Evidence map›Paper›PMID 40697798›Full record

ArticleAnnals of clinical epidemiology2025

Propensity score analysis revisited.

Yohei Hashimoto, Hideo Yasunaga

Abstract read
In one paragraph

Article in Annals of clinical epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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  5. Comparison of oral third- versus first-/ second-generation cephalosporins for acute uncomplicated cystitis: a nationwide retrospective cohort study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yohei HashimotoSave Sight Institute, The Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Hideo YasunagaDepartment of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Propensity score (PS) is the probability of the exposure being assigned, conditional on the observed baseline covariates. Many observational studies have used PS analyses to investigate the effects of exposure on outcomes. This report reviews the five steps of PS analyses: 1) calculating PS; 2) checking the overlap of PS; 3) implementing a matching or weighting method including PS matching, inverse-probability-of-treatment weighting, standardized mortality ratio weighting, matching weighting, and overlap weighting; 4) diagnosing the covariate balance; and 5) comparing the outcomes. Two groups are often compared in PS analyses; however, three-group comparisons can provide clinicians with more benefits in many situations in routine clinical practice. Thus, we describe not only two-group comparisons but also three-group comparisons by introducing a few studies that used generalized PS to compare three groups.

Indexed as

Cohort studiesEpidemiologic MethodsPropensity score

Identifiers

PMID40697798
PMCPMC12279407

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.