利用试验和观察数据评估有效性:试验模拟、可迁移性、基准和联合分析。

IF 5.2 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Issa J Dahabreh, Anthony Matthews, Jon A Steingrimsson, Daniel O Scharfstein, Elizabeth A Stuart
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引用次数: 0

摘要

试图解决类似研究问题的随机试验分析与观察分析之间的比较在流行病学和社会科学领域引发了许多争议。对于这种比较在什么情况下是合理的、它们对观察分析的有效性有什么影响、试验分析和观察分析是否可以结合起来解决有效性问题等问题,几乎没有达成共识。在此,我们将探讨在评估治疗效果时使用观察分析补充试验分析的方法。首先,我们回顾了模拟目标试验的观察分析设计框架,并介绍了其近期应用的证据图谱。然后,我们回顾了估算模拟目标人群平均治疗效果的方法:单独使用模拟数据的观察分析;使用可迁移性分析将试验推论扩展到目标人群。我们解释了将仿真分析得出的治疗效果估计值与试验得出的治疗效果估计值进行比较如何为观察分析是否能提供有效的疗效估计值提供证据--我们将这一过程称为基准分析--以及在某些情况下如何对试验和观察数据进行联合分析。我们以简化的实用性试验为例,说明了不同的方法及其在登记数据中的仿效。我们的结论是,通过结合定量方法和流行病学判断的过程,综合试验数据和观察数据--在可迁移性、基准或联合分析中--可以利用它们的互补优势来加强对比较效果的学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Trial and Observational Data to Assess Effectiveness: Trial Emulation, Transportability, Benchmarking, and Joint Analysis.

Comparisons between randomized trial analyses and observational analyses that attempt to address similar research questions have generated many controversies in epidemiology and the social sciences. There has been little consensus on when such comparisons are reasonable, what their implications are for the validity of observational analyses, or whether trial and observational analyses can be integrated to address effectiveness questions. Here, we consider methods for using observational analyses to complement trial analyses when assessing treatment effectiveness. First, we review the framework for designing observational analyses that emulate target trials and present an evidence map of its recent applications. We then review approaches for estimating the average treatment effect in the target population underlying the emulation: using observational analyses of the emulation data alone; and using transportability analyses to extend inferences from a trial to the target population. We explain how comparing treatment effect estimates from the emulation against those from the trial can provide evidence on whether observational analyses can be trusted to deliver valid estimates of effectiveness - a process we refer to as benchmarking - and, in some cases, allow the joint analysis of the trial and observational data. We illustrate different approaches using a simplified example of a pragmatic trial and its emulation in registry data. We conclude that synthesizing trial and observational data - in transportability, benchmarking, or joint analyses - can leverage their complementary strengths to enhance learning about comparative effectiveness, through a process combining quantitative methods and epidemiological judgements.

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来源期刊
Epidemiologic Reviews
Epidemiologic Reviews 医学-公共卫生、环境卫生与职业卫生
CiteScore
8.10
自引率
0.00%
发文量
10
期刊介绍: Epidemiologic Reviews is a leading review journal in public health. Published once a year, issues collect review articles on a particular subject. Recent issues have focused on The Obesity Epidemic, Epidemiologic Research on Health Disparities, and Epidemiologic Approaches to Global Health.
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