Sample selection and validity of exposure-disease association estimates in cohort studies

Overview & Synopsis

BACKGROUND: Participants in cohort studies are frequently selected from restricted source populations. It has been recognised that such restriction may affect the study validity. METHODS: We assessed the bias that may arise when analyses involve data from cohorts based on restricted source populations, surprisingly an area little studied in quantitative terms. We used Monte Carlo simulations based on a setting where the exposure and one risk factor for the outcome, which are not associated in the general population, influence selection into the cohort. All the parameters involved in the simulations (i.e. the prevalence and effects of exposure and risk factor on both the selection and outcome process, the selection prevalence, the baseline outcome incidence rate, and the sample size) were allowed to vary to reflect real life settings. RESULTS: The simulations show that when the exposure and risk factor are strongly associated with selection (odds ratios of 4 or 0.25) and the unmeasured risk factor is associated with a disease hazard ratio of 4, the bias in the estimated log odds ratio for the exposure-disease association is ± 0.15. When these associations decrease to values more commonly seen in epidemiological studies (e.g., odds and hazard ratios of 2 or 0.5), the bias in the log odds ratio drops to just ± 0.02. CONCLUSIONS: Using a restricted source population for a cohort study will, under a range of sensible scenarios, produce only relatively weak bias in estimates of the exposure-disease associations.