Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2023 Apr;38(4):622-626.
doi: 10.1016/j.arth.2022.08.030. Epub 2023 Jan 11.

Propensity Scores: Confounder Adjustment When Comparing Nonrandomized Groups in Orthopaedic Surgery

Affiliations
Review

Propensity Scores: Confounder Adjustment When Comparing Nonrandomized Groups in Orthopaedic Surgery

Dirk R Larson et al. J Arthroplasty. 2023 Apr.

Abstract

Many studies in arthroplasty research are based on nonrandomized, retrospective, registry-based cohorts. In these types of studies, patients belonging to different treatment or exposure groups often differ with respect to patient characteristics, medical histories, surgical indications, or other factors. Consequently, comparisons of nonrandomized groups are often subject to treatment selection bias and confounding. Propensity scores can be used to balance cohort characteristics, thus helping to minimize potential bias and confounding. This article explains how propensity scores are created and describes multiple ways in which they can be applied in the analysis of nonrandomized studies. Please visit the following (https://www.youtube.com/watch?v=sqgxl_nZWS4&t=3s) for a video that explains the highlights of the paper in practical terms.

Keywords: bias; confounding; inverse probability of treatment; propensity score; statistics; total joint arthroplasty.

PubMed Disclaimer

Conflict of interest statement

One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2022.08.030.

Figures

Fig. 1.
Fig. 1.
Standardized differences between patients before (solid triangles) and after (hollow dots) propensity score weighting.

References

    1. Zaniletti I, Larson DR, Lewallen DG, Berry DJ, Maradit Kremers H. Study types in orthopaedics research: is my study design appropriate for the research question? J Arthroplasty 2022;37:1939–44. - PMC - PubMed
    1. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011;46: 399–424. - PMC - PubMed
    1. Mundi R, Chaudhry H, Mundi S, Godin K, Bhandari M. Design and execution of clinical trials in orthopaedic surgery. Bone Joint Res 2014;3:161–8. - PMC - PubMed
    1. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983;70:41–55.
    1. Austin PC, Xin Yu AY, Vyas MV, Kapral MK. Applying propensity score methods in clinical research in neurology. Neurology 2021;97:856–63. - PMC - PubMed

Publication types