MODELING BIOMARKER RATIOS WITH GAMMA DISTRIBUTED COMPONENTS

• 成果类型: Article
• 署名作者: Berger, Moritz; Wagner, Michael; Schmid, Matthias
• 署名单位: University of Bonn; University of Bonn; Helmholtz Association; German Center for Neurodegenerative Diseases (DZNE)
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/18-AOAS1207
• 发表日期: 2019
• 页码: 548-572
• 关键词: chronic kidney-disease; amyloid-beta; cholesterol; RISK; individuals; association; isoflavones; dementia; DESIGN; gckd

摘要

We propose a regression model termed extended GB2 model, which is designed to analyze ratios of biomarkers in epidemiological and medical research. Typical examples of biomarker ratios are given by the LDL/HDL cholesterol ratio in cardiovascular research and the amyloid-beta 42/40 ratio in dementia research. Unlike regression modeling with a log-transformed response, which is often used to describe ratio outcomes in observational studies, the extended GB2 model directly links the expectation of the untransformed biomarker ratio to a set of covariates. This strategy allows for a simple interpretation of the predictor-response relationships in terms of multiplicative increases/decreases of the expected outcome, similar to Poisson and Cox regression. In the theoretical part of the paper, we derive the log-likelihood of the proposed model, analyze its properties, and provide details on confidence intervals and hypothesis testing. We will also present the results of a simulation study demonstrating the robustness of the proposed modeling approach against model misspecification. The usefulness of the method is demonstrated by two applications on the aforementioned LDL/HDL cholesterol and amyloid-beta 42/40 ratios. For this, we analyze data from a cohort study on kidney disease and from a large observational database on neurodegenerative diseases.