Covariate-adjusted log-rank test: guaranteed efficiency gain and universal applicability
Covariate-adjusted log-rank test: guaranteed efficiency gain and universal applicability
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DOI：
10.1093/biomet/asad045
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发表时间：
2023-09-10
期刊：
影响因子：
2.7
通讯作者：
Yi，Yanyao
中科院分区：
文献类型：
--
作者：
Ye，Ting;Shao，Jun;Yi，Yanyao
对于使用来自应用协变量自适应随机化的临床试验的右删失至事件时间数据的治疗效应的对数秩型检验，考虑非参数协变量调整。我们提出的协变量调整对数秩检验有一个简单的明确的公式和保证效率增益比未调整的测试。我们还表明，我们提出的测试实现了普遍适用性的意义上说，相同的测试公式可以普遍适用于简单的随机化和所有常用的协变量自适应随机化方案，如分层置换块和Pocock-Simon最小化，这不是一个属性所享有的未调整的对数秩检验。我们的方法是支持新的渐近理论和经验结果的I型误差和功率的测试。
Nonparametric covariate adjustment is considered for log-rank-type tests of the treatment effect with right-censored time-to-event data from clinical trials applying covariate-adaptive randomization. Our proposed covariate-adjusted log-rank test has a simple explicit formula and a guaranteed efficiency gain over the unadjusted test. We also show that our proposed test achieves universal applicability in the sense that the same formula of test can be universally applied to simple randomization and all commonly used covariate-adaptive randomization schemes such as the stratified permuted block and the Pocock–Simon minimization, which is not a property enjoyed by the unadjusted log-rank test. Our method is supported by novel asymptotic theory and empirical results for Type-I error and power of tests.