基于模型的估计在证据综合中的可移植性
1Methods and Outreach, Novo Nordisk Pharma, Madrid, Spain.
证据综合中的效应修改影响人口健康决策. 直接可折叠的措施提高了边际效应的可转移性,减少了医疗技术评估中的偏差.
科学领域:
- 生物统计学 生物统计学
- 卫生技术评估 卫生技术评估
- 证据综合 证据综合
背景情况:
- 效果修饰剂通常描述个体级别的治疗效果异质性.
- 边际影响估计对于人口层面的医疗技术评估决策至关重要.
- 非合性指标可能会受到预后变量的影响,影响边际效应.
研究的目的:
- 探索效应修改的影响,并测量证据合成中的可折叠性.
- 为了应对在获得可靠的边际效应估计人口层面的决策的挑战.
- 为改善跨研究效应估计的可转移性提供建议.
主要方法:
- 该研究讨论了效应修改和测量可折叠性的理论概念.
- 它分析了个人层面对人口层面影响措施的影响.
- 研究了统计建模和协变量调整在证据综合中的影响.
主要成果:
- 纯粹的预后变量可以改变边际效应,即使在个体级别的治疗效应均性,对于不可合的措施.
- 未经调整的间接比较可能由于共变量分布的不平衡而存在偏差.
- 在没有个体患者数据的情况下,对非可合并措施的共变量调整有限制.
结论:
- 直接可折叠的措施提高了研究之间的边际效应的可转移性.
- 使用直接可折叠的测量方法可以减少对共变量调整的依赖,当处理效应均或共变量平衡时.
- 直接可折叠的措施有助于选择适当的基线共变量进行调整,当治疗效应异质时.
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