在临床试验中复发性和终端事件的复合分析的统计方法
Yiyuan Huang1, Douglas Schaubel2, Min Zhang3
1Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
Lifetime data analysis
|October 15, 2025
概括
评估临床试验治疗效果需要分析复发性和终端事件. 非参数联合测试方法 (GL/NA) 和联合反复事件分析 (CRE) 在模拟中表现出卓越的性能,优于时间到第一个事件 (TTFE) 和胜率 (WR) 方法.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 生存分析的分析.
背景情况:
- 临床试验经常使用复发性和终端事件来评估治疗效果.
- 时间到第一个事件 (TTFE) 分析是一种流行的复合结果方法,旨在通过结合事件来增加统计能力.
- 存在其他复合结果和联合分析方法,但使用较少.
研究的目的:
- 审查和分类涉及复发性和终端事件的临床试验的主流复合分析方法.
- 通过全面的模拟研究来评估各种复合分析方法的性能.
- 确定控制I型错误和最大限度地提高处理效果评估功率的最有效方法.
主要方法:
- 将复合分析方法分类为复合结果 (例如,TTFE,CRE),联合分析 (例如,JFM,GL,NA) 和赢比类型 (例如,WR).
- 为了评估方法性能,进行了全面的模拟研究.
- 评估标准包括I型错误控制和各种场景的统计能力.
主要成果:
- 非参数联合测试方法 (Ghosh-Lin/Nelsen-Aalen方法) 和联合反复事件分析 (CRE) 显示了最好的整体性能.
- 时间到第一个事件 (TTFE) 和胜分数回归 (WR) 方法的统计能力明显较低.
- 包括与治疗无关或与治疗无关的事件通常会降低分析的效力.
结论:
- 非参数性关节测试和CRE被推用于分析临床试验中的复发性和终端事件,因为它们的性能优越.
- 当电力是主要关注点时,TFE和WR方法可能不太适合.
- 对于复合结果,仔细选择事件至关重要,以避免稀释治疗效应信号并降低统计能力.
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