowly perfused tissue:air partition 

2 coefficients for rats were measured, the authors suggested that 1,4-dioxane in the muscle and air 

3 may not have reached equilibrium in the highly gelatinous tissue homogenate (Reitz, et al., 

4 1990). Substitution of the liver value provided much closer agreement to the plasma data than 

5 when the muscle value was used. Further, doubling of the measured human blood:air partition 

6 coefficient improved the fit of the model to the human blood level data compared to the fit 

7 resulting from the measured value (Reitz, et al., 1990). The Reitz et al. (1990) model simulated 

8 three routes of 1,4-dioxane elimination: pulmonary exhalation, hepatic metabolism to HEAA, 

9 and urinary excretion of HEAA. The elimination of HEAA was modeled as a first-order transfer 

10 of 1,4-dioxane metabolite to urine.

11 Values for the metabolic rate constants, Vmax and Km, were optimized to achieve 

12 agreement with various observations. Reitz et al. (1990) optimized values for human Vmax and 

13 Km against the experimental human 1,4-dioxane inhalation data (Young, et al., 1977). As noted 

14 previously, because the human exposures were below the level needed to exhibit nonlinear 

15 kinetics, uncertainty exists in the ability of the optimized value of Vmax to simulate human 

16 1,4-dioxane metabolism above the concentration that would result in saturation of metabolism. 

17 Rat metabolic rate constants were obtained by optimization to simulated data from a two 

18 compartment empirical pharmacokinetic model, which was fitted to i.v. exposure data (Young, et 

19 al., 1978a; Young, et al., 1978b). As with the Leung and

20 The Leung and Paustenbach model (1990) and the Reitz et al. (1990) model included 

21 compartments for the liver and fat, although no tissue-specific concentration data were available 

22 to validate dosimetry for these organs. The derivations of human and rat HEAA elimination rate 

23 constants were not reported. Since no pharmacokinetics data for 1,4-dioxane in mice were 

24 available, mouse metabolic rate constants were allometrically scaled from rat and human values. 

3.5.2.3. Fisher et al. 

25 A PBPK model was developed by Fisher et al. (1997) to simulate a variety of volatile 

26 organic compounds (VOCs, including 1,4-dioxane) in lactating humans. This model was similar 

27 in structure to those of Leung and Paustenbach (1990) and Reitz et al. (1990) with the addition of 

28 elimination of 1,4-dioxane to breast milk. Experimental measurements were made for blood:air 

29 and milk:air partition coefficients. Other partition coefficient values were taken from Reitz et al. 

30 (1990). The model was not optimized, nor was performance tested against experimental 

31 exposure data. Thus, the ability of the model to simulate 1,4-dioxane exposure data is unknown. 

3.5.2.4. Sweeney et al.

32 The Sweeney et al. (2008) model consisted of fat, liver, slowly perfused, and other well 

33 perfused tissue compartments. Lung and stomach compartments were used to describe the route 

34 of exposure, and an overall volume of distribution compartment was used for calculation of 

35 urinary excretion levels of 1,4-dioxane and HEAA. Blood, saline, and tissue to air partition 
19

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 coefficient values for 1,4-dioxane were experimentally determined for rats and mice. Average 

2 values of the rat and mouse partition coefficients were used for humans. Metabolic constants 

3 (VmaxC and Km) for the rat were derived by optimization of data from an i.v. exposure of 1,000 

4 mg/kg (Young, et al., 1978a) for inducible metabolism. For uninduced VmaxC estimation, data 

5 generated by i.v. exposures to 3, 10, 30, and 100 mg/kg were used (Young, et al., 1978a). 

6 Sweeney et al. (2008) determined best fit values for VmaxC by fitting to blood data in the Young 

et al. (1978a). The best fit VmaxC values were 7.5, 10.8, and 12.7 mg/hr-kg0.75 7 for i.v. doses of 3 

8 to 100, 300, and 1,000 mg/kg, suggesting a gradual dose dependent increase in metabolic rate 

9 over i.v. doses ranging from 3 to 1,000 mg/kg. Although the Sweeney et al. (2008) model 

10 utilized two values for VmaxC (induced and uninduced), the PBPK model does not include a 

11 dose-dependent function description of the change of Vmax for i.v. doses between metabolic 

12 induced and uninduced exposures. Mouse VmaxC and absorption constants were derived by 

13 optimizing fits to the blood 1,4-dioxane concentrations in mice administered nominal doses of 

14 200 and 2,000 mg/kg 1,4-dioxane via gavage in a water vehicle (Young, et al., 1978a). The in 

15 vitro Vmax values for rats and mice were scaled to estimate in vivo rates. The scaled and 

16 optimized rat VmaxC values were very similar. The discrepancy between the scaled and 

17 optimized mouse values was larger, which was attributed to possible induction in mice at the 

18 lowest dose tested (200 mg/kg). The ratio of optimized/scaled values for the rat was used to 

19 adjust the scaled human VmaxC and Km values to projected in vivo values.

20 The Sweeney et al. (2008) model outputs were compared, by visual inspection, with data 

21 not used in fitting model parameters. The model predictions gave adequate match to the 1,4-

22 dioxane exhalation data in rats after a 1,000 mg/kg i.v. dose. 1,4-Dioxane exhalation was 

23 overpredicted by a factor of about 3 after a 10 mg/kg i.v. dose. Similarly, the simulations of 

24 exhaled 1,4-dioxane after oral dosing were adequate at 1,000 mg/kg and 100 mg/kg (within 

25 50%), but poor at 10 mg/kg (model over predicted by a factor of 5). The fit of the model to the 

26 human data (Young, et al., 1977) was problematic. Using physiological parameters of Brown et 

27 al. (1997) and measured partitioning parameters (Leung & Paustenbach, 1990; Sweeney, et al., 

28 2008) with no metabolism, measured blood 1,4-dioxane concentrations reported by Young et al. 

29 (1977) could not be achieved unless the estimated exposure concentration was increased by 2-

30 fold. As expected, inclusion of any metabolism resulted in a decrease in predicted blood 

31 concentrations. If estimated metabolism rates were used with the reported exposure 

32 concentration, urinary metabolite excretion was also underpredicted (Sweeney, et al., 2008).

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

33 As previously described, several pharmacokinetic models have been developed to predict 

34 the absorption, distribution, metabolism, and elimination of 1,4-dioxane in rats and humans. 

35 Single compartment, empirical models for rats (Young, et al., 1978a; Young, et al., 1978b) and 
20

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 humans (Young, et al., 1977) were developed to predict blood levels of 1,4-dioxane and urine 

2 levels of the primary metabolite, HEAA. PBPK models that describe the kinetics of 1,4-dioxane 

3 using biologically realistic flow rates, tissue volumes, enzyme affinities, metabolic processes, 

4 and elimination behaviors were also developed (Fisher, et al., 1997; Leung & Paustenbach, 1990; 

5 Reitz, et al., 1990; Sweeney, et al., 2008).

6 In developing updated toxicity values for 1,4-dioxane the available PBPK models were 

7 evaluated for their ability to predict observations made in experimental studies of rat and human 

8 exposures to 1,4-dioxane (Appendix B). The Reitz et al. (1990) and Leung and Paustenbach

9 (1990) PBPK models were both developed from a PBPK model of styrene (Ramsey & Andersen, 

10 1984), with the exception of minor differences in the use of partition coefficients and biological 

11 parameters. The model code for Leung and Paustenbach (1990) was unavailable in contrast to 

12 Reitz et al. (1990). The model of Reitz et al. (1990) was identified for further consideration to 

13 assist in the derivation of toxicity values, and the Sweeney et al. (2008) PBPK model was also 

14 evaluated. 

15 The biological plausibility of parameter values in the Reitz et al. (1990) human model 

16 were examined. The model published by Reitz et al. (1990) was able to predict the only 

17 available human inhalation data (50 ppm 1,4-dioxane for 6 hours; Young et al., (1977)) by

18 increasing (i.e., approximately doubling) the parameter values for human alveolar ventilation (30 

L/hour/kg0.74), cardiac output (30 L/hour/kg0.74 19 ), and the blood:air partition coefficient (3,650)

above the measured values of 13 L/minute/kg0.74 (Brown, et al., 1997), 14 L/hour/kg0.74 20 (Brown, 

21 et al., 1997), and 1,825 (Leung & Paustenbach, 1990), respectively. Furthermore, Reitz et al. 

22 (1990) replaced the measured value for the slowly perfused tissue:air partition coefficient (i.e., 

23 muscle—value not reported in manuscript) with the measured liver value (1,557) to improve the 

24 fit. Analysis of the Young et al. (1977) human data suggested that the apparent volume of 

25 distribution (Vd) for 1,4-dioxane was approximately 10-fold higher in rats than humans, 

26 presumably due to species differences in tissue partitioning or other process not represented in 

27 the model. Based upon these observations, several model parameters (e.g., 

28 metabolism/elimination parameters) were re-calibrated using biologically plausible values for 

29 flow rates and tissue:air partition coefficients.

30 Appendix B describes all activities that were conducted in the evaluation of the empirical 

31 models and the re-calibration and evaluation of the Reitz et al. (1990) PBPK model to determine 

32 the adequacy and preference for the potential use of the models.

33 The evaluation consisted of implementation of the Young et al. (1978a; 1978b; 1977)

34 empirical rat and human models using the acslXtreme simulation software, re-calibration of the 

35 Reitz et al. (1990) human PBPK model, and evaluation of the model parameters published by 

36 Sweeney et al. (2008). Using the model descriptions and equations given in Young et al. (1978a; 

37 1978b; 1977), model code was developed for the empirical models and executed, simulating the 
21

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 reported experimental conditions. The model output was then compared with the model output 

2 reported in Young et al. (1978a; 1978b; 1977).

3 The PBPK model of Reitz et al. (1990) was re-calibrated using measured values for 

4 cardiac and alveolar flow rates and tissue:air partition coefficients. The predictions of blood and 

5 urine levels of 1,4-dioxane and HEAA, respectively, from the re-calibrated model were 

6 compared with the empirical model predictions of the same dosimeters to determine whether the 

7 re-calibrated PBPK model could perform similarly to the empirical model. As part of the PBPK 

8 model evaluation, EPA performed a sensitivity analysis to identify the model parameters having 

9 the greatest influence on the primary dosimeter of interest, the blood level of 1,4-dioxane. 

10 Variability data for the experimental measurements of the tissue:air partition coefficients were 

11 incorporated to determine a range of model outputs bounded by biologically plausible values for 

12 these parameters. Model parameters from Sweeney et al. (2008) were also tested to evaluate the 

13 ability of the PBPK model to predict human data following exposure to 1,4-dioxane.

14 The rat and human empirical models of Young et al. (1978a; 1978b; 1977) were 

15 successfully implemented in acslXtreme and perform identically to the models reported in the 

16 published papers (Figures B-3 through B-7), with the exception of the lower predicted HEAA 

17 concentrations and early appearance of the peak HEAA levels in rat urine. The early appearance 

18 of peak HEAA levels cannot presently be explained, but may result from manipulations of kme or 

19 other parameters by Young et al. (1978a; 1978b) that were not reported. The lower predictions 

20 of HEAA levels are likely due to reliance on a standard urine volume production rate in the 

21 absence of measured (but unreported) urine volumes. While the human urinary HEAA 

22 predictions were lower than observations, this is due to parameter fitting of Young et al. (1977). 

23 No model output was published in Young et al. (1977) for comparison. The empirical models 

24 were modified to allow for user-defined inhalation exposure levels. However, no modifications 

25 were made to model oral exposures as adequate data to parameterize such modifications do not 

26 exist for rats or humans. Further evaluations of the Young et al. (1977) modified model were

27 conducted against data from the Kasai et al. (2008) subchronic inhalation study. The results of 

28 this evaluation are shown in Appendix B (Figure B-8). It shows that the Young et al. (1977)

29 inhalation empirical model failed to provide an adequate simulation of the 13 week inhalation 

30 exposure blood data of Kasai et al. (2008). Since the Young et al. (1977) model consistently 

31 overpredicted the Kasai et al. (2008) data, the lack of model fit is most likely due to the lack of 

32 inclusion of other metabolic processes or parameters. 

33 Several procedures were applied to the Reitz et al. (1990) human PBPK model to 

34 determine if an adequate fit of the model to the empirical model output or experimental 

35 observations could be attained using biologically plausible values for the model parameters. The 

36 re-calibrated model predictions for blood 1,4-dioxane levels do not come within 10-fold of the 

37 experimental values using measured tissue:air partition coefficients from Leung and Paustenbach
22

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (1990) or Sweeney et al. (2008) (Figures B-9 and B-10). The utilization of a slowly perfused 

2 tissue:air partition coefficient 10-fold lower than measured values produces exposure-phase 

3 predictions that are much closer to observations, but does not replicate the elimination kinetics 

4 (Figure B-11). Recalibration of the model with upper bounds on the tissue:air partition 

5 coefficients results in predictions that are still six- to sevenfold lower than empirical model 

6 prediction or observations (Figures B-13 and B-14). Exploration of the model space using an 

7 assumption of zero-order metabolism (valid for the 50 ppm inhalation exposure) showed that an 

8 adequate fit to the exposure and elimination data can be achieved only when unrealistically low 

9 values are assumed for the slowly perfused tissue:air partition coefficient (Figure B-17). 

10 Artificially low values for the other tissue:air partition coefficients are not expected to improve 

11 the model fit, as these parameters are shown in the sensitivity analysis to exert less influence on

12 blood 1,4-dioxane than VmaxC and Km. In the absence of actual measurements for the human 

13 slowly perfused tissue:air partition coefficient, high uncertainty exists for this model parameter 

14 value. Differences in the ability of rat and human blood to bind 1,4-dioxane may contribute to 

15 the difference in Vd. However, this is expected to be evident in very different values for rat and 

16 human blood:air partition coefficients, which is not the case (Table B-1). Therefore, some other, 

17 as yet unknown, modification to model structure may be necessary.

18 Similarly, Sweeney et al. (2008) also evaluated the available PBPK models (Leung & 

19 Paustenbach, 1990; Reitz, et al., 1990) for 1,4-dioxane. To address uncertainties and 

20 deficiencies in these models, the investigators conducted studies to fill data gaps and reduce 

21 uncertainties pertaining to the pharmacokinetics of 1,4-dioxane and HEAA in rats, mice, and 

22 humans. The following studies were performed: 

Partition coefficients, including measurements for mouse blood and tissues (liver, kidney, 

fat, and muscle) and confirmatory measurements for human blood and rat blood and 

muscle.

Blood time course measurements in mice conducted for gavage administration of 

nominal single doses (20, 200, or 2,000 mg/kg) of 1,4-dioxane administered in water.

Metabolic rate constants for rat, mouse, and human liver based on incubations of 

1,4-dioxane with rat, mouse, and human hepatocytes and measurement of HEAA. 

23 The studies conducted by Sweeney et al. (2008) resulted in partition coefficients that 

24 were consistent with previously measured values and those used in the Leung and Paustenbach 

25 (1990) model. Of noteworthy significance, the laboratory results of Sweeney et al. (2008) did 

26 not confirm the human blood:air partition coefficient Reitz et al. (1990) reported. Furthermore, 

27 Sweeney et al. (2008) estimated metabolic rate constants (VmaxC and Km) within the range used in 

28 the previous models (Leung & Paustenbach, 1990; Reitz, et al., 1990). Overall, the Sweeney et 

29 al. (2008) model utilized more rodent in vivo and in vitro data in model parameterization and 

30 refinement; however, the model was still unable to adequately predict the human blood data from 

31 Young et al. (1977).
23

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Updated PBPK models were developed based on these new data and data from previous 

2 kinetic studies in rats, workers, and human volunteers reported by Young et al. (1978a; 1978b; 

3 1976; 1977). The optimized rate of metabolism for the mouse was significantly higher than the 

4 value previously estimated. The optimized rat kinetic parameters were similar to those in the 

5 1990 models. Of the two available human studies (Young, et al., 1976; 1977), model predictions 

6 were consistent with one study, but did not fit the second as well. 

3.6. RAT NASAL EXPOSURE VIA DRINKING WATER

7 Sweeney et al. (2008) conducted a rat nasal exposure study to explore the potential for 

8 direct contact of nasal tissues with 1,4-dioxane-containing drinking water under bioassay 

9 conditions. Two groups of male Sprague Dawley rats (5/group) received drinking water in 

10 45-mL drinking water bottles containing a fluorescent dye mixture (Cell Tracker 

11 Red/FluoSpheres). The drinking water for one of these two groups also contained 0.5% 

12 1,4-dioxane, a concentration within the range used in chronic toxicity studies. A third group of 

13 five rats received tap water alone (controls). Water was provided to the rats overnight. The next 

14 morning, the water bottles were weighed to estimate the amounts of water consumed. Rats were 

15 sacrificed and heads were split along the midline for evaluation by fluorescence microscopy. 

16 One additional rat was dosed twice by gavage with 2 mL of drinking water containing 

17 fluorescent dye (the second dose was 30 minutes after the first dose; total of 4 mL administered) 

18 and sacrificed 5 hours later to evaluate the potential for systemic delivery of fluorescent dye to 

19 the nasal tissues.

20 The presence of the fluorescent dye mixture had no measurable impact on water 

21 consumption; however, 0.5% 1,4-dioxane reduced water consumption by an average of 62% of 

22 controls following a single, overnight exposure. Fluorescent dye was detected in the oral cavity 

23 and nasal airways of each animal exposed to the Cell Tracker Red/FluoSpheres mixture in their 

24 drinking water, including numerous areas of the anterior third of the nose along the nasal 

25 vestibule, maxillary turbinates, and dorsal nasoturbinates. Fluorescent dye was occasionally 

26 detected in the ethmoid turbinate region and nasopharynx. 1,4-Dioxane had no effect on the 

27 detection of the dye. Little or no fluorescence at the wavelength associated with the dye mixture 

28 was detected in control animals or in the single animal that received the dye mixture by oral 

29 gavage. The investigators concluded that the findings indicate rat nasal tissues are exposed by 

30 direct contact with drinking water under bioassay conditions.
24

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4. HAZARD IDENTIFICATION

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

CONTROLS

1 Case reports of acute occupational poisoning with 1,4-dioxane indicated that exposure to 

2 high concentrations resulted in liver, kidney, and central nervous system (CNS) toxicity (Barber, 

3 1934; Johnstone, 1959). Barber (1934) described four fatal cases of hemorrhagic nephritis and 

4 centrilobular necrosis of the liver attributed to acute inhalation exposure to high (unspecified) 

5 concentrations of 1,4-dioxane. Death occurred within 5–8 days of the onset of illness. Autopsy 

6 findings suggested that the kidney toxicity may have been responsible for lethality, while the 

7 liver effects may have been compatible with recovery. Jaundice was not observed in subjects 

8 and fatty change was not apparent in the liver. Johnstone (1959) presented the fatal case of one 

9 worker exposed to high concentrations of 1,4-dioxane through both inhalation and dermal 

10 exposure for a 1 week exposure duration. Measured air concentrations in the work environment 

11 of this subject were 208–650 ppm, with a mean value of 470 ppm. Clinical signs that were 

12 observed following hospital admission included severe epigastric pain, renal failure, headache, 

13 elevation in blood pressure, agitation and restlessness, and coma. Autopsy findings revealed 

14 significant changes in the liver, kidney, and brain. These included centrilobular necrosis of the 

15 liver and hemorrhagic necrosis of the kidney cortex. Perivascular widening was observed in the 

16 brain with small foci of demyelination in several regions (e.g., cortex, basal nuclei). It was 

17 suggested that these neurological changes may have been secondary to anoxia and cerebral 

18 edema.

19 Several studies examined the effects of acute inhalation exposure in volunteers. In a 

20 study performed at the Pittsburgh Experimental Station of the U.S. Bureau of Mines, eye 

21 irritation and a burning sensation in the nose and throat were reported in five men exposed to 

22 5,500 ppm of 1,4-dioxane vapor for 1 minute (Yant, Schrenk, Waite, & Patty, 1930). Slight 

23 vertigo was also reported by three of these men. Exposure to 1,600 ppm of 1,4-dioxane vapor 

24 for 10 minutes resulted in similar symptoms with a reduced intensity of effect. In a study 

25 conducted by the Government Experimental Establishment at Proton, England (Fairley, Linton, 

26 & Ford-Moore, 1934), four men were exposed to 1,000 ppm of 1,4-dioxane for 5 minutes. Odor 

27 was detected immediately and one volunteer noted a constriction in the throat. Exposure of six 

28 volunteers to 2,000 ppm for 3 minutes resulted in no symptoms of discomfort. Wirth and 

29 Klimmer (1936), of the Institute of Pharmacology, University of Wurzburg, reported slight 

30 mucous membrane irritation in the nose and throat of several human subjects exposed to 

 

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).
25

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 concentrations greater than 280 ppm for several minutes. Exposure to approximately 1,400 ppm 

2 for several minutes caused a prickling sensation in the nose and a dry and scratchy throat. 

3 Silverman et al. (1946) exposed 12 male and 12 female subjects to varying air concentrations of 

4 1,4-dioxane for 15 minutes. A 200 ppm concentration was reported to be tolerable, while a 

5 concentration of 300 ppm caused irritation to the eyes, nose, and throat. The study conducted by 

6 Silverman et al. (1946) was conducted by the Department of Industrial Hygiene, Harvard School 

7 of Public Health, and was sponsored and supported by a grant from the Shell Development 

8 Company. These volunteer studies published in the 1930s and 1940s (Fairley, et al., 1934; 

9 Silverman, et al., 1946; Wirth & Klimmer, 1936; Yant, et al., 1930) did not provide information 

10 on the human subjects research ethics procedures undertaken in these studies; however, there is 

11 no evidence that the conduct of the research was fundamentally unethical or significantly 

12 deficient relative to the ethical standards prevailing at the time the research was conducted.

13 Young et al. (1977) exposed four healthy adult male volunteers to a 50-ppm 

14 concentration of 1,4-dioxane for 6 hours. The investigators reported that the protocol of this 

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

16 Chemical Company and was followed rigorously. Perception of the odor of 1,4-dioxane 

17 appeared to diminish over time, with two of the four subjects reporting inability to detect the 

18 odor at the end of the exposure period. Eye irritation was the only clinical sign reported in this 

19 study. The pharmacokinetics and metabolism of 1,4-dioxane in humans were also evaluated in 

20 this study (see Section 3.3). Clinical findings were not reported in four workers exposed in the 

21 workplace to a TWA concentration of 1.6 ppm for 7.5 hours (Young, et al., 1976).

22 Ernstgård et al. (2006) examined the acute effects of 1,4-dioxane vapor in male and 

23 female volunteers. The study protocol was approved by the Regional Ethics Review Board in 

24 Stockholm, and performed following informed consent and according to the Helsinki 

25 declaration. In a screening study by these investigators, no self-reported symptoms (based on a 

26 visual analogue scale (VAS) that included ratings for discomfort in eyes, nose, and throat, 

27 breathing difficulty, headache, fatigue, nausea, dizziness, or feeling of intoxication) were 

28 observed at concentrations up to 20 ppm; this concentration was selected as a tentative no29 observed-adverse-effect-level (NOAEL) in the main study. In the main study, six male and six 

30 female healthy volunteers were exposed to 0 or 20 ppm 1,4-dioxane, at rest, for 2 hours. This 

31 exposure did not significantly affect symptom VAS ratings, blink frequency, pulmonary function 

32 or nasal swelling (measured before and at 0 and 3 hours after exposure), or inflammatory 

33 markers in the plasma (C-reactive protein and interleukin-6) of the volunteers. Only ratings for 

34 ―solvent smell‖ were significantly increased during exposure.

35 Only two well documented epidemiology studies were available for occupational workers 

36 exposed to 1,4-dioxane (Buffler, Wood, Suarez, & Kilian, 1978; Thiess, Tress, & Fleig, 1976). 
26

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 These studies did not provide evidence of effects in humans; however, the cohort size and 

2 number of reported cases were small.

4.1.1. Thiess et al. 

3 A cross-sectional survey was conducted by Thiess et al. (1976) in German workers 

4 exposed to 1,4-dioxane. The study evaluated health effects in 74 workers, including 24 who 

5 were still actively employed in 1,4-dioxane production at the time of the investigation, 

6 23 previously exposed workers who were still employed by the manufacturer, and 27 retired or 

7 deceased workers. The actively employed workers were between 32 and 62 years of age and had 

8 been employed in 1,4-dioxane production for 5–41 years. Former workers (age range not given) 

9 had been exposed to 1,4-dioxane for 3–38 years and retirees (age range not given) had been 

10 exposed for 12–41 years. Air concentrations in the plant at the time of the study were 

11 0.06–0.69 ppm. A simulation of previous exposure conditions (prior to 1969) resulted in air 

12 measurements between 0.06 and 7.2 ppm. 

13 Active and previously employed workers underwent a thorough clinical examination and 

14 X-ray, and hematological and serum biochemistry parameters were evaluated. The examination 

15 did not indicate pathological findings for any of the workers and no indication of malignant 

16 disease was noted. Hematology results were generally normal. Serum transaminase levels were 

17 elevated in 16 of the 47 workers studied; however, this finding was consistent with chronic 

18 consumption of more than 80 g of alcohol per day, as reported for these workers. No liver 

19 enlargement or jaundice was found. Renal function tests and urinalysis were normal in exposed 

20 workers. Medical records of the 27 retired workers (15 living at the time of the study) were 

21 reviewed. No symptoms of liver or kidney disease were reported and no cancer was detected. 

22 Medical reasons for retirement did not appear related to 1,4-dioxane exposure (e.g., emphysema, 

23 arthritis).

24 Chromosome analysis was performed on six actively employed workers and six control 

25 persons (not characterized). Lymphocyte cultures were prepared and chromosomal aberrations 

26 were evaluated. No differences were noted in the percent of cells with gaps or other 

27 chromosome aberrations. Mortality statistics were calculated for 74 workers of different ages 

28 and varying exposure periods. The proportional contribution of each of the exposed workers to 

29 the total time of observation was calculated as the sum of man-years per 10-year age group. 

30 Each person contributed one man-year per calendar year to the specific age group in which he 

31 was included at the time. The expected number of deaths for this population was calculated from 

32 the age-specific mortality statistics for the German Federal Republic for the years 1970–1973. 

33 From the total of 1,840.5 person-years, 14.5 deaths were expected; however, only 12 deaths were 

34 observed in exposed workers between 1964 and 1974. Two cases of cancer were reported, 

35 including one case of lamellar epithelial carcinoma and one case of myelofibrosis leukemia. 
27

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 These cancers were not considered to be the cause of death in these cases and other severe 

2 illnesses were present. Standardized mortality ratios (SMRs) for cancer did not significantly 

3 differ from the control population (SMR for overall population = 0.83; SMR for 65–75-year-old 

4 men = 1.61; confidence intervals (CIs) were not provided).

4.1.2. Buffler et al. 

5 Buffler et al. (1978) conducted a mortality study on workers exposed to 1,4-dioxane at a 

6 chemical manufacturing facility in Texas. 1,4-Dioxane exposure was known to occur in a 

7 manufacturing area and in a processing unit located 5 miles from the manufacturing plant. 

8 Employees who worked between April 1, 1954, and June 30, 1975, were separated into two 

9 cohorts based on at least 1 month of exposure in either the manufacturing plant (100 workers) or 

10 the processing area (65 workers). Company records and follow-up techniques were used to 

11 compile information on name, date of birth, gender, ethnicity, job assignment and duration, and 

12 employment status at the time of the study. Date and cause of death were obtained from copies 

13 of death certificates and autopsy reports (if available). Exposure levels for each job category 

14 were estimated using the 1974 Threshold Limit Value for 1,4-dioxane (i.e., 50 ppm) and 

15 information from area and personal monitoring. Exposure levels were classified as low 

16 (<25 ppm), intermediate (50–75 ppm), and high (>75 ppm). Monitoring was not conducted prior 

17 to 1968 in the manufacturing areas or prior to 1974 in the processing area; however, the study 

18 authors assumed that exposures would be comparable, considering that little change had been 

19 made to the physical plant or the manufacturing process during that time. Exposure to 

20 1,4-dioxane was estimated to be below 25 ppm for all individuals in both cohorts. 

21 Manufacturing area workers were exposed to several other additional chemicals and processing 

22 area workers were exposed to vinyl chloride.

23 Seven deaths were identified in the manufacturing cohort and five deaths were noted for 

24 the processing cohort. The average exposure duration was not greater for those workers who 

25 died, as compared to those still living at the time of the study. Cancer was the underlying cause 

26 of death for two cases from the manufacturing area (carcinoma of the stomach, alveolar cell 

27 carcinoma) and one case from the processing area (malignant mediastinal tumor). The workers 

28 from the manufacturing area were exposed for 28 or 38 months and both had a positive smoking 

29 history (>1 pack/day). Smoking history was not available for processing area workers. The 

30 single case of cancer in this area occurred in a 21-year-old worker exposed to 1,4-dioxane for 

31 1 year. The mortality data for both industrial cohorts were compared to age-race-sex specific 

32 death rates for Texas (1960–1969). Person-years of observation contributed by workers were 

33 determined over five age ranges with each worker contributing one person-year for each year of 

34 observation in a specific age group. The expected number of deaths was determined by applying 

35 the Texas 1960–1969 death rate statistics to the number of person years calculated for each 
28

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 cohort. The observed and expected number of deaths for overall mortality (i.e., all causes) was 

2 comparable for both the manufacturing area (7 observed versus 4.9 expected) and the processing 

3 area (5 observed versus 4.9 expected). No significant excess in cancer-related deaths was 

4 identified for both areas of the facility combined (3 observed versus 1.7 expected). A separate 

5 analysis was performed to evaluate mortality in manufacturing area workers exposed to 

6 1,4-dioxane for more than 2 years. Six deaths occurred in this group as compared to 

7 4.1 expected deaths. The use of a conditional Poisson distribution indicated no apparent excess 

8 in mortality or death due to malignant neoplasms in this study. It is important to note that the 

9 cohorts evaluated were limited in size. In addition, the mean exposure duration was less than 

10 5 years (<2 years for 43% of workers) and the latency period for evaluation was less than 

11 10 years for 59% of workers. The study authors recommended a follow-up investigation to 

12 allow for a longer latency period; however, no follow-up study of these workers has been 

13 published. 

4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS - ORAL AND INHALATION

14 The majority of the subchronic and chronic studies conducted for 1,4-dioxane were 

15 drinking water studies. To date, there are only two subchronic inhalation studies (Fairley, et al., 

16 1934; Kasai, et al., 2008) and two chronic inhalation studies (Kasai, et al., 2009; Torkelson, 

17 Leong, Kociba, Richter, & Gehring, 1974). The effects following oral and inhalation exposures 

18 are described in detail below. 

4.2.1. Oral Toxicity

4.2.1.1. Subchronic Oral Toxicity

19 Six rats and six mice (unspecified strains) were given drinking water containing 1.25% 

20 1,4-dioxane for up to 67 days (Fairley, et al., 1934). Using reference BWs and drinking water 

21 ingestion rates for rats and mice (U.S. EPA, 1988), it can be estimated that these rats and mice 

22 received doses of approximately 1,900 and 3,300 mg/kg-day, respectively. Gross pathology and 

23 histopathology were evaluated in all animals. Five of the six rats in the study died or were 

24 sacrificed in extremis prior to day 34 of the study. Mortality was lower in mice, with five of six 

25 mice surviving up to 60 days. Kidney enlargement was noted in 5/6 rats and 2/5 mice. Renal 

26 cortical degeneration was observed in all rats and 3/6 mice. Large areas of necrosis were 

27 observed in the cortex, while cell degeneration in the medulla was slight or absent. Tubular casts 

28 were observed and vascular congestion and hemorrhage were present throughout the kidney. 

29 Hepatocellular degeneration with vascular congestion was also noted in five rats and three mice. 

30 For this assessment, EPA identified the tested doses of 1,900 mg/kg-day in rats and 3,300 mg/kg-
29

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 day in mice as the lowest-observed-adverse-effect-levels (LOAELs) for liver and kidney 

2 degeneration in this study.

3 4.2.1.1.1. Stoner et al. 1,4-Dioxane was evaluated by Stoner et al. (1986)for its ability to induce 

4 lung adenoma formation in A/J mice. Six- to 8-week-old male and female A/J mice 

5 (16/sex/group) were given 1,4-dioxane by gavage or i.p. injection, 3 times/week for 8 weeks. 

6 Total cumulative dose levels were given as 24,000 mg/kg (oral), and 4,800, 12,000, or 

7 24,000 mg/kg (i.p.). Average daily dose estimates were calculated to be 430 mg/kg-day (oral), 

8 and 86, 210, or 430 mg/kg-day (i.p.) by assuming an exposure duration of 56 days. The authors 

9 indicated that i.p. doses represent the maximum tolerated dose (MTD), 0.5 times the MTD, and 

10 0.2 times the MTD. Mice were killed 24 weeks after initiation of the bioassay, and lungs, liver, 

11 kidney, spleen, intestines, stomach, thymus, salivary, and endocrine glands were examined for 

12 gross lesions. Histopathology examination was performed if gross lesions were detected. 

13 1,4-Dioxane did not induce lung tumors in male or female A/J mice in this study. 

14 4.2.1.1.2. Stott et al. In the Stott et al. (1981) study, male Sprague Dawley rats (4–6/group) 

15 were given average doses of 0, 10, or 1,000 mg/kg-day 1,4-dioxane (>99% pure) in their 

16 drinking water, 7 days/week for 11 weeks. It should be noted that the methods description in this 

17 report stated that the high dose was 100 mg/kg-day, while the abstract, results, and discussion 

sections indicated that the high dose was 1,000 mg/kg-day. Rats were implanted with a [6-18

3

19 H]thymidine loaded osmotic pump 7 days prior to sacrifice. Animals were sacrificed by 

20 cervical dislocation and livers were removed, weighed, and prepared for histopathology 

evaluation. [321 H]-Thymidine incorporation was measured by liquid scintillation spectroscopy.

22 An increase in the liver to BW ratio was observed in rats from the high dose group 

23 (assumed to be 1,000 mg/kg-day). Histopathological alterations, characterized as minimal 

24 centrilobular swelling, were also seen in rats from this dose group (incidence values were not 

reported). Hepatic DNA synthesis, measured by [325 H]-thymidine incorporation, was increased 

26 1.5-fold in high-dose rats. No changes relative to control were observed for rats exposed to 

27 10 mg/kg-day. EPA found a NOAEL value of 10 mg/kg-day and a LOAEL value of 

28 1,000 mg/kg-day for this study based on histopathological changes in the liver.

29 Stott et al. (1981) also performed several acute experiments designed to evaluate 

30 potential mechanisms for the carcinogenicity of 1,4-dioxane. These experiments are discussed 

31 separately in Section 4.5.2 (Mechanistic Studies). 

32 4.2.1.1.3. Kano et al. In the Kano et al. (2008) study, groups of 6-week-old F344/DuCrj rats 

33 (10/sex/group) and Crj:BDF1 mice (10/sex/group) were administered 1,4-dioxane (>99% pure) 

34 in the drinking water for 13 weeks. The animals were observed daily for clinical signs of 

35 toxicity. Food consumption and BWs were measured once per week and water consumption was 
30

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 measured twice weekly. Food and water were available ad libitum. The concentrations of 

2 1,4-dioxane in the water for rats and mice were 0, 640, 1,600, 4,000, 10,000, or 25,000 ppm. 

3 The investigators used data from water consumption and BW changes to calculate a daily intake 

4 of 1,4-dioxane by the male and female animals. Thus, male rats received doses of approximately 

5 0, 52, 126, 274, 657, and 1,554 mg 1,4-dioxane/kg-day and female rats received 0, 83, 185, 427, 

6 756, and 1,614 mg/kg-day. Male mice received 0, 86, 231, 585, 882, or 1,570 mg/kg-day and 

7 female mice received 0, 170, 387, 898, 1,620, or 2,669 mg/kg-day. 

8 No information was provided as to when the blood and urine samples were collected. 

9 Hematology analysis included red blood cell (RBC) count, hemoglobin, hematocrit, mean 

10 corpuscular volume (MCV), platelet count, white blood cell (WBC) count, and differential 

11 WBCs. Serum biochemistry included total protein, albumin, bilirubin, glucose, cholesterol, 

12 triglyceride (rat only), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate 

13 dehydrogenase (LDH), leucine aminopeptidase (LAP), alkaline phosphatase (ALP), creatinine 

14 phosphokinase (CPK) (rat only), urea nitrogen, creatinine (rat only), sodium, potassium, 

15 chloride, calcium (rat only), and inorganic phosphorous (rat only). Urinalysis parameters were 

16 pH, protein, glucose, ketone body, bilirubin (rat only), occult blood, and urobilinogen. Organ 

17 weights (brain, lung, liver, spleen, heart, adrenal, testis, ovary, and thymus) were measured, and 

18 gross necropsy and histopathologic examination of tissues and organs were performed on all 

19 animals (skin, nasal cavity, trachea, lungs, bone marrow, lymph nodes, thymus, spleen, heart, 

20 tongue, salivary glands, esophagus, stomach, small and large intestine, liver, pancreas, kidney, 

21 urinary bladder, pituitary thyroid adrenal, testes, epididymis, seminal vesicle, prostate, ovary, 

22 uterus, vagina, mammary gland, brain, spinal cord, sciatic nerve, eye, Harderian gland, muscle, 

bone, and parathyroid). Dunnett‘s test and χ223 test were used to assess the statistical significance 

24 of changes in continuous and discrete variables, respectively. 

25 Clinical signs of toxicity in rats were not discussed in the study report. One female rat in 

26 the high dose group (1,614 mg/kg-day) group died, but cause and time of death were not 

27 specified. Final BWs were reduced at the two highest dose levels in females (12 and 21%) and 

28 males (7 and 21%), respectively. Food consumption was reduced 13% in females at 

29 1,614 mg/kg-day and 8% in 1,554 mg/kg-day males. A dose-related decrease in water 

30 consumption was observed in male rats starting at 52 mg/kg-day (15%) and in females starting at 

31 185 mg/kg-day (12%). Increases in RBCs, hemoglobin, hematocrit, and neutrophils, and a 

32 decrease in lymphocytes were observed in males at 1554 mg/kg-day. In females, MCV was 

33 decreased at doses ≥ 756 mg/kg and platelets were decreased at 1,614 mg/kg-day. With the 

34 exception of the 30% increase in neutrophils in high-dose male rats, hematological changes were 

35 within 2–15% of control values. Total serum protein and albumin were significantly decreased 

36 in males at doses ≥ 274 mg/kg-day and in females at doses ≥ 427 mg/kg-day. Additional 

37 changes in high-dose male and female rats included decreases in glucose, total cholesterol, 
31

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 triglycerides, and sodium (and calcium in females), and increases in ALT (males only), AST, 

2 ALP, and LAP. Serum biochemistry parameters in treated rats did not differ more than twofold 

3 from control values. Urine pH was decreased in males at ≥ 274 mg/kg-day and in females at 

4 ≥ 756 mg/kg-day.

5 Kidney weights were increased in females at ≥185 mg/kg-day with a maximum increase 

6 of 15% and 44% at 1,614 mg/kg-day for absolute and relative kidney weight, respectively. No 

7 organ weight changes were noted in male rats. Histopathology findings in rats that were related 

8 to exposure included nuclear enlargement of the respiratory epithelium, nuclear enlargement of 

9 the olfactory epithelium, nuclear enlargement of the tracheal epithelium, hepatocyte swelling of 

10 the centrilobular area of the liver, vacuolar changes in the liver, granular changes in the liver, 

11 single cell necrosis in the liver, nuclear enlargement of the proximal tubule of the kidneys, 

12 hydropic changes in the proximal tubule of the kidneys, and vacuolar changes in the brain. The 

13 incidence data for histopathological lesions in rats are presented in Table 4-1. The effects that 

14 occurred at the lowest doses were nuclear enlargement of the respiratory epithelium in the nasal 

15 cavity and hepatocyte swelling in the central area of the liver in male rats. Based on these 

16 histopathological findings the study authors identified the LOAEL as 126 mg/kg-day and the 

17 NOAEL as 52 mg/kg-day.
32

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 9/10b10/10b9/10b10/10b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 10/10b9/10b10/10b

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 10/10b10/10b10/10b

Hepatocyte swelling 0/10 0/10 9/10b10/10b10/10b10/10b

Vacuolic change; liver 0/10 0/10 0/10 0/10 10/10b10/10b

Granular change; liver 0/10 0/10 0/10 5/10c2/10 10/10b

Single cell necrosis; liver 0/10 0/10 0/10 5/10c2/10 10/10b

Nuclear enlargement; renal proximal tubule 0/10 0/10 0/10 1/10 5/10c9/10b

Hydropic change; renal proximal tubule 0/10 0/10 0/10 0/10 0/10 7/10b

Vacuolic change; brain 0/10 0/10 0/10 0/10 0/10 10/10b

Female dose (mg/kg-day)a

0 83 185 427 756 1,614

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 5/10c10/10b10/10b8/9b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 9/10b10/10b8/9b

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 9/10b10/10b9/9b

Hepatocyte swelling 0/10 0/10 0/10 0/10 9/10b9/9b

Vacuolic change; liver 0/10 0/10 0/10 0/10 0/10 9/9b

Granular change; liver 2/10 0/10 1/10 5/10c5/10c8/9b

Single cell necrosis; liver 2/10 0/10 1/10 5/10 5/10 8/9b

Nuclear enlargement; proximal tubule 0/10 0/10 0/10 0/10 8/10b9/9b

Hydropic change; proximal tubule 0/10 0/10 0/10 0/10 0/10 5/9c

Vacuolic change; brain 0/10 0/10 0/10 0/10 0/10 9/9b

aData are presented for sacrificed animals.

b

p ≤ 0.01 by χ2test.

c

p ≤ 0.05.

Source: Kano et al. (2008)

1 Clinical signs of toxicity in mice were not discussed in the study report One male mouse 

2 in the high-dose group (1,570 mg/kg-day) died, but no information was provided regarding cause 

3 or time of death. Final BWs were decreased 29% in male mice at 1,570 mg/kg-day, but changed 

4 less than 10% relative to controls in the other male dose groups and in female mice. Food 

5 consumption was not significantly reduced in any exposure group. Water consumption was 

6 reduced 14–18% in male mice exposed to 86, 231, or 585 mg/kg-day. Water consumption was 

7 further decreased by 48 and 70% in male mice exposed to 882 and 1,570 mg/kg-day, 

8 respectively. Water consumption was also decreased 31 and 57% in female mice treated with 

9 1,620 and 2,669 mg/kg-day, respectively. An increase in MCV was observed in the two highest 

10 dose groups in both male (882 and 1,570 mg/kg-day) and female mice (1,620 and 

11 2,669 mg/kg-day). Increases in RBCs, hemoglobin, and hematocrit were also observed in high 
33

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 dose males (1,570 mg/kg-day). Hematological changes were within 2–15% of control values. 

2 Serum biochemistry changes in exposed mice included decreased total protein (at 

3 1,570 mg/kg-day in males, ≥1,620 mg/kg-day in females), decreased glucose (at 

4 1,570 mg/kg-day in males, ≥1,620 mg/kg-day in females), decreased albumin (at 

5 1,570 mg/kg-day in males, 2,669 mg/ kg-day in females), decreased total cholesterol 

6 (≥ 585 mg/kg-day in males, ≥1,620 mg/kg-day in females), increased serum ALT (at 

7 1,570 mg/kg-day in males, ≥ 620 mg/kg-day in females), increased AST (at 1,570 mg/kg-day in 

8 males, 2,669 mg/kg-day in females), increased ALP (≥ 585 mg/kg-day in males, 2,669 mg/kg9 day in females), and increased LDH (in females only at doses ≥ 1,620 mg/kg-day). With the 

10 exception of a threefold increase in ALT in male and female mice, serum biochemistry 

11 parameters in treated rats did not differ more than twofold from control values. Urinary pH was 

12 decreased in males at ≥ 882 mg/kg-day and in females at ≥ 1,620 mg/kg-day. 

13 Absolute and relative lung weights were increased in males at 1,570 mg/kg-day and in 

14 females at 1,620 and 2,669 mg/kg-day. Absolute kidney weights were also increased in females 

15 at 1,620 and 2,669 mg/kg-day and relative kidney weight was elevated at 2,669 mg/kg-day. 

16 Histopathology findings in mice that were related to exposure included nuclear enlargement of 

17 the respiratory epithelium, nuclear enlargement of the olfactory epithelium, eosinophilic change 

18 in the olfactory epithelium, vacuolic change in the olfactory nerve, nuclear enlargement of the 

19 tracheal epithelium, accumulation of foamy cells in the lung and bronchi, nuclear enlargement 

20 and degeneration of the bronchial epithelium, hepatocyte swelling of the centrilobular area of the 

21 liver, and single cell necrosis in the liver. The incidence data for histopathological lesions in 

22 mice are presented in Table 4-2. Based on the changes in the bronchial epithelium in female 

23 mice, the authors identified the dose level of 387 mg/kg-day as the LOAEL for mice; the 

24 NOAEL was 170 mg/kg-day (Kano, et al., 2008).
34

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 5/10b0/9

Eosinophilic change; nasal respiratory epithelium 0/10 0/10 0/10 0/10 0/10 5/9b

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 9/10c10/10c9/9c

Eosinophilic change; nasal olfactory epithelium 0/10 0/10 0/10 0/10 0/10 6/9c

Vacuolic change; olfactory nerve 0/10 0/10 0/10 0/10 0/10 9/9c

Nuclear enlargement; tracheal epithelium 0/10 0/10 0/10 7/10c9/10c9/9c

Accumulation of foamy cells; lung/bronchi 0/10 0/10 0/10 0/10 0/10 6/9c

Nuclear enlargement; bronchial epithelium 0/10 0/10 0/10 9/10c9/10c9/9c

Degeneration; bronchial epithelium 0/10 0/10 0/10 0/10 0/10 8/9c

Hepatocyte swelling 0/10 0/10 0/10 10/10c10/10c9/9c

Single cell necrosis; liver 0/10 0/10 0/10 5/10b10/10c9/9c

Female dose (mg/kg-day)a

0 170 387 898 1,620 2,669

Nuclear enlargement; nasal respiratory epithelium 0/10 0/10 0/10 3/10 3/10 7/10c

Eosinophilic change; nasal respiratory epithelium 0/10 0/10 1/10 1/10 5/10b9/10c

Nuclear enlargement; nasal olfactory epithelium 0/10 0/10 0/10 6/10b10/10c10/10c

Eosinophilic change; nasal olfactory epithelium 0/10 0/10 0/10 1/10c6/10b6/10b

Vacuolic change; olfactory nerve 0/10 0/10 0/10 0/10 2/10 8/10c

Nuclear enlargement; tracheal epithelium 0/10 0/10 2/10 9/10c10/10c10/10c

Accumulation of foamy cells; lung/bronchi 0/10 0/10 0/10 0/10 10/10c10/10c

Nuclear enlargement; bronchial epithelium 0/10 0/10 10/10c10/10c10/10c10/10c

Degeneration; bronchial epithelium 0/10 0/10 0/10 0/10 7/10c10/10c

Hepatocyte swelling 0/10 1/10 1/10 10/10c10/10c9/10b

Single cell necrosis; liver 0/10 0/10 0/10 7/10c10/10c9/10c

aData are presented for sacrificed animals.

b

p ≤ 0.01 by χ2test.

c

p ≤ 0.05.

Source: Kano et al (2008).

1 4.2.1.1.4. Yamamoto et al. Studies (Yamamoto et al., 1998; Yamamoto, Urano, & Nomura, 

2 1998) in rasH2 transgenic mice carrying the human prototype c-Ha-ras gene have been 

3 investigated as a bioassay model for rapid carcinogenicity testing. As part of validation studies 

4 of this model, 1,4-dioxane was one of many chemicals that were evaluated. RasH2 transgenic 

5 mice were F1 offspring of transgenic male C57BLr6J and normal female BALB/cByJ mice. 

6 CB6F1 mice were used as a nontransgenic control. Seven- to nine-week-old mice (10–15/group) 
35

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 were exposed to 0, 0.5, or 1% 1,4-dioxane in drinking water for 26 weeks. An increase in lung 

2 adenomas was observed in treated transgenic mice, as compared to treated nontransgenic mice. 

3 The tumor incidence in transgenic animals, however, was not greater than that observed in 

4 vehicle-treated transgenic mouse controls. Further study details were not provided.

4.2.1.2. Chronic Oral Toxicity and Carcinogenicity

5 4.2.1.2.1. Argus et al. Twenty-six adult male Wistar rats (Argus, Arcos, & Hoch-Ligeti, 1965)

6 weighing between 150 and 200 g were exposed to 1,4-dioxane (purity not reported) in the 

7 drinking water at a concentration of 1% for 64.5 weeks. A group of nine untreated rats served as 

8 control. Food and water were available ad libitum. The drinking water intake for treated 

9 animals was reported to be 30 mL/day, resulting in a dose/rat of 300 mg/day. Using a reference 

10 BW of 0.462 kg for chronic exposure to male Wistar rats (U.S. EPA, 1988), it can be estimated 

11 that these rats received daily doses of approximately 640 mg/kg-day. All animals that died or 

12 were killed during the study underwent a complete necropsy. A list of specific tissues examined 

13 microscopically was not provided; however, it is apparent that the liver, kidneys, lungs, 

14 lymphatic tissue, and spleen were examined. No statistical analysis of the results was conducted.

15 Six of the 26 treated rats developed hepatocellular carcinomas, and these rats had been 

16 treated for an average of 452 days (range, 448–455 days). No liver tumors were observed in 

17 control rats. In two rats that died after 21.5 weeks of treatment, histological changes appeared to 

18 involve the entire liver. Groups of cells were found that had enlarged hyperchromic nuclei. Rats 

19 that died or were killed at longer intervals showed similar changes, in addition to large cells with 

20 reduced cytoplasmic basophilia. Animals killed after 60 weeks of treatment showed small 

21 neoplastic nodules or multifocal hepatocellular carcinomas. No cirrhosis was observed in this 

22 study. Many rats had extensive changes in the kidneys often resembling glomerulonephritis, 

23 however, incidence data was not reported for these findings. This effect progressed from 

24 increased cellularity to thickening of the glomerular capsule followed by obliteration of the 

25 glomeruli. One treated rat had an early transitional cell carcinoma in the kidney‘s pelvis; this rat 

26 also had a large tumor in the liver. The lungs from many treated and control rats (incidence not 

27 reported) showed severe bronchitis with epithelial hyperplasia and marked peribronchial 

28 infiltration, as well as multiple abscesses. One rat treated with 1,4-dioxane developed leukemia 

29 with infiltration of all organs, particularly the liver and spleen, with large, round, isolated 

30 neoplastic cells. In the liver, the distribution of cells in the sinusoids was suggestive of myeloid 

31 leukemia. The dose of 640 mg/kg-day tested in this study was a free-standing LOAEL, 

32 identified by EPA, for glomerulonephritis in the kidney and histological changes in the liver 

33 (hepatocytes with enlarged hyperchromic nuclei, large cells with reduced cytoplasmic 

34 basophilia).
36

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 4.2.1.2.2. Argus et al.; Hoch-Ligeti et al. Five groups (28-32/dose group) of male 

2 Sprague Dawley rats (2-3 months of age) weighing 110–230 g at the beginning of the experiment 

3 were administered 1,4-dioxane (purity not reported) in the drinking water for up to 13 months at 

4 concentrations of 0, 0.75, 1.0, 1.4, or 1.8% (Argus, Sohal, Bryant, Hoch-Ligeti, & Arcos, 1973; 

5 Hoch-Ligeti, Argus, & Arcos, 1970). The drinking water intake was determined for each group 

6 over a 3-day measurement period conducted at the beginning of the study and twice during the 

7 study (weeks were not specified). The rats were killed with ether at 16 months or earlier if nasal 

8 tumors were clearly observable. Complete autopsies were apparently performed on all animals, 

9 but only data from the nasal cavity and liver were presented and discussed. The nasal cavity was 

10 studied histologically only from rats in which gross tumors in these locations were present; 

11 therefore, early tumors may have been missed and pre-neoplastic changes were not studied. No 

12 statistical analysis of the results was conducted. Assuming a BW of 0.523 kg for an adult male 

13 Sprague Dawley rat (U.S. EPA, 1988) and a drinking water intake of 30 mL/day as reported by 

14 the study authors, dose estimates were 0, 430, 574, 803, and 1,032 mg/kg-day. The progression 

15 of liver tumorigenesis was evaluated by an additional group of 10 male rats administered 1% 

16 1,4-dioxane in the drinking water (574 mg/kg-day), 5 of which were sacrificed after 8 months of 

17 treatment and 5 were killed after 13 months of treatment. Liver tissue from these rats and control 

18 rats was processed for electron microscopy examination. 

19 Nasal cavity tumors were observed upon gross examination in six rats (1/30 in the 0.75% 

20 group, 1/30 in the 1.0% group, 2/30 in the 1.4% group, and 2/30 in the 1.8% group). Gross 

21 observation showed the tumors visible either at the tip of the nose, bulging out of the nasal 

22 cavity, or on the back of the nose covered by intact or later ulcerated skin. As the tumors 

23 obstructed the nasal passages, the rats had difficulty breathing and lost weight rapidly. No 

24 neurological signs or compression of the brain were observed. In all cases, the tumors were 

25 squamous cell carcinomas with marked keratinization and formation of keratin pearls. Bony 

26 structure was extensively destroyed in some animals with tumors, but there was no invasion into 

27 the brain. In addition to the squamous carcinoma, two adenocarcinomatous areas were present. 

28 One control rat had a small, firm, well-circumscribed tumor on the back of the nose, which 

29 proved to be subcutaneous fibroma. The latency period for tumor onset was 329–487 days. 

30 Evaluation of the latent periods and doses received did not suggest an inverse relationship 

31 between these two parameters.

32 Argus et al. (1973) studied the progression of liver tumorigenesis by electron microscopy 

33 of liver tissues obtained following interim sacrifice at 8 and 13 months of exposure (5 rats/group, 

34 574 mg/kg-day). The first change observed in the liver was an increase in the size of the nucleus 

35 of the hepatocytes, mostly in the periportal area. Precancerous changes were characterized by 

36 disorganization of the rough endoplasmic reticulum, an increase in smooth endoplasmic 

37 reticulum, and a decrease in glycogen and increase in lipid droplets in hepatocytes. These 
37

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 changes increased in severity in the hepatocellular carcinomas in rats exposed to 1,4-dioxane for 

2 13 months.

3 Three types of liver nodules were observed in exposed rats at 13–16 months. The first 

4 consisted of groups of cells with reduced cytoplasmic basophilia and a slightly nodular 

5 appearance as viewed by light microscopy. The second type of circumscribed nodule was 

6 described consisting of large cells, apparently filled and distended with fat. The third type of 

7 nodule was described as finger-like strands, 2–3 cells thick, of smaller hepatocytes with large 

8 hyperchromic nuclei and dense cytoplasm. This third type of nodule was designated as an 

9 incipient hepatoma, since it showed all the histological characteristics of a fully developed 

10 hepatoma. All three types of nodules were generally present in the same liver. Cirrhosis of the 

11 liver was not observed. The numbers of incipient liver tumors and hepatomas in rats from this 

12 study (treated for 13 months and observed at 13–16 months) are presented in Table 4-3.

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

Sprague- Dawley rats exposed to 1,4-dioxane in drinking water for 

13 months

Dose (mg/kg-day)a

Incipient tumors Hepatomas Total

430 4 0 4

574 9 0 9

803 13 3 16

1,032 11 12 23

a

Precise incidences cannot be calculated since the number of rats per group was reported as 28–32; incidence in 

control rats was not reported; no statistical analysis of the results was conducted in the study.

Source: Argus et al. (1973).

13 Treatment with all dose levels of 1,4-dioxane induced marked kidney alterations, but 

14 quantitative incidence data were not provided. Qualitatively, the changes indicated 

15 glomerulonephritis and pyelonephritis, with characteristic epithelial proliferation of Bowman‘s 

16 capsule, periglomerular fibrosis, and distension of tubules. No kidney tumors were found. No 

17 tumors were found in the lungs. One rat at the 1.4% treatment level showed early peripheral 

18 adenomatous change of the alveolar epithelium and another rat in the same group showed 

19 papillary hyperplasia of the bronchial epithelium. The lowest dose tested (430 mg/kg-day) was 

20 considered a LOAEL by EPA for hepatic and renal effects in this study.

21 4.2.1.2.3. Hoch-Ligeti and Argus. Hoch-Ligeti and Argus (1970) provided a brief account of 

22 the results of exposure of guinea pigs to 1,4-dioxane. A group of 22 male guinea pigs (neither 

23 strain nor age provided) was administered 1,4-dioxane (purity not provided) in the drinking 

24 water for at least 23 months and possibly up to 28 months. The authors stated that the 

25 concentration of 1,4-dioxane was regulated so that normal growth of the guinea pigs was 
38

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 maintained, and varied 0.5–2% (no further information provided). The investigators further 

2 stated that the amount of 1,4-dioxane received by the guinea pigs over a 23-month period was 

3 588–635 g. Using a reference BW of 0.89 kg for male guinea pigs in a chronic study (U.S. EPA, 

4 1988) and assuming an exposure period of 700 days (23 months), the guinea pigs received doses 

5 between 944 and 1,019 mg 1,4-dioxane/kg-day. A group of ten untreated guinea pigs served as 

6 controls. All animals were sacrificed within 28 months, but the scope of the postmortem 

7 examination was not provided. 

8 Nine treated guinea pigs showed peri- or intrabronchial epithelial hyperplasia and nodular 

9 mononuclear infiltration in the lungs. Also, two guinea pigs had carcinoma of the gallbladder, 

10 three had early hepatomas, and one had an adenoma of the kidney. Among the controls, four 

11 guinea pigs had peripheral mononuclear cell accumulation in the lungs, and only one had 

12 hyperplasia of the bronchial epithelium. One control had formation of bone in the bronchus. No 

13 further information was presented in the brief narrative of this study. Given the limited reporting 

14 of the results, a NOAEL or LOAEL value was not provided for this study.

15 4.2.1.2.4. Kociba et al. Groups of 6–8-week-old Sherman rats (60/sex/dose level) were 

16 administered 1,4-dioxane (purity not reported) in the drinking water at levels of 0 (controls), 

17 0.01, 0.1, or 1.0% for up to 716 days (Kociba, McCollister, Park, Torkelson, & Gehring, 1974). 

18 The drinking water was prepared twice weekly during the first year of the study and weekly 

19 during the second year of the study. Water samples were collected periodically and analyzed for 

20 1,4-dioxane content by routine gas liquid chromatography. Food and water were available ad 

21 libitum. Rats were observed daily for clinical signs of toxicity, and BWs were measured twice 

22 weekly during the first month, weekly during months 2–7, and biweekly thereafter. Water 

23 consumption was recorded at three different time periods during the study: days 1–113, 114–

24 198, and 446–460. Blood samples were collected from a minimum of five male and five female 

25 control and high-dose rats during the 4th, 6th, 12th, and 18th months of the study and at 

26 termination. Each sample was analyzed for packed cell volume, total erythrocyte count, 

27 hemoglobin, and total and differential WBC counts. Additional endpoints evaluated included 

28 organ weights (brain, liver, kidney, testes, spleen, and heart) and gross and microscopic 

29 examination of major tissues and organs (brain, bone and bone marrow, ovaries, pituitary, uterus, 

30 mesenteric lymph nodes, heart, liver, pancreas, spleen, stomach, prostate, colon, trachea, 

31 duodenum, kidneys, esophagus, jejunum, testes, lungs, spinal cord, adrenals, thyroid, 

32 parathyroid, nasal turbinates, and urinary bladder). The number of rats with tumors, hepatic 

33 tumors, hepatocellular carcinomas, and nasal carcinomas were analyzed for statistical 

34 significance with Fisher‘s Exact test (one-tailed), comparing each treatment group against the 

respective control group. Survival rates were compared using χ235 Contingency Tables and 

36 Fisher‘s Exact test. Student‘s test was used to compare hematological parameters, body and 

37 organ weights, and water consumption of each treatment group with the respective control group.
39

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Male and female rats in the high-dose group (1% in drinking water) consumed slightly 

2 less water than controls. BW gain was depressed in the high-dose groups relative to the other 

3 groups almost from the beginning of the study (food consumption data were not provided). 

4 Based on water consumption and BW data for specific exposure groups, Kociba et al. (1974)

5 calculated mean daily doses of 9.6, 94, and 1,015 mg/kg-day for male rats and 19, 148, and 

6 1,599 mg/kg-day for female rats during days 114–198 for the 0.01, 0.1, and 1.0% concentration 

7 levels, respectively. Treatment with 1,4-dioxane significantly increased mortality among high8 dose males and females beginning at about 2–4 months of treatment. These rats showed 

9 degenerative changes in both the liver and kidneys. From the 5th month on, mortality rates of 

10 control and treated groups were not different. There were no treatment-related alterations in 

11 hematological parameters. At termination, the only alteration in organ weights noted by the 

12 authors was a significant increase in absolute and relative liver weights in male and female high13 dose rats (data not shown). Histopathological lesions were restricted to the liver and kidney from 

14 the mid- and high-dose groups and consisted of variable degrees of renal tubular epithelial and 

15 hepatocellular degeneration and necrosis (no quantitative incidence data were provided). Rats 

16 from these groups also showed evidence of hepatic regeneration, as indicated by hepatocellular 

17 hyperplastic nodule formation and evidence of renal tubular epithelial regenerative activity 

18 (observed after 2 years of exposure). These changes were not seen in controls or in low-dose 

19 rats. The authors determined a LOAEL of 94 mg/kg-day based on the liver and kidney effects in 

20 male rats. The corresponding NOAEL value was 9.6 mg/kg-day. 

21 Histopathological examination of all the rats in the study revealed a total of 132 tumors in 

22 114 rats. Treatment with 1% 1,4-dioxane in the drinking water resulted in a significant increase 

23 in the incidence of hepatic tumors (hepatocellular carcinomas in six males and four females). In 

24 addition, nasal carcinomas (squamous cell carcinoma of the nasal turbinates) occurred in one 

25 high-dose male and two high-dose females. Since 128 out of 132 tumors occurred in rats from 

26 the 12th to the 24th month, Kociba et al. (1974) assumed that the effective number of rats was 

27 the number surviving at 12 months, which was also when the first hepatic tumor was noticed. 

28 The incidences of liver and nasal tumors from Kociba et al. (1974) are presented in Table 4-4. 

29 Tumors in other organs were not elevated when compared to control incidence and did not 

30 appear to be related to 1,4-dioxane administration.
40

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-dioxane in the drinking water for 

2 years

Dose in mg/kg-day 

(average of male 

and female dose)

Effective 

number of 

animalsa

Number of tumorbearing 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 12b10c3

d

aRats surviving until 12 months on study.

b

p = 0.00022 by one-tailed Fisher‘s Exact test. 

c

p = 0.00033 by one-tailed Fisher‘s Exact test. 

d

p = 0.05491 by one-tailed Fisher‘s Exact test.

Source: Used with permission from Elsevier, Ltd., Kociba et al. (1974).

1 The high-dose level was the only dose that increased the formation of liver tumors over 

2 control (males 1,015 mg/kg-day; females 1,599 mg/kg-day) and also caused significant liver and 

3 kidney toxicity in these animals. The mid-dose group (males 94 mg/kg-day; females 148 mg/kg4 day) experienced hepatic and renal degeneration and necrosis, as well as regenerative 

5 proliferation in hepatocytes and renal tubule epithelial cells. No increase in tumor formation was 

6 seen in the mid-dose group. No toxicity or tumor formation was observed in either sex in the 

7 low-dose (males 9.6 mg/kg-day; females 19 mg/kg-day) group of rats. 

8 4.2.1.2.5. National Cancer Institute (NCI). Groups of Osborne-Mendel rats (35/sex/dose) and 

9 B6C3F1 mice (50/sex/dose) were administered 1,4-dioxane (≥ 99.95% pure) in the drinking 

10 water for 110 or 90 weeks, respectively, at levels of 0 (matched controls), 0.5, or 1% (NCI, 

11 1978). Solutions of 1,4-dioxane were prepared with tap water. The report indicated that at 

12 105 weeks from the earliest starting date, a new necropsy protocol was instituted. This affected 

13 the male controls and high-dose rats, which were started a year later than the original groups of 

14 rats and mice. Food and water were available ad libitum. Endpoints monitored in this bioassay 

15 included clinical signs (twice daily), BWs (once every 2 weeks for the first 12 weeks and every 

16 month during the rest of the study), food and water consumption (once per month in 20% of the 

17 animals in each group during the second year of the study), and gross and microscopic 

18 appearance of all major organs and tissues (mammary gland, trachea, lungs and bronchi, heart, 

19 bone marrow, liver, bile duct, spleen, thymus, lymph nodes, salivary gland, pancreas, kidney, 

20 esophagus, thyroid, parathyroid, adrenal, gonads, brain, spinal cord, sciatic nerve, skeletal 

21 muscle, stomach, duodenum, colon, urinary bladder, nasal septum, and skin). Based on the 

22 measurements of water consumption and BWs, the investigators calculated average daily intakes 
41

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 of 1,4-dioxane of 0, 240, and 530 mg/kg-day in male rats, 0, 350, and 640 mg/kg-day in female 

2 rats, 0, 720, and 830 mg/kg-day in male mice, and 0, 380, and 860 mg/kg-day in female mice. 

3 According to the report, the doses of 1,4-dioxane in high-dose male mice were only slightly 

4 higher than those of the low-dose group due to decreased fluid consumption in high-dose male 

5 mice.

6 During the second year of the study, the BWs of high-dose rats were lower than controls, 

7 those of low-dose males were higher than controls, and those of low-dose females were 

8 comparable to controls. The fluctuations in the growth curves were attributed to mortality by the 

9 investigators; quantitative analysis of BW changes was not done. Mortality was significantly 

10 increased in treated rats, beginning at approximately 1 year of study. Analysis of Kaplan-Meier 

11 curves (plots of the statistical estimates of the survival probability function) revealed significant 

12 positive dose-related trends (p < 0.001, Tarone test). In male rats, 33/35 (94%) in the control 

13 group, 26/35 (74%) in the mid-dose group, and 33/35 (94%) in the high-dose group were alive 

14 on week 52 of the study. The corresponding numbers for females were 35/35 (100%), 30/35 

15 (86%), and 29/35 (83%). Nonneoplastic lesions associated with treatment with 1,4-dioxane were 

16 seen in the kidneys (males and females), liver (females only), and stomach (males only). Kidney 

17 lesions consisted of vacuolar degeneration and/or focal tubular epithelial regeneration in the 

18 proximal cortical tubules and occasional hyaline casts. Elevated incidence of hepatocytomegaly 

19 also occurred in treated female rats. Gastric ulcers occurred in treated males, but none were seen 

20 in controls. The incidence of pneumonia was increased above controls in high-dose female rats. 

21 The incidence of nonneoplastic lesions in rats following drinking water exposure to 1,4-dioxane 

22 is presented in Table 4-5. EPA identified the LOAEL in rats from this study as 240 mg/kg-day 

23 for increased incidence of gastric ulcer and cortical tubular degeneration in the kidney in males; 

24 a NOAEL was not established.

Table 4-5. Incidence of nonneoplastic lesions in Osborne-Mendel rats 

exposed to 1,4-dioxane in drinking water

Males (mg/kg-day) Females (mg/kg-day)

0 240 530 0 350 640

Cortical tubule degeneration 0/31a20/31b

(65%)

27/33b

(82%)

0/31a0/34 10/32b

(31%)

Hepatocytomegaly 5/31 

(16%)

3/32

(9%)

11/33

(33%)

7/31a

(23%)

11/33

(33%)

17/32b

(53%)

Gastric ulcer 0/30a5/28b

(18%)

5/30b

(17%)

0/31 1/33

(3%)

1/30

(3%)

Pneumonia 8/30

(27%)

15/31

(48%)

14/33

(42%)

6/30a

(20%)

5/34

(15%)

25/32b

(78%)

a

Statistically significant trend for increased incidence by Cochran-Armitage test (p < 0.05) performed for this 

review.

b

Incidence significantly elevated compared to control by Fisher‘s Exact test (p < 0.05) performed for this review.
42

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

1 Neoplasms associated with 1,4-dioxane treatment were limited to the nasal cavity 

2 (squamous cell carcinomas, adenocarcinomas, and one rhabdomyoma) in both sexes, liver 

3 (hepatocellular adenomas) in females, and testis/epididymis (mesotheliomas) in males. The first 

4 tumors were seen at week 52 in males and week 66 in females. The incidence of squamous cell 

5 carcinomas in the nasal turbinates in male and female rats is presented in Table 4-6. Squamous 

6 cell carcinomas were first seen on week 66 of the study. Morphologically, these tumors varied 

7 from minimal foci of locally invasive squamous cell proliferation to advanced growths consisting 

8 of extensive columns of epithelial cells projecting either into free spaces of the nasal cavity 

9 and/or infiltrating into the submucosa. Adenocarcinomas of the nasal cavity were observed in 

10 3 of 34 high-dose male rats, 1 of 35 low-dose female rats, and 1 of 35 high-dose female rats. 

11 The single rhabdomyoma (benign skeletal muscle tumor) was observed in the nasal cavity of a

12 male rat from the low-dose group. A subsequent re-examination of the nasal tissue sections by 

13 Goldsworthy et al. (1991) concluded that the location of the tumors in the nasal apparatus was 

14 consistent with the possibility that the nasal tumors resulted from inhalation of water droplets by 

15 the rats (see Section 4.5.2 for more discussion of Goldsworthy et al. (1991)).

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

hepatocellular adenoma in Osborne-Mendel rats exposed to 1,4-dioxane in 

drinking water

Males (mg/kg-day)a

0 240b530

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%)d10/35 (29%)e8/35 (23%)c

Hepatocellular adenoma 0/31 (0%)f10/33 (30%)e11/32 (34%)e

aTumor incidence values were not adjusted for mortality.

bGroup 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).

16 The incidence of hepatocellular adenomas in male and female rats is presented in Table 

17 4-6. Hepatocellular adenomas were first observed in high-dose females in week 70 of the study. 

18 These tumors consisted of proliferating hepatic cells oriented as concentric cords. Hepatic cell 

19 size was variable; mitoses and necrosis were rare. Mesothelioma of the vaginal tunics of the 
43

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 testis/epididymis was seen in male rats (2/33, 4/33, and 5/34 in controls, low-, and high-dose 

2 animals, respectively). The difference between the treated groups and controls was not 

3 statistically significant. These tumors were characterized as rounded and papillary projections of 

4 mesothelial cells, each supported by a core of fibrous tissue. Other reported neoplasms were 

5 considered spontaneous lesions not related to treatment with 1,4-dioxane.

6 In mice, mean BWs of high-dose female mice were lower than controls during the second 

7 year of the study, while those of low-dose females were higher than controls. In males, mean 

8 BWs of high-dose animals were higher than controls during the second year of the study. 

9 According to the investigators, these fluctuations could have been due to mortality; no 

10 quantitative analysis of BWs was done. No other clinical signs were reported. Mortality was 

11 significantly increased in female mice (p < 0.001, Tarone test), beginning at approximately 

12 80 weeks on study. The numbers of female mice that survived to 91 weeks were 45/50 (90%) in 

13 the control group, 39/50 (78%) in the low-dose group, and 28/50 (56%) in the high-dose group. 

14 In males, at least 90% of the mice in each group were still alive at week 91. Nonneoplastic 

15 lesions that increased significantly due to treatment with 1,4-dioxane were pneumonia in males 

16 and females and rhinitis in females. The incidences of pneumonia were 1/49 (2%), 9/50 (18%), 

17 and 17/47 (36%) in control, low-dose, and high-dose males, respectively; the corresponding 

18 incidences in females were 2/50 (4%), 33/47 (70%), and 32/36 (89%). The incidences of rhinitis 

19 in female mice were 0/50, 7/48 (14%), and 8/39 (21%) in control, low-dose, and high-dose 

20 groups, respectively. Pair-wise comparisons of low-dose and high-dose incidences with controls 

21 for incidences of pneumonia and rhinitis in females using Fisher‘s Exact test (done for this

22 review) yielded p-values < 0.001 in all cases. Incidences of other lesions were considered to be 

23 similar to those seen in aging mice. The authors stated that hepatocytomegaly was commonly 

24 found in dosed mice, but the incidences were not significantly different from controls and 

25 showed no dose-response trend. EPA concluded the LOAEL for 1,4-dioxane in mice was 

26 380 mg/kg-day based on the increased incidence of pneumonia and rhinitis in female mice; a 

27 NOAEL was not established in this study. 

28 As shown in Table 4-7, treatment with 1,4-dioxane significantly increased the incidence 

29 of hepatocellular carcinomas or adenomas in male and female mice in a dose-related manner. 

30 Tumors were first observed on week 81 in high-dose females and in week 58 in high-dose males. 

31 Tumors were characterized by parenchymal cells of irregular size and arrangement, and were 

32 often hypertrophic with hyperchromatic nuclei. Mitoses were seldom seen. Neoplasms were 

33 locally invasive within the liver, but metastasis to the lungs was rarely observed. 
44

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

mice exposed to 1,4-dioxane in drinking water

Males (mg/kg-day)a

0 720 830

Hepatocellular carcinoma 2/49 (4%)b18/50 (36%)c24/47 (51%)c

Hepatocellular adenoma or carcinoma 8/49 (16%)b19/50 (38%)d28/47 (60%)c

Females (mg/kg-day)a

0 380 860

Hepatocellular carcinoma 0/50 (0%)b12/48 (25%)c29/37 (78%)c

Hepatocellular adenoma or carcinoma 0/50 (0%)b21/48 (44%)c35/37 (95%)c

aTumor 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).

1 In addition to liver tumors, a variety of other benign and malignant neoplasms occurred. 

2 However, the report (NCI, 1978) indicated that each type had been encountered previously as a 

3 spontaneous lesion in the B6C3F1 mouse. The report further stated that the incidences of these 

4 neoplasms were unrelated by type, site, group, or sex of the animal, and hence, not attributable to 

5 exposure to 1,4-dioxane. There were a few nasal adenocarcinomas (1/48 in low-dose females 

6 and 1/49 in high-dose males) that arose from proliferating respiratory epithelium lining of the 

7 nasal turbinates. These growths extended into the nasal cavity, but there was minimal local 

8 tissue infiltration. Nasal mucosal polyps were rarely observed. The polyps were derived from 

9 mucus-secreting epithelium and were otherwise unremarkable. There was a significant negative 

10 trend for alveolar/bronchiolar adenomas or carcinomas of the lung in male mice, such that the 

11 incidence in the matched controls was higher than in the dosed groups. The report (NCI, 1978)

12 indicated that the probable reason for this occurrence was that the dosed animals did not live as 

13 long as the controls, thus diminishing the possibility of the development of tumors in the dosed 

14 groups.

15 4.2.1.2.6. Kano et al.; Japan Bioassay Research Center; Yamazaki et al. The Japan 

16 Bioassay Research Center (JBRC) conducted a 2-year drinking water study determining the 

17 effects of 1,4-dioxane on both sexes of rats and mice. The study results have been reported 

18 several times: once as conference proceedings (Yamazaki et al., 1994), once as a laboratory 

19 report (JBRC, 1998), and most recently as a peer-reviewed manuscript (Kano et al., 2009). Dr. 

20 Yamazaki also provided some detailed information (Yamazaki, 2006). Variations in the data 

21 between these three reports were noted and included: (1) the level of detail on dose information 

22 reported; (2) categories for incidence data reported (e.g., all animals or sacrificed animals); and 

23 (3) analysis of non- and neoplastic lesions. 
45

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 The 1,4-dioxane dose information provided in the reports varied. Specifically, Yamazaki

2 et al. (1994) only included drinking water concentrations for each dose group. In contrast, JBRC 

3 (1998) included drinking water concentrations (ppm), in addition using body weights and water 

4 consumption measurements to calculate daily chemical intake (mg/kg-day). JBRC (1998)

5 reported daily chemical intake for each dose group as a range. Thus, for the External Peer 

6 Review draft of this Toxicological Review of 1,4-Dioxane (U.S. EPA, 2009b), the midpoint of 

7 the range was used. Kano et al. (2009) also reported a calculation of daily chemical intake based 

8 on body weight and water consumption measurements; however, for each dose group they 

9 reported a mean and standard deviation estimate. Therefore, because the mean more accurately 

10 represents the delivered dose than the midpoint of a range, the Kano et al. (2009) calculated 

11 mean chemical intake (mg/kg-day) is used for quantitative analysis of this data. 

12 The categories for which incidence rates were described also varied among the reports. 

13 Yamazaki et al. (1994) and Kano et al. (2009) reported histopathological results for all animals, 

14 including dead and moribund animals; however, the detailed JBRC laboratory findings (1998)

15 included separate incidence reports for dead and moribund animals, sacrificed animals, and all 

16 animals. 

17 Finally, the criteria used to evaluate some of the data were updated when JBRC published 

18 the most recent manuscript by Kano et al. (2009). The manuscript by Kano et al. (2009) stated 

19 that the lesions diagnosed in the earlier reports (JBRC, 1998; Yamazaki, et al., 1994) were re20 examined and recategorized as appropriate according to current pathological diagnostic criteria 

21 (see references in Kano et al. (2009)). 

22 Groups of F344/DuCrj rats (50/sex/dose level) were exposed to 1,4-dioxane (>99% pure) 

23 in the drinking water at levels of 0, 200, 1,000, or 5,000 ppm for 2 years. Groups of Crj:BDF1

24 mice (50/sex/dose level) were similarly exposed in the drinking water to 0, 500, 2,000, or 

25 8,000 ppm of 1,4-dioxane. The high doses were selected based on results from the Kano et al. 

26 (2008) 13-week drinking water study so as not to exceed the maximum tolerated dose (MTD) in 

27 that study. Both rats and mice were 6 weeks old at the beginning of the study. Food and water 

28 were available ad libitum. The animals were observed daily for clinical signs of toxicity; and 

29 BWs were measured once per week for 14 weeks and once every 2 weeks until the end of the 

30 study. Food consumption was measured once a week for 14 weeks and once every 4 weeks for 

31 the remainder of the study. The investigators used data from water consumption and BW to 

32 calculate an estimate of the daily intake of 1,4-dioxane (mg/kg-day) by male and female rats and 

33 mice. Kano et al. (2009) reported a calculated mean ± standard deviation for the daily doses of 

34 1,4-dioxane for the duration of the study. Male rats received doses of approximately 0, 11±1, 

35 55±3, or 274±18 mg/kg-day and female rats received 0, 18±3, 83±14, or 429±69 mg/kg-day. 

36 Male mice received doses of 0, 49±5, 191±21, or 677±74 mg/kg-day and female mice received 0, 

37 66±10, 278±40, or 964±88 mg/kg-day. For the remainder of this document, including the dose-
46

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 response analysis, the mean calculated intake values are used to identify dose groups. The Kano 

2 et al. (2009) study was conducted in accordance with the Organization for Economic Co3 operation and Development (OECD) Principles for Good Laboratory Practice (GLP). 

4 No information was provided as to when urine samples were collected. Blood samples 

5 were collected only at the end of the 2-year study (Yamazaki, 2006). Hematology analysis 

6 included RBCs, hemoglobin, hematocrit, MCV, platelets, WBCs and differential WBCs. Serum 

7 biochemistry included total protein, albumin, bilirubin, glucose, cholesterol, triglyceride (rat 

8 only), phospholipid, ALT, AST, LDH, LAP, ALP, γ-glutamyl transpeptidase (GGT), CPK, urea 

9 nitrogen, creatinine (rat only), sodium, potassium, chloride, calcium, and inorganic phosphorous. 

10 Urinalysis parameters were pH, protein, glucose, ketone body, bilirubin (rat only), occult blood, 

11 and urobilinogen. Organ weights (brain, lung, liver, spleen, heart, adrenal, testis, ovary, and 

12 thymus) were measured, and gross necropsy and histopathologic examination of tissues and 

13 organs were performed on all animals (skin, nasal cavity, trachea, lungs, bone marrow, lymph 

14 nodes, thymus, spleen, heart, tongue, salivary glands, esophagus, stomach, small and large 

15 intestine, liver, pancreas, kidney, urinary bladder, pituitary, thyroid, adrenal, testes, epididymis, 

16 seminal vesicle, prostate, ovary, uterus, vagina, mammary gland, brain, spinal cord, sciatic nerve, 

eye, Harderian gland, muscle, bone, and parathyroid). Dunnett‘s test and χ217 test were used to 

18 assess the statistical significance of changes in continuous and discrete variables, respectively.

19 For rats, growth and mortality rates were reported in Kano et al. (2009) for the duration 

20 of the study. Both male and female rats in the high dose groups (274 and 429 mg/kg-day, 

21 respectively) exhibited slower growth rates and terminal body weights that were significantly 

22 different (p < 0.05) compared to controls. A statistically significant reduction in terminal BWs 

23 was observed in high-dose male rats (5%, p < 0.01) and in high-dose female rats (18%, p < 0.01) 

24 (Kano, et al., 2009). Food consumption was not significantly affected by treatment in male or 

25 female rats; however, water consumption in female rats administered 18 mg/kg-day was 

26 significantly greater (p < 0.05) . 

27 All control and exposed rats lived at least 12 months following study initiation 

28 (Yamazaki, 2006); however, survival at the end of the 2-year study in the high dose group of 

29 male and female rats (274 and 429 mg/kg-day, respectively) was approximately 50%, which was 

30 significantly different compared to controls. The investigators attributed these early deaths to the 

31 increased incidence in nasal tumors and peritoneal mesotheliomas in male rats and nasal and 

32 hepatic tumors in female rats. (Yamazaki, 2006). 

33 Several hematological changes were noted in the JBRC report (1998): Decreases in RBC 

34 (male rats only), hemoglobin, hematocrit, and MCV; and increases in platelets in high-dose 

35 groups were observed (JBRC, 1998). These changes (except for MCV) also occurred in mid36 dose males. With the exception of a 23% decrease in hemoglobin in high-dose male rats and a 

37 27% increase in platelets in high-dose female rats, hematological changes were within 15% of 
47

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 control values. Significant changes in serum chemistry parameters occurred only in high-dose 

2 rats (males: increased phospholipids, AST, ALT, LDH, ALP, GGT, CPK, potassium, and 

3 inorganic phosphorus and decreased total protein, albumin, and glucose; females: increased total 

4 bilirubin, cholesterol, phospholipids, AST, ALT, LDH, GGT, ALP, CPK, and potassium, and 

5 decreased blood glucose) (JBRC, 1998). Increases in serum enzyme activities ranged from <2-

6 to 17-fold above control values, with the largest increases seen for ALT, AST, and GGT. Urine 

7 pH was significantly decreased at 274 mg/kg-day in male rats (not tested at other dose levels) 

8 and at 83 and 429 mg/kg-day in female rats (JBRC, 1998). Also, blood in the urine was seen in 

9 female rats at 83 and 429 mg/kg-day (JBRC, 1998). In male rats, relative liver weights were 

10 increased at 55 and 274 mg/kg-day (Kano, et al., 2009). In female rats, relative liver weight was 

11 increased at 429 mg/kg-day (Kano, et al., 2009). 

12 Microscopic examination of the tissues showed nonneoplastic alterations in the nasal 

13 cavity, liver, and kidneys mainly in high-dose rats and, in a few cases, in mid-dose rats (Table s 

14 4-8 and 4-9). Alterations in high-dose (274 mg/kg-day) male rats consisted of nuclear 

15 enlargement and metaplasia of the olfactory and respiratory epithelia, atrophy of the olfactory 

16 epithelium, hydropic changes and sclerosis of the lamina propria, adhesion, and inflammation. 

17 In female rats, nuclear enlargement of the olfactory epithelium occurred at doses ≥ 83 mg/kg18 day, and nuclear enlargement and metaplasia of the respiratory epithelium, squamous cell 

19 hyperplasia, respiratory metaplasia of the olfactory epithelium, hydropic changes and sclerosis of 

20 the lamina propria, adhesion, inflammation, and proliferation of the nasal gland occurred at 

21 429 mg/kg-day. Alterations were seen in the liver at ≥ 55 mg/kg-day in male rats (spongiosis 

22 hepatis, hyperplasia, and clear and mixed cell foci) and at 429 mg/kg-day in female rats 

23 (hyperplasia, spongiosis hepatis, cyst formation, and mixed cell foci). Nuclear enlargement of 

24 the renal proximal tubule occurred in males at 274 mg/kg-day and in females at ≥ 83 mg/kg-day 

25 (JBRC, 1998). 
48

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 epitheliumc0/50 0/50 0/50 26/50e

Squamous cell metaplasia; nasal respiratory epitheliumc0/50 0/50 0/50 31/50e

Squamous cell hyperplasia; nasal respiratory epitheliumc0/50 0/50 0/50 2/50

Nuclear enlargement; nasal olfactory epitheliumc0/50 0/50 5/50f38/50e

Respiratory metaplasia; nasal olfactory epitheliumd12/50 11/50 20/50 43/50

Atrophy; nasal olfactory epitheliumd0/50 0/50 0/50 36/50

Hydropic change; lamina propriad0/50 0/50 0/50 46/50

Sclerosis; lamina propriad0/50 0/50 1/50 44/50

Adhesion; nasal cavityd0/50 0/50 0/50 48/50

Inflammation; nasal cavityd0/50 0/50 0/50 13/50

Hyperplasia; liverd3/50 2/50 10/50 24/50

Spongiosis hepatis; liverd12/50 20/50 25/50f40/50

Clear cell foci; liverc3/50 3/50 9/50 8/50

Acidophilic cell foci; liverc12/50 8/50 7/50 5/50

Basophilic cell foci; liverc7/50 11/50 8/50 16/50f

Mixed-cell foci; liverc2/50 8/50 14/50e13/50e

Nuclear enlargement; kidney proximal tubuled0/50 0/50 0/50 50/50

aData presented for all animals, including animals that became moribund or died before the end of the study.

bDose levels from Kano et al. (2009).

cData from Kano et al. (2009).

dData from JBRC (1998). JBRC did not report statistical significance for the ―All animals‖ comparison.

e

p < 0.01 by χ2test.

f

p < 0.05 by χ2test.

