Interval estimation in two-stage, drop-the-losers clinical trials with flexible treatment selection
Interval estimation in two-stage, drop-the-losers clinical trials with flexible treatment selection
复制标题
DOI：
10.1002/sim.4308
复制
发表时间：
2011-10-15
影响因子：
2
通讯作者：
Wu, Samuel S.
中科院分区：
文献类型：
--
作者：
Neal, Dan;Casella, George;Wu, Samuel S.
在一个两阶段的淘汰失败者临床试验中，研究人员在第一阶段之后的中期分析中从多种治疗方法中选出“最佳”的一种。被选中的治疗方法继续进入第二阶段以确认其疗效，而其余的治疗方法（“失败者”）则从研究中被淘汰。吴等人（《生物统计学》2010年；97卷：405 - 418页）展示了当在第一阶段之后基于主要临床终点的最高疗效选择治疗方法时，如何构建所选治疗方法与对照之间平均差的置信限。在本文中，我们展示了当基于第一阶段的安全性数据、早期终点疗效数据、安全性和疗效数据的组合或任何其他预先指定的选择规则来选择治疗方法时，如何构建平均差的下置信限。这一结果扩展了淘汰失败者设计的适用性，因为在实践中，“最佳”治疗方法往往不是仅仅基于疗效而被选择的。版权所有（C）2011约翰威立父子有限公司
In a two-stage, drop-the-losers clinical trial, researchers choose the 'best' among a number of treatments at an interim analysis after the first stage. The selected treatment continues to the second stage for confirmation of efficacy, and the remaining treatments (the 'losers') are dropped from the study. Wu et al. (Biometrika 2010; 97:405-418) showed how to construct confidence limits for the mean difference between the selected treatment and the control when the treatment is chosen after the first stage based on the highest efficacy in the primary clinical endpoint. In this article, we show how to construct a lower confidence limit for the mean difference when the treatment is chosen based on first-stage safety data, early endpoint efficacy data, a combination of safety and efficacy data or any other prespecified selection rule. The result extends the applicability of drop-the-losers designs, for in practice, the 'best' treatment often is not chosen for efficacy alone. Copyright (C) 2011 John Wiley & Sons, Ltd.