Quantitative estimation and prediction of human cancer risks:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Lyon
IARC
1999
|
| Schriftenreihe: | International Agency for Research on Cancer: IARC scientific publications
131 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIII, 322 S. graph. Darst. |
| ISBN: | 9283221311 |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text | Foreword xi
Contributors xii
Acknowledgements xiii
Chapter 1. Quantitative estimation and prediction of human cancer risk: its history
and role in cancer prevention 1
A.J. McMichael and A. Woodward
1.1 Introduction 1
1.2 Historical background 2
1.3 Definitions of terms and concepts 3
1.4 Regulation and control of cancer risks 5
1.5 Risk prediction 7
1.6 Conclusions 8
References 9
Chapter 2. Quantitative estimation and prediction of cancer risk:
review of existing activities 11
L. Zeise, £ Cardis, K. Hemminki and M. Schwarz
2.1 Introduction 11
2.2 QEP by international bodies using standardized approaches 12
2.2.1 World Health Organization 12
2.2.1.1 Drinking water 12
2.2.1.2 Ambient air 13
2.2.1.3 Food residues and additives 14
2.2.1.4 General environmental evaluations 15
2.2.1.5 Developments in the practice of QEP at WHO 16
2.2.2 International bodies that assess radiation risks 16
2.2.3 Other international bodies 17
2.3 QEP by national institutions using standardized approaches 18
2.3.1 Netherlands 18
2.3.2 USA 19
2.3.2.1 Default risk prediction 20
2.3.2.2 UseofQEPs 21
2.3.3 Canada 22
2.3.4 Norway 24
2.3.5 United Kingdom 24
2.3.6 Germany 25
2.3.7 Denmark 25
2.4 Standard approaches to QEP for carcinogens 25
2.5 Attempts to improve QEP 28
2.5.1 Biologically based approaches 28
2.5.1.1 Integrated modelling of physiology, pharmacokinetics, pharmacodynamics and cell
dynamics: 2,3,7,8 tetrachlorodibenzo p dioxin (TCDD) 28
v
Quantitative Estimation and Prediction of Human Cancer Risks
2.5.1.2 Mechanistic modelling assuming cancer induced by chronic irritation: saccharin 29
2.5.1.3 Use of information on DNA cross links as a measure of dose: formaldehyde 30
2.5.1.4 Uncertainty and variability analysis in PBPK models: methylene chloride and
perchloroethylene 30
2.5.2 Meta analyses of epidemiological data: ionizing radiation and environmental
tobacco smoke 33
2.5.2.1 Ionizing radiation 33
2.5.2.2 Environmental tobacco smoke 34
2.5.3 Experimental and epidemiological efforts to improve estimates of benzene cancer potency 35
2.5.3.1 Modelling of benzene pharmacokinetics 36
2.5.3.2 Cohort exposure reconstruction and related dose response evaluations 37
2.5.4 Predictions of cancer potency without cancer bioassay or epidemiological data 38
2.5.4.1 Ethylene cancer potency inferred from metabolite ethylene oxide 38
2.5.4.2 Use of toxicity equivalency factors: complex mixtures 39
2.6 Conclusions 40
References 42
Chapter 3. Principles of the epidemiological approach to QEP 61
S. Moolgavkar, H. MellerandA. Woodward
3.1 Introduction 61
3.2 Measures of disease frequency and measures of effect 62
3.3 Confounding 64
3.4 Types of epidemiological study 64
3.4.1 Cohort studies 64
3.4.2 Case control studies 66
3.4.3 Ecological studies 67
3.5 Data analysis 68
3.6 Combined and meta analyses 69
3.7 Conclusions 71
References 71
Chapter 4. Measurement of exposure and outcome in epidemiological studies
used for quantitative estimation and prediction of risk 75
B. Armstrong and P. Boffetta
4.1 Introduction 75
4.2 Making the right exposure measurements 76
4.2.1 Nature of exposure measurements 76
4.2.2 Measurement of dose 76
4.2.3 Measurement of variation in exposure with time 77
4.3 Effects of exposure measurement error on QEP 79
4.3.1 Effect of exposure measurement error on the dose response relationship 79
4.3.1.1 Analytical epidemiological studies 80
4.3.1.2 Ecological studies 81
4.3.2 Measurement error in confounding 81