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 epitheliumc0/50 0/50 0/50 13/50e

Squamous cell metaplasia; nasal respiratory epitheliumc0/50 0/50 0/50 35/50 e

Squamous cell hyperplasia; nasal cavityc0/50 0/50 0/50 5/50

Nuclear enlargement; nasal olfactory epithelium c0/50 0/50 28/50e39/50

Respiratory metaplasia; nasal olfactory epitheliumd2/50 0/50 2/50 42/50

Atrophy; nasal olfactory epitheliumd0/50 0/50 1/50 40/50

Hydropic change; lamina propriad0/50 0/50 0/50 46/50

Sclerosis; lamina propriad0/50 0/50 0/50 48/50

Adhesion; nasal cavityd0/50 0/50 0/50 46/50

Inflammation; nasal cavityd0/50 0/50 1/50 15/50

Proliferation; nasal glandd0/50 0/50 0/50 11/50

Hyperplasia; liverd3/50 2/50 11/50e47/50

Spongiosis hepatis; liverd0/50 0/50 1/50 20/50

Cyst formation; liverd0/50 1/50 1/50 8/50

Acidophilic cell foci; liverc1/50 1/50 1/50 1/50

Basophilic cell foci; liverc23/50 27/50 31/50 8/50e

Clear cell foci; liverc1/50 1/50 5/50 4/50

Mixed-cell foci; liverc1/50 1/50 3/50 11/50f

Nuclear enlargement; kidney proximal tubuled0/50 0/50 6/50 39/50

aData presented for all animals, including animals that became moribund or died before the end of the study.

bDose levels from Kano et al. (2009).

cData from Kano et al. (2009).

dData from JBRC (1998). JBRC did not report statistical significance for the ―All animals‖ comparison.

e

p < 0.01 by χ2test.

f

p < 0.05 by χ2test.

Sources: Kano et al. (2009) and JBRC (1998).

1 NOAEL and LOAEL values for rats in this study were identified by EPA as 55 and 

2 274 mg/kg-day, respectively, based on toxicity observed in nasal tissue of male rats (i.e., atrophy 

3 of olfactory epithelium, adhesion, and inflammation). Metaplasia and hyperplasia of the nasal 

4 epithelium were also observed in high-dose male and female rats. These effects are likely to be 

5 associated with the formation of nasal cavity tumors in these dose groups. Nuclear enlargement 

6 was observed in the nasal olfactory epithelium and the kidney proximal tubule at a dose of 

7 83 mg/kg-day in female rats; however, it is unclear whether these alterations represent adverse 

8 toxicological effects. Hematological effects noted in male rats given 55 and 274 mg/kg-day 

9 (decreased RBCs, hemoglobin, hematocrit, increased platelets) were within 20% of control 

10 values. In female rats decreases in hematological effects were observed in the high dose group 

11 (429 mg/kg-day). A reference range database for hematological effects in laboratory animals 
50

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (Wolford et al., 1986) indicates that a 20% change in these parameters may fall within a normal 

2 range (10th–90th percentile values) and may not represent a treatment-related effect of concern. 

3 Liver lesions were also seen at a dose of 55 mg/kg-day in male rats; these changes are likely to 

4 be associated with liver tumorigenesis. Clear and mixed-cell foci are commonly considered 

5 preneoplastic changes and would not be considered evidence of noncancer toxicity. The nature 

6 of spongiosis hepatis as a preneoplastic change is less well understood (Bannasch, 2003; Karbe 

7 & Kerlin, 2002; Stroebel, Mayer, Zerban, & Bannasch, 1995). Spongiosis hepatis is a cyst-like 

8 lesion that arises from the perisinusoidal (Ito) cells (PSC) of the liver. It is commonly seen in 

9 aging rats, but has been shown to increase in incidence following exposure to hepatocarcinogens. 

10 Spongiosis hepatis can be seen in combination with preneoplastic foci in the liver or with 

11 hepatocellular adenoma or carcinoma and has been considered a preneoplastic lesion (Bannasch, 

12 2003; Stroebel, et al., 1995). This change can also be associated with hepatocellular hypertrophy 

13 and liver toxicity and has been regarded as a secondary effect of some liver carcinogens (Karbe 

14 & Kerlin, 2002). In the case of the JBRC (1998) study, spongiosis hepatis was associated with 

15 other preneoplastic changes in the liver (clear and mixed-cell foci). No other lesions indicative 

16 of liver toxicity were seen in this study; therefore, spongiosis hepatis was not considered 

17 indicative of noncancer effects. Serum chemistry changes (increases in total protein, albumin, 

18 and glucose; decreases in AST, ALT, LDH, and ALP, potassium, and inorganic phosphorous) 

19 were observed in both male and female rats (JBRC, 1998) in the high dose groups, 274 and 

20 429 mg/kg-day, respectively. These serum chemistry changes seen in terminal blood samples 

21 from high-dose male and female rats are likely related to tumor formation in these dose groups. 

22 Significantly increased incidences of liver tumors (adenomas and carcinomas) and tumors 

23 of the nasal cavity occurred in high-dose male and female rats (Tables 4-10 and 4-11) treated 

24 with 1,4-dioxane for 2 years (Kano, et al., 2009). The first liver tumor was seen at 85 weeks in 

25 high-dose male rats and 73 weeks in high-dose female rats (vs. 101–104 weeks in lower dose 

26 groups and controls) (Yamazaki, 2006). In addition, a significant increase (p ≤ 0.01, Fisher‘s 

27 Exact test) in mesotheliomas of the peritoneum was seen in high-dose males (28/50 versus 2/50 

28 in controls). Mesotheliomas were the single largest cause of death among high-dose male rats, 

29 accounting for 12 of 28 pretermination deaths (Yamazaki, 2006). Also, in males, there were 

30 increasing trends in mammary gland fibroadenoma and fibroma of the subcutis, both statistically 

31 significant (p < 0.01) by the Peto test of dose-response trend. Females showed a significant 

32 increasing trend in mammary gland adenomas (p < 0.01 by Peto‘s test). The tumor incidence 

33 values presented in Tables 4-10 and 4-11 were not adjusted for survival.
51

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 cavity

Squamous cell carcinoma 0/50 0/50 0/50 3/50a0/50 0/50 0/50 7/50a,b

Sarcoma 0/50 0/50 0/50 2/50 0/50 0/50 0/50 0/50

Rhabdomyosarcoma 0/50 0/50 0/50 1/50 0/50 0/50 0/50 0/50

Esthesioneuroepithelioma 0/50 0/50 0/50 1/50 0/50 0/50 0/50 1/50

Peritoneum

Mesothelioma 2/50 2/50 5/50 28/50a,b 1/50 0/50 0/50 0/50

Mammary gland

Fibroadenoma 1/50 1/50 0/50 4/50a3/50 2/50 1/50 3/50

Adenoma 0/50 1/50 2/50 2/50 6/50 7/50 10/50 16/50a,c

Either adenoma or fibroadenoma 1/50 2/50 2/50 6/50a8/50 8/50 11/50 18/50a,c

a

Statistically significant trend for increased tumor incidence by Peto‘s test (p < 0.01).

b

Significantly different from control by Fisher‘s exact test (p < 0.01).

c

Significantly different from control by Fisher‘s exact test (p < 0.05).

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009).

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

1,4-dioxane in drinking water for 2 years

Males Females

Dose (mg/kg-day) 0 11 55 274 0 18 83 429

Hepatocellular adenoma 3/50 4/50 7/50 32/50a,b 3/50 1/50 6/50 48/50a,b

Hepatocellular carcinoma 0/50 0/50 0/50 14/50a,b 0/50 0/50 0/50 10/50a,b

Either adenoma or carcinoma 3/50 4/50 7/50 39/50a,b 3/50 1/50 6/50 48/50a,b

a

Significantly different from control by Fisher‘s exact test (p < 0.01).

b

Statistically significant trend for increased tumor incidence by Peto‘s test (p < 0.01).

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009).

1 For mice, growth and mortality rates were reported in Kano et al. (2009) for the duration 

2 of the study. Similar to rats, the growth rates of male and female mice were slower than controls 

3 and terminal body weights were lower for the mid (p < 0.01 for males administered 191 mg/kg4 day and p < 0.05 for females administered 278 mg/kg-day) and high doses (p < 0.05 for males 

5 and females administered 677 and 964 mg/kg-day, respectively). There were no differences in 

6 survival rates between control and treated male mice; however, survival rates were significantly 

7 decreased compared to controls for female mice in the mid (278 mg/kg-day, approximately 40% 

8 survival) and high (964 mg/kg-day, approximately 20% survival) dose groups. The study 
52

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 authors attributed these early female mouse deaths to the significant incidence of hepatic tumors, 

2 and Kano et al. (2009) reported tumor incidence for all animals in the study (N=50), including 

3 animals that became moribund or died before the end of the study. Additional data on survival 

4 rates of mice were provided in a personal communication from Dr. Yamazaki (2006). Dr. 

5 Yamazaki reported that the survival of mice was low in all male groups (31/50, 33/50, 25/50 and 

6 26/50 in control, low-, mid-, and high-dose groups, respectively) and particularly low in high7 dose females (29/50, 29/50, 17/50, and 5/50 in control, low-, mid-, and high-dose groups, 

8 respectively). These deaths occurred primarily during the second year of the study. Survival at 

9 12 months in male mice was 50/50, 48/50, 50/50, and 48/50 in control, low-, mid-, and high-dose 

10 groups, respectively. Female mouse survival at 12 months was 50/50, 50/50, 48/50, and 48/50 in 

11 control, low-, mid-, and high-dose groups, respectively (Yamazaki, 2006). Furthermore, these 

12 deaths were primarily tumor related. Liver tumors were listed as the cause of death for 31 of the 

13 45 pretermination deaths in high-dose female Crj:BDF1 mice (Yamazaki, 2006). For mice, 

14 growth and mortality rates were reported in Kano et al. (2009) for the duration of the study. 

15 Similar to rats, the growth rates of male and female mice were slower than controls and terminal 

16 body weights were lower for the mid (p < 0.01 for males administered 191 mg/kg-day and p <

17 0.05 for females administered 278 mg/kg-day) and high doses (p < 0.05 for males and females 

18 administered 677 and 964 mg/kg-day, respectively). 

19 Food consumption was not significantly affected, but water consumption was reduced 

20 26% in high-dose male mice and 28% in high-dose female mice. Final BWs were reduced 43% 

21 in high-dose male mice and 15 and 45% in mid- and high-dose female mice, respectively. Male 

22 mice showed increases in RBC counts, hemoglobin, and hematocrit, whereas in female mice, 

23 there was a decrease in platelets in mid- and high-dose rats. With the exception of a 60% 

24 decrease in platelets in high-dose female mice, hematological changes were within 15% of 

25 control values. Serum AST, ALT, LDH, and ALP activities were significantly increased in mid26 and high-dose male mice, whereas LAP and CPK were increased only in high-dose male mice. 

27 AST, ALT, LDH, and ALP activities were increased in mid- and high-dose female mice, but 

28 CPK activity was increased only in high-dose female mice. Increases in serum enzyme activities 

29 ranged from less than two- to sevenfold above control values. Glucose and triglycerides were 

30 decreased in high-dose males and in mid- and high-dose females. High-dose female mice also 

31 showed decreases in serum phospholipid and albumin concentrations (not reported in males). 

32 Blood calcium was lower in high-dose females and was not reported in males. Urinary pH was 

33 decreased in high-dose males, whereas urinary protein, glucose, and occult blood were increased 

34 in mid- and high-dose female mice. Relative and absolute lung weights were increased in high35 dose males and in mid- and high-dose females (JBRC, 1998). Microscopic examination of the 

36 tissues for nonneoplastic lesions showed significant alterations in the epithelium of the 

37 respiratory tract, mainly in high-dose animals, although some changes occurred in mid-dose mice 
53

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (Tables 4-12 and 4-13). Commonly seen alterations included nuclear enlargement, atrophy, and 

2 inflammation of the epithelium. Other notable changes observed included nuclear enlargement 

3 of the proximal tubule of the kidney and angiectasis in the liver in high-dose male mice. 

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

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

Dose (mg/kg-day)a,b

0 49 191 677

Nuclear enlargement; nasal respiratory epitheliumc0/50 0/50 0/50 31/50e

Nuclear enlargement; nasal olfactory epitheliumc0/50 0/50 9/50e49/50e

Atrophy; nasal olfactory epitheliumd0/50 0/50 1/50 48/50

Inflammation; nasal cavityd1/50 2/50 1/50 25/50

Atrophy; tracheal epitheliumd0/50 0/50 0/50 42/50

Nuclear enlargement; tracheal epitheliumd0/50 0/50 0/50 17/50

Nuclear enlargement; bronchial epitheliumd0/50 0/50 0/50 41/50

Atrophy; lung/bronchial epitheliumd0/50 0/50 0/50 43/50

Accumulation of foamy cells; lungd1/50 0/50 0/50 27/50

Angiectasis; liverd2/50 3/50 4/50 16/50

Nuclear enlargement; kidney proximal tubuled0/50 0/50 0/50 39/50

aData presented for all animals, including animals that became moribund or died before the end of the study.

bDose levels from Kano et al. (2009).

cData from Kano et al. (2009).

dData from JBRC (1998). JBRC did not report statistical significance for the ―All animals‖ comparison.

e

p < 0.01 by χ2test.

Sources: 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 epitheliumc0/50 0/50 0/50 41/50e

Nuclear enlargement; nasal olfactory epitheliumc0/50 0/50 41/50e33/50e

Atrophy; nasal olfactory epitheliumd0/50 0/50 1/50 42/50

Inflammation; nasal cavityd2/50 0/50 7/50 42/50

Atrophy; tracheal epitheliumd0/50 0/50 2/50 49/50

Nuclear enlargement; bronchial epitheliumd0/50 1/50 22/50 48/50

Atrophy; lung/bronchial epitheliumd0/50 0/50 7/50 50/50

Accumulation of foamy cells; lungd0/50 1/50 4/50 45/50

aData presented for all animals, including animals that became moribund or died before the end of the study.

bDose levels from Kano et al. (2009).

cData from Kano et al. (2009).

dData from JBRC (1998). JBRC did not report statistical significance for the ―All animals‖ comparison.

e

p < 0.01 by χ2test.

Sources: Kano et al. (2009) and JBRC (1998).

1 NOAEL and LOAEL values for mice in this study were identified by EPA as 66 and 

2 278 mg/kg-day, respectively, based on nasal inflammation observed in female mice. Nuclear 

3 enlargement of the nasal olfactory epithelium and bronchial epithelium was also observed at a 

4 dose of 278 mg/kg-day in female mice; however, it is unclear whether these alterations represent 

5 adverse toxicological effects. The serum chemistry changes seen in terminal blood samples from 

6 male and female mice (mid- and high-dose groups) are likely related to tumor formation in these 

7 animals. Liver angiectasis, an abnormal dilatation and/or lengthening of a blood or lymphatic 

8 vessel, was seen in male mice given 1,4-dioxane at a dose of 677 mg/kg-day. 

9 Treatment with 1,4-dioxane resulted in an increase in the formation of liver tumors 

10 (adenomas and carcinomas) in male and female mice. The incidence of hepatocellular adenoma 

11 was statistically increased in male mice in the mid-dose group only. The incidence of male mice 

12 with hepatocellular carcinoma or either tumor type (adenoma or carcinoma) was increased in the 

13 low, mid, and high-dose groups. The appearance of the first liver tumor occurred in male mice at 

14 64, 74, 63, and 59 weeks in the control, low- mid-, and high-dose groups, respectively 

15 (Yamazaki, 2006). In female mice, increased incidence was observed for hepatocellular 

16 carcinoma in all treatment groups, while an increase in hepatocellular adenoma incidence was 

17 only seen in the 66 and 278 mg/kg-day dose groups (Table 4-14). The appearance of the first 

18 liver tumor in female mice occurred at 95, 79, 71, and 56 weeks in the control, low-, mid-, and 

19 high-dose groups, respectively (Yamazaki, 2006). The tumor incidence data presented for male 

20 and female mice in Table 4-14 are based on reanalyzed sample data presented in Kano et al. 
55

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (2009) that included lesions in animals that became moribund or died prior to the completion of 

2 the 2-year study.

3 Katagiri et al. (1998) summarized the incidence of hepatocellular adenomas and 

4 carcinomas in control male and female BDF1 mice from ten 2-year bioassays at the JBRC. For 

5 female mice, out of 499 control mice, the incidence rates were 4.4% for hepatocellular adenomas 

6 and 2.0% for hepatocellular carcinomas. Kano et al. (2009) reported a 10% incidence rate for 

7 hepatocellular adenomas and a 0% incidence rate for hepatocellular carcinomas in control female 

8 BDF1. The background incidence rates for male BDF1 mice were 15% and 22.8% for 

9 hepatocellular adenomas and carcinomas, respectively, out of 500 control mice in ten 2-year 

10 bioassays (Katagiri, et al., 1998). Background rates for B6C3F1 mice evaluated by the National 

11 Toxicology Program are similar (10.3% and 21.3% for hepatocellular adenomas and carcinomas 

12 in male mice, respectively; 4.0% and 4.1% for hepatocellular adenomas and carcinomas in 

13 female mice, respectively) to the BDF1 mice background rates observed by JBRC (Haseman, 

14 Huff, & Boorman, 1984). Thus, the BDF1 mouse is not particularly sensitive compared to the 

15 commonly used B6C3F1 strain and indicates that the results obtained by JBRC are reasonable.

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

in drinking water for 2 years

Males Females

Dose (mg/kg-day) 0 49 191 677 0 66 278 964

Nasal Cavity

Adenocarcinoma 0/50 0/50 0/50 0/50 0/50 0/50 0/50 1/50

Esthesioneuroepithelioma 0/50 0/50 0/50 1/50 0/50 0/50 0/50 0/50

Liver

Hepatocellular adenoma 9/50 17/50 23/50a11/50 5/50 31/50a20/50a3/50

Hepatocellular carcinoma 15/50 20/50 23/50 36/50a,b 0/50 6/50c30/50a45/50a,b

Either hepatocellular 

adenoma or carcinoma 23/50 31/50 37/50c

40/50a,b 5/50 35/50a41/50a46/50a,b

a

Significantly different from control by Fisher‘s exact test (p < 0.01).

b

Statistically significant trend for increased tumor incidence by Peto‘s test (p < 0.01).

c

Significantly different from control by Fisher‘s exact test (p < 0.05).

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009).

16 A weight of evidence evaluation of the carcinogenicity studies presented in Section 

17 4.2.1.2 is located in Section 4.7 and Table 4-19.
56

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.2.2. Inhalation Toxicity

4.2.2.1. Subchronic Inhalation Toxicity

1 4.2.2.1.1. Fairley et al. Rabbits, guinea pigs, rats, and mice (3–6/species/group) were exposed 

2 to 1,000, 2,000, 5,000, or 10,000 ppm of 1,4-dioxane vapor two-times a day for 1.5 hours 

3 (3 hours/day) for 5 days/week and 1.5 hours on the 6th day (16.5 hours/week) (Fairley, et al., 

4 1934). Animals were exposed until death occurred or were sacrificed at varying time periods. 

5 At the 10,000 ppm concentration, only one animal (rat) survived a 7-day exposure. The rest of 

6 the animals (six guinea pigs, three mice, and two rats) died within the first five exposures. 

7 Severe liver and kidney damage and acute vascular congestion of the lungs were observed in 

8 these animals. Kidney damage was described as patchy degeneration of cortical tubules with 

9 vascular congestion and hemorrhage. Liver lesions varied from cloudy hepatocyte swelling to 

10 large areas of necrosis. At 5,000 ppm, mortality was observed in two mice and one guinea pig 

11 following 15–34 exposures. The remaining animals were sacrificed following 49.5 hours 

12 (3 weeks) of exposure (three rabbits) or 94.5 hours (5 weeks) of exposure (three guinea pigs). 

13 Liver and kidney damage in both dead and surviving animals was similar to that described for 

14 the 10,000 ppm concentration. Animals (four rabbits, four guinea pigs, six rats, and five mice) 

15 were exposed to 2,000 ppm for 45–102 total exposure hours (approximately 2–6 weeks). Kidney 

16 and liver damage was still apparent in animals exposed to this concentration. Animals exposed 

17 to 1,000 ppm were killed at intervals with the total exposure duration ranging between 78 and 

18 202.5 hours (approximately 4–12 weeks). Cortical kidney degeneration and hepatocyte 

19 degeneration and liver necrosis were observed in these animals (two rabbits, three guinea pigs, 

20 three rats, and four mice). The low concentration of 1,000 ppm was identified by EPA as a 

21 LOAEL for liver and kidney degeneration in rats, mice, rabbits, and guinea pigs in this study.

22 4.2.2.1.2. Kasai et al. Male and female 6-week-old F344/DuCrj rats (10/sex/group) were 

23 exposed to nominal concentrations of 0 (clean air), 100, 200, 400, 800, 1,600, 3,200, or 6,400 

ppm (0, 360, 720, 1,400, 2,900, 5,800, 12000, and 23,000 mg/m324 , respectively) of vaporized 

25 1,4-dioxane (>99% pure) for 6 hours/day, 5 days/week, for 13 weeks in whole body inhalation 

26 chambers (Kasai et al., 2008, 195044). Each inhalation chamber housed 20 individual cages for 

27 10 males and 10 females. During exposure, the concentration of 1,4-dioxane vapor was 

28 determined every 15 minutes by gas chromatography. In addition, during exposure, animals 

29 received food and water ad libitum and the following data were collected: 1) clinical signs and 

30 mortality (daily); 2) BW and food intake (weekly); 3) urinary parameters using Ames reagent 

31 strips (measured during week 13 of the exposure); and 4) 1,4-dioxane content in plasma from 

32 three rats of both sexes (measured on the third day of exposure during weeks 12 and 13 at 1 hour 

33 postmortem). At the end of the 13 week exposure period or at the time of an animal‘s death 

34 during exposure, all organs were collected, weighed, and evaluated for macroscopic lesions. 
57

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Histopathological evaluations of organs and tissues were conducted in accordance with the 

2 OECD test guidelines, including all tissues of the respiratory tract. Hematological and clinical 

3 chemistry parameters were also measured using blood collected from the abdominal aorta of rats 

4 following an overnight fasting at the end of the 13-week exposure period. The measured 

5 hematological and clinical chemistry parameters included: red blood cell count, hemoglobin, 

6 hematocrit, MCV, AST, ALT, glucose, and triglyceride. Liver sections from male and female 

7 rats exposed to 800, 1,600 and 3,200 ppm of 1,4-dioxane were also analyzed for foci (in the 

8 absence of tumor formation) by immunohistochemical expression of glutathione S-transferase 

9 placental form (GST-P). Statistically significant differences between 1,4-dioxane and clean air 

exposed groups were determined using Dunnett‘s test or χ2 10 test. A p-value of 0.05 was 

11 considered the threshold for significance. 

12 All rats exposed to 6,400 ppm of 1,4-dioxane died by the end of the first week of 

13 exposure; the determined cause of death was renal failure and diagnosed as necrosis of the renal 

14 tubules. At concentrations lower than 6,400 ppm, mortality was not observed and all exposed 

15 rats were absent of clinical signs. Exposure-related effects on final BWs, organ weights, 

16 hematology parameters, and histopathological lesions were reported as compared to controls. 

17 Terminal BWs were significantly decreased in both sexes at 200 ppm (males, 6%, p <0.05; 

18 female, 7%, p <0.01) and 3,200 ppm (males, 7%, p <0.01; female, 10%, p <0.01); and 

19 additionally in females at 800 ppm (6%, p <0.01) and 1,600 ppm (8%, p <0.01). Statistically 

20 significant increases in several organ weights were observed, including liver (≥800 ppm, both 

21 sexes, p≤ 0.01; 800 ppm, males, p≤ 0.05), kidney (3,200 ppm, males, p≤ 0.01; ≥800 ppm, 

22 females, p≤ 0.01), and lung (≥1,600 ppm, males, p≤ 0.01; ≥200 ppm, females, p≤ 0.05; 400 

23 ppm, female, p≤ 0.05). Changes in hematological parameters were observed at 3,200 ppm 

24 including increased levels of hemoglobin (both sexes, p≤ 0.05), ALT (males, p≤ 0.05; female, p≤ 

25 0.01), RBC (both sexes, p≤ 0.01), AST (both sexes, p≤ 0.01), hematocrit ( females, p≤ 0.5), and 

26 MCV(both sexes, p≤ 0.1). In males only, at 3,200 ppm, decreased levels of glucose (p≤ 0.01) 

27 and triglyceride (p≤ 0.05) were observed; and in females only, at 200 ppm, an increased AST 

28 level in females (p≤ 0.05) was noted. At 3,200 ppm, in exposed male rats, urinary protein was 

29 slightly decreased; however, this data was not shown in this study. In plasma, a linear increase 

30 in 1,4-dioxane levels was detected at exposure concentrations of 400 ppm and above in both 

31 sexes, and the highest blood levels were observed in females. Exposure and/or sex-related 

32 histopathology findings included nuclear enlargement of the nasal respiratory, nasal olfactory, 

33 tracheal, and bronchial epithelium; vacuolic change in the olfactory and bronchial epithelium; 

34 atrophy of the nasal epithelium; hydropic change in the proximal tubules of the kidney; and 

35 single-cell necrosis and centrilobular swelling in the liver (Table 4-15). Severity of these 

36 histopathological lesions are noted in Table 4-15 as well. Further microscopic evaluation of liver 
58

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 tissue revealed GST-P positive liver foci in both sexes at 3,200 ppm (3/10 males, 2/10 females) 

2 and in females at 1,600 ppm (4/10) (Table 4-15). 

3 The study authors determined nuclear enlargement in the respiratory epithelium as the 

4 most sensitive lesion and a LOAEL value of 100 ppm was identified by the study authors based 

5 on the incidence data of this lesion in both male and female rats. 

6 Table 4-15. Incidence data of histopathological lesions in F344/DuCrj rats exposed 

7 to 1,4-dioxane vapor by whole-body inhalation for 13 weeks. 

8

Males

1,4-dioxane vapor concentration (ppm)a

Effectb0 (clean air) 100 200 400 800 1,600 3,200

Nuclear enlargement; nasal 

respiratory epithelium

0/10 7/10c

(7, 1+)

9/10c

(9, 1+)

7/10c

(7, 1+)

10/10c

(10, 1+)

10/10c

(10, 2+)

10/10c

(10, 2+)

Nuclear enlargement; nasal 

olfactory epithelium 

0/10 0/10 5/10

(5, 1+)

10/10c

(10, 1+)

10/10c

(10, 1+)

10/10c

(10, 2+)

10/10c

(10, 2+)

Nuclear enlargement; tracheal 

epithelium 

0/10 0/10 0/10 0/10 1/10

(1, 1+)

10/10c

(10, 1+)

10/10c

(10, 1+)

Nuclear enlargement; 

bronchial epithelium 

0/10 0/10 0/10 0/10 0/10 9/10c

(9, 1+)

10/10c

(10, 1+)

Vacuolic change; olfactory 

epithelium

0/10 1/10

(1, 1+)

3/10

(3, 1+)

6/10d

(6, 1+)

10/10c

(10, 1+)

10/10c

(10, 1+)

10/10c

(10, 1+)

Vacuolic change; bronchial 

epithelium

0/10 0/10 0/10 0/10 4/10

(4, 1+)

6/10d

(6, 1+)

6/10d

(6, 1+)

Atrophy; olfactory epitheliume- - - - - - -

Hepatocyte centrilobular 

swelling

0/10 0/10 0/10 0/10 0/10 1/10

(1, 1+)

10/10c

(10, 1+)

Hepatocyte single-cell necrosis 0/10 0/10 0/10 0/10 0/10 1/10

(1, 1+)

8/10c

(8, 1+)

Hydropic change; renal 

proximal tubulee

- - - - - - -

Females

1,4-dioxane vapor concentration (ppm)a

Effectb0 (clean air) 100 200 400 800 1,600 3,200

Nuclear enlargement; nasal 

respiratory epithelium

0/10 5/10d

(5, 1+)

9/10c

(9, 1+)

10/10c

(10, 1+)

10/10c

(10, 1+)

10/10c

(10, 2+)

10/10c

(10, 2+)

Nuclear enlargement; nasal 

olfactory epithelium

0/10 2/10

(2, 1+)

6/10d

(6, 1+)

10/10c

(9, 1+; 

1, 2+)

10/10c

(10, 1+)

10/10c

(7, 1+; 

3, 2+)

10/10c

(10, 2+)

Nuclear enlargement; tracheal 

epithelium

0/10 0/10 0/10 0/10 2/10

(2, 1+)

7/10c

(7, 1+)

10/10c

(10, 1+)

Nuclear enlargement; 

bronchial epithelium

0/10 0/10 0/10 0/10 0/10 0/10 10/10c

(10, 1+)

Vacuolic change; olfactory 

epithelium

0/10 1/10

(1, 1+)

2/10

(2, 1+)

3/10

(3, 1+)

7/10c

(7, 1+)

9/10c

(9, 1+)

10/10c

(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+)

5/10d

(5, 1+)

5/10d

(5, 1+)

4/10

(4, 1+)

Hepatocyte centrilobular 

swelling

0/10 0/10 0/10 0/10 0/10 1/10

(1, 1+)

8/10c

(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 6/10d

(6, 1+)

aData are presented for sacrificed animals.

bValues 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 χ2test.

d

p ≤ 0.05 by χ2test.

eData were not reported for male rats.

Source: Kasai et al. (2008)

4.2.2.2. Chronic Inhalation Toxicity and Carcinogenicity

1 4.2.2.2.1. Torkelson et al. Whole body exposures of male and female Wistar rats (288/sex) to 

2 1,4-dioxane vapors (99.9% pure) at a concentration of 0.4 mg/L (111 ppm), were carried out 

3 7 hours/day, 5 days/week for 2 years (Torkelson, et al., 1974). The age of the animals at the 

4 beginning of the study was not provided. The concentration of 1,4-dioxane vapor during 

5 exposures was determined with infrared analyzers. Food and water were available ad libitum 

6 except during exposures. Endpoints examined included clinical signs, eye and nasal irritation, 

7 skin condition, respiratory distress, and tumor formation. BWs were determined weekly. 

8 Standard hematological parameters were determined on all surviving animals after 16 and 

9 23 months of exposure. Blood collected at termination was used also for determination of 

10 clinical chemistry parameters (serum AST and ALP activities, blood urea nitrogen [BUN], and 

11 total protein). Liver, kidneys, and spleen were weighed and the major tissues and organs were 

12 processed for microscopic examination (lungs, trachea, thoracic lymph nodes, heart, liver, 

13 pancreas, stomach, intestine, spleen, thyroid, mesenteric lymph nodes, kidneys, urinary bladder, 

14 pituitary, adrenals, testes, ovaries, oviduct, uterus, mammary gland, lacrimal gland, lymph nodes, 

15 brain, vagina, and bone marrow, and any abnormal growths). Nasal tissues were not obtained for 

16 histopathological evaluation. Control and experimental groups were compared statistically using 

Student‘s t test, Yates corrected χ217 test, or Fisher‘s Exact test.

18 Exposure to 1,4-dioxane vapors had no significant effect on mortality or BW gain and 

19 induced no signs of eye or nasal irritation or respiratory distress. Slight, but statistically 

20 significant, changes in hematological and clinical chemistry parameters were within the normal 

21 physiological limits and were considered to be of no toxicological importance by the 

22 investigators. Altered hematological parameters included decreases in packed cell volume, RBC 

23 count, and hemoglobin, and an increase in WBC count in male rats. Clinical chemistry changes 

24 consisted of a slight decrease in both BUN (control—23 ± 9.9; 111-ppm 1,4-dioxane—19.8 ± 

25 8.8) and ALP activity (control—34.4 ± 12.1; 111-ppm 1,4-dioxane—29.9 ± 9.2) and a small 

26 increase in total protein (control—7.5 ± 0.37; 111-ppm 1,4-dioxane—7.9 ± 0.53) in male rats 

27 (values are mean ± standard deviation). Organ weights were not significantly affected. 

28 Microscopic examination of organs and tissues did not reveal any treatment-related effects. 
60

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Based on the lack of significant effects on several endpoints, EPA identified the exposure 

2 concentration of 0.4 mg/L (111 ppm) as a free standing NOAEL. The true NOAEL was likely to 

3 be higher.

4 Tumors, observed in all groups including controls, were characteristic of the rat strain 

5 used and were considered unrelated to 1,4-dioxane inhalation. The most common tumors were 

6 reticulum cell sarcomas and mammary tumors. Using Fisher‘s Exact test and a significance level 

7 of p < 0.05, no one type of tumor occurred more frequently in treated rats than in controls. No 

8 hepatic or nasal cavity tumors were seen in any rat. 

9 4.2.2.2.2. Kasai et al. Groups of male 6-week-old F344/DuCrj rats (50/group) weighing 120 ± 

10 5g (mean ± SD) at the beginning of the study were exposed via inhalation to nominal 

concentrations of 0 (clean air), 50, 250, and 1,250 ppm (0, 180, 900, and 4,500 mg/m311 , 

12 respectively) of vaporized 1,4-dioxane (>99% pure) for 6 hours/day, 5 days/week, for 104 weeks 

13 (2 years) in whole body inhalation chambers (Kasai, et al., 2009). Each inhalation chamber 

14 housed male rats individually in stainless-steel wire hanging cages. The authors stated female

15 counterparts were not exposed given data illustrating the absence of induced mesotheliomas 

16 following exposure to 1,4-dioxane in drinking water (Yamazaki, et al., 1994). During exposure, 

17 the concentration of 1,4-dioxane vapor was determined every 15 minutes by gas chromatography 

18 and animals received food and water ad libitum. In addition, during the 2-year exposure period, 

19 clinical signs and mortality were recorded daily. BW and food intake were measured once 

20 weekly for the first 14 weeks of exposure, and thereafter, every 4 weeks. At the end of the 2-

21 year exposure period or at the time of an animal‘s death during exposure, all organs were 

22 collected, weighed, and evaluated for macroscopic lesions. Additional examinations were 

23 completed on rats sacrificed at the end of the 2-year exposure period. Endpoints examined 

24 included: 1) histopathological evaluations of organs and tissues outlined in the OECD test 

25 guideline which included all tissues of the respiratory tract; 2) measurement of urinary 

26 parameters using Ames reagent strips during the last week of the exposure period; and 3) 

27 measurement of hematological parameters using blood collected from the abdominal aorta of rats 

28 following an overnight fasting at the end of the 2-year exposure period. Organs and tissues 

29 collected for histopathological examination were fixed in 10% neutral buffered formalin with the 

30 exception of nasal cavity samples. Nasal tissue was trimmed transversely at three levels after 

31 decalcification and fixation in a formic acid-formalin solution. The levels were demarcated at 

32 the following points: at the posterior edge of the upper incisor teeth (level 1), at the incisive 

33 papilla (level 2), and at the anterior edge of the upper molar teeth (level 3). All tissue samples 

34 were embedded in paraffin, and then sectioned (at 5 μm thickness) and stained with hematoxylin 

35 and eosin (H&E). For measured hematological parameters, analyses included: red blood cell 

36 count, hemoglobin, hematocrit, MCV, mean corpuscular hemoglobin (MCH), AST, ALT, ALP, 

and γ-GTP. Dunnett‘s test, χ2 37 test, and Fisher‘s exact test were used to determine statistical 
61

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 differences between 1,4-dioxane exposed and clean air exposed group data. A p-value of 0.05 

2 was considered the threshold for significance. 

3 Growth rates and survival rates were analyzed. Growth rates were not significantly 

4 affected by 1,4-dioxane exposures, but a decreasing trend in growth was observed during the 

5 latter half of the 2-year exposure period for all exposure doses (i.e., 50, 250, and 1,250 ppm). 

6 Survival rates were significantly decreased following 91 weeks of exposure to 1,250 ppm of 

7 1,4-dioxane. The authors attributed these deaths to increased incidences of peritoneal 

8 mesotheliomas, but also noted that nasal tumors could be a contributing factor. Terminal 

9 survival rates were 37/50, 37/50, 29/50, and 25/50 for 0, 50, 250, and 1,250 ppm exposed groups, 

10 respectively. Statistically significant changes in body and organ weights were also observed. 

11 Following exposure to 1,250 ppm of 1,4-dioxane, terminal body weights of rats were 6% less 

12 than the control (p≤ 0.05) and relative liver and lung weights of rats were 27% (p≤ 0.01), and 2% 

13 greater than the control, respectively. It is of note that the observed change in terminal body 

14 weight was not an effect of food consumption, which was determined to be unaltered by the 

15 study authors. 

16 Deformity in the nose was the only clinical sign reported in this study. This deformity 

17 was seen at exposure weeks 74 and 79 in one rat each, exposed to 250 ppm and 1,250 ppm of 

18 1,4-dioxane, respectively. Both of these rats did not survive the 2-year exposure with deaths 

19 caused by malignant nasal tumors. Altered hematological parameters were observed with 

20 significant changes at 1,250 ppm. Altered endpoints included decreased hemoglobin (p≤ 0.05), 

21 MCV (p≤ 0.05), and MCH (p≤ 0.01) and increased AST (p≤ 0.01), ALT (p≤ 0.01), ALP (p≤ 

22 0.01), and γ-GTP (p≤ 0.01) levels. In addition, urine pH was decreased in 1,250 ppm exposed 

23 rats (p≤ 0.05). 

24 Histopathology findings of pre- and nonneoplastic lesions associated with 1,4-dioxane 

25 treatment were seen in the nasal cavity, liver, and kidneys (Table 4-16). At the highest 

26 concentration of 1,250 ppm, all pre- and nonneoplastic lesions were significantly increased, as 

27 compared to controls, with the exception of clear and mixed cell foci in the liver. At the lowest 

28 concentration of 50 ppm, nuclear enlargement of the respiratory epithelium was the most 

29 sensitive lesion observed in the nasal cavity. Based on this finding, the study authors identified a 

30 LOAEL of 50 ppm in male rats. 

31 Tumor development was observed in the nasal cavity (squamous cell carcinoma), liver 

32 (hepatocellular adenoma and carcinoma), peritoneum (peritoneal mesothelioma), kidney (renal 

33 cell carcinoma), mammary gland (fibroadenoma and adenoma), Zymbal gland (adenoma), and 

34 subcutaneous tissue (subcutis fibroma). Tumor incidences with a dose-dependent, statistically 

35 significant positive trend (Peto‘s test) included nasal squamous cell carcinoma (p≤ 0.01), 

36 hepatocellular adenoma (p≤ 0.01), peritoneal mesothelioma (p≤ 0.01), mammary gland 

37 fibroadenoma (p≤ 0.05), and Zymbal gland adenoma (p≤ 0.01). Renal cell carcinoma was also 
62

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 identified as statistically significant with a positive dose-dependent trend (p≤ 0.01); however, no 

2 tumor incidences were reported at 50 and 250 ppm. At 1,250 ppm, significant increases in nasal 

3 squamous cell carcinoma, hepatocellular adenoma, and peritoneal mesothelioma were observed. 

4 At 250 ppm, significant increases in peritoneum mesothelioma and subcutis fibroma were 

5 observed. Table 4-17 presents a summary of tumor incidences found in this study. Further 

6 characterizations of neoplasms revealed nasal squamous cell carcinoma occurred at the dorsal 

7 area of the nose (levels 1-3) marked by keratinization and the progression of growth into 

8 surrounding tissue. Peritoneal mesotheliomas were characterized by complex branching 

9 structures originating from the mesothelium of the scrotal sac. Invasive growth into surrounding 

10 tissues was occasionally observed for peritoneal mesotheliomas. 

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 50/50a48/50a38/50a

Squamous cell metaplasia; nasal respiratory epithelium 0/50 0/50 7/50b44/50a

Squamous cell hyperplasia; nasal respiratory epithelium 0/50 0/50 1/50 10/50a

Inflammation; nasal respiratory epithelium 13/50 9/50 7/50 39/50a

Nuclear enlargement; nasal olfactory epithelium 0/50 48/50a48/50a45/50a

Respiratory metaplasia; nasal olfactory epithelium 11/50 34/50a49/50a48/50a

Atrophy; nasal olfactory epithelium 0/50 40/50a47/50a48/50a

Inflammation; nasal olfactory epithelium 0/50 2/50 32/50a34/50a

Hydropic change; lamina propria 0/50 2/50 36/50a49/50a

Sclerosis; lamina propria 0/50 0/50 22/50a40/50a

Proliferation; nasal gland 0/50 1/50 0/50 6/50b

Nuclear enlargement; liver centrilobular 0/50 0/50 1/50 30/50a

Necrosis; liver centrilobular 1/50 3/50 6/50 12/50a

Spongiosis hepatis; liver 7/50 6/50 13/50 19/50a

Clear cell foci; liver 15/50 17/50 20/50 23/50

Basophilic cell foci; liver 17/50 20/50 15/50 44/50a

Acidophilic cell foci; liver 5/50 10/50 12/50 25/50a

Mixed-cell foci; liver 5/50 3/50 4/50 14/50

Nuclear enlargement; kidney proximal tubule 0/50 1/50 20/50a47/50a

Hydropic change; kidney proximal tubule 0/50 0/50 5/50 6/50a

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 6/50b,c

Hepatocellular adenoma 1/50 2/50 3/50 21/50a,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 14/50a41/50a,c

Mammary gland fibroadenoma 1/50 2/50 3/50 5/50d

Mammary gland adenoma 0/50 0/50 0/50 1/50

Zymbal gland adenoma 0/50 0/50 0/50 4/50c

Subcutis fibroma 1/50 4/50 9/50a5/50

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. 

1 Bull et al. (1986) tested 1,4-dioxane as a cancer initiator in mice using oral, 

2 subcutaneous, and topical routes of exposure. A group of 40 female SENCAR mice (6–8 weeks

3 old) was administered a single dose of 1,000 mg/kg 1,4-dioxane (purity >99%) by gavage, 

4 subcutaneous injection, or topical administration (vehicle was not specified). A group of rats 

5 was used as a vehicle control (number of animals not specified). Food and water were provided 

6 ad libitum. Two weeks after administration of 1,4-dioxane, 12-O-tetradecanoylphorbol-13-

7 acetate (TPA) (1.0 μg in 0.2 mL of acetone) was applied to the shaved back of mice 

8 3 times/week for a period of 20 weeks. The yield of papillomas at 24 weeks was selected as a 

9 potential predictor of carcinoma yields at 52 weeks following the start of the promotion 

10 schedule. Acetone was used instead of TPA in an additional group of 20 mice in order to 

11 determine whether a single dose of 1,4-dioxane could induce tumors in the absence of TPA 

12 promotion.

13 1,4-Dioxane did not increase the formation of papillomas compared to mice initiated with 

14 vehicle and promoted with TPA, indicating lack of initiating activity under the conditions of the 

15 study. Negative results were obtained for all three exposure routes. A single dose of 

16 1,4-dioxane did not induce tumors in the absence of TPA promotion.
64

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.2.3.2. King et al. 

1 1,4-Dioxane was evaluated for complete carcinogenicity and tumor promotion activity in 

2 mouse skin (King, Shefner, & Bates, 1973). In the complete carcinogenicity study, 0.2 mL of a 

3 solution of 1,4-dioxane (purity not specified) in acetone was applied to the shaved skin of the 

4 back of Swiss Webster mice (30/sex) 3 times/week for 78 weeks. Acetone was applied to the 

5 backs of control mice (30/sex) for the same time period. In the promotion study, each animal 

6 was treated with 50 μg of dimethylbenzanthracene 1 week prior to the topical application of the 

7 1,4-dioxane solution described above (0.2 mL, 3 times/week, 78 weeks) (30 mice/sex). Acetone 

8 vehicle was used in negative control mice (30/sex). Croton oil was used as a positive control in 

9 the promotion study (30/sex). Weekly counts of papillomas and suspect carcinomas were made 

10 by gross examination. 1,4-Dioxane was also administered in the drinking water (0.5 and 1%) to 

11 groups of Osborne-Mendel rats (35/sex/group) and B6C3F1 mice for 42 weeks (control findings 

12 were only reported for 34 weeks).

13 1,4-Dioxane was negative in the complete skin carcinogenicity test using dermal 

14 exposure. One treated female mouse had malignant lymphoma; however, no papillomas were 

15 observed in male or female mice by 60 weeks. Neoplastic lesions of the skin, lungs, and kidney 

16 were observed in mice given the promotional treatment with 1,4-dioxane. In addition, the 

17 percentage of mice with skin tumors increased sharply after approximately 10 weeks of 

18 promotion treatment. Significant mortality was observed when 1,4-dioxane was administered as 

19 a promoter (only 4 male and 5 female mice survived for 60 weeks), but not as a complete 

20 carcinogen (22 male and 25 female mice survived until 60 weeks). The survival of acetone21 treated control mice in the promotion study was not affected (29 male and 26 female mice 

22 survived until 60 weeks); however, the mice treated with croton oil as a positive control 

23 experienced significant mortality (0 male and 1 female mouse survived for 60 weeks). The 

24 incidence of mice with papillomas was similar for croton oil and 1,4-dioxane; however, the 

25 tumor multiplicity (i.e., number of tumors/mouse) was higher for the croton oil treatment.

26 Oral administration of 1,4-dioxane in drinking water caused appreciable mortality in rats, 

27 but not mice, and increased weight gain in surviving rats and male mice. Histopathological 

28 lesions (i.e., unspecified liver and kidney effects) were also reported in exposed male and female 

29 rats; however, no histopathological changes were indicated for mice.

30 1,4-Dioxane was demonstrated to be a tumor promoter, but not a complete carcinogen in 

31 mouse skin, in this study. Topical administration for 78 weeks following initiation with 

32 dimethylbenzanthracene caused an increase in the incidence and multiplicity of skin tumors in 

33 mice. Tumors were also observed at remote sites (i.e., kidney and lung), and survival was 

34 affected. Topical application of 1,4-dioxane for 60 weeks in the absence of the initiating 

35 treatment produced no effects on skin tumor formation or mortality in mice.
65

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.2.3.3. Lundberg et al. 

1 Lundberg et al. (1987) evaluated the tumor promoting activity of 1,4-dioxane in rat liver. 

2 Male Sprague Dawley rats (8/dose group, 19 for control group) weighing 200 g underwent a 

3 partial hepatectomy followed 24 hours later by an i.p. injection of 30 mg/kg diethylnitrosamine 

4 (DEN) (initiation treatment). 1,4-Dioxane (99.5% pure with 25 ppm butylated hydroxytoluene 

5 as a stabilizer) was then administered daily by gavage (in saline vehicle) at doses of 0, 100, or 

6 1,000 mg/kg-day, 5 days/week for 7 weeks. Control rats were administered saline daily by 

7 gavage, following DEN initiation. 1,4-Dioxane was also administered to groups of rats that were 

8 not given the DEN initiating treatment (saline used instead of DEN). Ten days after the last 

9 dose, animals were sacrificed and liver sections were stained for GGT. The number and total 

10 volume of GGT-positive foci were determined.

11 1,4-Dioxane did not increase the number or volume of GGT-foci in rats that were not 

12 given the DEN initiation treatment. The high dose of 1,4-dioxane (1,000 mg/kg-day) given as a 

13 promoting treatment (i.e., following DEN injection) produced an increase in the number of 

14 GGT-positive foci and the total foci volume. Histopathological changes were noted in the livers 

15 of high-dose rats. Enlarged, foamy hepatocytes were observed in the midzonal region of the 

16 liver, with the foamy appearance due to the presence of numerous fat-containing cytoplasmic 

17 vacuoles. These results suggest that cytotoxic doses of 1,4-dioxane may be associated with 

18 tumor promotion of 1,4-dioxane in rat liver.

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND INHALATION 

4.3.1. Giavini et al. 

19 Pregnant female Sprague Dawley rats (18–20 per dose group) were given 1,4-dioxane 

20 (99% pure, 0.7% acetal) by gavage in water at concentrations of 0, 0.25, 0.5, or 1 mL/kg-day, 

21 corresponding to dose estimates of 0, 250, 500, or 1,000 mg/kg-day (density of 1,4-dioxane is 

22 approximately 1.03 g/mL) (Giavini, Vismara, & Broccia, 1985). The chemical was administered 

23 at a constant volume of 3 mL/kg on days 6–15 of gestation. Food consumption was determined 

24 daily and BWs were measured every 3 days. The dams were sacrificed with chloroform on 

25 gestation day 21 and the numbers of corpora lutea, implantations, resorptions, and live fetuses 

26 were recorded. Fetuses were weighed and examined for external malformations prior to the 

27 evaluation of visceral and skeletal malformations (Wilson‘s free-hand section method and 

28 staining with Alizarin red) and a determination of the degree of ossification.

29 Maternal weight gain was reduced by 10% in the high-dose group (1,000 mg/kg-day). 

30 Food consumption for this group was 5% lower during the dosing period, but exceeded control 

31 levels for the remainder of the study. No change from control was observed in the number of 

32 implantations, live fetuses, or resorptions; however, fetal birth weight was 5% lower in the 
66

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 highest dose group (p < 0.01). 1,4-Dioxane exposure did not increase the frequency of major 

2 malformations or minor anomalies and variants. Ossification of the sternebrae was reduced in 

3 the 1,000 mg/kg-day dose group (p < 0.05). The study authors suggested that the observed delay 

4 in sternebrae ossification combined with the decrease in fetal birth weight indicated a 

5 developmental delay related to 1,4-dioxane treatment. NOAEL and LOAEL values of 500 and 

6 1,000 mg/kg-day were identified from this study by EPA and based on delayed ossification of 

7 the sternebrae and reduced fetal BWs.

4.4. OTHER DURATION OR ENDPOINT-SPECIFIC STUDIES 

4.4.1. Acute and Short-term Toxicity

8 The acute (≤ 24 hours) and short-term toxicity studies (<30 days) of 1,4-dioxane in 

9 laboratory animals are summarized in Table 4-18. Several exposure routes were employed in 

10 these studies, including dermal application, drinking water exposure, gavage, vapor inhalation, 

11 and i.v. or i.p. injection. 

4.4.1.1. Oral Toxicity

12 Mortality was observed in many acute high-dose studies, and LD50 values for 

13 1,4-dioxane were calculated for rats, mice, and guinea pigs (Laug, Calvery, Morris, & Woodard, 

14 1939; Pozzani, Weil, & Carpenter, 1959; Smyth Hf Jr, Seaton, & Fischer, 1941). Clinical signs 

15 of CNS depression were observed, including staggered gait, narcosis, paralysis, coma, and death 

16 (de Navasquez, 1935; Laug, et al., 1939; Nelson, 1951; Schrenk & Yant, 1936). Severe liver and 

17 kidney degeneration and necrosis were often seen in acute studies (David, 1964; de Navasquez, 

18 1935; JBRC, 1998; Kesten, Mulinos, & Pomerantz, 1939; Laug, et al., 1939; Schrenk & Yant, 

19 1936). JBRC (1998) additionally reported histopathological lesions in the nasal cavity and the 

20 brain of rats following 2 weeks of exposure to 1,4-dioxane in the drinking water.

4.4.1.2. Inhalation Toxicity

21 Acute and short-term toxicity studies (all routes) are summarized in Table 4-18. 

22 Mortality occurred in many high-concentration studies (Nelson, 1951; Pozzani, et al., 1959; 

23 Wirth & Klimmer, 1936). Inhalation of 1,4-dioxane caused eye and nasal irritation, altered 

24 respiration, and pulmonary edema and congestion (Yant, et al., 1930). Clinical signs of CNS 

25 depression were observed, including staggered gait, narcosis, paralysis, coma, and death (Nelson, 

26 1951; Wirth & Klimmer, 1936). Liver and kidney degeneration and necrosis were also seen in 

27 acute and short-term inhalation studies (Drew, Patel, & Lin, 1978; Fairley, et al., 1934). 
67

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 Dosea Reference

Oral studies

Rat (inbred strain 

and gender 

unspecified)

Oral via 

drinking water

1–10 days of 

exposure

Ultrastructural 

changes in the 

kidney, degenerative 

nephrosis, hyaline 

droplet accumulation, 

crystal formation in 

mitochondria

11,000 mg/kg-day 

(5%)

David (1964)

Rat (strain and 

gender unspecified)

Oral via 

drinking water

5–12 days of 

exposure

Extensive 

degeneration of the 

kidney, liver damage, 

mortality in 

8/10 animals by 

12 days 

11,000 mg/kg-day 

(5%)

Kesten et al.

(1939)

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 hours prior to 

sacrifice

Increased ODC 

activity, hepatic 

CYP450 content, and 

DNA single-strand 

breaks

840 mg/kg (ODC 

activity only)

Kitchin and 

Brown (1990)

Female Carworth 

Farms-Nelson rat

Gavage Determination of a 

single dose LD50

Lethality LD50 = 6,400 mg/kg 

(14,200 ppm)

Pozzani et al.

(1959)

Male Wistar rat, 

guinea pig

Gavage Single dose, 

LD50 determination

Lethality LD50 (mg/kg):

rat = 7,120

guinea pig = 3,150

Smyth et al.

(1941)

Rat, mouse, guinea 

pig

Gavage Single dose; 

several dose 

groups

Clinical signs of CNS 

depression, stomach 

hemorrhage, kidney 

enlargement, and 

liver and kidney

degeneration

LD50 (mg/kg):

mouse = 5,900

rat = 5,400

guinea pig = 4,030

Laug et al.

(1939)

Rabbit Gavage Single gavage dose 

of 0, 207, 1,034, or 

2,068 mg/kg-day

Clinical signs of CNS 

depression, mortality 

at 2068 mg/kg, renal 

toxicity (polyuria 

followed by anuria), 

histopathological 

changes in liver and 

kidneys

1,034 mg/kg-day de Navasquez

(1935)

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 Dosea 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 days 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 hours of 

exposure

Mortality and 

narcosis 6,000 ppm

Nelson

(1951)

Female Carworth 

Farms-Nelson rat

Vapor 

inhalation

Determination of a 

4-hour inhalation 

LC50

Lethality LC50 = 51.3 mg/L Pozzani et al.

(1959)

Mouse, cat Vapor 

inhalation

8 hours/day for 

17 days

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 hours exposure, 

for 5 days; 

1.5 hour exposure 

for 1 day

Degeneration and 

necrosis in the kidney 

and liver, vascular 

congestion in the 

lungs

10,000 ppm Fairley et 

al.(1934)

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 Dosea Reference

Female 

Sprague Dawley rat

i.p. injection Single dose; 

LD50 values 

determined 

24 hours and 

14 days after 

injection

Increased serum SDH 

activity at 1/16th of 

the LD50 dose; no 

change at higher or 

lower doses

LD50 (mg/kg):

24 hours = 4,848

14 days = 799

Lundberg et 

al. (1986)

CBA/J mouse i.p. injection Daily injection for 

7 days, 0, 0.1, 1, 5, 

and 10%

Slightly lower 

lymphocyte response 

to mitogens

2,000 mg/kg-day 

(10%)

Thurman et 

al. (1978)

aLowest 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

1 Clinical signs of CNS depression have been reported in humans and laboratory animals 

2 following high dose exposure to 1,4-dioxane (see Sections 4.1 and 4.2.1.1). Neurological 

3 symptoms were reported in the fatal case of a worker exposed to high concentrations of 

4 1,4-dioxane through both inhalation and dermal exposure (Johnstone, 1959). These symptoms 

5 included headache, elevation in blood pressure, agitation and restlessness, and coma. Autopsy 

6 findings demonstrated perivascular widening in the brain, with small foci of demyelination in 

7 several regions (e.g., cortex, basal nuclei). It was suggested that these neurological changes may 

8 have been secondary to anoxia and cerebral edema. In laboratory animals, the neurological 

9 effects of acute high-dose exposure included staggered gait, narcosis, paralysis, coma, and death 

10 (de Navasquez, 1935; Laug, et al., 1939; Nelson, 1951; Schrenk & Yant, 1936; Yant, et al., 

11 1930). The neurotoxicity of 1,4-dioxane was further investigated in several studies described 

12 below (Frantik, Hornychova, & Horvath, 1994; Goldberg, Johnson, Pozzani, & Smyth, 1964; 

13 Kanada, Miyagawa, Sato, Hasegawa, & Honma, 1994; Knoefel, 1935).

4.4.2.1. Frantik et al.

14 The acute neurotoxicity of 1,4-dioxane was evaluated following a 4-hour inhalation 

15 exposure to male Wistar rats (four per dose group) and a 2-hour inhalation exposure to female 

16 H-strain mice (eight per dose group) (Frantik, et al., 1994). Three exposure groups and a control 

17 group were used in this study. Exposure concentrations were not specified, but apparently were 

18 chosen from the linear portion of the concentration-effect curve. The neurotoxicity endpoint 

19 measured in this study was the inhibition of the propagation and maintenance of an electrically20 evoked seizure discharge. This endpoint has been correlated with the behavioral effects and 

21 narcosis that occur following acute exposure to higher concentrations of organic solvents. 

22 Immediately following 1,4-dioxane exposure, a short electrical impulse was applied through ear 

23 electrodes (0.2 seconds, 50 hertz (Hz), 180 volts (V) in rats, 90 V in mice). Several time 

24 characteristics of the response were recorded; the most sensitive and reproducible measures of 
70

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 chemically-induced effects were determined to be the duration of tonic hind limb extension in 

2 rats and the velocity of tonic extension in mice.

3 Linear regression analysis of the concentration-effect data was used to calculate an 

4 isoeffective air concentration that corresponds to the concentration producing a 30% decrease in 

5 the maximal response to an electrically-evoked seizure. The isoeffective air concentrations for 

6 1,4-dioxane were 1,860 ± 200 ppm in rats and 2,400 ± 420 ppm in mice. A NOAEL value was 

7 not identified from this study.

4.4.2.2. Goldberg et al. 

8 Goldberg et al. (1964) evaluated the effect of solvent inhalation on pole climb 

9 performance in rats. Female rats (Carworth Farms Elias strain) (eight per dose group) were 

10 exposed to 0, 1,500, 3,000, or 6,000 ppm of 1,4-dioxane in air for 4 hours/day, 5 days/weeks, for 

11 10 exposure days. Conditioned avoidance and escape behaviors were evaluated using a pole 

12 climb methodology. Prior to exposure, rats were trained to respond to a buzzer or shock stimulus 

13 by using avoidance/escape behavior within 2 seconds. Behavioral criteria were the abolishment 

14 or significant deferment (>6 seconds) of the avoidance response (conditioned or buzzer response) 

15 or the escape response (buzzer plus shock response). Behavioral tests were administered on day

16 1, 2, 3, 4, 5, and 10 of the exposure period. Rat BWs were also measured on test days. 

17 1,4-Dioxane exposure produced a dose-related effect on conditioned avoidance behavior 

18 in female rats, while escape behavior was generally not affected. In the 1,500 ppm group, only 

19 one of eight rats had a decreased avoidance response, and this only occurred on days 2 and 5 of 

20 exposure. A larger number of rats exposed to 3,000 ppm (two or three of eight) experienced a

21 decrease in the avoidance response, and this response was observed on each day of the exposure 

22 period. The maximal decrease in the avoidance response was observed in the 6,000 ppm group 

23 during the first 2 days of exposure (75–100% of the animals were inhibited in this response). For 

24 exposure days 3–10, the percent of rats in the 6,000 ppm group with significant inhibition of the 

25 avoidance response ranged from 37–62%. At the end of the exposure period (day 10), the BWs 

26 for rats in the high exposure group were lower than controls.

4.4.2.3. Kanada et al.

27 Kanada et al. evaluated the effect of oral exposure to 1,4-dioxane on the regional 

28 neurochemistry of the rat brain (Kanada, et al., 1994). 1,4-Dioxane was administered by gavage 

29 to male Sprague Dawley rats (5/group) at a dose of 1,050 mg/kg, approximately equal to one30 fourth the oral LD50. Rats were sacrificed by microwave irradiation to the head 2 hours after 

31 dosing, and brains were dissected into small brain areas. Each brain region was analyzed for the 

32 content of biogenic amine neurotransmitters and their metabolites using high-performance liquid 

33 chromatography (HPLC) or GC methods. 1,4-Dioxane exposure was shown to reduce the 

34 dopamine and serotonin content of the hypothalamus. The neurochemical profile of all other 

35 brain regions in exposed rats was similar to control rats.
71

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.4.2.4. Knoefel 

1 The narcotic potency of 1,4-dioxane was evaluated following i.p. injection in rats and 

2 gavage administration in rabbits (Knoefel, 1935). Rats were given i.p. doses of 20, 30, or 

3 50 mmol/kg. No narcotic effect was seen at the lowest dose; however, rats given 30 mmol/kg 

4 were observed to sleep approximately 8–10 minutes. Rats given the high dose of 50 mmol/kg 

5 died during the study. Rabbits were given 1,4-dioxane at oral doses of 10, 20, 50, 75, or 

6 100 mmol/kg. No effect on the normal erect animal posture was observed in rabbits treated with 

7 less than 50 mmol/kg. At 50 and 75 mmol/kg, a semi-erect or staggering posture was observed; 

8 lethality occurred at both the 75 and 100 mmol/kg doses.

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

OF ACTION

4.5.1. Genotoxicity

9 The genotoxicity data for 1,4-dioxane are presented in Tables 4-19 and 4-20 for in vitro 

10 and in vivo tests, respectively. 1,4-Dioxane has been tested for genotoxic potential using in vitro 

11 assay systems with prokaryotic organisms, non-mammalian eukaryotic organisms, and 

12 mammalian cells, and in vivo assay systems using several strains of rats and mice. In the large 

13 majority of in vitro systems, 1,4-dioxane was not genotoxic. Where a positive genotoxic 

14 response was observed, it was generally observed in the presence of toxicity. Similarly, 

15 1,4-dioxane was not genotoxic in the majority of available in vivo studies. 1,4-Dioxane did not 

16 bind covalently to DNA in a single study with calf thymus DNA. Several investigators have 

17 reported that 1,4-dioxane caused increased DNA synthesis indicative of cell proliferation. 

18 Overall, the available literature indicates that 1,4-dioxane is nongenotoxic or weakly genotoxic.

19 Negative findings were reported for mutagenicity in in vitro assays with the prokaryotic 

20 organisms Salmonella typhimurium, Escherichia coli, and Photobacterium phosphoreum

21 (Mutatox assay) (Haworth, Lawlor, Mortelmans, Speck, & Zeiger, 1983; Hellmér & Bolcsfoldi, 

22 1992; Khudoley, Mizgireuv, & Pliss, 1987; Kwan, Dutka, Rao, & Liu, 1990; Morita & Hayashi, 

23 1998; Nestmann, Otson, Kowbel, Bothwell, & Harrington, 1984; Stott, et al., 1981). In in vitro 

24 assays with nonmammalian eukaryotic organisms, negative results were obtained for the 

25 induction of aneuploidy in yeast (Saccharomyces cerevisiae) and in the sex-linked recessive 

26 lethal test in Drosophila melanogaster (Yoon, Mason, Valencia, Woodruff, & Zimmering, 1985; 

27 Zimmermann, Mayer, Scheel, & Resnick, 1985). In the presence of toxicity, positive results 

28 were reported for meiotic nondisjunction in Drosophila (Munoz & Barnett, 2002).

29 The ability of 1,4-dioxane to induce genotoxic effects in mammalian cells in vitro has 

30 been examined in model test systems with and without exogenous metabolic activation and in 

31 hepatocytes that retain their xenobiotic-metabolizing capabilities. 1,4-Dioxane was reported as 

32 negative in the mouse lymphoma cell forward mutation assay (McGregor et al., 1991; Morita & 
72

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Hayashi, 1998). 1,4-Dioxane did not produce chromosomal aberrations or micronucleus 

2 formation in Chinese hamster ovary (CHO) cells (Galloway et al., 1987; Morita & Hayashi, 

3 1998). Results were negative in one assay for sister chromatid exchange (SCE) in CHO (Morita 

4 & Hayashi, 1998) and were weakly positive in the absence of metabolic activation in another 

5 (Galloway, et al., 1987). In rat hepatocytes, 1,4-dioxane exposure in vitro caused single-strand 

6 breaks in DNA at concentrations also toxic to the hepatocytes (Sina, Bean, Dysart, Taylor, & 

7 Bradley, 1983) and produced a positive genotoxic response in a cell transformation assay with 

8 BALB/3T3 cells also in the presence of toxicity (Sheu, Moreland, Lee, & Dunkel, 1988).

9 1,4-Dioxane was not genotoxic in the majority of available in vivo mammalian assays. 

10 Studies of micronucleus formation following in vivo exposure to 1,4-dioxane produced mostly 

11 negative results, including studies of bone marrow micronucleus formation in B6C3F1, BALB/c, 

12 CBA, and C57BL6 mice (McFee, Abbott, Gulati, & Shelby, 1994; Mirkova, 1994; Tinwell & 

13 Ashby, 1994) and micronucleus formation in peripheral blood of CD1 mice (Morita, 1994; 

14 Morita & Hayashi, 1998). Mirkova (1994) reported a dose-related increase in the incidence of 

15 bone marrow micronuclei in male and female C57BL6 mice 24 or 48 hours after administration 

16 of 1,4-dioxane. At a sampling time of 24 hours, a dose of 450 mg/kg produced no change 

17 relative to control, while doses of 900, 1,800, and 3,600 mg/kg increased the incidence of bone 

18 marrow micronuclei by approximately two-, three-, and fourfold, respectively. A dose of 

19 5,000 mg/kg also increased the incidence of micronuclei by approximately fourfold at 48 hours. 

20 This compares with the negative results for BALB/c male mice tested in the same study at a dose 

21 of 5,000 mg/kg and sampling time of 24 hours. Tinwell and Ashby (1994) could not explain the 

22 difference in response in the mouse bone marrow micronucleus assay with C57BL6 mice 

23 obtained in their laboratory (i.e., non-significant 1.6-fold increase over control) with the dose24 related positive findings reported by Mirkova (Mirkova, 1994) using the same mouse strain, 

25 1,4-dioxane dose (3,600 mg/kg) and sampling time (24 hours). Morita and Hayashi (1998)

26 demonstrated an increase in micronucleus formation in hepatocytes following 1,4-dioxane 

27 dosing and partial hepatectomy to induce cellular mitosis. DNA single-strand breaks were 

28 demonstrated in hepatocytes following gavage exposure to female rats (Kitchin & Brown, 1990).

29 Roy et al. (2005) examined micronucleus formation in male CD1 mice exposed to 

30 1,4-dioxane to confirm the mixed findings from earlier mouse micronucleus studies and to 

31 identify the origin of the induced micronuclei. Mice were administered 1,4-dioxane by gavage at 

32 doses of 0, 1,500, 2,500, and 3,500 mg/kg-day for 5 days. The mice were also implanted with 

33 5-bromo-2-deoxyuridine (BrdU)-releasing osmotic pumps to measure cell proliferation in the 

34 liver and to increase the sensitivity of the hepatocyte assay. The frequency of micronuclei in the 

35 bone marrow erythrocytes and in the proliferating BrdU-labeled hepatocytes was determined 

36 24 hours after the final dose. Significant dose-related increases in micronuclei were seen in the 

37 bone-marrow at all the tested doses (≥ 1,500 mg/kg-day). In the high-dose (3,500-mg/kg) mice, 
73

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 the frequency of bone marrow erythrocyte micronuclei was about 10-fold greater than the control 

2 frequency. Significant dose-related increases in micronuclei were also observed at the two 

3 highest doses (≥ 2,500 mg/kg-day) in the liver. Antikinetochore (CREST) staining or 

4 pancentromeric fluorescence in situ hybridization (FISH) was used to determine the origin of the 

5 induced micronuclei. The investigators determined that 80–90% of the micronuclei in both 

6 tissues originated from chromosomal breakage; small increase in micronuclei originating from 

7 chromosome loss was seen in hepatocytes. Dose-related statistically significant decreases in the 

8 ratio of bone marrow polychromatic erythrocytes (PCE):normochromatic erythrocytes (NCE), an 

9 indirect measure of bone marrow toxicity, were observed. Decreases in hepatocyte proliferation 

10 were also observed. Based on these results, the authors concluded that at high doses 1,4-dioxane 

11 exerts genotoxic effects in both the mouse bone marrow and liver; the induced micronuclei are 

12 formed primarily from chromosomal breakage; and 1,4-dioxane can interfere with cell 

13 proliferation in both the liver and bone marrow. The authors noted that reasons for the 

14 discrepant micronucleus assay results among various investigators was unclear, but could be 

15 related to the inherent variability present when detecting moderate to weak responses using small 

16 numbers of animals, as well as differences in strain, dosing regimen, or scoring criteria.

17 1,4-Dioxane did not affect in vitro or in vivo DNA repair in hepatocytes or in vivo DNA 

18 repair in the nasal cavity (Goldsworthy, et al., 1991; Stott, et al., 1981), but increased hepatocyte 

19 DNA synthesis indicative of cell proliferation in several in vivo studies (Goldsworthy, et al., 

20 1991; Miyagawa, Shirotori, Tsuchitani, & Yoshikawa, 1999; Stott, et al., 1981; Uno et al., 1994). 

21 1,4-Dioxane caused a transient inhibition of RNA polymerase A and B in the rat liver (Kurl, 

22 Poellinger, Lund, & Gustafsson, 1981), indicating a negative impact on the synthesis of 

23 ribosomal and messenger RNA (DNA transcription). Intravenous administration of 1,4-dioxane 

24 at doses of 10 or 100 mg/rat produced inhibition of both polymerase enzymes, with a quicker and 

25 more complete recovery of activity for RNA polymerase A, the polymerase for ribosomal RNA 

26 synthesis.

27 1,4-Dioxane did not covalently bind to DNA under in vitro study conditions (Woo, 

28 Argus, et al., 1977b). DNA alkylation was also not detected in the liver 4 hours following a 

29 single gavage exposure (1,000 mg/kg) in male Sprague Dawley rats (Stott, et al., 1981).

30 Rosenkranz and Klopman (1992) analyzed 1,4-dioxane using the computer automated 

31 structure evaluator (CASE) structure activity method to predict its potential genotoxicity and 

32 carcinogenicity. The CASE analysis is based on information contained in the structures of 

33 approximately 3,000 chemicals tested for endpoints related to mutagenic/genotoxic and 

34 carcinogenic potential. CASE selects descriptors (activating [biophore] or inactivating 

35 [biophobe] structural fragments) from a learning set of active and inactive molecules. Using the 

36 CASE methodology, Rosenkranz and Klopman (1992) predicted that 1,4-dioxane would be 

37 inactive for mutagenicity in several in vitro systems, including Salmonella, induction of 
74

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 chromosomal aberrations in CHO cells, and unscheduled DNA synthesis in rat hepatocytes. 

2 1,4-Dioxane was predicted to induce SCE in cultured CHO cells, micronuclei formation in rat 

3 bone marrow, and carcinogenicity in rodents.

4 Gene expression profiling in cultured human hepatoma HepG2 cells was performed using 

5 DNA microarrays to discriminate between genotoxic and other carcinogens (van Delft et al., 

6 2004). Van Delft et al. (2004) examined this method using a training set of 16 treatments (nine 

7 genotoxins and seven nongenotoxins) and a validation set (three and three), with discrimination 

8 models based on Pearson correlation analyses for the 20 most discriminating genes. As reported 

9 by the authors (van Delft, et al., 2004), the gene expression profile for 1,4-dioxane indicated a 

10 classification of this chemical as a ―nongenotoxic‖ carcinogen, and thus, 1,4-dioxane was 

11 included in the training set as a ―nongenotoxic‖ carcinogen. The accuracy for carcinogen 

12 classification using this method ranged from 33 to 100%, depending on which chemical data sets 

13 and gene expression signals were included in the analysis.

Table 4-19. Genotoxicity studies of 1,4-dioxane; in vitro

Test system Endpoint Test conditions

Resultsa

DosebSource

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. typhimurium 

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

Resultsa

DosebSource

Without 

activation

With 

activation

Nonmammalian eukaryotic organisms in vitro 

S. cerevisiae D61.M Aneuploidy Standard 16-hour 

incubation or coldinterruption 

regimen

–T ND 4.75% Zimmerman 

et al. (1985)

D. melanogaster Meiotic 

nondisjunction

Oocytes were 

obtained for 

evaluation 24 and 

48 hours after 

mating

+Tc NDd2% in sucrose 

media

Munoz and 

Barnett

(2002)

D. melanogaster Sex-linked 

recessive lethal 

test

Exposure by 

feeding and 

injection

– NDd

35,000 ppm in 

feed, 7 days or

50,000 ppm

(5% in water) 

by injection

Yoon et al.

(1985)

Mammalian cells in vitro

Rat hepatocytes DNA damage; 

single-strand 

breaks measured 

by alkaline 

elution

3-Hour exposure 

to isolated primary 

hepatocytes

+Te NDd0.3 mM Sina et al.

(1983)

Primary hepatocyte 

culture from male 

F344 rats

DNA repair Autoradiography – NDd1 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

+Tf NDd0.5 mg/mL Sheu et al.

(1988)
76

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Test system Endpoint Test conditions

Resultsa

DosebSource

Without 

activation

With 

activation

CHO cells SCE BrdU was added 

2 hours after 

1,4-dioxane

addition; chemical 

treatment was 

2 hours with S9 

and 25 hours 

without S9

±

g

– 10,520 μg/mL Galloway et 

al. (1987)

CHO cells Chromosomal 

aberration

Cells were 

harvested 8–

12 hours or 18–

26 hours after 

treatment (time of 

first mitosis)

– – 10,520 μg/mL Galloway et 

al. (1987)

CHO cells SCE 3 hour pulse 

treatment; 

followed by 

continuous 

treatment of BrdU 

for 23 or 26 hours

– – 5,000 μg/mL Morita and 

Hayashi

(1998)

CHO cells Chromosomal 

aberration

5 hour pulse 

treatment, 20 hour

pulse and 

continuous 

treatments, or 

44 hour

continuous 

treatment; cells 

were harvested 20 

or 44 hours 

following 

exposure

– – 5,000 μg/mL Morita and 

Hayashi

(1998)

CHO cells Micronucleus 

formation

5 hour pulse 

treatment or 

44 hour

continuous 

treatment; cells 

were harvested 

42 hours following 

exposure

– – 5,000 μg/mL Morita and 

Hayashi

(1998)

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

Resultsa

DosebSource

Without 

activation

With 

activation

a

+ = positive, ± = equivocal or weak positive, – = negative, T = toxicity. Endogenous metabolic 

activation is not applicable for in vivo studies.

bLowest effective dose for positive results/highest dose tested for negative results; ND = no data.

cRats were given doses of 0, 168, 840, 2,550, or 4,200 mg/kg at 4 and 21 hours prior to sacrifice. A 43 and 

50% increase in the fraction of DNA eluted was observed for doses of 2,550 and 4,200 mg/kg, 

respectively. Alkaline elution of DNA was not significantly different from control in the two lowest dose 

groups (168 and 840 mg/kg).

dA dose-related increase in the incidence of bone marrow micronuclei was observed in male and female 

C57BL6 mice 24 or 48 hours after administration of 1,4-dioxane. A dose of 450 mg/kg produced no 

change relative to control, while doses of 900, 1,800, 3,600, and 5,000 mg/kg increased the incidence of 

bone marrow micronuclei by approximately two-,three-, four- and fourfold, respectively.

eA dose-related increase in the incidence of hepatocyte micronuclei was observed in partially 

hepatectomized mice 6 days after administration of 1,4-dioxane. A dose of 1,000 mg/kg produced no 

change relative to control, while doses of 2,000 and 3,000 mg/kg increased the incidence of hepatocyte 

micronuclei by 2.4- and 3.4-fold, respectively.

f Significant increases in the frequency of micronucleated erythrocytes were observed at each test dose of 

1,4-dioxane (1,500, 2,500 and 3,500 mg/kg-day, 5 days/week).

gA dose-related increase in the frequency of micronuclei was observed in proliferating cells with micronuclei at 

2,500 and 3,500 mg/kg-day, 5 days/week. No increase in the frequency of micronuclei was seen in the nonproliferating cells.

hNo increase in the hepatocyte labeling index was observed 24 or 48 hours following a single gavage 

exposure of 1,000 mg/kg. Continuous administration of 1% 1,4-dioxane in the drinking water for up to 

2 weeks produced a twofold increase in the hepatocyte labeling index.

iA similar pattern of RNA polymerase inhibition was observed at doses of 10 and 100 mg/rat. Inhibition 

was more pronounced at the higher dose.

jHepatocyte viability was 86, 89, 87, 88, 78, and 86% 24 hours following exposure to 0, 1,000, 1,500, 

2,000, or 4,000 mg/kg. The incidence (%) of replicative DNA synthesis was increased by 2.5-fold 

(1,000 mg/kg) or 4.5-fold (1,500 and 2,000 mg/kg). No increase in replicative DNA synthesis was 

observed at the highest dose (4,000 mg/kg).

kReplicative DNA synthesis was measured 24, 39, and 48 hours following a single dose of 0, 1,000, or 

2,000 mg/kg. Hepatocyte viability ranged from 71 to 82%. The only increase in replicative DNA 

synthesis was observed 24 hours after administration of 2,000 mg/kg (threefold increase). Cell viability 

for this group was 79%.

lReplicative 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 Resultsa DosebSource

Female 

Sprague Dawley 

Rat

DNA damage; 

single-strand breaks 

measured by alkaline 

elution

Two gavage doses given 21 

and 4 hours prior to 

sacrifice

+

c

2,550 mg/kg Kitchin and 

Brown

(1990)

Male 

Sprague Dawley 

Rat

DNA alkylation in 

hepatocytes

Gavage; DNA isolation and 

HPLC analysis 4 hours after 

dosing

– 1,000 mg/kg Stott et al.

(1981)

Male 

B6C3F1

Mouse

Micronucleus 

formation in bone 

marrow

i.p. injection; analysis of 

polychromatic erythrocytes 

24 or 48 hours after dosing

– Single dose of 

4,000 mg/kg;

3 daily doses of 

2,000

McFee et al.

(1994)

Male and female 

C57BL6 

Mouse; 

male BALB/c 

Mouse

Micronucleus 

formation in bone 

marrow

Gavage; analysis of 

polychromatic erythrocytes 

24 or 48 hours after dosing

+ 

(C57BL6)d

– (BALB/c)

900 mg/kg 

(C57BL6);

5,000 mg/kg 

(BALB/c)

Mirkova

(1994)

Male 

CD1 

Mouse

Micronucleus 

formation in 

peripheral blood

Two i.p. injections (1/day); 

micronucleated 

reticulocytes measured 24, 

48, and 72 hours after the 

2nd dose

– 3,200 mg/kg Morita

(1994)

Male 

CD1 

Mouse

Micronucleus 

formation in 

hepatocytes

Gavage, partial 

hepatectomy 24 hours after 

dosing, hepatocytes 

analyzed 5 days after 

hepatectomy 

+

e

2,000 mg/kg Morita and 

Hayashi

(1998)

Male 

CD1 

Mouse

Micronucleus 

formation in 

peripheral blood

Gavage, partial 

hepatectomy 24 hours after 

dosing, peripheral blood 

obtained from tail vein 

24 hours after hepatectomy

– 3,000 mg/kg Morita and 

Hayashi

(1998)

Male 

CBA and 

C57BL6 Mouse

Micronucleus 

formation in bone 

marrow

Gavage; analysis of 

polychromatic erythrocytes 

from specimens prepared 

24 hours after dosing

– 3,600 mg/kg Tinwell and 

Ashby (1994)

Male 

CD1 

Mouse

Micronuclei 

formation in bone 

marrow

Gavage; analysis for 

micronucleated erythrocytes 

24 hours after dosing

+

f

1,500 mg/kg-day 

for 5 days

Roy et al.

(2005)

Male 

CD1 

Mouse

Micronuclei 

formation in 

hepatocytes

Gavage; analysis for 

micronuclei 24 hours after 

dosing

+

g

2,500 mg/kg-day 

for 5 days

Roy et 

al.(2005)

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 Resultsa DosebSource

Male 

F344

Rat

DNA repair in 

hepatocytes 

(autoradiography)

Gavage and drinking water 

exposure; thymidine 

incorporation

– 1,000 mg/kg for 

2 or 12 hours; 

1,500 mg/kg-day 

for 2 weeks or 

3,000 mg/kg-day 

for 1 week

Goldsworthy 

et al. (1991)

Male 

F344

Rat

DNA repair in nasal 

epithelial cells from 

the nasoturbinate or 

maxilloturbinate

Gavage and drinking water 

exposure; thymidine 

incorporation

– 1,500 mg/kg-day 

for 8 days + 

1,000 mg/kg 

gavage dose 

12 hours prior to 

sacrifice

Goldsworthy 

et al. (1991)

Male 

F344 

Rat

Replicative DNA 

synthesis (i.e., cell 

proliferation) in 

hepatocytes

Gavage and drinking water 

exposure; thymidine 

incorporation

+

h

(1–2-week 

exposure)

1,000 mg/kg for 

24 or 48 hours; 

1,500 mg/kg-day 

for 1 or 2 weeks

Goldsworthy 

et al. (1991)

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.

bLowest effective dose for positive results/highest dose tested for negative results; ND = no data.

cRats were given doses of 0, 168, 840, 2,550, or 4,200 mg/kg at 4 and 21 hours prior to sacrifice. A 43 and 

50% increase in the fraction of DNA eluted was observed for doses of 2,550 and 4,200 mg/kg, 

respectively. Alkaline elution of DNA was not significantly different from control in the two lowest dose 

groups (168 and 840 mg/kg).

dA dose-related increase in the incidence of bone marrow micronuclei was observed in male and female 

C57BL6 mice 24 or 48 hours after administration of 1,4-dioxane. A dose of 450 mg/kg produced no 

change relative to control, while doses of 900, 1,800, 3,600, and 5,000 mg/kg increased the incidence of 

bone marrow micronuclei by approximately two-,three-, four- and fourfold, respectively.

eA dose-related increase in the incidence of hepatocyte micronuclei was observed in partially 

hepatectomized mice 6 days after administration of 1,4-dioxane. A dose of 1,000 mg/kg produced no 

change relative to control, while doses of 2,000 and 3,000 mg/kg increased the incidence of hepatocyte 

micronuclei by 2.4- and 3.4-fold, respectively.

f

Significant increases in the frequency of micronucleated erythrocytes were observed at each test dose of 

1,4-dioxane (1,500, 2,500 and 3,500 mg/kg-day, 5 days/week).

gA dose-related increase in the frequency of micronuclei was observed in proliferating cells with micronuclei at 

2,500 and 3,500 mg/kg-day, 5 days/week. No increase in the frequency of micronuclei was seen in the nonproliferating cells.
80

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

hNo increase in the hepatocyte labeling index was observed 24 or 48 hours following a single gavage 

exposure of 1,000 mg/kg. Continuous administration of 1% 1,4-dioxane in the drinking water for up to 

2 weeks produced a twofold increase in the hepatocyte labeling index.

iA similar pattern of RNA polymerase inhibition was observed at doses of 10 and 100 mg/rat. Inhibition 

was more pronounced at the higher dose.

jHepatocyte viability was 86, 89, 87, 88, 78, and 86% 24 hours following exposure to 0, 1,000, 1,500, 

2,000, or 4,000 mg/kg. The incidence (%) of replicative DNA synthesis was increased by 2.5-fold 

(1,000 mg/kg) or 4.5-fold (1,500 and 2,000 mg/kg). No increase in replicative DNA synthesis was 

observed at the highest dose (4,000 mg/kg).

kReplicative DNA synthesis was measured 24, 39, and 48 hours following a single dose of 0, 1,000, or 

2,000 mg/kg. Hepatocyte viability ranged from 71 to 82%. The only increase in replicative DNA 

synthesis was observed 24 hours after administration of 2,000 mg/kg (threefold increase). Cell viability 

for this group was 79%.

lReplicative 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

1 Burmistrov et al. (2001) investigated the effect of 1,4-dioxane inhalation on free radical 

2 processes in the rat ovary and brain. Female rats (6–9/group, unspecified strain) were exposed to 

0, 10, or 100 mg/m33 of 1,4-dioxane vapor for 4 hours/day, 5 days/week, for 1 month. Rats were 

4 sacrificed during the morning or evening following exposure and the ovaries and brain cortex 

5 were removed and frozen. Tissue preparations were analyzed for catalase activity, glutathione 

peroxidase activity, and protein peroxidation. Inhalation of 100 mg/m36 of 1,4-dioxane resulted in 

7 a significant increase (p < 0.05) in glutathione peroxidase activity, and activation of free radical 

8 processes were apparent in both the rat ovary and brain cortex. No change in catalase activity or 

9 protein peroxidation was observed at either concentration. A circadian rhythm for glutathione 

10 peroxidase activity was absent in control rats, but occurred in rat brain and ovary following 

11 1,4-dioxane exposure.

4.5.2.2. Induction of Metabolism

12 The metabolism of 1,4-dioxane is discussed in detail in Section 3.3. 1,4-Dioxane has 

13 been shown to induce its own metabolism (Young, et al., 1978a; Young, et al., 1978b). Nannelli 

14 et al. (2005) (study details provided in Section 3.3) characterized the CYP450 isozymes that 

15 were induced by 1,4-dioxane in the liver, kidney, and nasal mucosa of the rat. In the liver, the 

16 activities of several CYP450 isozymes were increased (i.e., CYP2B1/2, CYP2E1, CYPC11); 

17 however, only CYP2E1 was inducible in the kidney and nasal mucosa. CYP2E1 mRNA was 

18 increased approximately two- to threefold in the kidney and nasal mucosa, but mRNA levels 

19 were not increased in the liver, suggesting that regulation of CYP2E1 is organ-specific. 

