Beautiful weights, misinterpreted effects: the use and misuse of overlap weighting in major medical journals, 2020-2025

John G Rizk; Giuseppe Lippi; Carl J Lavie

doi:10.1016/j.jclinepi.2025.112113

Beautiful weights, misinterpreted effects: the use and misuse of overlap weighting in major medical journals, 2020-2025

J Clin Epidemiol. 2026 Mar:191:112113. doi: 10.1016/j.jclinepi.2025.112113. Epub 2025 Dec 16.

Authors

John G Rizk¹, Giuseppe Lippi², Carl J Lavie³

Affiliations

¹ Department of Practice, Sciences, and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, MD, USA; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA. Electronic address: john.rizk@umaryland.edu.
² Section of Clinical Biochemistry, University of Verona, Verona, Italy.
³ John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine, New Orleans, LA, USA.

PMID: 41412484
DOI: 10.1016/j.jclinepi.2025.112113

Abstract

Objectives: To evaluate the implementation and reporting practices of overlap weighting in major medical journals.

Study design and setting: We reviewed observational studies published from January 2020 to September 2025 in five major medical journals (Annals of Internal Medicine, The British Medical Journal [BMJ], Journal of the American Medical Association [JAMA], JAMA Internal Medicine, and The New England Journal of Medicine [NEJM]) that used overlap weighting as a primary or sensitivity adjustment method. Reporting quality was assessed for estimand specification, definition of the overlap population, justification of the method, acknowledgment of advantages, and discussion of interpretability.

Results: Seventeen eligible studies were identified. Four studies (24%) correctly named the estimand as the average treatment effect in the overlap population; two (12%) misreported the estimand as average treatment effect, and the remainder did not specify an estimand. Ten studies (59%) described the overlap population at least partially. Sixteen studies (94%) highlighted at least one statistical advantage of overlap weighting, yet none acknowledged that results apply only to the overlap population. These results point to a notable gap in estimand reporting.

Conclusion: Clearer specification of the estimand and its target population is essential to prevent misinterpretation. Strengthening reporting standards will support more transparent and appropriate use of overlap weighting in medical research.

Plain language summary: This study examined how major medical journals (from 2020-2025) report studies using overlap weighting, a method that focuses on patients who could receive either treatment. Most studies acknowledged advantages of using overlap weighting but did not clearly state that results apply only to this "overlap" group. Clear reporting of the target population and effect estimate is needed to avoid misleading interpretations.

Keywords: Causal inference; Estimand; Observational studies; Overlap weighting; Propensity scores; Reporting.

MeSH terms

Humans
Observational Studies as Topic
Periodicals as Topic* / standards
Periodicals as Topic* / statistics & numerical data
Research Design*