Most randomized controlled trials with a time-to-event outcome are designed and analyzed assuming proportional hazards of the treatment effect. The sample-size calculation is based on a log-rank test or the equivalent Cox test. Nonproportional hazards are seen increasingly in trials and are recognized as a potential threat to the power of the log-rank test. To address the issue, Royston and Parmar (2016, BMC Medical Research Methodology 16: 16) devised a new "combined test" of the global null hypothesis of identical survival curves in each trial arm. The test, which combines the conventional Cox test with a new formulation, is based on the maximal standardized difference in restricted mean survival time (rmst) between the arms. The test statistic is based on evaluations of rmst over several preselected time points. The combined test involves the minimum p-value across the Cox and rmst-based tests, appropriately standardized to have the correct null distribution. In this article, I outline the combined test and introduce a command, stctest, that implements the combined test. I point the way to additional tools currently under development for power and sample-size calculation for the combined test.

中文翻译：

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临床试验中广义治疗效果的综合测试，具有事件发生时间结果。

大多数具有事件发生时间结果的随机对照试验都是在假设治疗效果的比例风险的情况下设计和分析的。样本量计算基于对数秩检验或等效的 Cox 检验。非比例风险越来越多地出现在试验中，并被认为是对数秩检验效力的潜在威胁。为了解决这个问题，Royston 和 Parmar (2016, BMC Medical Research Methodology 16:16) 设计了一个新的“组合检验”，对每个试验组中相同生存曲线的全局零假设进行检验。该测试结合了传统的 Cox 测试和新的配方，基于手臂之间受限平均生存时间 (rmst) 的最大标准化差异。测试统计基于对几个预选时间点的 rmst 的评估。组合检验涉及 Cox 和基于 rmst 检验的最小 p 值，适当标准化以具有正确的零分布。在本文中，我概述了组合测试并介绍了实现组合测试的命令 stctest。我指出了目前正在开发的用于组合测试的功效和样本大小计算的其他工具。