20 Induction of hepatic CYPB1/2 and CYP2E1 levels by phenobarbital or fasting did not increase 

21 the liver toxicity of 1,4-dioxane, as measured by hepatic glutathione content or serum ALT 

22 activity. This result suggested that highly reactive and toxic intermediates did not play a large 
81

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 role in the liver toxicity of 1,4-dioxane, even under conditions where metabolism was enhanced. 

2 This finding is similar to an earlier conclusion by Kociba et al. (1975) who evaluated toxicity 

3 from a chronic drinking water study alongside data providing a pharmacokinetic profile for 

4 1,4-dioxane. Kociba et al. (1975) concluded that liver toxicity and eventual tumor formation 

5 occurred only at doses where clearance pathways were saturated and elimination of 1,4-dioxane 

6 from the blood was reduced. Nannelli et al. (2005) further suggested that a sustained induction 

7 of CYP2E1 may lead to generation of reactive oxygen species contributing to target organ 

8 toxicity and regenerative cell proliferation; however, no data were provided to support this 

9 hypothesis. 

4.5.2.3. Mechanisms of Tumor Induction

10 Several studies have been performed to evaluate potential mechanisms for the 

11 carcinogenicity of 1,4-dioxane (Goldsworthy, et al., 1991; Kitchin & Brown, 1990; Stott, et al., 

12 1981). Stott et al. (1981) evaluated 1,4-dioxane in several test systems, including salmonella 

13 mutagenicity in vitro, rat hepatocyte DNA repair activity in vitro, DNA synthesis determination 

14 in male Sprague Dawley rats following acute gavage dosing or an 11-week drinking water 

15 exposure (described in Section 4.2.1), and hepatocyte DNA alkylation and DNA repair following 

16 a single gavage dose. This study used doses of 0, 10, 100, or 1,000 mg/kg-day, with the highest 

17 dose considered to be a tumorigenic dose level. Liver histopathology and liver to BW ratios 

18 were also evaluated in rats from acute gavage or repeated dose drinking water experiments.

19 The histopathology evaluation indicated that liver cytotoxicity (i.e., centrilobular 

20 hepatocyte swelling) was present in rats from the 1,000 mg/kg-day dose group that received 

21 1,4-dioxane in the drinking water for 11 weeks (Stott, et al., 1981). An increase in the liver to 

22 BW ratio accompanied by an increase in hepatic DNA synthesis was also seen in this group of 

23 animals. No effect on histopathology, liver weight, or DNA synthesis was observed in acutely 

24 exposed rats or rats that were exposed to a lower dose of 10 mg/kg-day for 11 weeks. 

25 1,4-Dioxane produced negative findings in the remaining genotoxicity assays conducted as part 

26 of this study (i.e., Salmonella mutagenicity, in vitro and in vivo rat hepatocyte DNA repair, and 

27 DNA alkylation in rat liver). The study authors suggested that the observed lack of genotoxicity 

28 at tumorigenic and cytotoxic dose levels indicates an epigenetic mechanism for 1,4-dioxane 

29 hepatocellular carcinoma in rats.

30 Goldsworthy et al. (1991) evaluated potential mechanisms for the nasal and liver 

31 carcinogenicity of 1,4-dioxane in the rat. DNA repair activity was evaluated as a measure of 

32 DNA reactivity and DNA synthesis was measured as an indicator of cell proliferation or 

33 promotional activity. In vitro DNA repair was evaluated in primary hepatocyte cultures from 

34 control and 1,4-dioxane-treated rats (1 or 2% in the drinking water for 1 week). DNA repair and 

35 DNA synthesis were also measured in vivo following a single gavage dose of 1,000 mg/kg, a 

36 drinking water exposure of 1% (1,500 mg/kg-day) for 1 week, or a drinking water exposure of 
82

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 2% (3,000 mg/kg-day) for 2 weeks. Liver to BW ratios and palmitoyl CoA oxidase activity were 

2 measured in the rat liver to determine whether peroxisome proliferation played a role in the liver 

3 carcinogenesis of 1,4-dioxane. In vivo DNA repair was evaluated in rat nasal epithelial cells 

4 derived from either the nasoturbinate or the maxilloturbinate of 1,4-dioxane-treated rats. These 

5 rats received 1% 1,4-dioxane (1,500 mg/kg-day) in the drinking water for 8 days, followed by a 

6 single gavage dose of 10, 100, or 1,000 mg/kg 12 hours prior to sacrifice. Archived tissues from 

7 the NCI (1978) bioassay were reexamined to determine the primary sites for tumor formation in 

8 the nasal cavity following chronic exposure in rats. Histopathology and cell proliferation were 

9 determined for specific sites in the nasal cavity that were related to tumor formation. This 

10 evaluation was performed in rats that were exposed to drinking water containing 1% 1,4-dioxane 

11 (1,500 mg/kg-day) for 2 weeks.

12 1,4-Dioxane and its metabolite 1,4-dioxane-2-one did not affect in vitro DNA repair in 

13 primary hepatocyte cultures (Goldsworthy, et al., 1991). In vivo DNA repair was also unaffected 

14 by acute gavage exposure or ingestion of 1,4-dioxane in the drinking water for a 1- or 2-week 

15 period. Hepatocyte cell proliferation was not affected by acute gavage exposure, but was 

16 increased approximately twofold following a 1–2-week drinking water exposure. A 5-day 

17 drinking water exposure to 1% 1,4-dioxane (1,500 mg/kg-day) did not increase the activity of 

18 palmitoyl coenzyme A or the liver to BW ratio, suggesting that peroxisome proliferation did not 

19 play a role in the hepatocarcinogenesis of 1,4-dioxane. Nannelli et al. (2005) also reported a lack 

20 of hepatic palmitoyl CoA induction following 10 days of exposure to 1.5% 1,4-dioxane in the 

21 drinking water (2,100 mg/kg-day). 

22 Treatment of rats with 1% (1,500 mg/kg-day) 1,4-dioxane for 8 days did not alter DNA 

23 repair in nasal epithelial cells (Goldsworthy, et al., 1991). The addition of a single gavage dose 

24 of up to 1,000 mg/kg 12 hours prior to sacrifice also did not induce DNA repair. Reexamination 

25 of tissue sections from the NCI (1978) bioassay suggested that the majority of nasal tumors were 

26 located in the dorsal nasal septum or the nasoturbinate of the anterior portion of the dorsal 

27 meatus (Goldsworthy, et al., 1991). No histopathological lesions were observed in nasal section 

28 of rats exposed to drinking water containing 1% 1,4-dioxane (1,500 mg/kg-day) for 2 weeks and 

29 no increase was observed in cell proliferation at the sites of highest tumor formation in the nasal 

30 cavity.

31 Female Sprague Dawley rats (three to nine per group) were given 0, 168, 840, 2,550, or 

32 4,200 mg/kg 1,4-dioxane (99% purity) by corn oil gavage in two doses at 21 and 4 hours prior to 

33 sacrifice (Kitchin & Brown, 1990). DNA damage (single-strand breaks measured by alkaline 

34 elution), ODC activity, reduced glutathione content, and CYP450 content were measured in the 

35 liver. Serum ALT activity and liver histopathology were also evaluated. No changes were 

36 observed in hepatic reduced glutathione content or ALT activity. Light microscopy revealed 

37 minimal to mild vacuolar degeneration in the cytoplasm of hepatocytes from three of five rats 
83

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 from the 2,550 mg/kg dose group. No histopathological lesions were seen in any other dose 

2 group, including rats given a higher dose of 4,200 mg/kg. 1,4-Dioxane caused 43 and 50% 

3 increases in DNA single-strand breaks at dose levels of 2,550 and 4,200 mg/kg, respectively. 

4 CYP450 content was also increased at the two highest dose levels (25 and 66% respectively). 

5 ODC activity was increased approximately two-, five-, and eightfold above control values at 

6 doses of 840, 2,550, and 4,200 mg/kg, respectively. The results of this study demonstrated that 

7 hepatic DNA damage can occur in the absence of significant cytotoxicity. Parameters associated 

8 with tumor promotion (i.e., ODC activity, CYP450 content) were also elevated, suggesting that 

9 promotion may play a role in the carcinogenesis of 1,4-dioxane.

4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS

10 Liver and kidney toxicity were the primary noncancer health effects associated with 

11 exposure to 1,4-dioxane in humans and laboratory animals. Several fatal cases of hemorrhagic 

12 nephritis and centrilobular necrosis of the liver were related to occupational exposure (i.e., 

13 inhalation and dermal contact) to 1,4-dioxane (Barber, 1934; Johnstone, 1959). Neurological 

14 changes were also reported in one case; including, headache, elevation in blood pressure, 

15 agitation and restlessness, and coma (Johnstone, 1959). Perivascular widening was observed in 

16 the brain of this worker, with small foci of demyelination in several regions (e.g., cortex, basal 

17 nuclei). Liver and kidney degeneration and necrosis were observed in acute oral and inhalation 

18 studies (David, 1964; de Navasquez, 1935; Drew, et al., 1978; Fairley, et al., 1934; JBRC, 1998; 

19 Kesten, et al., 1939; Laug, et al., 1939; Schrenk & Yant, 1936). The results of subchronic and 

20 chronic studies are discussed below.

4.6.1. Oral

21 Table 4-21 presents a summary of the noncancer results for the subchronic and chronic 

22 oral studies of 1,4-dioxane toxicity in experimental animals. Liver and kidney toxicity were the 

23 primary noncancer health effects of oral exposure to 1,4-dioxane in animals. Kidney damage at 

24 high doses was characterized by degeneration of the cortical tubule cells, necrosis with 

25 hemorrhage, and glomerulonephritis (Argus, et al., 1965; Fairley, et al., 1934; Kociba, et al., 

26 1974; NCI, 1978). Renal cell degeneration generally began with cloudy swelling of cells in the 

27 cortex (Fairley, et al., 1934). Nuclear enlargement of proximal tubule cells was observed at 

28 doses below those producing renal necrosis (JBRC, 1998; Kano, et al., 2008), but is of uncertain 

29 toxicological significance. The lowest dose reported to produce kidney damage was 94 mg/kg30 day, which produced renal degeneration and necrosis of tubule epithelial cells in male rats in the 

31 Kociba et al. (1974) study. Cortical tubule degeneration was seen at higher doses in the NCI 

32 (1978) bioassay (240 mg/kg-day, male rats), and glomerulonephritis was reported for rats given 

33 doses of ≥ 430 mg/kg-day (Argus, et al., 1965; 1973).
84

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table 4-21. Oral toxicity studies (noncancer effects) for 1,4-dioxane 

Species Dose/duration

NOAEL

(mg/kg-day)

LOAEL

(mg/kg-day) Effect Reference

Subchronic studies

Rat and mouse 

(6/species); 

unknown strain

Rats 0 or 1,900 mg/kgday; mice 0 or 

3,300 mg/kg-day for 

67 days

NA 1,900 rats

3,300 mice

Renal cortical degeneration 

and necrosis, hemorrhage; 

hepatocellular degeneration

Fairley et al.

(1934)

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/kgday 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 months

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)

B6C3F1 mouse 

(50/sex/dose 

level)

Males 0, 720, or 

830 mg/kg-day; females 

0, 380, or 860 mg/kg-day 

for 90 weeks

NA 380 Pneumonia and rhinitis NCI (1978)

F344/DuCrj rat 

(50/sex/dose 

level)

Males 0, 11, 55, or 

274 mg/kg-day; females 

0, 18, 83, or 429 mg/kgday for 2 years

55 274 Atrophy of nasal olfactory 

epithelium; nasal adhesion 

and inflammation

JBRC (1998); 

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/kgday for 2 years

11 55 Liver hyperplasia JBRC (1998); 

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/kgday 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/kgday 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/kgday 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 days 6–15

500 1,000 Delayed ossification of the 

sternebrae and reduced fetal 

BWs

Giavani et al.

(1985)

 

1 Liver effects included degeneration and necrosis, hepatocyte swelling, cells with 

2 hyperchromic nuclei, spongiosis hepatis, hyperplasia, and clear and mixed cell foci of the liver 

3 (Argus, et al., 1965; Argus, et al., 1973; Fairley, et al., 1934; Kano, et al., 2008; Kociba, et al., 

4 1974; NCI, 1978). Hepatocellular degeneration and necrosis were seen at high doses in a 

5 subchronic study (1,900 mg/kg-day in rats) (Fairley, et al., 1934) and at lower doses in a chronic 

6 study (94 mg/kg-day, male rats) (Kociba, et al., 1974). Argus et al. (1973) described a 

7 progression of preneoplastic effects in the liver of rats exposed to a dose of 575 mg/kg-day. 

8 Early changes (8 months exposure) were described as an increased nuclear size of hepatocytes, 

9 disorganization of the rough endoplasmic reticulum, an increase in smooth endoplasmic 

10 reticulum, a decrease in glycogen, an increase in lipid droplets in hepatocytes, and formation of 

11 liver nodules. Spongiosis hepatis, hyperplasia, and clear and mixed-cell foci were also observed 

12 in the liver of rats (doses >55 mg/kg-day in male rats) (JBRC, 1998; Kano, et al., 2009). Clear 

13 and mixed-cell foci are commonly considered preneoplastic changes and would not be 

14 considered evidence of noncancer toxicity when observed in conjunction with tumor formation. 

15 If exposure to 1,4-dioxane had not resulted in tumor formation, these lesions could represent 

16 potential noncancer toxicity. The nature of spongiosis hepatis as a preneoplastic change is less 

17 well understood (Bannasch, 2003; Karbe & Kerlin, 2002; Stroebel, et al., 1995). Spongiosis 

18 hepatis is a cyst-like lesion that arises from the perisinusoidal Ito cells of the liver. This change 

19 is sometimes associated with hepatocellular hypertrophy and liver toxicity (Karbe & Kerlin, 

20 2002), but may also occur in combination with preneoplastic foci, or hepatocellular adenoma or 

21 carcinoma (Bannasch, 2003; Stroebel, et al., 1995). In the case of the JBRC (1998) study, 

22 spongiosis hepatis was associated with other preneoplastic changes in the liver (hyperplasia, 

23 clear and mixed-cell foci). No other lesions indicative of liver toxicity were seen in this study; 

24 therefore, spongiosis hepatis was not considered indicative of noncancer effects. The activity of 
86

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 serum enzymes (i.e., AST, ALT, LDH, and ALP) was increased in rats and mice exposed to 

2 1,4-dioxane, although only in groups with high incidence of liver tumors. Blood samples were 

3 collected only at the end of the 2-year study, so altered serum chemistry may be associated with 

4 the tumorigenic changes in the liver. 

5 Hematological changes were reported in the JBRC (1998) study only. Mean doses are 

6 reported based on information provided in Kano et al. (2009). Observed increases in RBCs, 

7 hematocrit, hemoglobin in high-dose male mice (677 mg/kg-day) may be related to lower 

8 drinking water consumption (74% of control drinking water intake). Hematological effects 

9 noted in male rats given 55 mg/kg-day (decreased RBCs, hemoglobin, hematocrit, increased 

10 platelets) were within 20% of control values. A reference range database for hematological 

11 effects in laboratory animals (Wolford, et al., 1986) indicates that a 20% change in these 

12 parameters may fall within a normal range (10th–90th percentile values) and may not represent a 

13 treatment-related effect of concern.

14 Rhinitis and inflammation of the nasal cavity were reported in both the NCI (1978) (mice 

15 only, dose ≥ 380 mg/kg-day) and JBRC (1998) studies (≥ 274 mg/kg-day in rats, >278 mg/kg16 day in mice). The JBRC (1998) study also demonstrates atrophy of the nasal epithelium and 

17 adhesion in rats and mice. Nasal inflammation may be a response to direct contact of the nasal 

18 mucosa with drinking water containing 1,4-dioxane (Goldsworthy, et al., 1991; Sweeney, et al., 

19 2008) or could result from systemic exposure. Regardless, inflammation may indicate toxicity 

20 due to 1,4-dioxane exposure. A significant increase in the incidence of pneumonia was reported 

21 in mice from the NCI (1978) study. The significance of this effect is unclear, as it was not 

22 observed in other studies that evaluated lung histopathology (JBRC, 1998; Kano, et al., 2008; 

23 Kociba, et al., 1974). No studies were available regarding the potential for 1,4-dioxane to cause 

24 immunological effects. Metaplasia and hyperplasia of the nasal epithelium were also observed in 

25 high-dose male and female rats (JBRC, 1998); however, these effects are likely to be associated 

26 with the formation of nasal cavity tumors in these dose groups. Nuclear enlargement of the nasal 

27 olfactory epithelium was observed at a dose of 83 mg/kg-day in female rats (Kano, et al., 2009); 

28 however, it is unclear whether this alteration represents an adverse toxicological effect. Nuclear 

29 enlargement of the tracheal and bronchial epithelium and an accumulation of foamy cells in the 

30 lung were also seen in male and female mice give 1,4-dioxane at doses of ≥ 278 mg/kg for 

31 2 years (JBRC, 1998).

4.6.2. Inhalation

32 Two subchronic (Fairley, et al., 1934; Kasai, et al., 2008) and two chronic inhalation 

33 studies (Kasai, et al., 2009; Torkelson, et al., 1974) were identified. Nasal, liver, and kidney

34 toxicity were the primary noncancer health effects of inhalation exposure to 1,4-dioxane in 
87

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 animals. Table 4-22 presents a summary of the noncancer results for the subchronic and chronic 

2 inhalation studies of 1,4-dioxane toxicity in laboratory animals.

3 Of the inhalation studies, nasal tissue was only collected in rat studies conducted by 

4 Kasai et al. (2009; 2008). Damage to nasal tissue was reported frequently in these studies and 

5 statistically significant observations were noted as low as 50 ppm. Nasal effects included 

6 deformity of the nose and histopathological lesions characterized by enlarged epithelial nuclei 

7 (respiratory epithelium, olfactory epithelium, trachea, and bronchus), atrophy (olfactory 

8 epithelium), vacuolic change (olfactory epithelium and bronchial epithelium), squamous cell 

9 metaplasia and hyperplasia (respiratory epithelium), respiratory metaplasia (olfactory 

10 epithelium), inflammation (respiratory and olfactory epithelium), hydropic change (lamina 

11 propria), and sclerosis (lamina propria). In both studies, a concentration-dependent, statistically 

12 significant change in enlarged nuclei of the respiratory epithelium was considered the most 

13 severe nasal effect by the study authors; however, the toxicological significance of nuclear 

14 enlargement is uncertain. 

15 At high doses, liver damage was characterized by cell degeneration which varied from 

16 swelling (Fairley, et al., 1934; Kasai, et al., 2008) to necrosis (Fairley, et al., 1934; Kasai, et al., 

17 2009; Kasai, et al., 2008), spongiosis hepatis (Kasai, et al., 2009), nuclear enlargement of 

18 centrilobular cells (Kasai, et al., 2009) and basophilic and acidophilic cell foci (Kasai, et al., 

19 2009). Altered cell foci are commonly considered preneoplastic changes and would not be 

20 considered evidence of noncancer toxicity when observed in conjunction with tumor formation

21 (Bannasch, Moore, Klimek, & Zerban, 1982). Since exposure to 1,4-dioxane resulted in tumor 

22 formation, these lesions are not considered potential noncancer toxicity. 

23 At concentrations ranging from 200 ppm to 3,200 ppm, altered liver enzymes (i.e., AST, 

24 ALT, ALP, and γ-GTP), increased liver weights, and induction of GST-P was also observed

25 (Kasai, et al., 2009; Kasai, et al., 2008). Changes in the activity of serum enzymes were mostly

26 observed in exposed rat groups of high 1,4-dioxane concentrations (Kasai, et al., 2009; Kasai, et 

27 al., 2008). Induction of GST-P positive hepatocytes were observed in female rats at 1,600 ppm 

28 and male and female rats at 3,200 ppm following 13 weeks of exposure to 1,4-dioxane. GST-P 

29 is considered a good enzymatic marker for early detection of chemical hepatocarcinogenesis 

30 (Sato, 1989). Although, GST-P positive liver foci were not observed in the 2 year bioassay, the 

31 focally and proliferating GST-P positive hepatocytes noted in the 13 week study suggests 

32 eventual progression to hepatocellular tumors after 2 years of exposure and therefore would not 

33 be a potential noncancer effect.

34 The lowest concentration reported to produce liver lesions was 1,250 ppm, characterized 

35 by necrosis of centrilobular cells, spongiosis hepatis, and nuclear enlargement in the Kasai et al. 

36 (2009) study. However, as previously stated, the toxicological significance of nuclear 
88

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 enlargement lesions is uncertain; and altered cell foci may not be a potential noncancer effect 

2 given its observation in conjunction with tumor formation. 

3 Kidney effects were reported less frequently in these inhalation studies and were 

4 generally observed at higher exposure concentrations than nasal and liver effects. Kidney 

5 damage was described as patchy degeneration of cortical tubules with vascular congestion and 

6 hemorrhage (Fairley, et al., 1934), hydropic change of proximal tubules (Kasai, et al., 2009; 

7 Kasai, et al., 2008), and as nuclear enlargement of proximal tubules cells (Kasai, et al., 2009). 

8 Changes in serum chemistry and urinalysis variables were also noted as evidence of renal 

9 damage. In a 13 week inhalation study of male and female rats (Kasai, et al., 2008) kidney 

10 toxicity was only observed in female rats exposed to 3,200 ppm of 1,4-dioxane (i.e. hydropic 

11 change in the renal proximal tubules), which suggests a possible increased susceptibility of 

12 female rats to renal damage following inhalation exposure to 1,4-dioxane.

13 Other noted noncancer effects in laboratory animals included acute vascular congestion 

14 of the lungs (Fairley, et al., 1934); changes in relative lung weights (Kasai, et al., 2008); and 

15 decrease in body weight gain (Kasai, et al., 2009; Kasai, et al., 2008). Following a 13-week 

16 exposure, higher 1,4-dioxane plasma levels were found in female rats as compared to male rats

17 (Kasai, et al., 2008). 1,4-Dioxane was observed in plasma along with systemic effects following 

18 subchronic inhalation exposure to 1,4-dioxane in rats. 

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:

nuclear 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)

19 
89

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.6.3. Mode of Action Information 

1 The metabolism of 1,4-dioxane in humans was extensive at low doses (<50 ppm). The 

2 linear elimination of 1,4-dioxane in both plasma and urine indicated that 1,4-dioxane metabolism 

3 was a nonsaturated, first-order process at this exposure level (1976; Young, et al., 1977). Like 

4 humans, rats extensively metabolized inhaled 1,4-dioxane; however, plasma data from rats given 

single i.v. doses of 3, 10, 30, 100, or 1,000 mg [

14 5 C]-1,4-dioxane/kg demonstrated a dose-related 

6 shift from linear, first-order to nonlinear, saturable metabolism of 1,4-dioxane (Young, et al., 

7 1978a; Young, et al., 1978b). Conversely, using the Young et al. (1978a; 1978b) rat model, the 

8 metabolism of 1,4-dioxane in rats that were exposed to 400, 800, 1,600, and 3,200 ppm via 

9 inhalation for 13 weeks could not be accurately depicted due to a lack of knowledge on needed 

10 model parameters and biological processes (See Section 3.5.3 and Appendix B). Metabolism 

11 may be induced following prolonged inhalation exposure to 1,4-dioxane at concentrations up to 

12 3,200 ppm (Appendix B). 

13 1,4-Dioxane oxidation appeared to be CYP450-mediated, as CYP450 induction with 

14 phenobarbital or Aroclor 1254 and suppression with 2,4-dichloro-6-phenylphenoxy ethylamine 

15 or cobaltous chloride was effective in significantly increasing and decreasing, respectively, the 

16 appearance of HEAA in the urine of rats (Woo, Argus, et al., 1977a; Woo, et al., 1978). 

17 1,4-Dioxane itself induced CYP450-mediated metabolism of several barbiturates in Hindustan 

18 mice given i.p. injections of 25 and 50 mg/kg of 1,4-dioxane (Mungikar & Pawar, 1978). The 

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

20 notion that 1,4-dioxane may induce its own metabolism. 1,4-Dioxane has been shown to induce 

21 several isoforms of CYP450 in various tissues following acute oral administration by gavage or 

22 drinking water (Nannelli, et al., 2005). In the liver, the activity of several CYP450 isozymes was 

23 increased (i.e., CYP2B1/2, CYP2E1, CYPC11); however, only CYP2E1 was inducible in the 

24 kidney and nasal mucosa. CYP2E1 mRNA was increased approximately two- to threefold in the 

25 kidney and nasal mucosa, but mRNA levels were not increased in the liver, suggesting that 

26 regulation of CYP2E1 was organ-specific. 

27 Nannelli et al. (2005) investigated the role of CYP450 isozymes in the liver toxicity of 

28 1,4-dioxane. Hepatic CYPB1/2 and CYP2E1 levels were induced by phenobarbital or fasting 

29 and liver toxicity was measured as hepatic glutathione content or serum ALT activity. No 

30 increase in glutathione content or ALT activity was observed, suggesting that highly reactive and 

31 toxic intermediates did not play a large role in the liver toxicity of 1,4-dioxane, even under 

32 conditions where metabolism was enhanced. Pretreatment with inducers of mixed-function 

33 oxidases also did not significantly change the extent of covalent binding in subcellular fractions 

34 (Woo, Argus, et al., 1977b). Covalent binding was measured in liver, kidney, spleen, lung, 

35 colon, and skeletal muscle 1–12 hours after i.p. dosing with 1,4-dioxane. Covalent binding was 
90

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 highest in liver, spleen, and colon. Within hepatocytes, 1,4-dioxane distribution was greatest in 

2 the cytosolic fraction, followed by the microsomal, mitochondrial, and nuclear fractions. 

3 The absence of an increase in toxicity following an increase in metabolism suggests that 

4 accumulation of the parent compound may be related to 1,4-dioxane toxicity. This hypothesis is 

5 supported by a comparison of the pharmacokinetic profile of 1,4-dioxane with the toxicology 

6 data from a chronic drinking water study (Kociba, et al., 1975). This analysis indicated that liver 

7 toxicity did not occur unless clearance pathways were saturated and elimination of 1,4-dioxane 

8 from the blood was reduced. A dose-dependent increase of 1,4-dioxane accumulation in the 

9 blood was seen, which correlated to the observed dose-dependent increase in incidences of nasal, 

10 liver, and kidney toxicities (Kasai, et al., 2008). Alternative metabolic pathways (i.e., not 

11 CYP450 mediated) may be present at high doses of 1,4-dioxane; however, the available studies 

12 have not characterized these pathways or identified any possible reactive intermediates. Thus, 

13 the mechanism by which 1,4-dioxane induces tissue damage is not known, nor is it known 

14 whether the toxic moiety is 1,4-dioxane or a transient or terminal metabolite.

4.7. EVALUATION OF CARCINOGENICITY

4.7.1. Summary of Overall Weight of Evidence

15 Under the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), 1,4-dioxane is 

16 ―likely to be carcinogenic to humans‖ based on evidence of carcinogenicity in several 2-year 

17 bioassays conducted in four strains of rats, two strains of mice, and in guinea pigs (Argus, et al., 

18 1965; Argus, et al., 1973; Hoch-Ligeti & Argus, 1970; Hoch-Ligeti, et al., 1970; JBRC, 1998; 

19 Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978; Yamazaki, et al., 1994). 

20 Tissue sites where tumors have been observed in these laboratory animals due to exposure to 

21 1,4-dioxane include, peritoneal (JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Yamazaki, 

22 et al., 1994), mammary gland (JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Yamazaki, et 

23 al., 1994), liver (Kano, et al., 2009; Kasai, et al., 2009), kidney (Kasai, et al., 2009), Zymbal

24 gland (Kasai, et al., 2009), subcutaneous (Kasai, et al., 2009), nasal tissue (Argus, et al., 1973; 

25 Hoch-Ligeti, et al., 1970; JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 

26 1974; NCI, 1978; Yamazaki, et al., 1994), and lung (Hoch-Ligeti & Argus, 1970). Studies in 

27 humans are inconclusive regarding evidence for a causal link between occupational exposure to 

28 1,4-dioxane and increased risk for cancer; however, only two studies were available and these 

29 were limited by small cohort size and a small number of reported cancer cases (Buffler, et al., 

30 1978; Thiess, et al., 1976).

31 The available evidence is inadequate to establish a mode of action (MOA) by which 

32 1,4-dioxane induces liver tumors in rats and mice. A MOA hypothesis involving sustained 

33 proliferation of spontaneously transformed liver cells has some support from data indicating that 

34 1,4-dioxane acts as a tumor promoter in mouse skin and rat liver bioassays (King, et al., 1973; 
91

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Lundberg, et al., 1987). Dose-response and temporal data support the occurrence of cell 

2 proliferation and hyperplasia prior to the development of liver tumors (JBRC, 1998; Kociba, et 

3 al., 1974) in the rat model. However, the dose-response relationship for induction of hepatic cell 

4 proliferation has not been characterized, and it is unknown if it would reflect the dose-response 

5 relationship for liver tumors in the 2-year rat and mouse studies. Conflicting data from rat and 

6 mouse bioassays (JBRC, 1998; Kociba, et al., 1974) suggest that cytotoxicity may not be a 

7 required precursor event for 1,4-dioxane-induced cell proliferation. Data regarding a plausible 

8 dose response and temporal progression (see Table 4-21) from cytotoxicity and cell proliferation 

9 to eventual liver tumor formation are not available.

10 For nasal tumors, a hypothesized MOA includes metabolic induction, cytotoxicity, and 

11 regenerative cell proliferation. The induction of CYP450 has some support from data illustrating 

12 that following acute oral administration of 1,4-dioxane by gavage or drinking water, CYP2E1 

13 was inducible in nasal mucosa (Nannelli, et al., 2005). CYP2E1 mRNA was increased 

14 approximately two- to threefold in nasal mucosa (and in the kidney, see section 3.3) in the 

15 Nannelli et al. (2005) study. The possibility of the parent compound as a factor in the 

16 development of nasal tumors also has some support. Following a 13-week inhalation study in 

17 rats, a concentration-dependent accumulation of 1,4-dioxane in the blood was observed (Kasai, 

18 et al., 2008). Studies have shown that water-soluble, gaseous irritants cause nasal injuries such 

19 as squamous cell carcinomas (Morgan, Patterson, & Gross, 1986). Similarly, 1,4-dioxane, which 

20 has been reported as a miscible compound (Hawley & Lewis Rj Sr, 2001), also caused nasal 

21 injuries that were concentration-dependent, including nasal tumors (Kasai, et al., 2009). While 

22 cell proliferation was observed following 1,4-dioxane exposure in both a 2-year inhalation study 

23 in male rats (1,250 ppm) (Kasai, et al., 2009) and a 2-year drinking water study in male (274 

24 mg/kg-day) and female rats (429 mg/kg-day), no evidence of cytotoxicity in the nasal cavity was 

25 observed (Kasai, et al., 2009); therefore, cytotoxicity, as a key event, is not supported. 

26 The MOA by which 1,4-dioxane produces liver, nasal, lung, peritoneal (mesotheliomas), 

27 mammary gland, Zymbal gland, and subcutis tumors is unknown, and the available data do not 

28 support any hypothesized carcinogenic MOA for 1,4-dioxane.

29 U.S. EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a) indicate that 

30 for tumors occurring at a site other than the initial point of contact, the weight of evidence for 

31 carcinogenic potential may apply to all routes of exposure that have not been adequately tested at 

32 sufficient doses. An exception occurs when there is convincing information (e.g., toxicokinetic 

33 data) that absorption does not occur by other routes. Information available on the carcinogenic 

34 effects of 1,4-dioxane via the oral route demonstrates that tumors occur in tissues remote from 

35 the site of absorption. In addition, information on the carcinogenic effects of 1,4-dioxane via the 

36 inhalation route in animals also demonstrates that tumors occur at tissue sites distant from the 

37 portal of entry. Information on the carcinogenic effects of 1,4-dioxane via the inhalation and 
92

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 dermal routes in humans and via the dermal route in animals is absent. Based on the observance 

2 of systemic tumors following oral and inhalation exposure, it is assumed that an internal dose 

3 will be achieved regardless of the route of exposure. Therefore, 1,4-dioxane is ―likely to be 

4 carcinogenic to humans‖ by all routes of exposure.

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

5 Human studies of occupational exposure to 1,4-dioxane were inconclusive; in each case, 

6 the cohort size was limited and number of reported cases were of limited size was small (Buffler, 

7 et al., 1978; Thiess, et al., 1976).

8 Several carcinogenicity bioassays have been conducted for 1,4-dioxane in mice, rats, and 

9 guinea pigs (Argus, et al., 1965; Argus, et al., 1973; Hoch-Ligeti & Argus, 1970; Hoch-Ligeti, et 

10 al., 1970; JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978; 

11 Torkelson, et al., 1974; Yamazaki, et al., 1994). Liver tumors have been observed following 

12 drinking water exposure in male Wistar rats (Argus, et al., 1965), male guinea pigs (Hoch-Ligeti 

13 & Argus, 1970), male Sprague Dawley rats (Argus, et al., 1973; Hoch-Ligeti, et al., 1970), male 

14 and female Sherman rats (Kociba, et al., 1974), female Osborne-Mendel rats (NCI, 1978), male 

15 and female F344/DuCrj rats (JBRC, 1998; Kano, et al., 2009; Yamazaki, et al., 1994), male and 

16 female B6C3F1 mice (NCI, 1978), and male and female Crj:BDF1 mice (JBRC, 1998; Kano, et 

17 al., 2009; Yamazaki, et al., 1994); and following inhalation exposure in male F344 rats (Kasai, et 

18 al., 2009). In the earliest cancer bioassays, the liver tumors were described as hepatomas (Argus, 

19 et al., 1965; Argus, et al., 1973; Hoch-Ligeti & Argus, 1970; Hoch-Ligeti, et al., 1970); however, 

20 later studies made a distinction between hepatocellular carcinoma and hepatocellular adenoma 

21 (JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978; Yamazaki, 

22 et al., 1994). Both tumor types have been seen in rats and mice exposed to 1,4-dioxane via 

23 drinking water and inhalation. Kociba et al. (1974) noted evidence of liver toxicity at or below 

24 the dose levels that produced liver tumors but did not report incidence data for these effects. 

25 Hepatocellular degeneration and necrosis were observed in the mid- and high-dose groups of 

26 male and female Sherman rats exposed to 1,4-dioxane, while tumors were only observed at the 

27 highest dose. Hepatic regeneration was indicated in the mid- and high-dose groups by the 

28 formation of hepatocellular hyperplastic nodules. Kano et al., (2009) also provided evidence of 

29 liver hyperplasia in male F344/DuCrj rats at a dose level below the dose that induced a 

30 statistically significant increase in tumor formation. Kasai et al. (2009) noted evidence of liver 

31 toxicity and tumor incidences (i.e. hepatocellular adenoma) in male F344/DuCrj rats following 

32 inhalation exposures to 1,250 ppm. Increased liver toxicities included hepatocellular necrosis, 

33 spongiosis hepatis, and acidophilic and basophilic cell foci.

34 Nasal cavity tumors were also observed in Sprague Dawley rats (Argus, et al., 1973; 

35 Hoch-Ligeti, et al., 1970), Osborne-Mendel rats (NCI, 1978), Sherman rats (Kociba, et al., 
93

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 1974), and F344/DuCrj rats (JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Yamazaki, et 

2 al., 1994). Most tumors were characterized as squamous cell carcinomas. Nasal tumors were 

3 not elevated in B6C3F1 or Crj:BDF1 mice. Kano et al. (2009) and Kasai et al. (2009) were the 

4 only studies that evaluated nonneoplastic changes in nasal cavity tissue following prolonged 

5 exposure to 1,4-dioxane via oral and inhalation routes, respectively. Histopathological lesions in 

6 female F344/DuCrj rats were suggestive of toxicity and regeneration in this tissue (i.e., atrophy, 

7 adhesion, inflammation, nuclear enlargement, and hyperplasia and metaplasia of respiratory and 

8 olfactory epithelium). Some of these effects occurred at a lower dose (83 mg/kg-day) than that 

9 shown to produce nasal cavity tumors (429 mg/kg-day) in female rats. Re-examination of tissue 

10 sections from the NCI (1978) bioassay suggested that the majority of nasal tumors were located 

11 in the dorsal nasal septum or the nasoturbinate of the anterior portion of the dorsal meatus. 

12 Histopathological lesions in male F344/DuCrj rats following exposure to 1,4-dioxane via 

13 inhalation were also suggestive of toxicity and regeneration in the nasal cavity (i.e. atrophy, 

14 inflammation, nuclear enlargement, hyperplasia and metaplasia of the respiratory and olfactory 

15 epithelium, and inflammation). Some of these effects occurred at lower concentrations (50 ppm 

16 and 250 ppm) than those shown to produce nasal cavity tumors (1,250 ppm) in male rats. Nasal 

17 squamous cell carcinomas were observed in the dorsal area of levels 1-3 of the nasal cavity and 

18 were characterized as well-differentiated and keratinized. In two cases, invasive growth into 

19 adjacent tissue was noted, marked by carcinoma growth out of the nose and through a destroyed 

20 nasal bone.

21 Tumor initiation and promotion studies in mouse skin and rat liver suggested that 

22 1,4-dioxane does not initiate the carcinogenic process, but instead acts as a tumor promoter 

23 (Bull, et al., 1986; King, et al., 1973; Lundberg, et al., 1987) (see Section 4.2.3).

24 In addition to the liver and nasal tumors observed in several studies, a statistically 

25 significant increase in mesotheliomas of the peritoneum was seen in male rats from the Kano et 

26 al. (2009) study (JBRC, 1998; Yamazaki, et al., 1994) and the Kasai et al. (2009) study. Female 

27 rats dosed with 429 mg/kg-day in drinking water for 2 years also showed a statistically 

28 significant increase in mammary gland adenomas (JBRC, 1998; Kano, et al., 2009; Yamazaki, et 

29 al., 1994). In male rats, exposed via inhalation, a statistically significant positive trend of 

30 mammary gland adenomas was observed by Kasai et al. (2009). A statistically significant 

31 increase and/or trend of subcutis fibroma, Zymbal gland adenoma, and renal cell carcinoma 

32 incidences was also observed in male rats exposed for 2 years via inhalation (Kasai, et al., 2009).

33 A significant increase in the incidence of these tumors was not observed in other chronic oral or 

34 inhalation bioassays of 1,4-dioxane (Kociba, et al., 1974; NCI, 1978; Torkelson, et al., 1974). 
94

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.7.3. Mode of Action Information

1 The MOA by which 1,4-dioxane produces liver, nasal, peritoneal (mesotheliomas), 

2 mammary gland, Zymbal gland, and subcutis tumors is unknown, and the available data do not 

3 support any hypothesized mode of carcinogenic action for 1,4-dioxane. Available data also do 

4 not clearly identify whether 1,4-dioxane or one of its metabolites is responsible for the observed 

5 effects. The hypothesized MOAs for 1,4-dioxane carcinogenicity are discussed below within the 

6 context of the modified Hill criteria of causality as recommended in the most recent Agency 

7 guidelines (U.S. EPA, 2005a). MOA analyses were not conducted for peritoneal, mammary 

8 gland, Zymbal gland, or subcutis tumors due to the absence of any chemical specific information 

9 for these tumor types.

4.7.3.1. Identification of Key Events for Carcinogenicity

10 4.7.3.1.1. Liver. A key event in this MOA hypothesis is sustained proliferation of 

11 spontaneously transformed liver cells, resulting in the eventual formation of liver tumors. 

12 Precursor events in which 1,4-dioxane may promote proliferation of transformed liver cells are 

13 uncertain. One study suggests that induced liver cytotoxicity may be a key precursor event to 

14 cell proliferation leading to the formation of liver tumors (Kociba, et al., 1974), however, this 

15 study did not report incidence data for these effects. Other studies suggest that cell proliferation 

16 can occur in the absence of liver cytotoxicity. Liver tumors were observed in female rats and 

17 female mice in the absence of lesions indicative of cytotoxicity (JBRC, 1998; Kano, et al., 2008; 

18 NCI, 1978). Figure 4-1 presents a schematic representation of possible key events in the MOA 

19 for 1,4-dioxane liver carcinogenicity. These include: (1) oxidation by CYP2E1 and CYP2B1/2 

20 (i.e., detoxification pathway for 1,4-dioxane), (2) saturation of metabolism/clearance leading to 

21 accumulation of the parent 1,4-dioxane, (3) liver damage followed by regenerative cell 

22 proliferation, or (4) cell proliferation in the absence of cytotoxicity (i.e., mitogenesis), 

23 (5) hyperplasia, and (6) tumor formation. It is suggested that liver toxicity is related to the 

24 accumulation of the parent compound following metabolic saturation at high doses (Kociba, et 

25 al., 1975); however, no in vivo or in vitro assays have examined the toxicity of metabolites 

26 resulting from 1,4-dioxane to support this hypothesis. Nannelli et al. (2005) demonstrated that 

27 an increase in the oxidative metabolism of 1,4-dioxane via CYP450 induction using 

28 phenobarbital or fasting does not result in an increase in liver toxicity. This result suggested that 

29 highly reactive and toxic intermediates did not play a large role in the liver toxicity of 

30 1,4-dioxane, even under conditions where metabolism was enhanced. Alternative metabolic 

31 pathways (e.g., not CYP450 mediated) may be present at high doses of 1,4-dioxane; although the 

32 available studies have not characterized these pathways nor identified any possible reactive 

33 intermediates. Tumor promotion studies in mouse skin and rat liver suggest that 1,4-dioxane 

34 may enhance the growth of previously initiated cells (King, et al., 1973; Lundberg, et al., 1987). 
95

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 This is consistent with the increase in hepatocyte cell proliferation observed in several studies 

2 (Goldsworthy, et al., 1991; Miyagawa, et al., 1999; Stott, et al., 1981; Uno, et al., 1994). These 

3 mechanistic studies provide evidence of cell proliferation, but do not indicate whether 

4 mitogenesis or cytotoxicity is responsible for increased cell turnover.

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.

5 4.7.3.1.2. Nasal cavity. A possible key event in the MOA hypothesis for nasal tumors is 

6 sustained proliferation of spontaneously transformed nasal epithelial cells, resulting in the 

7 eventual formation of nasal cavity tumors. Cell proliferation was observed following 

8 1,4-dioxane exposure in both a 2-year inhalation study in male rats (1,250 ppm) (Kasai, et al., 

9 2009) and a 2-year drinking water study in male (274 mg/kg-day) and female rats (429 mg/kg10 day); however, no evidence of cytotoxicity in the nasal cavity was observed (Kasai, et al., 2009); 

11 therefore, cytotoxicity as a key event is not supported. The Kasai et al. (2009; 2008) studies 

12 suggest that nasal toxicity is related to the accumulation of the parent compound following 

13 metabolic saturation at high doses; however no in vivo or in vitro assays have examined the 

14 toxicity of metabolites resulting from 1,4-dioxane to support this hypothesis. Nannelli et al. 

15 (2005) demonstrated that CYP2E1 was inducible in nasal mucosa following acute oral 

16 administration of 1,4-dioxane by gavage or drinking water, which could potentially lead to an 

17 increase in the oxidative metabolism of 1,4-dioxane and nasal toxicity. However, Nannelli et al. 

18 (2005) did not characterize this pathway nor identify any possible reactive intermediates or nasal 

19 toxicities.

20

Toxicokinetics

Oral absorption of 

1,4-dioxane

Metabolism by 

CYP2E1 and 

CYP2B1/2

HEAA elimination 

in the urine

Metabolic 

saturation and 

accumulation of 

1,4-dioxane in the 

blood

MOA for Liver Tumors

Hepatocellular 

cytotoxicity

Cell proliferation in 

absence of 

cytotoxicity

Regenerative cell 

proliferation Hyperplasia

Hyperplasia

Tumor formation

Tumor promotion
96

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.7.3.2. Strength, Consistency, Specificity of Association

1 4.7.3.2.1. Liver. The plausibility of a MOA that would include liver cytotoxicity, with 

2 subsequent reparative cell proliferation, as precursor events to liver tumor formation is 

3 minimally supported by findings that nonneoplastic liver lesions occurred at exposure levels 

4 lower than those resulting in significantly increased incidences of hepatocellular tumors (Kociba, 

5 et al., 1974) and the demonstration of nonneoplastic liver lesions in subchronic (Kano, et al., 

6 2008) and acute and short-term oral studies (see Table 4-18). Because the incidence of 

7 nonneoplastic lesions was not reported by Kociba et al. (1974), it is difficult to know whether the 

8 incidence of liver lesions increased with increasing 1,4-dioxane concentration. Contradicting the 

9 observations by Kociba et al. (1974), liver tumors were observed in female rats and female mice 

10 in the absence of lesions indicative of cytotoxicity (JBRC, 1998; Kano, et al., 2008; NCI, 1978). 

11 This suggests that cytotoxicity may not be a requisite step in the MOA for liver cancer. 

12 Mechanistic and tumor promotion studies suggest that enhanced cell proliferation without 

13 cytotoxicity may be a key event; however, data showing a plausible dose response and temporal 

14 progression from cell proliferation to eventual liver tumor formation are not available (see 

15 Sections 4.7.3.3 and 4.7.3.4). Mechanistic studies that demonstrated cell proliferation after 

16 short-term exposure did not evaluate liver cytotoxicity (Goldsworthy, et al., 1991; Miyagawa, et 

17 al., 1999; Uno, et al., 1994). Studies have not investigated possible precursor events that may 

18 lead to cell proliferation in the absence of cytotoxicity (i.e., genetic regulation of mitogenesis).

19 4.7.3.2.2. Nasal cavity. Nasal cavity tumors have been demonstrated in several rat strains 

20 (JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978; Yamazaki, 

21 et al., 1994), but were not elevated in two strains of mice (JBRC, 1998; Kano, et al., 2009; NCI, 

22 1978; Yamazaki, et al., 1994). Chronic irritation was indicated by the observation of rhinitis 

23 and/or inflammation of the nasal cavity in rats from the JBRC (1998) and Kasai et al. (2009; 

24 2008) studies. The Kasai et al. (2009; 2008) studies also showed atrophy of the nasal epithelium 

25 in rats, and the JRBC (1998) study also observed atrophy of the nasal epithelium as well as

26 adhesion in rats. Regeneration of the nasal epithelium is demonstrated by metaplasia and 

27 hyperplasia observed in rats exposed to 1,4-dioxane (JBRC, 1998; Kano, et al., 2009; Kasai, et 

28 al., 2009; Yamazaki, et al., 1994). Oxidation of 1,4-dioxane metabolism by CYP450 is not 

29 supported as a key event in the MOA of nasal tumors. Nannelli et al. (2005) lacked details of 

30 possible reactive intermediates and resulting nasal toxicity. Accumulation of 1,4-dioxane in 

31 blood as a precursor event of nasal tumor formation is also not supported because the parent 

32 compound 1,4-dioxane was only measured in one subchronic study (Kasai, et al., 2008) and in 

33 this subchronic study no evidence of nasal cytotoxicity, cell proliferation, or incidence of nasal 

34 tumors were reported. 

35
97

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.7.3.3. Dose-Response Relationship

1 4.7.3.3.1. Liver. Table 4-23 presents the temporal sequence and dose-response relationship for 

2 possible key events in the liver carcinogenesis of 1,4-dioxane. Dose-response information 

3 provides some support for enhanced cell proliferation as a key event in the liver tumorigenesis of 

4 1,4-dioxane; however, the role of cytotoxicity as a required precursor event is not supported by 

5 data from more than one study. Kociba et al. (1974) demonstrated that liver toxicity and 

6 hepatocellular regeneration occurred at a lower dose level than tumor formation. Hepatocellular 

7 degeneration and necrosis were observed in the mid- and high-dose groups of Sherman rats 

8 exposed to 1,4-dioxane, although it is not possible to discern whether this effect was observed in 

9 both genders due to the lack of incidence data (Kociba, et al., 1974). Hepatic tumors were only 

10 observed at the highest dose (Kociba, et al., 1974). Hepatic regeneration was indicated in the 

11 mid- and high-dose group by the formation of hepatocellular hyperplastic nodules. Liver 

12 hyperplasia was also seen in rats from the JBRC (1998) study, at or below the dose level that 

13 resulted in tumor formation (Kano, et al., 2009); however, hepatocellular degeneration and 

14 necrosis were not observed. These results suggest that hepatic cell proliferation and hyperplasia 

15 may occur in the absence of significant cytotoxicity. Liver angiectasis (i.e., dilation of blood or 

16 lymphatic vessels) was observed in male mice at the same dose that produced liver tumors; 

17 however, the relationship between this vascular abnormality and tumor formation is unclear.

Table 4-23. 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 B6C3F1 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 B6C3F1 mice
98

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,g
99

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/kgday), 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.

gAll rats died during the first week of the 13-week bioassay (Kasai, et al., 2008).

hKasai et al. (2009) reported incidence rates for centrilobular necrosis and hepatocellular adenomas in male rats 

(1,250 ppm).

1 4.7.3.3.2. Nasal cavity. Table 4-24 presents the temporal sequence and dose-response 

2 relationship for possible key events in the nasal tissue carcinogenesis of 1,4-dioxane. Toxicity 

3 and regeneration in nasal epithelium (i.e., atrophy, adhesion, inflammation, and hyperplasia and 

4 metaplasia of respiratory and olfactory epithelium) was evident in one study at the same dose 

5 levels that produced nasal cavity tumors (JBRC, 1998; Kano, et al., 2009). In another study, 

6 dose-response information provided some support for nasal toxicity and regeneration in nasal 

7 epithelium occurring before tumor development (Kasai, et al., 2009). However, the role of 

8 cytotoxicity as a required precursor event is not supported by data from any of the reviewed 

9 studies. The accumulation of parent 1,4-dioxane as a key event has some support since

10 concentration-dependent increases were noted for both 1,4-dioxane in plasma and toxicities 

11 observed that are also other possible precursor events (i.e. regeneration in nasal 

12 epithelium)(Kasai, et al., 2008). In a subsequent study by Kasai et al. (2009) some of these same 

13 possible precursor events were observed at 50, 250, and 1,250 ppm with evidence of nasal 

14 tumors at the highest concentration (1,250 ppm). 
100

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 B6C3F1 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 B6C3F1 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 —a
101

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 these 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 hyperplasia 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

1 4.7.3.4.1. Liver. Available information regarding temporal relationships between the key event 

2 (sustained proliferation of spontaneously transformed liver cells) and the eventual formation of 

3 liver tumors is limited. A comparison of 13-week and 2-year studies conducted in F344/DuCrj 

4 rats and Crj:BDF1 mice at the same laboratory revealed that tumorigenic doses of 1,4-dioxane 

5 produced liver toxicity by 13 weeks of exposure (JBRC, 1998; Kano, et al., 2009; Kano, et al., 

6 2008). Hepatocyte swelling of the centrilobular area of the liver, vacuolar changes in the liver, 

7 granular changes in the liver, and single cell necrosis in the liver were observed in mice and rats 
102

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 given 1,4-dioxane in the drinking water for 13 weeks. Sustained liver damage may lead to 

2 regenerative cell proliferation and tumor formation following chronic exposure. As discussed 

3 above, histopathological evidence of regenerative cell proliferation has been seen following 

4 long-term exposure to 1,4-dioxane (JBRC, 1998; Kociba, et al., 1974). Tumors occurred earlier 

5 at high doses in both mice and rats from this study (Yamazaki, 2006); however, temporal 

6 information regarding hyperplasia or other possible key events was not available (i.e., interim 

7 blood samples not collected, interim sacrifices were not performed). Argus et al. (1973) studied 

8 the progression of tumorigenesis by electron microscopy of liver tissues obtained following 

9 interim sacrifices at 8 and 13 months of exposure (five rats/group, 574 mg/kg-day). The first 

10 change observed was an increase in the size of the nuclei of the hepatocytes, mostly in the 

11 periportal area. Precancerous changes were characterized by disorganization of the rough 

12 endoplasmic reticulum, increase in smooth endoplasmic reticulum, and decrease in glycogen and 

13 increase in lipid droplets in hepatocytes. These changes increased in severity in the 

14 hepatocellular carcinomas in rats exposed to 1,4-dioxane for 13 months.

15 Three types of liver nodules were observed in exposed rats at 13–16 months. The first 

16 consisted of groups of these cells with reduced cytoplasmic basophilia and a slightly nodular 

17 appearance as viewed by light microscopy. The second type of nodule was described consisting 

18 of large cells, apparently filled and distended with fat. The third type of nodule was described as 

19 finger-like strands, 2–3 cells thick, of smaller hepatocytes with large hyperchromic nuclei and 

20 dense cytoplasm. This third type of nodule was designated as an incipient hepatoma, since it 

21 showed all the histological characteristics of a fully developed hepatoma. All three types of 

22 nodules were generally present in the same liver.

23 4.7.3.4.2. Nasal cavity. No information was available regarding the temporal relationship 

24 between toxicity in the nasal epithelium and the formation of nasal cavity tumors. A comparison 

25 of 13-week and 2-year studies conducted in F344/DuCrj rats could not be conducted since the 

26 tumorigenic concentration of 1,4-dioxane was different from the concentration which produced 

27 nasal toxicities by 13 weeks of exposure (Kasai, et al., 2009; Kasai, et al., 2008). In addition, 

28 severity data were only provided in the shorter term study. Sustained nasal damage may lead to 

29 regenerative cell proliferation and tumor formation following chronic exposure. As discussed 

30 above (Section 4.2.2.2.1), histopathological evidence of regenerative cell proliferation has been 

31 seen following long-term exposure to 1,4-dioxane (Kasai, et al., 2009; Kasai, et al., 2008), and

32 observations of nasal tumors were also noted at the highest exposure concentration. Other 

33 incidences of nasal damage may have occurred before tumor formation; however, temporal 

34 information regarding these events was not available (i.e., interim blood samples not collected, 

35 interim sacrifices were not performed).
103

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.7.3.5. Biological Plausibility and Coherence

1 4.7.3.5.1. Liver. The hypothesis that sustained proliferation of spontaneously transformed liver 

2 cells is a key event within a MOA is possible based on supporting evidence indicating that 

3 1,4-dioxane is a tumor promoter of mouse skin and rat liver tumors (Bull, et al., 1986; King, et 

4 al., 1973; Lundberg, et al., 1987). Further support for this hypothesis is provided by studies 

5 demonstrating that 1,4-dioxane increased hepatocyte DNA synthesis, indicative of cell 

6 proliferation (Goldsworthy, et al., 1991; Miyagawa, et al., 1999; Stott, et al., 1981; Uno, et al., 

7 1994). In addition, the generally negative results for 1,4-dioxane in a number of genotoxicity 

8 assays indicates the carcinogenicity of 1,4-dioxane may not be mediated by a mutagenic MOA. 

9 The importance of cytotoxicity as a necessary precursor to sustained cell proliferation is 

10 biologically plausible, but is not supported by the dose-response in the majority of studies of 

11 1,4-dioxane carcinogenicity.

12 4.7.3.5.2. Nasal cavity. Sustained cell proliferation in response to cell death from toxicity may 

13 be related to the formation of nasal cavity tumors; however, this MOA is also not established . 

14 Nasal carcinogens are generally characterized as potent genotoxins (Ashby, 1994); however, 

15 other MOAs have been proposed for nasal carcinogens that induce effects through other 

16 mechanisms (Green et al., 2000; Kasper et al., 2007). 

17 The National Toxicological Program (NTP) database identified 12 chemicals from 

18 approximately 500 bioassays as nasal carcinogens and 1,4-dioxane was the only identified nasal 

19 carcinogen that showed little evidence of genotoxicity (Haseman & Hailey, 1997). Nasal tumors 

20 were not observed in an inhalation study in Wistar rats exposed to 111 ppm for 5 days/week for 

21 2 years (Torkelson, et al., 1974). 

4.7.3.6. Other Possible Modes of Action

22 An alternate MOA could be hypothesized that 1,4-dioxane alters DNA, either directly or 

23 indirectly, which causes mutations in critical genes for tumor initiation, such as oncogenes or 

24 tumor suppressor genes. Following these events, tumor growth may be promoted by a number of 

25 molecular processes leading to enhanced cell proliferation or inhibition of programmed cell 

26 death. The results from in vitro and in vivo assays do not provide overwhelming support for the 

27 hypothesis of a genotoxic MOA for 1,4-dioxane carcinogenicity. The genotoxicity data for 

28 1,4-dioxane were reviewed in Section 4.5.1 and were summarized in Table 4-19. Negative 

29 findings were reported for mutagenicity in Salmonella typhimurium, Escherichia coli, and 

30 Photobacterium phosphoreum (Mutatox assay) (Haworth, et al., 1983; Hellmér & Bolcsfoldi, 

31 1992; Khudoley, et al., 1987; Kwan, et al., 1990; Morita & Hayashi, 1998; Nestmann, et al., 

32 1984; Stott, et al., 1981). Negative results were also indicated for the induction of aneuploidy in 

33 yeast (Saccharomyces cerevisiae) and the sex-linked recessive lethal test in Drosophila 

34 melanogaster (Zimmermann, et al., 1985). In contrast, positive results were reported in assays 
104

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 for sister chromatid exchange (Galloway, et al., 1987), DNA damage (Kitchin & Brown, 1990), 

2 and in in vivo micronucleus formation in bone marrow (Mirkova, 1994; Roy, et al., 2005), and 

3 liver (Morita & Hayashi, 1998; Roy, et al., 2005). Lastly, in the presence of toxicity, positive 

4 results were reported for meiotic nondisjunction in drosophila (Munoz & Barnett, 2002), DNA 

5 damage (Sina, et al., 1983), and cell transformation (Sheu, et al., 1988). 

6 Additionally, 1,4-dioxane metabolism did not produce reactive intermediates that 

7 covalently bound to DNA (Stott, et al., 1981; Woo, Argus, et al., 1977b) and DNA repair assays 

8 were generally negative (Goldsworthy, et al., 1991; Stott, et al., 1981). No studies were 

9 available to assess the ability of 1,4-dioxane or its metabolites to induce oxidative damage to 

10 DNA.

4.7.3.7. Conclusions About the Hypothesized Mode of Action

11 4.7.3.7.1. Liver. The MOA by which 1,4-dioxane produces liver tumors is unknown, and 

12 available evidence in support of any hypothetical mode of carcinogenic action for 1,4-dioxane is 

13 inconclusive. A MOA hypothesis involving 1,4-dioxane induced cell proliferation is possible 

14 but data are not available to support this hypothesis. Pharmacokinetic data suggest that 

15 clearance pathways were saturable and target organ toxicity occurs after metabolic saturation. 

16 Liver toxicity preceded tumor formation in one study (Kociba, et al., 1974) and a regenerative 

17 response to tissue injury was demonstrated by histopathology. Liver hyperplasia and tumor 

18 formation have also been observed in the absence of cytotoxicity (JBRC, 1998; Kano, et al., 

19 2009). Cell proliferation and tumor promotion have been shown to occur after prolonged 

20 exposure to 1,4-dioxane (Bull, et al., 1986; Goldsworthy, et al., 1991; King, et al., 1973; 

21 Lundberg, et al., 1987; Miyagawa, et al., 1999; Stott, et al., 1981; Uno, et al., 1994).

22 4.7.3.7.2. Nasal cavity. The MOA for the formation of nasal cavity tumors is unknown, and 

23 evidence in support of any hypothetical mode of carcinogenic action for 1,4-dioxane is 

24 inconclusive. A MOA hypothesis involving nasal damage, cell proliferation, and hyperplasia is 

25 possible, but data are not available to support this hypothesis. One or more of these events is 

26 missing from the studies that examine nasal effects after exposure to 1,4-dioxane. Nasal cavity 

27 tumors have been reported in the absence of cell proliferation (Kasai, et al., 2009) and 

28 hyperplasia (JBRC, 1998; Kano, et al., 2009).

4.7.3.8. Relevance of the Mode of Action to Humans

29 Several hypothesized MOAs for 1,4-dioxane induced tumors in laboratory animals have 

30 been discussed along with the supporting evidence for each. As was stated, the MOA by which 

31 1,4-dioxane produces liver, nasal, peritoneal, and mammary gland tumors is unknown. Some 

32 mechanistic information is available to inform the MOA of the liver and nasal tumors but no 

33 information exists to inform the MOA of the observed peritoneal or mammary gland tumors 

34 (JBRC, 1998; Kano, et al., 2009; Yamazaki, et al., 1994). 
105

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES

1 There is no direct evidence to establish that certain populations and lifestages may be 

2 susceptible to 1,4-dioxane. Changes in susceptibility with lifestage as a function of the presence 

3 of microsomal enzymes that metabolize and detoxify this compound (i.e., CYP2E1 present in 

4 liver, kidney, and nasal mucosa can be hypothesized). Vieira et al. (1996) reported that large 

5 increases in hepatic CYP2E1 protein occur postnatally between 1 and 3 months in humans. 

6 Adult hepatic concentrations of CYP2E1 are achieved sometime between 1 and 10 years. To the 

7 extent that hepatic CYP2E1 levels are lower, children may be more susceptible to liver toxicity 

8 from 1,4-dioxane than adults. CYP2E1 has been shown to be inducible in the rat fetus. The 

9 level of CYP2E1 protein was increased by 1.4-fold in the maternal liver and 2.4-fold in the fetal 

10 liver following ethanol treatment, as compared to the untreated or pair-fed groups (Carpenter, 

11 Lasker, & Raucy, 1996). Pre- and postnatal induction of microsomal enzymes resulting from 

12 exposure to 1,4-dioxane or other drugs or chemicals may reduce overall toxicity following 

13 sustained exposure to 1,4-dioxane. 

14 Genetic polymorphisms have been identified for the human CYP2E1 gene (Hayashi, 

15 Watanabe, & Kawajiri, 1991; Watanabe, Hayashi, & Kawajiri, 1994) and were considered to be 

16 possible factors in the abnormal liver function seen in workers exposed to vinyl chloride (Huang, 

17 Huang, Cheng, Wang, & Hsieh, 1997). Individuals with a CYP2E1 genetic polymorphism 

18 resulting in increased expression of this enzyme may be less susceptible to toxicity following 

19 exposure to 1,4-dioxane.

20 Gender differences were noted in subchronic and chronic toxicity studies of 1,4-dioxane 

21 in mice and rats (see Sections 4.6 and 4.7). No consistent pattern of gender sensitivity was 

22 identified across studies. In a 13 week inhalation study of male and female rats (Kasai, et al., 

23 2008) kidney toxicity was observed in female rats exposed to 3,200 ppm of 1,4-dioxane (i.e. 

24 hydropic change in the renal proximal tubules), but not male rats, which suggests a possible 

25 increased susceptibility of female rats to renal damage following inhalation exposure to 

26 1,4-dioxane.
106

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

5. DOSE-RESPONSE ASSESSMENTS

5.1. ORAL REFERENCE DOSE (RfD)

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

1 Liver and kidney toxicity were the primary noncancer health effects associated with 

2 exposure to 1,4-dioxane in humans and laboratory animals. Occupational exposure to 

3 1,4-dioxane has resulted in hemorrhagic nephritis and centrilobular necrosis of the liver (Barber, 

4 1934; Johnstone, 1959). In animals, liver and kidney degeneration and necrosis were observed 

5 frequently in acute oral and inhalation studies (David, 1964; de Navasquez, 1935; Drew, et al., 

6 1978; Fairley, et al., 1934; JBRC, 1998; Kesten, et al., 1939; Laug, et al., 1939; Schrenk & Yant, 

7 1936). Liver and kidney effects were also observed following chronic oral exposure to 

8 1,4-dioxane in animals (Argus, et al., 1965; Argus, et al., 1973; JBRC, 1998; Kano, et al., 2009; 

9 Kociba, et al., 1974; NCI, 1978; Yamazaki, et al., 1994) (see Table 4-21).

10 Liver toxicity in the available chronic studies was characterized by necrosis, spongiosis 

11 hepatic, hyperplasia, cyst formation, clear foci, and mixed cell foci. Kociba et al. (1974)

12 demonstrated hepatocellular degeneration and necrosis at doses of 94 mg/kg-day (LOAEL in 

13 male rats) or greater. The NOAEL for liver toxicity was 9.6 mg/kg-day and 19 mg/kg-day in 

14 male and female rats, respectively. No quantitative incidence data were provided in this study. 

15 Argus et al. (1973) described early preneoplastic changes in the liver and JBRC (1998)

16 demonstrated liver lesions that are primarily associated with the carcinogenic process. Clear and 

17 mixed-cell foci in the liver are commonly considered preneoplastic changes and would not be 

18 considered evidence of noncancer toxicity. In the JBRC (1998) study, spongiosis hepatis was 

19 associated with other preneoplastic changes in the liver (clear and mixed-cell foci) and no other 

20 lesions indicative of liver toxicity were seen. Spongiosis hepatis was therefore not considered 

21 indicative of noncancer effects in this study. The activity of serum enzymes (i.e., AST, ALT, 

22 LDH, and ALP) was increased in mice and rats chronically exposed to 1,4-dioxane (JBRC, 

23 1998); however, these increases were seen only at tumorigenic dose levels. Blood samples were 

24 collected at study termination and elevated serum enzymes may reflect changes associated with 

25 tumor formation. Histopathological evidence of liver toxicity was not seen in rats from the 

26 JBRC (1998) study. The highest non-tumorigenic dose levels for this study approximated the 

27 LOAEL derived from the Kociba et al. (1974) study (94 and 148 mg/kg-day for male and female 

28 rats, respectively).

 

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

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

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

and the Integrated Risk Information System (IRIS).
107

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Kidney damage in chronic toxicity studies was characterized by degeneration of the 

2 cortical tubule cells, necrosis with hemorrhage, and glomerulonephritis (Argus, et al., 1965; 

3 Argus, et al., 1973; Fairley, et al., 1934; Kociba, et al., 1974; NCI, 1978). Kociba et al. (1974)

4 described renal tubule epithelial cell degeneration and necrosis at doses of 94 mg/kg-day 

5 (LOAEL in male rats) or greater, with a NOAEL of 9.6 mg/kg-day. No quantitative incidence 

6 data were provided in this study (Kociba, et al., 1974). Doses of ≥ 430 mg/kg-day 1,4-dioxane 

7 induced marked kidney alterations (Argus, et al., 1973). The observed changes included 

8 glomerulonephritis and pyelonephritis, with characteristic epithelial proliferation of Bowman‘s 

9 capsule, periglomerular fibrosis, and distension of tubules. Quantitative incidence data were not 

10 provided in this study. In the NCI (1978) study, kidney lesions in rats consisted of vacuolar 

11 degeneration and/or focal tubular epithelial regeneration in the proximal cortical tubules and 

12 occasional hyaline casts. Kidney toxicity was not seen in rats from the JBRC (1998) study at any 

13 dose level (highest dose was 274 mg/kg-day in male rats and 429 mg/kg-day in female rats). 

14 Kociba et al. (1974) was chosen as the principal study for derivation of the RfD because 

15 the liver and kidney effects in this study are considered adverse and represent the most sensitive 

16 effects identified in the database (NOAEL 9.6 mg/kg-day, LOAEL 94 mg/kg-day in male rats). 

17 Kociba et al. (1974) reported degenerative effects in the liver, while liver lesions reported in 

18 other studies (Argus, et al., 1973; JBRC, 1998) appeared to be related to the carcinogenic 

19 process. Kociba et al. (1974) also reported degenerative changes in the kidney. NCI (1978) and 

20 Argus et al. (1973) provided supporting data for this endpoint; however, kidney toxicity was 

21 observed in these studies at higher doses. JBRC (1998) reported nasal inflammation in rats 

22 (NOAEL 55 mg/kg-day, LOAEL 274 mg/kg-day) and mice (NOAEL 66 mg/kg-day, LOAEL 

23 278 mg/kg-day). 

24 Even though the study reported by Kociba et al. (1974) had one noteworthy weakness, it 

25 had several noted strengths, including: (1) two-year study duration; (2) use of both male and 

26 female rats and three dose levels, 10-fold apart, plus a control group; (3) a sufficient number of 

27 animals per dose group (60 animals/sex/dose group; and (4) the authors conducted a 

28 comprehensive evaluation of the animals including body weights and clinical observations, blood 

29 samples, organ weights of all the major tissues, and a complete histopathological examination of 

30 all rats. The authors did not report individual incidence data that would have allowed for a BMD 

31 analysis of this robust dataset. 

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

32 Several procedures were applied to the human PBPK model to determine if an adequate 

33 fit of the model to the empirical model output or experimental observations could be attained 

34 using biologically plausible values for the model parameters. The re-calibrated model 

35 predictions for blood 1,4-dioxane levels did not come within 10-fold of the experimental values 
108

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 using measured tissue:air partition coefficients of Leung and Paustenbach (1990) or Sweeney 

2 et al. (2008) (Figures B-8 and B-9). The utilization of a slowly perfused tissue:air partition 

3 coefficient 10-fold lower than measured values produces exposure-phase predictions that are 

4 much closer to observations, but does not replicate the elimination kinetics (Figure B-10). Re5 calibration of the model with upper bounds on the tissue:air partition coefficients results in 

6 predictions that are still six- to sevenfold lower than empirical model prediction or observations 

7 (Figures B-12 and B-13). Exploration of the model space using an assumption of zero-order 

8 metabolism (valid for the 50 ppm inhalation exposure) showed that an adequate fit to the 

9 exposure and elimination data can be achieved only when unrealistically low values are assumed 

10 for the slowly perfused tissue:air partition coefficient (Figure B-16). Artificially low values for 

11 the other tissue:air partition coefficients are not expected to improve the model fit, as these 

12 parameters are shown in the sensitivity analysis to exert less influence on blood 1,4-dioxane than 

13 VmaxC and Km. This suggests that the model structure is insufficient to capture the apparent 10-

14 fold species difference in the blood 1,4-dioxane between rats and humans. In the absence of 

15 actual measurements for the human slowly perfused tissue:air partition coefficient, high 

16 uncertainty exists for this model parameter value. Differences in the ability of rat and human 

17 blood to bind 1,4-dioxane may contribute to the difference in Vd. However, this is expected to 

18 be evident in very different values for rat and human blood:air partition coefficients, which is not 

19 the case (Table B-1). Therefore, some other, as yet unknown, modification to model structure 

20 may be necessary.

21 Kociba et al. (1974) did not provide quantitative incidence or severity data for liver and 

22 kidney degeneration and necrosis. Benchmark dose (BMD) modeling could not be performed 

23 for this study and the NOAEL for liver and kidney degeneration (9.6 mg/kg-day in male rats) 

24 was used as the point of departure (POD) in deriving the RfD for 1,4-dioxane. 

25 Alternative PODs were calculated using incidence data reported for cortical tubule 

26 degeneration in male and female rats (NCI, 1978) and liver hyperplasia (JBRC, 1998). The 

27 incidence data for cortical tubule cell degeneration in male and female rats exposed to 

28 1,4-dioxane in the drinking water for 2 years are presented in Table 5-1. Details of the BMD 

29 analysis of these data are presented in Appendix C. Male rats were more sensitive to the kidney 

30 effects of 1,4-dioxane than females and the male rat data provided the lowest POD for cortical 

31 tubule degeneration in the NCI (1978) study (BMDL10 of 22.3 mg/kg-day) (Table 5-2). 

32 Incidence data (JBRC, 1998; Kano, et al., 2009) for liver hyperplasia in male and female rats 

33 exposed to 1,4-dioxane in the drinking water for 2 years are presented in Table 5-3. Details of 

34 the BMD analysis of these data are presented in Appendix C. Male rats were more sensitive to 

35 developing liver hyperplasia due to exposure to 1,4-dioxane than females and the male rat data 

36 provided the lowest POD for hyperplasia in the JBRC (1998) study (BMDL10 of 23.8 mg/kg37 day) (Table 5-4). The BMDL10 values of 22.3 mg/kg-day and 23.8 mg/kg-day from the NCI 
109

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (1978) and JBRC (1998) studies, respectively, are about double the NOAEL (9.6 mg/kg-day) 

2 observed by Kociba et al. (1974).

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

0/31a20/31b27/33b0/31a0/34 10/32b

a

Statistically significant trend for increased incidence by Cochran-Armitage test (p < 0.05) performed for this 

review.

b

Incidence significantly elevated compared to control by Fisher‘s Exact test (p < 0.001) performed for this review.

Source: NCI (1978).

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

tubule degeneration in male and female Osborne-Mendel rats exposed to 

1,4-dioxane in drinking water for 2 years

BMD10 (mg/kg-day) BMDL10 (mg/kg-day)

Male rats 28.8 22.3

Female rats 596.4 452.4

Source: NCI (1978).

Table 5-3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to 

1,4-dioxane in drinking water for 2 yearsa

Males (mg/kg-day) Females (mg/kg-day)

0 11 55 274 0 18 83 429

3/40 2/45 9/35b12/22c0/38b0/37 1/38 14/24c

aDose 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 χ2test (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

BMD10 (mg/kg-day) BMDL10 (mg/kg-day)

Male rats 35.9 23.8

Female rats 137.3 88.5

Source: Kano et al. (2009); JBRC (1998).

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

The RfD of 3 × 10–21 mg/kg-day is based on liver and kidney toxicity in rats exposed to 

2 1,4-dioxane in the drinking water for 2 years (Kociba, et al., 1974). The Kociba et al. (1974)

3 study was chosen as the principal study because it provides the most sensitive measure of 

4 adverse effects by 1,4-dioxane. The incidence of liver and kidney lesions was not reported for 

5 each dose group. Therefore, BMD modeling could not be used to derive a POD. The RfD for 

6 1,4-dioxane is derived by dividing the NOAEL of 9.6 mg/kg-day (Kociba, et al., 1974) by a 

7 composite UF of 300, as follows:

8 RfD = NOAEL / UF

9 = 9.6 mg/kg-day / 300

= 0.03 or 3 × 10–210 mg/kg-day

11 The composite UF of 300 includes factors of 10 for animal-to-human extrapolation and 

12 for interindividual variability, and an UF of 3 for database deficiencies.

13 A default interspecies UF of 10 was used to account for pharmacokinetic and 

14 pharmacodynamic differences across species. Existing PBPK models could not be used to derive 

15 an oral RfD for 1,4-dioxane (Appendix B).

16 A default interindividual variability UF of 10 was used to account for variation in 

17 sensitivity within human populations because there is limited information on the degree to which 

18 humans of varying gender, age, health status, or genetic makeup might vary in the disposition of, 

19 or response to, 1,4-dioxane.

20 An UF of 3 for database deficiencies was applied due to the lack of a multigeneration 

21 reproductive toxicity study. A single oral prenatal developmental toxicity study in rats was 

22 available for 1,4-dioxane (Giavini, et al., 1985). This developmental study indicates that the 

23 developing fetus may be a target of toxicity.

24 An UF to extrapolate from a subchronic to a chronic exposure duration was not necessary 

25 because the RfD was derived from a study using a chronic exposure protocol.

26 An UF to extrapolate from a LOAEL to a NOAEL was not necessary because the RfD 

27 was based on a NOAEL. Kociba et al. (1974) was a well-conducted, chronic drinking water 
111

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 study with an adequate number of animals. Histopathological examination was performed for 

2 many organs and tissues, but clinical chemistry analysis was not performed. NOAEL and 

3 LOAEL values were derived by the study authors based on liver and kidney toxicity; however 

4 quantitative incidence data was not reported. Several additional oral studies (acute/short-term, 

5 subchronic, and chronic durations) were available that support liver and kidney toxicity as the 

6 critical effect (Argus, et al., 1973; JBRC, 1998; Kano, et al., 2008; NCI, 1978) (Tables 4-15 and 

7 4-17). Although degenerative liver and kidney toxicity was not observed in rats from the JBRC 

8 (1998) study at doses at or below the LOAEL in the Kociba et al. (1974) study, other endpoints 

9 such as metaplasia and hyperplasia of the nasal epithelium, nuclear enlargement, and 

10 hematological effects, were noted. 

5.1.4. RfD Comparison Information 

11 PODs and sample oral RfDs based on selected studies included in Table 4-18 are arrayed 

12 in Figures 5-1 to 5-3, and provide perspective on the RfD supported by Kociba et al. (1974). 

13 These figures should be interpreted with caution because the PODs across studies are not 

14 necessarily comparable, nor is the confidence in the data sets from which the PODs were derived 

15 the same. PODs in these figures may be based on a NOAEL, LOAEL, or BMDL (as indicated), 

16 and the nature, severity, and incidence of effects occurring at a LOAEL are likely to vary. To 

17 some extent, the confidence associated with the resulting sample RfD is reflected in the 

18 magnitude of the total UF applied to the POD (i.e., the size of the bar); however, the text of 

19 Sections 5.1.1 and 5.1.2 should be consulted for a more complete understanding of the issues 

20 associated with each data set and the rationale for the selection of the critical effect and principal 

21 study used to derive the RfD.

22 The predominant noncancer effect of chronic oral exposure to 1,4-dioxane is 

23 degenerative effects in the liver and kidney. Figure 5-1 provides a graphical display of effects 

24 that were observed in the liver following chronic oral exposure to 1,4-dioxane. Information 

25 presented includes the PODs and UFs that could be considered in deriving the oral RfD. As 

26 discussed in Sections 5.1.1 and 5.1.2, among those studies that demonstrated liver toxicity, the 

27 study by Kociba et al. (1974) provided the data set most appropriate for deriving the RfD. For 

28 degenerative liver effects resulting from 1,4-dioxane exposure, the Kociba et al. (1974) study 

29 represents the most sensitive effect and dataset observed in a chronic bioassay (Figure 5-1).

30 Kidney toxicity as evidenced by glomerulonephritis (Argus, et al., 1965; Argus, et al., 

31 1973) and degeneration of the cortical tubule (Kociba, et al., 1974; NCI, 1978) has also been 

32 observed in response to chronic exposure to 1,4-dioxane. As was discussed in Sections 5.1 and 

33 5.2, degenerative effects were observed in the kidney at the same dose level as effects in the liver 

34 (Kociba, et al., 1974). A comparison of the available datasets from which an RfD could 

35 potentially be derived is presented in Figure 5-2.
112

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Rhinitis and inflammation of the nasal cavity were reported in both the NCI (1978) (mice 

2 only, dose ≥ 380 mg/kg-day) and JBRC (1998) studies (≥ 274 mg/kg-day in rats, >278 mg/kg3 day in mice). JBRC (1998) reported nasal inflammation in rats (NOAEL 55 mg/kg-day, LOAEL 

4 274 mg/kg-day) and mice (NOAEL 66 mg/kg-day, LOAEL 278 mg/kg-day). A comparison of 

5 the available datasets from which an RfD could potentially be derived is presented in Figure 5-3.

6 Figure 5-4 displays PODs for the major targets of toxicity associated with oral exposure 

7 to 1,4-dioxane. Studies in experimental animals have also found that relatively high doses of 

8 1,4-dioxane (1,000 mg/kg-day) during gestation can produce delayed ossification of the 

9 sternebrae and reduced fetal BWs (Giavini, et al., 1985). This graphical display (Figure 5-4) 

10 compares organ specific toxicity for 1,4-dioxane, including a single developmental study. The 

11 most sensitive measures of degenerative liver are and kidney effects. The sample RfDs for 

12 degenerative liver and kidney effects are identical since they were derived from the same study

13 and dataset (Kociba, et al., 1974) and are presented for completeness. 

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

with corresponding applied uncertainty factors and derived RfDs following 

oral exposure to 1,4-dioxane.

0.01

0.1

1

10

100

Liver hyperplasia;

NOAEL; 2 yr rat

drinking water study 

Hepatocellular

degeneration and

necrosis; NOAEL; 2 yr

rat drinking water study 

Increase in serum liver

enzymes; NOAEL; 2 yr

mouse drinking water

study 

Increase in serum liver

enzymes; NOAEL; 2 yr

rat drinking water study 

Liver hyperplasia;

BMDL10; 2 yr rat

drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Rat Rat Mouse Rat Rat
113

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

with corresponding applied uncertainty factors and derived RfDs following 

oral exposure to 1,4-dioxane.

0.01

0.1

1

10

100

1000

Glomerulonephritis; LOAEL; 13 month

rat drinking water study 

Degeneration and necrosis of tubular

epithelium; NOAEL; 2 yr rat drinking

water study 

Cortical tubule degeneration; BMDL10;

2 yr rat drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Rat Rat Rat
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.

0.1

1

10

100

Nasal inflammation; NOAEL; 2 yr mouse drinking water study Nasal inflammation; NOAEL; 2 yr rat drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Mouse Rat
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 

1 An assessment for 1,4-dioxane was previously posted on the IRIS database in 1988. An 

2 oral RfD was not developed as part of the 1988 assessment.

5.2. INHALATION REFERENCE CONCENTRATION (RFC)

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

3 Two human studies of occupational exposure to 1,4-dioxane have been published 

4 (Buffler, et al., 1978; Thiess, et al., 1976); however, neither study provides sufficient information 

5 and data to quantify subchronic or chronic noncancer effects. In each study, findings were 

6 inconclusive and the cohort size and number of reported cases were limited (Buffler, et al., 1978; 

7 Thiess, et al., 1976). 

8 Four inhalation studies in animals were identified in the literature; two, 13-week 

9 subchronic studies in laboratory animals (Fairley, et al., 1934; Kasai, et al., 2008) and two, 2-

10 year chronic studies in rats (Kasai, et al., 2009; Torkelson, et al., 1974). 

0.01

0.1

1

10

100

1000

Degeneration and necrosis

of tubular epithelium;

NOAEL; 2 yr rat drinking

water study 

Hepatocellular

degeneration and necrosis;

NOAEL; 2 yr rat drinking

water sduy 

Delayed ossification of

sternebrae and reduced

fetal body weight; NOAEL;

rat study gestation days 6-

15 

Nasal inflammation;

NOAEL; 2 yr mouse

drinking water study 

Dose (mg/kg-day)

POD

Animal-to-human

Human variation

LOAEL to NOAEL

Subchronic to Chronic

Database deficiencies

RfD

Rat Rat Rat Mouse
116

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 In the subchronic study by Fairley et al. (1934) rabbits, guinea pigs, rats, and mice 

2 (3-6/species/group) were exposed to 1,000, 2,000, 5,000, or 10,000 ppm of 1,4-dioxane vapor for 

3 1.5 hours two times a day for 5 days, 1.5 hours for one day, and no exposure on the seventh day. 

4 Animals were exposed until death occurred or were sacrificed after various durations of exposure 

5 (3-202.5 hours). Detailed dose-response information was not provided; however, severe liver 

6 and kidney damage and acute vascular congestion of the lungs were observed at concentrations ≥ 

7 1,000 ppm. 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. In this study, a LOAEL of 1,000 ppm for liver and kidney degeneration 

10 in rats, mice, rabbits, and guinea pigs was identified by the EPA.

11 In the subchronic study by Kasai et al. (2008) male and female rats (10/group/sex) were 

12 exposed to 0, 100, 200, 400, 800, 1,600, 3,200, and 6,400 ppm of 1,4-dioxane for 6 hours/day, 5 

13 days/week for 13 weeks. This study observed a range of 1,4-dioxane induced nonneoplastic 

14 effects across several organ systems including the liver and respiratory tract (from the nose to the

15 bronchus region) in both sexes and the kidney in females. Detailed dose-response information 

16 was provided, illustrating a concentration-dependent increase of nuclear enlargement of nasal

17 (respiratory and olfactory), trachea, and bronchus epithelial cells (both sexes); vacuolic change 

18 of nasal and bronchial epithelial cells (both sexes), necrosis and centrilobular swelling of 

19 hepatocytes (both sexes); and hydropic change in the proximal tubules of the kidney (females). 

20 The study authors determined nuclear enlargement of the nasal respiratory epithelium as the 

21 most sensitive lesion and a LOAEL of 100 ppm was identified based on this effect. 

22 Torkelson et al. (1974) performed a chronic inhalation study in which male and female 

23 Wistar rats (288/sex) were exposed to 111 ppm 1,4-dioxane vapor for 7 hours/day, 5 days/week 

24 for 2 years. Control rats (192/sex) were exposed to filtered air. No significant effects were 

25 observed on BWs, survival, organ weights, hematology, clinical chemistry, or histopathology. 

26 A free standing NOAEL of 111 ppm was identified in this study by EPA. 

27 Kasai et al. (2009) reported data for groups of male F344 rats (50/group) exposed to 0, 

28 50, 250, and 1,250 ppm of 1,4-dioxane for 6 hours/day, 5 days/week, for 2 years. In contrast to 

29 the subchronic Kasai et al. (2008) study, this 2-year bioassay reported more nonneoplastic effects 

30 in multiple organ systems. Additional noted incidences included: (1) inflammation of nasal

31 respiratory and olfactory epithelium, (2) squamous cell metaplasia and hyperplasia of nasal 

32 respiratory epithelium, (3) atrophy and respiratory metaplasia of olfactory epithelium, (4)

33 hydropic change and sclerosis in lamina propria of nasal cavity, (5) nuclear enlargement in 

34 proximal tubules of kidney and in centrilobular of liver, (6) centrilobular necrosis in the liver, 

35 and (7) spongiosis hepatis. Some of these histopathological lesions were significantly increased 

36 compared to controls at the lowest exposure level (50 ppm), including nuclear enlargement of 

37 respiratory and olfactory epithelium; and atrophy and respiratory metaplasia of olfactory 
117

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 epithelium. Many of these histopathological lesions were increased in a concentration-dependent 

2 manner.

