Longitudinal clinical trials are often designed to compare treatments on the basis of multiple outcomes. For example in the case of cardiac trials, the outcomes of interest include mortality as well as cardiac events and hospitalization. For a COVID-19 trial, the outcomes of interest include mortality, time on ventilator, and time in hospital. Earlier work by these authors proposed a non-parametric test based on a composite of multiple endpoints referred to as the Finkelstein-Schoenfeld (FS) test (Finkelstein and Schoenfeld. Stat Med. 1999;18(11):1341–1354.). More recently, an estimate of the treatment comparison based on multiple endpoints (related to the FS test) was proposed (Pocock et al. Eur Heart J. 2011;33(2):176–182.). This estimate, which summarized the ratio of the number of patients who fared better vs worse on the experimental arm was coined the win ratio. The aim of this article is to provide guidance in the design of a trial that will use the FS test or the win ratio. The issues that will be considered are the sample size, sequential monitoring, and adaptive designs.

中文翻译：

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基于复合终点设计纵向临床试验：样本量、监测和适应

纵向临床试验通常旨在根据多种结果比较治疗。例如，在心脏试验的情况下，感兴趣的结果包括死亡率以及心脏事件和住院率。对于 COVID-19 试验，感兴趣的结果包括死亡率、使用呼吸机的时间和住院时间。这些作者的早期工作提出了一种基于多个端点的组合的非参数检验，称为 Finkelstein-Schoenfeld ( FS ) 检验（Finkelstein 和 Schoenfeld. Stat Med . 1999;18(11):1341–1354.）。最近，提出了基于多个终点（与 FS 测试相关）的治疗比较估计（Pocock 等人，Eur Heart J. 2011;33(2):176–182.)。这一估计总结了实验组中表现较好与较差的患者人数之比，被称为胜率。本文的目的是为使用 FS 测试或胜率的试验设计提供指导。将要考虑的问题是样本量、序贯监测和适应性设计。