不一致的一致性:在应用流行病学研究中评估明确的干预假设
Jerzy Eisenberg-Guyot1, Katrina L Kezios2, Seth J Prins2,3
1Division of Epidemiology, NYU Grossman School of Medicine, New York, NY, USA.
International journal of epidemiology
|March 4, 2025
概括
研究人员很少在使用g方法或目标最大概率估计 (TMLE) 估计因果效应时指定明确的干预措施. 本次审查强调了在流行病学研究中应用因果推断假设的重大差距.
科学领域:
- 流行病学 流行病学
- 因果推理因果推理
- 健康研究方法 健康研究方法
背景情况:
- 教科书指南强调了对因果效应估计的明确干预假设.
- 缺乏对研究中如何处理这一假设的系统评估.
- 本研究探讨了使用g方法或有针对性的最大概率估计 (TMLE) 在流行病学研究中对明确干预假设的解释和应用.
研究的目的:
- 系统地审查使用g方法或TMLE的研究人员如何在观测流行病学研究中解释和解决明确的干预假设.
- 评估研究在多大程度上指定了明确的干预措施,并讨论了关键因果推理假设.
主要方法:
- 在2000年至2021年期间发表在具有影响力的流行病学期刊上观察性流行病学研究的综述.
- 评估作者是否旨在估计假设的干预效应.
- 评估讨论和说明因果推理假设,包括一致性和明确的干预措施.
主要成果:
- 只有20%的研究旨在估计假设的干预效应.
- 几乎没有研究 (1/29) 具体说明"如何"对暴露进行干预.
- 64%没有说明"如何"的研究对一致性有影响 (治疗变异无关).
- 虽然79%的人提到一致性,但只有45%的人将发现解释为假设的干预效应.
- 只有38%的干预效应研究包含了明确定义的干预措施.
结论:
- 在指导方针中,明确的干预假设与其在研究中的应用之间存在重大差异.
- 干预效应研究的作者很少批判性地检查明确的干预假设的有效性.
- 在流行病学研究中,需要改进对精确定义的干预措施的规范和批判性评估.
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