3 Because Fairley et al. (1934) did not present the statistics of the dose response data, and 

4 Torkelson et al. (1974) identified a free-standing NOAEL only, neither study was sufficient to 

5 characterize the inhalation risks of 1,4-dioxane. A route extrapolation from oral toxicity data 

6 was not performed because 1,4-dioxane inhalation causes direct effects on the respiratory tract 

7 (i.e., respiratory irritation in humans, pulmonary congestion in animals) (Fairley, et al., 1934; 

8 Wirth & Klimmer, 1936; Yant, et al., 1930), which would not be accounted for in a cross-route 

9 extrapolation. In addition, available kinetic models are not suitable for this purpose (Appendix 

10 B).

11 The chronic Kasai et al. (2009) study was selected as the principal study for the 

12 derivation of the RfC. Based on the noncancer database for 1,4-dioxane, this study demonstrated 

13 exposure concentration-related effects for histopathological lesions at lower doses as compared 

14 to the subchronic Kasai et al. study (2008). In addition, the Kasai et al. (2009) 2-year bioassay 

15 study utilized 50 animals per exposure group, a range of exposure concentrations which were 

16 based on the results of the subchronic study (2008) and thoroughly examined toxicity of 1-

17 4,dioxane in multiple organ systems. This 2-year bioassay (Kasai, et al., 2009) did not observe 

18 effects in both sexes, but the use of only male rats was proposed by the study authors as justified 

19 by data illustrating the absence of induced mesotheliomas in female rats following exposure to 

20 1,4-dioxane in drinking water (Yamazaki, et al., 1994). 

21 All systemic and portal-of-entry nonneoplastic lesions from the Kasai et al. (2009) study 

22 that were statistically increased at the low- or mid- exposure concentration (50 or 250 ppm) 

23 compared to controls, or the lesions that demonstrated a dose-response relationship in the 

24 absence of statistical significance were considered candidates for the critical effect. The 

25 candidate endpoints included centrilobular necrosis of the liver, spongiosis hepatis, squamous 

26 cell metaplasia of nasal respiratory epithelium, squamous cell hyperplasia of nasal respiratory 

27 epithelium, respiratory metaplasia of nasal olfactory epithelium, sclerosis in lamina propria of 

28 nasal cavity, and two degenerative nasal lesions, that is, atrophy of nasal olfactory epithelium 

29 and hydropic change in the lamina propria (Table 5-5). Despite statistical increases at the low30 and mid exposure concentrations, incidences of nuclear enlargement of respiratory epithelium 

31 (nasal cavity), olfactory epithelium (nasal cavity), and proximal tubule (kidney) were not 

32 considered candidates for the critical effect given that the toxicological significance of nuclear 

33 enlargement is uncertain (See Section 4.6.2 and Table 4-22).
118

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table 5-5. Incidences of nonneoplastic lesions resulting from chronic 

exposure (ppm) to 1,4-dioxane considered 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 12/50a

Spongiosis hepatis 7/50 6/50 13/50 19/50 a

Nasal Squamous cell metaplasia; 

respiratory epithelium 0/50 0/50 7/50b

44/50a

Squamous cell hyperplasia; 

respiratory epithelium 0/50 0/50 1/50 10/50a

Respiratory metaplasia; 

olfactory epithelium 11/50 34/50a

49/50a48/50a

Atrophy; olfactory epithelium 0/50 40/50a47/50a48/50a

Hydropic change; 

lamina propria 0/50 2/50 36/50a

49/50a

Sclerosis; lamina propria 0/50 0/50 22/50a40/50a

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

1 Benchmark dose (BMD) modeling methodology (U.S. EPA, 2000a) was used to analyze 

2 the candidate endpoints identified for 1,4-dioxane. Use of BMD methods involves fitting 

3 mathematical models to the observed dose-response data and provides a BMD and its 95% lower 

4 confidence limit (BMDL) associated with a predetermined benchmark response (BMR). The 

5 suitability of these methods to determine a POD is dependent on the nature of the toxicity 

6 database for a specific chemical. For 1,4-dioxane, the selected datasets in Table 5-5 were 

7 analyzed using BMD modeling. Information regarding the degree of change in the selected 

8 endpoints that is considered biologically significant was not available. Therefore, a BMR of 

9 10% extra risk was selected under the assumption that it represents a mimimally biologically 

10 significant response level (U.S. EPA, 2000a). 

11 BMD model results were inadequate (poor fit and/or substantial model uncertainty – see 

12 Appendix F) for the following nasal lesions: atrophy (olfactory epithelium), respiratory 

13 metaplasia (olfactory epithelium), and sclerosis (lamina propria). Considering the datasets for 

14 atrophy and respiratory metaplasia, in which the first non-control dose had a response level 

15 substantially above the desired BMR, the use of BMD methods included substantial model 

16 uncertainty (Appendix F). The detailed results of the BMDS analysis are provided in Appendix 
119

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 F. Consequently, NOAELs and LOAELs were used as potential PODs for the endpoints not 

2 suitable for BMD modeling. 

5.2.3. Exposure Duration and Dosimetric Adjustments

3 Because an RfC is a measure that assumes continuous human exposure over a lifetime, 

4 data derived from animal studies need to be adjusted to account for the noncontinuous exposure 

5 protocols used in animal studies. In the Kasai et al. (2009) study, rats were exposed to 1,4-

6 dioxane for 6 hours/day, 5 days/week for 2 years. Therefore, the duration-adjusted PODs for 

7 nasal and systemic lesions in rats were calculated as follows: 

7days

days exposed per week

24hours

hours exposed per day POD (ppm) POD(ppm) ADJ

8

RfCs are typically expressed in units of mg/m

3

9 ; so PODADJ (ppm) values were 

converted using the chemical specific conversion factor of 1 ppm = 3.6 mg/m310 for 1,4-dioxane 

11 (Table 2-1). The following calculation was used: 

1ppm

3.6 mg/m POD (mg/m ) POD (ppm)

3

ADJ

3

ADJ

12

The calculated PODADJ (mg/m313 ) values for all considered endpoints are presented in the 

14 last column of Table 5-6. 

Table 5-6. Duration adjusted POD estimates for best fitting BMDS models or 

NOAEL/LOAEL from chronic exposure to 1,4-dioxane 

Endpoint NOAELa

(ppm)

LOAELb

(ppm) Model BMR BMD(ppm)

BMDL

(ppm)

PODADJ

(mg/m3)

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 DichotomousHill10 220 60 38.6

Spongiosis hepatis; 

Liver

250 1250 Log-logisticd10 314 172 111
120

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

aNOAEL is identified as the highest tested exposure dose at which there is no statistically significant effect in the 

exposed group as compared to control.

bLOAEL is identified as the lowest tested exposure dose at which there is a statistically significant effect in the 

exposed group as compared to control.

cBMDS model results are not adequate for use to derive a POD. Therefore, NOAEL/LOAEL approach is 

recommended to determine a PODADJ for these endpoints. BMDS analysis for these endpoints is included in 

Appendix F.

dDichotomous Hill model had lowest BMDL, but model output warned that the BMDL estimate was ―imprecise at 

best‖. 

1 Based on analysis of data in Table 5-5, hydropic change, atrophy, and respiratory 

2 metaplasia were a considered for selection of the critical effect. Typically, chemical-induced 

3 nasal effects include atrophy and/or necrosis, cell proliferation/hyperplasia, and metaplasia 

4 depending on the nature of the tissue damage and exposure (Boorman, Morgan, & Uriah, 1990; 

5 Gaskell, 1990; Harkema, Carey, & Wagner, 2006). These effects are often accompanied by an 

6 inflammatory response. BMD analysis indicated hydropic change of lamina propria was the 

7 most sensitive endpoint. Hydropic change and atrophy were the two degenerative nasal lesions 

8 observed (Table 5-5); however, because hydropic change has a NOAEL (i.e., 50 ppm) and a 

9 calculated BMDL (i.e., 47 ppm) at an exposure concentration equivalent to the LOAEL (i.e., 50 

10 ppm) designated for other nasal lesions (i.e., atrophy and respiratory metaplasia), hydropic 

11 change was not selected as the critical effect. Therefore, in this assessment the LOAEL approach 

12 is the preferred methodology for selection of the critical effect and POD. 

13 Using the LOAEL approach, atrophy and respiratory metaplasia of the olfactory 

epithelium are identified as the most sensitive endpoints with a PODADJ of 32.2 mg/m314 . Since 

15 atrophy of the olfactory epithelium had an increased incidence rate at the LOAEL compared to 

16 respiratory metaplasia and is likely to occur earlier in the continuum of pathological events 

17 associated with respiratory tract effects, it is selected as the critical effect in this assessment. 

18 For the derivation of a RfC based upon an animal study, the selected POD must be 

19 adjusted to reflect the human equivalent concentration (HEC). The HEC was calculated by the 

20 application of the appropriate dosimetric adjustment factor (DAF), in accordance with the U.S. 

21 EPA RfC methodology (U.S. EPA, 1994b). DAFs are ratios of animal and human physiologic 

22 parameters, and are dependent on the nature of the contaminant (particle or gas) and the target 

23 site (e.g., respiratory tract or remote to the portal-of-entry) (U.S. EPA, 1994b). 

24 1,4-Dioxane is miscible with water and has a high blood:air partition coefficient. 

25 Typically, highly water-soluble and directly reactive chemicals (i.e. Category 1 gases) partition 

26 greatly into the upper respiratory tract, induce portal-of-entry effects, and do not accumulate 

27 significantly in the blood. 1,4-Dioxane induces both systemic and portal of entry effects and has

28 been measured in the blood after inhalation exposure (Kasai, et al., 2008). The observations of 

29 systemic (i.e., nonrespiratory) effects and measured blood levels resulting from 1,4-dioxane 

30 exposure clearly indicate that this compound is absorbed into the bloodstream and distributed 
121

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 throughout the body. Furthermore, the lack of an anterior to posterior gradient for the nasal 

2 effects induced by 1,4-dioxane is not typical of chemicals which are predominantly directly 

3 reactive. Thus, 1,4-dioxane might be best described as a water-soluble and non-directly reactive 

4 gas. Gases such as these are readily taken up into respiratory tract tissues and can also diffuse 

5 into the blood capillaries (Medinsky & Bond, 2001). The effects in the olfactory epithelium may 

6 be the result of the metabolism of 1,4-dioxane to an acid metabolite; however, for the reasons 

7 stated above it is unclear whether or not these effects are solely the result of portal-of-entry or 

8 systemic delivery. A similar pattern of systemic effects (i.e., respiratory tract effects) were 

9 observed after oral exposure to 1,4-dioxane . 

10 Consequently, for dosimetric purposes, the human equivalent concentration (HEC) for 

11 1,4-dioxane was calculated by the application of the appropriate dosimetric adjustment factor 

12 (DAF) for systemic acting gases (i.e. Category 3 gases), in accordance with the U.S. EPA RfC 

13 methodology (U.S. EPA, 1994b) as follows: 

14

15 DAF = (Hb/g)A/(Hb/g)H 

16 where: 

17 (Hb/g)A = the animal blood:air partition coefficient =1861 (Sweeney, et al., 2008)

18 (Hb/g)H = the human blood:air partition coefficient =1666 (Sweeney, et al., 2008)

19 DAF = 1861/1666

20 DAF = 1.12 

21

22 Given that the animal blood:air partition coefficient is higher than the human value 

23 resulting in a DAF>1, a default value of 1 is substituted in accordance with the U.S. EPA RfC 

24 methodology (U.S. EPA, 1994b). Analysis of the existing inhalation dosimetry modeling 

25 database supports the application of a DAF of 1 to be appropriate (U.S. EPA, 2009a). 

26 Application of these models to gases that have similar physicochemical properties and induce 

27 similar nasal effects as 1,4-dioxane estimate DAFs ≥ 1.

28 Utilizing a DAF of 1, the HEC for atrophy of the olfactory epithelium in male 

29 F344/DuCrj rats is calculated as follows:

30

PODHEC (mg/m3) = PODADJ (mg/m331 ) × DAF 

= PODADJ (mg/m332 ) × 1.0 

= 32.2 mg/m3 33 × 1.0 

= 32.2 mg/m334

35

Therefore, the PODHEC of 32.2 mg/m336 for the critical effect of atrophy of the olfactory 

37 epithelium is used for the derivation of a RfC for 1,4-dioxane. 
122

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/m3 1 is based on atrophy of the olfactory epithelium in male rats 

2 exposed to 1,4-dioxane via inhalation for 2 years (Kasai, et al., 2009). The RfC for 1,4-dioxane is 

3 derived by dividing the PODHEC for 1,4-dioxane by a composite UF of 1000. 

4

5 RfC = PODHEC / UF

= 32.2 mg/m36 / 1000

= 0.0322 or 3 × 10–2 mg/m37

8

9 The composite UF of 1000 includes factors of 10 for LOAEL-to-NOAEL extrapolation 

10 and for human interindividual variability, and factors of 3 were used for animal-to-human 

11 extrapolation and for database deficiencies. 

12 An UF of 10 was used to extrapolate from a LOAEL to a NOAEL given significant 

13 incidence data reported at the lowest tested concentration for this endpoint. A NOAEL for 

14 atrophy of the olfactory epithelium was not identified in this study. Adequate BMD model 

15 estimates were not available for derivation of the RfC, and since a NOAEL was not identified for 

16 atrophy of the olfactory epithelium, the LOAEL (lowest dose tested in the study by Kasai et al. 

17 (2009)) was chosen as the POD.

18 A default interindividual variability UF of 10 was used to account for variation in 

19 sensitivity within human populations because there is limited information on the degree to which 

20 humans of varying gender, age, health status, or genetic makeup might vary in the disposition of, 

21 or response to, 1,4-dioxane.

22 An UF of 3 was used to for animal-to-human extrapolation to account for 

23 pharmacodynamic differences between species. This uncertainty factor for animal-to-human 

24 extrapolation is comprised of two separate and equal areas of uncertainty to account for 

25 difference in the toxicokinetics and toxicodynamics of animals and humans. In this assessment, 

26 the toxicokinetic uncertainty was accounted for by the calculation of a HEC by the application of 

27 a dosimetric adjustment factor as outlined in the RfC methodology (U.S. EPA, 1994b). As the 

28 toxicokinetic differences are thus accounted for, only the toxicodynamic uncertainties remain, 

29 and an UF of 3 is retained to account for this uncertainty.

30 An UF of 3 for database deficiencies was applied due to the lack of a multigeneration 

31 reproductive toxicity study. The oral toxicity database included a single prenatal developmental 

32 study that indicated the developing fetus may be a target of toxicity (Giavini, et al., 1985)

33 An UF to extrapolate from a subchronic to a chronic exposure duration was not necessary 

34 because the RfC was derived from a study using a chronic exposure protocol.
123

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

5.2.5. RfC Comparison Information

1 Figure 5-5 presents PODs, applied UFs, and derived sample RfCs for possible endpoints 

2 from the chronic inhalation Kasai et al. (2009) in male rats. The PODs are based on the BMDL10, 

3 NOAEL, or LOAEL and appropriate unit conversion and duration and dosimetric adjustments 

4 were applied before applications of uncertainty factors. 

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

5 An assessment for 1,4-dioxane was previously posted on the IRIS database in 1988 and 

6 2010. An inhalation RfC was not developed as part of either the 1988 or 2010 assessment.

5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE AND INHALATION 

REFERENCE CONCENTRATION

7 Risk assessments need to portray associated uncertainty. The following discussion 

8 identifies uncertainties associated with the RfD and RfC for 1,4-dioxane. As presented earlier in 

9 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 

10 uncertainty factor approach (U.S. EPA, 1994b, 2002a) was used to derive the RfD and RfC for 
124

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 1,4-dioxane. Using this approach, the POD was divided by a set of factors to account for 

2 uncertainties associated with a number of steps in the analysis, including extrapolation from 

3 LOAEL to NOAEL exposure and responses observed in animal bioassays to humans, a diverse 

4 population of varying susceptibilities, and to account for database deficiencies. Because 

5 information specific to 1,4-dioxane was unavailable to fully inform many of these extrapolations, 

6 default factors were generally applied.

7 An adequate range of animal toxicology data are available for the hazard assessment of 

8 1,4-dioxane, as described throughout the previous section (Section 4). The database of oral 

9 toxicity studies includes chronic drinking water studies in rats and mice, multiple subchronic 

10 drinking water studies conducted in rats and mice, and a developmental study in rats. Toxicity 

11 associated with oral exposure to 1,4-dioxane is observed predominately in the liver and kidney. 

12 The database of inhalation toxicity studies in animals includes two subchronic bioassays in 

13 rabbits, guinea pigs, mice, and rats, and two chronic inhalation bioassays in rats. Toxicity 

14 associated with inhalation exposure to 1,4-dioxane was observed predominately in the liver and 

15 nasal cavity. In addition to oral and inhalation data, there are PBPK models and genotoxicity 

16 studies of 1,4-dioxane. Critical data gaps have been identified and uncertainties associated with 

17 data deficiencies of 1,4-dioxane are more fully discussed below.

18 Consideration of the available dose-response data led to the selection of the two-year 

19 drinking water bioassay in Sherman rats (Kociba, et al., 1974) as the principal study and 

20 increased liver and kidney degeneration as the critical effects for deriving the RfD for 

21 1,4-dioxane. The dose-response relationship for oral exposure to 1,4-dioxane and cortical tubule 

22 degeneration in Osborne-Mendel rats (NCI, 1978) was also suitable for deriving a RfD, but it is 

23 associated with higher a POD and potential RfD compared to Kociba et al. (1974).

24 The RfD was derived by applying UFs to a NOAEL for degenerative liver and kidney 

25 effects. The incidence data for the observed effects were not reported in the principal study 

26 (Kociba, et al., 1974), precluding modeling of the dose-response. However confidence in the 

27 NOAEL can be derived from additional studies (Argus, et al., 1965; Argus, et al., 1973; JBRC, 

28 1998; NCI, 1978) that observed effects on the same organs at comparable dose levels and by the 

29 BMDL generated by modeling of the kidney dose-response data from the chronic NCI (1978)

30 study.

31 The RfC was derived by applying UFs to a LOAEL for atrophy of the olfactory 

32 epithelium. The incidence data for the observed effects were not appropriate for BMD modeling 

33 for this endpoint (see Appendix F). The LOAEL for this effect was less than or equal to the 

34 LOAEL or NOAEL for other effects observed in the same study.

35 Extrapolating from animals to humans embodies further issues and uncertainties. The 

36 effect and the magnitude associated with the dose at the POD in rodents are extrapolated to 

37 human response. Pharmacokinetic models are useful to examine species differences in 
125

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 pharmacokinetic processing; however, it was determined that dosimetric adjustment using 

2 pharmacokinetic modeling to reduce uncertainty following oral exposure to 1,4-dioxane was not 

3 supported. Insufficient information was available to quantitatively assess toxicokinetic or 

4 toxicodynamic differences between animals and humans, so a 10-fold UF was used to account 

5 for uncertainty in extrapolating from laboratory animals to humans in the derivation of the RfD. 

6 A DAF was used to account for pharmacokinetic differences between rodents and humans in the 

7 derivation of the RfC; however, there was no information to inform pharmacodynamic 

8 differences between species, so a reduced UF of 3 was used in derivation of the RfC to account 

9 for these uncertainties.

10 Heterogeneity among humans is another uncertainty associated with extrapolating doses 

11 from animals to humans. Uncertainty related to human variation needs consideration. In the 

12 absence of 1,4-dioxane-specific data on human variation, a factor of 10 was used to account for 

13 uncertainty associated with human variation in the derivation of the RfD and RfC. Human 

14 variation may be larger or smaller; however, 1,4-dioxane-specific data to examine the potential 

15 magnitude of over- or under-estimation are unavailable.

16 Uncertainties in the assessment of the health hazards of 1,4-dioxane are associated with 

17 deficiencies in reproductive toxicity information. The oral and inhalation databases lack a 

18 multigeneration reproductive toxicity study. A single oral prenatal developmental toxicity study 

19 in rats was available for 1,4-dioxane (Giavini, et al., 1985). This developmental study indicates 

20 that the developing fetus may be a target of toxicity. The database of inhalation studies also 

21 lacks a developmental toxicity study.

5.4. CANCER ASSESSMENT

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

5.4.1.1. Oral Study/Data

22 Three chronic drinking water bioassays provided incidence data for liver tumors in rats 

23 and mice, and nasal cavity, peritoneal, and mammary gland tumors in rats only (JBRC, 1998; 

24 Kano, et al., 2009; Kociba, et al., 1974; NCI, 1978; Yamazaki, et al., 1994). The dose-response 

25 data from each of these studies are summarized in Table 5-7. With the exception of the NCI 

26 (1978) study, the incidence of nasal cavity tumors was generally lower than the incidence of liver 

27 tumors in exposed rats. The Kano et al. (2009) drinking water study was chosen as the principal 

28 study for derivation of an oral cancer slope factor (CSF) for 1,4-dioxane. This study used three 

29 dose groups in addition to controls and characterized the dose-response relationship at lower 

30 exposure levels, as compared to the high doses employed in the NCI (1978) bioassay (Table 5-

31 7). The Kociba et al. (1974) study also used three dose groups and low exposures; however, the 

32 study authors only reported the incidence of hepatocellular carcinoma, which may underestimate 
126

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 the combined incidence of rats with adenoma or carcinoma. In addition to increased incidence of 

2 liver tumors, chosen as the most sensitive target organ for tumor formation, the Kano et al. 

3 (2009) study also noted increased incidence of peritoneal and mammary gland tumors. Nasal 

4 cavity tumors were also seen in high-dose male and female rats; however, the incidence of nasal 

5 tumors was much lower than the incidence of liver tumors in both rats and mice.

6 In a personal communication, Dr. Yamazaki (2006) provided that the survival of mice 

7 was low in all male groups (31/50, 33/50, 25/50 and 26/50 in control, low-, mid-, and high-dose 

8 groups, respectively) and particularly low in high-dose females (29/50, 29/50, 17/50, and 5/50 in 

9 control, low-, mid-, and high-dose groups, respectively). These deaths occurred primarily during 

10 the second year of the study. Survival at 12 months in male mice was 50/50, 48/50, 50/50, and 

11 48/50 in control, low-, mid-, and high-dose groups, respectively. Female mouse survival at 

12 12 months was 50/50, 50/50, 48/50, and 48/50 in control, low-, mid-, and high-dose groups, 

13 respectively (Yamazaki, 2006). Furthermore, these deaths were primarily tumor related. Liver 

14 tumors were listed as the cause of death for 31 of the 45 pretermination deaths in high-dose 

15 female Crj:BDF1 mice (Yamazaki, 2006). Thus, the high mortality rates in the female mice 

16 were still considered to be relevant for this analysis.

Table 5-7. Incidence of liver, nasal cavity, peritoneal, and mammary gland 

tumors in rats and mice exposed to 1,4-dioxane in drinking water for 2 years 

(based on survival to 12 months)

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 

combineda,b

0 1/106h0/106h NA NA

14 0/110 0/110 NA NA

121 1/106 0/106 NA NA

1,307 10/66i3/66 NA NA

NCI (1978) Male Osborne-Mendel 

ratsb

0 NA 0/33h NA NA

240 NA 12/26 NA NA

530 NA 16/33i NA NA

Female OsborneMendel ratsb,c0 0/31h0/34h NA NA

350 10/30i10/30i NA NA

640 11/29i8/29i NA NA

Male B6C3F1 miced0 8/49h NA NA NA

720 19/50i NA NA NA

830 28/47i NA NA NA

Female B6C3F1 miced0 0/50h NA NA NA

380 21/48i NA NA NA

860 35/37i NA NA NA
127

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Kano et al. (2009) Male F344/DuCrj 

ratsd,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 39/50j,k 7/50k28/50j,k 6/50k

Female F344/DuCrj 

ratsd,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 48/50j,k 8/50j,k 0/50 18/50i,k

Male Crj:BDF1 miced0 23/50 0/50 NA NA

49 31/50 0/50 NA NA

191 37/50i0/50 NA NA

677 40/50j,k 1/50 NA NA

Female Crj:BDF1

miced

0 5/50 0/50 NA NA

66 35/50j0/50 NA NA

278 41/50j0/50 NA NA

964 46/50j,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

1 Epidemiological studies of populations exposed to 1,4-dioxane are not adequate for dose2 response analysis and derivation of an inhalation unit risk (IUR). However, two chronic 

3 inhalation studies in animals are available and were evaluated for the potential to estimate an 

4 IUR (Table 5-8). The chronic inhalation study conducted by Torkelson et al. (1974) in rats did 

5 not find any treatment-related tumors; however, only a single exposure concentration was used 

6 (111 ppm 1,4-dioxane vapor for 7 hours/day, 5 days/week for 2 years). A chronic bioassay of 

7 1,4-dioxane by the inhalation route reported by Kasai et al. (2009) provides data adequate for 

8 dose-response modeling and was subsequently chosen as the principal study for the derivation of 

9 an IUR for 1,4-dioxane. In this bioassay, groups of 50 male F344 rats were exposed to either 0, 

10 50, 250 or 1,250 ppm 1,4-dioxane, 6 hours/day, 5 days/week, for 2 years (104-weeks). In male 

11 F344 rats, 1,4-dioxane produced a statistically significant increase in incidence and/or a 

12 statistically significant dose-response trend for the following tumor types: hepatomas, nasal 

13 squamous cell carcinomas, renal cell carcinomas, peritoneal mesotheliomas, mammary gland 
128

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 fibroadenomas, Zymbal gland adenomas, and subcutis fibromas (Kasai, et al., 2009). It is 

2 important to note that the incidence of adenomas and the incidence of carcinomas within a dose 

3 group at a site or tissue (i.e., liver) in rodents are sometimes combined. This practice is based 

4 upon the hypothesis that adenomas may develop into carcinomas if exposure at the same dose 

5 was continued (McConnell, Solleveld, Swenberg, & Boorman, 1986; U.S. EPA, 2005a). 

6 Consistent with the oral cancer assessment (Appendix D), the incidence of hepatic adenomas and 

7 carcinomas was summed without double-counting, to calculate the combined incidence of either 

8 a hepatocellular carcinoma or adenoma in rodents (See Table 5-8).

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

Liverc

Nasal 

cavityd Kidneye Peritonealf

Mammary 

gland

Zymbal 

glandgSubcutish

Torkelson 

et al. 

(1974)

a

Male 

Wistar 

rats

0 0/150 0/150 0/150i NA NA NA 0/150

111 0/206 0/206 1/206i NA NA NA 2/206

Female 

Wistar 

rats

0 0/139 0/139 1/139j NA 11/139k NA 0/139

111 0/217 0/217 0/217j NA 29/217k NA 0/217

Kasai et 

al. 

(2009)

b

Male 

F344 

rats

0 1/50 0/50 0/50 2/50 1/50l0/50 1/50

50 2/50 0/50 0/50 4/50 2/50l0/50 4/50

250 4/50 1/50 0/50 14/50n3/50l0/50 9/50n

1,250 22/50 6/50m4/50 41/50n5/50l4/50 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 provided via personal 

communication from Dr. Tatsuya Kasai to Dr. Reeder Sams on 12/23/2008 (2008). Statistics were not reported. 

Individual incidence 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.

mTumor incidence significantly elevated compared with that in controls by Fisher‘s exact test (p ≤ 0.05).

nTumor 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

9 Table 5-9 summarizes the incidence of hepatocellular adenoma or carcinoma in rats and 

10 mice from the Kano et al. (2009) 2-year drinking water study. There were statistically 
129

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 significant increasing trends in tumorigenic response for males and females of both species. The 

2 dose-response curve for female mice is steep, with 70% incidence of liver tumors occurring in 

3 the low-dose group (66 mg/kg-day). Exposure to 1,4-dioxane increased the incidence of these 

4 tumors in a dose-related manner.

5 A significant increase in the incidence of peritoneal mesothelioma was observed in high6 dose male rats only (28/50 rats, Table 5-7). The incidence of peritoneal mesothelioma was lower 

7 than the observed incidence of hepatocellular adenoma or carcinoma in male rats (Table 5-9); 

8 therefore, hepatocellular adenoma or carcinoma data were used to derive an oral CSF for 

9 1,4-dioxane.

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 tumorsa

Male F344/DuCrj rats 0 3/50

11 4/50

55 7/50

274 39/50b,c

Female F344/DuCrj rats 0 3/50

18 1/50

83 6/50

429 48/50b,c

Male Crj:BDF1 mice 0 23/50

49 31/50

191 37/50d

677 40/50b,c

Female Crj:BDF1 mice 0 5/50

66 35/50c

278 41/50c

964 46/50b,c

a

Incidence of either hepatocellular adenoma or carcinoma.

b

p < 0.05; positive dose-related trend (Peto‘s test).

c

Significantly different from control at p < 0.01 by Fisher‘s Exact test.

d

Significantly different from control at p < 0.01 by Fisher‘s Exact test.

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009).

5.4.2.2. Inhalation Data

10 Multi-tumor dose-response modeling was performed for all tumor responses from the 

11 Kasai et al. (2009) bioassay. Kasai et al. (2009) reported tumor incidence data for male F344 

12 rats exposed via inhalation to 0, 50, 250, or 1,250 ppm 1,4-dioxane for 6 hours/day, 5days/week, 

13 for 2 years (104-weeks). Statistically significant dose-response trends for the increase in tumors 
130

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 with increasing dose was observed for the nasal cavity squamous cell carcinomas, hepatomas, 

2 renal cell carcinomas, peritoneal mesotheliomas, mammary gland fibroadenomas, and Zymbal

3 gland adenomas. Following 250 ppm 1,4-dioxane exposure statistically elevated tumor 

4 incidences were found in two tissue types (peritoneal mesothelioma and subcutis fibroma) 

5 compared to controls. Tumor incidences following 1,250 ppm inhalation exposure to 1,4-

6 dioxane were statistically elevated compared to controls in three tissues (nasal cavity squamous 

7 cell carcinoma, hepatomas, and peritoneal mesothelioma). Incidence data for the tumor types 

8 reported by Kasai et al. (2009) are summarized in Table 5-10.

Table 5-10. Incidence of tumors in F344 male rats exposed to 1,4-dioxane for 

104 weeks (6 hours/day, 5 days/week)

Tumor Type Animal Exposure (ppm)

0 50 250 1,250

Nasal cavity squamous cell carcinoma 0/50 0/50 1/50 6/50a,b

Hepatocellular adenoma 1/50 2/50 3/50 21/50a,c

Hepatocellular carcinoma 0/50 0/50 1/50 2/50

Hepatocellular adenoma or carcinomae1/50 2/50 4/50 22/50a,c

Renal cell carcinoma 0/50 0/50 0/50 4/50a

Peritoneal mesothelioma 2/50 4/50 14/50c41/50a,c

Mammary gland fibroadenoma 1/50 2/50 3/50 5/50d

Mammary gland adenoma 0/50 0/50 0/50 1/50

Zymbal gland adenoma 0/50 0/50 0/50 4/50a

Subcutis fibroma 1/50 4/50 9/50c5/50

a

Statistically significant trend for increased tumor incidence by Peto‘s test (p ≤ 0.01).

bTumor incidence significantly elevated compared with that in controls by Fisher‘s exact test (p ≤ 0.05).

cTumor 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 12/23/2008 (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

9 Human equivalent doses (HEDs) were calculated from the administered animal doses 

using a BW scaling factor (BW0.75 10 ). This was accomplished using the following equation:

0.25

human BW (kg)

animal BW (kg)

11

HED animal dose (mg/kg)

12 For all calculations, a human BW of 70 kg was used. HEDs for the principal study (Kano, et al., 

13 2009) are given in Table 5-11. HEDs were also calculated for supporting studies (Kociba, et al., 

14 1974; NCI, 1978) and are also shown in Table 5-11.
131

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table 5-11. Calculated HEDs for the tumor incidence data used for doseresponse modeling

Study Species/strain/gender

Animal BW (g)

TWA

Animal dose 

(mg/kg-day)

HED

(mg/kg-day)d

Kano et al. (2009) Male F344/DuCrj rats 432a11 3.1

432a81 23

432a398 112

Female F344/DuCrj rats 267a18 4.5

267a83 21

267a429 107

Male Crj:BDF1 mice 47.9a49 7.9

47.9a191 31

47.9a677 110

Female Crj:BDF1 mice 35.9a66 10

35.9a278 42

35.9a964 145

Kociba et al. (1974) Male and female (combined) 

Sherman rats 

325b14 3.7

325b121 32

285c1,307 330

NCI (1978) Male Osborne-Mendel rats 470b240 69

470b530 152

Female Osborne-Mendel rats 310b350 90

310b640 165

Male B6C3F1 mice 32b720 105

32b830 121

Female B6C3F1 mice 30b380 55

30b860 124

a TWA BWs were determined from BW growth curves provided for each species and gender.

bTWA BWs were determined from BW curve provided for control animals.

cBWs 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).

dHEDs are calculated as HED = (animal dose) × (animal BW / human BW)0.25

.

Sources: Kano et al. (2009); Kociba et al. (1974); and NCI (1978).

1 The U.S. EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a)

2 recommend that the method used to characterize and quantify cancer risk from a chemical is 

3 determined by what is known about the mode of action of the carcinogen and the shape of the 

4 cancer dose-response curve. The linear approach is recommended if the mode of action of 

5 carcinogenicity is not understood (U.S. EPA, 2005a). In the case of 1,4-dioxane, the mode of 

6 carcinogenic action for peritoneal, mammary, nasal, and liver tumors is unknown. Therefore, a 

7 linear low-dose extrapolation approach was used to estimate human carcinogenic risk associated 

8 with 1,4-dioxane exposure.
132

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 However, several of the external peer review panel members (Appendix A: Summary of 

2 External Peer Review and Public Comments and Disposition) recommended that the mode of 

3 action data support the use of a nonlinear extrapolation approach to estimate human carcinogenic 

4 risk associated with exposure to 1,4-dioxane and that such an approach should be presented in 

5 the Toxicological Review. As discussed in Section 4.7.3., numerous short-term in vitro and a 

6 few in vivo tests were nonpositive for 1,4-dioxane-induced genotoxicity. Results from two-stage 

7 mouse skin tumor bioassays demonstrated that 1,4-dioxane does not initiate mouse skin tumors, 

8 but it is a promoter of skin tumors initiated by DMBA (King, et al., 1973). These data suggest 

9 that a potential mode of action for 1,4-dioxane-induced tumors may involve proliferation of cells 

10 initiated spontaneously, or by some other agent, to become tumors (Bull, et al., 1986; 

11 Goldsworthy, et al., 1991; King, et al., 1973; Lundberg, et al., 1987; Miyagawa, et al., 1999; 

12 Stott, et al., 1981; Uno, et al., 1994). However, key events related to the promotion of tumor 

13 formation by 1,4-dioxane are unknown. Therefore, under the U.S. EPA Guidelines for 

14 Carcinogen Risk Assessment (U.S. EPA, 2005a), EPA concluded that the available information 

15 does not establish a plausible mode of action for 1,4-dioxane and data are insufficient to establish 

16 significant biological support for a nonlinear approach. EPA determined that there are no data 

17 available to inform the low-dose region of the dose response, and thus, a nonlinear approach was 

18 not included.

19 Accordingly, the CSF for 1,4-dioxane was derived via a linear extrapolation from the 

20 POD calculated by curve fitting the experimental dose-response data. The POD is the 95% 

21 lower confidence limit on the dose associated with a benchmark response (BMR) near the lower 

22 end of the observed data. The BMD modeling analysis used to estimate the POD is described in 

23 detail in Appendix D and is summarized below in Section 5.4.4.

24 Model estimates were derived for all available bioassays and tumor endpoints (Appendix 

25 D); however, the POD used to derive the CSF is based on the most sensitive species and target 

26 organ in the principal study (Kano, et al., 2009). 

27 The oral CSF was calculated using the following equation:

BMDL

BMR

28

CSF

5.4.3.2. Inhalation

29 In accordance with the U.S. EPA (1994b) RfC methodology, the HEC values for the 

30 various tumors were calculated by the application of DAFs. As discussed in Section 5.2.3. since 

31 1,4-dioxane is miscible with water, has a high partition coefficient, and systemic and portal of 

32 entry effects are observed, a DAF of 1.0 was applied. The lifetime continuous inhalation risk for 

33 humans is defined as the slope of the line from the POD, the lower 95% bound on the exposure 

34 associated with a level of extra risk near the low end of the data range. 
133

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 All PODs were converted to equivalent continuous exposure levels by multiplying by [(6 

2 hours)/(24 hours)] ×[(5 days)/(7 days)], or 0/178, under the assumption of equal cumulative 

3 exposures leading to equivalent outcomes. 

4 Given the multiplicity of tumor sites, basing the IUR on one tumor site may 

5 underestimate the carcinogenic potential of 1,4-dioxane. Simply pooling the counts of animals 

6 with one or more tumors (i.e., counts of tumor bearing animals) would tend to underestimate the 

7 overall risk when tumors are independent across sites and ignores potential differences in the 

8 dose-response relationships across the sites (Bogen, 1990; Spurgeon, Hopkin, & Jones, 1994). 

9 NRC (1994) also noted that the assumption of independence across tumor types is not likely to 

10 produce substantial error in the risk estimates unless tumors are known to be biologically 

11 dependent.

12 Kopylev et al. (2009) describe a Markov Chain Monte Caro (MCMC) computational 

13 approach to calculating the dose associated with a specified composite risk under assumption of 

14 independence of tumors. The Guidelines for Carcinogen Risk Assessment recommend 

15 calculation of an upper bound to account for uncertainty in the estimate (U.S. EPA, 2005a). For 

16 uncertainty characterization, MCMC methods have the advantage of providing information about 

17 the full distribution of risk and/or benchmark dose, which can be used in generating a confidence 

18 bound. This MCMC approach building on the re-sampling approach recommended by Bogen 

19 (1990), which also provides a distribution of the combined potency across sites. The Bayesian 

20 MCMC computations were conducted using WinBugs (Spiegelhalter, Thomas, & Best, 2003)

21 and additional details of this analysis are included in Appendix G. In addition, the best fitting 

22 BMDS multistage model was determined for each individual tumor type as shown in Section 

23 5.4.4.2 and Appendix G. 

24 IUR estimates based were calculated using the following equation:

25 IUR = BMR / HEC

5.4.4. Oral Slope Factor and Inhalation Unit Risk

5.4.4.1. Oral Slope Factor 

26 The dichotomous models available in the Benchmark Dose Software (BMDS, version 

27 2.1.1) were fit to the incidence data for ―either hepatocellular carcinoma or adenoma‖ in rats and 

28 mice, as well as mammary and peritoneal tumors in rats exposed to 1,4-dioxane in the drinking 

29 water (Kano, et al., 2009; Kociba, et al., 1974; NCI, 1978) (Table 5-7). Animal doses are used 

30 for BMD modeling and HED BMD and BMDL values are calculated using the animal TWAs 

31 (Table 5-12) and a human BW of 70kg. Doses associated with a BMR of 10% extra risk were 

32 calculated. BMDs and BMDLs from all models are reported, and the output and plots 

33 corresponding to the best-fitting model are shown (Appendix D). When the best-fitting model is 

34 not a multistage model, the multistage model output and plot are also provided (Appendix D). A 
134

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 summary of the BMDS model predictions for the Kano et al. (2009), NCI (1978), and Kociba 

2 et al. (1974) studies is shown in Table 5-12. 

Table 5-12. BMD HED and BMDLHED values from models fit to tumor 

incidence data for rats and mice exposed to 1,4-dioxane in drinking water for 

2 years and corresponding oral CSFs

Study Gender/strain/species Tumor type

BMDHED

a

(mg/kg-day)

BMDLHED

a

(mg/kgday)Oral CSF

(mg/kg-day)-1

Kano et al.

(2009)

Male F344/DuCrj ratsb Hepatocellular 

adenoma or 

carcinoma

17.43 14.33 7.0 x 10-3

Female F344/DuCrj ratsc19.84 14.43 6.9 x 10-3

Male Crj:BDF1 miced5.63 2.68 3.7 x 10-2

Female Crj:BDF1 miced0.83 0.55 0.18

Female Crj:BDF1 miced, e 3.22e2.12e0.14

Female Crj:BDF1 miced, f 7.51f4.95f0.10

Female F344/DuCrj ratsg Nasal 

squamous cell 

carcinoma

94.84 70.23 1.4 x 10-3

Male F344/DuCrj ratsg91.97 68.85 1.5 x 10-3

Male F344/DuCrj ratsbPeritoneal 

mesothelioma

26.09 21.39 4.7 x 10-3

Female F344/DuCrj ratsd Mammary 

gland 

adenoma

40.01 20.35 4.9 x 10-3

Kociba et al.

(1974)

Male and female (combined) 

Sherman ratsg

Nasal 

squamous cell 

carcinomas

448.24 340.99 2.9 x 10-4

Male and female (combined) 

Sherman ratsb

Hepatocellular 

carcinoma

290.78 240.31 4.2 x 10-4

NCI (1978) Male Osborne Mendel ratsd Nasal 

squamous cell 

carcinomas

16.10 10.66 9.4 x 10-3

Female Osborne Mendel ratsd40.07 25.82 3.9 x 10-3

Female Osborne Mendel ratsd Hepatocellular 

adenoma

28.75 18.68 5.4 x 10-3

Female B6C3F1 micec Hepatocellular 

adenoma or 

carcinoma

23.12 9.75 1.0 x 10-2

Male B6C3F1 miceh87.98 35.67 2.8 x 10-3

aValues associated with a BMR of 10% unless otherwise noted.

b

Probit model, slope parameter not restricted.

cMultistage model, degree of polynomial = 2.

dLog-logistic model, slope restricted ≥ 1.

eValues associated with a BMR of 30%.

fValues associated with a BMR of 50%.

gMultistage model, degree of polynomial =3.

hGamma model.

3 The multistage model did not provide an adequate fit (as determined by AIC, p-value 

< 0.1, and χ24 p > |0.1|) to the data for the incidence of hepatocellular adenoma or carcinoma in 

5 female mice (Appendix D). The high dose was dropped for the female mouse liver tumor dataset 

6 in an attempt to achieve an adequate fit; however, an adequate fit was still not achieved. 
135

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Because the female mice were clearly the most sensitive group tested, other BMD models were 

2 applied to the female mouse liver tumor dataset to achieve an adequate fit. The log-logistic 

3 model was the only model that provided adequate fit for this data set due to the steep rise in the 

4 dose-response curve (70% incidence at the low dose) followed by a plateau at near maximal 

5 tumor incidence in the mid- and high-dose regions (82 and 92% incidence, respectively). The 

6 predicted BMD10 and BMDL10 for the female mouse data are presented in Table 5-12, as well as 

7 BMDHED and BMDLHED values associated with BMRs of 30 and 50% . 

8 The multistage model also did not provide an adequate fit to mammary tumor incidence 

9 data for the female rat or male rat peritoneal tumors. The predicted BMD10 and BMDL10 for 

10 female rat mammary tumors and male peritoneal tumors obtained from the log-logistic and 

11 probit models, respectively, are presented in Table 5-12.

12 A comparison of the model estimates derived for rats and mice from the Kano et al. 

13 (2009), NCI (1978), and Kociba et al. (1974) studies (Table 5-12) indicates that female mice are 

14 more sensitive to liver carcinogenicity induced by 1,4-dioxane compared to other species or 

15 tumor types. The BMDL50 HED for the female mouse data was chosen as the POD and the CSF of 

0.10 (mg/kg-day)-116 was calculated as follows:

-1

50 HED

0.10 (mg/kg - day)

4.95 mg/kg - day (BMDL for female mice)

0.50

17

CSF

18 Calculation of a CSF for 1,4-dioxane is based upon the dose-response data for the most 

19 sensitive species and gender.

5.4.4.2. Inhalation Unit Risk 

20 Inhalation unit risk estimates were based on the multiple carcinogenic effects of 

21 1,4-dioxane observed in rats via the inhalation route.

22 The multistage cancer models available in the Benchmark Dose Software (BMDS, 

23 version 2.1.1) were fit to the incidence data for each tumor type observed in rats exposed to 

1,4-dioxane via inhalation (Kasai, et al., 2009) to determine the degree (e.g., 1st, 2nd, or 3rd 24 ) of the 

25 multistage model that best fit the data (details in Appendix G). A Bayesian MCMC analysis was 

26 performed using WinBUGS to calculate the total tumor risk. For comparative purposes only, a 

27 total tumor analysis was also performed with the BMDS (version 2.2Beta) MSCombo model and 

28 yielded similar results (See Appendix G). MSCombo is a new addition to BMDS that allows for 

29 multi-tumor analysis. A summary of the BMDS model predictions for the Kasai et al. (2009)

30 study is shown in Table 5-13. Animal exposure concentrations were used for BMD modeling 

31 and continuous human equivalent exposures were calculated by adjusting for duration of 

32 exposure (Table 5-13) and applying an appropriate DAF (see Section 5.2.3). In accordance with 

33 the U.S. EPA (2005a) Cancer Guidelines, the BMCL10 (lower bound on the concentration 

34 estimated to produce a 10% increase in tumor incidence over background) was estimated for the 

35 dichotomous incidence data and the results of the model that best characterized the cancer 
136

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 incidences were selected. BMCs and BMCLs from all models are reported, and the output and 

2 plots corresponding to the best-fitting model are shown (Appendix G). 

3 The IUR estimates are provided in Table 5-13. Human equivalent risks estimated from 

the individual rat tumor sites ranged from 1.5 × 10-7to 2.4 × 10-6(μg/m3)

-1

4 (or rounded to one 

significant figure, 2 × 10-7to 2 × 10-6(μg/m3)

-1

). The highest IUR (2.4 × 10-6(μg/m3)

-1

5 ) 

corresponded to peritoneal mesotheliomas in male rats, and the lowest IUR (1.5 × 10-7(μg/m3)

-1

6 ) 

7 corresponded to renal cell carcinoma and Zymbal gland adenomas in male rats. 

Table 5-13. Dose-response modeling summary results for male rat tumors 

associated with inhalation exposure to 1,4-dioxane for 2 years

Tumor Typea

Multistage 

Model 

Degreeb

Point of Departurec

IUR 

Estimatee

(μg/m3)

-1

Bioassay Exposure 

Concentration (ppm)

HEC 

(mg/m3)

d

BMC10 BMCL10 BMC10 BMCL10

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 Analysisf39.2 31.4 25.2 20.2 5.0 × 10-6

aTumor incidence data from Kasai et al. (2009).

bBest-fitting multistage model degree (p>0.1, lowest AIC). See Appendix G for modeling details.

cBMC = Concentration at specified extra risk (benchmark dose); BMCL = 95% lower bound on concentration at 

specified extra risk.

dHuman continuous equivalent estimated by multiplying exposures by [(6 hours)/(24 hours) × (5 days)/(7 days) x 

molecular weight of 1,4-dioxane]/ 24.45.

eThe inhalation unit risk (μg/m3

)

-1 was derived from the BMCL10, the 95% lower bound on the concentration 

associated with a 10% extra cancer risk. Specifically, by dividing the BMR (0.10) by the BMCL10. Thus, 

representing an upper bound, continuous lifetime exposure estimate of cancer potency.

fResults in this table are from the Bayesian analysis using WinBUGS. Additionally, for comparative purposes only, 

total tumor analysis was performed with the draft BMDS (version 2.2Beta) MSCombo model and yielded similar 

results (See Appendix G).

8 Given the multiplicity of tumor sites, basing the inhalation unit risk on one tumor site 

9 may underestimate the carcinogenic potential of 1,4-dioxane. Consistent with recommendations 

10 of the NRC (1994) and the current Guidelines for Carcinogen Risk Assessment (U.S. EPA, 

11 2005a) for the assessment of total risk, and upper bound risk for all tumor sites in male F344 rats 

12 was estimated. This estimate of total risk describes the risk of developing any combination of 

13 the tumor types considered, not just the risk of developing all simultaneously. As shown in 

14 Table 5-13, the resulting total inhalation unit risk for all tumor types for male F344 rats was 5 × 

10-6(μg/m3)

-1

15 . Overall, the consideration of the other tumor sites approximately doubled the unit 
137

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

risk compared to the highest unit risk associated with any individual tumor type, 2 × 10-61

(μg/m3)

-1

2 for male peritoneal mesotheliomas.

3 The HEC BMCL10 for the male rat combined tumor estimate was chosen as the POD and 

the IUR of 5 × 10-6(μg/m3)

-1

4 was calculated as follows:

3 -1 6 3 -1

6 3 -1

3

3 -1 3 -1

3 -1

3

3 -1

IUR ( g/m ) 5 10 ( g/m )

5 10 ( g/m )

10 mg

1 g

IUR ( g/m ) 0.005 (mg/m )

0.005 (mg/m )

20.2 mg/m

0.10 IUR (mg/m )

μ μ

μ

μ

5

μ

6 Based on the analysis discussed above, the recommended upper bound estimate on 

human extra cancer risk from continuous lifetime exposure to 1,4-dioxane is 5 × 10-6(μg/m3)

-1

7 . 

8 The recommended unit risk estimate reflects the exposure-response relationships for the multiple 

9 tumor sites in male F344 rats.

5.4.5. Previous Cancer Assessment

10 A previous cancer assessment was posted for 1,4-dioxane on IRIS in 1988. 1,4-Dioxane 

11 was classified as a Group B2 Carcinogen (probable human carcinogen; sufficient evidence from 

12 animal studies and inadequate evidence or no data from human epidemiology studies (U.S. EPA, 

13 1986a)) based on the induction of nasal cavity and liver carcinomas in multiple strains of rats, 

14 liver carcinomas in mice, and gall bladder carcinomas in guinea pigs. An oral CSF of 0.011 

(mg/kg-day)-115 was derived from the tumor incidence data for nasal squamous cell carcinoma in 

16 male rats exposed to 1,4-dioxane in drinking water for 2 years (NCI, 1978). The linearized 

17 multistage extra risk procedure was used for linear low dose extrapolation. An inhalation unit 

18 risk was not previously derived.

5.5. UNCERTAINTIES IN CANCER RISK VALUES

19 As in most risk assessments, extrapolation of study data to estimate potential risks to 

20 human populations from exposure to 1,4-dioxane has engendered some uncertainty in the results. 

21 Several types of uncertainty may be considered quantitatively, but other important uncertainties 

22 cannot be considered quantitatively. Thus an overall integrated quantitative uncertainty analysis 

23 is not presented. In addition, the use of the assumptions, particularly those underlying the 

24 Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a) is explained and the decision 

25 concerning the preferred approach is given and justified. Principal uncertainties are summarized 

26 below and in Table 5-14.
138

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

5.5.1. Sources of Uncertainty

5.5.1.1. Choice of Low-Dose Extrapolation Approach

1 The range of possibilities for the low-dose extrapolation of tumor risk for exposure to 

2 1,4-dioxane, or any chemical, ranges from linear to nonlinear, but is dependent upon a plausible 

3 MOA(s) for the observed tumors. The MOA is a key consideration in clarifying how risks 

4 should be estimated for low-dose exposure. Exposure to 1,4-dioxane has been observed in 

5 animal models to induce multiple tumor types, including liver adenomas and carcinomas, nasal 

6 carcinomas, mammary adenomas and fibroadenomas, and mesotheliomas of the peritoneal cavity 

7 (JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978). MOA 

8 information that is available for the carcinogenicity of 1,4-dioxane has largely focused on liver 

9 adenomas and carcinomas, with little or no MOA information available for the remaining tumor 

10 types. In Section 4.7.3, hypothesized MOAs were explored for 1,4-dioxane. Information that 

11 would provide sufficient support for any MOA is not available. In the absence of a MOA(s) for 

12 the observed tumor types, a linear low-dose extrapolation approach was used to estimate human 

13 carcinogenic risk associated with 1,4-dioxane exposure. 

14 It is not possible to predict how additional MOA information would impact the dose15 response assessment for 1,4-dioxane because of the variety of tumors observed and the lack of 

16 data on how 1,4-dioxane or a metabolite thereof, interacts with cells starting the progression to 

17 the observed tumors.

18 In general, the Agency has preferred to use the multistage model for analyses of tumor 

19 incidence and related endpoints because they have a generic biological motivation based on 

20 long-established mathematical models such as the Moolgavkar-Venzon-Knudsen (MVK) model. 

21 The MVK model does not necessarily characterize all modes of tumor formation, but it is 

22 a starting point for most investigations and, much more often than not, has provided at least an 

23 adequate description of tumor incidence data.

24 The multistage cancer model provided good fits for the tumor incidence data following a 

25 2-year inhalation exposure to 1,4-dioxane by male rats (Kasai, et al., 2009). However, in the 

26 studies evaluated for the oral cancer assessment (Kano, et al., 2009; Kociba, et al., 1974; NCI, 

27 1978), the multistage model provided good descriptions of the incidence of a few tumor types in 

28 male (nasal cavity) and female (hepatocellular and nasal cavity) rats and in male mice 

29 (hepatocellular) exposed to 1,4-dioxane (Appendix D for details). The multistage model did not 

30 provide an adequate fit for the female mouse liver tumor dataset based upon the following (U.S. 

31 EPA, 2000a):

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 their χ2residuals (values were 

greater than an absolute value of one).

1 BMDS software typically implements the guidance in the external peer review draft 

2 BMD technical guidance document (U.S. EPA, 2000a) by imposing constraints on the values of 

3 certain parameters of the models. When these constraints were imposed, the multistage model 

4 and most other models did not fit the incidence data for female mouse liver adenomas or 

5 carcinomas. 

6 The log-logistic model was selected because it provides an adequate fit for the female 

7 mouse data (Kano, et al., 2009). A BMR of 50% was used because it is proximate to the 

8 response at the lowest dose tested and the BMDL50 HED was derived by applying appropriate 

9 parameter constraints, consistent with recommended use of BMDS in the BMD technical 

10 guidance document (U.S. EPA, 2000a).

11 The human equivalent oral CSFs estimated from tumor datasets with statistically 

significant increases ranged from 4.2 × 10-412 to 0.18 per mg/kg-day (Table 5-12), a range of about 

13 three orders of magnitude, with the extremes coming from the combined male and female rat 

14 data for hepatocellular carcinomas (Kociba, et al., 1974) and the female mouse combined liver 

15 adenoma and carcinomas (Kano, et al., 2009).

5.5.1.2. Dose Metric 

16 1,4-Dioxane is known to be metabolized in vivo. However, it is unknown whether a 

17 metabolite or the parent compound, or some combination of parent compound and metabolites, is 

18 responsible for the observed toxicity. If the actual carcinogenic moiety is proportional to 

19 administered exposure, then use of administered exposure as the dose metric is the least biased 

20 choice. On the other hand, if this is not the correct dose metric, then the impact on the CSF is 

21 unknown.

5.5.1.3. Cross-Species Scaling 

For the oral cancer assessment, an adjustment for cross-species scaling (BW0.75 22 ) was 

23 applied to address toxicological equivalence of internal doses between each rodent species and 

24 humans, consistent with the 2005 Guidelines for Carcinogen Risk Assessment (U.S. EPA, 

25 2005a). It is assumed that equal risks result from equivalent constant lifetime exposures.

26 Differences in the anatomy of the upper respiratory tract and resulting differences in 

27 absorption or in local respiratory system effects are sources of uncertainty in the inhalation 

28 cancer assessment. 

5.5.1.4. Statistical Uncertainty at the POD 

29 Parameter uncertainty can be assessed through confidence intervals. Each description of 

30 parameter uncertainty assumes that the underlying model and associated assumptions are valid. 

31 For the log-logistic model applied to the female mouse data following oral exposure, there is a 
140

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 reasonably small degree of uncertainty at the 10% excess incidence level (the POD for linear 

2 low-dose extrapolation). For the multistage model applied for the male rat inhalation dataset, 

3 there is a reasonable small degree of uncertainty at the 10% extra risk level (the POD for linear 

4 low-dose extrapolation). 

5.5.1.5. Bioassay Selection 

5 The study by Kano et al. (2009) was used for development of an oral CSF. This was a 

6 well-designed study, conducted in both sexes in two species (rats and mice) with a sufficient 

7 number (N=50) of animals per dose group. The number of test animals allocated among three 

8 dose levels and an untreated control group was adequate, with examination of appropriate 

9 toxicological endpoints in both sexes of rats and mice. Alternative bioassays (Kociba, et al., 

10 1974; NCI, 1978) were available and were fully considered for the derivation of the oral CSF.

11 The study by Kasai et al. (2009) was used for derivation of an inhalation unit risk. This 

12 was a well-designed and peer reviewed study, conducted in male rats with a sufficient number 

13 (N=50) of animals per dose group. Three dose levels plus an untreated control group were 

14 examined following exposure to 1,4-dioxane via inhalation for 2 years. Other bioassays (Kasai, 

15 et al., 2008; Torkelson, et al., 1974) were available and were considered for the derivation of the 

16 inhalation unit risk. 

5.5.1.6. Choice of Species/Gender 

17 The oral CSF for 1,4-dioxane was quantified using the tumor incidence data for the 

18 female mouse, which was shown to be more sensitive than male mice or either sex of rats to the 

19 carcinogenicity of 1,4-dioxane. While all data, both species and sexes reported from the Kano 

20 et al. (2009) study, were suitable for deriving an oral CSF, the female mouse data represented the 

21 most sensitive indicator of carcinogenicity in the rodent model. The lowest exposure level 

22 (66 mg/kg-day or 10 mg/kg-day [HED]) resulted in a considerable and significant increase in 

23 combined liver adenomas and carcinomas observed. Additional testing of doses within the range 

24 of control and the lowest dose (66 mg/kg-day or 10 mg/kg-day [HED]) could refine and reduce 

25 uncertainty for the oral CSF. 

26 A personal communication from Dr. Yamazaki (2006) provided that the survival of mice 

27 was particularly low in high-dose females (29/50, 29/50, 17/50, and 5/50 in control, low-, mid-, 

28 and high-dose groups, respectively). These deaths occurred primarily during the second year of 

29 the study. Female mouse survival at 12 months was 50/50, 50/50, 48/50, and 48/50 in control, 

30 low-, mid-, and high-dose groups, respectively (Yamazaki, 2006). Furthermore, these deaths 

31 were primarily tumor related. Liver tumors were listed as the cause of death for 1/21, 2/21, 8/33, 

32 and 31/45 of the pretermination deaths in control, low-, mid- and, high-dose female Crj:BDF1

33 mice (Yamazaki, 2006). Therefore, because a number of the deaths in female mice were

34 attributed to liver tumors, this endpoint and species was still considered to be relevant for this 

35 analysis; however, the high mortality rate does contribute uncertainty.
141

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Additionally, the incidence of hepatocellular adenomas and carcinomas in historical 

2 controls was evaluated with the data from Kano et al. (2009). Katagiri et al. (1998) summarized 

3 the incidence of hepatocellular adenomas and carcinomas in control male and female BDF1 mice 

4 from ten 2-year bioassays at the JBRC. For female mice, out of 499 control mice, the incidence 

5 rates were 4.4% for hepatocellular adenomas and 2.0% for hepatocellular carcinomas. Kano et 

6 al. (2009) reported a 10% incidence rate for hepatocellular adenomas and a 0% incidence rate for 

7 hepatocellular carcinomas in control female BDF1. These incidence rates are near the historical 

8 control values and thus are appropriate for consideration in this assessment.

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 studies in the 2-year 

12 bioassay conducted by the same laboratory (Kasai, et al., 2009).

5.5.1.7. Relevance to Humans 

13 The derivation of the oral CSF is derived using the tumor incidence in the liver of female 

14 mice. A thorough review of the available toxicological data available for 1,4-dioxane provides 

15 no scientific justification to propose that the liver adenomas and carcinomas observed in animal 

16 models due to exposure to 1,4-dioxane are not relevant to humans. As such, liver adenomas and 

17 carcinomas were considered relevant to 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 adjustment for 

21 differences in sensitivity among rodents and humans.

5.5.1.8. Human Population Variability 

22 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 are unavailable. This lack of understanding about potential differences in 

26 metabolism and susceptibility across exposed human 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.
142

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table 5-14. 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 lowdose 

extrapolation 

from POD 

A linear low-dose extrapolation approach was used 

to estimate human carcinogenic risk associated 

with 1,4-dioxane exposure. Where data are 

insufficient to ascertain the MOA, EPA‘s 2005 

Guidelines for Carcinogen Risk Assessment 

recommend application of a linear low-dose 

extrapolation approach. 

Dose metric Alternatives could ↑ 

or ↓ CSF by an 

unknown extent

Used 

administered 

exposure

Experimental evidence supports a role for 

metabolism in toxicity, but it is unclear if the 

parent compound, metabolite or both contribute to 

1,4-dioxane toxicity.

Cross-species 

scaling 

Alternatives could ↓ 

or ↑ CSF [e.g., 3.5-

fold ↓ (scaling by 

BW) or ↑ twofold 

(scaling by BW0.67 )]

BW0.75 (default 

approach)

There are no data to support alternatives. BW0.75

scaling was used to calculate equivalent 

cumulative exposures for estimating equivalent 

human risks. PBPK modeling was conducted but 

not deemed suitable for interspecies extrapolation. 

Bioassay Alternatives could ↑ 

or ↓ 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 studies is considered 

relevant to human exposure.

Human 

population 

variability in 

metabolism 

and response/ 

sensitive 

subpopulations

Low-dose risk ↑ or ↓ 

to an unknown extent

Considered 

qualitatively

No data to support range of human 

variability/sensitivity, including whether children 

are more sensitive. 
143

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE 

RESPONSE

6.1. HUMAN HAZARD POTENTIAL

1 1,4-Dioxane is absorbed rapidly following oral and inhalation exposure, with much less 

2 absorption occurring from the dermal route. 1,4-Dioxane is primarily metabolized to HEAA, 

3 which is excreted in the urine. Liver, kidney, and nasal toxicity are the primary noncancer health 

4 effects associated with exposure to 1,4-dioxane in humans and laboratory animals. Several fatal 

5 cases of hemorrhagic nephritis and centrilobular necrosis of the liver were related to 

6 occupational exposure (i.e., inhalation and dermal contact) to 1,4-dioxane (Barber, 1934; 

7 Johnstone, 1959). Neurological changes were also reported in one case, including headache, 

8 elevation in blood pressure, agitation and restlessness, and coma (Johnstone, 1959). Perivascular 

9 widening was observed in the brain of this worker, with small foci of demyelination in several 

10 regions (e.g., cortex, basal nuclei). Severe liver and kidney degeneration and necrosis were 

11 observed frequently in acute oral and inhalation studies (≥ 1,000 mg/kg-day oral, ≥ 1,000 ppm 

12 inhalation) (David, 1964; de Navasquez, 1935; Drew, et al., 1978; Fairley, et al., 1934; JBRC, 

13 1998; Kesten, et al., 1939; Laug, et al., 1939; Schrenk & Yant, 1936).

14 Liver and kidney toxicity were the primary noncancer health effects of subchronic and 

15 chronic oral exposure to 1,4-dioxane in animals. Hepatocellular degeneration and necrosis were 

16 observed (Kociba, et al., 1974) and preneoplastic changes were noted in the liver following 

17 chronic administration of 1,4-dioxane in drinking water (Argus, et al., 1973; JBRC, 1998; Kano, 

18 et al., 2009). Liver and kidney toxicity appear to be related to saturation of clearance pathways 

19 and an increase in the 1,4-dioxane concentration in the blood (Kociba, et al., 1974). Kidney 

20 damage was characterized by degeneration of the cortical tubule cells, necrosis with hemorrhage, 

21 and glomerulonephritis (Argus, et al., 1965; Argus, et al., 1973; Fairley, et al., 1934; Kociba, et 

22 al., 1974; NCI, 1978). In chronic inhalation studies conducted in rats, nasal and liver toxicity 

23 were the primary noncancer health effects. Degeneration of nasal tissue (i.e. metaplasia, 

24 hyperplasia, atrophy, hydropic change, and vacuolic change ) and preneoplastic cell proliferation 

25 were observed in the nasal cavity following 2 years of 1,4-dioxane exposure via inhalation 

26 (Kasai, et al., 2009). Liver toxicity was described as necrosis of the centrilobular region and 

27 preneoplastic changes were noted as well.

28 Several carcinogenicity bioassays have been conducted for 1,4-dioxane in mice, rats, and 

29 guinea pigs (Argus, et al., 1965; Argus, et al., 1973; Hoch-Ligeti & Argus, 1970; Hoch-Ligeti, et 

30 al., 1970; JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978; 

 

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

1 Torkelson, et al., 1974). Liver tumors (hepatocellular adenomas and carcinomas) have been 

2 observed following drinking water exposure in several species and strains of rats, mice, and 

3 guinea pigs and following inhalation exposure in rats. Nasal (squamous cell carcinomas), 

4 peritoneal, mammary, Zymbal gland, and subcutaneous tumors were also observed in rats, but 

5 were not seen in mice. With the exception of the NCI (1978) study, the incidence of nasal cavity 

6 tumors was generally lower than that of tumors observed in other tissues of the same study 

7 population.

8 Under the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), 1,4-dioxane is 

9 ―likely to be carcinogenic to humans‖ based on evidence of multiple tissue carcinogenicity in 

10 several 2-year bioassays conducted in three strains of rats, two strains of mice, and in guinea pigs 

11 (Argus, et al., 1965; Argus, et al., 1973; Hoch-Ligeti & Argus, 1970; Hoch-Ligeti, et al., 1970; 

12 JBRC, 1998; Kano, et al., 2009; Kasai, et al., 2009; Kociba, et al., 1974; NCI, 1978). Studies in 

13 humans found no conclusive evidence for a causal link between occupational exposure to 

14 1,4-dioxane and increased risk for cancer; however, only two studies were available and these 

15 were limited by small cohort size and a small number of reported cancer cases (Buffler, et al., 

16 1978; Thiess, et al., 1976).

17 The available evidence is inadequate to establish a MOA by which 1,4-dioxane induces 

18 tumors in rats and mice. The genotoxicity data for 1,4-dioxane is generally characterized as 

19 negative, although several studies may suggest the possibility of genotoxic effects (Galloway, et 

20 al., 1987; Kitchin & Brown, 1990; Mirkova, 1994; Morita & Hayashi, 1998; Roy, et al., 2005). 

21 A MOA hypothesis for liver tumors involving sustained proliferation of spontaneously 

22 transformed liver cells has some support by evidence that suggests 1,4-dioxane is a tumor 

23 promoter in mouse skin and rat liver bioassays (King, et al., 1973; Lundberg, et al., 1987). Some 

24 dose-response and temporal evidence support the occurrence of cell proliferation and hyperplasia 

25 prior to the development of liver tumors (JBRC, 1998; Kociba, et al., 1974). However, the dose26 response relationship for the induction of hepatic cell proliferation has not been characterized, 

27 and it is unknown if it would reflect the dose-response relationship for liver tumors in the 2-year 

28 rat and mouse studies. Conflicting data from rat and mouse bioassays (JBRC, 1998; Kociba, et 

29 al., 1974) suggest that cytotoxicity is not a required precursor event for 1,4-dioxane-induced cell 

30 proliferation. Liver tumors were observed in female rats and female mice in the absence of 

31 lesions indicative of cytotoxicity (JBRC, 1998; Kano, et al., 2009; NCI, 1978). Data regarding a 

32 plausible dose response and temporal progression from cytotoxicity to cell proliferation and 

33 eventual liver tumor formation are not available. Hypothesized MOAs by which 1,4-dioxane 

34 induces tumors in other organ systems such as the respiratory system are uncertain (See Section 

35 4.7.3).
145

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

6.2. DOSE RESPONSE

6.2.1. Noncancer/Oral

The RfD of 3 × 10-21 mg/kg-day was derived based on liver and kidney toxicity in rats 

2 exposed to 1,4-dioxane in the drinking water for 2 years (Kociba, et al., 1974). This study was 

3 chosen as the principal study because it provides the most sensitive measure of adverse effects 

4 by 1,4-dioxane. The incidence of liver and kidney lesions was not reported for each dose group. 

5 Therefore, BMD modeling could not be used to derive a POD. Instead, the RfD is derived by 

6 dividing the NOAEL of 9.6 mg/kg-day by a composite UF of 300 (factors of 10 for animal-to7 human extrapolation and interindividual variability, and an UF of 3 for database deficiencies). 

8 Information was unavailable to quantitatively assess toxicokinetic or toxicodynamic differences 

9 between animals and humans and the potential variability in human susceptibility; thus, the 

10 interspecies and intraspecies uncertainty factors of 10 were applied. In addition, a threefold 

11 database uncertainty factor was applied due to the lack of information addressing the potential 

12 reproductive toxicity associated with 1,4-dioxane. 

13 The overall confidence in the RfD is medium. Confidence in the principal study (Kociba, 

14 et al., 1974) is medium. Confidence in the database is medium due to the lack of a 

15 multigeneration reproductive toxicity study. Reflecting medium confidence in the principal 

16 study and medium confidence in the database, confidence in the RfD is medium.

6.2.2. Noncancer/Inhalation

The RfC of 3 × 10-2 mg/m317 was derived based on olfactory epithelium atrophy in rats 

18 exposed for 2 years to 1,4-dioxane via inhalation (Kasai, et al., 2009). This study was chosen as 

19 the principal study because it provides the adequate study design and most sensitive measure of 

20 adverse effects by 1,4-dioxane. The POD was derived using the LOAEL for olfactory atrophy in 

21 male rats from the Kasai et al. (2009) study. A composite UF of 1000 was applied, consisting 

22 of factors of 10 for a LOAEL-to NOAEL extrapolation and for interindividual variability, and 3

23 for animal-to-human extrapolation and for database deficiencies. 

24 The overall confidence in the RfC is medium. Confidence in the principal study (Kasai, 

25 et al., 2009) is medium. Confidence in the database is medium due to the lack of supporting 

26 studies and a multigeneration reproductive toxicity study. Reflecting medium confidence in the 

27 principal study and medium confidence in the database, the confidence in the RfC is medium.

6.2.3. Cancer

28 Under EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), 

29 1,4-dioxane is ―likely to be carcinogenic to humans‖ by all routes of exposure. This descriptor is 

30 based on evidence of carcinogenicity from animal studies. 
146

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)-11 was based on liver tumors in female 

2 mice from a chronic study (Kano, et al., 2009). The available data indicate that the MOA(s) by 

3 which 1,4-dioxane induces peritoneal, mammary, or nasal tumors in rats and liver tumors in rats 

4 and mice is unknown (see Section 4.7.3 for a more detailed discussion of 1,4-dioxane‘s 

5 hypothesized MOAs). Therefore, based on the U.S. EPA‘s Guidelines for Carcinogen Risk 

6 Assessment (U.S. EPA, 2005a), a linear low dose extrapolation was used. The POD was 

7 calculated by curve fitting the animal experimental dose-response data from the range of 

8 observation and converting it to a HED (BMDL50 HED of 4.95 mg/kg-day). 

9 The uncertainties associated with the quantitation of the oral CSF are discussed below.

6.2.3.2. Inhalation

An inhalation unit risk (IUR) for 1,4-dioxane of 5 x 10-6(μg/m3)

-1

10 was based on a chronic 

11 inhalation study conducted by Kasai et al. (2009), Statistically significant increases in tumor 

12 incidence and positive dose-response trends were observed at multiple sites in the male rat 

13 including the nasal cavity (squamous cell carcinoma), liver (adenoma), peritoneal 

14 (mesothelioma), and the subcutis (fibroma). Statistically significant dose-response trends were 

15 also observed in the kidney (carcinoma), mammary gland (fibroadenoma), and the Zymbal gland 

16 (adenoma). The available data indicate that the MOA(s) by which 1,4-dioxane induces tumors in 

17 rats is unknown (see Section 4.7.3 for a more detailed discussion of 1,4-dioxane‘s hypothesized 

18 MOAs). Therefore, based on the U.S. EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. 

19 EPA, 2005a), a linear low dose extrapolation was used. A Bayesian approach (see Section 

20 5.4.3.2 and Appendix G for details) was used to calculate the POD for the total tumor risk 

21 following inhalation of 1,4-dioxane. The POD was calculated by curve fitting the animal 

22 experimental dose-response data from the range of observation and converting it to a continuous 

23 human equivalent exposure. 

24 The uncertainties associated with the quantitation of the IUR are discussed below.

6.2.3.3. Choice of Low-Dose Extrapolation Approach 

25 The range of possibilities for the low-dose extrapolation of tumor risk for exposure to 

26 1,4-dioxane, or any chemical, ranges from linear to nonlinear, but is dependent upon a plausible 

27 MOA(s) for the observed tumors. The MOA is a key consideration in clarifying how risks 

28 should be estimated for low-dose exposure. Exposure to 1,4-dioxane has been observed in 

29 animal models to induce multiple tumor types, including liver adenomas and carcinomas, nasal 

30 carcinomas, mammary adenomas and fibroadenomas, and mesotheliomas of the peritoneal cavity 

31 (Kano, et al., 2009). MOA information that is available for the carcinogenicity of 1,4-dioxane 

32 has largely focused on liver adenomas and carcinomas, with little or no MOA information 

33 available for the remaining tumor types. In Section 4.7.3, hypothesized MOAs were explored 

34 for 1,4-dioxane. Data are not available to support a carcinogenic MOA for 1,4-dioxane. In the 
147

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 absence of a MOA(s) for the observed tumor types associated with exposure to 1,4-dioxane, a 

2 linear low-dose extrapolation approach was used to estimate human carcinogenic risk associated 

3 with 1,4-dioxane exposure. 

4 In general, the Agency has preferred to use the multistage model for analyses of tumor 

5 incidence and related endpoints because they have a generic biological motivation based on 

6 long-established mathematical models such as the MVK model. The MVK model does not 

7 necessarily characterize all modes of tumor formation, but it is a starting point for most 

8 investigations and, much more often than not, has provided at least an adequate description of 

9 tumor incidence data.

10 The multistage cancer model did provide good fits for the tumor incidence data following 

11 a 2-year inhalation exposure to 1,4-dioxane by male rats (Kasai, et al., 2009). However, in the 

12 studies evaluated for the oral cancer assessment (Kano, et al., 2009; Kociba, et al., 1974; NCI, 

13 1978) the multistage model provided good descriptions of the incidence of a few tumor types in 

14 male (nasal cavity) and female (hepatocellular and nasal cavity) rats and in male mice 

15 (hepatocellular) exposed to 1,4-dioxane (see Appendix D for details). However, the multistage 

16 model did not provide an adequate fit for female mouse liver tumor dataset based upon the 

17 following (U.S. EPA, 2000a):

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 χ2residuals (values were 

greater than an absolute value of one).

18 BMDS software typically implements the guidance in the BMD technical guidance 

19 document (U.S. EPA, 2000a) by imposing constraints on the values of certain parameters of the 

20 models. When these constraints were imposed, the multistage model and most other models did 

21 not fit the incidence data for female mouse liver adenomas or carcinomas.

22 The log-logistic model was selected because it provides an adequate fit for the female 

23 mouse data (Kano, et al., 2009). A BMR of 50% was used because it is proximate to the 

24 response at the lowest dose tested and the BMDL50 was derived by applying appropriate 

25 parameter constraints, consistent with recommended use of BMDS in the BMD technical 

26 guidance document (U.S. EPA, 2000a).

27 The human equivalent oral CSF estimated from liver tumor datasets with statistically 

significant increases ranged from 4.2 × 10-4to 1.0 × 10-128 per mg/kg-day, a range of about three 

29 orders of magnitude, with the extremes coming from the combined male and female data for 

30 hepatocellular carcinomas (Kociba, et al., 1974) and the female mouse liver adenoma and 

31 carcinoma dataset (Kano, et al., 2009).
148

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

6.2.3.4. Dose Metric 

1 1,4-Dioxane is known to be metabolized in vivo. However, evidence does not exist to 

2 determine whether the parent compound, metabolite(s), or a combination of the parent compound 

3 and metabolites is responsible for the observed toxicity following exposure to 1,4-dioxane. If the 

4 actual carcinogenic moiety is proportional to administered exposure, then use of administered 

5 exposure as the dose metric is the least biased choice. On the other hand, if this is not the correct 

6 dose metric, then the impact on the CSF is unknown.

6.2.3.5. Cross-Species Scaling 

For the oral cancer assessment, an adjustment for cross-species scaling (BW0.75 7 ) was 

8 applied to address toxicological equivalence of internal doses between each rodent species and 

9 humans, consistent with the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). It is 

10 assumed that equal risks result from equivalent constant lifetime exposures.

11 Differences in the anatomy of the upper respiratory tract and resulting differences in 

12 absorption or in local respiratory system effects are sources of uncertainty in the inhalation 

13 cancer assessment. 

6.2.3.6. Statistical Uncertainty at the POD 

14 Parameter uncertainty can be assessed through confidence intervals. Each description of 

15 parameter uncertainty assumes that the underlying model and associated assumptions are valid. 

16 For the log-logistic model applied to the female mouse data following oral exposure, there is a 

17 reasonably small degree of uncertainty at the 50% excess incidence level (the POD for linear 

18 low-dose extrapolation). For the multistage model applied for the male rat inhalation dataset, 

19 there is a reasonable small degree of uncertainty at the 10% extra risk level (the POD for linear 

20 low-dose extrapolation). 

6.2.3.7. Bioassay Selection 

21 The study by Kano et al. (2009) was used for development of an oral CSF. This was a 

22 well-designed study, conducted in both sexes in two species (rats and mice) with a sufficient 

23 number (N=50) of animals per dose group. The number of test animals allocated among three 

24 dose levels and an untreated control group was adequate, with examination of appropriate 

25 toxicological endpoints in both sexes of rats and mice. Alternative bioassays (Kociba, et al., 

26 1974; NCI, 1978) were available and were fully considered for the derivation of the oral CSF.

27 The study by Kasai et al. (2009) was used for derivation of an inhalation unit risk. This 

28 was a well-designed and peer reviewed study, conducted in male rats with a sufficient number 

29 (N=50) of animals per dose group. Three dose levels plus an untreated control group were 

30 examined following exposure to 1,4-dioxane via inhalation for 2 years. Other bioassays (Kasai, 

31 et al., 2008; Torkelson, et al., 1974) were available and were fully considered for the derivation 

32 of the inhalation unit risk. 
149

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

6.2.3.8. Choice of Species/Gender 

1 The oral CSF for 1,4-dioxane was derived using the tumor incidence data for the female 

2 mouse, which was thought to be more sensitive than male mice or either sex of rats to the 

3 carcinogenicity of 1,4-dioxane. While all data, from both species and sexes reported from the 

4 Kano et al. (2009) study, were suitable for deriving an oral CSF, the female mouse data 

5 represented the most sensitive indicator of carcinogenicity in the rodent model. The lowest 

6 exposure level (66 mg/kg-day [animal dose] or 10 mg/kg-day [HED]) observed a considerable 

7 and significant increase in combined liver adenomas and carcinomas. Additional testing of doses 

8 within the range of control and the lowest dose (66 mg/kg-day [animal dose] or 10 mg/kg-day 

9 [HED]) could refine and reduce uncertainty for the oral CSF. 

10 Male F344 rat data were used to estimate risk following inhalation of 1,4-dioxane. Kasai 

11 et al. (2008) showed that male rats were more sensitive than female rats to the effects of 1,4-

12 dioxane following inhalation; therefore, male rats were chosen to be studied in the 2-year 

13 bioassay conducted by the same laboratory (Kasai, et al., 2009).

6.2.3.9. Relevance to Humans 

14 The oral CSF was derived using the tumor incidence in the liver of female mice. A 

15 thorough review of the available toxicological data available for 1,4-dioxane provides no 

16 scientific justification to propose that the liver adenomas and carcinomas observed in animal 

17 models following exposure to 1,4-dioxane are not plausible in humans. Liver adenomas and 

18 carcinomas were considered plausible outcomes in humans due to exposure to 1,4-dioxane. 

19 The derivation of the inhalation unit risk is based on the tumor incidence at multiple sites 

20 in male rats. There is no information on 1,4-dioxane to indicate that the observed rodent tumors 

21 are not relevant to humans. Further, no data exist to guide quantitative adjustment for 

22 differences in sensitivity among rodents and humans.

6.2.3.10. Human Population Variability 

23 The extent of inter-individual variability in 1,4-dioxane metabolism has not been 

24 characterized. A separate issue is that the human variability in response to 1,4-dioxane is also 

25 unknown. Data exploring whether there is differential sensitivity to 1,4-dioxane carcinogenicity 

26 across life stages is unavailable. This lack of understanding about potential differences in 

27 metabolism and susceptibility across exposed human populations thus represents a source of 

28 uncertainty. Also, the lack of information linking a MOA for 1,4-dioxane to the observed 

29 carcinogenicity is a source of uncertainty.
150

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

7. REFERENCES

1 ACS. (American Chemical Society). (1990). Handbook of Chemical Property Estimation 

2 Methods: Environmental Behavior of Organic Compounds. Washington, DC: American 

3 Chemical Society.

4 Agrawal, A. K., & Shapiro, B. H. (2000). Differential expression of gender-dependent hepatic 

5 isoforms of cytochrome P-450 by pulse signals in the circulating masculine episodic 

6 growth hormone profile of the rat. Journal of Pharmacology and Experimental 

7 Therapeutics, 292(1), 228-237. 

8 Amendments to the Clean Air Act. Sec. 604. Phase-out of production and consumption of class I 

9 substances, 42 (1990).

10 Andersen, M. E., Clewell Hj , 3rd, Gargas, M. L., Smith, F. A., & Reitz, R. H. (1987). 

11 Physiologically based pharmacokinetics and the risk assessment process for methylene 

12 chloride. Toxicology and Applied Pharmacology, 87(2), 185-205. doi: 10.1016/0041-

13 008x(87)90281-x

14 Argus, M. F., Arcos, J. C., & Hoch-Ligeti, C. (1965). Studies on the carcinogenic activity of 

15 protein-denaturing agents: Hepatocarcinogenicity of dioxane. Journal of the National 

16 Cancer Institute, 35(6), 949-958. 

17 Argus, M. F., Sohal, R. S., Bryant, G. M., Hoch-Ligeti, C., & Arcos, J. C. (1973). Dose-response 

18 and ultrastructural alterations in dioxane carcinogenesis. Influence of methylcholanthrene 

19 on acute toxicity. European Journal of Cancer, 9(4), 237-243. doi: 10.1016/0014-

20 2964(73)90088-1

21 Ashby, J. (1994). The genotoxicity of 1,4-dioxane. Mutation Research, 322(2), 141-142. doi: 

22 10.1016/0165-1218(94)00022-0

23 Atkinson, R. (1989). Kinetics and mechanisms of the gas-phase reactions of the hydroxyl radical 

24 with organic compounds. Washington, DC: American Chemical Society.

25 ATSDR. (Agency for Toxic Substances and Disease Registry). (2007). Toxicological profile for 

26 1,4 dioxane. Draft for public comment. Atlanta, GA: Author Retrieved from 

27 http://www.atsdr.cdc.gov/toxprofiles/tp187.pdf.

28 Bannasch, P. (2003). Comments on R. Karbe and R.L. Kerlin (2002) Cystic 

29 degeneration/spongiosis hepatis (Toxicol Pathol 30 (2), 216-227). Toxicologic Pathology, 

30 31(5), 566-570. doi: 10.1080/01926230390224700

31 Bannasch, P., Moore, M. A., Klimek, F., & Zerban, H. (1982). Biological markers of 

32 preneoplastic foci and neoplastic nodules in rodent liver. Toxicologic Pathology, 10(2), 

33 19-34. doi: 10.1177/019262338201000204

34 Barber, H. (1934). Haemorrhagic nephritis and necrosis of the liver from dioxan poisoning. 

35 Guy's Hospital Reports, 84, 267-280. 

36 Bogen, K. T. (1990). Uncertainty in Environmental Health Risk Assessment. New York: Garlend 

37 Publishing Company.

38 Boorman, G. A., Morgan, K. T., & Uriah, L. C. (1990). Nose, larynx and trachea Pathology of 

39 the Fischer Rat. Reference and Atlas (pp. 315-337). San Diego, CA: Academic Press, San 

40 Diego.

 

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).
151

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Braun, W. H., & Young, J. D. (1977). Identification of beta-hydroxyethoxyacetic acid as the 

2 major urinary metabolite of 1,4-dioxane in the rat. Toxicology and Applied 

3 Pharmacology, 39(1), 33-38. doi: 10.1016/0041-008x(77)90174-0

4 Bronaugh, R. L. (1982). Percutaneous absorption of cosmetic ingredients. In P. Frost & S. N. 

5 Horwitz (Eds.), Principles of cosmetics for the dermatologist (pp. 277-284). St. Louis, 

6 MO: C.V. Mosby.

7 Brown, R. P., Delp, M. D., Lindstedt, S. L., Rhomberg, L. R., & Beliles, R. P. (1997). 

8 Physiological parameter values for physiologically based pharmacokinetic models. 

9 Toxicology and Industrial Health, 13(4), 407-484. doi: 10.1177/074823379701300401

10 Buffler, P. A., Wood, S. M., Suarez, L., & Kilian, D. J. (1978). Mortality follow-up of workers 

11 exposed to 1,4-dioxane. Journal of Occupational and Environmental Medicine, 20(4), 

12 255-259. 

13 Bull, R. J., Robinson, M., & Laurie, R. D. (1986). Association of carcinoma yield with early 

14 papilloma development in SENCAR mice. Environmental Health Perspectives, 68, 11-

15 17. 

16 Burmistrov, S. O., Arutyunyan, A. V., Stepanov, M. G., Oparina, T. I., & Prokopenko, V. M. 

17 (2001). Effect of chronic inhalation of toluene and dioxane on activity of free radical 

18 processes in rat ovaries and brain. Bulletin of Experimental Biology and Medicine, 

19 132(3), 832-836. 

20 Carpenter, S. P., Lasker, J. M., & Raucy, J. L. (1996). Expression, induction, and catalytic 

21 activity of the ethanol-inducible cytochrome P450 (CYP2E1) in human fetal liver and 

22 hepatocytes. Molecular Pharmacology, 49(2), 260-268. 

23 Clark, B., Furlong, J. W., Ladner, A., & Slovak, A. J. M. (1984). Dermal toxicity of dimethyl 

24 acetylene dicarboxylate, N-methyl pyrrolidone, triethylene glycol dimethyl ether, dioxane 

25 and tetralin in the rat. IRCS Medical Science, 12, 296-297. 

26 CRC. (Crc). (2000). Handbook of Chemistry and Physics (81 ed.). Boca Raton, FL: CRC Press 

27 LLC.

28 David, H. (1964). Electron-microscopic findings in dioxan-dependent nephrosis in rat kidneys. 

29 Beitraege zur Pathologischen Anatomie und Allgemeinen Pathologie, 130, 187-212. 

30 de Navasquez, S. (1935). Experimental tubular necrosis of the kidneys accompanied by liver 

31 changes due to dioxane poisoning. Journal of Hygiene, 35(4), 540-548. 

