集体测序平台试验中虚假发现率的在线控制 (Online control of the False Discovery Rate in group-sequential platform trials)

When testing multiple hypotheses, a suitable error rate should be controlled even in exploratory trials. Conventional methods to control the False Discovery Rate (FDR) assume that all p-values are available at the time point of test decision. In platform trials, however, treatment arms enter and leave the trial at any time during its conduct. Therefore, the number of treatments and hypothesis tests is not fixed in advance and hypotheses are not tested at once, but sequentially. Recently, for such a setting the concept of online control of the FDR was introduced. We investigate the LOND procedure to control the online FDR in platform trials and propose an extension to allow for interim analyses with the option of early stopping for efficacy or futility for individual hypotheses. The power depends sensitively on the prior distribution of effect sizes, e.g., whether true alternatives are uniformly distributed over time or not. We consider the choice of design parameters for the LOND procedure to maximize the overall power and compare the OBrien-Fleming group-sequential design with the Pocock approach. Finally we investigate the impact on error rates by including both concurrent and non-concurrent control data.

翻译：当测试多种假设时,即使是在试探性试验中,也应控制适当的误差率。控制假发现率(FDR)的常规方法假定,在测试决定的时间点,所有p值都可用。但是,在平台试验中,处理武器在试验期间随时进入试验并离开试验,因此,治疗和假设试验的数目没有事先固定,假设试验没有同时进行,而是顺序试验。最近,为了建立这种设置,采用了FDR的在线控制概念。我们调查LOND程序,在平台试验中控制在线FDR(FDR),并提出延期建议,允许进行临时分析,选择及早停止对个别假设的功效或无效性进行早期检查。这种权力取决于先前的效应大小分布,例如,真正的替代品是否在时间上统一分布,我们考虑LOND程序的设计参数的选择,以尽量扩大总的力量,并将Obrien-Fleming集团序列设计与Pocock 方法进行比较。最后,我们通过包括同时和非对数据的控制,对误差率的影响进行调查。