1. Accommodating Measurements Below a Limit of Detection: A Novel Application of Cox Regression
- Author
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Irva Hertz-Picciotto, Clarice R. Weinberg, Kaushik Annam, Lindsey A. Ho, Brenda W. Gillespie, Todd A. Jusko, Barry I. Graubard, Gregg E. Dinse, and Frederick W. Miller
- Subjects
Male ,Data Interpretation ,Polychlorinated Dibenzodioxins ,Practice of Epidemiology ,Epidemiology ,Developmental Disabilities ,hazard identification ,Medical and Health Sciences ,8-tetrachlorodibenzo-p-dioxin ,Mathematical Sciences ,Cohort Studies ,Toxicology ,Theoretical ,Models ,Limit of Detection ,Statistics ,Odds Ratio ,Medicine ,Prospective Studies ,nondetects ,Hazard ratio ,Linear model ,Confounding Factors, Epidemiologic ,Environmental exposure ,Statistical ,proportional hazards ,Polychlorinated Biphenyls ,4′-trichlorobiphenyl ,Data Interpretation, Statistical ,4-trichlorobiphenyl ,Environmental Pollutants ,Female ,Psychomotor disorder ,Analyte ,Odds ,Sex Factors ,Humans ,Computer Simulation ,Proportional Hazards Models ,Epidemiologic ,business.industry ,Proportional hazards model ,Prevention ,Infant ,National Health and Nutrition Examination Survey ,Environmental Exposure ,Odds ratio ,Models, Theoretical ,Health Surveys ,Confounding Factors ,Cross-Sectional Studies ,Logistic Models ,Case-Control Studies ,Epidemiologic Research Design ,Linear Models ,Psychomotor Disorders ,business ,Biomarkers - Abstract
In environmental epidemiology, measurements of exposure biomarkers often fall below the assay's limit of detection. Existing methods for handling this problem, including deletion, substitution, parametric regression, and multiple imputation, can perform poorly if the proportion of "nondetects" is high or parametric models are mis-specified. We propose an approach that treats the measured analyte as the modeled outcome, implying a role reversal when the analyte is a putative cause of a health outcome. Following a scale reversal as well, our approach uses Cox regression to model the analyte, with confounder adjustment. The method makes full use of quantifiable analyte measures, while appropriately treating nondetects as censored. Under the proportional hazards assumption, the hazard ratio for a binary health outcome is interpretable as an adjusted odds ratio: the odds for the outcome at any particular analyte concentration divided by the odds given a lower concentration. Our approach is broadly applicable to cohort studies, case-control studies (frequency matched or not), and cross-sectional studies conducted to identify determinants of exposure. We illustrate the method with cross-sectional survey data to assess sex as a determinant of 2,3,7,8-tetrachlorodibenzo-p-dioxin concentration and with prospective cohort data to assess the association between 2,4,4'-trichlorobiphenyl exposure and psychomotor development.
- Published
- 2014
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