32 Derosa, C. T., Wilbur, S., Holler, J., Richter, P., & Stevens, Y. W. (1996). Health evaluation of 

33 1,4-dioxane. Toxicology and Industrial Health, 12(1), 1-43. doi: 

34 10.1177/074823379601200101

35 Drew, R. T., Patel, J. M., & Lin, F. N. (1978). Changes in serum enzymes in rats after inhalation 

36 of organic solvents singly and in combination. Toxicology and Applied Pharmacology, 

37 45(3), 809-819. doi: 10.1016/0041-008x(78)90172-2

38 Ernstgard, L., Iregren, A., Sjogren, B., & Johanson, G. (2006). Acute effects of exposure to 

39 vapours of dioxane in humans. Human and Experimental Toxicology, 25(12), 723-729. 

40 doi: 10.1177/0960327106073805

41 Fairley, A., Linton, E. C., & Ford-Moore, A. H. (1934). The toxicity to animals of 1:4 dioxan. 

42 Journal of Hygiene, 34(4), 486-501. doi: 10.1017/s0022172400043266

43 Fisher, J., Mahle, D., Bankston, L., Greene, R., & Gearhart, J. (1997). Lactational transfer of 

44 volatile chemicals in breast milk. American Industrial Hygiene Association Journal, 

45 58(6), 425-431. doi: 10.1080/15428119791012667

46 Franke, C., Studinger, G., Berger, G., Böhling, S., Bruckmann, U., Cohors-Fresenborg, D., & 

47 Jöhncke, U. (1994). The assessment of bioaccumulation. Chemosphere, 29(7), 1501-

48 1514. doi: 10.1016/0045-6535(94)90281-x
152

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Frantik, E., Hornychova, M., & Horvath, M. (1994). Relative acute neurotoxicity of solvents: 

2 Isoeffective air concentrations of 48 compounds evaluated in rats and mice. 

3 Environmental Research, 66(2), 173-185. doi: 10.1006/enrs.1994.1053

4 Galloway, S. M., Armstrong, M. J., Reuben, C., Colman, S., Brown, B., Cannon, C., . . . Zeiger, 

5 E. (1987). Chromosome aberrations and sister chromatid exchanges in Chinese hamster 

6 ovary cells: Evaluations of 108 chemicals. Environmental and Molecular Mutagenesis, 

7 10(S10), 1-175. doi: 10.1002/em.2850100502

8 Gaskell, B. A. (1990). Nonneoplastic changes in the olfactory epithelium-- experimental studies. 

9 Environmental Health Perspectives, 85, 275-289. 

10 Giavini, E., Vismara, C., & Broccia, M. L. (1985). Teratogenesis study of dioxane in rats. 

11 Toxicology Letters, 26(1), 85-88. doi: 10.1016/0378-4274(85)90189-4

12 Goldberg, M. E., Johnson, H. E., Pozzani, U. C., & Smyth, H. F., Jr. (1964). Effect of repeated 

13 inhalation of vapors of industrial solvents on animal behavior: I. Evaluation of nine 

14 solvent vapors on pole-climb performance in rats. American Industrial Hygiene 

15 Association Journal, 25(4), 369-375. 

16 Goldsworthy, T. L., Monticello, T. M., Morgan, K. T., Bermudez, E., Wilson, D. M., Jäckh, R., 

17 & Butterworth Be. (1991). Examination of potential mechanisms of carcinogenicity of 

18 1,4-dioxane in rat nasal epithelial cells and hepatocytes. Archives of Toxicology, 65(1), 1-

19 9. doi: 10.1007/bf01973495

20 Green, T., Lee, R., Moore, R. B., Ashby, J., Willis, G. A., Lund, V. J., & Clapp Mjl. (2000). 

21 Acetochlor-induced rat nasal tumors: Further studies on the mode of action and relevance 

22 to humans. Regulatory Toxicology and Pharmacology, 32(1), 127-133. doi: 

23 10.1006/rtph.2000.1413

24 Grosjean, D. (1990). Atmospheric chemistry of toxic contaminants. 2. Saturated aliphatics: 

25 Acetaldehyde, dioxane, ethylene glycol ethers, propylene oxide. Journal of the Air and 

26 Waste Management Association (1990-1992), 40(11), 1522-1531. 

27 Hansch, C., Leo, A., & Hoekman, D. (1995). Exploring QSAR: Hydrophobic, Electronic, and 

28 Steric Constants (Vol. 2). Washington, DC: American Chemical Society.

29 Harkema, J. R., Carey, S. A., & Wagner, J. G. (2006). The nose revisited: A brief review of the 

30 comparative structure, function, and toxicologic pathology of the nasal epithelium. 

31 Toxicologic Pathology, 34(3), 252-269. 

32 Haseman, J. K., & Hailey, J. R. (1997). An update of the National Toxicology Program database 

33 on nasal carcinogens. Mutation Research, 380(1-2), 3-11. doi: 10.1016/s0027-

34 5107(97)00121-8

35 Haseman, J. K., Huff, J., & Boorman, G. A. (1984). Use of historical control data in 

36 carcinogenicity studies in rodents. Toxicologic Pathology, 12(2), 126-135. doi: 

37 10.1177/019262338401200203

38 Hawley, G. G., & Lewis Rj Sr. (2001). Hawley's Condensed Chemical Dictionary (14 ed.). New 

39 York, NY: John Wiley & Sons, Inc.

40 Haworth, S., Lawlor, T., Mortelmans, K., Speck, W., & Zeiger, E. (1983). Salmonella 

41 mutagenicity test results for 250 chemicals. Environmental Mutagenesis, 5(Suppl 1), 3-

42 142. doi: 10.1002/em.2860050703

43 Hayashi, S., Watanabe, J., & Kawajiri, K. (1991). Genetic polymorphisms in the 5'-flanking 

44 region change transcriptional regulation of the human cytochrome P450IIE1 gene. 

45 Journal of Biochemistry, 110(4), 559-565. 

46 Hellmér, L., & Bolcsfoldi, G. (1992). An evaluation of the E. coli K-12 uvrB/recA DNA repair 

47 host-mediated assay. I. In vitro sensitivity of the bacteria to 61 compounds. Mutation 

48 Research, 272(2), 145-160. doi: 10.1016/0165-1161(92)90043-l
153

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Hoch-Ligeti, C., & Argus, M. F. (1970). Effect of carcinogens on the lung of guinea pigs. In P. 

2 Nettlesheim, M. G. Hanna Jr & J. W. Deatherage Jr (Eds.), Morphology of Experimental 

3 Respiratory Carcinogenesis: Proceedings of a Biology Division, Oak Ridge National 

4 Laboratory, Conference held in Gatlinburg, Tennessee, May 13-16, 1970 (Vol. 21, pp. 

5 267-279). Oak Ridge, TN: United States Atomic Energy Comission, Division of 

6 Technical Information.

7 Hoch-Ligeti, C., Argus, M. F., & Arcos, J. C. (1970). Induction of carcinomas in the nasal cavity 

8 of rats by dioxane. British Journal of Cancer, 24(1), 164-167. 

9 HSDB. (Hazardous Substances Data Bank). (2007). 1,4-Dioxane. Bethesda, Maryland: National 

10 Library of Medicine, National Toxicology Program, Hazardous Substances Data Bank.

11 Huang, C. Y., Huang, K. L., Cheng, T. J., Wang, J. D., & Hsieh, L. L. (1997). The GST T1 and 

12 CYP2E1 genotypes are possible factors causing vinyl chloride induced abnormal liver 

13 function. Archives of Toxicology, 71(8), 482-488. doi: 10.1007/s002040050416

14 IARC. (International Agency for Research on Cancer). (1999). 1,4-Dioxane. Lyon, France: 

15 World Health Organization Retrieved from 

16 http://monographs.iarc.fr/ENG/Monographs/vol71/mono71-25.pdf.

17 ICRP. (International Commission on Radiological Protection). (1975). Report of the task group 

18 on reference man: ICRP publication 23 (Vol. 23). New York, NY: International 

19 Commission of Radiological Protection, Pergamon Press.

20 JBRC. (Japan Bioassay Research Center). (1998). Two-year studies of 1,4-dioxane in F344 rats 

21 and BDF1 mice (drinking water). Kanagawa, Japan: Author.

22 Johnstone, R. T. (1959). Death due to dioxane? AMA Archives of Industrial Health, 20, 445-447. 

23 Kanada, M., Miyagawa, M., Sato, M., Hasegawa, H., & Honma, T. (1994). Neurochemical 

24 profile of effects of 28 neurotoxic chemicals on the central nervous system in rats (1) 

25 Effects of oral administration on brain contents of biogenic amines and metabolites. 

26 Industrial Health, 32(3), 145-164. doi: 10.2486/indhealth.32.145

27 Kano, H., Umeda, Y., Kasai, T., Sasaki, T., Matsumoto, M., Yamazaki, K., . . . Fukushima, S. 

28 (2009). Carcinogenicity studies of 1,4-dioxane administered in drinking-water to rats and 

29 mice for 2 years. Food and Chemical Toxicology, 47(11), 2776-2784. doi: 

30 10.1016/j.fct.2009.08.012

31 Kano, H., Umeda, Y., Saito, M., Senoh, H., Ohbayashi, H., Aiso, S., . . . Fukushima, S. (2008). 

32 Thirteen-week oral toxicity of 1,4-dioxane in rats and mice. Journal of Toxicological 

33 Sciences, 33(2), 141-153. doi: 10.2131/jts.33.141

34 Karbe, E., & Kerlin, R. L. (2002). Cystic degeneration/spongiosis hepatis in rats. Toxicologic 

35 Pathology, 30(2), 216-227. doi: 10.1080/019262302753559551

36 Kasai, T., Kano, H., Umeda, Y., Sasaki, T., Ikawa, N., Nishizawa, T., . . . Fukushima, S. (2009). 

37 Two-year inhalation study of carcinogenicity and chronic toxicity of 1,4-dioxane in male 

38 rats. Inhalation Toxicology, 21(11), 889-897. doi: 10.1080/08958370802629610

39 Kasai, T., Saito, M., Senoh, H., Umeda, Y., Aiso, S., Ohbayashi, H., . . . Fukushima, S. (2008). 

40 Thirteen-week inhalation toxicity of 1,4-dioxane in rats. Inhalation Toxicology, 20(10), 

41 961-971. doi: 10.1080/08958370802105397

42 Kasper, P., Uno, Y., Mauthe, R., Asano, N., Douglas, G., Matthews, E., . . . Speit, G. (2007). 

43 Follow-up testing of rodent carcinogens not positive in the standard genotoxicity testing 

44 battery: IWGT workgroup report. Mutation Research, 627(1), 106-116. doi: 

45 10.1016/j.mrgentox.2006.10.007

46 Katagiri, T., Nagano, K., Aiso, S., Senoh, H., Sakura, Y., Takeuchi, T., & Okudaira, M. (1998). 

47 A pathological study on spontaneous hepatic neoplasms in BDF1 mice. Journal of 

48 Toxicologic Pathology, 11(1), 21-25. doi: 10.1293/tox.11.21
154

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Kesten, H. D., Mulinos, M. G., & Pomerantz, L. (1939). Pathologic effects of certain glycols and 

2 related compounds. Archives of Pathology, 27, 447-465. 

3 Khudoley, V. V., Mizgireuv, I., & Pliss, G. B. (1987). The study of mutagenic activity of 

4 carcinogens and other chemical agents with Salmonella typhimurium assays: Testing of 

5 126 compounds. Archiv fuer Geschwulstforschung, 57(6), 453-462. 

6 King, M. E., Shefner, A. M., & Bates, R. R. (1973). Carcinogenesis bioassay of chlorinated 

7 dibenzodioxins and related chemicals. Environmental Health Perspectives, 5, 163-170. 

8 Kitchin, K. T., & Brown, J. L. (1990). Is 1,4-dioxane a genotoxic carcinogen? Cancer Letters, 

9 53(1), 67-71. doi: 10.1016/0304-3835(90)90012-m

10 Knoefel, P. K. (1935). Narcotic potency of some cyclic acetals. Journal of Pharmacology and 

11 Experimental Therapeutics, 53(4), 440-444. 

12 Kociba, R. J., McCollister, S. B., Park, C., Torkelson, T. R., & Gehring, P. J. (1974). 1,4-

13 dioxane. I. Results of a 2-year ingestion study in rats. Toxicology and Applied 

14 Pharmacology, 30(2), 275-286. doi: 10.1016/0041-008x(74)90099-4

15 Kociba, R. J., Torkelson, T. R., Young, J. D., & Gehring, P. J. (1975). 1,4-Dioxane: Correlation 

16 of the results of chronic ingestion and inhalation studies with its dose-dependent fate in 

17 rats Proceedings of the 6th Annual Conference on Environmental Toxicology (pp. 345-

18 354). Wright-Patterson Air Force Base, OH: Wright-Patterson Air Force Base, Air Force 

19 Systems Command, Aerospace Medical Division, Aerospace Medical Research 

20 Laboratory.

21 Kopylev, L., John Fox, J., & Chen, C. (2009). Combining risks from several tumors using 

22 Markov Chain Monte Carlo. In R. M. Cooke (Ed.), Uncertainty Modeling in Dose 

23 Response (1 ed., pp. 197-205). Hoboken, NJ: John Wiley & Sons.

24 Kurl, R. N., Poellinger, L., Lund, J., & Gustafsson, J. A. (1981). Effects of dioxane on RNA 

25 synthesis in the rat liver. Archives of Toxicology, 49(1), 29-33. doi: 10.1007/bf00352068

26 Kwan, K. K., Dutka, B. J., Rao, S. S., & Liu, D. (1990). Mutatox test: A new test for monitoring 

27 environmental genotoxic agents. Environmental Pollution, 65(4), 323-332. doi: 

28 10.1016/0269-7491(90)90124-u

29 Laug, E. P., Calvery, H. O., Morris, H. J., & Woodard, G. (1939). The toxicology of some 

30 glycols and derivatives. Journal of Industrial Hygiene and Toxicology, 21(6), 173-201. 

31 Lesage, S., Jackson, R. E., Priddle, M. W., & Riemann, P. G. (1990). Occurrence and fate of 

32 organic solvent residues in anoxic groundwater at the Gloucester landfill, Canada. 

33 Environmental Science and Technology, 24(4), 559-566. doi: 10.1021/es00074a016

34 Leung, H. W., & Paustenbach, D. J. (1990). Cancer risk assessment for dioxane based upon a 

35 physiologically-based pharmacokinetic approach. Toxicology Letters, 51, 147-162. 

36 Lewandowski, T. A., & Rhomberg, L. R. (2005). A proposed methodology for selecting a 

37 trichloroethylene inhalation unit risk value for use in risk assessment. Regulatory 

38 Toxicology and Pharmacology, 41, 39-54. doi: 10.1016/j.yrtph.2004.09.003

39 Lewis, R. J., Sr. (2000). Sax's Dangerous Properties of Industrial Materials (10 ed.). New York, 

40 NY: John Wiley & Sons, Inc.

41 Lundberg, I., Ekdahl, M., Kronevi, T., Lidums, V., & Lundberg, S. (1986). Relative 

42 hepatotoxicity of some industrial solvents after intraperitoneal injection or inhalation 

43 exposure in rats. Environmental Research, 40, 411-420. doi: 10.1016/s0013-

44 9351(86)80116-5

45 Lundberg, I., Hogberg, J., Kronevi, T., & Holmberg, B. (1987). Three industrial solvents 

46 investigated for tumor promoting activity in the rat liver. Cancer Letters, 36(1), 29-33. 

47 doi: 10.1016/0304-3835(87)90099-1

48 Marzulli, F. N., Anjo, D. M., & Maibach, H. I. (1981). In vivo skin penetration studies of 2,4-

49 toluenediamine, 2,4-diaminoanisole, 2-nitro-p-phenylenediamine, p-dioxane and N-
155

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 nitrosodiethanolamine in cosmetics. Food and Cosmetics Toxicology, 19(6), 743-747. 

2 doi: 10.1016/0015-6264(81)90530-7

3 McConnell, E. E., Solleveld, H. A., Swenberg, J. A., & Boorman, G. A. (1986). Guidelines for 

4 combining neoplasms for evaluation of rodent carcinogenesis studies. Journal of the 

5 National Cancer Institute, 76, 283-289. 

6 McFee, A. F., Abbott, M. G., Gulati, D. K., & Shelby, M. D. (1994). Results of mouse bone 

7 marrow micronucleus studies on 1,4-dioxane. Mutation Research, 322(2), 145-148. 

8 McGregor, D. B., Brown, A. G., Howgate, S., McBride, D., Riach, C., & Caspary, W. J. (1991). 

9 Responses of the L5178Y mouse lymphoma cell forward mutation assay. V: 27 coded 

10 chemicals. Environmental and Molecular Mutagenesis, 17(3), 196-219. doi: 

11 10.1002/em.2850170309

12 Medinsky, M. A., & Bond, J. A. (2001). Sites and mechanisms for uptake of gases and vapors in 

13 the respiratory tract. Toxicology, 160, 165-172. 

14 The Merck Index: An Encyclopedia of Chemicals, Drugs, and Biologicals. (2001). (13th ed.). 

15 Whitehouse Station, NJ: Merck & Co., Inc.

16 Meylan, W. M., Howard, P. H., Boethling, R. S., Aronson, D., Printup, H., & Gouchie, S. 

17 (1999). Improved method for estimating bioconcentration/bioaccumulation factor from 

18 octanol/water partition coefficient. Environmental Toxicology and Chemistry, 18(4), 664-

19 672. doi: 10.1002/etc.5620180412

20 Mikheev, M. I., Gorlinskaya Ye, P., & Solovyova, T. V. (1990). The body distribution and 

21 biological action of xenobiotics. Journal of Hygiene, Epidemiology, Microbiology and 

22 Immunology, 34(4), 329-336. 

23 Mirkova, E. T. (1994). Activity of the rodent carcinogen 1,4-dioxane in the mouse bone marrow 

24 micronucleus assay. Mutation Research, 322(2), 142-144. 

25 Miyagawa, M., Shirotori, T., Tsuchitani, M., & Yoshikawa, K. (1999). Repeat-assessment of 

26 1,4-dioxane in a rat-hepatocyte replicative DNA synthesis (RDS) test: Evidence for 

27 stimulus of hepatocyte proliferation. Experimental and Toxicologic Pathology, 51(6), 

28 555-558. 

29 Morgan, K. T., Patterson, D. L., & Gross, E. A. (1986). Responses of the nasal mucociliary 

30 apparatus of F-344 rats to formaldehyde gas. Toxicology and Applied Pharmacology, 

31 82(1), 1-13. doi: 10.1016/0041-008x(86)90431-x

32 Morita, T. (1994). No clastogenicity of 1,4 dioxane as examined in the mouse peripheral blood 

33 micronucleus test. Honyu Dobutsu Shiken Bunkakai Kaiho, 2, 7-8. 

34 Morita, T., & Hayashi, M. (1998). 1,4-Dioxane is not mutagenic in five in vitro assays and 

35 mouse peripheral blood micronucleus assay, but is in mouse liver micronucleus assay. 

36 Environmental and Molecular Mutagenesis, 32(3), 269-280. doi: 10.1002/(sici)1098-

37 2280(1998)32:3<269::aid-em10>3.0.co;2-8

38 Mungikar, A. M., & Pawar, S. S. (1978). Induction of the hepatic microsomal mixed function 

39 oxidase system in mice by p-dioxane. Bulletin of Environmental Contamination and 

40 Toxicology, 20, 797-804. doi: 10.1007/bf01683603

41 Munoz, E. R., & Barnett, B. M. (2002). The rodent carcinogens 1,4-dioxane and thiourea induce 

42 meiotic non-disjunction in Drosophila melanogaster females. Mutation Research, 517(1-

43 2), 231-238. doi: 10.1016/s1383-5718(02)00083-9

44 Nannelli, A., De Rubertis, A., Longo, V., & Gervasi, P. G. (2005). Effects of dioxane on 

45 cytochrome P450 enzymes in liver, kidney, lung and nasal mucosa of rat. Archives of 

46 Toxicology, 79(2), 74-82. doi: 10.1007/s00204-004-0590-z

47 NCI. (National Institutes of Health, National Cancer Institute). (1978). Bioassay of 1,4-dioxane 

48 for possible carcinogenicity. (Report No. 78-1330 NCICGTR-80). Bethesda, MD: 
156

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 National Cancer Institute Retrieved from 

2 http://ntp.niehs.nih.gov/ntp/htdocs/LT_rpts/tr080.pdf.

3 Nelson, N. (1951). Solvent toxicity with particular reference to certain octyl alcohols and 

4 dioxanes. Medical Bulletin, 11, 226-238. 

5 Nestmann, E. R., Otson, R., Kowbel, D. J., Bothwell, P. D., & Harrington, T. R. (1984). 

6 Mutagenicity in a modified Salmonella assay of fabric-protecting products containing 

7 1,1,1-trichloroethane. Environmental and Molecular Mutagenesis, 6(1), 71-80. doi: 

8 10.1002/em.2860060109

9 NRC. (National Research Council). (1983). Risk assessment in the federal government: 

10 Managing the process. Washington, DC: National Academy Press.

11 NRC. (National Research Council). (2009). Science and Decisions: Advancing Risk Assessment. 

12 Washington, DC: Author.

13 Park, J. H., Hussam, A., Couasnon, P., Fritz, D., & Carr, P. W. (1987). Experimental 

14 reexamination of selected partition coefficients from Rohrschneider's data set. Analytical 

15 Chemistry, 59(15), 1970-1976. doi: 10.1021/ac00142a016

16 Platz, J., Sehested, J., Mogelberg, T., Nielsen, O. J., & Wallington, T. J. (1997). Atmospheric 

17 chemistry of 1,4-dioxane. Faraday Transactions 1, 93(16), 2855-2863. doi: 

18 10.1039/a700598i

19 Pozzani, U. C., Weil, C. S., & Carpenter, C. P. (1959). The toxicological basis of threshold limit 

20 values. 5: The experimental inhalation of vapor mixtures by rats, with notes upon the 

21 relationship between single dose inhalation and single dose oral data. American Industrial 

22 Hygiene Association Journal, 20, 364-369. doi: 10.1080/00028895909343733

23 Ramsey, J. C., & Andersen, M. E. (1984). A physiologically based description of the inhalation 

24 pharmacokinetics of styrene in rats and humans. Toxicology and Applied Pharmacology, 

25 73(1), 159-175. doi: 10.1016/0041-008x(84)90064-4

26 Reitz, R. H., McCroskey, P. S., Park, C. N., Andersen, M. E., & Gargas, M. L. (1990). 

27 Development of a physiologically based pharmacokinetic model for risk assessment with 

28 1,4-dioxane. Toxicology and Applied Pharmacology, 105(1), 37-54. doi: 10.1016/0041-

29 008x(90)90357-z

30 Rosenkranz, H. S., & Klopman, G. (1992). 1,4-dioxane: Prediction of in vivo clastogenicity. 

31 Mutation Research, 280(4), 245-251. doi: 10.1016/0165-1218(92)90054-4

32 Roy, S. K., Thilagar, A. K., & Eastmond, D. A. (2005). Chromosome breakage is primarily 

33 responsible for the micronuclei induced by 1,4-dioxane in the bone marrow and liver of 

34 young CD-1 mice. Mutation Research, 586(1), 28-37. doi: 

35 10.1016/j.mrgentox.2005.05.007

36 Sato, K. (1989). Glutathione transferases as markers of preneoplasia and neoplasia. Advances in 

37 Cancer Research, 52, 205-255. 

38 Schrenk, H. H., & Yant, W. P. (1936). Toxicity of dioxan. Journal of Industrial Hygiene and 

39 Toxicology, 18(7), 448-460. 

40 Sheu, C. W., Moreland, F. M., Lee, J. K., & Dunkel, V. C. (1988). In vitro BALB/3T3 cell 

41 transformation assay of nonoxynol-9 and 1,4-dioxane. Environmental and Molecular 

42 Mutagenesis, 11(1), 41-48. doi: 10.1002/em.2850110106

43 Silverman, L., Schulte, H. F., & First, M. W. (1946). Further studies on sensory response to 

44 certain industrial solvent vapors. Journal of Industrial Hygiene and Toxicology, 28, 262-

45 266. 

46 Sina, J. F., Bean, C. L., Dysart, G. R., Taylor, V. I., & Bradley, M. O. (1983). Evaluation of the 

47 alkaline elution/rat hepatocyte assay as a predictor of carcinogenic/mutagenic potential. 

48 Mutation Research, 113(5), 357-391. doi: 10.1016/0165-1161(83)90228-5
157

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Smyth Hf Jr, Seaton, J., & Fischer, L. (1941). The single dose toxicity of some glycols and 

2 derivatives. Journal of Industrial Hygiene and Toxicology, 23, 259-268. 

3 Spiegelhalter, D., Thomas, A., & Best, N. (2003). WinBugs version 1.4 user manual. Cambridge, 

4 UK: MRC Biostatistics Unit.

5 Spurgeon, D. J., Hopkin, S. P., & Jones, D. T. (1994). Effects of cadmium, copper, lead and zinc 

6 on growth, reproduction and survival of the earthworm Eisenia fetida (savigny): assessing 

7 the environmental impact of point-source metal contamination in terrestrial ecosystems. 

8 Environmental Pollution, 84, 123-130. 

9 Stickney, J. A., Sager, S. L., Clarkson, J. R., Smith, L. A., Locey, B. J., Bock, M. J., . . . Olp, S. 

10 F. (2003). An updated evaluation of the carcinogenic potential of 1,4-dioxane. Regulatory 

11 Toxicology and Pharmacology, 38(2), 183-195. doi: 10.1016/s0273-2300(03)00090-4

12 Stoner, G. D., Conran, P. B., Greisiger, E. A., Stober, J., Morgan, M., & Pereira, M. A. (1986). 

13 Comparison of two routes of chemical administration on the lung adenoma response in 

14 strain A/J mice. Toxicology and Applied Pharmacology, 82, 19-31. doi: 10.1016/0041-

15 008x(86)90433-3

16 Stott, W. T., Quast, J. F., & Watanabe, P. G. (1981). Differentiation of the mechanisms of 

17 oncogenicity of 1,4-dioxane and 1,3-hexachlorobutadiene in the rat. Toxicology and 

18 Applied Pharmacology, 60(2), 287-300. doi: 10.1016/0041-008x(91)90232-4

19 Stroebel, P., Mayer, F., Zerban, H., & Bannasch, P. (1995). Spongiotic pericytoma: A benign 

20 neoplasm deriving from the perisinusoidal (Ito) cells in rat liver. The American Journal of 

21 Pathology, 146(4), 903-913. 

22 Surprenant, K. S. (2002). Dioxane Ullmann's Encyclopedia of Industrial Chemistry (6th ed., pp. 

23 543). Weinheim, Germany: Wiley-VCH Verlag.

24 Sweeney, L. M., Thrall, K. D., Poet, T. S., Corley, R. A., Weber, T. J., Locey, B. J., . . . Gargas, 

25 M. L. (2008). Physiologically based pharmacokinetic modeling of 1,4-dioxane in rats, 

26 mice, and humans. Toxicological Sciences, 101(1), 32-50. doi: 10.1093/toxsci/kfm251

27 Thiess, A. M., Tress, E., & Fleig, I. (1976). Arbeitsmedizinische Untersuchungsergebnisse von 

28 Dioxan-exponierten Mitarbeitern [Industrial-medical investigation results in the case of 

29 workers exposed to dioxane]. Arbeitsmedizin, Sozialmedizin, Umweltmedizin, 11, 35-46. 

30 Thurman, G. B., Simms, B. G., Goldstein, A. L., & Kilian, D. J. (1978). The effects of organic 

31 compounds used in the manufacture of plastics on the responsivity of murine and human 

32 lymphocytes. Toxicology and Applied Pharmacology, 44(3), 617-641. doi: 10.1016/0041-

33 008x(78)90269-7

34 Tinwell, H., & Ashby, J. (1994). Activity of 1,4-dioxane in mouse bone marrow micronucleus 

35 assays. Mutation Research, 322(2), 148-150. 

36 Torkelson, T. R., Leong, B. K. J., Kociba, R. J., Richter, W. A., & Gehring, P. J. (1974). 1,4-

37 Dioxane. II. Results of a 2-year inhalation study in rats. Toxicology and Applied 

38 Pharmacology, 30(2), 287-298. doi: 10.1016/0041-008x(74)90100-8

39 U.N. Environment Programme. (United Nations Environment Programme). (2000). The 

40 Montreal Protocol on substances that deplete the ozone layer. Nairobi, Kenya: United 

41 Nations Environment Programme, Ozone Secretariat Retrieved from 

42 http://www.google.com/url?sa=t&source=web&cd=1&ved=0CBIQFjAA&url=http%3A

43 %2F%2Fwww.unep.org%2Fozone%2Fpdfs%2Fmontreal-protocol2000.pdf&ei=-

44 c89TPX0N9PRngf-i-jdDg&usg=AFQjCNH4OHl5inPn5XFcYTvblPPRDZu45 fQ&sig2=qqSaM_nuQlX1Hc409kBvgw.

46 U.S. EPA. (U.S. Environmental Protection Agency). (1986a). Guidelines for carcinogen risk 

47 assessment. (Report No. EPA/630/R-00/004). Washington, DC: U.S. Environmental 

48 Protection Agency, Risk Assessment Forum Retrieved from 

49 http://epa.gov/raf/publications/pdfs/CA%20GUIDELINES_1986.PDF.
158

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 U.S. EPA. (U.S. Environmental Protection Agency). (1986b). Guidelines for mutagenicity risk 

2 assessment. (Report No. EPA/630/R-98/003). Washington, DC: U.S. Environmental 

3 Protection Agency, Risk Assessment Forum Retrieved from 

4 http://www.epa.gov/iris/backgrd.html.

5 U.S. EPA. (U.S. Environmental Protection Agency). (1986c). Guidelines for the health risk 

6 assessment of chemical mixtures. (Report No. EPA/630/R-98/002). Washington, DC: 

7 U.S. Environmental Protection Agency, Risk Assessment Forum Retrieved from 

8 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=22567.

9 U.S. EPA. (U.S. Environmental Protection Agency). (1988). Recommendations for and 

10 documentation of biological values for use in risk assessment. (Report No. EPA/600/6-

11 87/008). Cincinnati, OH: U.S. Environmental Protection Agency, Office of Research and 

12 Development Retrieved from 

13 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=34855.

14 U.S. EPA. (U.S. Environmental Protection Agency). (1991). Guidelines for developmental 

15 toxicity risk assessment. (Report No. EPA/600/FR-91/001). Washington, DC: U.S. 

16 Environmental Protection Agency, Risk Assessment Forum Retrieved from 

17 http://www.epa.gov/iris/backgrd.html.

18 U.S. EPA. (U.S. Environmental Protection Agency). (1994a). Interim policy for particle size and 

19 limit concentration issues in inhalation toxicity studies. Washington, DC: U.S. 

20 Environmental Protection Agency, Office of Pesticide Products, Health Effects Division 

21 Retrieved from http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=186068.

22 U.S. EPA. (U.S. Environmental Protection Agency). (1994b). Methods for derivation of 

23 inhalation reference concentrations and application of inhalation dosimetry. (Report No. 

24 EPA/600/8-90/066F). Washington, DC: U.S. Environmental Protection Agency, Office 

25 of Research and Development Retrieved from 

26 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=71993.

27 U.S. EPA. (U.S. Environmental Protection Agency). (1995). The use of the benchmark dose 

28 approach in health risk assessment. (Report No. EPA/630/R-94/007). Washington, DC: 

29 U.S. Environmental Protection Agency, Risk Assessment Forum.

30 U.S. EPA. (U.S. Environmental Protection Agency). (1996). Guidelines for reproductive toxicity 

31 risk assessment. (Report No. EPA/630/R-96/009). Washington, DC: U.S. Environmental 

32 Protection Agency, Risk Assessment Forum Retrieved from 

33 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=2838.

34 U.S. EPA. (U.S. Environmental Protection Agency). (1998). Guidelines for neurotoxicity risk 

35 assessment. (Report No. EPA/630/R-95/001F). Washington, DC: U.S. Environmental 

36 Protection Agency, Risk Assessment Forum Retrieved from 

37 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=12479.

38 U.S. EPA. (U.S. Environmental Protection Agency). (2000a). Benchmark dose technical 

39 guidance document [external review draft]. (Report No. EPA/630/R-00/001). 

40 Washington, DC: U.S. Environmental Protection Agency, Risk Assessment Forum 

41 Retrieved from http://www.epa.gov/raf/publications/benchmark-dose-doc-draft.htm.

42 U.S. EPA. (U.S. Environmental Protection Agency). (2000b). Science policy council handbook: 

43 Risk characterization. (Report No. EPA 100-B-00-002). Washington, D.C.: U.S. 

44 Environmental Protection Agency, Office of Research and Development, Office of 

45 Science Policy Retrieved from http://www.epa.gov/osa/spc/pdfs/rchandbk.pdf.

46 U.S. EPA. (U.S. Environmental Protection Agency). (2000c). Supplementary guidance for 

47 conducting health risk assessment of chemical mixtures. (Report No. EPA/630/R48 00/002). Washington, DC: U.S. Environmental Protection Agency, Risk Assessment 

49 Forum Retrieved from http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=20533.
159

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 U.S. EPA. (U.S. Environmental Protection Agency). (2002a). A review of the reference dose and 

2 reference concentration processes. (Report No. EPA/630/P-02/0002F). Washington, DC: 

3 U.S. Environmental Protection Agency, Risk Assessment Forum Retrieved from 

4 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=55365.

5 U.S. EPA. (U.S. Environmental Protection Agency). (2002b, February 22, 2010). Toxic 

6 Substances Control Act (TSCA) Inventory Update Database, from 

7 http://www.epa.gov/iur/

8 U.S. EPA. (U.S. Environmental Protection Agency). (2005a). Guidelines for carcinogen risk 

9 assessment, final report. (Report No. EPA/630/P-03/001F). Washington, DC: U.S. 

10 Environmental Protection Agency, Risk Assessment Forum Retrieved from 

11 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283.

12 U.S. EPA. (U.S. Environmental Protection Agency). (2005b). Supplemental guidance for 

13 assessing susceptibility from early-life exposure to carcinogens. (Report No. EPA/630/R14 03/003F). Washington, DC: U.S. Environmental Protection Agency, Risk Assessment 

15 Forum Retrieved from http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=160003.

16 U.S. EPA. (U.S. Environmental Protection Agency). (2006a). A framework for assessing health 

17 risk of environmental exposures to children. (Report No. EPA/600/R-05/093F). 

18 Washington, DC: U.S. Environmental Protection Agency, Office of Research and 

19 Development Retrieved from 

20 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=158363.

21 U.S. EPA. (U.S. Environmental Protection Agency). (2006b). U.S. Environmental Protection 

22 Agency peer review handbook. (Report No. EPA/100/B-06/002). Washington, DC: U.S. 

23 Environmental Protection Agency, Science Policy Council Retrieved from 

24 http://www.epa.gov/peerreview/pdfs/peer_review_handbook_2006.pdf.

25 U.S. EPA. (U.S. Environmental Protection Agency). (2009a). Status report: Advances in 

26 inhalation dosimetry of gases and vapors with portal of entry effects in the upper 

27 respiratory tract. (Report No. EPA/600/R-09/072). Research Triangle Park, NC: U.S. 

28 Environmental Protection Agency, National Center for Environmental Assessment 

29 Retrieved from http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=212131.

30 U.S. EPA. (U.S. Environmental Protection Agency). (2009b). Toxicological review of 1,4-

31 dioxane (CAS No. 123-91-1) in support of summary information on the Intergrated Risk 

32 Information System (IRIS) [External Review Draft]. (Report No. EPA/635/R-09/005). 

33 Washington, DC: U.S. Environmental Protection Agency, Integrated Risk Information 

34 System Retrieved from http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=199330.

35 U.S. EPA. (U.S. Environmental Protection Agency). (2010). Toxicological review of 1,4-

36 Dioxane (CAS No. 123-91-1) in support of summary information on the Integrated Risk 

37 Information System (IRIS). Washington, DC: Author.

38 Uno, Y., Takasawa, H., Miyagawa, M., Inoue, Y., Murata, T., & Yoshikawa, K. (1994). An in 

39 vivo-in vitro replicative DNA synthesis (RDS) test using rat hepatocytes as an early 

40 prediction assay for nongenotoxic hepatocarcinogens screening of 22 known positives 

41 and 25 noncarcinogens. Mutation Research, 320(3), 189-205. doi: 10.1016/0165-

42 1218(94)90046-9

43 van Delft, J. H., van Agen, E., van Breda, S. G., Herwijnen, M. H., Staal, Y. C., & Kleinjans, J. 

44 C. (2004). Discrimination of genotoxic from non-genotoxic carcinogens by gene 

45 expression profiling. Carcinogenesis, 25(7), 1265-1276. doi: 10.1093/carcin/bgh108

46 Vieira, I., Sonnier, M., & Cresteil, T. (1996). Developmental expression of CYP2E1 in the 

47 human liver: hypermethylation control of gene expression during the neonatal period. 

48 European Journal of Biochemistry, 238(2), 476-483. doi: 10.1111/j.1432-

49 1033.1996.0476z.x
160

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Watanabe, J., Hayashi, S., & Kawajiri, K. (1994). Different regulation and expression of the 

2 human CYP2E1 gene due to the Rsal polymorphism in the 5'-flanking region. Journal of 

3 Biochemistry, 116(2), 321-326. 

4 Waxman, D. J., Pampori, N. A., Ram, P. A., Agrawal, A. K., & Shapiro, B. H. (1991). Interpulse 

5 interval in circulating growth hormone patterns regulates sexually dimorphic expression 

6 of hepatic cytochrome P450. Proceedings of the National Academy of Sciences, 88(15), 

7 6868-6872. 

8 Wirth, W., & Klimmer, O. (1936). [On the toxicology of organic solvents. 1,4 dioxane 

9 (diethylene dioxide)]. Archiv fuer Gewerbepathologie und Gewerbehygiene, 17, 192-206. 

10 Wolfe, N. L., & Jeffers, P. M. (2000). Hydrolysis. In R. S. Boethling & D. Mackay (Eds.), 

11 Handbook of Property Estimation Methods for Chemicals: Environmental and Health 

12 Sciences (pp. 311-333). Boca Raton, FL: Lewis Publishers.

13 Wolford, S. T., Schroer, R. A., Gohs, F. X., Gallo, P. P., Brodeck, M., Falk, H. B., & Ruhren, R. 

14 (1986). Reference range data base for serum chemistry and hematology values in 

15 laboratory animals. Journal of Toxicology and Environmental Health, Part A: Current 

16 Issues, 18(2), 161-188. doi: 10.1080/15287398609530859

17 Woo, Y. T., Arcos, J. C., Argus, M. F., Griffin, G. W., & Nishiyama K. (1977). Structural 

18 identification of p-dioxane-2-one as the major urinary metabolite of p-dioxane. Naunyn19 Schmiedeberg's Archives of Pharmacology, 299(3), 283-287. doi: 10.1007/bf00500322

20 Woo, Y. T., Argus, M. F., & Arcos, J. C. (1977a). Metabolism in vivo of dioxane: Effect of 

21 inducers and inhibitors of hepatic mixed-function oxidases. Biochemical Pharmacology, 

22 26(16), 1539-1542. doi: 10.1016/0006-2952(77)90431-2

23 Woo, Y. T., Argus, M. F., & Arcos, J. C. (1977b). Tissue and subcellular distribution of 3H24 dioxane in the rat and apparent lack of microsome-catalyzed covalent binding in the 

25 target tissue. Life Sciences, 21(10), 1447-1456. doi: 10.1016/0024-3205(77)90199-0

26 Woo, Y. T., Argus, M. F., & Arcos, J. C. (1978). Effect of mixed-function oxidase modifiers on 

27 metabolism and toxicity of the oncogen dioxane. Cancer Research, 38(6), 1621-1625. 

28 Yamamoto, S., Ohsawa, M., Nishizawa, T., Saito, A., Kasai, T., Noguchi, T., . . . Matsushima, T. 

29 (2000). Long-term toxicology study of 1,4-Dioxane in the F344 rats by multiple-route 

30 exposure (drinking water and inhalation). Journal of Toxicological Sciences, 25(4), 347. 

31 Yamamoto, S., Urano, K., Koizumi, H., Wakana, S., Hioki, K., Mitsumori, K., . . . Nomura T. 

32 (1998). Validation of transgenic mice carrying the human prototype c-Ha-ras gene as a 

33 bioassay model for rapid carcinogenicity testing. Environmental Health Perspectives, 

34 106(S1), 57-69. 

35 Yamamoto, S., Urano, K., & Nomura, T. (1998). Validation of transgenic mice harboring the 

36 human prototype c-Ha-ras gene as a bioassay model for rapid carcinogenicity testing. 

37 Toxicology Letters, 102-103(S1), 473-478. doi: 10.1016/s0378-4274(98)00341-5

38 Yamazaki, K. (2006). [Correspondence between Kazunori Yamazaki and Julie Stickney].

39 Yamazaki, K., Ohno, H., Asakura, M., Narumi, A., Ohbayashi, H., Fujita, H., . . . Sakabe, H. 

40 (1994). Two-year toxicological and carcinogenesis studies of 1,4-dioxane in F344 rats 

41 and BDF1 mice. In K. Sumino, S. Sato & N. G. Shinkokai (Eds.), Proceedings: Second 

42 Asia-Pacific Symposium on Environmental and Occupational Health 22-24 July, 1993: 

43 Kobe (pp. 193-198). Kobe, Japan: Kobe University School of Medicine, International 

44 Center for Medical Research.

45 Yant, W. P., Schrenk, H. H., Waite, C. P., & Patty, F. A. (1930). Acute response of guinea pigs 

46 to vapors of some new commercial organic compounds: VI. Dioxan. Public Health 

47 Reports, 45, 2023-2032. 

48 Yasuhara, A., Shiraishi, H., Nishikawa, M., Yamamoto, T., Uehiro, T., Nakasugi, O., . . . Noma, 

49 Y. (1997). Determination of organic components in leachates from hazardous waste 
161

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 disposal sites in Japan by gas chromatography-mass spectrometry. Journal of 

2 Chromatography A, 774(1-2), 321-332. doi: 10.1016/s0021-9673(97)00078-2

3 Yasuhara, A., Tanaka, Y., Tanabe, A., Kawata, K., & Katami, T. (2003). Elution of 1,4-dioxane 

4 from waste landfill sites. Bulletin of Environmental Contamination and Toxicology, 

5 71(3), 641-647. doi: 10.1007/s00128-003-8917-7

6 Yoon, J. S., Mason, J. M., Valencia, R., Woodruff, R. C., & Zimmering, S. (1985). Chemical 

7 mutagenesis testing in Drosophila. IV. Results of 45 coded compounds tested for the 

8 National Toxicology Program. Environmental Mutagenesis, 7(3), 349-367. doi: 

9 10.1002/em.2860070310

10 Young, J. D., Braun, W. H., & Gehring, P. J. (1978a). The dose-dependent fate of 1,4-dioxane in 

11 rats. Journal of Environmental Pathology and Toxicology, 2(2), 263-282. doi: 

12 10.1080/15287397809529693

13 Young, J. D., Braun, W. H., & Gehring, P. J. (1978b). Dose-dependent fate of 1,4-dioxane in 

14 rats(b). Journal of Toxicology and Environmental Health, Part A: Current Issues, 4(5), 

15 709-726. doi: 10.1080/15287397809529693

16 Young, J. D., Braun, W. H., Gehring, P. J., Horvath, B. S., & Daniel, R. L. (1976). 1,4-Dioxane 

17 and beta-hydroxyethoxyacetic acid excretion in urine of humans exposed to dioxane 

18 vapors. Toxicology and Applied Pharmacology, 38(3), 643-646. doi: 10.1016/0041-

19 008x(76)90195-2

20 Young, J. D., Braun, W. H., Rampy, L. W., Chenoweth, M. B., & Blau, G. E. (1977). 

21 Pharmacokinetics of 1,4-dioxane in humans. Journal of Toxicology and Environmental 

22 Health, 3(3), 507-520. doi: 10.1080/15287397709529583

23 Zimmermann, F. K., Mayer, V. W., Scheel, I., & Resnick, M. A. (1985). Acetone, methyl ethyl 

24 ketone, ethyl acetate, acetonitrile and other polar aprotic solvents are strong inducers of 

25 aneuploidy in Saccharomyces cerevisiae. Mutation Research, 149(3), 339-351. doi: 

26 10.1016/0027-5107(85)90150-2

27
A-1

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC

COMMENTS AND DISPOSITION

1 Note: The comments and responses in this appendix were in regards to the oral 

2 assessment previously reviewed. A summary of external peer review and public comments and 

3 disposition following review of the inhalation assessment for 1,4-dioxane will be included when 

4 they become available.

5 The Toxicological Review of 1,4-Dioxane has undergone formal external peer review 

6 performed by scientists in accordance with EPA guidance on peer review (U.S. EPA, 2000b, 

7 2006b). The external peer reviewers were tasked with providing written answers to general 

8 questions on the overall assessment and on chemical-specific questions in areas of scientific 

9 controversy or uncertainty. A summary of significant comments made by the external reviewers 

10 and EPA‘s responses to these comments arranged by charge question follow. In many cases the 

11 comments of the individual reviewers have been synthesized and paraphrased for development of 

12 Appendix A. The majority of the specific observations (in addition to EPA‘s charge questions) 

13 made by the peer reviewers were incorporated into the document and are not discussed further in 

14 this Appendix. Public comments that were received are summarized and addressed following the 

15 peer-reviewers‘ comments and disposition.

A.1. EXTERNAL PEER REVIEW PANEL COMMENTS

16 The reviewers made several editorial suggestions to clarify portions of the text. These 

17 changes were incorporated in the document as appropriate and are not discussed further.

18 In addition, the external peer reviewers commented on decisions and analyses in the 

19 Toxicological Review of 1,4-Dioxane under multiple charge questions, and these comments were 

20 organized and summarized under the most appropriate charge question.

A.1.1. General Charge Questions 

21 1. Is the Toxicological Review logical, clear and concise? Has EPA accurately, clearly and 

22 objectively represented and synthesized the scientific evidence for noncancer and cancer 

23 hazards?

24 Comment: All reviewers found the Toxicological Review to be logical, clear, and concise. 

25 One reviewer remarked that it was an accurate, open-minded and balanced analysis of the 

26 literature. Most reviewers found that the scientific evidence was presented objectively 

27 and transparently; however, one reviewer suggested two things to improve the objectivity 

 

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

1 and transparency (1) provide a clear description of the mode of action and how it feeds 

2 into the choice of the extrapolation for the cancer endpoint and (2) provide a presentation 

3 of the outcome if internal dose was used in the cancer and noncancer assessments.

4 One reviewer commented that conclusions could not be evaluated in a few places 

5 where dose information was not provided (Sections 3.2, 3.3 and 4.5.2.2). The same 

6 reviewer found the MOA schematics, key event temporal sequence/dose-response table, 

7 and the POD plots to be very helpful in following the logic employed in the assessment.

8

9 Response: The mode of action analysis and how conclusions from that analysis fed into 

10 the choice of extrapolation method for the cancer assessment are discussed further under 

11 charge questions C2 and C5. Because of the decision not to utilize the PBPK models, 

12 internal doses were not calculated and thus were not included as alternatives to using the 

13 external dose as the POD for the cancer and noncancer assessments.

14 In the sections noted by the reviewer (3.2, 3.3, and 4.5.2.2) dose information was 

15 added as available. In Section 3.2, Mikheev et al. (1990) did not report actual doses, 

16 which is noted in this section. All other dose information in this section was found to be 

17 present after further review by the Agency. In Section 3.3, dose information for Woo 

18 et al. (1977a; 1978) was added to the paragraph. In Section 4.5.2.2, study details for 

19 Nannelli et al. (2005) were provided earlier in Section 3.3 and a statement referring the 

20 reader to this section was added.

21

22 2. Please identify any additional studies that should be considered in the assessment of the 

23 noncancer and cancer health effects of 1,4-dioxane.

24 Comment: Five reviewers stated they were unaware of any additional studies available to 

25 add to the oral toxicity evaluation of 1,4-dioxane. These reviewers also acknowledged 

26 the Kasai et al. (2009; 2008) publications that may be of use to derive toxicity values 

27 following inhalation of 1,4-dioxane. 

28 a. Kasai T; Saito H; Senoh Y; et al. (2008) Thirteen-week inhalation toxicity of 

29 1,4-dioxane in rats. Inhal Toxicol 20: 961-971.

30 b. Kasai T; Kano Y; Umeda T; et al. (2009) Two-year inhalation study of 

31 carcinogenicity and chronic toxicity of 1,4-dioxane in male rats. Inhal Toxicol in 

32 press.

33 Other references suggested by reviewers include:

34 c. California Department of Health Services (1989) Risk Specific Intake Levels for 

35 the Proposition 65 Carcinogen 1, 4-dioxane. Reproductive and Cancer Hazard 

36 Assessment Section. Office of Environmental Health Hazard Assessment
A-3

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 d. National Research Council (2009) Science and Decisions: Advancing Risk 

2 Assessment. Committee on Improving Risk Analysis Approaches Used by the 

3 U.S. EPA. Washington, D.C., National Academy Press. 

4 e. ATSDR (2007) Toxicological Profile for 1,4-dioxane. Agency for Toxic 

5 Substances and Disease Registry. Atlanta, GA.

6 f. Stickney JA; Sager SL; Clarkson JR; et al. (2003) An updated evaluation of the 

7 carcinogenic potential of 1,4-dioxane. Regul Toxicol Pharmacol 38: 183-195.

8 g. Yamamoto S; Ohsawa M; Nishizawa T; et al. (2000) Long-term toxicology 

9 study of 1,4-dioxane in R344 rats by multiple-route exposure (drinking water and 

10 inhalation). J Toxicol Sci 25: 347.

11

12 Response: The references a-b above will be evaluated for derivation of an RfC and IUR, 

13 which will follow as an update to this oral assessment. References c and e noted above 

14 were considered during development of this assessment as to the value they added to the 

15 cancer and noncancer analyses. Reference g listed above is an abstract from conference 

proceedings from the 27th 16 Annual Meeting of the Japanese Society of Toxicology; 

17 abstracts are not generally considered in the development of an IRIS assessment. 

18 Reference d reviews EPA‘s current risk assessment procedures and provides no specific 

19 information regarding 1,4-dioxane. The Stickney et al. (2003) reference was a review 

20 article and no new data were presented, thus it was not referenced in this Toxicological 

21 Review but the data were considered during the development of this assessment. 

22 Following external peer review (as noted above) Kano et al. (2009) was added to 

23 the assessment, which was an update and peer-reviewed published manuscript of the 

24 JBRC (1998) report.

25

26 3. Please discuss research that you think would be likely to increase confidence in the database 

27 for future assessments of 1,4-dioxane.

28 Comment: All reviewers provided suggestions for additional research that would 

29 strengthen the assessment and reduce uncertainty in several areas. The following is a 

30 brief list of questions that were identified that could benefit from further research. What 

31 are the mechanisms responsible for the acute and chronic nephrotoxicity? Is the acute 

32 kidney injury (AKI) multifactorial? Are there both tubular and glomerular/vascular 

33 toxicities that result in cortical tubule degeneration and evidence for glomerulonephritis? 

34 What are the functional correlates of the histologic changes in terms of assessment of 

35 renal function? What is the exposure in utero and risk to the fetus and newborn? What are 

36 the concentrations in breast milk following maternal exposure to 1,4-dioxane? What is 

37 the risk for use of contaminated drinking water to reconstitute infant formula? What are 
A-4

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 the exposures during early human development? What is the pharmacokinetic and 

2 metabolic profile of 1,4-dioxane during development? What are the susceptible 

3 populations (e.g., individuals with decreased renal function or chronic renal disease, 

4 obese individuals, gender, age)?

5 Additional suggestions for future research include: evaluation of potential 

6 epigenetic mechanisms of carcinogenicity, additional information on sources of exposure 

7 and biological concentrations as well as human toxicokinetic data for derivation of 

8 parameter to refine PBPK model, studies to determine toxic moiety, focused studies to 

9 inform mode of action, additional inhalation studies and a multigeneration reproductive 

10 toxicity study.

11 One reviewer suggested additional analyses of the existing data including a 

12 combined analysis of the multiple datasets and outcomes for cancer and non-cancer 

13 endpoints, evaluation of the dose metrics relevant to the MOA to improve confidence in 

14 extrapolation approach and uncertainty factors, and complete a Bayesian analysis of

15 human pharmacokinetic data to estimate human variability in key determinants of 

16 toxicity (e.g., metabolic rates and partition coefficients).

17

18 Response: A number of research suggestions were provided for further research that may 

19 enhance future health assessments of 1,4-dioxane. Regarding the suggested additional 

20 analyses for the existing data, EPA did not identify a MOA in this assessment, thus 

21 combined analysis of the cancer and non-cancer endpoints as well as application of 

22 various dose metrics to a MOA is not applicable. Because the human PBPK model was 

23 not implemented in this assessment for oral exposure to 1,4-dioxane a Bayesian analysis 

24 was not completed. No additional changes to the Toxicological Review of 1,4-Dioxane

25 were made in response to these research recommendations.

26

27 4. Please comment on the identification and characterization of sources of uncertainty in 

28 Sections 5 and 6 of the assessment document. Please comment on whether the key sources of 

29 uncertainty have been adequately discussed. Have the choices and assumptions made in the 

30 discussion of uncertainty been transparently and objectively described? Has the impact of the 

31 uncertainty on the assessment been transparently and objectively described?

32 Comment: Six reviewers stated Sections 5 and 6 adequately discussed and characterized 

33 uncertainty, in a succinct, and transparent manner. One reviewer suggested adding 

34 additional discussion of uncertainty relating to the critical study used in the cancer 

35 assessment and another reviewer suggested adding more discussion around the 

36 uncertainty of the toxic moiety.
A-5

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 One reviewer made specific comments on uncertainty surrounding the Kociba et 

2 al. (1974) study as used for derivation of the RfD, choice of the non-cancer dose metric, 

3 and use of a 10%BMR as the basis for the CSF derivation. These comments and 

4 responses are summarized below under their appropriate charge question.

5

6 Response: The majority of the reviewers thought the amount of uncertainty discussion 

7 was appropriate. Since the external review, Kano et al. (2009) was published and this 

8 assessment was updated accordingly (previously JBRC (1998). It is assumed the 

9 uncertainty referred to by the reviewer was addressed by the published Kano et al. (2009)

10 paper.

11 Clarification regarding the uncertainty surrounding the identification of the toxic 

12 moiety was added to Section 4.6.3 stating that the mechanism by which 1,4-dioxane 

13 induces tissue damage is not known, nor is it known whether the toxic moiety is 

14 1,4-dioxane or a metabolite of 1,4-dioxane. Additional text was added to Section 4.7.3 

15 clarifying that available data also do not clearly identify whether 1,4-dioxane or one of its 

16 metabolites is responsible for the observed effects. The impact of the lack of evidence to 

17 clearly identify a toxic moiety related to 1,4-dioxane exposure was summarized in 

18 Sections 5.5.1.2 and 6.2.3.2.

A.1.2. Oral reference dose (RfD) for 1,4-dioxane

19 1. A chronic RfD for 1,4-dioxane has been derived from a 2-year drinking water study (Kociba, 

20 et al., 1974) in rats and mice. Please comment on whether the selection of this study as the 

21 principal study has been scientifically justified. Has the selection of this study been 

22 transparently and objectively described in the document? Are the criteria and rationale for 

23 this selection transparently and objectively described in the document? Please identify and 

24 provide the rationale for any other studies that should be selected as the principal study.

25 Comment: Seven of the reviewers agreed that the use of the Kociba et al. (1974) study 

26 was the best choice for the principal study. 

27 One reviewer stated that Kociba et al. (1974) was not the best choice because it 

28 reported only NOAEL and LOAELs without providing incidence data for the endpoints. 

29 This reviewer also stated that the study should not have been selected based on sensitivity 

30 of the endpoints, but rather study design and adequacy of reporting of the study results. 

31 Additionally, this reviewer suggested a better principal study would be either the NCI 

32 (1978) or JBRC (1998) study.

33

34 Response: The reviewer is correct that Kociba et al. (1974) did not provide incidence 

35 data; however, Kociba et al. (1974) identified a NOAEL (9.6 mg/kg-day) and LOAEL 

36 (94 mg/kg-day) within the text of the manuscript. Kociba et al. (1974) was a well 
A-6

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 conducted chronic bioassay (four dose levels, including controls, with 60 rats/sex/group) 

2 and seven of the peer reviewers found this study to be appropriate as the basis for the 

3 RfD. Further support for the selection of the Kociba et al. (1974) as the principal study 

4 comes from comparison of the liver and kidney toxicity data reported by JBRC (1998)

5 and NCI (1978), which was presented in Section 5.1. The effects reported by JBRC 

6 (1998) and NCI (1978) were consistent with what was observed by Kociba et al. (1974)

7 and within a similar dose range. Derivation of an RfD from these datasets resulted in a 

8 similar value (Section 5.1.).

9

10 2. Degenerative liver and kidney effects were selected as the critical effect. Please comment on 

11 whether the rationale for the selection of this critical effect has been scientifically justified. 

12 Are the criteria and rationale for this selection transparently and objectively described in the 

13 document? Please provide a detailed explanation. Please comment on whether EPA‘s 

14 rationale regarding adversity of the critical effect for the RfD has been adequately and 

15 transparently described and is scientifically supported by the available data. Please identify 

16 and provide the rationale for any other endpoints that should be considered in the selection of 

17 the critical effect.

18 Comment: Five of the reviewers agreed with the selection of liver and kidney effects as 

19 the critical effect. One of these reviewers suggested analyzing all datasets following dose 

20 adjustment (e.g., body weight scaling or PBPK model based) to provide a better rationale 

21 for selection of a critical effect.

22 One reviewer stated that 1,4-dioxane causing liver and kidney organ specific 

23 effects is logical; however, with regards to nephrotoxicity, the models and limited human 

24 data have not addressed the mechanisms of injury or the clinical correlates to the 

25 histologic data. Also, advances in the field of biomarkers have not yet been used for the 

26 study of 1,4-dioxane.

27 One reviewer found the selection of these endpoints to be  ̳without merit‘ because 

28 of the lack of incidence data to justify the NOAEL and LOAEL values identified in the 

29 study. This reviewer suggested selecting the most sensitive endpoint(s) from the NCI 

30 (NCI, 1978) or JBRC (1998) studies for the basis of the RfD, but did not provide a 

31 suggestion as to what effect should be selected.

32

33 Response: The liver and kidney effects from Kociba et al. (1974) was supported as the 

34 critical effect by most of the reviewers. PBPK model adjustment was not performed 

35 because the PBPK model was found to be inadequate for use in the assessment. EPA 

36 acknowledges that neither the mechanisms of injury nor the clinical correlates to 
A-7

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 histologic data exist for 1,4-dioxane. This type of information could improve future 

2 health assessments of 1,4-dioxane. 

3 As stated above, Kociba et al. (1974) identified a NOAEL (9.6 mg/kg-day) and 

4 LOAEL (94 mg/kg-day) within the text of the manuscript and was a well conducted 

5 chronic bioassay (four dose levels, including controls, with 60 rats/sex/group). 

6

7 3. Kociba et al. (1974) derived a NOAEL based upon the observation of degenerative liver and 

8 kidney effects and these data were utilized to derive the point of departure (POD) for the 

9 RfD. Please provide comments with regard to whether the NOAEL approach is the best 

10 approach for determining the POD. Has the approach been appropriately conducted and 

11 objectively and transparently described? Please identify and provide rationales for any 

12 alternative approaches for the determination of the POD and discuss whether such 

13 approaches are preferred to EPA‘s approach.

14 Comment: Seven reviewers agreed with the NOAEL approach described in the 

15 document. One of these reviewers also questioned whether any attempt was made to

16 ―semi-qualitatively represent the histopathological observations to facilitate a quantitative 

17 analysis‖.

18 One reviewer stated that data were not used to derive the POD, but rather a claim 

19 by the authors of Kociba et al. (1974) of the NOAEL and LOAEL for the endpoints. This 

20 reviewer preferred the use of a BMD approach for which data include the reported 

21 incidence rather than a study reported NOAEL or LOAEL.

22

23 Response: The suggestion to ―semi-qualitatively represent the histopathological 

24 observations to facilitate a quantitative analysis‖ was not incorporated into the document 

25 because it is unclear how this would be conducted since Kociba et al. (1974) did not 

26 provide incidence data and the reviewer did not illustrate their suggested approach. See 

27 responses to B1 and B2 regarding the NOAEL and LOAEL approach. The Agency 

28 agrees that a Benchmark Dose approach is preferred over the use of a NOAEL or 

29 LOAEL for the POD if suitable data (e.g., reflecting the most sensitive sex, species, and 

30 endpoint identified) are available for modeling and, if suitable data are not available, then 

31 NOAEL and LOAEL values are utilized. In this case, the data were not suitable for 

32 BMD modeling and the LOAEL or NOAEL approach was used. 

33

34 4. EPA evaluated the PBPK and empirical models available to describe kinetics following 

35 inhalation of 1,4-dioxane (Reitz, et al., 1990; Young, et al., 1978a; Young, et al., 1978b; 

36 Young, et al., 1977). EPA concluded that the use of existing, revised, and recalibrated PBPK 

37 models for 1,4-dioxane were not superior to default approaches for the dose-extrapolation 
A-8

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 between species. Please comment on whether EPA‘s rationale regarding the decision to not 

2 utilize existing or revised PBPK models has been adequately and transparently described and 

3 is supported by the available data. Please identify and provide the rationale for any 

4 alternative approaches that should be considered or preferred to the approach presented in the 

5 toxicological review.

6 Comment: Six reviewers found the decision not to utilize the available PBPK models to 

7 be appropriate and supported by available data. One of these reviewers suggested 

8 presenting as part of the uncertainty evaluation an adjustment of the experimental doses 

9 based on metabolic saturation. Another reviewer stated Appendix B was hard to follow 

10 and that the main document should include a more complete description of the model 

11 refinement effort performed by Sweeney et al. (2008).

12 Two reviewers noted a complete evaluation of the models was evident; one of the 

13 reviewers questioned the decision not to use the models on the basis that they were 

14 unable to fit the human blood PK data for 1,4-dioxane. This reviewer suggested the rat 

15 model might fit the human blood PK data, thus raising concern in the reliance on the 

16 human blood PK data to evaluate the PBPK model for 1,4-dioxane. Instead, the reviewer 

17 suggested the human urinary metabolite data may be sufficient to give confidence in the 

18 model. One other reviewer also questioned the accuracy of the available human data. 

19 One reviewer commented that the rationale for not using the PBPK model to extrapolate 

20 from high to low dose was questioned. In addition, the reviewer suggested that two 

21 aspects of the model code for Reitz et al. (1990) need to be verified:

22 a. In the document, KLC is defined as a first-order rate constant and is scaled by 

BW0.7 23 . This is inconsistent when multiplied by concentration does not result 

24 in units of mg/hr. However, if the parameter is actually considered a 

25 clearance constant (zero-order rate constant) then the scaling rule used, as well 

26 as the interpretations provided, would be acceptable.

27 b. It is unclear as to why AM is calculated on the basis of RAM and not RMEX. 

28 RMEX seems to represent the amount metabolized per unit time.

29

30 Response: The USEPA performed a rigorous evaluation of the PBPK models available 

31 for 1,4-dioxane. This effort was extensively described in Section 3.5 and in Appendix B. 

32 In short, several procedures were applied to the human PBPK model to determine if an 

33 adequate fit of the model to the empirical model output or experimental observations 

34 could be attained using biologically plausible values for the model parameters. The re35 calibrated model predictions for blood 1,4-dioxane levels did not come within 10-fold of 

36 the experimental values using measured tissue:air partition coefficients of (Leung & 

37 Paustenbach, 1990) or (Sweeney, et al., 2008) (Figures B-8 and B-9). The utilization of a 
A-9

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 slowly perfused tissue:air partition coefficient 10-fold lower than measured values 

2 produces exposure-phase predictions that are much closer to observations, but does not 

3 replicate the elimination kinetics (Figure B-10). Re-calibration of the model with upper 

4 bounds on the tissue:air partition coefficients results in predictions that are still six- to 

5 sevenfold lower than empirical model prediction or observations (Figures B-12 and B6 13). Exploration of the model space using an assumption of first-order metabolism (valid 

7 for the 50 ppm inhalation exposure) showed that an adequate fit to the exposure and 

8 elimination data can be achieved only when unrealistically low values are assumed for 

9 the slowly perfused tissue:air partition coefficient (Figure B-16). Artificially low values 

10 for the other tissue:air partition coefficients are not expected to improve the model fit, as 

11 these parameters are shown in the sensitivity analysis to exert less influence on blood 

12 1,4-dioxane than VmaxC and Km. In the absence of actual measurements for the human 

13 slowly perfused tissue:air partition coefficient, high uncertainty exists for this model 

14 parameter value. Differences in the ability of rat and human blood to bind 1,4-dioxane 

15 may contribute to the difference in Vd. However, this is expected to be evident in very 

16 different values for rat and human blood:air partition coefficients, which is not the case 

17 (Table B-1). Therefore, some other, as yet unknown, modification to model structure 

18 may be necessary.

19 The results of USEPA‘s model evaluation were confirmed by other investigators 

20 (Sweeney, et al., 2008). Sweeney et al. (2008) concluded that the available PBPK model 

21 with refinements resulted in an under-prediction of human blood levels for 1,4-dioxane 

22 by six- to seven fold. It is anticipated that the high uncertainty in predictions of the 

23 PBPK model for 1,4-dioxane would not result in a more accurate derivation of human 

24 health toxicity values.

25 Because it is unknown whether the parent or the metabolite is the toxic moiety, 

26 analyses were not conducted to adjust the experimental doses on the basis of metabolic 

27 saturation.

28 The discussion of Sweeney et al. (2008) was expanded in the main document in 

29 Section 3.5.3. In the absence of evidence to the contrary, the Agency cannot discount the 

30 human blood kinetic data published by Young et al. (1977). Even though the PBPK 

31 model provided satisfactory fits to the rodent kinetic data, it was not used to extrapolate 

32 from high dose to low dose in the animal because an internal dose metric was not 

33 identified and external doses were utilized in derivation of the toxicity values.

34 KLC was implemented by USEPA during the evaluation of the model and should 

35 have been described as a clearance constant (zero-order rate constant) with units of 

L/hr/kg0.70 36 . These corrections have been made in the document; however, this does not 
A-10

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 impact the model predictions because it was in reference to the terminology used to 

2 describe this constant.

3 The reviewer is correct that RMEX is the rate of metabolism of 1,4-dioxane per 

4 unit time; however an amount of 1,4-dioxane metabolized was not calculated in the Reitz 

5 et al. (1990) model code. Thus, AM is the amount of the metabolite (i.e., HEAA) in the 

6 body rather than the amount metabolized of 1,4-dioxane. RAM was published by Reitz 

7 et al. (1990) as equation 2 for the change in the amount of metabolite in the body per unit 

8 time. AMEX is the amount of the metabolite excreted in the urine. While the variables 

9 used are confusing, the code describes the metabolism of 1,4-dioxane as published in the 

10 manuscripts. The comments in the model code were updated to make this description 

11 more clear (Appendix B).

12

13 5. Please comment on the selection of the uncertainty factors applied to the POD for the 

14 derivation of the RfD. For instance, are they scientifically justified and transparently and 

15 objectively described in the document? If changes to the selected uncertainty factors are 

16 proposed, please identify and provide a rationale(s). Please comment specifically on the 

17 following uncertainty factors:

18 An interspecies uncertainty factor of 10 was used to account for uncertainties in 

19 extrapolating from laboratory animals to humans because a PBPK model to support 

20 interspecies extrapolation was not suitable.

21 An intraspecies (human variability) uncertainty factor of 10 was applied in deriving the 

22 RfD because the available information on the variability in human response to 

23 1,4-dioxane is considered insufficient to move away from the default uncertainty factor 

24 of 10.

25 A database uncertainty factor of 3 was used to account for lack of adequate 

26 reproductive toxicity data for 1,4-dioxane, and in particular absence of a 

27 multigeneration reproductive toxicity study. Has the rationale for the selection of these 

28 uncertainty factors been transparently and objectively described in the document? 

29 Please comment on whether the application of these uncertainty factors has been 

30 scientifically justified.

31

32 Comment: 

33 One reviewer noted the uncertainty factors appear to be the standard default choices and 

34 had no alternatives to suggest.

35 o Five reviewers agreed that the use of an uncertainty factor of 10 for the interspecies 

extrapolation is fully supportable. One reviewer suggested using BW3/4 36 scaling 

37 rather than an uncertainty factor of 10 for animal to human extrapolation. Along 
A-11

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 the same lines, one reviewer suggested a steady-state quantitative analysis to 

2 determine the importance of pulmonary clearance and hepatic clearance and stated 

3 that if hepatic clearance scales to body surface and pulmonary clearance is 

4 negligible, then an adjusted uncertainty factor based on body surface scaling would 

5 be more appropriate.

6 o Seven reviewers stated that the uncertainty factor of 10 for interindividual 

7 variability (intraspecies) is fully supportable.

8 o Six reviewers commented that the uncertainty factor of 3 for database deficiencies 

9 is fully justifiable. One reviewer suggested adding text to clearly articulate the 

10 science policy for the use of a factor of 3 for database deficiencies.

11

12 Response: The preferred approach to interspecies scaling is the use of a PBPK model; 

13 however, the PBPK models available for 1,4-dioxane are not suitable for use in this 

14 health assessment as outlined elsewhere. Another approach that has been commonly 

15 implemented in the cancer assessments is the use of body weight scaling based on body 

surface area (BW3/4 scaling). It is not standard practice to apply BW3/4 16 scaling in 

17 noncancer assessments at this time. The current default approach used by the Agency 

18 when PBPK models are not available for extrapolation is the application of an UFA of 10, 

19 which was implemented in this assessment. 

20 The absence of a multigenerational reproductive study is why the uncertainty 

21 factor for database deficiencies (UFD) was retained; however, it was reduced from 10 to 

22 3. In the text in Section 5.1.3 text was included to clearly state that because of the 

23 absence of a multigenerational reproductive study for 1,4-dioxane an uncertainty factor of 

24 3 was used for database deficiencies. No other changes regarding the use of the 

25 uncertainty factors were made to the document.

A.1.3. Carcinogenicity of 1,4-dioxane

26 1. Under the EPA‘s 2005 Guidelines for Carcinogen Risk Assessment 

27 (www.epa.gov/iris/backgr-d.htm), the Agency concluded that 1,4-dioxane is likely to be 

28 carcinogenic to humans. Please comment on the cancer weight of evidence characterization. 

29 Has the scientific justification for the weight of evidence descriptor been sufficiently, 

30 transparently and objectively described? Do the available data for both liver tumors in rats 

31 and mice and nasal, mammary, and peritoneal tumors in rats support the conclusion that 

32 1,4-dioxane is a likely human carcinogen?

33 Comment: All reviewers agreed with the Agency‘s conclusion that 1,4-dioxane is ―likely 

34 to be carcinogenic to humans‖. However, two reviewers also thought 1,4-dioxane could 

35 be categorized as a potential human carcinogen, since low-dose environmental exposures 

36 would be unlikely to result in cancer. One reviewer also suggested providing a brief 
A-12

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 recapitulation of the guidance provided by the 2005 Guidelines for Carcinogen Risk 

2 Assessment regarding classification of a compound as likely to be carcinogenic to 

3 humans and how a chemical falls into this category.

4

5 Response: The document includes a weight-of-evidence approach to categorize the 

6 carcinogenic potential of 1,4-dioxane. This was included in Section 4.7.1 based upon 

7 U.S. EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). 1,4-Dioxane 

8 can be described as likely to be carcinogenic to humans based on evidence of liver 

9 carcinogenicity in several 2-year bioassays conducted in three strains of rats, two strains 

10 of mice, and in guinea pigs. Additionally, tumors in other organs and tissues have been 

11 observed in rats due to exposure to 1,4-dioxane. 

12

13 2. Evidence indicating the mode of action of carcinogenicity of 1,4-dioxane was considered. 

14 Several hypothesized MOAs were evaluated within the Toxicological Review and EPA 

15 reached the conclusion that a MOA(s) could not be supported for any tumor types observed 

16 in animal models. Please comment on whether the weight of the scientific evidence supports 

17 this conclusion. Please comment on whether the rationale for this conclusion has been 

18 transparently and objectively described. Please comment on data available for 1,4-dioxane 

19 that may provide significant biological support for a MOA beyond what has been described 

20 in the Toxicological Review. Considerations should include the scientific support regarding 

21 the plausibility for the hypothesized MOA(s), and the characterization of uncertainty 

22 regarding the MOA(s).

23 Comment: Three reviewers commented that the weight of evidence clearly supported the 

24 conclusion that a mode of action could not be identified for any of the tumor sites. One 

25 reviewer commented that there is inadequate evidence to support a specific MOA with 

26 any confidence and low-dose linear extrapolation is necessary; this reviewer also pointed 

27 out that EPA should not rule out a metabolite as the toxic moiety. 

28 One reviewer stated this was outside of his/her area of expertise but indicated that 

29 the discussion was too superficial and suggested adding statements as to what the Agency 

30 would consider essential information to make a determination about a MOA. 

31 Two reviewers commented that even though the MOA for 1,4-dioxane is not clear 

32 there is substantial evidence that the MOA is non-genotoxic. One of these reviewers also

33 suggested that a nonlinear cancer risk assessment model should be utilized.

34 One reviewer suggested adding more text to the summary statement to fully 

35 reflect the available MOA information which should be tied to the conclusion and choice 

36 of an extrapolation model.

37
A-13

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Response: The Agency agrees with the reviewer not to rule out a toxic metabolite as the 

2 toxic moiety. In Section 5.5.1.2 text is included relating that there is not enough 

3 information to determine whether the parent compound, its metabolite(s), or a 

4 combination is responsible for the observed toxicities following exposure to 1,4-dioxane.

5 It is not feasible to describe the exact data that would be necessary to conclude 

6 that a particular MOA was operating to induce the tumors observed following 

7 1,4-dioxane exposure. In general, the data would fit the general criteria described in the 

8 U.S. EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). For 

9 1,4-dioxane, several MOA hypotheses have been proposed and are explored for the 

10 observed liver tumors in Section 4.7.3. This analysis represents the extent to which data 

11 could provide support for any particular MOA.

12 One reviewer suggested that the evidence indicating that 1,4-dioxane is not 

13 genotoxic supports a nonlinear approach to low-dose extrapolation. In accordance with

14 the U.S. EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), the 

15 absence of evidence for genotoxicity does not invoke the use of nonlinear low-dose 

16 extrapolation, nor does it define a MOA. A nonlinear low-dose extrapolation can be 

17 utilized when a MOA supporting a nonlinear dose response is identified. For 1,4-dioxane 

18 this is not the case; a cancer MOA for any of the tumor types observed in animal models 

19 has not been elucidated. Therefore, as concluded in the Toxicological Review, the 

20 application of a nonlinear low-dose extrapolation approach was not supported.

21 Additional text has been added to Section 5.4.3.2 to relay the fact that several 

22 reviewers recommended that the MOA data support the use of a nonlinear extrapolation 

23 approach to estimate human carcinogenic risk associated with exposure to 1,4-dioxane 

24 and that such an approach should be presented in the Toxicological Review. Additional 

25 text has also been added to the summary statement in Section 6.2.3 stating that the weight 

26 of evidence is inadequate to establish a MOA(s) by which 1,4-dioxane induces peritoneal, 

27 mammary, or nasal tumors in rats and liver tumors in rats and mice (see Section 4.7.3 for 

28 a more detailed discussion of 1,4-dioxane‘s hypothesized MOAs). 

29

30 3. A two-year drinking water cancer bioassay (JBRC, 1998) was selected as the principal study 

31 for the development of an oral slope factor (OSF). Please comment on the appropriateness of 

32 the selection of the principal study. Has the rationale for this choice been transparently and 

33 objectively described?

34 Comment: 

35 Seven reviewers agreed with the choice of the JBRC (1998) study as the principal 

36 study for the development of an OSF. However, two reviewers that agreed with the 

37 choice of JBRC (1998) also commented on the description and evaluation of the study. 
A-14

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 One reviewer commented the evaluation of the study should be separated from the 

2 evaluation/selection of endpoints within the study. The other reviewer suggested that 

3 details on the following aspects should be added to improve transparency of the study: 

4 (1) rationale for selection of doses; (2) temporal information on body weight for 

5 individual treatment groups; (3) temporal information on mortality rates; and (4) dosing 

6 details. 

7 One reviewer thought that the complete rationale for selection of the JBRC (1998)

8 study was not provided because there was no indication of whether the study was 

9 conducted under GLP conditions, and the study was not peer reviewed or published. This 

10 reviewer noted the NCI (1978) study was not appropriate for use, but that the Kociba et 

11 al. (1974) study may have resulted in a lower POD had they employed both sexes of mice 

12 and combined benign and malignant tumors.

13

14 Response: Since the External Peer Review draft of the Toxicological Review of 

15 1,4-Dioxane was released (U.S. EPA, 2009b), the cancer portion of the study conducted 

16 by the JBRC laboratory was published in the peer-reviewed literature as Kano et al. 

17 (2009). This manuscript was reviewed by EPA. EPA determined that the data published 

18 by Kano et al. (2009) should be included in the assessment of 1,4-dioxane for several 

19 reasons: (1) while the JBRC (1998) was a detailed laboratory report, it was not peer20 reviewed; (2) the JBRC improved the diagnosis of pre- and neoplastic lesions in the liver 

21 according to the current diagnostic criteria and submitted the manuscript based on this 

22 updated data; (3) the Kano et al. (2009) peer-reviewed manuscript included additional 

23 information such as body weight growth curves and means and standard deviations of 

24 estimated dose for both rats and mice of both sexes. Thus, the Toxicological Review was 

25 updated to reflect the inclusion of the data from Kano et al. (2009), and Appendix E was 

26 added for a clear and transparent display of the data included in the multiple reports.

27 In response to the peer reviewers, dose information was updated throughout the 

28 assessment and are also provided in detail in Section 4.2.1.2.6, along with temporal 

29 information on body weights and mortality. Text was also added to Section 4.2.1.2.6 

30 regarding the choice of high dose selection as included in the Kano et al. (2009)

31 manuscript. Additional discussion regarding the mortality rates was also added to 

32 Section 5.4.1 in selection of the critical study for the oral cancer assessment. 

33 Documentation that the study was conducted in accordance with Organization for 

34 Economic Co-operation and Development (OECD) Principles of Good Laboratory 

35 Practice (GLP) is provided in the manuscript (Kano, et al., 2009) and this was also added 

36 to the text in Section 4.2.1.2.6.

37
A-15

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 4. Combined liver tumors (adenomas and carcinomas) in female Cjr:BDF1 mice from the JBRC 

2 (1998) study were chosen as the most sensitive species and gender for the derivation of the 

3 final OSF. Please comment on the appropriateness of the selections of species and gender. 

4 Please comment on whether the rationale for these selections is scientifically justified. Has 

5 the rationale for these choices been transparently and objectively described?

6 Comment: Six reviewers agreed the female Cjr:BDF1 mice should be used for the 

7 derivation of the OSF. Five of these reviewers agreed with the rationale for the selection 

8 of the female Cjr:BDF1 mouse as the most sensitive gender and species. However, one 

9 reviewer suggested that the specific rationale (i.e., that the final OSF is determined by 

10 selecting the gender/species that gives the greatest OSF value) be stated clearly in a 

11 paragraph separate from the other considerations of study selection.

12 One reviewer was unsure of both the scientific justification for combining benign 

13 and malignant liver tumors, as well as the background incidence of the observed liver 

14 tumors in historical control Cjr:BDF1 male and female mice.

15 One reviewer commented that the scientific basis for the selection of female 

16 Cjr:BDF1 mice was unclear. This reviewer thought that the rationale for the choice of 

17 this strain/sex compared to all others was not clearly articulated. 

18

19 Response: Using the approach described in the Guidelines for Carcinogen Risk 

20 Assessment (U.S. EPA, 2005a) studies were first evaluated based on their quality and 

21 suitability for inclusion in the assessment. Once the studies were found to be of sufficient 

22 quality for inclusion in the assessment, the dose-response analysis was performed with 

23 the goal of determining the most appropriate endpoint and species for use in the 

24 derivation of an OSF. These topics are discussed in detail in Section 4.7 and 5.4. 

25 Benign and malignant tumors that arise from the same cell type (e.g., 

26 hepatocellular) may be combined to more clearly identify the weight of evidence for a 

27 chemical. This is in accordance with the US EPA‘s 2005 Guidelines for Carcinogen Risk 

28 Assessment as referenced in the Toxicological Review. In the absence of a MOA (MOA 

29 analysis described in detail in Section 4.7.) for 1,4-dioxane carcinogenicity, it is not 

30 possible to determine which species may more closely resemble humans. Text in Section 

31 5.4.4 indicates that the calculation of an OSF for 1,4-dioxane is based upon the dose32 response data for the most sensitive species and gender. 

33

34 5. Has the scientific justification for deriving a quantitative cancer assessment been 

35 transparently and objectively described? Regarding liver cancer, a linear low-dose 

36 extrapolation approach was utilized to derive the OSF. Please provide detailed comments on 

37 whether this approach to dose-response assessment is scientifically sound, appropriately 
A-16

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 conducted, and objectively and transparently described in the document. Please identify and 

2 provide the rationale for any alternative approaches for the determination of the OSF and 

3 discuss whether such approaches are preferred to EPA‘s approach.

4 Comment: Four reviewers agreed with the approach for the dose-response assessment. 

5 One reviewer commented that even if a nongenotoxic MOA were identified for 

6 1,4-dioxane it may not be best evaluated by threshold modeling. One reviewer 

7 commented the use of the female mouse data provided an appropriate health protective 

8 and scientifically valid approach.

9 One reviewer commented that the basic adjustments and extrapolation method for 

10 derivation of the OSF were clearly and adequately described, but disagreed with the 

11 linear low-dose extrapolation. This reviewer suggested that the lack of certainty regarding 

12 the MOA was not a sufficient cause to default to a linear extrapolation. Another reviewer 

13 commented that the rationale for a linear low-dose extrapolation to derive the OSF was 

14 not clear, but may be in accordance with current Agency policy in the absence of a 

15 known MOA. This reviewer also commented that 1,4-dioxane appears to be non16 genotoxic and nonlinear models should be tested on the available data to determine if 

17 they provide a better fit and are more appropriate.

18 One reviewer thought that the justification for a linear extrapolation was not 

19 clearly provided and that a disconnect between the MOA summary and the choice of a 

20 linear extrapolation model existed. In addition, this reviewer commented that the 

21 pharmacokinetic information did not support the use of a linear extrapolation approach, 

22 but rather use of animal PBPK models to extrapolate from high to low dose that would 

23 result in a mixture of linear and nonlinear extrapolation models was warranted.

24 One reviewer suggested consideration of an integrated assessment of the cancer 

25 and noncancer endpoints; however, if linear low-dose extrapolation remains the approach 

26 of choice by the Agency, then the effect of choosing BMRs other than 10% was 

27 recommended to at least be included in the uncertainty discussion. Using BMRs lower 

28 than 10% may allow for the identification of a risk level for which the low-dose slope is 

29  ̳best‘ estimated. 

30

31 Response: The EPA conducted a cancer MOA analysis evaluating all of the 

32 available data for 1,4-dioxane. Application of the framework in the USEPA‘s Guidelines 

33 for Carcinogen Risk Assessment (2005a) demonstrates that the available evidence to 

34 support any hypothesized MOA for 1,4-dioxane-induced tumors does not exist. In the 

35 absence of a MOA, the USEPA‘s Guidelines for Carcinogen Risk Assessment (2005a)

36 indicate that a low dose linear extrapolation should be utilized for dose response analysis 

37 (see Section 5.4). Some of the potential uncertainty associated with this conclusion was 
A-17

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 characterized in Section 5.5. Note that there is no scientific basis to indicate that in the 

2 absence of evidence for genotoxicity a nonlinear low-dose extrapolation should be used. 

3 As concluded in the Toxicological Review, the application of a nonlinear low-dose 

4 extrapolation approach was not supported.

5 With regards to the PBPK model available for 1,4-dioxane, it is clear that there 

6 currently exist deficiencies within the model and as such, the model was not utilized for 

7 interspecies extrapolation. Given the deficiencies and uncertainty in the 1,4-dioxane 

8 model it also does not provide support for a MOA. 

9 Lastly, in the absence of a MOA for 1,4-dioxane carcinogenicity it is not possible 

10 to harmonize the cancer and noncancer effects to assess the risk of health effects due to 

11 exposure. However, the choice of the BMDL10,which was more than 15-fold lower than 

12 the response at the lowest dose (66 mg/kg-day), was reconsidered in response to a public 

13 comment. BMDs and BMDLs were calculated using a BMR of 30 and 50% extra risk 

14 (BMD30, BMDL30, BMD50, and BMDL50). A BMR of 50% was used as it resulted in a 

15 BMDL closest to the response level at the lowest dose tested in the bioassay. 

A.2. PUBLIC COMMENTS

16 Comments on the Toxicological Review of 1,4-Dioxane submitted by the public are summarized 

17 below in the following categories: Oral reference dose for 1,4-dioxane, carcinogenicity of 

18 1,4-dioxane, PBPK modeling, and other comments.

A.2.1. Oral reference dose (RfD) for 1,4-dioxane

19 Comment: An UF for database deficiencies is not necessary because of considerable 

20 evidence showing no reproductive or developmental effects from 1,4-dioxane exposure.

