将试验结果传输到外部目标人群当试验参与影响坚持时
Rachael K Ross1, Iván Díaz2, Amy J Pitts3
1From the Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.
Epidemiology (Cambridge, Mass.)
|October 27, 2025
概括
随机临床试验结果可能不适用于现实世界的人群,因为坚持的差异. 本研究提出了一项灵敏度分析,以解决这一差距,提高治疗效应的概括性.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 随机临床试验 (RCT) 对于治疗指南至关重要,但往往缺乏对现实世界人口的概括性.
- 协变量和治疗结果介质的差异,例如坚持性,限制了RCT发现的适用性.
- 已经建立了解决共同变量差异的现有方法,但调解器差异的方法,特别是坚持,是有限的.
研究的目的:
- 开发一种灵敏度分析框架,以便在缺乏依从数据的情况下将RCT结果推广到现实世界的人口.
- 通过考虑试验与现实环境之间的坚持差异,提出估计目标人群中平均潜在结果的方法.
- 将开发的方法应用于运输阿片类药物使用障碍药物的治疗有效性数据.
主要方法:
- 提出了一项灵敏度分析,其中包含了试验和目标人群之间的相对坚持差异的参数.
- 讨论了使用外部知识来指定灵敏度参数的方法,包括范围设置和蒙特卡洛采样.
- 引入了平均反事实结果的两个估计器:一个插件估计器和一个使用机器学习的双强单步估计器.
主要成果:
- 提出的灵敏度分析允许估计在现实世界的人群中治疗效应,即使缺少依从数据.
- 双强度估计器通过支持机器学习来估计干扰参数,从而提供灵活性.
- 该方法已成功应用于运输阿片类药物使用障碍治疗的复发风险数据.
结论:
- 开发的灵敏度分析框架提高了随机临床试验结果对现实世界人口的概括性.
- 拟议的估计器提供了可靠的方法来解决坚持差异和估计治疗效应.
- 这项工作对在不同人群中为治疗指南和临床决策提供信息具有重大意义.
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