4.3.2.1 Analytical epidemiological studies 81
4.3.2.2 Ecological studies 81
4.3.3 Example of effects of exposure measurement error on QEP 81
4.3.4 Conclusions 82
vi
Contents
4.4 Prevention of exposure measurement error 82
4.4.1 Quality in the design of measurement instruments 82
4.4.2 Quality control in making and using measurements 84
4.4.3 Other factors 85
4.5 Control of the effects of exposure measurement error 86
4.5.1 Multiple measures of exposure 86
4.5.2 Adjustment of study results for the effects of measurement error 87
4.5.3 Control of a covariate related to measurement error 89
4.5.4 Resources for the control of exposure measurement error 90
4.6 Error in the measurement of outcome 90
4.6.1 Death from cancer 90
4.6.2 Incidence of cancer 91
4.6.3 Preneoplastic lesions 92
4.6.4 Molecular markers of early carcinogenic effect 92
4.6.5 Sources, measurement and prevention of error in the measurement of outcome 93
4.6.6 Effect of error in measurement of outcome on the dose response relationship 96
4.7 Conclusions 97
References 97
Chapter 5. Long and medium term carcinogenicity studies in animals and
short term genotoxicity tests 103
V. Feron, M. Schwarz, K. Hemminki and D. Krewski
5.1 General principles 103
5.2 Design and analysis of cancer bloassays 104
5.2.1 Long term studies 104
5.2.1.1 Design and conduct 104
5.2.1.2 Statistical analysis 107
5.2.2 Medium term studies 1°8
5.2.2.1 Mouse skin 109
5.2.2.2 Liver 110
5.2.2.3 Other organs 112
5.3 Transgenic animals 114
5.4 Useofbiomarkers 116
5.5 Short term tests i17
5.6 Conclusions 118
References 119
Chapter 6. Empirical approaches to risk estimation and prediction 131
D. Krewski, E. Cardis, L Zeise and V. Feron
6.1 Introduction 131
62 Modelling epidemiologlcal data 132
6 2.1 Cohort studies 133
6 2.2 Case control studies 136
6.2.3 Generalized linear models 137
6 2.4 Choice of model form 137
6 2.5 Other measures of risk 139
63 Modelling toxicological data 140
6.3.1 Quantal response models 140
uii
Quantitative Estimation and Prediction of Human Cancer Risks
6.3.2 Models of time to response . 142
6.4 Patterns of exposure and risk 145
6.5 Carcinogenic potency 148
6.5.1 TheTDs,, 148
6.5.2 Variation in carcinogenic potency 150
6.5.3 Correlation between TDM and other measures of toxicity 151
6.5.4 Numerical ranking systems 152
6.6 Joint exposures and carcinogenic mixtures 153
6.6.1 Modelling the risk of joint exposures 154
6.6.2 Theoretical predictions of the risks of joint exposures 155
6.6.3 Empirical studies of the risks of joint exposures 156
6.6.4 Modelling joint exposures 157
6.7 Risk prediction 158
6.7.1 Extrapolation from high to low doses 158
6.7.2 Interspecies extrapolation 159
6.8 Variability, uncertainty and sensitivity analyses 161
6.8.1 Sources and characterizations of variability 162
6.8.2 Sources and characterizations of uncertainty 163
6.8.3 Sensitivity analysis 164
6.9 Summary and conclusions . 164
References 167
Chapter 7. Mechanisms of carcinogenesis and biologically based models for
estimation and prediction of risk 179
S. Moolgavkar, D. Krewski and M. Schwarz
7.1 Introduction 179
7.2 Mechanisms of carcinogenesis 180
7.2.1 Introduction 180
7.2.2 Oncogenes and tumour suppressor genes 180
7.2.3 Proliferation and terminal differentiation of cells 182
7.2.4 Action of environmental agents 183
7.2.4.1 Metabolic factors 183
7.2.4.2 DNAbinding 184
7.2.4.3 Mutations in critical genes 184
7.2.4.4 Cell proliferation 185
7.2.5 Classification of carcinogenic agents 186
7.3 Interindivldual variation 187
7.3.1 Genetic predisposition 187
7.3.2 Interindividual and interspecies variation in carcinogen metabolism 187
7.3.3 Interindividual variation in DNA repair 189
7.4 Interspecies variation 190
7.5 Biologically based dose response models 190
7.5.1 Introduction 190
7.5.2 The Armitage Doll multistage model 193
7.5.3 The two mutation model 196