21

22 Response: Due to the lack of a multigenerational reproductive study for 1,4-dioxane an 

23 UF of 3 was retained for database deficiencies. Without clear evidence showing a lack of 

24 reproductive or developmental effects in a multigenerational reproductive study, there is 

25 still uncertainty in this area.

26

A.2.2. Carcinogenicity of 1,4-dioxane

27 Comment: Using liver tumors as the basis for the oral CSF is more appropriate than 

28 nasal tumors (1988 IRIS assessment of 1,4-dioxane); however, the use of mouse liver 

29 tumor data is inappropriate because it is inconsistent with other liver models both 

30 quantitatively and in the dose-response pattern. High mortality rates in the study are also 

31 a limitation. Liver tumor data from rats should be used instead, which represents a better 

32 animal model for 1,4-dioxane carcinogenicity assessment.
A-18

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 Response: Even though the dose-response is different for mice and rats, the female mice 

3 were considered to be appropriate for the carcinogenicity assessment for several reasons. 

4 The female mouse liver tumors from the Kano et al. (2009)report were found to be the 

5 most sensitive species and endpoint. Section 4.2.1.2.6 was updated to include additional 

6 information on mortality rates. The majority of the animals lived past 52 weeks (only 4 

7 females died prior to 52 weeks, 2 in each the mid- and high-dose groups). The cause of 

8 death in the female mice that died between 1 and 2 years was attributed to liver tumors. 

9

10 Comment: The OSF was based on the most sensitive group, Crj:BDF1 mice; however 

11 BDF1 mice have a high background rate of liver tumors. The incidence of liver tumors in 

12 historical controls for this gender/species should be considered in the assessment. 

13 Sensitivity of the test species/gender as well as other criteria should be considered in the 

14 selection of the appropriate study, including internal and external validity as outlined in 

15 Lewandowski and Rhomberg (2005). The female Crj:BDF1 mice had a low survival rate 

16 that should be considered in the selection of the animal model for 1,4-dioxane 

17 carcinogenicity.

18

19 Response: Katagiri et al. (1998) summarized the incidence of hepatocellular adenomas 

20 and carcinomas in control male and female BDF1 mice from ten 2-year bioassays at the 

21 JBRC. For female mice, out of 499 control mice, the incidence rates were 4.4% for 

22 hepatocellular adenomas and 2.0% for hepatocellular carcinomas. Kano et al. (2009)

23 reported a 10% incidence rate for hepatocellular adenomas and a 0% incidence rate for 

24 hepatocellular carcinomas in control female BDF1. These incidence rates are near the 

25 historical control values and thus are appropriate for consideration in this assessment. 

26 Additional text regarding these historical controls was added to the study description in 

27 Section 4.2.1.2.6. 

28

29 Comment: Low-dose linear extrapolation for the oral CSF is not appropriate nor justified 

30 by the data. The weight of evidence supports a threshold (nonlinear) MOA when 

31 metabolic pathway is saturated at high doses. Nonlinear extrapolations should be 

32 evaluated and presented for 1,4-dioxane. Oral CSFs should be derived and presented 

using both the BW3/4 33 scaling as well as available PBPK models to extrapolate across 

34 species.

35

36 Response: The absence of evidence for genotoxicity/mutagenicity does not indicate the 

37 use of nonlinear low-dose extrapolation. For 1,4-dioxane, a MOA to explain the 
A-19

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 induction of tumors does not exist so the nature of the low-dose region of the doseresponse is unknown. The oral CSF for 1,4-dioxane was derived using BW3/4 2 scaling for 

3 interspecies extrapolation. The PBPK and empirical models available for 1,4-dioxane 

4 were evaluated and found not to be adequate for use in this assessment, described in 

5 detail in Appendix B.

6

7 Comment: The POD for the BDF1 female mouse is 15-fold lower than the lowest dose 

8 in the bioassay, thus the POD is far below the lower limit of the data and does not follow 

9 the U.S. EPA‘s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a).

10

11 Response: The comment is correct that the animal BMDL10 was more than 15-fold 

12 lower than the response at the lowest dose (66 mg/kg-day) in the bioassay. BMDs and 

13 BMDLs were calculated using a BMR of 30 and 50% extra risk (BMD30, BMDL30, 

14 BMD50, and BMDL50). A BMR of 50% was chosen as it resulted in a BMDL closest to 

15 the response level at the lowest dose tested in the bioassay. 

16

17 Comment: The geometric mean of the oral cancer slope factors (as done with B[a]P & 

18 DDT) should have been used instead of relying on the female BDF1 mouse data, since a 

19 MOA could not be determined for 1,4-dioxane.

20

21 Response: In accordance with the BMD technical guidance document (U.S. EPA, 2000a), 

22 averaging tumor incidence is not a standard or default approach. Averaging the tumor 

23 incidence response diminishes the effect seen in the sensitive species/gender.

24

25 Comment: EPA should critically reexamine the choice of JBRC (1998) as the principal 

26 study since it has not been published or peer-reviewed. A transcript of e-mail 

27 correspondence should be provided.

28

29 Response: JBRC (1998) was published as conference proceedings as Yamazaki et al. 

30 (1994) and recently in the peer-reviewed literature as Kano et al. (2009). Additional study 

31 information was also gathered from the authors (Yamazaki, 2006) and is available upon 

32 request from the IRIS Hotline. The peer-reviewed and published data from Kano et al. 

33 (2009) was incorporated into the final version of the Toxicological Review of 

34 1,4-Dioxane. 

35

36 Comment: The WOE does not support a cancer descriptor of likely to be carcinogenic to 

37 humans determination, but rather suggestive human carcinogen at the high dose levels 
A-20

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 used in rodent studies seems more appropriate for the following reasons: 1) lack of 

2 conclusive human epidemiological data; 2) 1,4-dioxane is not mutagenic; and 3) evidence 

3 at high doses it would act via cell proliferation MOA.

4

5 Response: A cancer classification of ―likely,” based on evidence of liver carcinogenicity 

6 in several two-year bioassays conducted in three strains of rats, two strains of mice, and 

7 in guinea pigs was chosen. Also, mesotheliomas of the peritoneum, mammary, and nasal 

8 tumors have been observed in rats. The Agency agrees that human epidemiological 

9 studies are inconclusive. The evidence at any dose is insufficient to determine a MOA.

10

A.2.3. PBPK Modeling

11 Comment: EPA should have used and considered PBPK models to derive the oral 

12 toxicity values (rat to human extrapolation) rather than relying on a default method. The 

13 draft did not consider the Sweeney et al. (2008) model. The PBPK model should be used 

14 for both noncancer and cancer dose extrapolation.

15

16 Response: The Agency evaluated the Sweeney et al. (2008) publication and this was 

17 included in Appendix B of the document. Text was added to the main document in 

18 Section 3.5.2.4 and 3.5.3 regarding the evaluation of Sweeney et al. (2008). This model 

19 was determined not to be appropriate for interspecies extrapolation. Additionally, see 

20 response to the external peer review panel comment B4. 

21

22 Comment: EPA should use the modified inhalation inputs used in the Reitz et al. (1990)

23 model and the updated input parameters provided in Sweeney et al. (2008) and add a 

24 compartment for the kidney

25

26 Response: See response to previous comment regarding evaluation of Sweeney et al. 

27 (2008). Modification of the model to add a kidney compartment is not within the scope 

28 of this assessment. 

A.2.4. Other Comments

29 Comment: EPA should consider the Kasai et al. (2009; 2008) studies for inhalation and 

30 MOA relevance.

31

32 Response: The 13 week and 2-year inhalation studies by Kasai et al. (2009; 2008) were 

33 published late in the development stage of this assessment. The IRIS Program will 
A-21

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 evaluate these recently published 1,4-dioxane inhalation data for the potential to derive 

2 an RfC in a separate assessment.

3

4 Comment: 1,4-Dioxane is not intentionally added to cosmetics and personal care 

5 products – correct sentence on page 4.

6

7 Response: This oversight was corrected in the document.
B-1

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

B.1. BACKGROUND

1 Several pharmacokinetic models have been developed to predict the absorption, 

2 distribution, metabolism, and elimination of 1,4-dioxane in rats and humans. Single 

3 compartment, empirical models for rats (Young, et al., 1978a; Young, et al., 1978b) and humans 

4 (Young, et al., 1977) were developed to predict blood levels of 1,4-dioxane and urine levels of 

5 the primary metabolite, β-hydroxyethoxy acetic acid (HEAA). Physiologically based 

6 pharmacokinetic (PBPK) models that describe the kinetics of 1,4-dioxane using biologically 

7 realistic flow rates, tissue volumes and affinities, metabolic processes, and elimination behaviors, 

8 were also developed (Fisher, et al., 1997; Leung & Paustenbach, 1990; Reitz, et al., 1990). 

9 In developing updated toxicity values for 1,4-dioxane, the available PBPK models were 

10 evaluated for their ability to predict observations made in experimental studies of rat and human 

11 exposures to 1,4-dioxane. The model of Reitz et al. (1990) was identified for further 

12 consideration to assist in the derivation of toxicity values. Issues related to the biological 

13 plausibility of parameter values in the Reitz et al. (1990) human model were identified. The 

14 model was able to predict the only available human inhalation data set (Young, et al., 1977) by 

15 increasing (i.e., doubling) parameter values for human alveolar ventilation, cardiac output, and 

16 the blood:air partition coefficient above the measured values. Furthermore, the measured value 

17 for the slowly perfused tissue:air partition coefficient (i.e., muscle) was replaced with the 

18 measured liver value to improve the fit. Analysis of the Young et al. (1977) human data 

19 suggested that the apparent volume of distribution (Vd) for 1,4-dioxane was approximately 10-

20 fold higher in rats than humans, presumably due to species differences in tissue partitioning or 

21 other process not represented in the model. Subsequent exercising of the model demonstrated 

22 that selecting a human slowly perfused tissue:air partition coefficient much lower than the 

23 measured rat value resulted in better agreement between model predictions of 1,4-dioxane in 

24 blood and experimental observations. Based upon these observations, several model parameters 

25 (e.g., metabolism/elimination parameters) were re-calibrated using biologically plausible values 

26 for flow rates and tissue:air partition coefficients. 

 

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

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

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

and the Integrated Risk Information System (IRIS).
B-2

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 This appendix describes activities conducted in the evaluation of the empirical models 

2 (Young, et al., 1978a; Young, et al., 1978b; Young, et al., 1977), and re-calibration and 

3 exercising of the Reitz et al. (1990) PBPK model, and evaluation of the Sweeney et al. (2008)

4 model to determine the potential utility of the PBPK models for 1,4-dioxane for interspecies and 

5 route-to-route extrapolation. 

B.2. SCOPE

6 The scope of this effort consisted of implementation of the Young et al. (1978a; 1978b; 

7 1977) empirical rat and human models using the acslXtreme simulation software, re-calibration 

8 of the Reitz et al. (1990) human PBPK model, and evaluation of model parameters published by 

9 Sweeney et al. (2008). Using the model descriptions and equations given in Young et al. (1978a; 

10 1978b; 1977), model code was developed for the empirical models and executed, simulating the 

11 reported experimental conditions. The model output was then compared with the model output 

12 reported in Young et al. (1978a; 1978b; 1977).

13 The PBPK model of Reitz et al. (1990) was re-calibrated using measured values for 

14 cardiac and alveolar flow rates and tissue:air partition coefficients. The predictions of blood and 

15 urine levels of 1,4-dioxane and HEAA, respectively, from the re-calibrated model were 

16 compared with the empirical model predictions of the same dosimeters to determine whether the 

17 re-calibrated PBPK model could perform similarly to the empirical model. As part of the PBPK 

18 model evaluation, EPA performed a sensitivity analysis to identify the model parameters having 

19 the greatest influence on the primary dosimeter of interest, the blood level of 1,4-dioxane. 

20 Variability data for the experimental measurements of the tissue:air partition coefficients were 

21 incorporated to determine a range of model outputs bounded by biologically plausible values for 

22 these parameters. Model parameters from Sweeney et al. (2008) were also tested to evaluate the 

23 ability of the PBPK model to predict human data following exposure to 1,4-dioxane.

B.3. IMPLEMENTATION OF THE EMPIRICAL MODELS IN acslXtreme

24 The empirical models of Young et al. (1978a; 1978b; 1977) for 1,4-dioxane in rats and 

25 humans were reproduced using acslXtreme, version 2.3 (Aegis Technologies, Huntsville, AL). 

26 Model code files were developed using the equations described in the published papers. 

27 Additional files containing experiment-specific information (i.e., BWs, exposure levels, and 

28 duration) were also generated.

B.3.1. Model Descriptions 

29 The empirical model of Young et al. (1978a; 1978b) for 1,4-dioxane in rats is shown in 

30 Figure B-1. This is a single-compartment model that describes the absorption and metabolism 

31 kinetics of 1,4-dioxane in blood and urine. No information is reported describing pulmonary 
B-3

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 absorption or intravenous (i.v.) injection/infusion of 1,4-dioxane. The metabolism of 

2 1,4-dioxane and subsequent appearance of HEAA is described by Michaelis-Menten kinetics 

3 governed by a maximum rate (Vmax, μg/mL-hour) and affinity constant (Km, μg/mL) . Both 

4 1,4-dioxane and HEAA are eliminated via the first-order elimination rate constants, ke and kme, 

respectively (hour-15 ) by which 35% of 1,4-dioxane and 100% of HEAA appear in the urine, 

6 while 65% of 1,4-dioxane is exhaled. Blood concentration of 1,4-dioxane is determined by 

7 dividing the instantaneous amount of 1,4-dioxane in blood by a Vd of 301 mL/kg BW. 

Source: Used with permission from Taylor & Francis, Young et al. (1978a; 1978b).

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

rats.

8 Figure B-2 illustrates the empirical model for 1,4-dioxane in humans as described in 

9 Young et al. (1977). Like the rat model, the human model predicts blood 1,4-dioxane and 

10 urinary 1,4-dioxane and HEAA levels using a single-compartment structure. However, the 

11 metabolism of 1,4-dioxane to HEAA in humans is modeled as a first-order process governed by 

a rate constant, KM (hour-112 ). Urinary deposition of 1,4-dioxane and HEAA is described using the 

13 first order rate constants, ke(diox) and kme(HEAA), respectively. Pulmonary absorption is described 

14 by a fixed rate of 76.1 mg/hour (kINH). Blood concentrations of 1,4-dioxane and HEAA are 

15 calculated as instantaneous amount (mg) divided by Vd(diox) or Vd(HEAA), respectively (104 and 

16 480 mL/kg BW, respectively). 

Inhalation (kINH)

i.v. admin me body

m body

body body k HEAA

K Diox

V Diox

dt

dHEAA max

e body

m body

body body k Diox

K Diox

V Diox

dt

dDiox max k Diox e

kme HEAA

Urine

Urine (35%)

Exhaled (65%)

Inhalation (kINH)

i.v. admin me body

m body

body body k HEAA

K Diox

V Diox

dt

dHEAA max

e body

m body

body body k Diox

K Diox

V Diox

dt

dDiox max k Diox e

kme HEAA

Urine

Urine (35%)

Exhaled (65%)
B-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

1 Several modifications were made to the empirical models. The need for the 

2 modifications arose in some cases from incomplete reporting of the Young et al. (1978a; 1978b; 

3 1977) studies and in other cases from the desire to add capabilities to the models to assist in the 

4 derivation of toxicity values.

5 For the rat model, no information was given by Young et al. (1978a; 1978b) regarding 

6 the parameterization of pulmonary absorption (or exhalation) or i.v. administration of 

7 1,4-dioxane. Therefore, additional parameters were added to simulate these processes in the 

simplest form. To replicate 1,4-dioxane inhalation, a first-order rate constant, kINH (hour-18 ), was 

9 introduced. kINH was multiplied by the inhalation concentration and the respiratory minute 

10 volume of 0.238 L/minute (Young, et al., 1978a; 1978b). The value for kINH was estimated by 

11 optimization against the blood time course data of Young et al. (1978a; 1978b). Intravenous 

12 (i.v.) administration was modeled as instantaneous appearance of the full dose at the start of the 

13 simulation. Rat urinary HEAA data were reported by Young et al. (1978a; 1978b) in units of 

14 concentration. To simulate urinary HEAA concentration, an estimate of urine volume was 

15 required. Since observed urinary volumes were not reported by Young et al. (1978a; 1978b), a 

16 standard rat urine production rate of 0.00145 L/hour was used. 

17 For humans, Young et al. (1977) used a fixed 1,4-dioxane inhalation uptake rate of 

18 76.1 mg/hour, which corresponded to observations during a 50 ppm exposure. In order to 

19 facilitate user-specified inhalation concentrations, pulmonary absorption was modeled. The 

20 modeling was performed identically to the rat model, but using a human minute volume of 

21 7 L/minute. Urinary HEAA data were reported by Young et al. (1977) as a cumulative amount 

22 (mg) of HEAA. Cumulative amount of HEAA in the urine is readily calculated from the rate of 

Inhalation (kINH)

AHEAA Vd (HEAA) ConcHEAA

Dioxane Urine

HEAA

KM

ke (diox)

kme (HEAA)

Cumulative 

Dioxane and 

HEAA ADiox Vd (Diox ) Conc Diox

Inhalation (kINH)

AHEAA Vd (HEAA) ConcHEAA

Dioxane Urine

HEAA

KM

ke (diox)

kme (HEAA)

Cumulative 

Dioxane and 

HEAA ADiox Vd (Diox ) Conc Diox
B-5

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 transfer of HEAA from plasma to urine, so no modification was necessary to simulate this dose 

2 metric for humans. 

3 Neither empirical model of Young et al. (1978a; 1978b; 1977) described oral uptake of 

4 1,4-dioxane. Adequate data to estimate oral absorption parameters are not available for either 

5 rats or humans; therefore, neither empirical model was modified to include oral uptake.

B.3.3. Results

6 The acslXtreme implementation of the Young et al. (1978a; 1978b) rat empirical model 

7 simulates the 1,4-dioxane blood levels from the i.v. experiments identically to the model output 

8 reported in the published paper (Figure B-3). However, the acslXtreme version predicts urinary 

9 HEAA concentrations in rats that are approximately threefold lower and reach a maximum 

10 sooner than the predicted levels reported in the paper (Figure B-4). These discrepancies may be 

11 due, at least in part, to the reliance in the acslXtreme implementation on a constant, standard, 

12 urine volume rather than experimental measurements, which may have been different from the 

13 assumed value and may have varied over time. Unreported model parameters (e.g., lag times for 

14 appearance of excreted HEAA in bladder urine) may also contribute to the discrepancy. 

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 

implementation (left) and published (right) empirical rat model simulations 

of i.v. administration experiments.

Observations and predictions of 1,4-dioxane in rat blood 

following 3 to 1000 mg/kg IV injection

0.1

1.0

10.0

100.0

1000.0

0 10 20 30 40 50 60 70

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

Observations and predictions of 1,4-dioxane in rat blood 

following 3 to 1000 mg/kg IV injection

0.1

1.0

10.0

100.0

1000.0

0 10 20 30 40 50 60 70

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations
B-6

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: Used with permission from Taylor & Francis, Young et al. (1978a; 1978b).

Figure B-4. Output of HEAA urine level data from acslXtreme 

implementation (left) and published (right) empirical rat model simulations 

of i.v. administration experiments.

1 The Young et al. (1978a; 1978b) report did not provide model predictions for the 50-ppm 

2 inhalation experiment. However, the acslXtreme implementation produces blood 1,4-dioxane 

3 predictions that are quite similar to the reported observations (Figure B-5). As with the urine 

4 data from the i.v. experiment, the acslXtreme-predicted urinary HEAA concentrations are 

5 approximately threefold lower than the observations, presumably for the same reasons discussed 

6 above for the i.v. predictions.

Observations and predictions of HEAA in rat urine 

following 10 or 1000 mg/kg IV injection

1

10

100

1000

10000

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

a (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

Observations and predictions of HEAA in rat urine 

following 10 or 1000 mg/kg IV injection

1

10

100

1000

10000

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

a (1978) empirical model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations
B-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.

1 Inhalation data for a single exposure level (50 ppm) are available for humans. The 

2 acslXtreme predictions of the blood 1,4-dioxane observations are identical to the predictions 

3 reported in Young et al. (1977) (Figure B-6). Limited blood HEAA data were reported, and the 

4 specimen analysis was highly problematic (e.g., an analytical interference was sometimes present 

5 from which HEAA could not be separated). For this reason, Young et al. (1977) did not compare 

6 predictions of the blood HEAA data to observations in their manuscript. 

Observations and predictions of 1,4-dioxane in rat blood 

following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et al

(1978) empirical model

Young et al (1978)

observations

Observations and predictions of HEAA in rat urine 

following a 6 hour 50 ppm inhalation exposure

0.0

5.0

10.0

15.0

20.0

25.0

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

al (1978) empirical

model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

acsl version – Young et 

al. (1978a, b) empirical 

model

Young et al. (1978a, b) 

observations

Observations and predictions of 1,4-dioxane in rat blood 

following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et al

(1978) empirical model

Young et al (1978)

observations

Observations and predictions of HEAA in rat urine 

following a 6 hour 50 ppm inhalation exposure

0.0

5.0

10.0

15.0

20.0

25.0

0 10 20 30 40 50

Time (hrs)

Urinary 

HEAA Conc (mg/L)

acsl version - Young et

al (1978) empirical

model

Young et al (1978)

observations

acsl version – Young et al. 

(1978a, b) empirical model

Young et al. (1978a, b) 

observations

acsl version – Young et 

al. (1978a, b) empirical 

model

Young et al. (1978a, b) 

observations
B-8

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: Used with permission 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.

1 Data for cumulative urinary HEAA amounts are provided in Young et al. (1977), and no 

2 analytical problems for these data were reported. Nevertheless, model predictions for urinary 

3 HEAA were not presented in the manuscript. The acslXtreme prediction of the HEAA kinetics 

4 profile is similar to the observations, although predicted values are approximately 1.5- to 2-fold 

5 lower than the observed values (Figure B-7). Unlike urinary HEAA observations in the rat, 

6 human observations were reported as cumulative amount produced, negating the need for urine 

7 volume data. Therefore, discrepancies between model predictions and experimental observations 

8 for humans cannot be attributed to uncertainties in urine volumes in the subjects. Further 

9 evaluation of the Young et al. (1977) empirical model was conducted against subchronic 

10 inhalation exposure data reported by Kasai et al. (2008). In the experimental study, male and 

11 female F344 rats were exposed to 0, 100, 200, 400, 800, 1,600, 3,200, or 6,400ppm 1,4-dioxane 

12 in a 13-week inhalation study. The simulations of the Young et al. (1977) model did not provide 

13 an adequate fit (Figure B-8) for the measured plasma levels at each exposure level of 1,4-dioxane 

14 as reported by Kasai et al. (2008).

15

Observations and predictions of 1,4-dioxane in human 

blood following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1977) empirical model

observed

Observations and predictions of 1,4-dioxane in human 

blood following a 6 hour 50 ppm inhalation exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

acsl version - Young et

al (1977) empirical model

observed
B-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 

plasma 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

1 The empirical models described by Young et al. (1978a; 1978b; 1977) for rats and 

2 humans were implemented using acslXtreme. The models were modified to allow for user3 defined inhalation levels by addition of a first-order rate constant for pulmonary uptake of 

Observations and predictions of HEAA in human urine 

following a 6 hour 50 ppm inhalation exposure

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

acsl version - Young et al

(1977) empirical model

observed
B-10

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 1,4-dioxane, fitted to the inhalation data. No modifications were made for oral absorption as 

2 adequate data are not available for parameter estimation. The acslXtreme predictions of 

3 1,4-dioxane in the blood are identical to the published predictions for simulations of 6-hour, 50-

4 ppm inhalation exposures in rats and humans and 3 to 1,000 mg/kg i.v. doses in rats (Figures B5 3, B-5, and B-6). However, the acslXtreme version predicts lower urinary HEAA concentrations 

6 in rats appearing earlier than either the Young et al. (1978a; 1978b) model predictions or the 

7 experimental observations. The lower predicted urinary HEAA levels in the acslXtreme 

8 implementation for rats is likely due to use of default values for urine volume in the absence of 

9 measured volumes. The reason for differences in time-to-peak levels is unknown, but may be 

10 the result of an unreported adjustment by Young et al. (1978a; 1978b) in model parameter 

11 values. Additionally, the modified Young et al. (1978a; 1978b; 1977) model failed to provide 

12 adequate fit to blood data reported following subchronic inhalation of 1,4-dioxane in rats (Kasai, 

13 et al., 2008). For humans, Young et al. (1977) did not report model predictions of urinary HEAA 

14 levels. The urinary HEAA levels predicted by acslXtreme were low relative to the observations. 

15 However, unlike the situation in rats, these data are not dependent on unreported urine volumes 

16 (observations were reported as cumulative HEAA amount rather than HEAA concentration), but 

17 reflect the model parameter values reported by Young et al. (1977). Presently, there is no 

18 explanation for the lack of fit of the reported urinary HEAA elimination rate constant to the 

19 observations.

B.4. INITIAL RE-CALIBRATION OF THE PBPK MODEL

20 Concern regarding adjustments made to some of the parameter values in Reitz et al. 

21 (1990) prompted a re-calibration of the Reitz et al. (1990) human PBPK model using more 

22 biologically plausible values for all measured parameter values. Reitz et al. (1990) doubled the 

23 measured physiological flows and blood:air partition coefficient and substituted the slowly24 perfused tissue:air partition coefficient with the liver:air value in order to attain an adequate fit to 

25 the observations. This approach increases uncertainty in these parameter values, and in the 

26 utilization of the model for cross-species dose extrapolation. Therefore, the model was re27 calibrated using parameter values that are more biologically plausible to determine whether an 

28 adequate fit of the model to the available data can be attained. 

B.4.1. Sources of Values for Flow Rates 

The cardiac output of 30 L/hour/kg0.74 29 (Table B-1) reported by Reitz et al. (Reitz, et al., 

1990) is approximately double the mean resting value of 14 L/hour/kg0.74 30 reported in the widely 

31 accepted compendium of Brown et al. (1997). Resting cardiac output was reported to be 5.2 

L/minute (or 14 L/hour/kg0.74 32 ), while strenuous exercise resulted in a flow of 9.9 L/minute (or 26 

L/hour/kg0.74 33 ) (Brown, et al., 1997). Brown et al. (1997) also cite the ICRP (1975) as having a 
B-11

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 mean respiratory minute volume of 7.5 L/minute, which results in an alveolar ventilation rate of 

5 L/minute (assuming 33% lung dead space), or 13 L/minute/kg0.74 2 . Again, this is roughly half 

the value of 30 L/hour/kg0.74 3 employed for this parameter by Reitz et al. (1990). Young et al. 

4 (1977) reported that the human subjects exposed to 50 ppm for 6 hours were resting inside a 

5 walk-in exposure chamber. Thus, use of cardiac output and alveolar ventilation rates of 30 

L/hour/kg0.74 6 is not consistent with the experimental conditions being simulated.

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) EPAc

Physiological Flows

 Cardiac output (QCC)a30 -- -- 17.0

 Alveolar ventilation (QPC)a30 -- -- 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 ± 739b1,557

 Rapidly perfused tissue:air (PRA) 1,557 -- -- 1,557

 Slowly perfused tissue:air (PSA) 1,557 997 ± 254 1,348 ± 290b166

Metabolic Constants

 Maximum rate for 1,4-dioxane 

metabolism (VmaxC)

d

6.35 -- -- 5.49

 Metabolic affinity constant (Km)

e

3.00 -- -- 9.8

 HEAA urinary elimination rate 

constant (kme)

f

0.56 -- -- 0.44

aL/hour/kg BW0.74

bMeasurement for rat tissue

cBiologically plausible values utilized by EPA in this assessment

dmg/hour/kg BW0.75

emg/L

f

hour-1

7 Examination of the experimental data of Young et al. (1977) yields an estimated alveolar 

ventilation to be 7 L/minute (or 16 L/hour/kg0.74 8 ) for volunteers having a mean BW of 84 kg. 

9 This rate is based on the Young et al. (1977) estimate of 76.1 mg/hour for 1,4-dioxane uptake. 

10 Based on these findings, the cardiac output and alveolar ventilation rates of 17.0 and 17.7 

L/hour/kg0.74 11 were biologically plausible for the experimental subjects. These rate estimates are 

12 based on calculations made using empirical data and are consistent with standard human values 

13 and the experimental conditions (i.e., subject exertion level) reported by Young et al. (1977). 

14 Therefore, these flow values were chosen for the model re-calibration. 
B-12

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

B.4.2. Sources of Values for Partition Coefficients

1 Two data sources are available for the tissue:air equilibrium partition coefficients for 

2 1,4-dioxane: Leung and Paustenbach (1990) and Sweeney et al. (2008). Both investigators 

3 report mean values and standard deviations for human blood:air, rat liver:air, and rat muscle:air 

4 (e.g., slowly perfused tissue:air), while Leung and Paustenbach et al. (1990) also reported values 

5 for rat fat:air (Table B-1).

B.4.3. Calibration Method

6 The PBPK model was twice re-calibrated using the physiological flow values suggested 

7 values (current EPA assessment, see Table B-1) and the partition coefficients of Leung and 

8 Paustenbach (1990) and Sweeney et al. (2008) separately. For each calibration, the metabolic 

9 parameters VmaxC and Km, were simultaneously fit (using the parameter estimation tool provided 

10 in the acslXtreme software) to the output of 1,4-dioxane blood concentrations generated by the 

11 acslXtreme implementation of the Young et al. (1977) empirical human model for a 6 hour, 

12 50 ppm inhalation exposure. Subsequently, the HEAA urinary elimination rate constant, kme, 

13 was fitted to the urine HEAA predictions from the empirical model. The empirical model 

14 predictions, rather than experimental observations, were used to provide a more robust data set 

15 for model fitting, as the empirical model simulation provided 240 data points (one prediction 

16 every 0.1 hour) compared with hourly experimental observations, and to avoid introducing error 

17 by calibrating the model to data digitally captured from Young et al. (1977).

B.4.4. Results

18 Results of the model re-calibration are provided in Table B-2. The re-calibrated values 

19 for VmaxC and kme associated with the Leung and Paustenbach (1990) or Sweeney et al. (2008)

20 tissue:air partition coefficients are very similar. However, the fitted value for Km using the 

21 Sweeney et al. (2008) partition coefficients is far lower (0.0001 mg/L) than that resulting from 

22 use of the Leung and Paustenbach (1990) partition coefficients (2.5 mg/L). This appears to be 

23 due to the higher slowly perfused tissue:air partition coefficient determined by Sweeney et al. 

24 (2008) (1,348 vs. 997), resulting in a higher apparent Vd than if the Leung and Paustenbach 

25 (1990) value is used. Thus, the optimization algorithm selects a low Km, artificially saturating 

26 metabolism in an effort to drive predicted blood 1,4-dioxane levels closer to the empirical model 

27 output. Saturation of metabolism during a 50 ppm inhalation exposure is inconsistent with the 

28 observed kinetics.
B-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 ratesaand tissue:air partition coefficients

Source of Partition Coefficients Leung and Paustenbach (1990) Sweeney et al. (2008)

Maximum rate for 1,4-dioxane metabolism (VmaxC)

b

16.9 20.36

Metabolic affinity constant (Km)

c

2.5 0.0001

HEAA urinary elimination rate constant (kme)

d

0.18 0.17

aCardiac output = 17.0 L/hour/kg BW0.74, alveolar ventilation = 17.7 L/hour/kg BW0.74

bmg/hour/kg BW0.75

cmg/L

d

hour-1

1 Plots of predicted and experimentally observed blood 1,4-dioxane and urinary HEAA 

2 levels are shown in Figure B-9. Neither re-calibration resulted in an adequate fit to the blood 

3 1,4-dioxane data from the empirical model output or the experimental observations. Re4 calibration using either the Leung and Paustenbach (1990) or Sweeney et al. (2008) partition 

5 coefficients resulted in blood 1,4-dioxane predictions that were at least 10-fold lower than 

6 empirical model predictions or observations. 

Source: Used with permission from Elsevier, Ltd., Leung and Paustenbach (1990).

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

and urinary HEAA levels (right) following re-calibration of the human PBPK 

model with tissue:air partition coefficient values. 

7 The refitted values for kme resulted in HEAA levels in urine that were very similar to the 

8 empirical model output (compare Figures B-7, B-9, and B-10), which was not surprising, given 

9 the fitting of a single parameter to the data.

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using 

PC values of Gargas (L&P, 1990)

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predicted

Observations and Predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: Kme fit while using PC values of 

Gargas (L&P, 1990)

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Kmfit while using PC 

values from Leung and Paustenbach (1990)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Leung and Paustenbach (1990)

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using 

PC values of Gargas (L&P, 1990)

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predicted

Observations and Predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: Kme fit while using PC values of 

Gargas (L&P, 1990)

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Kmfit while using PC 

values from Leung and Paustenbach (1990)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Leung and Paustenbach (1990)
B-14

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: Used with permission of Oxford Journals, Sweeney et al. (2008).

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

and urinary HEAA levels (right) following re-calibration of the human PBPK 

model with tissue:air partition coefficient values. 

1 Outputs of the blood 1,4-dioxane and urinary HEAA levels using the suggested (Table B2 1) parameters are shown in Figure B-11. These outputs rely on a very low value for the slowly 

3 perfused tissue:air partition coefficient (166) that is six- to eightfold lower than the measured 

4 values reported in Leung and Paustenbach (1990) and Sweeney et al. (2008), and 10-fold lower 

5 than the value used by Reitz et al. (1990). While the predicted maximum blood 1,4-dioxane 

6 levels are much closer to the observations, the elimination kinetics are markedly different, 

7 producing higher predicted elimination rates compared to observations during the post-exposure 

8 phase of the experiment.

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using PC 

values of Soelberg et al (2006)

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predricted

Observations and Predictions of HEAA in human urine from a 6-

hour, 50 ppm exposure: Kme fit while using PC values of 

Soelberg et al (2006)

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Kmfit while using PC 

values from Sweeney et al. (2008)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Sweeney et al. (2008)

Observations and Predictions of 1,4-Dioxane in human blood 

from a 6-hour, 50 ppm exposure: Vmax & Km fit while using PC 

values of Soelberg et al (2006)

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

PBPK predicted

observed

empirical predricted

Observations and Predictions of HEAA in human urine from a 6-

hour, 50 ppm exposure: Kme fit while using PC values of 

Soelberg et al (2006)

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

PBPK predicted

observed

empirical predicted

Observations and predictions of 1,4-dioxane in human blood from 

a 6-hour, 50 ppm exposure: VmaxC and Kmfit while using PC 

values from Sweeney et al. (2008)

Observations and predictions of HEAA in human urine from a 

6-hour, 50 ppm exposure: kme fit while using PC values from 

Sweeney et al. (2008)
B-15

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Figure B-11. Predicted and observed blood 1,4-dioxane concentrations (left) 

and urinary HEAA levels (right) using EPA estimated biologically plausible 

parameters (Table B-1).

B.4.5. Conclusions for PBPK Model Implementation

1 Re-calibration of the human PBPK model was performed using experiment-specific 

2 values for cardiac output and alveolar ventilation (Young, et al., 1977) and measured mean 

3 tissue:air 1,4-dioxane partition coefficients reported by Leung and Paustenbach (1990) or 

4 Sweeney et al. (2008). The resulting predictions of 1,4-dioxane in blood following a 6-hour, 50-

5 ppm inhalation exposure were 10-fold (or more) lower than either the observations or the 

6 empirical model predictions, while the predictions of urinary HEAA by the PBPK and empirical 

7 models were similar to each other, but lower than observed values (Figures B-9 and B-10). 

8 Output from the model using biologically plausible parameter values (Table B-1), Figure B-11 

9 shows that application of a value for the slowly perfused tissue:air partition coefficient, which is 

10 10-fold lower than the measured value reported by Leung and Paustenbach (1990), results in 

11 closer agreement of the predictions to observations during the exposure phase, but not during the 

12 elimination phase. Thus, model re-calibration using experiment-specific flow rates and mean 

13 measured partition coefficients does not result in an adequate fit of the PBPK model to the 

14 available data. 

15 The Sweeney et al. (2008) PBPK model consisted of compartments for fat, liver, slowly 

16 perfused, and other well perfused tissues. Lung and stomach compartments were used to 

17 describe the route of exposure, and an overall volume of distribution compartment was used for 

18 calculation of urinary excretion levels of 1,4-dioxane and its metabolite, HEAA. Metabolic 

19 constants (VmaxC and Km) for the rat PBPK model were derived by optimization data from an 

20 i.v. exposure of 1,000 mg/kg data (Young, et al., 1978a; Young, et al., 1978b) for induced 

21 metabolism. For uninduced metabolism data generated by i.v. exposures to 3, 10, 30, and 100 

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and predictions of 1,4-dioxane in 

human blood from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Observations and predictions of HEAA in human 

urine from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and Predictions of 1,4-Dioxane in human 

blood from a 6-hour, 50 ppm exposure: EPA PKWG's 

parameter estimates used 

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

predicted

observed

Observations and Predictions of HEAA in human urine 

from a 6-hour, 50 ppm exposure: EPA PKWG's parameter 

estimates used 

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

predicted

observed

Observations and predictions of 1,4-dioxane in 

human blood from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used

Observations and predictions of HEAA in human 

urine from a 6-hour, 50 ppm exposure: 

EPA parameter estimates used
B-16

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 mg/kg were used (Young, et al., 1978a; Young, et al., 1978b). Data generated from the 300 

2 mg/kg i.v. exposure was not used to estimate VmaxC and Km. The best fitting values for VmaxC 

3 to estimate the blood data from the Young et al. (1978a; 1978b) study using the Sweeney et al. 

4 (2008) model resulted in VmaxC values of 12.7, 10.8, 7.4 mg/kg-hr; suggesting a gradual dose 

5 dependent increase in metabolic rate with dose. These estimates were for a range of doses 

6 between 3 and 1,000 mg/kg i.v. dose. Although the Sweeney et al. (2008) model utilized two 

7 values for VmaxC (induced and uninduced), the PBPK model does not include dose-dependent 

8 function description of the change of Vmax for i.v. doses between 100 and 1,000 mg/kg. PBPK 

9 model outputs were compared with other data not used in fitting model parameters by visual 

10 inspection. The model predictions gave adequate match to the 1,4-dioxane exhalation data after a 

11 1,000 mg/kg i.v. dose. 1,4-Dioxane exhalation was overpredicted by a factor of about 3 for the 

12 10 mg/kg i.v. dose. Similarly, the simulations of exhaled 1,4-dioxane after oral dosing were 

13 adequate at 1,000 mg/kg, and 100 mg/kg (within 50%), but poor at 10 mg/kg (model 

14 overpredicted by a factor of five). The fit of the model to the human data (Young, et al., 1977)

15 was also problematic (Sweeney, et al., 2008). Using physiological parameters of Brown et al. 

16 (1997) and measured partitioning parameters (Leung & Paustenbach, 1990; Sweeney, et al., 

17 2008) with no metabolism, measured blood 1,4-dioxane concentrations reported by Young et al. 

18 (1977) could not be achieved unless the estimated exposure concentration was increased from 53 

19 to 100 ppm. Inclusion of any metabolism necessarily decreased predicted blood concentrations. 

20 If estimated metabolism rates were used with the reported exposure concentration, urinary 

21 metabolite excretion was underpredicted (Sweeney, et al., 2008). Thus, the models were 

22 inadequate to use for rat to human extrapolation.

B.4.6. SENSITIVITY ANALYSIS

23 A sensitivity analysis of the Reitz et al. (1990) model was performed to determine which 

24 PBPK model parameters exert the greatest influence on the outcome of dosimeters of interest—

25 in this case, the concentration of 1,4-dioxane in blood. Knowledge of model sensitivity is useful 

26 for guiding the choice of parameter values to minimize model uncertainty.

B.4.7. Method

27 A univariate sensitivity analysis was performed on all of the model parameters for two 

28 endpoints: blood 1,4-dioxane concentrations after 1 and 4 hours of exposure. These time points 

29 were chosen to assess sensitivity during periods of rapid uptake (1 hour) and as the model 

30 approached steady state (4 hours) for blood 1,4-dioxane. Model parameters were perturbated 1% 

31 above and below nominal values and sensitivity coefficients were calculated as follows:

( )

( ) ( )

( )

'

f x

x

x

f x x f x

f x
B-17

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 where x is the model parameter, f(x) is the output variable, Δx is the perturbation of the 

2 parameter from the nominal value, and f‘(x) is the sensitivity coefficient. The sensitivity 

3 coefficients were scaled to the nominal value of x and f(x) to eliminate the potential effect of 

4 units of expression. As a result, the sensitivity coefficient is a measure of the proportional 

5 change in the blood 1,4-dioxane concentration produced by a proportional change in the 

6 parameter value, with a maximum value of 1. 

B.4.8. Results

7 The sensitivity coefficients for the seven most influential model parameters at 1 and 

8 4 hours of exposure are shown in Figure B-12. The three parameters with the highest sensitivity 

9 coefficients in descending order are alveolar ventilation (QPC) (1.0), the blood:air partition 

10 coefficient (PB) (0.65), and the slowly perfused tissue:air partition coefficient (PSA) (0.51). Not 

11 surprisingly, these were the parameters that were doubled or given surrogate values in the Reitz 

12 et al. (1990) model in order to achieve an adequate fit to the data. Because of the large influence 

13 of these parameters on the model, it is important to assign values to these parameters in which 

14 high confidence is placed, in order to reduce model uncertainty.

Figure B-12. The highest seven sensitivity coefficients (and associated 

parameters) for blood 1,4-dioxane concentrations (CV) at 1 (left) and 4 

(right) hours of a 50-ppm inhalation exposure.

B.5. PBPK MODEL EXERCISES USING BIOLOGICALLY PLAUSIBLE PARAMETER 

BOUNDARIES

15 The PBPK model includes numerous physiological parameters whose values are typically 

16 taken from experimental observations. In particular, values for the flow rates (cardiac output and 

17 alveolar ventilation) and tissue:air partition coefficients (i.e., mean and standard deviations) are 

18 available from multiple sources as means and variances. The PBPK model was exercised by 

0.01 0.10 1.00

QPC

PB

PSA

QSC

QCC

VMAXC

KM

Parameter

Sensitivity Coefficients: CV - 1hr

0.01 0.10 1.00

QPC

PB

PSA

VMAXC

KM

PRA

QSC

Parameter

Sensitivity Coefficients: CV - 4 hr

QPC

PB

PSA

QSC

QCC

VmaxC

Km

QPC

PB

PSA

VmaxC

Km

PRA

QSC

0.01 0.10 1.00

QPC

PB

PSA

QSC

QCC

VMAXC

KM

Parameter

Sensitivity Coefficients: CV - 1hr

0.01 0.10 1.00

QPC

PB

PSA

VMAXC

KM

PRA

QSC

Parameter

Sensitivity Coefficients: CV - 4 hr

QPC

PB

PSA

QSC

QCC

VmaxC

Km

QPC

PB

PSA

VmaxC

Km

PRA

QSC
B-18

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 varying the partition coefficients over the range of biological plausibility (parameter mean ± 

2 2 standard deviations), re-calibrating the metabolism and elimination parameters, and exploring 

3 the resulting range of blood 1,4-dioxane concentration time course predictions. Cardiac output 

4 and alveolar ventilation were not varied because the experiment-specific values used did not 

5 include any measure of inter-individual variation.

B.5.1. Observations Regarding the Volume of Distribution

6 Young et al. (1978a; 1978b) used experimental observations to estimate a Vd for 

7 1,4-dioxane in rats of 301 mL, or 1,204 mL/kg BW. For humans, the Vd was estimated to be 

8 104 mL/kg BW (Young, et al., 1977). It is possible that a very large volume of the slowly 

9 perfused tissues in the body of rats and humans may be a significant contributor to the estimated 

10 10-fold difference in distribution volumes for the two species. This raises doubt regarding the 

11 appropriateness of using the measured rat slowly perfused tissue:air partition coefficient as a 

12 surrogate values for humans in the PBPK model. 

B.5.2. Defining Boundaries for Parameter Values

13 Given the possible 10-fold species differences in the apparent Vd for 1,4-dioxane in rats 

14 and humans, boundary values for the partition coefficients were chosen to exercise the PBPK 

15 model across its performance range to either minimize or maximize the simulated Vd. This was 

16 accomplished by defining biologically plausible values for the partition coefficients as the 

17 mean ± 2 standard deviations of the measured values. Thus, to minimize the simulated Vd for 

18 1,4-dioxane, the selected blood:air partition coefficient was chosen to be the mean + 2 standard 

19 deviations, while all of the other tissue:air partition coefficients were chosen to be the mean – 2 

20 standard deviations. This created conditions that would sequester 1,4-dioxane in the blood, away 

21 from other tissues. To maximize the simulated 1,4-dioxane Vd, the opposite selections were 

22 made: blood and other tissue:air partition coefficients were chosen as the mean – 2 standard 

23 deviations and mean + 2 standard deviations, respectively. Subsequently, VmaxC, Km, and kme

24 were optimized to the empirical model output data as described in Section B.4.3. This procedure 

25 was performed for both the Leung and Paustenbach (1990) and Sweeney et al. (2008) partition 

26 coefficients (Table B-1). The two predicted time courses resulting from the re-calibrated model 

27 with partition coefficients chosen to minimize or maximize the 1,4-dioxane Vd represent the 

28 range of model performance as bounded by biologically plausible parameter values.

B.5.3. Results

29 The predicted time courses for a 6-hour, 50-ppm inhalation exposure for the re-calibrated 

30 human PBPK model with mean (central tendency) and ± 2 standard deviations from the mean 

31 values for partition coefficients are shown in Figure B-13 for the Leung and Paustenbach (1990)

32 values and Figure B-14 for the Sweeney et al. (2008) values. The resulting fitted values for 
B-19

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 VmaxC, Km, and kme, are given in Table B-3. By bounding the tissue:air partition coefficients with 

2 upper and lower limits on biologically plausible values from Leung and Paustenbach (1990) or 

3 Sweeney et al. (2008), the model predictions are still at least six- to sevenfold lower than either 

4 the empirical model output or the experimental observations. The range of possible urinary 

5 HEAA predictions brackets the prediction of the empirical model, but this agreement is not 

6 surprising, as the cumulative rate of excretion depends only on the rate of metabolism of 

7 1,4-dioxane, and not on the apparent Vd for 1,4-dioxane. These data show that the PBPK model 

8 cannot adequately reproduce the predictions of blood 1,4-dioxane concentrations of the Young 

9 et al. (1977) human empirical model or the experimental observations when constrained by 

10 biologically plausible values for physiological flow rates and tissue:air partition coefficients.

Source: Used with permission of Elsevier, Ltd., Leung and Paustenbach (1990)

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

upper and lower boundaries on partition coefficients with empirical model 

predictions and experimental observations for blood 1,4-dioxane 

concentrations (left) and urinary HEAA levels (right) from a 6-hour, 50-ppm 

inhalation exposure.

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Gargas PC UCL

Gargas PC Central

Gargas PC LCL

observations

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data

Young et al. (1977) empirical model

Leung and Paustenbach (1990) PC – UCL 

Leung and Paustenbach (1990) PC – Central

Leung and Paustenbach (1990) PC – LCL

Young et al. (1977) observation data
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-14. 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 ratesaand selected upper and lower boundary values for 

tissue:air partition coefficients

Source of partition coefficients

Leung and Paustenbach (1990) Sweeney et al. (2008)

For maximal Vd For minimal Vd For maximal Vd For minimal Vd

Maximum rate for 1,4-dioxane 

metabolism (VmaxC)

b

14.95 18.24 17.37 21.75

Metabolic dissociation constant

(Km)

c

5.97 0.0001 4.88 0.0001

HEAA urinary elimination rate 

constant (kme)

d

0.18 0.17 0.26 0.19

aCardiac output = 17.0 L/hour/kg BW0.74, alveolar ventilation = 17.7 L/hour/kg BW0.74

bmg/hour/kg BW0.75

cmg/L

d

hour-1

B.5.4. Alternative Model Parameterization

1 Since the PBPK model does not predict the experimental observations of Young et al. 

2 (1977) when parameterized by biologically plausible values, an exercise was performed to 

3 explore alternative parameters and values capable of producing an adequate fit of the data. Since 

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation 

data

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation data

1,4-Dioxane in human blood from a 6-hour, 50 ppm 

exposure

0.1

1.0

10.0

100.0

0 5 10 15

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Cumulative HEAA in human urine from a 6-hour, 50 ppm 

exposure

0

100

200

300

400

500

600

700

0 5 10 15 20 25

Time (hrs)

Cumulative Urinary 

HEAA Amount (mg)

Young empirical model

Soelberg PCs UCL

Soelberg PCs central 

Soelberg PCs LCL

observations

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation 

data

Young et al. (1977) empirical model

Sweeney et al. (2008) PC – UCL 

Sweeney et al. (2008) PC – Central

Sweeney et al. (2008) PC – LCL

Young et al. (1977) observation data
B-21

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 the metabolism of 1,4-dioxane appears to be linear in humans for a 50-ppm exposure (Young, et 

2 al., 1977), the parameters VmaxC and Km were replaced by a zero-order, non-saturable metabolism 

3 rate constant, kLC. This rate constant was fitted to the experimental blood 1,4-dioxane data using 

4 partition coefficient values of Sweeney et al. (2008) to minimize the Vd (i.e., maximize the blood 

5 1,4-dioxane levels). The resulting model predictions are shown in Figure B-15. As before, the 

6 maximum blood 1,4-dioxane levels were approximately sevenfold lower than the observed 

7 values.

Figure B-15. Predictions of blood 1,4-dioxane concentration following 

calibration of a zero-order metabolism rate constant, kLC, to the 

experimental data.

8 A re-calibration was performed using only the data from the exposure phase of the 

9 experiment, such that the elimination data did not influence the initial metabolism and tissue 

10 distribution. The model predictions from this exercise are shown in Figure B-16. These 

11 predictions are more similar to the observations made during the exposure phase of the 

12 experiment; however, this is achieved at greatly reduced elimination rate (compare Figures B-11

13 and B-16). 

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure: KLC (3.0) fitted to all observations

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

KLC-fitted model

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm

exposure: kLC (3.0) fitted to all observations

Young et al. (1977) empirical 

model

kLC – fitted model

Young et al. (1977) 

observation data

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure: KLC (3.0) fitted to all observations

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

KLC-fitted model

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm

exposure: kLC (3.0) fitted to all observations

Young et al. (1977) empirical 

model

kLC – fitted model

Young et al. (1977) 

observation data
B-22

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

calibration of a zero-order metabolism rate constant, kLC, to only the 

exposure phase of the experimental data.

1 Finally, the model was re-calibrated by simultaneously fitting kLC and the slowly 

2 perfused tissue:air partition coefficient to the experimental data with no bounds on possible 

3 values (except that they be non-zero). The fitted slowly perfused tissue:air partition coefficient 

4 was an extremely low (and biologically unlikely) value of 0.0001. The resulting model 

5 predictions, however, were closer to the observations than even the empirical model predictions 

6 (Figure B-17). These exercises show that better fits to the observed blood 1,4-dioxane kinetics 

7 are achieved only when parameter values are adjusted in a way that corresponds to a substantial 

8 decrease in apparent Vd of 1,4-dioxane in the human, relative to the rat (e.g., decreasing the 

9 slowly perfused tissue:air partition coefficient to extremely low values, relative to observations). 

10 Downward adjustment of the elimination parameters (e.g., decreasing kLC) increases the 

11 predicted blood concentrations of 1,4-dioxane, achieving better agreement with observations 

12 during the exposure phase of the experiment; however, it results in unacceptably slow 

13 elimination kinetics, relative to observations following cessation of exposure. These 

14 observations suggest that some other process not captured in the present PBPK model structure is 

15 responsible for the species differences in 1,4-dioxane Vd and the inability to reproduce the 

16 human experimental inhalation data with biologically plausible parameter values.

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure: KLC (0.1) fitted 1-6 hour

 observations

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

KLC-fitted model

observations

1,4-Dioxane in human blood from a 6-hour, 50 ppm

exposure: kLC (0.1) fitted 1 to 6-hour observations

Young et al. (1977) empirical 

model

kLC – fitted model

Young et al. (1977) 

observation data
B-23

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Figure B-17. Predictions of blood 1,4-dioxane concentration following 

simultaneous calibration of a zero-order metabolism rate constant, kLC, and 

slowly perfused tissue:air partition coefficient to the experimental data.

B.6. CONCLUSIONS

1 The rat and human empirical models of Young et al. (1978a; 1978b; 1977) were 

2 successfully implemented in acslXtreme and perform identically to the models reported in the 

3 published papers (Figures 3-3 through 3-6), with the exception of the lower predicted HEAA 

4 concentrations and early appearance of the peak HEAA levels in rat urine. The early appearance 

5 of peak HEAA levels cannot presently be explained, but may result from manipulations of kme or 

6 other parameters by Young et al. (1978a; 1978b) that were not reported. The lower predictions 

7 of HEAA levels are likely due to reliance on a standard urine volume production rate in the 

8 absence of measured (but unreported) urine volumes. While the human urinary HEAA 

9 predictions were lower than observations, this is due to parameter fitting of Young et al. (1977). 

10 No model output was published in Young et al. (1977) for comparison. The empirical models 

11 were modified to allow for user-defined inhalation exposure levels. However, no modifications 

12 were made to model oral exposures because adequate data to parameterize such modifications do 

13 not exist for rats or humans. The inhalation Young et al. (1977) model failed to provide adequate 

14 fits to the subchronic exposure plasma levels of 1,4-dioxane in rats using the data from the Kasai 

15 et al. (2008) study.

16 Several procedures were applied to the human PBPK model to determine if an adequate 

17 fit of the model to the empirical model output or experimental observations could be attained 

18 using biologically plausible values for the model parameters. The re-calibrated model 

19 predictions for blood 1,4-dioxane levels do not come within 10-fold of the experimental values 

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Metab and slow PCfitted model

observations

Young et al. (1977) empirical 

model

Metabolism and slow PCfitted model

Young et al. (1977) 

observation data

1,4-Dioxane in human blood from a 6-hour,

 50 ppm exposure

0.1

2.1

4.1

6.1

8.1

10.1

12.1

14.1

16.1

0 2 4 6 8 10 12 14

Time (hrs)

Blood 1,4-Dioxane Concentration 

(mg/L)

Young empirical model

Metab and slow PCfitted model

observations

Young et al. (1977) empirical 

model

Metabolism and slow PCfitted model

Young et al. (1977) 

observation data
B-24

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 using measured tissue:air partition coefficients from Leung and Paustenbach (1990) or Sweeney 

2 et al. (2008) (Figures B-9 and B-10). Use of a slowly perfused tissue:air partition coefficient 10-

3 fold lower than measured values produces exposure-phase predictions that are much closer to 

4 observations, but does not replicate the elimination kinetics (Figure B-11). Re-calibration of the 

5 model with upper bounds on the tissue:air partition coefficients results in predictions that are still 

6 six- to sevenfold lower than empirical model prediction or observations (Figures B-13 and B-14). 

7 Exploration of the model space using an assumption of first-order metabolism (valid for the 50-

8 ppm inhalation exposure) showed that an adequate fit to the exposure and elimination data can 

9 be achieved only when unrealistically low values are assumed for the slowly perfused tissue:air 

10 partition coefficient (Figure B-17). Artificially low values for the other tissue:air partition 

11 coefficients are not expected to improve the model fit, because the sensitivity analysis to exert 

12 less influence on blood 1,4-dioxane than VmaxC and Km. This suggests that the model structure is 

13 insufficient to capture the apparent 10-fold species difference in the blood 1,4-dioxane Vd

14 between rats and humans. In the absence of actual measurements for the human slowly perfused 

15 tissue:air partition coefficient, high uncertainty exists for this model parameter value. 

16 Differences in the ability of rat and human blood to bind 1,4-dioxane may contribute to the 

17 difference in Vd. However, this is expected to be evident in very different values for rat and 

18 human blood:air partition coefficients, which is not the case (Table B-1). Therefore, some other, 

19 as yet unknown, modification to model structure may be necessary. Sweeney et al. (2008) PBPK 

20 model provided an overall improvement on previous models; however, the Sweeney et al. (2008)

21 inhalation model predictions of animal and human data were problematic.
B-25

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

B.7. acslXtreme CODE FOR THE YOUNG ET AL. EMPIRCAL MODEL FOR 

1,4-DIOXANE IN RATS

1 PROGRAM: Young (1978a) rat.csl 

2 !-----------------------------------------------------------------

3 ! Created by Michael Lumpkin, Syracuse Research Corporation, 08/06

4 ! This program implements the 1-compartment empirical model for 1,4-dioxane

5 ! in rats, developed by Young et al. 1978a, b. Program was modified to run

6 ! in ACSL Xtreme and to include user-defined i.v. and inhalation concentrations 

7 !(MLumpkin, 08/06)

8 !-----------------------------------------------------------------

9

10 INITIAL

11

12 !*****Timing and Integration Commands*****

13 ALGORITHM IALG=2 !Gear integration algorithm for stiff systems 

14 !MERROR %%%%=0.01 !Relative error for lead in plasma

15 NSTEPS NSTP=1000 !Number of integration steps per communication interval

16 CINTERVAL CINT=0.1 !Communication interval

17 CONSTANT TSTART=0. !Start of simulation (hr)

18 CONSTANT TSTOP=70. !End of simulation (hr)

19

20 !*****MODEL PARAMETERS*****

21 CONSTANT BW=0.215 !Body weight (kg)

22 CONSTANT MINVOL=0.238 !respiratory minute volume (L/min) estimated from Young et al. 

23 (1978)

24 CONSTANT IVDOSE = 0. !IV dose (mg/kg)! 

25 CONSTANT CONC = 0. !inhalation concentration (ppm)

26

27 CONSTANT MOLWT=88.105 !mol weight of 1,4-dioxane

28 CONSTANT TCHNG=6.0 !Exposure pulse 1 width (hr)

29 CONSTANT TDUR=24.0 !Exposure duration (hr)

30 CONSTANT TCHNG2=120.0 !Exposure pulse 2 width (hr)

31 CONSTANT TDUR2=168.0 !Exposure duration 2 (hr)

32

33 CONSTANT Vmax=4.008 !(mcg/mL/hr) 

34 CONSTANT Km=6.308 !(mcg/mL) 

35 CONSTANT Kinh=0.43 !pulmonary absorption constant (/hr)

36 CONSTANT Ke=0.0149 !(/hr)

37 CONSTANT Kme=0.2593 !(/hr)

38 CONSTANT Vd=0.3014 !(L)

39

40 IV = IVDOSE*BW 

41 AmDIOXi=IV

42

43 END !Of Initial Section

44

45 DYNAMIC
B-26

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 DERIVATIVE

2

3 !*** Dioxane inhalation concentration ***

4 CIZONE=PULSE(0.0, TDUR, TCHNG) * PULSE(0.0, TDUR2, TCHNG2)

5 !First pulse is hours/day, second pulse is hours/week

6 CI=CONC*CIZONE*MOLWT/24450. !Convert to mg/L

7

8 !*** Dioxane metabolism/1st order elimination ***

9 dAmDIOX=(Kinh*CI*(MINVOL*60))-((Vmax*(AmDIOX))/(Km+(AmDIOX)))-

10 (Ke*(AmDIOX))

11 AmDIOX=INTEG(dAmDIOX,AmDIOXi)

12 ConcDIOX=AmDIOX/Vd !plasma dioxane concentration (mcg/mL)

13 AUCDIOX=INTEG(ConcDIOX,0) !plasma dioxane AUC

14

15 !*** HEAA production and 1st order metabolism ***

16 dAmHEAA=((Vmax*(AmDIOX))/(Km+(AmDIOX)))-(Kme*(AmHEAA))

17 AmHEAA=INTEG(dAmHEAA,0.) 

18 ConcHEAA=AmHEAA/Vd !plasma HEAA concentration

19

20 !*** 1st order dioxane elimination to urine ***

21 dAmDIOXu=(Ke*(AmDIOX))*0.35

22 AmDIOXu=INTEG(dAmDIOXu,0.) 

23 ConcDIOXu=Ke*AmDIOX*0.35/1.45e-3 !urine production approx 1.45e-3 L/hr in SD rats

24

25 !*** 1st order dioxane exhaled ***

26 dAmDIOXex=(Ke*(AmDIOX))*0.65

27 AmDIOXex=INTEG(dAmDIOXex,0.) 

28

29 !*** 1st order HEAA elimination to urine ***

30 dAmHEAAu=(Kme*(AmHEAA))

31 AmHEAAu=INTEG(dAmHEAAu,0.) 

32 ConcHEAAu=Kme*AmHEAA/1.45e-3 !urine production approx 1.45e-3 L/hr in SD rats

33

34 END !of Derivative Section

35

36 DISCRETE

37

38 END !of Discrete Section

39

40 TERMT (T .GT. TSTOP)

41

42 END !of Dynamic Section

43

44 TERMINAL

45

46 END !of Terminal Section

47

48 END !of Program
B-27

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

B.8. acslXtreme CODE FOR THE YOUNG ET AL. EMPIRICAL MODEL FOR 

1,4-DIOXANE IN HUMANS

1 PROGRAM: Young (1977) human.csl

2 !-----------------------------------------------------------------

3 ! Created by Michael Lumpkin, Syracuse Research Corporation, 01/06

4 ! This program implements the 1-compartment model for 1,4-dioxane in humans,

5 ! developed by Young et al., 1977. Program was modified to run

6 ! in acslXtreme (MLumpkin, 08/06)

7 !-----------------------------------------------------------------

8

9 INITIAL

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=120. !End of simulation (hr)

18

19 !*****MODEL PARAMETERS*****

20 !CONSTANT DATA=1 !Optimization dataset

21 CONSTANT MOLWT=88.105 !mol weight for 1,4-dioxane

22 CONSTANT DOSE=0. !Dose (mg/kg

23 CONSTANT CONC=0. !Inhalation concentration (ppm)

24 CONSTANT BW=84.1 !Body weight (kg)

25 CONSTANT MINVOL=7.0 !pulmonary minute volume (L/min)

26 CONSTANT F=1.0 !Fraction of dose absorbed

27 CONSTANT kinh=1.06 !Rate constant for inhalation (mg/hr); optimized by MHL

28 CONSTANT ke=0.0033 !Rate constant for dioxane elim to urine (hr-1)

29 CONSTANT km=0.7096 !Rate constant for metab of dioxane to HEAA (hr-1)

30 CONSTANT kme=0.2593 !Rate constant for transfer from rapid to blood (hr-1)

31 CONSTANT VdDkg=0.104 !Volume of distribution for dioxane (L/kg BW)

32

33 CONSTANT VdMkg=0.480 !Volume of distribution for HEAA (L/kg BW)

34 CONSTANT OStart=0. !Time of first oral dose (hr)

35 CONSTANT OPeriod=120. !Oral Dose pulse period (hr)

36 CONSTANT OWidth=1. !Width (gavage/drink time) of oral dose (hr)

37

38 CONSTANT IStart=0. !Time of inhalation onset (hr)

39 CONSTANT IPeriod=120. !Inhalation pulse period (hr)

40 CONSTANT IWidth=6. !Width (duration) of inhalation exposure (hr)

41

42 END !Of Initial Section

43

44 DYNAMIC

45

46 DERIVATIVE
B-28

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 ! VARIABLES and DEFINED VALUES** ***

2 VdD=BW*VdDkg !Volume of distribution for dioxane

3 VdM=BW*VdMkg !Volume of distribution for HEAA

4

5 InhalePulse=PULSE(IStart,IPeriod,IWidth)

6 Inhale=CONC*InhalePulse*MOLWT/24450. !Convert to mg/L

7

8 !*****DIFFERENTIAL EQUATIONS FOR COMPARTMENTS 

9

10 !** * Dioxane in the body (plasma) ***

11 dAMTbD=(Kinh*Inhale*(MINVOL*60))-(AMTbD*km)-(AMTbD*ke)

12 AMTbD=INTEG(dAMTbD,0.)

13 CbD=AMTbD/VdD

14 AUCbD=INTEG(CbD,0)

15

16 !*** HEAA in the body (plasma)***

17 dAMTbM=AMTbD*km-AMTbM*kme

18 AMTbM=INTEG(dAMTbM,0.)

19 CbM=AMTbM/VdM

20

21 !*** Cumulative Dioxane in the urine ***

22 dAMTuD=(AMTbD*ke)

23 AMTuD=INTEG(dAMTuD,0.)

24

25 !*** Cumulative HEAA in the urine ***

26 dAMTuM=(AMTbM*kme)

27 AMTuM=INTEG(dAMTuM,0.)

28

29 END !Of Derivative Section

30

31 DISCRETE

32

33 END !of Discrete Section

34

35 TERMT (T .GT. TSTOP)

36

37 END !Of Dynamic Section

38

39 TERMINAL

40

41 END !of Terminal Section

42

43 END !of Program
B-29

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

B.9. acslXtreme CODE FOR THE REITZ ET AL. PBPK MODEL FOR 1,4- DIOXANE

1 (Reitz, et al., 1990)

2 PROGRAM: DIOXANE.CSL (Used in Risk Estimation Procedures)

3 !Added a venous blood compartment and 1st order elim of metab.'

4 !Mass Balance Checked OK for Inhal, IV, Oral, and Water RHR'

5 !Defined Dose Surrogates for Risk Assessment 01/04/89'

6 !Modified the Inhal Route to use PULSE for exposure conditions'

7 !Modifications by GLDiamond, Aug2004, marked as !**

8 !

9 !Metabolism of dioxane modified by MLumpkin, Oct2006, to include 1st order

10 !or saturable kinetics. For 1st order, set VmaxC=0; for M-Menten, set KlC=0.

11 !

12 INITIAL

13

14 INTEGER I 

15 I=1

16 ! ARRAY TDATA(20) ! CONSTANT TDATA=999, 19*1.0E-6 !**

17 CONSTANT BW = 0.40 !'Body weight (kg)'

18 CONSTANT QPC = 15. !'Alveolar ventilation rate (l/hr)'

19 CONSTANT QCC = 15. !'Cardiac output (l/hr)'

20

21 !Flows to Tissue Compartments'

22 CONSTANT QLC = 0.25 !'Fractional blood flow to liver'

23 CONSTANT QFC = 0.05 !'Fractional blood flow to fat'

24 CONSTANT QSC = 0.18 !'Fractional blood flow to slow'

25 QRC = 1.0 - (QFC + QSC + QLC)

26 CONSTANT SPDC = 1.0 ! diffusion constant for slowly perfused tissues

27

28 !Volumes of Tissue/Blood Compartments'

29 CONSTANT VLC = 0.04 !'Fraction liver tissue'

30 CONSTANT VFC = 0.07 !'Fraction fat tissue'

31 CONSTANT VRC = 0.05 !'Fraction Rapidly Perf tissue'

32 CONSTANT VBC = 0.05 !'Fraction as Blood'

33 VSC = 0.91 - (VLC + VFC + VRC + VBC)

34

35 !Partition Coefficients'

36 CONSTANT PLA = 1557. !'Liver/air partition coefficient'

37 CONSTANT PFA = 851. !'Fat/air partition coefficient'

38 CONSTANT PSA = 2065. !'Muscle/air (Slow Perf) partition'

39 CONSTANT PRA = 1557. !'Richly perfused tissue/air partition'

40 CONSTANT PB = 1850. !'Blood/air partition coefficient'

41

42 !Other Compound Specific Parameters'

43 CONSTANT MW = 88.1 !'Molecular weight (g/mol)'

44 CONSTANT KLC = 12.0 ! temp zero-order metab constant

45 CONSTANT VMAXC = 13.8 !'Maximum Velocity of Metabol.'

46 CONSTANT KM = 29.4 !'Michaelis Menten Constant'

47 CONSTANT ORAL = 0.0 !'Oral Bolus Dose (mg/kg)'
B-30

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 CONSTANT KA = 5.0 !'Oral uptake rate (/hr)'

2 CONSTANT WATER = 0.0 !'Conc in Water (mg/liter, ppm)'

3 CONSTANT WDOSE=0.0 !Water dose (mg/kg/day) **

4 CONSTANT IV = 0.0 !'IV dose (mg/kg)'

5 CONSTANT CONC = 0.0 !'Inhaled concentration (ppm)'

6 CONSTANT KME = 0.276 !'Urinary Elim constant for met (hr-1)'

7

8 !Timing commands'

9 CONSTANT TSTOP = 50 !'Length of experiment (hrs)'

10 CONSTANT TCHNG = 6 !'Length of inhalation exposure (hrs)'

11 CINTERVAL CINT=0.1

12 CONSTANT WIDD=24. !**

13 CONSTANT PERD=24. !**

14 CONSTANT PERW=168. !**

15 CONSTANT WIDW=168. !**

16 CONSTANT DAT=0.017 !**

17

18 !Scaled parameters calculated in this section of Program'

19 QC=QCC*BW**0.74

20 QP=QPC*BW**0.74

21 QL=QLC*QC

22 QF=QFC*QC

23 QS=QSC*QC

24 QR=QRC*QC

25 VL=VLC*BW

26 VF=VFC*BW

27 VS=VSC*BW 

28 VR=VRC*BW

29 VB=VBC*BW

30 PL=PLA/PB

31 PR=PRA/PB

32 PS=PSA/PB

33 PF=PFA/PB

34 KL = KLC*bw**0.7 ! Zero-order metab constant 

35 VMAX = VMAXC*BW**0.7

36 DOSE = ORAL*BW !'Initial Amount in Stomach'

37 AB0 = IV*BW !'Initial Amount in Blood'

38 !DRINK = 0.102*BW**0.7*WATER/24 !'Input from water (mg/hr)' !**

39 !DRINKA = 0.102*BW**0.7*WATER/DAT !'Input from water (mg/hr)' !**

40 DRINKA=WDOSE*BW/DAT

41 CV = AB0/VB !'Initialize CV'

42

43 END !'End of INITIAL'

44

45 DYNAMIC

46

47 ALGORITHM IALG = 2 !'Gear method for stiff systems'

48 TERMT(T .GE. TSTOP )
B-31

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 CR = AR/VR

2 CS = AS/VS

3 CF = AF/VF

4 BODY = AL + AR + AS + AF + AB + TUMMY

5 BURDEN = AM + BODY

6 TMASS = BURDEN + AX + AMEX

7

8 !Calculate the Interval Excretion Data here:'

9 ! DAX = AMEX-AMEX2

10 ! IF(DOSE .LE. 0.0 .AND. IV .LE. 0.0 ) GO TO SKIP1

11 ! PCTAX = 100*(AX - AX2)/(DOSE + IV*BW)

12 ! PCTMX = 100*(AMEX - AMEX2)/(DOSE + IV*BW)

13 ! SKIP1.. CONTINUE

14 ! IF(T .LT. TDATA(I) .OR. I .GE. 20 ) GO TO SKIP

15 ! AX2=AX

16 ! AMEX2=AMEX

17 ! I=I+1

18 ! SKIP.. CONTINUE

19

20 !DISCRETE EXPOSE

21 ! CIZONE = 1.0 ! CALL LOGD(.TRUE.) Turns on inhalation exposure?

22 !END

23 !DISCRETE CLEAR

24 ! CIZONE = 0.0 ! CALL LOGD(.TRUE.)

25 !END

26

27 DERIVATIVE

28

29 !Use Zero-Crossing Form of DISCRETE Function Here'

30 ! SCHEDULE command must be in DERIVATIVE section'

31 ! DAILY = PULSE (0.0, PER1, TCHNG )

32 ! WEEKLY = PULSE (0.0, PER2, LEN2 )

33 ! SWITCHY = DAILY * WEEKLY

34 !SCHEDULE EXPOSE .XP. SWITCHY - 0.995

35 !SCHEDULE CLEAR .XN. SWITCHY - 0.005

36

37 DAILY=PULSE(0.0,PERD,WIDD)

38 WEEKLY=PULSE(0.0,PERW,WIDW)

39 SWITCHY = DAILY * WEEKLY

40

41 !**********************Modified Here for Wong*****************'

42 CI = CONC * MW / 24451.0 * SWITCHY!**

43

44 !CA = Concentration in arterial blood (mg/l)'

45 CA = (QC*CV+QP*CI)/(QC+(QP/PB))

46 CX = CA/PB

47

48 DRINK=DRINKA*SWITCHY !**
B-32

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 !TUMMY = Amount in stomach'

3 RTUMMY = -KA*TUMMY

4 TUMMY = INTEG(RTUMMY,DOSE)

5 !RAX = Rate of Elimination in Exhaled air'

6 RAX = QP*CX

7 AX = INTEG(RAX, 0.0)

8

9 !AS = Amount in slowly perfused tissues (mg)'

10 RAS = SPDC*(CA-CVS) !now governed by diffusion-limited constant, SPDC, instead of QS

11 AS = INTEG(RAS,0.)

12 CVS = AS/(VS*PS)

13

14 !AR = Amount in rapidly perfused tissues (mg)'

15 RAR = QR*(CA-CVR)

16 AR = INTEG(RAR,0.)

17 CVR = AR/(VR*PR)

18

19 !AF = Amount in fat tissue (mg)'

20 RAF = QF*(CA-CVF)

21 AF = INTEG(RAF,0.)

22 CVF = AF/(VF*PF)

23

24 !AL = Amount in liver tissue (mg)'

25 RAL = QL*(CA-CVL) - KL*CVL - VMAX*CVL/(KM+CVL) + KA*TUMMY + DRINK 

26 AL = INTEG(RAL,0.)

27 CVL = AL/(VL*PL)

28

29 !Metabolism comments updated by EDM on 2/1/10

30 !AM = Amount metabolized (mg)'

31 RMEX = (KL*CVL)+(VMAX*CVL/(KM+CVL)) !Rate of 1,4-dioxane metabolism 

32 RAM = (KL*CVL)+(VMAX*CVL)/(KM+CVL) - KME*AM !Rate of change of metabolite 

33 in body

34

35 AM = INTEG(RAM, 0.0) !'Amt Metabolite in body

36 CAM = AM/BW !'Conc Metabolite in body'

37 AMEX = INTEG(KME*AM, 0.0) !'Amt Metabolite Excreted via urine'

38

39 !AB = Amount in Venous Blood'

40 RAB = QF*CVF + QL*CVL + QS*CVS + QR*CVR - QC*CV

41 AB = INTEG(RAB, AB0)

42 CV = AB/VB

43 AUCV = INTEG(CV, 0.0)

44

45 !Possible Dose Surrogates for Risk Assessment Defined Here'

46

47 CEX = 0.667*CX + 0.333*CI !'Conc in Exhal Air'

48 AVECON = PLA * (CEX+CI)/2 !'Ave Conc in Nose Tissue'
B-33

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 AUCCON = INTEG(AVECON, 0.0) !'Area under Curve (Nose)'

2

3 AUCMET = INTEG(CAM, 0.0) !'Area under Curve (Metab)'

4

5 CL = AL/VL !'Conc Liver Tissue'

6 AUCL = INTEG(CL, 0.0) !'Area under Curve (Liver)'

7 AAUCL=AUCL/TIME

8

9 ! Dose Surrogates are Average Area under Time/Conc Curve per 24 hrs'

10 IF (T .GT. 0) TIME=T

11 dayS = TIME/24.0

12 NOSE = AUCCON/DAYS !'Nasal Turbinates'

13 LIVER = AUCL/DAYS !'Liver Tissues'

14 METAB = AUCMET/DAYS !'Stable Metabolite'

15

16 END !'End of dynamic'

17

18 END ! End of TERMINAL

19

20 END !'End of PROGRAM
C-1

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

C.1. CORTICAL TUBULE DEGENERATION

1 All available dichotomous models in the Benchmark Dose Software (version 2.1.1) were

2 fit to the incidence data shown in Table C-1, for cortical tubule degeneration in male and female 

3 Osborne-Mendel rats exposed to 1,4-dioxane in the drinking water (NCI, 1978). Doses 

4 associated with a BMR of a 10% extra risk were calculated.

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

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

Males (mg/kg-day) Females (mg/kg-day)

0 240 530 0 350 640

0/31a20/31b

(65%)

27/33b

(82%)

0/31a0/34 10/32b

(31%)

a

Statistically significant trend for increased incidence by Cochran-Armitage test (p < 0.05) performed for this 

review.

b

Incidence significantly elevated compared to control by Fisher‘s exact test (p < 0.05) performed for this review.

Source: NCI (1978).

As assessed by the χ25 goodness-of-fit test, several models in the software provided 

6 adequate fits to the data for the incidence of cortical tubule degeneration in male and female rats 

(χ27 p ≥ 0.1) (Table C-2). Comparing across models, a better fit is indicated by a lower AIC 

8 value (U.S. EPA, 2000a). As assessed by Akaike‘s Information Criterion (AIC), the log-probit 

9 model provided the best fit to the cortical tubule degeneration incidence data for male rats 

10 (Table C-2, Figure C-1) and could be used to derive a POD of 38.5 mg/kg-day for this endpoint. 

11 The Weibull model provided the best fit to the data for female rats (Table C-2, Figure C-5) and 

12 could be used to derive a POD of 452.4 mg/kg-day for this endpoint. For those models that 

13 exhibit adequate fit, models with the lower AIC values are preferred. Differences in AIC values 

14 of less than 1 are generally not considered important. BMDS modeling results for all 

15 dichotomous models are shown in Table C-2. 

 

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

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

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

and the Integrated Risk Information System (IRIS)
C-2

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

models fit to incidence data for cortical tubule degeneration in male and 

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

water

1

Model AIC p-valuea

Scaled 

Residual of 

Interest

BMD10

(mg/kg-day)

BMDL10

(mg/kg-day)

Male

Gammab74.458 0.6514 0 28.80 22.27

Logistic 89.0147 0.0011 -1.902 88.48 65.84

Log-logisticc75.6174 1 0 20.85 8.59

Log-probitc74.168 0.7532 0 51.41 38.53

Multistage 

(2 degree)d74.458 0.6514 0 28.80 22.27

Probit 88.782 0.0011 -1.784 87.10 66.32

Weibullb74.458 0.6514 0 28.80 22.27

Quantal-Linear 74.458 0.6514 0 28.80 22.27

Female

Gammab41.9712 0.945 0.064 524.73 437.08

Logistic 43.7495 0.9996 0 617.44 471.92

Log-logisticc41.7501 0.9999 0 591.82 447.21

Log-probitc43.7495 0.9997 0 584.22 436.19

Multistage 

(2 degree)d48.1969 0.1443 -1.693 399.29 297.86

Probit 43.7495 0.9997 0 596.02 456.42

Weibullb41.75 0.9999 0 596.45 452.36

Quantal-Linear 52.3035 0.03 -2.086 306.21 189.49

a

p-Value from the χ2goodness-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.

dBetas 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 ==================================================================== 

2 Probit Model. (Version: 3.1; Date: 05/16/2008) 

3 Input Data File: C:\14DBMDS\lnp_nci_mrat_cortdeg_Lnp-BMR10-restrict.(d) 

4 Gnuplot Plotting File: C:\14DBMDS\lnp_nci_mrat_cortdeg_Lnp-BMR10-restrict.plt

5 Mon Feb 01 14:49:17 2010

6 ==================================================================== 

7 BMDS Model Run 

8 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

9 The form of the probability function is: 

10

11 P[response] = Background + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)),

12

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 = 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

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 100 200 300 400 500 

dose

LogProbit Model with 0.95 Confidence Level

14:49 02/01 2010

BMDL BMD

 

LogProbit
C-4

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 User has chosen the log transformed model

2

3

4 Default Initial (and Specified) Parameter Values 

5 background = 0

6 intercept = -5.14038

7 slope = 1

8

9

10 Asymptotic Correlation Matrix of Parameter Estimates

11 (*** The model parameter(s) -background -slope have been estimated at a boundary 

12 point, or have been specified by the user, and do not appear in the correlation 

13 matrix)

14

15 intercept

16 intercept 1

17

18

19 Parameter Estimates

20

21 95.0% Wald Confidence Interval

22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

23 background 0 NA

24 intercept -5.22131 0.172682 -5.55976 -4.88286

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

31

32 Analysis of Deviance Table

33

34 Model Log(likelihood) # Param's Deviance Test d.f. P-value

35 Full model -35.8087 3

36 Fitted model -36.084 1 0.550629 2 0.7593

37 Reduced model -65.8437 1 60.07 2 <.0001

38

39 AIC: 74.168

40

41

42 Goodness of Fit 

43 Scaled

44 Dose Est._Prob. Expected Observed Size Residual

45 ------------------------------------------------------------------------

46 0.0000 0.0000 0.000 0.000 31 0.000

47 240.0000 0.6023 18.672 20.000 31 0.487

48 530.0000 0.8535 28.166 27.000 33 -0.574

49

50 Chi^2 = 0.57 d.f. = 2 P-value = 0.7532

51

52

53 Benchmark Dose Computation

54 Specified effect = 0.1

55 Risk Type = Extra risk 

56 Confidence level = 0.95

57 BMD = 51.4062

58 BMDL = 38.5284
C-5

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

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 ==================================================================== 

2 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: Z:\14Dioxane\BMDS\wei_nci_frat_cortdeg_Wei-BMR10-Restrict.(d) 

4 Gnuplot Plotting File: Z:\14Dioxane\BMDS\wei_nci_frat_cortdeg_Wei-BMR10-Restrict.plt

5 Fri Dec 04 14:20:41 2009

6 ==================================================================== 

7 BMDS Model Run 

8 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

9 The form of the probability function is: 

10

11 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)]

12

13 Dependent variable = Effect

14 Independent variable = Dose

15 Power parameter is restricted as power >=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

24

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600 

dose

Weibull Model with 0.95 Confidence Level

14:20 12/04 2009

BMDL BMD

 

Weibull
C-6

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial (and Specified) Parameter Values 

2 Background = 0.015625

3 Slope = 1.55776e-010

4 Power = 3.33993

5

6

7 Asymptotic Correlation Matrix of Parameter Estimates

8 (*** The model parameter(s) -Background -Power have been estimated at a boundary 

9 point, or have been specified by the user, and do not appear in the correlation 

10 matrix)

11

12 Slope

13 Slope -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 NA

19 Slope 1.15454e-051 1.#QNAN 1.#QNAN 1.#QNAN

20 Power 18 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 Analysis of Deviance Table

26

27 Model Log(likelihood) # Param's Deviance Test d.f. P-value

28 Full model -19.8748 3

29 Fitted model -19.875 1 0.000487728 2 0.9998

30 Reduced model -32.1871 1 24.6247 2 <.0001

31

32 AIC: 41.75

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 0.0000 0.000 0.000 34 -0.016

41 640.0000 0.3125 9.999 10.000 32 0.000

42

43 Chi^2 = 0.00 d.f. = 2 P-value = 0.9999

44

45

46 Benchmark Dose Computation

47 Specified effect = 0.1

48 Risk Type = Extra risk 

49 Confidence level = 0.95

50 BMD = 596.445

51 BMDL = 452.359
C-7

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

C.2. LIVER HYPERPLASIA 

1 All available dichotomous models in the Benchmark Dose Software (version 2.1.1) were 

2 fit to the incidence data shown in Table C-3, for liver hyperplasia in male and female 

3 F344/DuCrj rats exposed to 1,4-dioxane in the drinking water (JBRC, 1998; Kano, et al., 2009). 

4 Benchmark doses associated with a BMR of a 10% extra risk were calculated.

Table C-3. Incidence of liver hyperplasia in F344/DuCrj rats exposed to 

1,4-dioxane in drinking watera

Males (mg/kg-day) Females (mg/kg-day)

0 11 55 274 0 18 83 429

3/40 2/45 9/35a12/22c2/38b2/37 9/38 24/24c

aDose information from Kano et al. (2009) and incidence data from sacrificed animals from JBRC (1998).

b

Incidence significantly elevated compared to control by χ2test (p < 0.05).

c

Incidence significantly elevated compared to control by χ2test (p < 0.01).

Sources: Kano et al. (2009); JBRC (1998).

5 For incidence of liver hyperplasia in F344 male rats, the logistic, probit, and 

dichotomous-Hill models all exhibited a statistically significant lack of fit (i.e., 26 p-value < 0.1; 

7 see Table C-4), and thus should not be considered further for identification of a POD. All of the 

8 remaining models exhibited adequate fit, but the AIC values for the gamma, multistage, quantal9 linear, and Weibull models were lower than the AIC values for the log-logistic and log-probit 

10 models. Finally, the AIC values for gamma, multistage, quantal-linear, and Weibull models in 

11 Table C-4 are equivalent and, in this case, essentially represent the same model. Therefore, 

12 consistent with the external review draft Benchmark Dose Technical Guidance (U.S. EPA, 

13 2000a), any of them with equal AIC values (gamma, multistage, quantal-linear, or Weibull) 

14 could be used to identify a POD for this endpoint of 23.8 mg/kg-day.

15 For liver hyperplasias in F344 female rats exposed to 1,4-dioxane, the quantal-linear and 

dichotomous-Hill models did not result in a good fit (i.e., 216 p-value < 0.1; See Table C-4). The 

17 multistage (3-degree) model had the lowest AIC value and was selected as the best-fitting model. 

