Group sequential enrichment design incorporating subgroup selection
Group sequential enrichment design incorporating subgroup selection
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DOI：
10.1002/sim.5738
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发表时间：
2013-07-20
影响因子：
2
通讯作者：
Turnbull, Bruce W.
中科院分区：
文献类型：
--
作者：
Magnusson, Baldur P.;Turnbull, Bruce W.
药物开发临床试验的一个重要组成部分是分析患者亚组（亚群）的治疗疗效。由于对多重性的关切以及常常涉及的小样本量，这种分析可能带来重大的统计挑战，并可能导致误导性结论。作为一个验证性无缝II/III期设计，我们提出了一个自适应富集组序贯程序，资源可以集中在亚组最有可能响应治疗。停止边界通过上、下支出函数定义。该程序是在有效的分数，使正常的，二进制的，或时间到事件的数据进行分析。它通过在第一阶段消除似乎不可能获得治疗益处的人群来解决稀释效应。随后，使用成组序贯设计对剩余合并人群的治疗疗效进行明确评估。该程序提供了强有力的保护familywise I型错误率，我们采用了自举算法来获得点和区间估计，调整的选择偏差。我们给出的例子来演示如何使用的设计。我们与自适应两阶段组合检验程序和不考虑子群存在的组序贯检验进行比较。数值结果表明，该程序具有很高的权力，以检测亚组特定的影响和使用多个中期分析点可以导致大量的样本量节省。版权所有（c）2013约翰威利父子有限公司
An important component of clinical trials in drug development is the analysis of treatment efficacy in patient subgroups (subpopulations). Because of concerns of multiplicity and of the small sample sizes often involved, such analyses can present substantial statistical challenges and may lead to misleading conclusions. As a confirmatory seamless phase II/III design, we propose an adaptive enrichment group sequential procedure whereby resources can be concentrated on subgroups most likely to respond to treatment. Stopping boundaries are defined through upper and lower spending functions. The procedure is presented in terms of the efficient score, enabling the analysis of normal, binary, or time-to-event data. It addresses the dilution effect by eliminating populations at the first stage that appear likely to derive no therapeutic benefit. It subsequently proceeds with the definitive assessment of treatment efficacy among the remaining pooled populations using a group sequential design. The procedure provides strong protection of familywise type I error rate, and we employ a bootstrap algorithm to obtain point and interval estimates that are adjusted for the selection bias. We give examples to demonstrate how the design is used. We make comparisons with adaptive two-stage combination test procedures and with a group sequential test that does not account for the presence of subgroups. Numerical results show that the procedure has high power to detect subgroup-specific effects and the use of multiple interim analysis points can lead to substantial sample size savings. Copyright (c) 2013 John Wiley & Sons, Ltd.