A Bayesian hierarchical framework to integrate dietary exposure and biomarker measurements into aetiological models

In this study, dietary and serum measurements of vitamin-B6 and folate from two nested case-control studies within the European Prospective Investigation into Cancer and Nutrition (EPIC) study were integrated in a Bayesian framework to explore the data measurement error structure and relate dietary exposures to cancer risk. A Bayesian hier-archical model was developed, including: an exposure model, to define the unknown true intake distribution; a measurement model, to relate true intake to observed assessments; and a disease model, to estimate exposure/cancer relationships. Serum and plasma levels of vitamin-B6 and folate were inversely associated with kidney and lung cancer risk, while dietary assessments of these vitamins were not associated with kidney and lung cancer risk. The Bayesian synthesis of this data suggests a protective effect but with substantial uncertainty in the effect size.