适应式多臂两阶段设计的两种方法的比较
Cyrus Mehta1,2, Martin Kappler1
1Cytel Corporation, Cambridge, Massachusetts, USA.
Statistics in medicine
|July 15, 2025
概括
本研究比较了分析组序列随机临床试验的两种方法. 与p值组合方法相比,条件错误率方法提供了更大的统计能力来识别有效的治疗方法.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 统计方法 统计方法
背景情况:
- 组序列随机临床试验允许进行中间分析和适应性设计修改.
- 将多个处理臂与一个共同的控制器进行比较需要强大的统计方法来保持错误率.
研究的目的:
- 评估和比较两种统计方法来分析两阶段组顺序随机临床试验.
- 评估p值组合方法和条件错误率方法在控制家族智能错误率 (FWER) 和最大化统计功能的性能.
主要方法:
- 该研究考虑了两阶段的组序列设计,其中包括自适应性样本大小调整和临时手臂下降.
- 两个方法,p值组合和条件错误率,在理论上进行了讨论,并使用模拟研究进行了比较.
- 在这两种程序中,控制了家庭智能错误率 (FWER).
主要成果:
- 无论是p值组合方法还是条件错误率方法,都有效控制了家庭智能错误率 (FWER).
- 与p值组合方法相比,条件错误率方法在各种场景和替代假设中显示出更高的统计能力.
结论:
- 条件错误率方法是一种更强大的方法,用于在两阶段组顺序随机临床试验中确定有效的治疗方法.
- 这些发现表明,应考虑使用条件错误率方法,因为它在保持统计严格的同时提高了检测治疗效应的能力.
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