病例队列研究设计中相对危险度的估计及其应用

目的:系统介绍病例队列研究设计的基本原理，以及风险比（ HR）的常用估计方法及其应用。 方法:首先，介绍病例队列研究设计的基本原理；其次，对Prentice法、Self-Prentice法和Barlow法加权Cox比例风险回归模型进行描述和说明；最后，以上海市女性健康队列研究为例，分析全队列数据与...

Statistical methods for relative risk estimation and applications in case-cohort study

Objective To systematically introduce the design of case-cohort study and the statistical methods of relative risk estimation and their application in the design. Methods First, we introduced the basic principles of case-cohort study design. Secondly, Prentice''s method, Self-Prentice method and Barlow method were described in the weighted Cox proportional hazard regression models in detail, finally, the data from the Shanghai Women''s Health Study were used as an example to analyze the association between obesity and liver cancer incidence in the full cohort and case-cohort sample, and the results of parameters from each method were compared. Results Significant association was observed between obesity and risk for liver cancer incidence in women in both the full cohort and the case-cohort sample. In the Cox proportional hazard regression model, the partial regression coefficients of the full cohort and the case-cohort sample fluctuated with the adjustment of confounding factors, but the hazard ratio estimates of them were close. There was a difference in the standard error of the partial regression coefficient between the full cohort and the case-cohort sample. The standard error of the partial regression coefficient of the case-cohort sample was larger than that of the full cohort, resulting in a wider 95% confidence interval of the relative risk. In the weighted Cox proportional hazard regression model, the standard error of the partial regression coefficient of Prentice''s method was closer to the parameter estimates from full cohort than Self-Prentice method and Barlow method, and the 95% confidence interval of hazard ratio was closer to that of the full cohort. Conclusions Case-cohort design could yield parameter results closer to the full cohort by collecting and analyzing data from sub-cohort members and patients with the disease, and reduce sample size and improve research efficiency. The results suggested that Prentice''s method would be preferred in case-cohort design.