7.5.4 The hazard function: analysis of incidence data 198
7.5.5 Radon and lung cancer in rats 199
7.5.6 Reanalysis of the Colorado Plateau uranium miners data 200
7.5.7 Analysis of intermediate lesions 201
viii
Contents
7.5.8 Rodent hepatocarcinogenesis 202
7.5.9 Initiation promotion in mouse skin 204
7.5.10 Joint analyses of premalignant and malignant lesions 205
7.5.11 Limitations of biologically based models 205
7.5.12 Data requirements 206
7.6 Pharmacokinetic modelling 207
7.6.1 Development of a PBPK model 208
7.6.1.1 Mathematical description of a PBPK model 208
7.6.1.2 Selection of model compartments 209
7.6.2 Determination of physiological, biochemical and metabolic parameters 210
7.6.2.1 Physiological parameters 210
7.6.2.2 Partition coefficients 210
7.6.2.3 Metabolic parameters 211
7.6.3 Tissue dosimetry 211
7.6.4 Applications 212
7.6.5 Uncertainty, variability and sensitivity analyses 212
7.6.6 Summary and conclusions 213
7.7 Receptor binding models 213
7.8 Summary and conclusions 215
APPENDIX
A.I The Armitage Doll model 217
A.2 The two mutation model 217
A.2.1 The hazard function 217
A.2.2 Number and size distribution of intermediate foci 219
References 221
Chapter 8. Review of specific examples of QEP 239
£ Cardis, L. Zeise, M. Schwarz and S. Moolgavkar
8.1 Introduction 239
8.2 Radon and lung cancer 240
8.2.1 Introduction 240
8.2.2 Sources of data 240
8.2.2.1 Occupational epidemiological studies 240
8.2.2.2 Animal studies 244
8.2.2.3 Residential radon studies 244
8.2.2.4 Mechanistic studies 247
8.2.2.5 Cofactors and effect modifiers 248
8.2.2.6 Lung dosimetry 249
8.2.3 Empirical approach to QEP 249
8.2.3.1 BEIRIV 249
8.2.3.2 Joint analyses of 11 studies on miners 250
8.2.4 Mechanistic modelling 252
8.2.5 Comparison of QEP results 256
8 2.6 Remaining uncertainties, needs for the future 256
8.3 Aflatoxins and liver cancer 257
8 3.1 Introduction 257
8.3.2 Epidemiological studies 257
83.2.1 Correlation studies 257
8.3.2.2 Case control studies 260
ix
Quantitative Estimation and Prediction of Human Cancer Risks
8.3.2.3 Cohort studies 260
8.3.3 Experimental data 264
8.3.3.1 Animal bioassay 264
8.3.3.2 Pharmacokinetics 264
8.3.3.3 DNA adducts 265
8.3.3.4 Target gene 266
8.3.3.5 Animal models of aflatoxin and HBV interaction 267
8.3.4 Review of risk assessments 267
8.3.4.1 Assessments based on the correlation studies . 269
8.3.4.2 Analyses based on the Guangxi, China cohort data 269
8.3.5 Discussion 273
8.3.5.1 Reliability of exposure estimates in epidemiological studies 273
8.3.5.2 Impact of hepatitis B virus on aflatoxin risk 273
8.3.5.3 Genetically determined differences in human susceptibility 274
8.3.5.4 Shape of the dose response curve 275
8.3.5.5 Impact of background exposures 275
8.3.6 Research needs 275
8.4 2,3,7,8 Tetrachlorodibenzo partHlioxin (TCDD) 276
8.4.1 Introduction 276
8.4.2 Experimental data 276
8.4.2.1 Animal bioassay 276
8.4.2.2. Pharmacokinetic data . 278
8.4.2.3 Initiation promotion studies 278
8.4.2.4 Short term tests 279
8.4.2.5 Mechanistic aspects of TCDD action 279
8.4.3 Epidemiological studies 281
8.4.4 Risk assessment 283
8.4.5 Conclusions 284
References 284
Chapter 9. Future perspectives, unresolved issues and research needs 305
S. Moolgavkar, A. Woodward, D. Krewski, £ Cardis and L Zeise
9.1 Introduction .305
9.2 An example: the case of dioxin (TCDD) 305
9.3 Future perspectives and research needs in epidemiology 306
9.3.1 Genetic and environmental factors in cancer epidemiology 306
9.3.2 Exposure/dose assessment 307
9.3.3 Biomarkers of exposure and surrogate end points 308
9.3.4 Interindividual variation in susceptibility to carcinogen exposure 309
9.4 Future perspectives and research needs in toxicological studies 311
9.4.1 Intermediate lesions 311
9.4.2 Cell proliferation kinetics 311
9.4.3 Statistical considerations 312
