Section for Biostatistics, Department of Public Health, Aarhus University, Aarhus, Denmark.
Stat Med. 2023 Dec 30;42(30):5723-5735. doi: 10.1002/sim.9937. Epub 2023 Oct 28.
The win ratio has become a popular method for comparing multiple event data between two groups in clinical cohort studies. The win ratio compares the event data in prioritized order, where the first prioritized event is death and a typical example for the second prioritized event is hospitalization. Literature is sparse on inference for win and loss parameters, including the win ratio, for censored event data. Inference for two prioritized censored event times has been developed for independent right-censoring. Many clinical studies include recurrent event data such as hospitalizations. In this article, we suggest inference for win-loss parameters for death and a recurrent event outcome under independent right-censoring. The small sample properties of the proposed method are studied in a simulation study showing that the variance formula is accurate even for small samples. The method is applied on a data set from a randomized clinical trial.
胜率已成为临床队列研究中比较两组多项事件数据的一种常用方法。胜率按优先级比较事件数据,优先级最高的事件是死亡,优先级次高的事件通常是住院。关于删失事件数据的胜率和损失参数的推断文献很少。对于独立右删失,已经开发出了用于两个优先级删失事件时间的推断方法。许多临床研究包括住院等复发性事件数据。在本文中,我们建议在独立右删失下对死亡和复发性事件结局的胜负参数进行推断。模拟研究研究了所提出方法的小样本特性,结果表明,即使对于小样本,方差公式也是准确的。该方法应用于一项随机临床试验数据集。