18 Therefore, consistent with the BMD technical guidance document (U.S. EPA, 2000a), the 

19 BMDL from the multistage (3-degree) model was selected to yield a POD for this endpoint of 

20 27.1 mg/kg-day.
C-8

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

hyperplasias in male and female F344 rats exposed to 1,4-dioxane in drinking 

water for 2 years

Model AIC p-valuea

Scaled 

Residual of 

Interest

BMD10

(mg/kg-day)

BMDL10

(mg/kg-day)

Male

Gammab114.172 0.3421 0.886 35.90 23.81

Logistic 117.047 0.0706 1.869 83.56 63.29

Log-logisticc115.772 0.1848 0.681 33.39 16.96

Log-probitc115.57 0.1431 1.472 54.91 37.05

Multistaged

(2 degree) 114.172 0.3421 0.886 35.90 23.81

Probit 116.668 0.0859 1.804 76.69 58.57

Weibullb114.172 0.3421 0.886 35.90 23.81

Quantal-Linear 114.172 0.3421 0.886 35.90 23.81

Dichotomous-Hill 117.185 NCe-0.2398 32.01 14.84

Female

Gammab78.8357 0.9783 0 70.78 40.51

Logistic 77.0274 0.9174 -0.016 54.66 41.11

Log-logisticc78.8357 0.9781 0 77.72 51.21

Log-probitc78.8357 0.9781 0 74.64 50.97

Multistaged

(2 degree) 76.9718 0.9563 -0.107 56.06 31.17

Multistaged

(3 degree) 76.8351 0.9999 0 65.28 27.08

Probit 77.0308 0.9095 0.017 52.53 38.44

Weibullb78.8349 0.9995 0 66.47 36.14

Quantal-Linear 87.3833 0.0245 -1.116 21.52 15.61

Dichotomous-Hill 2972.99 NCe0 NCe NCe

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eNC=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 support 

results Table C-4.

1 ==================================================================== 

2 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

3 Input Data File: Z:\14Dioxane\BMDS\gam_jbrc1998_mrat_liver_hyper_Gam-BMR10-

4 Restrict.(d) 

5 Gnuplot Plotting File: Z:\14Dioxane\BMDS\gam_jbrc1998_mrat_liver_hyper_Gam-BMR10-

6 Restrict.plt

7 Fri Dec 04 14:35:02 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

12

13 P[response]= background+(1-background)*CumGamma[slope*dose,power],

14 where CumGamma(.) is the cummulative Gamma distribution function

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Power parameter is restricted as power >=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

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250 

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Gamma Multi-Hit
C-10

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Parameter Convergence has been set to: 1e-008

2

3

4 Default Initial (and Specified) Parameter Values 

5 Background = 0.0853659

6 Slope = 0.00479329

7 Power = 1.3

8

9

10 Asymptotic Correlation Matrix of Parameter Estimates

11 (*** The model parameter(s) -Power 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 Slope

15 Background 1 -0.36

16 Slope -0.36 1

17

18 Parameter Estimates

19 95.0% Wald Confidence Interval

20 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

21 Background 0.0569658 0.0278487 0.00238329 0.111548

22 Slope 0.00293446 0.000814441 0.00133818 0.00453073

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 -53.9471 4

32 Fitted model -55.0858 2 2.27725 2 0.3203

33 Reduced model -67.6005 1 27.3066 3 <.0001

34

35 AIC: 114.172

36

37

38 Goodness of Fit 

39 Scaled

40 Dose Est._Prob. Expected Observed Size Residual

41 ------------------------------------------------------------------------

42 0.0000 0.0570 2.279 3.000 40 0.492

43 11.0000 0.0869 3.911 2.000 45 -1.011

44 55.0000 0.1975 6.913 9.000 35 0.886

45 274.0000 0.5780 12.715 12.000 22 -0.309

46

47 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421

48

49

50 Benchmark Dose Computation

51 Specified effect = 0.1

52 Risk Type = Extra risk 

53 Confidence level = 0.95

54 BMD = 35.9046

55 BMDL = 23.8065
C-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 ==================================================================== 

2 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

3 Input Data File: Z:\14Dioxane\BMDS\mst_jbrc1998_mrat_liver_hyper_Mst-BMR10-

4 restrict.(d) 

5 Gnuplot Plotting File: Z:\14Dioxane\BMDS\mst_jbrc1998_mrat_liver_hyper_Mst-BMR10-

6 Restrict.plt

7 Fri Dec 04 14:35:06 2009

8 ==================================================================== 

9 BMDS Model Run 

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 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 = 3

23 Total number of specified parameters = 0

24 Degree of polynomial = 2

25

26

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250 

dose

Multistage Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Multistage
C-12

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Maximum number of iterations = 250

2 Relative Function Convergence has been set to: 1e-008

3 Parameter Convergence has been set to: 1e-008

4

5

6

7 Default Initial Parameter Values 

8 Background = 0.0750872

9 Beta(1) = 0.00263797

10 Beta(2) = 0

11

12

13 Asymptotic Correlation Matrix of Parameter Estimates

14 (*** The model parameter(s) -Beta(2) have been estimated at a boundary point, or have 

15 been specified by the user, and do not appear in the correlation matrix)

16

17 Background Beta(1)

18 Background 1 -0.49

19 Beta(1) -0.49 1

20

21

22 Parameter Estimates

23 95.0% Wald Confidence Interval

24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

25 Background 0.0569658 * * *

26 Beta(1) 0.00293446 * * *

27 Beta(2) 0 * * *

28

29 * - Indicates that this value is not calculated.

30

31

32

33 Analysis of Deviance Table

34

35 Model Log(likelihood) # Param's Deviance Test d.f. P-value

36 Full model -53.9471 4

37 Fitted model -55.0858 2 2.27725 2 0.3203

38 Reduced model -67.6005 1 27.3066 3 <.0001

39

40 AIC: 114.172

41

42

43 Goodness of Fit 

44 Scaled

45 Dose Est._Prob. Expected Observed Size Residual

46 ------------------------------------------------------------------------

47 0.0000 0.0570 2.279 3.000 40 0.492

48 11.0000 0.0869 3.911 2.000 45 -1.011

49 55.0000 0.1975 6.913 9.000 35 0.886

50 274.0000 0.5780 12.715 12.000 22 -0.309

51

52 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421

53

54

55 Benchmark Dose Computation

56 Specified effect = 0.1

57 Risk Type = Extra risk 

58 Confidence level = 0.95

59 BMD = 35.9046

60 BMDL = 23.8065

61 BMDU = 82.1206

62

63 Taken together, (23.8065, 82.1206) is a 90% two-sided confidence interval for the BMD
C-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 ==================================================================== 

2 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: Z:\14Dioxane\BMDS\wei_jbrc1998_mrat_liver_hyper_Wei-BMR10-

4 Restrict.(d) 

5 Gnuplot Plotting File: Z:\14Dioxane\BMDS\wei_jbrc1998_mrat_liver_hyper_Wei-BMR10-

6 Restrict.plt

7 Fri Dec 04 14:35:08 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

12

13 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)]

14

15 Dependent variable = Effect

16 Independent variable = Dose

17 Power 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

23 Parameter Convergence has been set to: 1e-008

24

25

26

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250 

dose

Weibull Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Weibull
C-14

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial (and Specified) Parameter Values 

2 Background = 0.0853659

3 Slope = 0.00253609

4 Power = 1

5

6

7 Asymptotic Correlation Matrix of Parameter Estimates

8 (** The model parameter(s) -Power have been estimated at a boundary point, or have 

9 been specified by the user, and do not appear in the correlation matrix )

10

11 Background Slope

12 Background 1 -0.36

13 Slope -0.36 1

14

15

16 Parameter Estimates

17 95.0% Wald Confidence Interval

18 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

19 Background 0.0569661 0.0278498 0.00238155 0.111551

20 Slope 0.00293445 0.000814445 0.00133816 0.00453073

21 Power 1 NA

22

23 NA - Indicates that this parameter has hit a bound implied by some inequality 

24 constraint and thus has no standard error.

25

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 = 35.9047

54 BMDL = 23.8065
C-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 

support the results in Table C-4.

1 ==================================================================== 

2 Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: Z:\14Dioxane\BMDS\qln_jbrc1998_mrat_liver_hyper_Qln-BMR10.(d) 

4 Gnuplot Plotting File: Z:\14Dioxane\BMDS\qln_jbrc1998_mrat_liver_hyper_Qln-BMR10.plt

5 Fri Dec 04 14:35:09 2009

6 ==================================================================== 

7 BMDS Model Run 

8 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

9 The form of the probability function is: 

10

11 P[response] = background + (1-background)*[1-EXP(-slope*dose)]

12

13

14 Dependent variable = Effect

15 Independent variable = Dose

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 Default Initial (and Specified) Parameter Values 

24 Background = 0.0853659

25 Slope = 0.00253609

26 Power = 1 Specified

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0 50 100 150 200 250 

dose

Quantal Linear Model with 0.95 Confidence Level

14:35 12/04 2009

BMDL BMD

 

Quantal Linear
C-16

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2 (*** The model parameter(s) -Power have been estimated at a boundary point, or have 

3 been specified by the user, and do not appear in the correlation matrix)

4

5 Background Slope

6 Background 1 -0.36

7 Slope -0.36 1

8

9

10

11 Parameter Estimates

12 95.0% Wald Confidence Interval

13 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

14 Background 0.0569665 0.02785 0.00238157 0.111551

15 Slope 0.00293447 0.000814452 0.00133818 0.00453077

16

17

18

19 Analysis of Deviance Table

20

21 Model Log(likelihood) # Param's Deviance Test d.f. P-value

22 Full model -53.9471 4

23 Fitted model -55.0858 2 2.27725 2 0.3203

24 Reduced model -67.6005 1 27.3066 3 <.0001

25

26 AIC: 114.172

27

28

29 Goodness of Fit 

30 Scaled

31 Dose Est._Prob. Expected Observed Size Residual

32 ------------------------------------------------------------------------

33 0.0000 0.0570 2.279 3.000 40 0.492

34 11.0000 0.0869 3.911 2.000 45 -1.011

35 55.0000 0.1975 6.913 9.000 35 0.886

36 274.0000 0.5780 12.716 12.000 22 -0.309

37

38 Chi^2 = 2.15 d.f. = 2 P-value = 0.3421

39

40

41 Benchmark Dose Computation

42 Specified effect = 0.1

43 Risk Type = Extra risk 

44 Confidence level = 0.95

45 BMD = 35.9044

46 BMDL = 23.8065
C-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 ==================================================================== 

2 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

3 Input Data File: H:\14Dioxane\BMDS\mst_jbrc1998_frat_liver_hyper_Mst-BMR10-Restrict4 3deg.(d) 

5 Gnuplot Plotting File: H:\14Dioxane\BMDS\mst_jbrc1998_frat_liver_hyper_Mst-BMR10-

6 Restrict-3deg.plt

7 Fri May 21 10:30:14 2010

8 ==================================================================== 

9 BMDS Model Run 

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 beta3*dose^3)]

15

16 The parameter betas are restricted to be positive

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 = 4

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 50 100 150 200 250 300 350 400 450 

dose

Multistage Model with 0.95 Confidence Level

10:30 05/21 2010

BMDL BMD

 

Multistage
C-18

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Total number of specified parameters = 0

2 Degree of polynomial = 3

3

4 Maximum number of iterations = 250

5 Relative Function Convergence has been set to: 1e-008

6 Parameter Convergence has been set to: 1e-008

7

8 Default Initial Parameter Values 

9 Background = 0

10 Beta(1) = 0

11 Beta(2) = 0

12 Beta(3) = 1.2696e+012

13

14 Asymptotic Correlation Matrix of Parameter Estimates

15

16 (*** The model parameter(s) -Beta(1), -Beta(2) have been estimated at a boundary 

17 point, or have been specified by the user, and do not appear in the correlation 

18 matrix)

19

20 Background Beta(3)

21 Background 1 -0.55

22 Beta(3) -0.55 1

23

24

25 Parameter Estimates

26

27 95.0% Wald Confidence Interval

28 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

29 Background 0.0523101 * * *

30 Beta(1) 0 * * *

31 Beta(2) 0 * * *

32 Beta(3) 3.78712e-007 * * *

33

34 * - Indicates that this value is not calculated.

35

36

37 Analysis of Deviance Table

38

39 Model Log(likelihood) # Param's Deviance Test d.f. P-value

40 Full model -36.4175 4

41 Fitted model -36.4175 2 0.00016582 2 0.9999

42 Reduced model -79.9164 1 86.9979 3 <.0001

43

44 AIC: 76.8351

45

46 Goodness of Fit 

47 Scaled

48 Dose Est._Prob. Expected Observed Size Residual

49 ------------------------------------------------------------------------

50 0.0000 0.0523 1.988 2.000 38 0.009

51 18.0000 0.0544 2.013 2.000 37 -0.009

52 83.0000 0.2368 8.999 9.000 38 0.000

53 429.0000 1.0000 24.000 24.000 24 0.000

54

55 Chi^2 = 0.00 d.f. = 2 P-value = 0.9999

56

57 Benchmark Dose Computation

58 Specified effect = 0.1

59 Risk Type = Extra risk 

60 Confidence level = 0.95

61 BMD = 65.2814

62 BMDL = 27.0766

63 BMDU = 91.3457

64

65 Taken together, (27.0766, 91.3457) is a 90% two-sided confidence interval for the BMD
D-1

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

1 Dichotomous models available in the Benchmark Dose Software (BMDS) (version 2.1.1) 

2 were fit to the incidence data for hepatocellular carcinoma and/or adenoma for mice and rats, as 

3 well as nasal cavity tumors, peritoneal mesotheliomas, and mammary gland adenomas in rats 

4 exposed to 1,4-dioxane in the drinking water. Doses associated with a benchmark response 

5 (BMR) of a 10% extra risk were calculated. BMD10 and BMDL10 values from the best fitting 

model, determined by adequate global- fit (χ2 6 p ≥ 0.1) and AIC values, are reported for each 

7 endpoint (U.S. EPA, 2000a). If the multistage cancer model is not the best fitting model for a 

8 particular endpoint, the best-fitting multistage cancer model for that endpoint is also presented as 

9 a point of comparison. 

10 A summary of the model predictions for the Kano et al. (2009) study are shown in 

11 Table D-1. The data and BMD modeling results are presented separately for each dataset as 

12 follows:

13 Hepatic adenomas and carcinomas in female F344 rats (Tables D-2 and D-3; Figure D-1)

14 Hepatic adenomas and carcinomas in male F344 rats (Tables D-4 and D-5; Figures D-2 

15 and D-3)

16 Significant tumor incidence data at sites other than the liver (i.e., nasal cavity, mammary 

17 gland, and peritoneal) in male and female F344 rats (Table D-6)

18 o Nasal cavity tumors in female F344 rats (Table D-7; Figure D-4)

19 o Nasal cavity tumors in male F344 rats (Table D-8; Figure D-5)

20 o Mammary gland adenomas in female F344 rats (Table D-9; Figures D-6 and D-7)

21 o Peritoneal mesotheliomas in male F344 rats (Table D-10; Figures D-8 and D-9)

22 Hepatic adenomas and carcinomas in female BDF1 mice (Tables D-11, D-12, and D-13; 

23 Figures D-10, D-11, D-12, and D-13)

24 Hepatic adenomas and carcinomas in male BDF1 mice (Tables D-14 and D-15; Figures 

25 D-14 and D-15)

26 Data and BMD modeling results from the additional chronic bioassays (Kociba, et al., 1974; 

27 NCI, 1978) were evaluated for comparison with the data from Kano et al. (2009). These results 

28 are presented as follows:

 

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

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

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

and the Integrated Risk Information System (IRIS)
D-2

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Summary of BMDS dose-response modeling estimates associated with liver and nasal 

2 tumor incidence data resulting from chronic oral exposure to 1,4-dioxane in rats and mice

3 (Table D-16)

4 Incidence of hepatocellular carcinoma and nasal squamous cell carcinoma in male and 

5 female Sherman rats (combined) (Kociba, et al., 1974) treated with 1,4-dioxane in the 

6 drinking water for 2 years (Table D-17)

7 o BMDS dose-response modeling results for incidence of hepatocellular carcinoma in 

8 male and female Sherman rats (combined) (Kociba, et al., 1974) exposed to 

9 1,4-dioxane in drinking water for 2 years (Table D-18; Figures D-16 and D-17)

10 o BMDS dose-response modeling results for incidence of nasal squamous cell 

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

12 exposed to 1,4-dioxane in the drinking water for 2 years (Table D-19; Figure D-18)

13 Incidence of nasal cavity squamous cell carcinoma and hepatocellular adenoma in 

14 Osborne-Mendel rats (NCI, 1978) exposed to 1,4-dioxane in the drinking water (Table D15 20)

16 o BMDS dose-response modeling results for incidence of hepatocellular adenoma in 

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

18 water for 2 years (Table D-21; Figures D-19 and D-20)

19 o BMDS dose-response modeling results for incidence of nasal cavity squamous cell 

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

21 drinking water for 2 years (Table D-22; Figures D-21 and D-22)

22 o BMDS dose-response modeling results for incidence of nasal cavity squamous cell 

23 carcinoma in male Osborne-Mendel rats (NCI, 1978) exposed to 1,4-dioxane in the 

24 drinking water for 2 years (Table D-23; Figures D-23 and D-24)

25 Incidence of hepatocellular adenoma or carcinoma in male and female B6C3F1 mice 

26 (NCI, 1978) exposed to 1,4-dioxane in drinking water (Table D-24)

27 o BMDS dose-response modeling results for the combined incidence of hepatocellular 

28 adenoma or carcinoma in female B6C3F1 mice (NCI, 1978) exposed to 1,4-dioxane in 

29 the drinking water for 2 years (Table D-25; Figure D-25)

30 o BMDS dose-response modeling results for incidence of combined hepatocellular 

31 adenoma or carcinoma in male B6C3F1 mice (NCI, 1978) exposed to 1,4-dioxane in 

32 the drinking water for 2 years (Table D-26; Figures D-26 and D-27). 

D.1. GENERAL ISSUES AND APPROACHES TO BMDS MODELING

D.1.1. Combining Data on Adenomas and Carcinomas

33 The incidence of adenomas and the incidence of carcinomas within a dose group at a site 

34 or tissue in rodents are sometimes combined. This practice is based upon the hypothesis that 
D-3

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 adenomas may develop into carcinomas if exposure at the same dose was continued (McConnell, 

2 et al., 1986; U.S. EPA, 2005a). The incidence at high doses of both tumors in rat and mouse 

3 liver is high in the key study (Kano, et al., 2009). The incidence of hepatic adenomas and 

4 carcinomas was summed without double-counting them so as to calculate the combined 

5 incidence of either a hepatic carcinoma or a hepatic adenoma in rodents. 

6 The variable N is used to denote the total number of animals tested in the dose group. 

7 The variable Y is used here to denote the number of rodents within a dose group that have 

8 characteristic X, and the notation Y(X) is used to identify the number with a specific 

9 characteristic X. Modeling was performed on the adenomas and carcinomas separately and the 

10 following combinations of tumor types:

11 Y(adenomas) = number of animals with adenomas, whether or not carcinomas are 

12 present;

13 Y(carcinomas) = number of animals with carcinomas, whether or not adenomas are also 

14 present;

15 Y(either adenomas or carcinomas) = number of animals with adenomas or carcinomas, 

16 not both = Y(adenomas) + Y(carcinomas) – Y(both adenomas and carcinomas);

17 Y(neither adenomas nor carcinomas) = number of animals with no adenomas and no 

18 carcinomas = N - Y(either adenomas or carcinomas).

D.1.2. Model Selection Criteria

19 Multiple models were fit to each dataset. The model selection criteria used in the BMD 

20 technical guidance document (U.S. EPA, 2000a) were applied as follows:

21 p-value for goodness-of-fit > 0.10

22 AIC smaller than other acceptable models

χ

2

23 residuals as small as possible

24 No systematic patterns of deviation of model from data

25 Additional criteria were applied to eliminate implausible dose-response functions:

26 Monotonic dose-response functions, e.g. no negative coefficients of polynomials in MS 

27 models

28 No infinitely steep dose-response functions near 0 (control dose), achieved by requiring 

29 the estimated parameters ―power‖ in the Weibull and Gamma models and ―slope‖ in the 

30 log-logistic model to have values ≥ 1. 

31 Because no single set of criteria covers all contingencies, an extended list of preferred models are 

32 presented below in Table D-1. 
D-4

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.1.3. Summary 

1 The BMDS models recommended to calculate rodent BMD and BMDL values and 

2 corresponding human BMDHED and BMDLHED values are summarized in Table D-1.

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

BMDa

mg/kgday

BMDLa

mg/kgday

BMDHED

a

mg/kgday

BMDLHE

D

a

mg/kgday

Female F344 Rat

Hepatic

Tumors

Lowest 

AIC

Multistage

(2 degree)

91.5898 0.4516 79.83 58.09 19.84 14.43

Mammary

Gland

Tumors

Lowest 

AIC

LogLogistic 194.151 0.8874 161.01 81.91 40.01 20.35

Nasal

Cavity

Tumors

Lowest 

AIC

Multistage

(3 degree)

42.6063 0.9966 381.65 282.61 94.84 70.23

Male R344 Rat

Hepatic

Tumors

Lowest 

AIC

Probit 147.787 0.9867 62.20 51.12 17.43 14.33

Peritoneal

Mesothelioma

Lowest 

AIC

Probit 138.869 0.9148 93.06 76.32 26.09 21.39

Nasal

Cavity 

Tumors

Lowest 

AIC

Multistage

(3 degree)

24.747 0.9989 328.11 245.63 91.97 68.85

Female BDF1 Mouse

Hepatic 

Tumors

Lowest 

AIC

LogLogistic 176.214 0.1421 5.54 3.66 0.83 0.55

BMR 50% LogLogistic 176.214 0.1421 49.88b32.93b7.51b4.95b

Male BDF1 Mouse

Hepatic 

Tumors

Lowest 

AIC

LogLogistic248.839 0.3461 34.78 16.60 5.63 2.68

3

a

4 Values for BMR 10% unless otherwise noted.

b

5 BMR 50%.

D.2. FEMALE F344 RATS: HEPATIC CARCINOMAS AND ADENOMAS

6 The incidence data for hepatic carcinomas and adenomas in female F344 rats (Kano, et 

7 al., 2009) are shown in Table D-2.
D-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).

1 Note that the incidence of rats with adenomas, with carcinomas, and with either 

2 adenomas or carcinomas are monotone non-decreasing functions of dose except for 3 female rats 

3 in the control group. These data therefore appear to be appropriate for dose-response modeling 

4 using BMDS.

5 The results of the BMDS modeling for the entire suite of models are presented in 

6 Table D-3. 

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

incidence of hepatic adenomas and carcinomas in female F344 rats (Kano, et 

al., 2009)

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 93.1067 0.3024 89.46 62.09 0.027 22.23 15.43

Logistic 91.7017 0.4459 93.02 71.60 0.077 23.12 17.79

LogLogistic 93.102 0.3028 88.34 65.52 0.016 21.95 16.28

LogProbitb93.0762 0.3074 87.57 66.19 0.001 21.76 16.45

Multistage-Cancer 

(1 degree) 114.094 0.0001 25.58 19.92 -1.827 6.36 4.95

Multistage-Cancer

(2 degree)c 91.5898 0.4516 79.83 58.09 -0.408 19.84 14.43

Multistage-Cancer 

(3 degree) 93.2682 0.2747 92.81 59.31 0.077 23.06 14.74

Probit 91.8786 0.3839 85.46 67.84 -0.116 21.24 16.86

Weibull 93.2255 0.2825 92.67 59.89 0.088 23.03 14.88

Quantal-Linear 114.094 0.0001 25.58 19.92 -1.827 6.36 4.95

Dichotomous-Hill 4458.37 NCd NCd NCd0 0 0

aMaximum absolute χ2

residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

b

Slope restricted ≥ 1.

cBest-fitting model.

dValue 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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_hepato_adcar_Msc4 BMR10-2poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_hepato_adcar_Msc-BMR10-2poly.plt

7 Mon Oct 26 08:20:52 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

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 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 = 3

23 Total number of specified parameters = 0

24 Degree of polynomial = 2

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 

31 Background = 0.0281572

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 50 100 150 200 250 300 350 400 450 Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

07:20 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-7

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Beta(1) = 0

2 Beta(2) = 1.73306e-005

3

4 Asymptotic Correlation Matrix of Parameter Estimates (*** The model parameter(s) -

5 Beta(1)have been estimated at a boundary point, or have been specified by the user, 

6 and do not appear in the correlation matrix )

7

8 Background Beta(2)

9 Background 1 -0.2

10 Beta(2) -0.2 1

11

12 Parameter Estimates

13 95.0% Wald Confidence Interval

14 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

15 Background 0.0362773 * * *

16 Beta(1) 0 * * *

17 Beta(2) 1.65328e-005 * * *

18

19 * - Indicates that this value is not calculated.

20

21

22 Analysis of Deviance Table

23

24 Model Log(likelihood) # Param's Deviance Test d.f. P-value

25 Full model -42.9938 4

26 Fitted model -43.7949 2 1.60218 2 0.4488

27 Reduced model -120.43 1 154.873 3 <.0001

28

29 AIC: 91.5898

30

31 Goodness of Fit 

32 Scaled

33 Dose Est._Prob. Expected Observed Size Residual

34 ------------------------------------------------------------------------

35 0.0000 0.0363 1.814 3.000 50 0.897

36 18.0000 0.0414 2.071 1.000 50 -0.760

37 83.0000 0.1400 7.001 6.000 50 -0.408

38 429.0000 0.9540 47.701 48.000 50 0.202

39

40 Chi^2 = 1.59 d.f. = 2 P-value = 0.4516

41

42 Benchmark Dose Computation

43

44 Specified effect = 0.1

45 Risk Type = Extra risk 

46 Confidence level = 0.95

47 BMD = 79.8299

48 BMDL = 58.085

49 BMDU = 94.0205

50

51 Taken together, (58.085 , 94.0205) is a 90% two-sided confidence interval for the BMD

52

53 Multistage Cancer Slope Factor = 0.00172161
D-8

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.3. MALE F344 RATS: HEPATIC CARCINOMAS AND ADENOMAS

1 The data for hepatic adenomas and carcinomas in male F344 rats (Kano, et al., 2009) are 

2 shown in Table D-4.

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

4 Note that the incidence of rats with hepatic adenomas, carcinomas, and with either 

5 adenomas or carcinomas are monotone non-decreasing functions of dose. These data therefore 

6 appear to be appropriate for dose-response modeling using BMDS.

7 The results of the BMDS modeling for the entire suite of models tested using the data for 

8 hepatic adenomas and carcinomas for male F344 rats are presented in Table D-5. 
D-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

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 149.884 0.7257 62.41 30.79 -0.03 17.49 8.63

Logistic 147.813 0.9749 68.74 55.39 0.097 19.27 15.53

LogLogistic 149.886 0.7235 62.10 34.61 -0.021 17.41 9.70

LogProbitb149.913 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

Probitc147.787 0.9867 62.20 51.12 -0.05 17.43 14.33

Weibull 149.856 0.7576 62.63 30.11 -0.039 17.56 8.44

Quantal-Linear 152.836 0.0978 23.82 18.34 -0.186 6.68 5.14

Dichotomous-Hill 4441.71 NCd NCd NCd0 0 0

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

b

Slope restricted ≥ 1.

cBest-fitting model.

dValue 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 ==================================================================== 

2 Probit Model. (Version: 3.1; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_hepato_adcar_Prb4 BMR10.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_hepato_adcar_Prb-BMR10.plt

7 Mon Oct 26 08:32:08 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13 P[response] = CumNorm(Intercept+Slope*Dose),

14 where CumNorm(.) is the cumulative normal distribution function

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Slope parameter is not restricted

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

27 Default Initial (and Specified) Parameter Values 

28 background = 0 Specified

29 intercept = -1.51718

30 slope = 0.00831843

31

 0

 0.2

 0.4

 0.6

 0.8

 0 50 100 150 200 250 

dose

Probit Model with 0.95 Confidence Level

07:32 10/26 2009

BMDL BMD

 

Probit
D-11

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2 (*** The model parameter(s) -background have been estimated at a boundary point, or 

3 have been specified by the user, and do not appear in the correlation matrix )

4

5 intercept slope

6 intercept 1 -0.69

7 slope -0.69 1

8

9

10 Parameter Estimates

11 95.0% Wald Confidence Interval

12 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

13 intercept 1.53138 0.160195 -1.84535 -1.2174

14 slope 0.00840347 0.000976752 0.00648907 0.0103179

15

16

17 Analysis of Deviance Table

18

19 Model Log(likelihood) # Param's Deviance Test d.f. P-value

20 Full model -71.8804 4

21 Fitted model -71.8937 2 0.0265818 2 0.9868

22 Reduced model -115.644 1 87.528 3 <.0001

23

24 AIC: 147.787

25

26

27 Goodness of Fit 

28 Scaled

29 Dose Est._Prob. Expected Observed Size Residual

30 ------------------------------------------------------------------------

31 0.0000 0.0628 3.142 3.000 50 -0.083

32 11.0000 0.0751 3.754 4.000 50 0.132

33 55.0000 0.1425 7.125 7.000 50 -0.050

34 274.0000 0.7797 38.985 39.000 50 0.005

35

36 Chi^2 = 0.03 d.f. = 2 P-value = 0.9867

37

38 Benchmark Dose Computation

39

40 Specified effect = 0.1

41 Risk Type = Extra risk 

42 Confidence level = 0.95

43 BMD = 62.1952

44 BMDL = 51.1158

45
D-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 

hepatic adenomas and carcinomas in male F344 rats.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_hepato_adcar_Msc4 BMR10-3poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_hepato_adcar_Msc-BMR10-3poly.plt

7 Mon Oct 26 08:32:08 2009

8 ==================================================================== 

9

10 BMDS Model Run 

11 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

12

13 The form of the probability function is: P[response] = background + (1-background)*[1-

14 EXP(-beta1*dose^1-beta2*dose^2-beta3*dose^3)]

15

16 The parameter betas are restricted to be positive

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 = 4

24 Total number of specified parameters = 0

25 Degree of polynomial = 3

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

31 Default Initial Parameter Values 

 0

 0.2

 0.4

 0.6

 0.8

 0 50 100 150 200 250 

dose

Multistage Cancer Model with 0.95 Confidence Level

07:32 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-13

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Background = 0.0623822

2 Beta(1) = 0.00142752

3 Beta(2) = 0

4 Beta(3) = 5.14597e-008

5 Asymptotic Correlation Matrix of Parameter Estimates

6 (*** The model parameter(s) -Beta(2)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(1) Beta(3)

10 Background 1 -0.67 0.58

11 Beta(1) -0.67 1 -0.95

12 Beta(3) 0.58 -0.95 1

13

14

15 Parameter Estimates

16

17 95.0% Wald Confidence Interval

18 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

19 Background 0.0619918 * * *

20 Beta(1) 0.001449 * * *

21 Beta(2) 0 * * *

22 Beta(3) 5.11829e-008 * * *

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 -71.8804 4

32 Fitted model -71.8858 3 0.0107754 1 0.9173

33 Reduced model -115.644 1 87.528 3 <.0001

34

35 AIC: 149.772

36

37

38 Goodness of Fit 

39 Scaled

40 Dose Est._Prob. Expected Observed Size Residual

41 ------------------------------------------------------------------------

42 0.0000 0.0620 3.100 3.000 50 -0.058

43 11.0000 0.0769 3.844 4.000 50 0.083

44 55.0000 0.1412 7.059 7.000 50 -0.024

45 274.0000 0.7799 38.997 39.000 50 0.001

46

47 Chi^2 = 0.01 d.f. = 1 P-value = 0.9171

48

49

50 Benchmark Dose Computation

51

52 Specified effect = 0.1

53 Risk Type = Extra risk 

54 Confidence level = 0.95

55 BMD = 63.6179

56 BMDL = 27.4913

57 BMDU = 123.443

58

59 Taken together, (27.4913, 123.443) is a 90% two-sided confidence interval for the BMD

60

61 Multistage Cancer Slope Factor = 0.00363752
D-14

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.4. F344 RATS: TUMORS AT OTHER SITES

1 The data for tumors at sites other than the liver in male and female F344 rats (Kano, et 

2 al., 2009) are shown in Table D-6. Note that the incidence of rats with these endpoints are 

3 monotone non-decreasing functions (except female peritoneal mesotheliomas). These data 

4 therefore appear to be appropriate for dose-response modeling using BMDS.

Table D-6. Data for significant tumors at other sites in male and female F344 

rats (Kano, et al., 2009)

Tumor site and type

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).

5 The results of the BMDS modeling for the entire suite of models are presented in Tables 

6 D-7 through Table D-10 for tumors in the nasal cavity, mammary gland, and peritoneal cavity. 
D-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 ratsa(Kano, et al., 2009)

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2b

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 44.4964 1 403.82 269.03 0 100.35 66.85

Logistic 44.4963 1 421.54 351.74 0 104.75 87.41

LogLogistic 44.4963 1 413.69 268.85 0 102.80 66.81

LogProbitc44.4963 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 1.64×10-8102.87 92.58

aNasal cavity tumors in female F344 rats include squamous cell carcinoma and esthesioneuro-epithelioma.

bMaximum absolute χ2

residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

c

Slope restricted ≥ 1.

dBest-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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_nasal_car_Msc4 BMR10-3poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_nasal_car_Msc-BMR10-3poly.plt

7 Mon Oct 26 08:28:58 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: P[response] = background + (1-

12 background)*[1-EXP(-beta1*dose^1-beta2*dose^2-beta3*dose^3)]

13

14 The parameter betas are restricted to be positive

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Total number of observations = 4

19 Total number of records with missing values = 0

20 Total number of parameters in model = 4

21 Total number of specified parameters = 0

22 Degree of polynomial = 3

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

30 Beta(1) = 0

31 Beta(2) = 0

32 Beta(3) = 1.91485e-009

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 50 100 150 200 250 300 350 400 450 

dose

Multistage Cancer Model with 0.95 Confidence Level

07:28 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-17

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2 (*** The model parameter(s) -Background -Beta(1) -Beta(2) 

3 have been estimated at a boundary point, or have been specified by the user,

4 and do not appear in the correlation matrix )

5

6 Beta(3)

7 Beta(3) 1

8

9 Parameter Estimates

10

11 95.0% Wald Confidence Interval

12 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

13 Background 0 * * *

14 Beta(1) 0 * * *

15 Beta(2) 0 * * *

16 Beta(3) 1.89531e-009 * * *

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 -20.2482 4

25 Fitted model -20.3031 1 0.109908 3 0.9906

26 Reduced model -30.3429 1 20.1894 3 0.0001551

27

28 AIC: 42.6063

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 50 0.000

36 18.0000 0.0000 0.001 0.000 50 -0.024

37 83.0000 0.0011 0.054 0.000 50 -0.233

38 429.0000 0.1390 6.949 7.000 50 0.021

39

40 Chi^2 = 0.06 d.f. = 3 P-value = 0.9966

41

42

43 Benchmark Dose Computation

44

45 Specified effect = 0.1

46 Risk Type = Extra risk 

47 Confidence level = 0.95

48 BMD = 381.651

49 BMDL = 282.609

50 BMDU = 500.178

51

52 Taken together, (282.609, 500.178) is a 90% two-sided confidence interval for the BMD

53

54 Multistage Cancer Slope Factor = 0.000353846
D-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 ratsa(Kano, et al., 2009)

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2b

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 26.6968 1 299.29 244.10 0 83.89 68.42

Logistic 26.6968 1 281.06 261.29 0 78.78 73.24

LogLogistic 26.6968 1 288.31 245.29 0 80.81 68.75

LogProbitc26.6968 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 6.25×10-581.44 73.29

aNasal cavity tumors in male F344 rats include squamous cell carcinoma, Sarcoma: NOS, rhabdomyosarcoma, and 

esthesioneuro-epithelioma.

bMaximum absolute χ2

residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

c

Slope restricted ≥ 1.

dBest-fitting model.
D-19

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009).

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

male F344 rats.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_nasal_car_Msc4 BMR10-3poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_nasal_car_Msc-BMR10-3poly.plt

7 Mon Oct 26 08:34:20 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: P[response] = background + (1-background)*[1-

12 EXP(-beta1*dose^1-beta2*dose^2-beta3*dose^3)]

13

14 The parameter betas are restricted to be positive

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Total number of observations = 4

19 Total number of records with missing values = 0

20 Total number of parameters in model = 4

21 Total number of specified parameters = 0

22 Degree of polynomial = 3

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

 0

 0.05

 0.1

 0.15

 0 50 100 150 200 250 300 

dose

Multistage Cancer Model with 0.95 Confidence Level

07:34 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-20

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Beta(1) = 0

2 Beta(2) = 0

3 Beta(3) = 3.01594e-009

4

5

6 Asymptotic Correlation Matrix of Parameter Estimates

7

8 (*** The model parameter(s) -Background -Beta(1) -Beta(2) 

9 have been estimated at a boundary point, or have been specified by the user,

10 and do not appear in the correlation matrix )

11

12 Beta(3)

13 Beta(3) 1

14

15

16 Parameter Estimates

17

18 95.0% Wald Confidence Interval

19 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

20 Background 0 * * *

21 Beta(1) 0 * * *

22 Beta(2) 0 * * *

23 Beta(3) 2.98283e-009 * * *

24

25 * - Indicates that this value is not calculated.

26

27

28

29 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -11.3484 4

33 Fitted model -11.3735 1 0.0502337 3 0.9971

34 Reduced model -15.5765 1 8.45625 3 0.03747

35

36 AIC: 24.747

37

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 11.0000 0.0000 0.000 0.000 50 -0.014

45 55.0000 0.0005 0.025 0.000 50 -0.158

46 274.0000 0.0595 2.976 3.000 50 0.015

47

48 Chi^2 = 0.03 d.f. = 3 P-value = 0.9989

49

50

51 Benchmark Dose Computation

52

53 Specified effect = 0.1

54 Risk Type = Extra risk 

55 Confidence level = 0.95

56 BMD = 328.108

57 BMDL = 245.634

58 BMDU = 1268.48

59

60 Taken together, (245.634, 1268.48) is a 90% two-sided confidence interval for the BMD

61

62 Multistage Cancer Slope Factor = 0.00040711
D-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

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 194.222 0.8559 176.66 99.13 0.465 43.90 24.63

Logistic 194.475 0.7526 230.35 159.73 0.612 57.24 39.69

LogLogisticb194.151 0.8874 161.01 81.91 0.406 40.01 20.35

LogProbitc195.028 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 NCd94.06 14.02 3.49×10-523.37 3.48

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-fitting model.

c

Slope restricted ≥ 1.

dValue 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 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: C:\14DBMDS\lnl_kano2009_frat_mamm_ad_Lnl-BMR10-Restrict.(d) 

4 Gnuplot Plotting File: C:\14DBMDS\lnl_kano2009_frat_mamm_ad_Lnl-BMR10-Restrict.plt

5 Mon Feb 01 11:31:31 2010

6 ==================================================================== 

7 BMDS Model Run 

8 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

9 The form of the probability function is: 

10

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 = 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 = 0.12

27 intercept = -7.06982

28 slope = 1

29 Asymptotic Correlation Matrix of Parameter Estimates

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200 250 300 350 400 450 

dose

Log-Logistic Model with 0.95 Confidence Level

11:31 02/01 2010

BMDL BMD

 

Log-Logistic
D-23

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 (*** The model parameter(s) -slope have been estimated at a boundary point, or have 

3 been specified by the user, and do not appear in the correlation matrix )

4

5 background intercept

6 background 1 -0.53

7 intercept -0.53 1

8

9 Parameter Estimates

10

11 95.0% Wald Confidence Interval

12 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

13 background 0.130936 * * *

14 intercept -7.2787 * * *

15 slope 1 * * *

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 Full model -94.958 4

25 Fitted model -95.0757 2 0.235347 2 0.889

26 Reduced model -98.6785 1 7.4409 3 0.0591

27

28 AIC: 194.151

29

30

31 Goodness of Fit 

32 Scaled

33 Dose Est._Prob. Expected Observed Size Residual

34 ------------------------------------------------------------------------

35 0.0000 0.1309 6.547 6.000 50 -0.229

36 18.0000 0.1416 7.080 7.000 50 -0.032

37 83.0000 0.1780 8.901 10.000 50 0.406

38 429.0000 0.3294 16.472 16.000 50 -0.142

39

40 Chi^2 = 0.24 d.f. = 2 P-value = 0.8874

41

42

43 Benchmark Dose Computation

44 Specified effect = 0.1

45 Risk Type = Extra risk 

46 Confidence level = 0.95

47 BMD = 161.012

48 BMDL = 81.9107
D-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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_mamm_ad_Msc-BMR10-

4 1poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_frat_mamm_ad_Msc-BMR10-1poly.plt

7 Mon Oct 26 08:27:02 2009

8 ==================================================================== 

9 BMDS Model Run 

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

29

30 Default Initial Parameter Values 

31 Background = 0.136033

32 Beta(1) = 0.000570906

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200 250 300 350 400 450 

dose

Multistage Cancer Model with 0.95 Confidence Level

07:27 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-25

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2

3 Background Beta(1)

4 Background 1 -0.58

5 Beta(1) -0.58 1

6

7

8 Parameter Estimates

9

10 95.0% Wald Confidence Interval 

11 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

12 Background .133161 * * *

13 Beta(1) 0.000596394 * * *

14

15 * - Indicates that this value is not calculated.

16

17

18

19 Analysis of Deviance Table

20

21 Model Log(likelihood) # Param's Deviance Test d.f. P-value

22 Full model -94.958 4

23 Fitted model -95.111 2 0.305898 2 0.8582

24 Reduced model -98.6785 1 7.4409 3 0.0591

25

26 AIC: 194.222

27

28

29 Goodness of Fit 

30 Scaled

31 Dose Est._Prob. Expected Observed Size Residual

32 ------------------------------------------------------------------------

33 0.0000 0.1332 6.658 6.000 50 -0.274

34 18.0000 0.1424 7.121 7.000 50 -0.049

35 83.0000 0.1750 8.751 10.000 50 0.465

36 429.0000 0.3288 16.442 16.000 50 -0.133

37

38 Chi^2 = 0.31 d.f. = 2 P-value = 0.8559

39

40

41 Benchmark Dose Computation

42

43 Specified effect = 0.1

44 Risk Type = Extra risk 

45 Confidence level = 0.95

46 BMD = 176.663

47 BMDL = 99.1337

48 BMDU = 501.523

49

50 Taken together, (99.1337, 501.523) is a 90% two-sided confidence interval for the BMD

51

52 Multistage Cancer Slope Factor = 0.00100874
D-26

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

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

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 140.701 0.9189 73.52 35.62 0.018 20.61 9.98

Logistic 139.016 0.8484 103.52 84.35 0.446 29.02 23.65

LogLogistic 140.699 0.9242 72.56 36.37 0.014 20.34 10.19

LogProbitb140.69 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

Probitc138.869 0.9148 93.06 76.32 0.315 26.09 21.39

Weibull 140.709 0.8915 74.77 35.59 0.027 20.96 9.97

Quantal-Linear 140.826 0.3617 41.04 30.51 -1.066 11.50 8.55

Dichotomous-Hill 2992 NCd NCd NCd0 0 0

aMaximum absolute χ2

residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

b

Slope restricted ≥ 1.

cBest-fitting model.

dValue 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 ==================================================================== 

2 Probit Model. (Version: 3.1; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_peri_meso_Prb4 BMR10.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kano2009_mrat_peri_meso_Prb-BMR10.plt

7 Mon Oct 26 08:41:29 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 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 Default Initial (and Specified) Parameter Values 

26 background = 0 Specified

27 intercept = -1.73485

28 slope = 0.00692801

29

30 Asymptotic Correlation Matrix of Parameter Estimates

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 50 100 150 200 250 

dose

Probit Model with 0.95 Confidence Level

07:41 10/26 2009

BMDL BMD

 

Probit
D-28

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (*** The model parameter(s) -background have been estimated at a boundary point, or 

2 have been specified by the user, and do not appear in the correlation matrix )

3

4 intercept slope

5 intercept 1 -0.75

6 slope -0.75 1

7

8 Parameter Estimates

9 95.0% Wald Confidence Interval

10 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

11 intercept -1.73734 0.18348 -2.09695 -1.37772

12 slope 0.00691646 0.000974372 0.00500672 0.00882619

13

14 Analysis of Deviance Table

15 Model Log(likelihood) # Param's Deviance Test d.f. P-value

16 Full model -67.3451 4

17 Fitted model -67.4344 2 0.178619 2 0.9146

18 Reduced model -95.7782 1 56.8663 3 <.0001

19 AIC: 138.869

20

21 Goodness of Fit 

22 Scaled

23 Dose Est._Prob. Expected Observed Size Residual

24 ------------------------------------------------------------------------

25 0.0000 0.0412 2.058 2.000 50 -0.041

26 11.0000 0.0483 2.417 2.000 50 -0.275

27 55.0000 0.0874 4.370 5.000 50 0.315

28 274.0000 0.5627 28.134 28.000 50 -0.038

29

30 Chi^2 = 0.18 d.f. = 2 P-value = 0.9148

31 Benchmark Dose Computation

32 Specified effect = 0.1

33 Risk Type = Extra risk 

34 Confidence level = 0.95

35 BMD = 93.0615

36 BMDL = 76.3242

37

38
D-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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_peri_meso_Msc4 BMR10-2poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mrat_peri_meso_Msc-BMR10-2poly.plt

7 Mon Oct 26 08:41:28 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13

14 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2)]

15

16 The parameter betas are restricted to be positive

17

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 = 3

25 Total number of specified parameters = 0

26 Degree of polynomial = 2

27

28 Maximum number of iterations = 250

29 Relative Function Convergence has been set to: 1e-008

30 Parameter Convergence has been set to: 1e-008

31

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 50 100 150 200 250 

dose

Multistage Cancer Model with 0.95 Confidence Level

07:41 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-30

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 Background = 0.0358706

3 Beta(1) = 0.000816174

4 Beta(2) = 7.47062e-006

5

6

7 Asymptotic Correlation Matrix of Parameter Estimates

8

9 Background Beta(1) Beta(2)

10 Background 1 -0.67 0.59

11 Beta(1) -0.67 1 -0.98

12 Beta(2) 0.59 -0.98 1

13

14 Parameter Estimates

15 95.0% Wald Confidence Interval

16 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

17 Background 0.0366063 * * *

18 Beta(1) 0.000757836 * * *

19 Beta(2) 7.6893e-006 * * *

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 -67.3451 4

27 Fitted model -67.3733 3 0.056567 1 0.812

28 Reduced model -95.7782 1 56.8663 3 <.0001

29

30 AIC: 140.747

31

32

33 Goodness of Fit 

34 Scaled

35 Dose Est._Prob. Expected Observed Size Residual

36 ------------------------------------------------------------------------

37 0.0000 0.0366 1.830 2.000 50 0.128

38 11.0000 0.0455 2.275 2.000 50 -0.186

39 55.0000 0.0972 4.859 5.000 50 0.067

40 274.0000 0.5605 28.027 28.000 50 -0.008

41

42 Chi^2 = 0.06 d.f. = 1 P-value = 0.8135

43

44

45 Benchmark Dose Computation

46

47 Specified effect = 0.1

48 Risk Type = Extra risk 

49 Confidence level = 0.95

50 BMD = 77.7277

51 BMDL = 35.4296

52 BMDU = 118.349

53

54 Taken together, (35.4296, 118.349) is a 90% two-sided confidence interval for the BMD

55

56 Multistage Cancer Slope Factor = 0.0028225
D-31

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.5. FEMALE BDF1 MICE: HEPATIC CARCINOMAS AND ADENOMAS

1 Data for female BDF1 mouse hepatic carcinomas and adenomas are shown in Table D2 11. Note that the incidence of carcinomas and the incidence of either adenomas or carcinomas 

3 are monotone non-decreasing functions of dose. These data therefore appear to be appropriate 

4 for dose-response modeling using BMDS. However, the incidence of adenomas clearly reaches 

5 a peak value at 66 mg/kg-day and then decreases sharply with increasing dose. This cannot be 

6 modeled by a multistage model using only non-negative coefficients. To some extent the 

7 incidence of ―either adenomas or carcinomas‖ retains some of the inverted-U shaped dose8 response of the adenomas, which dominate based on their high incidence at the lowest dose 

9 groups (66 and 278 mg/kg-day), thus is not well characterized by any multistage model.

Table D-11. Data for hepatic adenomas and carcinomas in female BDF1 mice 

(Kano, et al., 2009)

Tumor 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).

10 The results of the BMDS modeling for the entire suite of models for hepatic adenomas 

11 and carcinomas in female BDF1 mice are presented in Table D-12. The multistage models did 

12 not provide reasonable fits to the incidence data for hepatocellular adenoma or carcinoma in 

13 female BDF1 mice. The log-logistic model provided the best-fit to the data as indicated by the 

14 AIC and p-value as was chosen as the best-fitting model to carry forward in the analysis; 

15 however, this model resulted in a BMDL10 much lower than the response level at the lowest dose 

16 in the study (Kano, et al., 2009). Thus, the log-logistic model was run for BMRs of 30 and 50%. 

17 The output from these models are shown in Figures D-11 and D-12. A summary of the BMD 

18 results for BMRs of 10, 30, and 50% are shown in Table D-13. Using a higher BMR resulted in 

19 BMDLs closer to the lowest observed response data, and a BMR of 50% was chosen to carry 

20 forward in the analysis. 

21 The graphical output from fitting these models suggested that a simpler model obtained 

22 by dropping the data point for the highest dose (964 mg/kg-day) might also be adequate. This 

23 was tested and the results did not affect the choice of the model, nor significantly affect the 

24 resulting BMDs and BMDLs.
D-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 BDF1 mice (Kano, 

et al., 2009)

1

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 203.331 0 26.43 19.50 -2.654 3.98 2.94

Logistic 214.951 0 58.05 44.44 3.201 8.74 6.69

LogLogisticb176.214 0.1421 5.54 3.66 -0.121 0.83 0.55

LogProbitc198.354 0 26.37 19.57 -1.166 3.97 2.95

Multistage-Cancer

(1 degree) 203.331 0 26.43 19.50 -2.654 3.98 2.94

Multistage-Cancer

(2 degree) 203.331 0 26.43 19.50 -2.654 3.98 2.94

Multistage-Cancer

(3 degree) 203.331 0 26.43 19.50 -2.654 3.98 2.94

Probit 217.671 0 69.89 56.22 3.114 10.5 8.46

Weibull 203.331 0 26.43 19.50 -2.654 3.98 2.94

Quantal-Linear 203.331 0 26.43 19.50 -2.654 3.98 2.94

Dichotomous-Hill 7300.48 NCd NCd NCd0 0 0

aMaximum absolute χ2

residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-fitting model, lowest AIC value.

c

Slope restricted ≥ 1.

dValue unable to be calculated (NC: not calculated) by BMDS.

Table D-13. BMDS LogLogistic dose-response modeling results using BMRs 

of 10, 30, and 50% for the combined incidence of hepatic adenomas and 

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

BMR AIC p-value

BMD

mg/kg-day

BMDL

mg/kg-day χ

2a

BMDHED

mg/kg-day

BMDLHED

mg/kg-day

10% 176.214 0.1421 5.54 3.66 -0.121 0.83 0.55

30% 176.214 0.1421 21.38 14.11 -0.121 3.22 2.12

50% 176.214 0.1421 49.88 32.93 0 7.51 4.95

aMaximum absolute χ2

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 BDF1 mice with a BMR of 10%.

1 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: 

4 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR10-

5 Restrict.(d) 

6 Gnuplot Plotting File: 

7 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR10-

8 Restrict.plt

9 Wed May 12 11:26:35 2010

10 ==================================================================== 

11 BMDS Model Run 

12 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

13 The form of the probability function is: 

14 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]

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

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 

dose

Log-Logistic Model with 0.95 Confidence Level

11:26 05/12 2010

BMDLBMD

 

Log-Logistic
D-34

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 Parameter Values 

7 background = 0.1

8 intercept = -4.33618

9 slope = 1

10

11 Asymptotic Correlation Matrix of Parameter Estimates

12 (*** The model parameter(s) -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 background intercept

16 background 1 -0.32

17 intercept -0.32 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 0.105265 * * *

24 intercept -3.90961 * * *

25 slope 1 * * *

26

27 * - Indicates that this value is not calculated.

28

29 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -84.3055 4

33 Fitted model -86.107 2 3.6029 2 0.1651

34 Reduced model -131.248 1 93.8853 3 <.0001

35

36 AIC: 176.214

37

38

39 Goodness of Fit 

40 Scaled

41 Dose Est._Prob. Expected Observed Size Residual

42 ------------------------------------------------------------------------

43 0.0000 0.1053 5.263 5.000 50 -0.121

44 66.0000 0.6149 30.743 35.000 50 1.237

45 278.0000 0.8639 43.194 41.000 50 -0.905

46 964.0000 0.9560 47.799 46.000 50 -1.240

47

48 Chi^2 = 3.90 d.f. = 2 P-value = 0.1421

49

50

51 Benchmark Dose Computation

52 Specified effect = 0.1

53 Risk Type = Extra risk 

54 Confidence level = 0.95

55 BMD = 5.54218

56 BMDL = 3.65848

57
D-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 BDF1 mice with a BMR of 30%.

1 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: 

4 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR30-

5 Restrict.(d) 

6 Gnuplot Plotting File: 

7 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR30-

8 Restrict.plt

9 Wed May 12 11:26:36 2010

10 ==================================================================== 

11 BMDS Model Run 

12 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

13 The form of the probability function is: 

14 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]

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

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 

dose

Log-Logistic Model with 0.95 Confidence Level

11:26 05/12 2010

BMDL BMD

 

Log-Logistic
D-36

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 User has chosen the log transformed model

2

3 Default Initial Parameter Values 

4 background = 0.1

5 intercept = -4.33618

6 slope = 1

7

8 Asymptotic Correlation Matrix of Parameter Estimates

9 (*** The model parameter(s) -slope have been estimated at a boundary point, or have 

10 been specified by the user, and do not appear in the correlation matrix)

11

12 background intercept

13 background 1 -0.32

14 intercept -0.32 1

15

16 Parameter Estimates

17

18 95.0% Wald Confidence Interval

19 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

20 background 0.105265 * * *

21 intercept -3.90961 * * *

22 slope 1 * * *

23

24 * - Indicates that this value is not calculated.

25

26

27 Analysis of Deviance Table

28

29 Model Log(likelihood) # Param's Deviance Test d.f. P-value

30 Full model -84.3055 4

31 Fitted model -86.107 2 3.6029 2 0.1651

32 Reduced model -131.248 1 93.8853 3 <.0001

33

34 AIC: 176.214

35

36

37 Goodness 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 = 0.3

51 Risk Type = Extra risk 

52 Confidence level = 0.95

53 BMD = 21.377

54 BMDL = 14.1113
D-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 BDF1 mice with a BMR of 50%.

1 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: 

4 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR50-

5 Restrict.(d) 

6 Gnuplot Plotting File: 

7 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_fmouse_hepato_adcar_Lnl-BMR50-

8 Restrict.plt

9 Wed May 12 11:26:36 2010

10 ==================================================================== 

11 BMDS Model Run 

12 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

13 The form of the probability function is: 

14 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]

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

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 

dose

Log-Logistic Model with 0.95 Confidence Level

11:26 05/12 2010

BMDL BMD

 

Log-Logistic
D-38

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 Parameter Values 

7 background = 0.1

8 intercept = -4.33618

9 slope = 1

10

11 Asymptotic Correlation Matrix of Parameter Estimates

12 (*** The model parameter(s) -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 background intercept

16 background 1 -0.32

17 intercept -0.32 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 0.105265 * * *

24 intercept -3.90961 * * *

25 slope 1 * * *

26

27 * - Indicates that this value is not calculated.

28

29 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -84.3055 4

33 Fitted model -86.107 2 3.6029 2 0.1651

34 Reduced model -131.248 1 93.8853 3 <.0001

35

36 AIC: 176.214

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 Computation

51 Specified effect = 0.5

52 Risk Type = Extra risk 

53 Confidence level = 0.95

54 BMD = 49.8797

55 BMDL = 32.9263
D-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 BDF1 mice.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: 

4 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_fmouse_hepato_adcar_Msc-BMR10-1poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_fmouse_hepato_adcar_Msc-BMR10-1poly.plt

7 Wed May 12 11:26:31 2010

8 ==================================================================== 

9 BMDS Model Run 

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 parameters = 0

23 Degree of polynomial = 1

24

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 

dose

Multistage Cancer Model with 0.95 Confidence Level

11:26 05/12 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-40

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 Background = 0.51713

7 Beta(1) = 0.00201669

8

9 Asymptotic Correlation Matrix of Parameter Estimates

10

11 Background Beta(1)

12 Background 1 -0.65

13 Beta(1) -0.65 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 0.265826 * * *

20 Beta(1) 0.00398627 * * *

21

22 * - Indicates that this value is not calculated.

23

24 Analysis of Deviance Table

25

26 Model Log(likelihood) # Param's Deviance Test d.f. P-value

27 Full model -84.3055 4

28 Fitted model -99.6653 2 30.7195 2 2.1346928e-007

29 Reduced model -131.248 1 93.8853 3 <.0001

30

31 AIC: 203.331

32

33 Goodness of Fit 

34 Scaled

35 Dose Est._Prob. Expected Observed Size Residual

36 ------------------------------------------------------------------------

37 0.0000 0.2658 13.291 5.000 50 -2.654

38 66.0000 0.4357 21.783 35.000 50 3.770

39 278.0000 0.7576 37.880 41.000 50 1.030

40 964.0000 0.9843 49.213 46.000 50 -3.651

41

42 Chi^2 = 35.65 d.f. = 2 P-value = 0.0000

43

44

45 Benchmark Dose Computation

46 Specified effect = 0.1

47

48 Risk Type = Extra risk 

49 Confidence level = 0.95

50 BMD = 26.4309

51 BMDL = 19.5045

52 BMDU = 37.5583

53

54 Taken together, (19.5045, 37.5583) is a 90% two-sided confidence interval for the BMD

55

56 Multistage Cancer Slope Factor = 0.00512702
D-41

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.6. MALE BDF1 MICE: HEPATIC CARCINOMAS AND ADENOMAS

1 Data for hepatic carcinomas and adenomas in male BDF1 mice (Kano, et al., 2009) are 

2 shown in Table D-14. Note that the incidence of carcinomas and the incidence of either 

3 adenomas or carcinomas are monotone non-decreasing functions of dose. These data therefore 

4 appear to be appropriate for dose-response modeling using BMDS. However, the incidence of 

5 adenomas clearly reaches a peak value at 191 mg/kg-day and then decreases sharply with 

6 increasing dose. This cannot be modeled by a multistage model using only non-negative 

7 coefficients. To some extent the incidence of ―either adenomas or carcinomas or both‖ retains 

8 some of the inverted-U shaped dose-response of the adenomas, which dominate based on their 

9 high incidence at the lowest dose groups (49 and 191 mg/kg-day), thus is not well characterized 

10 by any multistage model.

Table D-14. Data for hepatic adenomas and carcinomas in male BDF1 mice 

(Kano, 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).

11 The results of the BMDS modeling for the entire suite of models for hepatic adenomas 

12 and carcinomas in male BDF1 mice are presented in Table D-15. 
D-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 BDF1 mice (Kano, et 

al., 2009)

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 250.551 0.1527 70.99 44.00 0.605 11.48 7.12

Logistic 251.187 0.112 91.89 61.98 0.529 14.86 10.02

LogLogisticb248.839 0.3461 34.78 16.60 0.656 5.63 2.68

LogProbitc252.244 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 NCd11.60 1.63 -1.25×10-51.88 0.26

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-fitting model.

c

Slope restricted ≥ 1.

dValue 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 BDF1 mice.

1 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: 

4 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_mmouse_hepato_adcar_Lnl-BMR10-

5 Restrict.(d) 

6 Gnuplot Plotting File: 

7 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_kano2009_mmouse_hepato_adcar_Lnl-BMR10-

8 Restrict.plt

9 Thu Nov 12 09:09:36 2009

10 ==================================================================== 

11 BMDS Model Run 

12 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

13 The form of the probability function is: 

14 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]

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 User has chosen the log transformed model

27

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0.9

 0 100 200 300 400 500 600 700 

dose

Log-Logistic Model with 0.95 Confidence Level

07:30 10/26 2009

BMDL BMD

 

Log-Logistic
D-44

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 background = 0.46

3 intercept = -5.58909

4 slope = 1

5 Asymptotic Correlation Matrix of Parameter Estimates

6

7 (*** The model parameter(s) -slope 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 intercept

11 background 1 -0.69

12 intercept -0.69 1

13

14

15 Parameter Estimates

16

17 95.0% Wald Confidence Interval

18 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

19 background 0.507468 * * *

20 intercept -5.74623 * * *

21 slope 1 * * *

22

23 * - Indicates that this value is not calculated.

24

25

26 Analysis of Deviance Table

27

28 Model Log(likelihood) # Param's Deviance Test d.f. P-value

29 Full model -121.373 4

30 Fitted model -122.419 2 2.09225 2 0.3513

31 Reduced model -128.859 1 14.9718 3 0.001841

32

33 AIC: 248.839

34

35

36 Goodness of Fit 

37 Scaled

38 Dose Est._Prob. Expected Observed Size Residual

39 ------------------------------------------------------------------------

40 0.0000 0.5075 25.373 23.000 50 -0.671

41 49.0000 0.5741 28.707 31.000 50 0.656

42 191.0000 0.6941 34.706 37.000 50 0.704

43 677.0000 0.8443 42.214 40.000 50 -0.863

44

45 Chi^2 = 2.12 d.f. = 2 P-value = 0.3461

46

47

48 Benchmark Dose Computation

49 Specified effect = 0.1

50 Risk Type = Extra risk 

51 Confidence level = 0.95

52 BMD = 34.7787

53 BMDL = 16.5976
D-45

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: Used with permission from Elsevier, Ltd., Kano et al. (2009).

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

hepatic adenomas and carcinomas in male BDF1 mice.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: 

4 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mmouse_hepato_adcar_Msc-BMR10-1poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kano2009_mmouse_hepato_adcar_Msc-BMR10-1poly.plt

7 Mon Oct 26 08:30:50 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

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

29

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0.9

 0 100 200 300 400 500 600 700 

dose

Multistage Cancer Model with 0.95 Confidence Level

07:30 10/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-46

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 Background = 0.573756

3 Beta(1) = 0.00123152

4

5 Asymptotic Correlation Matrix of Parameter Estimates

6 Background Beta(1)

7 Background 1 -0.58

8 Beta(1) -0.58 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 0.545889 * * *

16 Beta(1) 0.00148414 * * *

17

18 * - Indicates that this value is not calculated.

19

20

21

22 Analysis of Deviance Table

23

24 Model Log(likelihood) # Param's Deviance Test d.f. P-value

25 Full model -121.373 4

26 Fitted model -123.275 2 3.80413 2 0.1493

27 Reduced model -128.859 1 14.9718 3 0.001841

28

29 AIC: 250.551

30

31

32 Goodness of Fit 

33 Scaled

34 Dose Est._Prob. Expected Observed Size Residual

35 ------------------------------------------------------------------------

36 0.0000 0.5459 27.294 23.000 50 -1.220

37 49.0000 0.5777 28.887 31.000 50 0.605

38 191.0000 0.6580 32.899 37.000 50 1.223

39 677.0000 0.8337 41.687 40.000 50 -0.641

40

41 Chi^2 = 3.76 d.f. = 2 P-value = 0.1527

42

43

44 Benchmark Dose Computation

45

46 Specified effect = 0.1

47 Risk Type = Extra risk 

48 Confidence level = 0.95

49 BMD = 70.9911

50 BMDL = 44.0047

51 BMDU = 150.117

52

53 Taken together, (44.0047, 150.117) is a 90% two-sided confidence interval for the BMD

54

55 Multistage Cancer Slope Factor = 0.00227248
D-47

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.7. BMD MODELING RESULTS FROM ADDITIONAL CHRONIC BIOASSAYS

1 Data and BMDS modeling results for the additional chronic bioassays (Kociba, et al., 

2 1974; NCI, 1978) were evaluated for comparison with the Kano et al. (2009) study. These 

3 results are presented in the following sections. 

4 The BMDS dose-response modeling estimates and HEDs that resulted are presented in 

5 detail in the following sections and a summary is provided in Table D-16.

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

with liver and nasal tumor incidence data resulting from chronic oral 

exposure to 1,4-dioxane in rats and mice

Endpoint

Model 

selection 

criterion

Model 

Type AIC

pvalue

BMD10

mg/kgday

BMDL10

mg/kgday

BMD10 HED

mg/kgdayBMDL10 HED

mg/kg-day

Kociba et al., (1974)

Male and Female (combined) Sherman Rats

Hepatic

Tumorsa

Lowest 

AIC

Probit 84.3126 0.606 1113.94 920.62 290.78 240.31

Nasal

Cavity

Tumorsb

Lowest 

AIC

Multistage

(3 degree)

26.4156 0.9999 1717.16 1306.29 448.24 340.99

NCI, (1978)

Female Osborne-Mendel Rats

Hepatic

Tumorsc

Lowest 

AIC

LogLogistic 84.2821 0.7333 111.46 72.41 28.75 18.68

Nasal

Cavity 

Tumorsb

Lowest 

AIC

LogLogistic 84.2235 0.2486 155.32 100.08 40.07 25.82

NCI, (1978)

Male Osborne-Mendel Rats

Nasal

Cavity 

Tumorsb

Lowest 

AIC

LogLogistic 92.7669 0.7809 56.26 37.26 16.10 10.66

NCI, (1978)

Female B6C3F1 Mice

Hepatic 

Tumorsd

Lowest 

AIC, 

Multistage 

model

Multistage

(2 degree)

85.3511 1 160.68 67.76 23.12 9.75

NCI, (1978)

Male B6C3F1 Mice

Hepatic 

Tumorsd

Lowest 

AIC

Gamma 177.539 0.7571 601.69 243.92 87.98 35.67

a

Incidence of hepatocellular carcinoma.

b

Incidence of nasal squamous cell carcinoma.

c

Incidence of hepatocellular adenoma.

d

Incidence of hepatocellular adenoma or carcinoma.
D-48

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.7.1. Hepatocellular Carcinoma and Nasal Squamous Cell Carcinoma (Kociba, et al., 

1974)

1 The incidence data for hepatocellular carcinoma and nasal squamous cell carcinoma are 

2 presented in Table D-17. The predicted BMD10 HED and BMDL10 HED values are also presented in 

3 Tables D-18 and D-19 for hepatocellular carcinomas and nasal squamous cell carcinomas, 

4 respectively.

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 male and female dose)

Incidence of hepatocellular 

carcinomaa

Incidence of nasal 

squamous cell carcinomaa

0 1/106b0/106c

14 0/110 0/110

121 1/106 0/106

1307 10/66d3/66d

aRats surviving until 12 months on study.

b

p < 0.001; positive dose-related trend (Cochran-Armitage test).

c

p < 0.01; positive dose-related trend (Cochran-Armitage test).

d

p < 0.001; Fisher‘s Exact test.

Source: Used with permission from Elsevier, Ltd., Kociba et al. (1974).
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

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 86.2403 0.3105 985.13 628.48 -0.005 257.15 164.05

Logistic 84.3292 0.6086 1148.65 980.95 -0.004 299.84 256.06

LogLogistic 86.2422 0.3103 985.62 611.14 -0.005 257.28 159.53

LogProbitb84.4246 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

Probitc84.3126 0.606 1113.94 920.62 -0.005 290.78 240.31

Weibull 86.2443 0.3104 998.33 629.93 -0.005 260.60 164.43

Quantal-Linear 85.1187 0.3838 940.12 583.58 0.279 245.40 152.33

Dichotomous-Hill 1503.63 NCd NCd NCd0 0 0

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

b

Slope restricted ≥ 1.

cBest-fitting model.

dValue 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 ==================================================================== 

2 Probit Model. (Version: 3.1; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kociba_mf_rat_hepato_car_Prb4 BMR10.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\pro_kociba_mf_rat_hepato_car_Prb-BMR10.plt

7 Tue Oct 27 12:54:14 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13 P[response] = CumNorm(Intercept+Slope*Dose),where CumNorm(.) is the cumulative normal 

14 distribution function

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Slope parameter is not restricted

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 Initial (and Specified) Parameter Values 

27 background = 0 Specified

28 intercept = -2.62034

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0 200 400 600 800 1000 1200 

dose

Probit Model with 0.95 Confidence Level

11:54 10/27 2009

BMDL BMD

 

Probit
D-51

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 slope = 0.0012323

2 Asymptotic Correlation Matrix of Parameter Estimates

3 (*** The model parameter(s) -background have been estimated at a boundary point, or 

4 have been specified by the user, and do not appear in the correlation matrix )

5

6 intercept slope

7 intercept 1 -0.82

8 slope -0.82 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 intercept -2.55961 0.261184 -3.07152 -2.0477

16 slope 0.00117105 0.000249508 0.000682022 0.00166008

17

18

19 Analysis of Deviance Table

20

21 Model Log(likelihood) # Param's Deviance Test d.f. P-value

22 Full model -39.3891 4

23 Fitted model -40.1563 2 1.53445 2 0.4643

24 Reduced model -53.5257 1 28.2732 3 <.0001

25

26 AIC: 84.3126

27

28

29 Goodness of Fit 

30 Scaled

31 Dose Est._Prob. Expected Observed Size Residual

32 ------------------------------------------------------------------------

33 0.0000 0.0052 0.555 1.000 106 0.598

34 14.0000 0.0055 0.604 0.000 110 -0.779

35 121.0000 0.0078 0.827 1.000 106 0.191

36 1307.0000 0.1517 10.014 10.000 66 -0.005

37

38 Chi^2 = 1.00 d.f. = 2 P-value = 0.6060

39

40

41 Benchmark Dose Computation

42

43 Specified effect = 0.1

44 Risk Type = Extra risk 

45 Confidence level = 0.95

46 BMD = 1113.94

47 BMDL = 920.616
D-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 

hepatocellular 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_hepato_car_Msc4 BMR10-1poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_hepato_car_Msc-BMR10-1poly.plt

7 Tue Oct 27 12:54:10 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13

14 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)]

15

16 The parameter betas are restricted to be positive

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 = 2

24 Total number of specified parameters = 0

25 Degree of polynomial = 1

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

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0 200 400 600 800 1000 1200 

dose

Multistage Cancer Model with 0.95 Confidence Level

11:54 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-53

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 Background = 0.000925988

3 Beta(1) = 0.000124518

4

5

6 Asymptotic Correlation Matrix of Parameter Estimates

7 Background Beta(1)

8 Background 1 -0.44

9 Beta(1) -0.44 1

10

11

12 Parameter Estimates

13

14 95.0% Wald Confidence Interval

15 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

16 Background 0.0038683 * * *

17 Beta(1) 0.000112071 * * *

18

19 * - Indicates that this value is not calculated.

20

21

22 Analysis of Deviance Table

23

24 Model Log(likelihood) # Param's Deviance Test d.f. P-value

25 Full model -39.3891 4

26 Fitted model -40.5594 2 2.34056 2 0.3103

27 Reduced model -53.5257 1 28.2732 3 <.0001

28

29 AIC: 85.1187

30

31

32 Goodness of Fit 

33 Scaled

34 Dose Est._Prob. Expected Observed Size Residual

35 ------------------------------------------------------------------------

36 0.0000 0.0039 0.410 1.000 106 0.923

37 14.0000 0.0054 0.597 0.000 110 -0.775

38 121.0000 0.0173 1.832 1.000 106 -0.620

39 1307.0000 0.1396 9.213 10.000 66 0.279

40

41 Chi^2 = 1.92 d.f. = 2 P-value = 0.3838

42

43

44 Benchmark Dose Computation

45

46 Specified effect = 0.1

47 Risk Type = Extra risk 

48 Confidence level = 0.95

49 BMD = 940.124

50 BMDL = 583.576

51 BMDU = 1685.88

52

53 Taken together, (583.576, 1685.88) is a 90% two-sided confidence interval for the BMD

54

55 Multistage Cancer Slope Factor = 0.000171357
D-54

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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

squamous cell carcinoma in male and female Sherman rats (combined) 

(Kociba, et al., 1974) exposed to 1,4-dioxane in the drinking water for 2 years

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 28.4078 1 1572.09 1305.86 0 410.37 340.87

Logistic 28.4078 1 1363.46 1306.67 0 355.91 341.09

LogLogistic 28.4078 1 1464.77 1306.06 0 382.35 340.93

LogProbitb28.4078 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 5.53×10-7382.62 344.35

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

b

Slope restricted ≥ 1.

cBest-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 ==================================================================== 

3 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

4 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_nasal_car_Msc5 BMR10-3poly.(d) 

6 Gnuplot Plotting File: 

7 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_kociba_mf_rat_nasal_car_Msc-BMR10-3poly.plt

8 Tue Oct 27 07:25:02 2009

9 ==================================================================== 

10 BMDS Model Run 

11 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

12

13 The form of the probability function is: 

14

15 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1-beta2*dose^2-

16 beta3*dose^3)]

17

18 The parameter betas are restricted to be positive

19

20 Dependent variable = Effect

21 Independent variable = Dose

22

23 Total number of observations = 4

24 Total number of records with missing values = 0

25 Total number of parameters in model = 4

26 Total number of specified parameters = 0

27 Degree of polynomial = 3

28

 0

 0.02

 0.04

 0.06

 0.08

 0.1

 0.12

 0.14

 0 200 400 600 800 1000 1200 1400 1600 1800 

dose

Multistage Cancer Model with 0.95 Confidence Level

06:25 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-56

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 Default Initial Parameter Values 

5 Background = 0

6 Beta(1) = 0

7 Beta(2) = 0

8 Beta(3) = 2.08414e-011

9

10

11 Asymptotic Correlation Matrix of Parameter Estimates

12

13 (*** The model parameter(s) -Background -Beta(1) -Beta(2) 

14 have been estimated at a boundary point, or have been specified by the user,

15 and do not appear in the correlation matrix )

16

17 Beta(3)

18 Beta(3) 1

19

20

21 Parameter Estimates

22

23 95.0% Wald Confidence Interval

24 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

25 Background 0 * * *

26 Beta(1) 0 * * *

27 Beta(2) 0 * * *

28 Beta(3) 2.08088e-011 * * *

29

30 * - Indicates that this value is not calculated.

31

32

33

34 Analysis of Deviance Table

35

36 Model Log(likelihood) # Param's Deviance Test d.f. P-value

37 Full model -12.2039 4

38 Fitted model -12.2078 1 0.00783284 3 0.9998

39 Reduced model -17.5756 1 10.7433 3 0.0132

40

41 AIC: 26.4156

42

43

44 Goodness of Fit 

45 Scaled

46 Dose Est._Prob. Expected Observed Size Residual

47 ------------------------------------------------------------------------

48 0.0000 0.0000 0.000 0.000 106 0.000

49 14.0000 0.0000 0.000 0.000 110 -0.003

50 121.0000 0.0000 0.004 0.000 106 -0.063

51 1307.0000 0.0454 2.996 3.000 66 0.002

52

53 Chi^2 = 0.00 d.f. = 3 P-value = 0.9999

54

55

56 Benchmark Dose Computation

57

58 Specified effect = 0.1

59 Risk Type = Extra risk 

60 Confidence level = 0.95

61 BMD = 1717.16

62 BMDL = 1306.29

63 BMDU = 8354.46

64

65 Taken together, (1306.29, 8354.46) is a 90% two-sided confidence interval for the BMD

66
D-57

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Multistage Cancer Slope Factor = 7.65529e-005

D.7.2. Nasal Cavity Squamous Cell Carcinoma and Liver Hepatocellular Adenoma in 

Osborne-Mendel Rats (NCI, 1978)

2 The incidence data for hepatocellular adenoma (female rats) and nasal squamous cell 

3 carcinoma (male and female rats) are presented in Table D-20. The log-logistic model 

4 adequately fit both the male and female rat nasal squamous cell carcinoma data, as well as 

5 female hepatocellular adenoma incidence data. For all endpoints and genders evaluated in this 

6 section, compared to the multistage models, the log-logistic model had a higher p-value, as well 

7 as both a lower AIC and lower BMDL. The results of the BMDS modeling for the entire suite of 

8 models are presented in Tables D-21 through D-23.

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

hepatocellular adenoma in Osborne-Mendel rats (NCI, 1978) exposed to 

1,4-dioxane in the drinking water

Male rat Animal Dose (mg/kg-day)a

0 240b530

Nasal cavity squamous cell carcinoma 0/33c12/26d16/33d

Female rat Animal Dose (mg/kg-day)a

0 350 640

Nasal cavity squamous cell carcinoma 0/34c10/30d8/29d

Hepatocellular adenoma 0/31c10/30d11/29d

aTumor incidence values were adjusted for mortality (NCI, 1978).

bGroup not included in statistical analysis by NCI (1978) because the dose group was started a year earlier 

without appropriate controls.

c

p ≤ 0.001; positive dose-related trend (Cochran-Armitage test).

d

p ≤ 0.001; Fisher‘s Exact test.

Source: NCI (1978).
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

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 84.6972 0.5908 132.36 94.06 0 34.144 24.26

Logistic 92.477 0.02 284.09 220.46 1.727 73.29 56.87

LogLogisticb84.2821 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

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-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 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_hepato_ad_Lnl-BMR10-

4 Restrict.(d) 

5 Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_hepato_ad_Lnl6 BMR10-Restrict.plt

7 Tue Oct 27 07:32:13 2009

8 ==================================================================== 

9 BMDS Model Run 

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 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 = -6.62889

29 slope = 1

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600 

dose

Log-Logistic Model with 0.95 Confidence Level

06:32 10/27 2009

BMDL BMD

 

Log-Logistic
D-60

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 Asymptotic Correlation Matrix of Parameter Estimates

3

4 (*** The model parameter(s) -background -slope have been estimated at a boundary 

5 point, or have been specified by the user, and do not appear in the correlation 

6 matrix)

7

8 intercept

9 intercept 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 intercept -6.91086 * * *

17 slope 1 * * *

18

19 * - Indicates that this value is not calculated.

20

21

22 Analysis of Deviance Table

23

24 Model Log(likelihood) # Param's Deviance Test d.f. P-value

25 Full model -40.8343 3

26 Fitted model -41.141 1 0.613564 2 0.7358

27 Reduced model -50.4308 1 19.1932 2 <.0001

28

29 AIC: 84.2821

30

31

32 Goodness of Fit 

33 Scaled

34 Dose Est._Prob. Expected Observed Size Residual

35 ------------------------------------------------------------------------

36 0.0000 0.0000 0.000 0.000 31 0.000

37 350.0000 0.2587 8.536 10.000 33 0.582

38 640.0000 0.3895 12.464 11.000 32 -0.531

39

40 Chi^2 = 0.62 d.f. = 2 P-value = 0.7333

41

42

43 Benchmark Dose Computation

44

45 Specified effect = 0.1

46 Risk Type = Extra risk 

47 Confidence level = 0.95

48 BMD = 111.457

49 BMDL = 72.4092
D-61

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_hepato_ad_Msc-BMR10-

4 1poly.(d) 

5 Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_hepato_ad_Msc6 BMR10-1poly.plt

7 Tue Oct 27 07:32:16 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13

14 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)]

15

16 The parameter betas are restricted to be positive

17

18 Dependent variable = Effect

19 Independent variable = Dose

20

21 Total number of observations = 3

22 Total number of records with missing values = 0

23 Total number of parameters in model = 2

24 Total number of specified parameters = 0

25 Degree of polynomial = 1

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

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600 

dose

Multistage Cancer Model with 0.95 Confidence Level

06:32 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-62

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 Default Initial Parameter Values 

3 Background = 0.0385912

4 Beta(1) = 0.000670869

5 Asymptotic Correlation Matrix of Parameter Estimates

6

7 (*** The model parameter(s) -Background have been estimated at a boundary point, or 

8 have been specified by the user, and do not appear in the correlation matrix)

9

10 Beta(1)

11 Beta(1) 1

12

13

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 * * *

20 Beta(1) 0.00079602 * * *

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 model -40.8343 3

30 Fitted model -41.3486 1 1.02868 2 0.5979

31 Reduced model -50.4308 1 19.1932 2 <.0001

32

33 AIC: 84.6972

34

35

36 Goodness of Fit 

37 Scaled

38 Dose Est._Prob. Expected Observed Size Residual

39 ------------------------------------------------------------------------

40 0.0000 0.0000 0.000 0.000 31 0.000

41 350.0000 0.2432 8.024 10.000 33 0.802

42 640.0000 0.3992 12.774 11.000 32 -0.640

43

44 Chi^2 = 1.05 d.f. = 2 P-value = 0.5908

45

46

47 Benchmark Dose Computation

48

49 Specified effect = 0.1

50 Risk Type = Extra risk 

51 Confidence level = 0.95

52 BMD = 132.359

53 BMDL = 94.0591

54 BMDU = 194.33

55

56 Taken together, (94.0591, 194.33 ) is a 90% two-sided confidence interval for the BMD

57

58 Multistage Cancer Slope Factor = 0.00106316
D-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-dioxane in the drinking water for 2 years

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 84.7996 0.1795 176.28 122.27 1.466 45.47 31.54

Logistic 92.569 0.0056 351.51 268.75 2.148 90.68 69.33

LogLogisticb84.2235 0.2486 155.32 100.08 0 40.07 25.82

LogProbitc87.3162 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

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-fitting model.

c

Slope restricted ≥ 1.
D-64

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

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 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_nasal_car_Lnl-BMR10-

4 Restrict.(d) 

5 Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_frat_nasal_car_Lnl6 BMR10-Restrict.plt

7 Tue Oct 27 07:30:09 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13

14 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]

15

16

17 Dependent variable = Effect

18 Independent variable = Dose

19 Slope parameter is restricted as slope >= 1

20

21 Total number of observations = 3

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

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600 

dose

Log-Logistic Model with 0.95 Confidence Level

06:30 10/27 2009

BMDL BMD

 

Log-Logistic
D-65

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 User has chosen the log transformed model

2

3

4 Default Initial Parameter Values 

5 background = 0

6 intercept = -6.64005

7 slope = 1

8

9

10 Asymptotic Correlation Matrix of Parameter Estimates

11 (*** The model parameter(s) -background -slope have been estimated at a boundary 

12 point, or have been specified by the user, and do not appear in the correlation 

13 matrix)

14

15 intercept

16 intercept 1

17

18

19 Parameter Estimates

20

21 95.0% Wald Confidence Interval

22 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

23 background 0 * * *

24 intercept -7.24274 * * *

25 slope 1 * * *

26

27 * - Indicates that this value is not calculated.

28

29 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -39.7535 3

33 Fitted model -41.1117 1 2.71651 2 0.2571

34 Reduced model -47.9161 1 16.3252 2 0.0002851

35

36 AIC: 84.2235

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 34 0.000

43 350.0000 0.2002 7.008 10.000 35 1.264

44 640.0000 0.3140 10.992 8.000 35 -1.090

45

46 Chi^2 = 2.78 d.f. = 2 P-value = 0.2486

47

48

49 Benchmark Dose Computation

50

51 Specified effect = 0.1

52 Risk Type = Extra risk 

53 Confidence level = 0.95

54 BMD = 155.324

55 BMDL = 100.081
D-66

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_nasal_car_Msc-BMR10-

4 1poly.(d) 

5 Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_frat_nasal_car_Msc6 BMR10-1poly.plt

7 Tue Oct 27 07:30:12 2009

8 ==================================================================== 

9 BMDS Model Run 

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 = 3

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 Convergence has been set to: 1e-008

28

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600 

dose

Multistage Cancer Model with 0.95 Confidence Level

06:30 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-67

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 Background = 0.0569154

3 Beta(1) = 0.00042443

4

5 Asymptotic Correlation Matrix of Parameter Estimates

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 Parameter Estimates

13

14 95.0% Wald Confidence Interval

15 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

16 Background 0 * * *

17 Beta(1) 0.000597685 * * *

18

19 * - Indicates that this value is not calculated.

20

21 Analysis of Deviance Table

22

23 Model Log(likelihood) # Param's Deviance Test d.f. P-value

24 Full model -39.7535 3

25 Fitted model -41.3998 1 3.29259 2 0.1928

26 Reduced model -47.9161 1 16.3252 2 0.0002851

27

28 AIC: 84.7996

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 34 0.000

35 350.0000 0.1888 6.607 10.000 35 1.466

36 640.0000 0.3179 11.125 8.000 35 -1.134

37

38 Chi^2 = 3.44 d.f. = 2 P-value = 0.1795

39

40 Benchmark Dose Computation

41 Specified effect = 0.1

42 Risk Type = Extra risk 

43 Confidence level = 0.95

44 BMD = 176.281

45 BMDL = 122.274

46 BMDU = 271.474

47

48 Taken together, (122.274, 271.474) is a 90% two-sided confidence interval for the BMD

49

50 Multistage Cancer Slope Factor = 0.000817837
D-68

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table D-23. BMDS 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

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 93.6005 0.5063 73.94 54.724 0 21.17 15.66

Logistic 103.928 0.0061 179.05 139.26 2.024 51.25 39.86

LogLogisticb92.7669 0.7809 56.26 37.26 0 16.10 10.66

LogProbitc95.0436 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

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-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 ==================================================================== 

2 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_mrat_nasal_car_Lnl-BMR10-

4 Restrict.(d) 

5 Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\lnl_nci_mrat_nasal_car_Lnl6 BMR10-Restrict.plt

7 Tue Oct 27 07:27:57 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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 = 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 User has chosen the log transformed model

26

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500 

dose

Log-Logistic Model with 0.95 Confidence Level

06:27 10/27 2009

BMDL BMD

 

Log-Logistic
D-70

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 background = 0

3 intercept = -6.08408

4 slope = 1

5

6 Asymptotic Correlation Matrix of Parameter Estimates

7 (*** The model parameter(s) -background -slope 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 intercept

12 intercept 1

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 * * *

19 intercept -6.2272 * * *

20 slope 1 * * *

21

22 * - Indicates that this value is not calculated.

