School of Mathematics, Capital Normal University, Beijing, China.
School of Statistics and Mathematics, Shanghai Lixin University of Accounting and Finance, Shanghai, China.
Biometrics. 2021 Mar;77(1):150-161. doi: 10.1111/biom.13260. Epub 2020 Mar 28.
In many medical studies, markers are contingent on recurrent events and the cumulative markers are usually of interest. However, the recurrent event process is often interrupted by a dependent terminal event, such as death. In this article, we propose a joint modeling approach for analyzing marker data with informative recurrent and terminal events. This approach introduces a shared frailty to specify the explicit dependence structure among the markers, the recurrent, and terminal events. Estimation procedures are developed for the model parameters and the degree of dependence, and a prediction of the covariate-specific cumulative markers is provided. The finite sample performance of the proposed estimators is examined through simulation studies. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is illustrated.
在许多医学研究中，标志物取决于复发性事件，累积标志物通常是研究的重点。然而，复发性事件过程常常被一个相关的终末事件（如死亡）所打断。在本文中，我们提出了一种联合建模方法，用于分析具有信息性复发性和终末事件的标志物数据。该方法引入了一个共享的 frailty，以指定标志物、复发性事件和终末事件之间的显式依赖结构。为模型参数和依赖程度开发了估计程序，并提供了协变量特定累积标志物的预测。通过模拟研究检验了所提出估计量的有限样本性能。通过来自弗吉尼亚大学卫生系统的慢性心力衰竭患者的医疗成本研究的应用来说明。
