Evidence map›Paper›PMID 29750409›Full record

ArticleAmerican journal of epidemiology2018

Implications of the Propensity Score Matching Paradox in Pharmacoepidemiology.

John E Ripollone, Krista F Huybrechts, Kenneth J Rothman, Ryan E Ferguson, Jessica M Franklin

Abstract readEvaluation Study
In one paragraph

Article in American journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Propensity score matching.Nature methods · 2024
    Article
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  20. Risks of incident major osteoporotic fractures following SARS-CoV-2 infection among older individuals: a population-based cohort study in Hong Kong.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2024
    Article
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

5 authors.

John E RipolloneDepartment of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts.
Krista F HuybrechtsDepartment of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts.
Kenneth J RothmanDepartment of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts.
Ryan E FergusonDepartment of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts.
Jessica M FranklinDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.

Funding

Improved methods to assess the comparative safety of new psychiatric medicationsK01MH099141 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI HUYBRECHTS, KRISTA F · 2013 to 2017
$882k
NIMH NIH HHS K01 MH099141
6 · The paper itself

Abstract

Recent work has demonstrated that propensity score matching may lead to increased covariate imbalance, even with the corresponding decrease in propensity score distance between matched units. The extent to which this paradoxical phenomenon might harm causal inference in real epidemiologic studies has not been explored. We evaluated the effect of this phenomenon using insurance claims data from the Pharmaceutical Assistance Contract for the Elderly (1999-2002) and Medicaid Analytic eXtract (2000-2007) databases in the United States. For each data set, we created several 1:1 propensity-score-matched data sets by manipulating the size of the covariate set used to generate propensity scores, the index exposure prevalence in the prematched data set, and the matching algorithm. We matched all index units, then progressively pruned matched sets in order of decreasing propensity score distance, calculating covariate imbalance after each pruning. Although covariate imbalance sometimes increased after progressive pruning of matched sets, the application of commonly used propensity score calipers for defining an acceptable match stopped pruning near the lowest region of the imbalance trend and resulted in an improvement over the imbalance in the prematched data set. Thus, propensity score matching does not appear to induce increased covariate imbalance when standard propensity score calipers are applied in these types of pharmacoepidemiologic studies.

Indexed as

Propensity ScoreAlgorithmsHumansPharmacoepidemiology

Identifiers

PMID29750409
PMCPMC6118075

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.