使用治疗权重的逆概率调整的胜利比率
Duolao Wang1, Sirui Zheng1, Ying Cui2
1Biostatistics Unit, Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke, UK.
Journal of biopharmaceutical statistics
|November 10, 2023
概括
本研究引入了调整后获胜率方法,以解决临床试验中基线共变量失衡的问题. 新方法提高了胜利比率.
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
- 统计分析 统计分析
背景情况:
- 胜率方法在临床试验中被广泛使用,但缺乏对基线共变量失衡的调整.
- 现有的分层制胜比率方法受到层次数的限制.
研究的目的:
- 建议使用治疗权重的逆概率 (IPTW) 进行调整的胜利比率方法,以控制基线共变量失衡.
- 评估拟议的调整胜利率方法的统计特性和性能.
主要方法:
- 开发了一个调整后的胜利比率,结合了三个IPTW调整:IPTW-平均治疗效应 (IPTW-ATE),稳定IPTW-ATE (SIPTW-ATE) 和IPTW-平均治疗效应在受治疗者 (IPTW-ATT) 中.
- 导出了调整后的胜利比率的差异.
- 在CHARM试验中应用了分析复合结果的方法,并通过模拟评估了性能.
主要成果:
- 调整后的胜利比率方法有效地纠正了基线共变量失衡.
- 拟议的三种调整后的胜利比率在检测治疗差异方面表现出类似的能力.
- 调整后的胜率显示在比例危险下,功率略低于调整后的考克斯模型,但在违反这一假设时,功率始终更高.
结论:
- 拟议的调整胜率方法提供了一个强大的方法来处理临床试验分析中的共变异不平衡.
- 这些方法在不符合比例危险假设的情况下,比标准调整的考克斯模型提供了更好的功率.
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