Pfizer Corporation, Cambridge, Massachusetts.
Cytel Inc, Cambridge, Massachusetts.
Stat Med. 2020 Apr 15;39(8):1084-1102. doi: 10.1002/sim.8464. Epub 2020 Feb 11.
Two methods for designing adaptive multiarm multistage (MAMS) clinical trials, originating from conceptually different group sequential frameworks are presented, and their operating characteristics are compared. In both methods pairwise comparisons are made, stage-by-stage, between each treatment arm and a common control arm with the goal of identifying active treatments and dropping inactive ones. At any stage one may alter the future course of the trial through adaptive changes to the prespecified decision rules for treatment selection and sample size reestimation, and notwithstanding such changes, both methods guarantee strong control of the family-wise error rate. The stage-wise MAMS approach was historically the first to be developed and remains the standard method for designing inferentially seamless phase 2-3 clinical trials. In this approach, at each stage, the data from each treatment comparison are summarized by a single multiplicity adjusted P-value. These stage-wise P-values are combined by a prespecified combination function and the resultant test statistic is monitored with respect to the classical two-arm group sequential efficacy boundaries. The cumulative MAMS approach is a more recent development in which a separate test statistic is constructed for each treatment comparison from the cumulative data at each stage. These statistics are then monitored with respect to multiplicity adjusted group sequential efficacy boundaries. We compared the powers of the two methods for designs with two and three active treatment arms, under commonly utilized decision rules for treatment selection, sample size reestimation and early stopping. In our investigations, which were carried out over a reasonably exhaustive exploration of the parameter space, the cumulative MAMS designs were more powerful than the stage-wise MAMS designs, except for the homogeneous case of equal treatment effects, where a small power advantage was discernable for the stage-wise MAMS designs.
提出了两种源自概念上不同的群组序贯框架的设计自适应多臂多阶段（MAMS）临床试验的方法，并比较了它们的操作特点。在这两种方法中，通过逐个阶段地对每个治疗臂与共同对照臂进行两两比较，旨在确定有效治疗方法并淘汰无效治疗方法。在任何阶段，都可以通过对治疗选择和样本量重新估计的预设决策规则进行适应性更改来改变试验的未来进程，尽管有这些更改，但这两种方法都保证了对总体错误率的严格控制。阶段式 MAMS 方法是历史上首先开发的方法，并且仍然是设计推断性无缝的 2-3 期临床试验的标准方法。在这种方法中，在每个阶段，来自每个治疗比较的数据都通过单个多重调整 P 值进行总结。这些阶段式 P 值通过预设的组合函数进行组合，并且所得的检验统计量与经典的两臂群组序贯功效边界进行监测。累积 MAMS 方法是一种较新的方法，其中在每个阶段从累积数据中为每个治疗比较构建单独的检验统计量。然后，针对多重调整的群组序贯功效边界对这些统计量进行监测。我们比较了这两种方法在常用的治疗选择、样本量重新估计和早期停止决策规则下，用于设计具有两个和三个有效治疗臂的方法的功效。在我们的研究中，对参数空间进行了合理详尽的探索，累积 MAMS 设计比阶段式 MAMS 设计更有效，除了治疗效果相等的均匀情况外，在阶段式 MAMS 设计中可以察觉到较小的功效优势。