23

24 Analysis of Deviance Table

25

26 Model Log(likelihood) # Param's Deviance Test d.f. P-value

27 Full model -45.139 3

28 Fitted model -45.3835 1 0.488858 2 0.7832

29 Reduced model -59.2953 1 28.3126 2 <.0001

30

31 AIC: 92.7669 

32

33 Goodness of Fit

34 Scaled

35 Dose Est._Prob. Expected Observed Size Residual

36 ------------------------------------------------------------------------

37 0.0000 0.0000 0.000 0.000 33 0.000

38 240.0000 0.3216 10.612 12.000 33 0.517

39 530.0000 0.5114 17.388 16.000 34 -0.476

40

41 Chi^2 = 0.49 d.f. = 2 P-value = 0.7809

42 Benchmark Dose Computation

43

44 Specified effect = 0.1

45 Risk Type = Extra risk 

46 Confidence level = 0.95

47 BMD = 56.2596

48 BMDL = 37.256
D-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 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mrat_nasal_car_Msc-BMR10-

4 1poly.(d) 

5 Gnuplot Plotting File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mrat_nasal_car_Msc6 BMR10-1poly.plt

7 Tue Oct 27 07:28:00 2009

8 ==================================================================== 

9 BMDS Model Run 

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 = 3

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 Convergence has been set to: 1e-008

28 Default Initial Parameter Values 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500 

dose

Multistage Cancer Model with 0.95 Confidence Level

06:28 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-72

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Background = 0.0578996

2 Beta(1) = 0.00118058

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) 0.00142499 * * *

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 -45.139 3

24 Fitted model -45.8002 1 1.32238 2 0.5162

25 Reduced model -59.2953 1 28.3126 2 <.0001

26

27 AIC: 93.6005

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 33 -0.000

34 240.0000 0.2896 9.558 12.000 33 0.937

35 530.0000 0.5301 18.024 16.000 34 -0.695

36

37 Chi^2 = 1.36 d.f. = 2 P-value = 0.5063

38

39 Benchmark Dose Computation

40 Specified effect = 0.1

41 Risk Type = Extra risk 

42 Confidence level = 0.95

43 BMD = 73.9379

44 BMDL = 54.7238

45 BMDU = 103.07

46

47 Taken together, (54.7238, 103.07 ) is a 90% two-sided confidence interval for the BMD

48

49 Multistage Cancer Slope Factor = 0.00182736
D-73

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

D.7.3. Hepatocellular Adenoma or Carcinoma in B6C3F1 Mice (NCI, 1978)

1 The incidence data for hepatocellular adenoma or carcinoma in male and female 

2 mice are presented in Table D-24. The 2-degree polynomial model (betas restricted ≥ 0) 

3 was the lowest degree polynomial that provided an adequate fit to the female mouse data 

4 (Figure D-25), while the gamma model provided the best fit to the male mouse data 

5 (Figure D-26). The results of the BMDS modeling for the entire suite of models are 

6 presented in Tables D-25 and D-26 for the female and male data, respectively.

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

female B6C3F1 mice (NCI, 1978) exposed to 1,4-dioxane in drinking water

Male mouse Animal Dose (mg/kg-day)a Female mouse Animal Dose (mg/kg-day)a

0 720 830 0 380 860

8/49b19/50d28/47c0/50b21/48c35/37c

aTumor 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 B6C3F1 mice 

(NCI, 1978) exposed to 1,4-dioxane in the drinking water for 2 years

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gamma 85.3511 1 195.69 105.54 0 28.16 15.19

Logistic 89.1965 0.0935 199.63 151.35 0.675 28.72 21.78

LogLogistic 85.3511 1 228.08 151.16 0 32.82 21.75

LogProbitb85.3511 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

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

b

Slope restricted ≥ 1.

cBest-fitting model.
D-75

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

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

hepatocellular adenoma or carcinoma in female B6C3F1 mice exposed to 

1,4-dioxane in drinking water.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_fmouse_hepato_adcar_Msc4 BMR10-2poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_fmouse_hepato_adcar_Msc-BMR10-2poly.plt

7 Tue Oct 27 07:36:26 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

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 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 = 3

23 Total number of specified parameters = 0

24 Degree of polynomial = 2

25

26

27 Maximum number of iterations = 250

28 Relative Function Convergence has been set to: 1e-008

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 100 200 300 400 500 600 700 800 900 

dose

Multistage Cancer Model with 0.95 Confidence Level

06:36 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-76

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Parameter Convergence has been set to: 1e-008

2

3 Default Initial Parameter Values 

4 Background = 0

5 Beta(1) = 2.68591e-005

6 Beta(2) = 3.91383e-006

7

8

9 Asymptotic Correlation Matrix of Parameter Estimates

10 (*** The model parameter(s) -Background have been estimated at a boundary point, or 

11 have been specified by the user, and do not appear in the correlation matrix)

12

13 Beta(1) Beta(2)

14 Beta(1) 1 -0.92

15 Beta(2) -0.92 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 Beta(1) 2.686e-005 * * *

24 Beta(2) 3.91382e-006 * * *

25

26 * - Indicates that this value is not calculated.

27

28

29 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -40.6756 3

33 Fitted model -40.6756 2 3.20014e-010 1 1

34 Reduced model -91.606 1 101.861 2 <.0001

35

36 AIC: 85.3511

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

43 380.0000 0.4375 21.000 21.000 48 0.000

44 860.0000 0.9459 35.000 35.000 37 0.000

45

46 Chi^2 = 0.00 d.f. = 1 P-value = 1.0000

47

48

49 Benchmark Dose Computation

50 Specified effect = 0.1

51 Risk Type = Extra risk 

52 Confidence level = 0.95

53 BMD = 160.678

54 BMDL = 67.7635

55 BMDU = 186.587

56

57 Taken together, (67.7635, 186.587) is a 90% two-sided confidence interval for the BMD

58

59 Multistage Cancer Slope Factor = 0.00147572
D-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 B6C3F1 mice 

(NCI, 1978) exposed to 1,4-dioxane in drinking water

Model AIC p-value

BMD10

mg/kg-day

BMDL10

mg/kg-day χ

2a

BMD10 HED

mg/kg-day

BMDL10 HED

mg/kg-day

Gammab177.539 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 NCc622.39 283.04 0 91.01 41.39

LogProbitd179.443 NCc631.51 305.44 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 NCc608.81 249.71 0 89.02 36.51

Quantal-Linear 180.618 0.0762 164.29 117.37 0.079 24.02 17.16

aMaximum absolute χ2 residual deviation between observed and predicted count. Values much larger than 1 are 

undesirable.

bBest-fitting model.

cValue 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 B6C3F1 mice exposed to 1,4-dioxane in 

drinking water.

1 ==================================================================== 

2 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\gam_nci_mmouse_hepato_adcar_Gam4 BMR10-Restrict.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\gam_nci_mmouse_hepato_adcar_Gam-BMR10-Restrict.plt

7 Tue Oct 27 07:34:35 2009

8 ==================================================================== 

9 BMDS Model Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11

12 The form of the probability function is: 

13 P[response]= background+(1-background)*CumGamma[slope*dose,power],

14 where CumGamma(.) is the cummulative Gamma distribution function

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Power parameter is restricted as power >=1

19

20 Total number of observations = 3

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 (and Specified) Parameter Values 

27 Background = 0.17

28 Slope = 0.000671886

29 Power = 1.3

30

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500 600 700 800 

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

06:34 10/27 2009

BMDL BMD

 

Gamma Multi-Hit
D-79

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2 (*** The model parameter(s) -Power have been estimated at a boundary point, or have 

3 been specified by the user, and do not appear in the correlation matrix)

4

5 Background Slope

6 Background 1 -0.52

7 Slope -0.52 1

8

9 Parameter Estimates

10 95.0% Wald Confidence Interval

11 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

12 Background 0.160326 0.0510618 0.060247 0.260405

13 Slope 0.0213093 0.000971596 0.019405 0.0232136

14 Power 18 NA

15

16 NA - Indicates that this parameter has hit a bound implied by some inequality 

17 constraint and thus has no standard error.

18

19 Analysis of Deviance Table

20

21 Model Log(likelihood) # Param's Deviance Test d.f. P-value

22 Full model -86.7213 3

23 Fitted model -86.7693 2 0.096042 1 0.7566

24 Reduced model -96.715 1 19.9875 2 <.0001

25

26 AIC: 177.539

27

28 Goodness of Fit 

29 Scaled

30 Dose Est._Prob. Expected Observed Size Residual

31 ------------------------------------------------------------------------

32 0.0000 0.1603 7.856 8.000 49 0.056

33 720.0000 0.3961 19.806 19.000 50 -0.233

34 830.0000 0.5817 27.339 28.000 47 0.196

35

36 Chi^2 = 0.10 d.f. = 1 P-value = 0.7571

37 Benchmark Dose Computation

38 Specified effect = 0.1

39 Risk Type = Extra risk 

40 Confidence level = 0.95

41 BMD = 601.692

42 BMDL = 243.917
D-80

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Source: NCI (1978).

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

hepatocellular adenoma or carcinoma in male B6C3F1 mice exposed to 

1,4-dioxane in drinking water.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.7; Date: 05/16/2008) 

3 Input Data File: L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mmouse_hepato_adcar_Msc4 BMR10-2poly.(d) 

5 Gnuplot Plotting File: 

6 L:\Priv\NCEA_HPAG\14Dioxane\BMDS\msc_nci_mmouse_hepato_adcar_Msc-BMR10-2poly.plt

7 Tue Oct 27 07:34:42 2009

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)]

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 = 3

23 Total number of specified parameters = 0

24 Degree of polynomial = 2

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

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0 100 200 300 400 500 600 700 800 

dose

Multistage Cancer Model with 0.95 Confidence Level

06:34 10/27 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation
D-81

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Default Initial Parameter Values 

2 Background = 0.131156

3 Beta(1) = 0

4 Beta(2) = 9.44437e-007

5

6 Asymptotic Correlation Matrix of Parameter Estimates

7 (*** The model parameter(s) -Beta(1) 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 Beta(2)

11 Background 1 -0.72

12 Beta(2) -0.72 1

13

14

15 Parameter Estimates

16

17 95.0% Wald Confidence Interval

18 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

19 Background 0.1568 * * *

20 Beta(1) 0 * * *

21 Beta(2) 8.38821e-007 * * *

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 -86.7213 3

31 Fitted model -87.7413 2 2.04001 1 0.1532

32 Reduced model -96.715 1 19.9875 2 <.0001

33

34 AIC: 179.483

35

36

37 Goodness of Fit 

38 Scaled

39 Dose Est._Prob. Expected Observed Size Residual

40 ------------------------------------------------------------------------

41 0.0000 0.1568 7.683 8.000 49 0.124

42 720.0000 0.4541 22.707 19.000 50 -1.053

43 830.0000 0.5269 24.764 28.000 47 0.946

44

45 Chi^2 = 2.02 d.f. = 1 P-value = 0.1554

46

47

48 Benchmark Dose Computation

49

50 Specified effect = 0.1

51 Risk Type = Extra risk 

52 Confidence level = 0.95

53 BMD = 354.409

54 BMDL = 126.241

55 BMDU = 447.476

56

57 Taken together, (126.241, 447.476) is a 90% two-sided confidence interval for the BMD

58

59 Multistage Cancer Slope Factor = 0.000792138
E-1

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

APPENDIX E. COMPARISON OF SEVERAL DATA REPORTS FOR THE JBRC

2-YEAR 1,4-DIOXANE DRINKING WATER STUDY

1 As described in detail in Section 4.2.1.2.6 of this Toxicological Review of 1,4-Dioxane, 

2 the JBRC conducted a 2-year drinking water study on the effects of 1,4-dioxane in both sexes of 

3 rats and mice. The results from this study have been reported three times, once as conference 

4 proceedings (Yamazaki, et al., 1994), once as a detailed laboratory report (JBRC, 1998), and 

5 once as a published manuscript (Kano, et al., 2009). After the External Peer Review draft of the 

6 Toxicological Review of 1,4-Dioxane (U.S. EPA, 2009b) had been released, the Kano et al. 

7 (2009) manuscript was published; thus, minor changes to the Toxicological Review of 

8 1,4-Dioxane occurred. 

9 The purpose of this appendix is to provide a clear and transparent comparison of the 

10 reporting of this 2-year 1,4-dioxane drinking water study. The variations included: (1) the level 

11 of detail on dose information reported; (2) categories for incidence data reported (e.g., all 

12 animals or sacrificed animals); and (3) analysis of non- and neoplastic lesions. Even though the 

13 data contained in the reports varied, the differences were minor and did not did not significantly 

14 affect the qualitative or quantitative cancer assessment. 

15 Tables contained within this appendix provide a comparison of the variations in the 

16 reported data (JBRC, 1998; Kano, et al., 2009; Yamazaki, et al., 1994). Tables E-1 and E-2 

17 show the histological nonneoplastic findings provided for male and female F344 rats, 

18 respectively. Tables E-3 and E-4 show the histological neoplastic findings provided for male 

19 and female F344 rats, respectively. Tables E-5 and E-6 show the histological nonneoplastic 

20 findings provided for male and female F344 rats, respectively. Tables E-7 and E-8 show the 

21 histological neoplastic findings provided for male and female Crj:BDF1 mice, respectively.

 

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

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

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

and the Integrated Risk Information System (IRIS)
E-2

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table E-1. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in male F344 rats

Yamazaki et al. (1994)aJBRC (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 

respiratory 

epithelium;

nuclear 

enlargement

All animals Not reported 0/50 0/50 0/50 26/50 0/50 0/50 0/50 26/50e

Sacrificed 

animals

Not reported 0/40 0/45 0/35 12/22

e Not reported 

Nasal 

respiratory 

epithelium; 

squamous 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 31/50e

Sacrificed 

animals

Not reported 0/40 0/45 0/35 15/22e Not reported

Nasal 

respiratory 

epithelium; 

squamous 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; 

proliferation 

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; 

nuclear 

enlargement 

All animals Not reported 0/50 0/50 5/50 38/50 0/50 0/50 5/50 38/50e

Sacrificed 

animals

Not reported 0/40 0/45 4/35 20/22e Not reported

Nasal olfactory 

epithelium; 

respiratory 

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 22/22e Not reported

Nasal 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 17/22e Not reported

Lamina 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 20/22e Not reported

Lamina 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 20/22e Not reported

Nasal 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 21/22e Not reported

Nasal 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 7/22e 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 12/22e Not reported
E-3

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Yamazaki et al. (1994)aJBRC (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 21/35f21/22e 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 9/35f7/22e Not reported

Acidophilic cell 

foci; liver

All animals Not reported Not reported 12/50 8/50 7/50 5/50

Sacrificed 

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 16/50f

Sacrificed 

animals

Not reported 7/40 11/45 6/35 8/22f Not reported

Mixed-cell foci; 

liver

All animals Not reported 2/50 8/50 14/50 13/50 2/50 8/50 14/50e 13/50e

Sacrificed 

animals

Not reported 2/40 8/45 14/35e22/22e 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 22/22e Not reported

aDose 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) .

cKano 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-2. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in female F344 rats

Yamazaki et al. (1994)aJBRC (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 respiratory 

epithelium; nuclear 

enlargement

All animals Not reported 0/50 0/50 0/50 13/50 0/50 0/50 0/50 13/50e

Sacrificed 

animals Not reported 0/38 0/37 0/38 7/24e Not reported

Nasal respiratory 

epithelium; 

squamous 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 35/50e

Sacrificed 

animals Not reported 0/38 0/37 0/38 18/24e Not reported

Nasal 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 4/24f Not reported

Nasal gland; All animals 0/50 0/50 0/50 11/50 0/50 0/50 0/50 11/50 Not reported
E-4

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Yamazaki et al. (1994)aJBRC (1998) Kano et al. (2009)

proliferation Sacrificed 

animals Not reported 0/38 0/37 0/38 8/24e Not reported

Nasal olfactory 

epithelium; nuclear 

enlargement

All animals Not reported 0/50 0/50 28/50 39/50 0/50 0/50 28/50e39/50e

Sacrificed 

animals Not reported 0/38 0/37 24/38e

22/24e Not reported

Nasal 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 24/24e Not reported

Nasal 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 22/24e Not reported

Lamina 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 23/24e Not reported

Lamina 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 23/24e Not reported

Nasal 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 24/24e Not reported

Nasal 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 7/24e Not reported

Liver; 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 24/24e Not reported

Liver; 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 14/24e Not reported

Liver; 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 5/24f Not reported

Liver; clear cell foci

All animals Not reported Not reported 1/50 1/50 5/50 4/50

Sacrificed 

animals Not reported Not reported Not reported

Liver; acidophilic 

cell foci

All animals Not reported Not reported 1/50 1/50 1/50 1/50

Sacrificed 

animals Not reported Not reported Not reported

Liver; basophilic 

cell foci

All animals Not reported Not reported 23/50 27/50 31/50 8/50e

Sacrificed 

animals Not reported Not reported Not reported

Liver; mixed-cell 

foci

All animals Not reported 1/50 1/50 3/50 11/50 1/50 1/50 3/50 11/50f

Sacrificed 

animals Not reported 1/38 1/37 3/38 7/24f Not reported

Kidney 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 22/24e Not reported
E-5

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Yamazaki et al. (1994)aJBRC (1998) Kano et al. (2009)

aDose 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) .

cKano 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. Neoplastic lesions: Comparison of histological findings reported 

for the 2-year JBRC drinking water study in male F344 rats

Yamazaki et al. (1994)aJBRC (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 3/50e

0/50 0/50 0/50 3/50e

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 24/50d,e 3/50 4/50 7/50 32/50d,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 14/50d,e 0/50 0/50 0/50 14/50d,e

Sacrificed 

animals Not reported Not reported Not reported
E-6

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Yamazaki et al. (1994)aJBRC (1998) Kano et al. (2009)

Hepatocellular adenoma 

or carcinoma

All 

animals Not reported 0/50 2/50 4/49 33/50d,e 3/50 4/50 7/50 39/50d,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 28/50d,e 2/50 2/50 5/50 28/50d,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 12/50e

5/50 3/50 5/50 12/50e

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 4/50e

1/50 1/50 0/50 4/50e

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 6/50e

Sacrificed 

animals Not reported Not reported Not reported

aDose 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) .

cKano 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. 

eSignificantly increased by Peto test for trend p < 0.01. 

Table E-4. Neoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in female F344 rats

Yamazaki et al. (1994)aJBRC (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 7/50d,f 0/50 0/50 0/50 7/50e,f

Sacrificed 

animals

Not reported Not reported Not reported
E-7

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Yamazaki et al. (1994)aJBRC (1998) Kano et al. (2009)

Sarcoma NOS All animals 0/50 0/50 0/50 0/50 Not reported 0/50 0/50 0/50 0/50

Sacrificed 

animals

Not reported Not reported Not reported

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 38/50e,f 3/50 1/50 6/50 48/50e,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 10/50e,f 0/50 0/50 0/50 10/50e,f

Sacrificed 

animals

Not reported Not reported Not reported

Hepatocellular 

adenoma or carcinoma

All animals Not reported 1/50 0/50 5/50 40/50e,f 3/50 1/50 6/50 48/50e,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 16/50d,f 6/50 7/50 10/50 16/50d,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 18/50d,f

Sacrificed 

animals

Not reported Not reported Not reported

aDose 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) .

cKano 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. 

fSignificantly increased by Peto test for trend p < 0.01. 
E-8

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table E-5. Nonneoplastic lesions: Comparison of histological findings 

reported for the 2-year JBRC drinking water study in male Crj:BDF1 mice

Yamazaki et al. (1994) JBRC (1998)d Kano et al. (2009)

Drinking water concentration (ppm)

0 500 2,000 8,000 0 500 2,000 8,000 0 500 2,000 8,000

Calculated Dose (Intake [mg/kg-day])b,c

Not reported Control

0

37-94

(66)

144-358

(251)

451-1086

(768) 0 49±5 191±21 677±74

Nasal respiratory epithelium; 

nuclear enlargement

All 

animals Not reported 0/50 0/50 0/50 31/50 0/50 0/50 0/50 31/50e

Sacrificed 

animals Not reported 0/31 0/33 0/25 19/26e Not reported

Nasal olfactory epithelium; 

nuclear enlargement

All 

animals Not reported 0/50 0/50 9/50 49/50 0/50 0/50 9/50e

49/50e

Sacrificed 

animals Not reported 0/31 0/33 7/25e

26/26e Not reported

Nasal 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 26/26e Not reported

Nasal 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 15/26e Not reported

Tracheal epithelium; atrophy

All 

animals Not reported 0/50 0/50 0/50 42/50 Not reported

Sacrificed 

animals Not reported 0/31 0/33 0/25 24/26e Not reported

Tracheal 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 12/26e Not reported

Bronhcial 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 24/26e Not reported

Bronchial 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 26/26e Not reported

Lung/bronchial; accumlation of 

foamy cells

All 

animals Not reported 1/50 0/50 0/50 27/50 Not reported

Sacrificed 

animals Not reported 1/31 0/33 0/25 22/26e 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 8/26f Not reported
E-9

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Yamazaki et al. (1994) JBRC (1998)d Kano et al. (2009)

Kidney 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 22/26e Not reported

Testis; mineralization

All 

animals Not reported 40/50 42/50 38/50 34/50 Not reported

Sacrificed 

animals Not reported 28/31 30/33 24/25f

21/26f Not reported

aDose 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) .

cKano 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. 

1
E-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:BDF1 mice

Yamazaki et al. (1994)aJBRC (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 41/50e

Sacrificed 

animals Not reported 0/29 0/29 0/17 5/5e Not reported

Nasal olfactory 

epithelium; Nuclear 

enlargement

All animals Not reported 0/50 0/50 41/50 33/50 0/50 0/50 41/50e33/50e

Sacrificed 

animals Not reported 0/29 0/29 17/17e

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 5/5e 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 5/17e

5/5e 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 5/5e 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 13/17e

5/5e 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 5/5e 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 5/5e 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

aDose 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.

bStatistical 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) .

dKano 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. Neoplastic lesions: Comparison of histological findings reported 

for the 2-year JBRC drinking water study in male Crj:BDF1 mice

Yamazaki et al. (1994)aJBRC (1998) Kano et al. (2009)

Drinking water concentration (ppm)

0 500 2,000 8,000 0 500 2,000 8,000 0 500 2,000 8,000

Calculated Dose (Intake [mg/kg-day])b,c

Not reported Control

0

37-94

(66)

144-

358

(251)

451-

1086

(768)

0 49±5 191±21 677±74

Nasal cavity

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 22/50e8/50 9/50 17/50 23/50e11/50

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 36/50d,e 15/50 20/50 23/50 36/50e,f

Sacrificed 

animals Not reported Not reported Not reported

Either adenoma 

or carcinoma

All Animals Not reported 21/50 31/50 37/50 39/50d,e 23/50 31/50 37/50d40/50e,f

Sacrificed 

animals Not reported Not reported Not reported

aDose 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) .

cKano 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. 

eSignificantly increased by Peto test for trend p < 0.01. 

f

p ≤ 0.01 by Fisher's Exact test. 

1
F-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:BDF1 mice

Yamazaki et al. (1994)aJBRC (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 30/50d20/50d2/50e5/50 31/50d20/50d3/50

Sacrificed 

animals Not reported Not reported Not reported

Hepatocellular carcinomas

All animals 0/50 6/50 30/50 45/50 0/50 6/50f30/50d45/50d,g 0/50 6/50f30/50d45/50d,g

Sacrificed 

animals Not reported Not reported Not reported

Either adenoma 

or carcinoma

All animals Not reported 4/50 34/50d41/50d46/50d,g 5/50 35/50d41/50d46/50d,g

Sacrificed 

animals Not reported Not reported Not reported

aDose 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) .

cKano 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.

eSignificantly decreased by Cochran-Armitage test for trend p < 0.05

f p ≤ 0.05 by Fisher's Exact test.

gSignificantly increased by Peto test for trend p < 0.01
F-13

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

APPENDIX F. DETAILS OF BMD ANALYSIS FOR INHALATION RfC FOR 

1,4-DIOXANE

F.1. CENTRILOBULAR NECROSIS OF THE LIVER

1 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

2 fit to the incidence data shown in Table F-1, for centrilobular necrosis of the liver in male 

3 F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (Kasai, et al., 2009). Doses 

4 associated with a BMR of a 10% extra risk were calculated.

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%)

12/50a

(24%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. (2009). 

5

As assessed by the χ26 goodness-of-fit test, several models in the software provided 

adequate fits to the incidence data of centrilobular necrosis of the liver in male rats (χ27 p ≥ 0.1) 

8 (Table F-2). Comparing across adequately fitting models, the BMDL estimates were not within 

9 threefold difference of each other. Therefore, in accordance with EPA BMD technical guidance

10 (U.S. EPA, 2000a), the adequately fitting model that resulted in the lowest BMDL was selected 

11 as appropriate for deriving a POD which was the Dichotomous-Hill model. BMDS modeling 

12 results for all dichotomous models are shown in Table F-2 and the model plot (Figure F-1) and 

13 output for the selected Dichotomous-Hill model l are included immediately after the table. 

 

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)
F-14

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table F-2. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

129.692 0.5099 0.786 502.444 308.113

Logistic 131.043 0.2794 -0.142 794.87 609.269

Log-logisticc

129.465 0.568 0.676 453.169 258.687

Log-probitc

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

Weibullb129.692 0.5099 0.786 502.461 308.113

Quantal-Linear 129.692 0.5099 0.786 502.461 308.113

DichotomousHillc, e 130.404 0.7459 -0.179 219.51 59.5598

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eBold 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 ==================================================================== 

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_Centr_necrosis_liver_Dhl-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/dhl_Centr_necrosis_liver_Dhl-BMR10-Restrict.plt

7 Wed Jan 12 16:34:41 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 predicted 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

23 Total number of records with missing values = 0

24 Maximum number of iterations = 250

25 Relative Function Convergence has been set to: 1e-008

26 Parameter Convergence has been set to: 1e-008

27

28 Default Initial Parameter Values 

29 v = -9999

30 g = -9999

31 intercept = -8.08245

32 slope = 1

33

34

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0.4

 0 200 400 600 800 1000 1200 Fraction Affected

dose

Dichotomous-Hill Model with 0.95 Confidence Level

16:18 01/12 2011

BMDL BMD

 

Dichotomous-Hill
F-16

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2 (*** The model parameter(s) –slope have been estimated at a boundary point, or have 

3 been specified by the user, and do not appear in the correlation matrix)

4

5 v g intercept

6 v 1 -0.25 -0.89

7 g -0.25 1 0.016

8 intercept -0.89 0.016 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 v 0.311077 0.156196 0.00493876 0.617216

16 g 0.0709966 0.0662298 -0.0588115 0.200805

17 intercept -6.06188 1.34538 -8.69878 -3.42498

18 slope 1 NA

19

20 NA - Indicates that this parameter has hit a bound implied by some inequality 

21 constraint and thus has no standard error.

22

23

24 Analysis of Deviance Table

25

26 Model Log(likelihood) # Param's Deviance Test d.f. P-value

27 Full model -62.1506 4

28 Fitted model -62.2022 3 0.103279 1 0.7479

29 Reduced model -69.3031 1 14.305 3 0.002518

30

31 AIC: 130.404

32

33 Goodness of Fit 

34 Scaled

35 Dose Est._Prob. Expected Observed Size Residual

36 ------------------------------------------------------------------------

37 0.0000 0.0221 1.104 1.000 50 -0.100

38 50.0000 0.0522 2.612 3.000 50 0.247

39 250.0000 0.1285 6.423 6.000 50 -0.179

40 1250.0000 0.2372 11.861 12.000 50 0.046

41

42 Chi^2 = 0.10 d.f. = 1 P-value = 0.7459

43

44

45 Benchmark Dose Computation

46 Specified effect = 0.1

47 Risk Type = Extra risk 

48 Confidence level = 0.95

49 BMD = 219.51

50 BMDL = 59.5598

F.2. SPONGIOSIS HEPATIS

51 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

52 fit to the incidence data shown in Table F-3, for spongiosis hepatis of the liver in male 

53 F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (Kasai, et al., 2009). Doses 

54 associated with a BMR of a 10% extra risk were calculated.
F-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%)

19/50a

(38%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. (2009). 

As assessed by the χ21 goodness-of-fit test, several models in the software provided 

adequate fits to the incidence data of spongiosis of the liver in male rats (χ22 p ≥ 0.1) (Table F-4). 

3 BMDL estimates for all adequately fitting models were not within threefold difference of each other

4 (U.S. EPA, 2000a). Therefore, in accordance with EPA BMD technical guidance (U.S. EPA, 

5 2000a), the adequately fitting model that resulted in the lowest BMDL was selected as 

6 appropriate for deriving a POD which was the Dichotomous-Hill model. However, the 

7 Dichotomous-Hill model, warned that the BMDL estimate was ―imprecise at best‖ (see Figure F8 2 and subsequent textual model output). Comparing across all models (excluding the 

9 dichotomous-hill model), a better fit is indicated by a lower AIC value since the BMDL estimates 

10 for all appropriately fitting models were within threefold difference of each other (U.S. EPA, 

11 2000a). As assessed by the AIC, the log-logistic model provided the best fit to the spongiosis 

12 incidence data for male rats (Table F-4, Figure F-3and subsequent textual model output) and 

13 could be used to derive a POD for this endpoint. 

Table F-4. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab206.472 0.4482 1.031 369.422 224.993

Logistic 207.141 0.3159 1.242 537.295 392.318

Log-logisticc, f 206.229 0.5102 0.912 314.34 172.092

Log-probitc

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

Weibullb

206.472 0.4482 1.031 369.422 224.993

Quantal-Linear 206.472 0.4482 1.031 369.422 224.993

DichotomousHillc, e 206.364 0.4671 1.031 289.919 59.69
F-18

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eModel output warned that the BMDL estimate was ―imprecise at best‖.

fBold 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 ==================================================================== 

3 Dichotomous Hill Model. (Version: 1.2; Date: 12/11/2009) 

4 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

5 files/dhl_spong_hepa_liver_Dhl-BMR10-Restrict.(d) 

6 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

7 files/dhl_spong_hepa_liver_Dhl-BMR10-Restrict.plt

8 Wed Jan 12 16:52:46 2011

9 ==================================================================== 

10 BMDS_Model_Run 

11 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

12 The form of the probability function is: 

13

14 P[response] = v*g +(v-v*g)/[1+EXP(-intercept-slope*Log(dose))]

15 where: 0 <= g < 1, 0 < v <= 1

16 v is the maximum probability of response predicted by the model,

17 and v*g is the background estimate of that probability.

18

19 Dependent variable = Effect

20 Independent variable = Dose

21 Slope parameter is restricted as slope >= 1

22

23 Total number of observations = 4

 0.1

 0.2

 0.3

 0.4

 0.5

 0 200 400 600 800 1000 1200 Fraction Affected

dose

Dichotomous-Hill Model with 0.95 Confidence Level

16:52 01/12 2011

BMDL BMD

 

Dichotomous-Hill
F-19

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Total number of records with missing values = 0

2 Maximum number of iterations = 250

3 Relative Function Convergence has been set to: 1e-008

4 Parameter Convergence has been set to: 1e-008

5

6 Default Initial Parameter Values 

7 v = -9999

8 g = -9999

9 intercept = -8.74962

10 slope = 1.13892

11

12 Asymptotic Correlation Matrix of Parameter Estimates

13 (*** The model parameter(s) -v -slope 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 g intercept

17 g 1 -0.53

18 intercept -0.53 1

19

20 Parameter Estimates

21

22 95.0% Wald Confidence Interval

23 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

24 v 1 NA

25 g 0.125 0.0332679 0.0597961 0.190204

26 intercept -7.86683 0.396424 -8.6438 -7.08985

27 slope 1 NA

28

29 NA - Indicates that this parameter has hit a bound implied by some inequality 

30 constraint and thus has no standard error.

31

32 Analysis of Deviance Table

33

34 Model Log(likelihood) # Param's Deviance Test d.f. P-value

35 Full model -100.45 4

36 Fitted model -101.182 2 1.46273 2 0.4813

37 Reduced model -106.633 1 12.3646 3 0.006233

38

39 AIC: 206.364

40

41 Goodness of Fit 

42 Scaled

43 Dose Est._Prob. Expected Observed Size Residual

44 ------------------------------------------------------------------------

45 0.0000 0.1250 6.250 7.000 50 0.321

46 50.0000 0.1415 7.073 6.000 50 -0.435

47 250.0000 0.2015 10.075 13.000 50 1.031

48 1250.0000 0.4084 20.420 19.000 50 -0.409

49

50 Chi^2 = 1.52 d.f. = 2 P-value = 0.4671

51

52

53 Benchmark Dose Computation

54 Specified effect = 0.1

55 Risk Type = Extra risk 

56 Confidence level = 0.95

57 BMD = 289.919

58

59 Warning: BMDL computation is at best imprecise for these data

60 BMDL = 59.69

61

62
F-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 ==================================================================== 

2 Logistic Model. (Version: 2.13; Date: 10/28/2009) 

3 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

4 files/lnl_spong_hepa_liver_Lnl-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/lnl_spong_hepa_liver_Lnl-BMR10-Restrict.plt

7 Wed Jan 12 16:52:44 2011

8 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

12

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

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

27 Default Initial Parameter Values 

28 background = 0.14

29 intercept = -8.74962

30 slope = 1.13892

31

 0.1

 0.2

 0.3

 0.4

 0.5

 0 200 400 600 800 1000 1200 Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

16:52 01/12 2011

BMDL BMD

 

Log-Logistic
F-21

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Asymptotic Correlation Matrix of Parameter Estimates

2 (*** The model parameter(s) -slope have been estimated at a boundary point, or have 

3 been specified by the user, and do not appear in the correlation matrix)

4

5 background intercept

6 background 1 -0.54

7 intercept -0.54 1

8

9 Parameter Estimates

10 95.0% Wald Confidence Interval

11 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

12 background 0.13769 * * *

13 intercept -7.9477 * * *

14 slope 1 * * *

15

16 * - Indicates that this value is not calculated.

17

18

19 Analysis of Deviance Table

20

21 Model Log(likelihood) # Param's Deviance Test d.f. P-value

22 Full model -100.45 4

23 Fitted model -101.115 2 1.3283 2 0.5147

24 Reduced model -106.633 1 12.3646 3 0.006233

25

26 AIC: 206.229

27

28

29 Goodness of Fit 

30 Scaled

31 Dose Est._Prob. Expected Observed Size Residual

32 ------------------------------------------------------------------------

33 0.0000 0.1377 6.885 7.000 50 0.047

34 50.0000 0.1527 7.633 6.000 50 -0.642

35 250.0000 0.2077 10.385 13.000 50 0.912

36 1250.0000 0.4019 20.097 19.000 50 -0.316

37

38 Chi^2 = 1.35 d.f. = 2 P-value = 0.5102

39

40

41 Benchmark Dose Computation

42 Specified effect = 0.1

43 Risk Type = Extra risk 

44 Confidence level = 0.95

45 BMD = 314.34

46 BMDL = 172.092

F.3. SQUAMOUS CELL METAPLASIA

47 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

48 fit to the incidence data shown in Table F-5, for squamous cell metaplasia of the respiratory 

49 epithelium in male F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (NCI, 1978). 

50 Doses associated with a BMR of a 10% extra risk were calculated.
F-22

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table F-5. Incidence 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 7/50b

(14%)

44/50a

(88%)

a

p≤ 0.01 by Fisher‘s exact test.

b

p≤ 0.05 by Fisher‘s exact test.

Source: Kasai et al. (2009). 

1 For incidence of squamous cell metaplasia in F344/DuCrj male rats, the logistic and 

probit models all exhibited a statistically significant lack of fit (i.e., 22 p-value < 0.1; see 

3 Table F-6), and thus should not be considered further for identification of a POD. All of the 

4 remaining models exhibited adequate fit. The BMDL estimates for all appropriately fitting models 

5 were within threefold difference of each other, indicating that BMDL selection should be made based 

6 on model fit (U.S. EPA, 2000a). As assessed by the AIC, the Log-probit model provided the best 

7 fit to the squamous cell metaplasia data for male rats (Table F-6, Figure F-4), and could be used 

8 to derive a POD for this endpoint. 

Table F-6. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

81.687 0.8682 0.24 218.38 150.329

Logistic 89.4148 0.0464 1.806 370.443 288.535

Log-logisticc

81.5252 0.9142 0.131 218.218 158.293

Log-probitc, 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

Weibullb

82.1236 0.7679 0.33 218.435 145.383

Quantal-Linear 92.9215 0.0198 -1.76 87.682 68.8015

DichotomousHillc

83.1888 0.9995 0 240.867 161.945
F-23

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eBold 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 ==================================================================== 

2 Probit Model. (Version: 3.2; Date: 10/28/2009) 

3 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

4 files/lnp_squ_cell_meta_re_Lnp-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/lnp_squ_cell_meta_re_Lnp-BMR10-Restrict.plt

7 Thu Jan 13 13:11:09 2011

8 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

12

13 P[response] = Background + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)),

14 where CumNorm(.) is the cumulative normal distribution function

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

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 1200 Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

13:11 01/13 2011

BMDL BMD

 

LogProbit
F-24

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 User has chosen the log transformed model

6

7 Default Initial (and Specified) Parameter Values 

8 background = 0

9 intercept = -6.76507

10 slope = 1.09006

11

12 Asymptotic Correlation Matrix of Parameter Estimates

13 (*** The model parameter(s) -background have been estimated at a boundary point, or 

14 have been specified by the user, and do not appear in the correlation matrix)

15

16 intercept slope

17 intercept 1 -0.99

18 slope -0.99 1

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 NA

25 intercept -8.86173 1.2226 -11.258 -6.46548

26 slope 1.40803 0.193057 1.02965 1.78642

27

28 NA - Indicates 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 -38.5944 4

35 Fitted model -38.615 2 0.041197 2 0.9796

36 Reduced model -113.552 1 149.916 3 <.0001

37

38 AIC: 81.23

39

40 Goodness of Fit 

41 Scaled

42 Dose Est._Prob. Expected Observed Size Residual

43 ------------------------------------------------------------------------

44 0.0000 0.0000 0.000 0.000 50 0.000

45 50.0000 0.0004 0.020 0.000 50 -0.141

46 250.0000 0.1384 6.922 7.000 50 0.032

47 1250.0000 0.8808 44.038 44.000 50 -0.017

48

49 Chi^2 = 0.02 d.f. = 2 P-value = 0.9894

50

51

52 Benchmark Dose Computation

53 Specified effect = 0.1

54 Risk Type = Extra risk 

55 Confidence level = 0.95

56 BMD = 217.79

57 BMDL = 159.619

F.4. SQUAMOUS CELL HYPERPLASIA

58 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

59 fit to the incidence data shown in Table F-7, for squamous cell hyperplasia of the respiratory 
F-25

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 epithelium in male F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (NCI, 1978). 

2 Doses associated with a BMR of a 10% extra risk were calculated.

Table F-7. Incidence of squamous cell hyperplasia 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 1/50

(2%)

10/50a

(20%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. (2009). 

3 For incidence of squamous cell hyperplasia in F344/DuCrj male rats, the logistic, probit, 

and quantal-linear models all exhibited a statistically significant lack of fit (i.e., 24 p-value < 0.1; 

5 see Table F-8), and thus should not be considered further for identification of a POD. All of the 

6 remaining models exhibited adequate fit. The BMDL estimates for all appropriately fitting models 

7 were within threefold difference of each other, indicating that BMDL selection should be made based 

8 on model fit (U.S. EPA, 2000a). As assessed by the AIC, the Log-probit model provided the best 

9 fit to the squamous cell hyperplasia data for male rats (Table F-8, Figure F-5 and subsequent 

10 textual model output), and could be used to derive a POD for this endpoint. 

Table F-8. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

81.687 0.8682 0.24 218.38 150.329

Logistic 89.4148 0.0464 1.806 370.443 288.535

Log-logisticc

81.5252 0.9142 0.131 218.218 158.293

Log-probitc, 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

Weibullb

82.1236 0.7679 0.33 218.435 145.383

Quantal-Linear 92.9215 0.0198 -1.76 87.682 68.8015

DichotomousHillc

83.1888 0.9995 0 240.867 161.945
F-26

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eBold 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 ==================================================================== 

2 Probit Model. (Version: 3.2; Date: 10/28/2009) 

3 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

4 files/lnp_squ_cell_hyper_re_Lnp-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/lnp_squ_cell_hyper_re_Lnp-BMR10-Restrict.plt

7 Thu Jan 13 13:25:05 2011

8 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

12

13 P[response] = Background + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)),

14 where CumNorm(.) is the cumulative normal distribution function

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

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 200 400 600 800 1000 1200 Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

13:25 01/13 2011

BMDL BMD

 

LogProbit
F-27

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 User has chosen the log transformed model

6

7 Default Initial (and Specified) Parameter Values 

8 background = 0

9 intercept = -7.75604

10 slope = 1

11

12 Asymptotic Correlation Matrix of Parameter Estimates

13 (*** The model parameter(s) -background -slope have been estimated at a boundary 

14 point, or have been specified by the user, and do not appear in the correlation 

15 matrix)

16

17 intercept

18 intercept 1

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 NA

25 intercept -7.90911 0.186242 -8.27414 -7.54408

26 slope 1 NA

27

28 NA - Indicates 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 -29.9221 4

35 Fitted model -30.2589 1 0.673572 3 0.8794

36 Reduced model -42.5964 1 25.3487 3 <.0001

37

38 AIC: 62.5177

39

40 Goodness of Fit 

41 Scaled

42 Dose Est._Prob. Expected Observed Size Residual

43 ------------------------------------------------------------------------

44 0.0000 0.0000 0.000 0.000 50 0.000

45 50.0000 0.0000 0.002 0.000 50 -0.040

46 250.0000 0.0085 0.424 1.000 50 0.889

47 1250.0000 0.2182 10.911 10.000 50 -0.312

48

49 Chi^2 = 0.89 d.f. = 3 P-value = 0.8282

50

51

52 Benchmark Dose Computation

53 Specified effect = 0.1

54 Risk Type = Extra risk 

55 Confidence level = 0.95

56 BMD = 755.635

57 BMDL = 560.86

F.5. RESPIRATORY METAPLASIA

58 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

59 fit to the incidence data shown in Table F-9, for respiratory metaplasia of the olfactory 
F-28

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 epithelium in male F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (NCI, 1978). 

2 Doses associated with a BMR of a 10% extra risk were calculated.

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%)

48/50a

(96%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. (2009).

As assessed by the χ23 goodness-of-fit test, no models in the software provided adequate 

4 fits to the data for the incidence of respiratory metaplasia of the olfactory epithelium in male rats 

(χ25 p ≥ 0.1) (Table F-10). However, given that first non-control dose had a response level 

6 substantially above the desired BMR (i.e. 10%), the use of BMD methods included substantial 

7 model uncertainty. The model uncertainty associated with this dataset is related to low-dose 

8 extrapolation and consistent with BMD technical guidance document (USEPA, 2000), all 

9 available dichotomous models in the Benchmark Dose Software (version 2.1.2) were fit to the 

incidence data shown in Table F-9 with the highest dose group omitted. As assessed by the χ210

11 goodness-of-fit test , the logistic, log-logistic, log-probit, and probit models all exhibited a 

statistically significant lack of fit (i.e., 212 p-value < 0.1;See Table F-11), and thus should not be 

13 considered further for identification of a POD. The BMDL estimates for all appropriately fitting 

14 models were within threefold difference of each other, indicating that BMDL selection should be 

15 made based on model fit (U.S. EPA, 2000a). The AIC values for gamma, multistage, quantal16 linear, and Weibull models in Table F-11 are equivalent and the lowest and, in this case, 

17 essentially represent the same model. Therefore, consistent with the external review draft 

18 Benchmark Dose Technical Guidance (U.S. EPA, 2000a), any of them with equal AIC values 

19 (gamma, multistage, quantal-linear, or Weibull) could be used to identify a POD for this 

20 endpoint. The model plot for the gamma model (Figure F-6) and output are included immediately 

21 after the table. 

22
F-29

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table F-10. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

179.68 0 -2.07 17.4082 12.3829

Logistic 191.339 0 1.788 34.2946 24.5917

Log-logisticc

152.72 0.0285 0.039 4.05465 1.90233

Log-probitc161.267 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

Weibullb

179.68 0 -2.07 17.4082 12.3829

Quantal-Linear 179.68 0 -2.07 17.4082 12.3829

DichotomousHillc

150.466 NA 0 38.8552 31.4727

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

Source: Kasai et al. (2009). 

Table F-11. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab, e 129.463 0.5815 -0.106 6.46848 4.73742

Logistic 133.583 0.0119 -1.031 12.5197 9.34421

Log-logisticc

131.182 NA 0 14.2075 3.77044

Log-probitc131.182 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

Weibullb

129.463 0.5815 -0.106 6.46847 4.73742

Quantal-Linear e

129.463 0.5815 -0.106 6.46847 4.73742
F-30

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eBold 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 ==================================================================== 

2 Gamma Model. (Version: 2.15; Date: 10/28/2009) 

3 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

4 files/gam_resp_meta_no high dose_Gam-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/gam_resp_meta_no high dose_Gam-BMR10-Restrict.plt

7 Thu Jan 13 16:24:15 2011

8 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

12

13 P[response]= background+(1-background)*CumGamma[slope*dose,power],

14 where CumGamma(.) is the cummulative Gamma distribution function

15

16 Dependent variable = Effect

17 Independent variable = Dose

18 Power parameter is restricted as power >=1

19

20 Total number of observations = 3

21 Total number of records with missing values = 0

 0.2

 0.4

 0.6

 0.8

 1

 0 50 100 150 200 250 Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

16:24 01/13 2011

BMDL BMD

 

Gamma Multi-Hit
F-31

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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 (and Specified) Parameter Values 

6 Background = 0.230769

7 Slope = 0.022439

8 Power = 1.3

9

10 Asymptotic Correlation Matrix of Parameter Estimates

11 (*** The model parameter(s) -Power 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 Slope

15 Background 1 -0.33

16 Slope -0.33 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 0.226249 0.0588535 0.110898 0.3416

23 Slope 0.0162883 0.00320976 0.00999729 0.0225793

24 Power 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 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -62.5908 3

33 Fitted model -62.7313 2 0.280907 1 0.5961

34 Reduced model -99.1059 1 73.0301 2 <.0001

35

36 AIC: 129.463

37

38 Goodness of Fit 

39 Scaled

40 Dose Est._Prob. Expected Observed Size Residual

41 ------------------------------------------------------------------------

42 0.0000 0.2262 11.312 11.000 50 -0.106

43 50.0000 0.6573 32.865 34.000 50 0.338

44 250.0000 0.9868 49.341 49.000 50 -0.422

45

46 Chi^2 = 0.30 d.f. = 1 P-value = 0.5815

47

48 Benchmark Dose Computation

49 Specified effect = 0.1

50 Risk Type = Extra risk 

51 Confidence level = 0.95

52 BMD = 6.46848

53 BMDL = 4.73742

F.6. ATROPHY

54 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

55 fit to the incidence data shown in Table F-12, for atrophy of the olfactory epithelium in male 

56 F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (Kasai, et al., 2009). Doses 

57 associated with a BMR of a 10% extra risk were calculated.
F-32

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table F-12. 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

0/50 40/50 a

(80%)

47/50 a

(94%)

48/50a

(96%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. (2009).

As assessed by the χ21 goodness-of-fit test, the gamma, logistic, log-probit, multistage, 

2 probit, Weibull, and quantal-linear models all exhibited a statistically significant lack of fit (i.e., 

2

3 p-value < 0.1;See Table F-13), and thus should not be considered further for identification of a 

4 POD. The BMDL estimates for all appropriately fitting models were within threefold difference of 

5 each other, indicating that BMDL selection should be made based on model fit (U.S. EPA, 2000a). 

6 As assessed by the AIC, the Log-logistic model provided the best fit to the atrophy data for male 

7 rats (Table F-13, Figure F-7), and could be used to derive a POD for this endpoint. However, 

8 given that first non-control dose had a response level substantially above the desired BMR (i.e. 

9 10%), the use of BMD methods included substantial model uncertainty. 

Table F-13. Goodness-of-fit statistics and BMD10 and BMDL10 values from 

models fit to incidence data for atrophy of olfactory epithelium in male 

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

Model AIC p-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

159.444 0 0 9.93187 8.14152

Logistic 190.692 0 4.342 33.9373 25.4454

Log-logisticc

93.9074 0.3023 0 1.67195 1.01633

Log-probitc

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

Weibullb159.444 0 0 9.9319 8.14152

Quantal-Linear 159.444 0 0 9.9319 8.14152

DichotomousHillc

95.5314 1 0 2.93951 0.544697

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eBold 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 ==================================================================== 

2 Logistic Model. (Version: 2.13; Date: 10/28/2009) 

3 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

4 files/lnl_atrophy_Lnl-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/lnl_atrophy_Lnl-BMR10-Restrict.plt

7 Fri Jan 14 09:53:22 2011

8 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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

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

27 Default Initial Parameter Values 

28 background = 0

29 intercept = -3.48908

30 slope = 1

31

32 Asymptotic Correlation Matrix of Parameter Estimates

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 1200 Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

09:53 01/14 2011

BMDLBMD

 

Log-Logistic
F-34

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (*** The model parameter(s) -background -slope have been estimated at a boundary 

2 point, or have been specified by the user, and do not appear in the correlation 

3 matrix)

4

5 intercept

6 intercept 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 * * *

12 intercept -2.71122 * * *

13 slope 1 * * *

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 -44.7657 4

21 Fitted model -45.9537 1 2.37596 3 0.4981

22 Reduced model -126.116 1 162.701 3 <.0001

23

24 AIC: 93.9074

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 0.7687 38.433 40.000 50 0.525

32 250.0000 0.9432 47.161 47.000 50 -0.099

33 1250.0000 0.9881 49.405 48.000 50 -1.833

34

35 Chi^2 = 3.65 d.f. = 3 P-value = 0.3023

36

37 Benchmark Dose Computation

38 Specified effect = 0.1

39 Risk Type = Extra risk 

40 Confidence level = 0.95

41 BMD = 1.67195

42 BMDL = 1.01633

F.7. HYPDROPIC CHANGE

43 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

44 fit to the incidence data shown in Table F-14, for hydropic change of the lamina propria in the 

45 nasal cavity of male F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (Kasai, et al., 

46 2009). Doses associated with a BMR of a 10% extra risk were calculated.

47
F-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%)

49/50a

(98%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al., (2009).

1 For incidence of hydropic change of the lamina propria in F344/DuCrj male rats, the 

2 gamma, logistic, multistage, probit, Weibull, and quantal-linear models all exhibited a 

statistically significant lack of fit (i.e., 23 p-value < 0.1; see Table F-16), and thus should not be 

4 considered further for identification of a POD. The BMDL estimates for all appropriately fitting 

5 models were within threefold difference of each other, indicating that BMDL selection should be 

6 made based on model fit (U.S. EPA, 2000a). As assessed by the AIC, the Log-logistic model 

7 provided the best fit to the hydropic change of the lamina propria data for male rats (Table F-15, 

8 Figure F-8 and subsequent text output), and could be used to derive a POD of for this endpoint. 

Table F-15. Goodness-of-fit statistics and BMD10 and BMDL10 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

98.3441 0.0002 -1.321 51.979 28.7632

Logistic 117.957 0 -1.143 89.2909 70.6131

Log-logisticc

90.5388 0.6819 -0.333 68.5266 46.7808

Log-probitc

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

Weibullb

100.225 0.0033 -1.899 39.1371 23.9762

Quantal-Linear 99.3482 0.0256 -2.411 28.7899 22.6831

DichotomousHillc

91.8937 1 0 73.1032 49.2687

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eBold 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 ==================================================================== 

2 Logistic Model. (Version: 2.13; Date: 10/28/2009) 

3 Input Data File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

4 files/lnl_hydrpic_Lnl-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/lnl_hydrpic_Lnl-BMR10-Restrict.plt

7 Fri Jan 14 10:30:47 2011

8 ==================================================================== 

9 BMDS_Model_Run 

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 = -11.5745

29 slope = 2.19638

30

31 Asymptotic Correlation Matrix of Parameter Estimates

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 1200 Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

10:30 01/14 2011

BMDL BMD

 

Log-Logistic
F-37

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 (*** The model parameter(s) -background have been estimated at a boundary point, or 

2 have been specified by the user, and do not appear in the correlation matrix)

3

4 intercept slope

5 intercept 1 -0.99

6 slope -0.99 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 intercept -12.1316 * * *

14 slope 2.3501 * * *

15

16 * - Indicates that this value is not calculated.

17

18 Analysis of Deviance Table

19

20 Model Log(likelihood) # Param's Deviance Test d.f. P-value

21 Full model -42.9468 4

22 Fitted model -43.2694 2 0.645129 2 0.7243

23 Reduced model -136.935 1 187.976 3 <.0001

24

25 AIC: 90.5388

26

27 Goodness of Fit 

28 Scaled

29 Dose Est._Prob. Expected Observed Size Residual

30 ------------------------------------------------------------------------

31 0.0000 0.0000 0.000 0.000 50 0.000

32 50.0000 0.0503 2.515 2.000 50 -0.333

33 250.0000 0.6994 34.969 36.000 50 0.318

34 1250.0000 0.9903 49.515 49.000 50 -0.744

35

36 Chi^2 = 0.77 d.f. = 2 P-value = 0.6819

37

38

39 Benchmark Dose Computation

40 Specified effect = 0.1

41 Risk Type = Extra risk 

42 Confidence level = 0.95

43 BMD = 68.5266

44 BMDL = 46.7808

F.8. SCLEROSIS

45 All available dichotomous models in the Benchmark Dose Software (version 2.1.2) were 

46 fit to the incidence data shown in Table F-16, for sclerosis of the lamina propria in the nasal 

47 cavity of male F344/DuCrj rats exposed to 1,4-dioxane vapors for 2 years (Kasai, et al., 2009). 

48 Doses associated with a BMR of a 10% extra risk were calculated.
F-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%)

40/50a

(80%)

a

p≤ 0.01 by Fisher‘s exact test.

Source: Kasai et al. (2009).

As assessed by the χ21 goodness-of-fit test , all models with the exception of the 

dichotomous-hill model, exhibited a statistically significant lack of fit (i.e., 22 p-value < 0.1;See 

3 Table F-17), and thus should not be considered further for identification of a POD. Since the 

4 dichotomous-hill model provided the only fit to the sclerosis of the lamina propria data for male 

rats as assessed by the χ25 goodness-of-fit test (Table F-17, Figure F-9 and subsequent text 

6 output), it could be considered to derive a POD for this endpoint; however, the model output 

7 warned that the BMDL estimate was ―imprecise at best‖. 

Table F-17. Goodness-of-fit statistics and BMD10 and BMDL10 values from 

models fit to incidence data for sclerosis 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-valuea

Scaled 

Residual of 

Interest

BMD10

(ppm)

BMDL10

(ppm)

Male

Gammab

134.416 0.0123 -1.89 75.4489 57.6938

Logistic 161.562 0 4.542 244.217 196.446

Log-logisticc

130.24 0.0683 -1.579 86.3863 52.4762

Log-probitc

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

Weibullb132.436 0.0356 -1.949 71.9719 57.6471

Quantal-Linear 132.436 0.0356 -1.949 71.9719 57.6471

DichotomousHillc, e 124.633 0.9994 0 206.74 167.46

a

p-Value from the χ2goodness-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.

dBetas restricted to ≥0.

eModel output warned that the BMDL estimate was ―imprecise at best‖.

Source: Kasai et al. (2009). 

8
F-39

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 ==================================================================== 

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_sclerosis_Dhl-BMR10-Restrict.(d) 

5 Gnuplot Plotting File: C:/Documents and Settings/pgillesp/Desktop/BMDS 

6 files/dhl_sclerosis_Dhl-BMR10-Restrict.plt

7 Fri Jan 14 10:53:28 2011

8 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

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 = -11.4511

31 slope = 1.86444

32

33 Asymptotic Correlation Matrix of Parameter Estimates

34 (*** The model parameter(s) -g have been estimated at a boundary point, or have been 

35 specified by the user, and do not appear in the correlation matrix)

36

37 v intercept slope

38 v 1 0.00074 -0.00078

39 intercept 0.00074 1 -1

40 slope -0.00078 -1 1

41

42 Parameter Estimates

43

44 95.0% Wald Confidence Interval

45 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

46 v 0.8 0.0565686 0.689128 0.910872

47 g 0 NA

48 intercept -62.1804 4133.38 -8163.46 8039.1

49 slope 11.2979 748.603 -1455.94 1478.53

50

51 NA - Indicates that this parameter has hit a bound implied by some inequality 

52 constraint and thus has no standard error.

53

54

55 Analysis of Deviance Table

56

57 Model Log(likelihood) # Param's Deviance Test d.f. P-value

58 Full model -59.3166 4

59 Fitted model -59.3166 3 1.23973e-006 1 0.9991

60 Reduced model -123.82 1 129.007 3 <.0001

61

62 AIC: 124.633

63

64 Goodness of Fit 

65 Scaled

66 Dose Est._Prob. Expected Observed Size Residual
F-40

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 ------------------------------------------------------------------------

2 0.0000 0.0000 0.000 0.000 50 0.000

3 50.0000 0.0000 0.000 0.000 50 -0.001

4 250.0000 0.4400 22.000 22.000 50 0.000

5 1250.0000 0.8000 40.000 40.000 50 -0.000

6

7 Chi^2 = 0.00 d.f. = 1 P-value = 0.9994

8

9 Benchmark Dose Computation

10 Specified effect = 0.1

11 Risk Type = Extra risk 

12 Confidence level = 0.95

13 BMD = 206.74

14

15 Warning: BMDL computation is at best imprecise for these data

16 BMDL = 167.46

Figure F-9. BMD Log-logistic model 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.

 0

 0.2

 0.4

 0.6

 0.8

 0 200 400 600 800 1000 1200 Fraction Affected

dose

Dichotomous-Hill Model with 0.95 Confidence Level

10:53 01/14 2011

BMDL BMD

 

Dichotomous-Hill
G-41

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

APPENDIX G. DETAILS OF BMD ANALYSIS FOR INHALATION UNIT RISK FOR 

1,4-DIOXANE

1 Multistage cancer models available in the Benchmark Dose Software (BMDS) (version 

2 2.2beta) were fit to the incidence data for hepatocellular carcinoma and/or adenoma, nasal cavity 

3 squamous cell carcinoma, renal cell carcinoma, peritoneal mesothelioma, and mammary gland 

4 fibroadenoma, Zymbal gland adenoma, and subcutis fibroma in rats exposed to 1,4-dioxane 

5 vapors for 2 years (Kasai, et al., 2009). Concentrations associated with a benchmark response 

6 (BMR) of a 10% extra risk were calculated. BMC10 and BMCL10 values from the best fitting 

model, determined by adequate global- fit (χ2 7 p ≥ 0.1) and AIC values, are reported for each 

8 endpoint (U.S. EPA, 2000a). Given the multiplicity of tumor sites, basing the IUR on one tumor 

9 site will underestimate the carcinogenic potential of 1,4-dioxane. A Bayesian analysis was 

10 performed using WinBUGS ((Spiegelhalter, et al., 2003), freeware developed by the MRC 

11 Biostatistical Unit, Cambridge, United Kingdom (available at http://www.mrc12 bsu.cam.ac.uk/bugs/winbugs/contents.shtml)) and reported in detail in Section G.3. In addition, 

13 the combined tumor analysis was also performed using the beta version of the BMDS MSCombo 

14 model (BMDS Version 2.2beta) and is included in Section G.4. The results of both analyses 

15 were very similar.

16 A summary of the BMDS model predictions for the Kasai et al. (2009) study are shown 

17 in Table G-1. 

G.1. GENERAL ISSUES AND APPROACHES TO BMDS AND MULTITUMOR 

MODELING

G.1.1. Combining Data tumor types

18 The incidence of adenomas and the incidence of carcinomas within a dose group at a site 

19 or tissue in rodents are sometimes combined. This practice is based upon the hypothesis that 

20 adenomas may develop into carcinomas if exposure at the same dose was continued (McConnell, 

21 et al., 1986; U.S. EPA, 2005a). In the same manner and was done for the oral cancer assessment 

22 (Appendix D), the incidence of hepatic adenomas and carcinomas was summed without double23 counting them so as to calculate the combined incidence of either a hepatic carcinoma or a 

24 hepatic adenoma in rodents. 

25 The remaining of the tumor types were assumed to occur independently.

 

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)
G-42

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

G.1.2. Summary 

1 The BMDS models recommended to calculate rodent BMC10 and BMCL10 values for 

2 individual tumor types and combined tumor analysis are summarized in Table G-1. The first 

3 order multistage models for most tumor types were selected because they resulted in the lowest 

4 AIC values; however, for renal cell carcinoma and Zymbal gland adenoma, the lowest AIC 

5 model was not the first order model. In BMDS, the third order model resulted in the lowest AIC 

(1st, 2nd, and 3rd 6 degree models were evaluated); however, using the MCMC approach in 

7 WinBUGS, the third order multistage model did not converge while the second order model did 

8 converge. Thus, for renal cell carcinoma and Zymbal gland adenoma, the second order 

9 multistage model was used in both the MCMC (WinBugs) approach and the BMDS (Version 2.2 

10 beta) MSCombo approach for direct comparison of results. These results are shown below in 

11 Table G-1.

Table G-1. Summary of BMC10 and BMCL10 model results for individual 

tumor types 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

BMC10

(ppm)

BMCL10

(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 fibromaaFirst 89.2 0.5245 0.537 141.762 81.9117

WinBUGS multitumor analysisb39.2 31.4

BMDS Version 2.2beta MSCombo 40.4 30.3

aHigh-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 FOR MULTISTAGE CANCER MODELS FOR 

INIDIVIDUAL TUMOR TYPES

12 For tumor incidence data reported in the Kasai et al. (2009) 2-year inhalation bioassay, 

13 multistage cancer models of 1, 2, and 3 degrees were implemented BMDS (Version 2.2Beta). 

14 Incidence data used for BMD analysis are shown in Table G-2. Tumor incidence for mammary 

15 gland adenoma was excluded from this analysis since only 1 tumor of this type was found across 

16 all doses.
G-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 6/50b,c

Hepatocellular adenoma 1/50 2/50 3/50 21/50a,c

Hepatocellular carcinoma 0/50 0/50 1/50 2/50

Hepatocellular adenoma or carcinoma 1/50 2/50 4/50 22/50a,c

Renal cell carcinoma 0/50 0/50 0/50 4/50c

Peritoneal mesothelioma 2/50 4/50 14/50a41/50a,c

Mammary gland fibroadenoma 1/50 2/50 3/50 5/50d

Zymbal gland adenoma 0/50 0/50 0/50 4/50c

Subcutis fibroma 1/50 4/50 9/50a5/50

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 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)

G.2.1. Nasal Squamous Cell Carcinoma

1 The incidence data for nasal squamous cell carcinoma were monotonic non-decreasing 

2 functions of dose; therefore, these data appear to be appropriate for dose-response modeling 

using BMDS. The results of the BMDS modeling for the multistage cancer model for 1st, 2nd 3 , 

and 3rd-degree polynomials are shown in Table G-3. The 1st 4 -degree polynomial was the best 

fitting model based on AIC. The plot (Figure G-1) and model output for the 1st 5 -degree model are 

6 shown below.

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

BMC10

(ppm)

BMCL10

(ppm)

Firstb49.0308 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

aBest-fitting model based on AIC.

7

8
G-44

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Figure G-1. Multistage model (1st-degree) for male rat nasal squamous cell 

carcinomas.

1 ==================================================================== 

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 ==================================================================== 

9 BMDS_Model_Run 

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

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0 200 400 600 800 1000 1200 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:26 11/17 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-45

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Relative Function Convergence has been set to: 1e-008

2 Parameter Convergence has been set to: 1e-008

3

4

5 Default Initial Parameter Values 

6 Background = 0

7 Beta(1) = 0.000104666

8

9 Asymptotic Correlation Matrix of Parameter Estimates

10 (***The model parameter(s) -Background have been estimated at a boundary point, or 

11 have been specified by the user, and do not appear in the correlation matrix )

12

13 Beta(1)

14 Beta(1) 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) 9.51733e-005 * * *

21

22 * - Indicates that this value is not calculated.

23

24 Analysis of Deviance Table

25

26 Model Log(likelihood) # Param's Deviance Test d.f. P-value

27 Full model -23.2482 4

28 Fitted model -23.5154 1 0.534383 3 0.9113

29 Reduced model -30.3429 1 14.1894 3 0.002658

30

31 AIC: 49.0308

32

33 Log-likelihood Constant 20.493267595834471 

34

35

36 Goodness of Fit 

37 Scaled

38 Dose Est._Prob. Expected Observed Size Residual

39 ------------------------------------------------------------------------

40 0.0000 0.0000 0.000 0 50 0.000

41 50.0000 0.0047 0.237 0 50 -0.488

42 250.0000 0.0235 1.176 1 50 -0.164

43 1250.0000 0.1122 5.608 6 50 0.176

44

45 Chi^2 = 0.30 d.f. = 3 P-value = 0.9607

46

47

48 Benchmark Dose Computation

49

50 Specified effect = 0.1

51 Risk Type = Extra risk 

52 Confidence level = 0.95

53 BMD = 1107.04

54 BMDL = 629.948

55 BMDU = 2215.11

56

57 Taken together, (629.948, 2215.11) is a 90% two-sided confidence interval for the BMD

G.2.2. Hepatocellular Adenoma and Carcinoma

58 The incidence data for the occurrence of either hepatocellular adenoma or carcinoma 

59 were combined for this analysis as explained in G.1.1. The incidence data were monotonic non60 decreasing functions of dose; therefore, these data appear to be appropriate for dose-response 
G-46

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 modeling using BMDS. The results of the BMDS modeling for the multistage cancer model for 

1

st, 2nd, and 3rd

-degree polynomials are shown in Table G-4. The 1st 2 -degree polynomial was the 

best fitting model based on AIC. The plot (Figure G-2) and model output for the 1st 3 -degree 

4 model are shown below.

Table G-4. BMDS Multistage cancer dose-response modeling results for the 

incidence of either hepatocellular adenoma or carcinoma 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

BMC10

(ppm)

BMCL10

(ppm)

Firsta127.86 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

aBest-fitting model based on AIC.

Figure G-2. Multistage model (1st-degree) for male rat hepatocellular 

adenomas and carcinomas.

5

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0 200 400 600 800 1000 1200 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:24 11/17 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-47

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 ==================================================================== 

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 ==================================================================== 

9 BMDS_Model_Run 

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 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 Convergence has been set to: 1e-008

28

29 Default Initial Parameter Values 

30 Background = 0.00480969

31 Beta(1) = 0.0004548

32

33 Asymptotic Correlation Matrix of Parameter Estimates

34

35 Background Beta(1)

36 Background 1 -0.53

37 Beta(1) -0.53 1

38

39 Parameter Estimates

40

41 95.0% Wald Confidence Interval

42 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

43 Background 0.0170678 * * *

44 Beta(1) 0.000416776 * * *

45

46 * - Indicates that this value is not calculated.

47

48 Analysis of Deviance Table

49

50 Model Log(likelihood) # Param's Deviance Test d.f. P-value

51 Full model -61.5341 4

52 Fitted model -61.9302 2 0.792109 2 0.673

53 Reduced model -82.7874 1 42.5066 3 <.0001

54

55 AIC: 127.86

56

57 Log-likelihood Constant 55.486699676972215 

58

59 Goodness of Fit 

60 Scaled

61 Dose Est._Prob. Expected Observed Size Residual

62 ------------------------------------------------------------------------

63 0.0000 0.0171 0.853 1 50 0.160

64 50.0000 0.0373 1.867 2 50 0.099

65 250.0000 0.1143 5.716 4 50 -0.763

66 1250.0000 0.4162 20.810 22 50 0.342
G-48

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Chi^2 = 0.73 d.f. = 2 P-value = 0.6928

2

3

4 Benchmark Dose Computation

5

6 Specified effect = 0.1

7 Risk Type = Extra risk 

8 Confidence level = 0.95

9 BMD = 252.799

10 BMDL = 182.256

11 BMDU = 371.457

12

13 Taken together, (182.256, 371.457) is a 90% two-sided confidence interval for the BMD

14

G.2.3. Renal Cell Carcinoma and Zymbal Gland Adenoma

15 The incidence data for renal cell carcinomas and Zymbal gland adenomas were the same. 

16 These data were monotonic non-decreasing functions of dose; therefore, these data appear to be 

17 appropriate for dose-response modeling using BMDS. The results of the BMDS modeling for 

the multistage cancer model for 1st, 2nd, and 3rd 18 -degree polynomials are shown in Table G-5. The 

3

rd 19 -degree polynomial was the best fitting model based on AIC; however, when conducting the 

multitumor analysis, WinBUGS was unable to converge using the 3rd 20 degree model. Thus, the 

2

nd 21 degree model was used in the multitumor analyses. The plots (Figure G-3 and G-4) and 

model outputs for both the 2nd and 3rd 22 -degree models are shown below.

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

BMC10

(ppm)

BMCL10

(ppm)

First 31.6629 0.8004 0.446 1974.78 957.63

Second 30.2165 0.9817 0.085 1435.28 999.44

Thirda29.9439 0.9984 0.017 1355.16 1016.15

aBest-fitting model based on AIC.
G-49

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Figure G-3. Multistage model (2nd-degree) for male rat renal cell carcinomas 

and Zymbal gland adenomas.

1 ==================================================================== 

2 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 

3 Input Data File: C:/Documents and 

4 Settings/emclanah/Desktop/BMD_14D_Cancer/Data/msc_Kasai2009_renal_Msc2-BMR10.(d) 

5 Gnuplot Plotting File: C:/Documents and 

6 Settings/emclanah/Desktop/BMD_14D_Cancer/Data/msc_Kasai2009_renal_Msc2-BMR10.plt

7 Thu Feb 10 10:17:39 2011

8 ==================================================================== 

9 BMDS_Model_Run 

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 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 = 3

23 Total number of specified parameters = 0

24 Degree of polynomial = 2

25

26 Maximum number of iterations = 250

 0

 0.05

 0.1

 0.15

 0.2

 0 200 400 600 800 1000 1200 1400 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:17 02/10 2011

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-50

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Relative Function Convergence has been set to: 1e-008

2 Parameter Convergence has been set to: 1e-008

3

4 Default Initial Parameter Values 

5 Background = 0

6 Beta(1) = 0

7 Beta(2) = 5.40386e-008

8

9 Asymptotic Correlation Matrix of Parameter Estimates

10 (*** The model parameter(s) -Background -Beta(1) 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 Beta(2)

15 Beta(2) 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 * * *

21 Beta(1) 0 * * *

22 Beta(2) 5.11454e-008 * * *

23

24 * - Indicates that this value is not calculated.

25

26 Analysis of Deviance Table

27

28 Model Log(likelihood) # Param's Deviance Test d.f. P-value

29 Full model -13.9385 4

30 Fitted model -14.1082 1 0.339554 3 0.9524

31 Reduced model -19.6078 1 11.3387 3 0.01003

32

33 AIC: 30.2165

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 50 0.000

40 50.0000 0.0001 0.006 0.000 50 -0.080

41 250.0000 0.0032 0.160 0.000 50 -0.400

42 1250.0000 0.0768 3.840 4.000 50 0.085

43

44 Chi^2 = 0.17 d.f. = 3 P-value = 0.9817

45

46 Benchmark Dose Computation

47 Specified effect = 0.1

48 Risk Type = Extra risk 

49 Confidence level = 0.95

50 BMD = 1435.28

51 BMDL = 999.44

52

53 BMDU = 3666.87

54

55 Taken together, (999.44 , 3666.87) is a 90% two-sided confidence interval for the BMD

56

57 Multistage Cancer Slope Factor = 0.000100056
G-51

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Figure G-4. Multistage model (3rd-degree) for male rat renal cell carcinomas.

1 ==================================================================== 

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 ==================================================================== 

9 BMDS_Model_Run 

10 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

11 The form of the probability function is: 

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

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

 0

 0.05

 0.1

 0.15

 0.2

 0 200 400 600 800 1000 1200 1400 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:28 11/17 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-52

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

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) = 0

7 Beta(3) = 4.2804e-011

8

9

10 Asymptotic Correlation Matrix of Parameter Estimates

11 (*** The model parameter(s) -Background -Beta(1) -Beta(2) have been estimated at a 

12 boundary point, or have been specified by the user, and do not appear in the 

13 correlation matrix)

14

15 Beta(3)

16 Beta(3) 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 * * *

23 Beta(1) 0 * * *

24 Beta(2) 0 * * *

25 Beta(3) 4.23353e-011 * * *

26

27 * - Indicates that this value is not calculated.

28

29 Analysis of Deviance Table

30

31 Model Log(likelihood) # Param's Deviance Test d.f. P-value

32 Full model -13.9385 4

33 Fitted model -13.9719 1 0.0669578 3 0.9955

34 Reduced model -19.6078 1 11.3387 3 0.01003

35

36 AIC: 29.9439

37

38 Log-likelihood Constant 12.347138085809094 

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 50 0.000

46 50.0000 0.0000 0.000 0 50 -0.016

47 250.0000 0.0007 0.033 0 50 -0.182

48 1250.0000 0.0794 3.968 4 50 0.017

49

50 Chi^2 = 0.03 d.f. = 3 P-value = 0.9984

51

52

53 Benchmark Dose Computation

54 Specified effect = 0.1

55 Risk Type = Extra risk 

56 Confidence level = 0.95

57 BMD = 1355.16

58 BMDL = 1016.15

59 BMDU = 3393.6

60

61 Taken together, (1016.15, 3393.6 ) is a 90% two-sided confidence interval for the BMD
G-53

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

G.2.4. Peritoneal Mesothelioma

1 The incidence data for peritoneal mesotheliomas were monotonic non-decreasing 

2 functions of dose; therefore, these data appear to be appropriate for dose-response modeling 

using BMDS. The results of the BMDS modeling for the multistage cancer model for 1st, 2nd 3 , 

and 3rd-degree polynomials are shown in Table G-6. The 1st 4 -degree polynomial was the best 

fitting model based on AIC. The plot (Figure G-5) and model output for the 1st 5 -degree model are 

6 shown below.

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

BMC10

(ppm)

BMCL10

(ppm)

Firsta155.433 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 (1st-degree) for male rat peritoneal 

mesotheliomas.

1 ==================================================================== 

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 ==================================================================== 

9 BMDS_Model_Run 

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 parameters = 0

23 Degree of polynomial = 1

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

 0

 0.2

 0.4

 0.6

 0.8

 1

 0 200 400 600 800 1000 1200 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:31 11/17 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-55

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 Default Initial Parameter Values 

3 Background = 0.0172414

4 Beta(1) = 0.00135351

5

6 Asymptotic Correlation Matrix of Parameter Estimates

7

8 Background Beta(1)

9 Background 1 -0.45

10 Beta(1) -0.45 1

11

12 Parameter Estimates

13 95.0% Wald Confidence Interval

14 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

15 Background 0.033631 * * *

16 Beta(1) 0.00128167 * * *

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 -75.553 4

24 Fitted model -75.7165 2 0.326905 2 0.8492

25 Reduced model -123.008 1 94.9105 3 <.0001

26

27 AIC: 155.433

28

29 Log-likelihood Constant 68.666413125908832 

30

31 Goodness of Fit 

32 Scaled

33 Dose Est._Prob. Expected Observed Size Residual

34 ------------------------------------------------------------------------

35 0.0000 0.0336 1.682 2 50 0.250

36 50.0000 0.0936 4.681 4 50 -0.331

37 250.0000 0.2986 14.928 14 50 -0.287

38 1250.0000 0.8053 40.265 41 50 0.263

39

40 Chi^2 = 0.32 d.f. = 2 P-value = 0.8509

41

42 Benchmark Dose Computation

43 Specified effect = 0.1

44 Risk Type = Extra risk 

45 Confidence level = 0.95

46 BMD = 82.2057

47 BMDL = 64.3808

48 BMDU = 107.497

49

50 Taken together, (64.3808, 107.497) is a 90% two-sided confidence interval for the BMD

G.2.5. Mammary Gland Fibroadenoma

51 The incidence data for mammary gland fibroadenomas were monotonic non-decreasing 

52 functions of dose; therefore, these data appear to be appropriate for dose-response modeling 

using BMDS. The results of the BMDS modeling for the multistage cancer model for 1st, 2nd 53 , 

and 3rd 54 -degree polynomials are shown in Table G-7. Since quadratic and cubic terms of the 

multistage models evaluated resulted in the estimates on the boundary, i.e. equal to 0, the 1st 55 -

56 degree polynomial was selected based on model parsimony. The plot (Figure G-6) and model 

output for the 1st 57 -degree model are shown below.
G-56

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Table G-7. BMDS Multistage cancer 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

BMC10

(ppm)

BMCL10

(ppm)

Firsta86.29 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

aAll model fits were equivalent based on AIC. Selected 1st

-degree model based on parsimony.

1

Figure G-6. Multistage model (1st-degree) for male rat mammary gland 

fibroadenoma.

2 ==================================================================== 

3 MS_COMBO. (Version: 1.4; Date: 10/20/2010) 

4 Input Data File: C:\Documents and 

5 Settings\emclanah\Desktop\BMD_14D_Cancer\Data\New.(d) 

6 Gnuplot Plotting File: C:\Documents and 

7 Settings\emclanah\Desktop\BMD_14D_Cancer\Data\New.plt

8 Wed Nov 17 10:57:55 2010

9 ==================================================================== 

 0

 0.05

 0.1

 0.15

 0.2

 0 200 400 600 800 1000 1200 1400 1600 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:34 11/17 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-57

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 BMDS_Model_Run 

2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

3 The form of the probability function is: 

4 P[response] = background + (1-background)*[1-EXP(-beta1*dose^1)]

5

6 The parameter betas are restricted to be positive

7

8 Dependent variable = EFFECT

9 Independent variable = DOSE

10

11 Total number of observations = 4

12 Total number of records with missing values = 0

13 Total number of parameters in model = 2

14 Total number of specified parameters = 0

15 Degree of polynomial = 1

16

17 Maximum number of iterations = 250

18 Relative Function Convergence has been set to: 1e-008

19 Parameter Convergence has been set to: 1e-008

20

21 Default Initial Parameter Values 

22 Background = 0.0335609

23 Beta(1) = 5.91694e-005

24

25 Asymptotic Correlation Matrix of Parameter Estimates

26

27 Background Beta(1)

28 Background 1 -0.61

29 Beta(1) -0.61 1

30

31 Parameter Estimates

32

33 95.0% Wald Confidence Interval

34 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

35 Background 0.0315836 * * *

36 Beta(1) 6.44224e-005 * * *

37

38 * - Indicates that this value is not calculated.

39

40 

41 Analysis of Deviance Table

42

43 Model Log(likelihood) # Param's Deviance Test d.f. P-value

44 Full model -40.9017 4

45 Fitted model -41.145 2 0.486662 2 0.784

46 Reduced model -42.5964 1 3.3895 3 0.3354

47

48 AIC: 86.29

49

50 Log-likelihood Constant 35.472345543489602 

51

52 Goodness of Fit 

53 Scaled

54 Dose Est._Prob. Expected Observed Size Residual

55 ------------------------------------------------------------------------

56 0.0000 0.0316 1.579 1 50 -0.468

57 50.0000 0.0347 1.735 2 50 0.205

58 250.0000 0.0471 2.353 3 50 0.432

59 1250.0000 0.1065 5.326 5 50 -0.149

60

61 Chi^2 = 0.47 d.f. = 2 P-value = 0.7904

62

63

64 Benchmark Dose Computation

65 Specified effect = 0.1

66 Risk Type = Extra risk 
G-58

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Confidence level = 0.95

2 BMD = 1635.46

3 BMDL = 703.034

4 BMDU = 1.9523e+009

5

6 Taken together, (703.034, 1.9523e+009) is a 90% two-sided confidence interval for the 

7 BMD

G.2.6. Subcutis Fibroma

8 The incidence data for subcutis fibroma were monotonic non-decreasing functions of 

9 dose for the control (0 ppm), low (50 ppm), and mid-dose (250 ppm); however, the incidence 

10 rate at the high dose (1,250 ppm) was lower than observed at the mid-dose. No BMDS model 

11 had reasonable fit to the data without dropping the high dose. The results of the BMDS 

modeling for the multistage cancer model for 1st, 2nd, and 3rd 12 -degree polynomials with the high 

13 dose dropped are shown in Table G-8. Since quadratic and cubic terms of multistage models 

evaluated resulted in the estimates on the boundary, i.e. equal to 0, , the 1st 14 -degree polynomial 

was selected based on model parsimony. The plot (Figure G-7) and model output for the 1st 15 -

16 degree model are shown below. 

Table G-8. BMDS Multistage cancer dose-response modeling results for the 

incidence of subcutis fibromas 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

BMC10

(ppm)

BMCL10

(ppm)

Firsta89.2094 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

aAll model fits were equivalent based on AIC. Selected 1st

-degree model based on parsimony.
G-59

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

Figure G-7. Multistage model (1st-degree) for male rat subcutis fibroma (high 

dose dropped).

1 =================================================================== 

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 ==================================================================== 

9 BMDS_Model_Run 

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 = 3

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

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 50 100 150 200 250 

dose

Multistage Cancer Model with 0.95 Confidence Level

10:56 11/17 2010

BMDL BMD

 

Multistage Cancer

Linear extrapolation
G-60

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 Parameter Convergence has been set to: 1e-008

2

3 Default Initial Parameter Values 

4 Background = 0.0327631

5 Beta(1) = 0.000673665

6

7

8 Asymptotic Correlation Matrix of Parameter Estimates

9

10 Background Beta(1)

11 Background 1 -0.68

12 Beta(1) -0.68 1

13

14 Parameter Estimates

15

16 95.0% Wald Confidence Interval

17 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

18 Background 0.0262054 * * *

19 Beta(1) 0.00074322 * * *

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 -42.4101 3

27 Fitted model -42.6047 2 0.389155 1 0.5327

28 Reduced model -46.5274 1 8.23466 2 0.01629

29

30 AIC: 89.2094

31

32 Log-likelihood Constant 37.900888781466982 

33

34 Goodness of Fit 

35 Scaled

36 Dose Est._Prob. Expected Observed Size Residual

37 ------------------------------------------------------------------------

38 0.0000 0.0262 1.310 1 50 -0.275

39 50.0000 0.0617 3.086 4 50 0.537

40 250.0000 0.1913 9.566 9 50 -0.204

41 Chi^2 = 0.41 d.f. = 1 P-value = 0.5245

42

43

44 Benchmark Dose Computation

45 Specified effect = 0.1

46 Risk Type = Extra risk 

47 Confidence level = 0.95

48 BMD = 141.762

49 BMDL = 81.9117

50 BMDU = 364.364

51

52 Taken together, (81.9117, 364.364) is a 90% two-sided confidence interval for the BMD

G.3. MULTITUMOR ANALYSIS USING BAYESIAN METHODS

53 Given the multiplicity of tumor sites, basing the IUR on one tumor site will 

54 underestimate the carcinogenic potential of 1,4-dioxane. Simply pooling the counts of animals 

55 with one or more tumors (i.e., counts of tumor bearing animals) would tend to underestimate the 

56 overall risk when tumors are independent across sites and ignores potential differences in the 

57 dose-response relationships across the sites (Bogen, 1990; Spurgeon, et al., 1994). NRC (1994)
G-61

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1 also noted that the assumption of independence across tumor types is not likely to produce 

2 substantial error in the risk estimates unless tumors are known to be biologically dependent.

3 Kopylev et al. (2009) describe a Markov Chain Monte Caro (MCMC) computational 

4 approach to calculating the dose associated with a specified composite risk under assumption of 

5 independence of tumors. The current Guidelines for Carcinogen Risk Assessment recommend 

6 calculation of an upper bound to account for uncertainty in the estimate (U.S. EPA, 2005a). For 

7 uncertainty characterization, MCMC methods have the advantage of providing information about 

8 the full distribution of risk and/or benchmark dose, which can be used in generating a confidence 

9 bound. This MCMC approach building on the re-sampling approach recommended by Bogen 

10 (1990), and also provides a distribution of the combined potency across sites.

11 For individual tumor data modeled using the multistage model:

P(d | q) = 1 - exp[-(q0 + q1d + q2d

2 + ... + qkdk

12 )], qi≥0

13 the model for the combined tumor risk is still multistage, with a functional form that has 

14 the sum of stage-specific multistage coefficients as the corresponding multistage coefficient;

Pc(d | q) = 1 - exp[-(qΣ0i + qΣ1id + qΣ2id

2 + ... + qΣkidk

15 )],

16 The resulting equation for fixed extra risk (BMR) is polynomial in dose (when logarithms 

17 of both sides are taken) and can be straightforwardly solved for a combined BMC. Computation 

18 of the confidence bound on combined risk BMC can be accomplished via likelihood methods 

19 (BMDS-MSCOMBO), re-sampling (bootstrap) or Bayesian methods.

20 The MCMC computations were conducted using WinBUGS (Spiegelhalter, et al., 

21 2003)(freeware developed by the MRC Biostatistical Unit, Cambridge, United Kingdom, 

22 available at http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/contents.shtml). 

23 In a Bayesian analysis, the choice of the appropriate prior is important. In the examples 

24 developed by Kopylev et al. (2009), a diffuse (i.e., high variance or low tolerance) Gaussian 

25 prior restricted to be nonnegative was used; such diffuse priors performed reasonably well. 

The mean and the 5th 26 percentile of the posterior distribution of combined BMC provide 

27 estimates of the mean BMC and the lower bound on the BMC (BMCL), respectively, for the 

28 combined tumor risk.

29 The values calculated using this method were: mean BMC10 39.2ppm, and BMCL10

30 31.4. 

G.4. MULTITUMOR ANALYSIS USING BMDS MSCOMBO (BETA)

31 The combined tumor analysis was also performed with beta version of the MSCombo model in 

32 BMDS (Version 2.2beta). The model resulted in similar results to the Bayesian method and 

33 model output is shown below for the combined calculation.

34

35 **** Start of combined BMD and BMDL Calculations.****

36 Combined Log-Likelihood -277.79874987953076 

37 Combined Log-likelihood Constant 246.62591390071873 

38
G-62

DRAFT DELIBERATIVE – DO NOT CITE OR QUOTE

1

2 Benchmark Dose Computation

3 Specified effect = 0.1

4 Risk Type = Extra risk 

5 Confidence level = 0.95

6 BMD = 40.4937

7 BMDL = 32.331

8

9