在具有多个事件时间结果的试验中量化治疗效果.
Brian Lee Claggett1, Zachary R McCaw2, Lu Tian3
1Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston.
NEJM evidence
|August 30, 2023
概括
一种新的无模型方法使用多个结果的曲线下的面积 (AUC) 估计治疗效果. 这种方法应用于心力衰竭住院和心血管死亡,在联合治疗中,疾病负担减少了14%.
科学领域:
- 生物统计学 生物统计学
- 临床试验 临床试验
- 心血管研究研究心血管研究
背景情况:
- 在临床试验中分析多个事件时间的传统方法依赖于特定的模型假设.
- 违反这些假设可能会导致误导治疗效果估计.
- 需要强大的,无模型的分析程序,以便更好地进行临床解释.
研究的目的:
- 引入和验证一种强大的,无模型的方法来分析具有多个结果的时间到事件数据.
- 用曲线下的面积 (AUC) 作为累积疾病负担的度量来量化治疗效应.
- 证明该方法的应用和改善临床试验设计的潜力.
主要方法:
- 计算了每个治疗组的累积事件计数曲线下的面积 (AUC).
- 解释的AUC是平均总失去的无事件时间,较高的AUC表明更糟糕的结果.
- 量化治疗效应通过AUCs之间的比率或差异之间的群体.
主要成果:
- 在PARAGON-HF试验中,心力衰竭住院和心血管死亡的AUC分别为sacubitril/valsartan和valsartan的11.3和13.1事件月.
- 0.86的AUC比率表明疾病负担减少了14%,有利于sacubitril/valsartan.
- 以这种方法设计的未来研究将需要比传统的时间到第一次事件分析更少的患者.
结论:
- 拟议的AUC方法是可靠的,不需要模型,并提供了随时间推移治疗效应的临床可解释的总结.
- 这种方法为分析临床试验中复杂事件数据提供了有价值的替代方案.
- 该方法可以为更有效的研究设计提供信息,可能减少患者招募人数.
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