9.5 Future perspectives and research needs for biologically based models of carcinogenesis 313
9.6 The bioassay 317
9.7 Conclusions 317
References 318
x
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| indexdate | 2024-07-09T18:31:41Z |
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| isbn | 9283221311 |
| language | English |
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| series | International Agency for Research on Cancer: IARC scientific publications |
| series2 | International Agency for Research on Cancer: IARC scientific publications |
| spelling | Quantitative estimation and prediction of human cancer risks ed. by S. Moolgavkar ... Lyon IARC 1999 XIII, 322 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier International Agency for Research on Cancer: IARC scientific publications 131 Modell (DE-588)4039798-1 gnd rswk-swf Krebsrisiko (DE-588)4165566-7 gnd rswk-swf Grenzwert (DE-588)4129627-8 gnd rswk-swf Prognose (DE-588)4047390-9 gnd rswk-swf Umweltchemikalie (DE-588)4117281-4 gnd rswk-swf Carcinogen (DE-588)4032909-4 gnd rswk-swf Risikoanalyse (DE-588)4137042-9 gnd rswk-swf Carcinogenität (DE-588)4206051-5 gnd rswk-swf Quantitative Methode (DE-588)4232139-6 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Krebsrisiko (DE-588)4165566-7 s Prognose (DE-588)4047390-9 s DE-604 Umweltchemikalie (DE-588)4117281-4 s Carcinogenität (DE-588)4206051-5 s Risikoanalyse (DE-588)4137042-9 s Quantitative Methode (DE-588)4232139-6 s Carcinogen (DE-588)4032909-4 s Grenzwert (DE-588)4129627-8 s Modell (DE-588)4039798-1 s Moolgavkar, Suresh H. Sonstige oth International Agency for Research on Cancer: IARC scientific publications 131 (DE-604)BV000002423 131 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008612584&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Quantitative estimation and prediction of human cancer risks International Agency for Research on Cancer: IARC scientific publications Modell (DE-588)4039798-1 gnd Krebsrisiko (DE-588)4165566-7 gnd Grenzwert (DE-588)4129627-8 gnd Prognose (DE-588)4047390-9 gnd Umweltchemikalie (DE-588)4117281-4 gnd Carcinogen (DE-588)4032909-4 gnd Risikoanalyse (DE-588)4137042-9 gnd Carcinogenität (DE-588)4206051-5 gnd Quantitative Methode (DE-588)4232139-6 gnd |
| subject_GND | (DE-588)4039798-1 (DE-588)4165566-7 (DE-588)4129627-8 (DE-588)4047390-9 (DE-588)4117281-4 (DE-588)4032909-4 (DE-588)4137042-9 (DE-588)4206051-5 (DE-588)4232139-6 (DE-588)4143413-4 |
| title | Quantitative estimation and prediction of human cancer risks |
| title_auth | Quantitative estimation and prediction of human cancer risks |
| title_exact_search | Quantitative estimation and prediction of human cancer risks |
| title_full | Quantitative estimation and prediction of human cancer risks ed. by S. Moolgavkar ... |
| title_fullStr | Quantitative estimation and prediction of human cancer risks ed. by S. Moolgavkar ... |
| title_full_unstemmed | Quantitative estimation and prediction of human cancer risks ed. by S. Moolgavkar ... |
| title_short | Quantitative estimation and prediction of human cancer risks |
| title_sort | quantitative estimation and prediction of human cancer risks |
| topic | Modell (DE-588)4039798-1 gnd Krebsrisiko (DE-588)4165566-7 gnd Grenzwert (DE-588)4129627-8 gnd Prognose (DE-588)4047390-9 gnd Umweltchemikalie (DE-588)4117281-4 gnd Carcinogen (DE-588)4032909-4 gnd Risikoanalyse (DE-588)4137042-9 gnd Carcinogenität (DE-588)4206051-5 gnd Quantitative Methode (DE-588)4232139-6 gnd |
| topic_facet | Modell Krebsrisiko Grenzwert Prognose Umweltchemikalie Carcinogen Risikoanalyse Carcinogenität Quantitative Methode Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008612584&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000002423 |
| work_keys_str_mv | AT moolgavkarsureshh quantitativeestimationandpredictionofhumancancerrisks |