将膳食暴露与生物标志物测量整合到病因学模型中的贝叶斯分层框架

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

Journal of the Royal Statistical Society. Series C: Applied Statistics · 2025
被引 2
ABS 3

中文导读

本研究开发了一个贝叶斯分层模型,整合膳食和血清测量数据,分析维生素B6和叶酸与肾癌、肺癌风险的关系,发现血清水平有保护作用但效应大小不确定。

Abstract

Abstract 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 study were integrated in a Bayesian framework to explore the data measurement error structure and relate dietary exposures to cancer risk. A Bayesian hierarchical 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 these data suggests a protective effect but with substantial uncertainty in the effect size.

贝叶斯统计营养流行病学癌症病因学生物标志物