Wassmer Gernot, Dragalin Vlad
a Aptiv Solutions , Reston , Virginia , USA.
J Biopharm Stat. 2015;25(4):651-69. doi: 10.1080/10543406.2014.920869.
Adaptive population enrichment designs enable the data-driven selection of one or more pre-specified subpopulations in an interim analysis, and the confirmatory proof of efficacy in the selected subset at the end of the trial. Sample size reassessment and other adaptive design changes can be performed as well. Strong control of the experimentwise Type I error rate is guaranteed by use of the combination testing principle together with the closed testing argument. In this paper the general methodology and designing issues when planning such a design are reviewed. It is shown how to derive overall confidence intervals and p-values. Criteria for assessing the operating characteristics of these designs are given, and the application is illustrated by examples.
适应性群体富集设计能够在期中分析中通过数据驱动选择一个或多个预先指定的亚组，并在试验结束时对所选亚组进行疗效的确证性证明。也可以进行样本量重新评估和其他适应性设计变更。通过使用联合检验原则和封闭检验论证，能够确保对实验性I型错误率进行严格控制。本文回顾了规划此类设计时的一般方法和设计问题。展示了如何推导总体置信区间和p值。给出了评估这些设计操作特性的标准，并通过实例进行了说明。
