Recall bias in population-based case-control studies of ovarian cancer and genital talc use: potential impact and quantitative bias analysis

Introduction Quantitative bias analysis (QBA) methods have been developed, with growing applications to epidemiological studies. Bayesian QBA methods may be superior in effectively using evidence-based priors and study data to displace fixed-value assumptions, and in characterizing distributions of adjusted point estimates and associated uncertainty. Methods We applied simple QBA and Bayesian QBA methods to population-based case-control studies on ovarian cancer and genital talcum powder use. Our hypothesis was that differential misclassification of self-reported historical talcum powder use led to statistically significant associations in several of these studies. Simple bias analysis results covering ranges of published exposure sensitivity and specificity estimates for genital talc use were generated. Bayesian QBA models generated posterior means and 95% credible level intervals (CrI’s) of bias-adjusted odds ratio (OR), sensitivities and specificities of controls and cases, respectively, using pooled case-control study data. Results The mean Bayesian posterior OR was 1.08 (95% CrI 0.67–1.77), mean case and control sensitivities were 0.87 and 0.78 and mean case and control specificities were 0.86 and 0.90, respectively. Model diagnostics indicated good fit. Conclusion Upon adjusting only for hypothesized differential exposure misclassification bias, the association between ovarian cancer and genital talc use was attenuated relative to the unadjusted one. While other potential sources of bias may be operating within this body of studies, exposure reporting bias likely accounts for the statistically significant ORs reported in the individual case-control studies.