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Modeling epidemiologic studies of occupational cohorts for the quantitative assessment of carcinogenic hazards
Author(s) -
Stayner Leslie,
Smith Randy,
Bailer A. John,
Luebeck E. Georg,
Moolgavkar Suresh H.
Publication year - 1995
Publication title -
american journal of industrial medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.7
H-Index - 104
eISSN - 1097-0274
pISSN - 0271-3586
DOI - 10.1002/ajim.4700270202
Subject(s) - medicine , poisson regression , risk assessment , environmental health , proportional hazards model , exposure assessment , regression analysis , risk analysis (engineering) , statistics , population , surgery , computer science , computer security , mathematics
Epidemiologic studies of occupational cohorts have played a major role in the quantitative assessment of risks associated with several carcinogenic hazards and are likely to play an increasingly important role in this area. Relatively little attention has been given in either the epidemiologic or the risk assessment literature to the development of appropriate methods for modeling epidemiologic data for quantitative risk assessment (QRA). The purpose of this paper is to review currently available methods for modeling epidemiologic data for risk assessment. The focus of this paper is on methods for use with retrospective cohort mortality studies of occupational groups for estimating cancer risk, since these are the data most commonly used when epidemiologic information is used for QRA. Both empirical (e.g., Poisson regression and Cox proportionate hazards model) and biologic (e.g., two‐stage models) models are considered. Analyses of a study of lung cancer among workers exposed to cadmium are used to illustrate these modeling methods. Based on this example it is demonstrated that the selection of a particular model may have a large influence on the resulting estimates of risk.