在临床试验中,用于有序复合终点的胜利时间的使用
James F Troendle1, Eric S Leifer1, Song Yang1
1Office of Biostatistics Research, Division of Intramural Research of the National Heart, Lung, and Blood Institute, NIH/DHHS, Bethesda, Maryland, USA.
Statistics in medicine
|February 28, 2024
概括
新的临床试验方法,包括胜率的变体,更好地捕捉患者的整体治疗益处.
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:
- 临床试验通常通过分析时间到第一个事件的数据来评估治疗效益.
- 现有的方法,如普通胜率,可能无法完全捕捉患者的整体治疗经验.
- 需要采用统计方法,以便更全面地评估治疗的益处和危害.
研究的目的:
- 引入和评估用于测量多个临床事件的临床试验中获胜率的新变体.
- 开发更好地反映患者对整体治疗益处和危害的观点的方法.
- 将这些新方法的性能与复合事件和普通胜利比率等现有方法进行比较.
主要方法:
- 开发了几种新的胜率变体,包括在临床状态中花费的时间.
- 一种变体优先考虑死亡,同时考虑其他州的时间.
- 其他变体包括平均双赢时间,与参考分布对比的预期胜利时间 (EWT) 和使用估计临床状态分布的方法.
- 建议采用组合测试方法,在各种场景中测试强大的功率.
- 使用模拟和重新分析心力衰竭试验的方法进行了比较.
主要成果:
- 模拟表明,基于预期胜利时间 (EWT) 或估计的临床状态分布的变体在死亡治疗效益显著时,提供了更高的功率.
- 这些新的方法在特定场景中,与对对比或复合事件方法相比,表现优越.
- 这些方法提供了对治疗效果的更细致的评估,更好地与以患者为中心的结果保持一致.
结论:
- 建议的胜率变体和组合测试方法提供了更好的统计能力和在临床试验中对患者更相关的治疗益处评估.
- 纳入临床状态时间的方法,特别是EWT和估计状态分布,对于检测治疗益处是有效的,特别是在死亡率方面.
- 这些先进的统计工具增强了对临床试验结果的解释,以指导治疗决策.
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