Vanderbilt University School of Medicine, Nashville, Tennessee, U.S.A.
American Hip Institute Research Foundation, Chicago, Illinois, U.S.A.
Arthroscopy. 2022 Feb;38(2):632-642. doi: 10.1016/j.arthro.2021.06.037. Epub 2021 Sep 20.
Rigorous and reproducible methodology of controlling for bias is essential for high-quality, evidence-based studies. Propensity score matching (PSM) is a valuable way to control for bias and achieve pseudo-randomization in retrospective observation studies. The purpose of this review is to 1) provide a clear conceptual framework for PSM, 2) recommend how to best report its use in studies, and 3) offer some practical examples of implementation. First, this article covers the concepts behind PSM, discusses its pros and cons, and compares it with other methods of controlling for bias, namely, hard/exact matching and regression analysis. Second, recommendations are given for what to report in a manuscript when PSM is used. Finally, a worked example is provided, which can also serve as a template for the reader's own studies. A study's conclusions are only as strong as its methods. PSM is an invaluable tool for producing rigorous and reproducible results in observational studies. The goal of this article is to give practicing clinical physicians not only a better understanding of PSM and its implications but the ability to implement it for their own studies. STUDY DESIGN: Review.
严格且可重现的偏倚控制方法对于高质量、基于证据的研究至关重要。倾向评分匹配(PSM)是一种在回顾性观察研究中控制偏倚和实现伪随机化的有价值方法。本综述的目的是:1)提供 PSM 的清晰概念框架;2)推荐在研究中最佳报告其使用的方法;3)提供实施的一些实际示例。首先,本文涵盖了 PSM 背后的概念,讨论了其优缺点,并将其与其他控制偏倚的方法(即硬匹配/精确匹配和回归分析)进行了比较。其次,给出了在使用 PSM 时应在论文中报告的内容的建议。最后,提供了一个实例研究,也可以作为读者自己研究的模板。研究的结论取决于其方法的严谨性和可重复性。PSM 是在观察性研究中产生严谨且可重现结果的宝贵工具。本文的目的不仅是让临床医生更好地理解 PSM 及其意义,而且还能为他们自己的研究实施 PSM。研究设计:综述。