Evidence map›Paper›PMID 29456922›Full record

ArticleCurrent epidemiology reports2017

Propensity Scores in Pharmacoepidemiology: Beyond the Horizon.

John W Jackson, Ian Schmid, Elizabeth A Stuart

Abstract read
In one paragraph

Article in Current epidemiology reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
–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

35 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  4. Impact of Graft Velocity on Saphenous Vein Graft Atherosclerosis after Coronary Artery Bypass Grafting.Annals of thoracic and cardiovascular surgery : official journal of the Association of Thoracic and Cardiovascular Surgeons of Asia · 2024
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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

3 authors.

John W JacksonDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.
Ian SchmidDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.
Elizabeth A StuartDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.

Funding

Using propensity scores for causal inference with covariate measurement errorR01MH099010 · NIMH · JOHNS HOPKINS UNIVERSITY · PI STUART, ELIZABETH A. · 2013 to 2016
$1.1M
NIMH NIH HHS L30 MH111012NIMH NIH HHS R01 MH099010
6 · The paper itself

Abstract

purpose of reviewPropensity score methods have become commonplace in pharmacoepidemiology over the past decade. Their adoption has confronted formidable obstacles that arise from pharmacoepidemiology's reliance on large healthcare databases of considerable heterogeneity and complexity. These include identifying clinically meaningful samples, defining treatment comparisons, and measuring covariates in ways that respect sound epidemiologic study design. Additional complexities involve correctly modeling treatment decisions in the face of variation in healthcare practice, and dealing with missing information and unmeasured confounding. In this review, we examine the application of propensity score methods in pharmacoepidemiology with particular attention to these and other issues, with an eye towards standards of practice, recent methodological advances, and opportunities for future progress. RECENT

findingsPropensity score methods have matured in ways that can advance comparative effectiveness and safety research in pharmacoepidemiology. These include natural extensions for categorical treatments, matching algorithms that can optimize sample size given design constraints, weighting estimators that asymptotically target matched and overlap samples, and the incorporation of machine learning to aid in covariate selection and model building. SUMMARY: These recent and encouraging advances should be further evaluated through simulation and empirical studies, but nonetheless represent a bright path ahead for the observational study of treatment benefits and harms.

Indexed as

causal inferencecomparative effectivenessnon-experimental studypharmacoepidemiologypropensity scorestudy design

Identifiers

PMID29456922
PMCPMC5810585

What OpenQuestion holds

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Registered trials

None linked

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.