Evidence map›Paper›PMID 39538155›Full record

ArticleBMC medical research methodology2024

A comparison of time-varying propensity score vs sequential stratification approaches to longitudinal matching with a time-varying treatment.

Morgan Richey, Matthew L Maciejewski, Lindsay Zepel, David Arterburn, Aniket Kawatkar, Caroline E Sloan, Valerie A Smith

Abstract readComparative Study
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Morgan RicheyDepartment of Population Health Sciences, Duke University School of Medicine, Durham, 27705, NC, USA.
Matthew L MaciejewskiDepartment of Population Health Sciences, Duke University School of Medicine, Durham, 27705, NC, USA. mlm34@duke.edu.
Lindsay ZepelDepartment of Population Health Sciences, Duke University School of Medicine, Durham, 27705, NC, USA.
David ArterburnDepartment of Medicine, University of Washington, Seattle, WA, USA.
Aniket KawatkarDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Caroline E SloanCenter of Innovation to Accelerate Discovery and Practice Transformation, Affairs Medical Center, Durham Veterans, Durham, NC, USA.
Valerie A SmithDepartment of Population Health Sciences, Duke University School of Medicine, Durham, 27705, NC, USA.

Funding

Long-term Costs and Return on Investment for Bariatric SurgeryR01DK125380 · NIDDK · DUKE UNIVERSITY · PI ARTERBURN, DAVID ERIC, MACIEJEWSKI, MATTHEW L · 2020 to 2023
$2.7M
NIDDK NIH HHS R01 DK125380
6 · The paper itself

Abstract

backgroundMethods for matching in longitudinal cohort studies, such as sequential stratification and time-varying propensity scores, facilitate causal inferences in the context of time-dependent treatments that are not randomized where patient eligibility or treatment status changes over time. The tradeoffs in available approaches have not been compared previously, so we compare two methods using simulations based on a retrospective cohort of patients eligible for weight loss surgery, some of whom received it.

methodsThis study compares matching completeness, bias, coverage, and precision among three approaches to longitudinal matching: (1) time-varying propensity scores (tvPS), (2) sequential stratification that matches exactly on all covariates used in tvPS (SS-Full) and (3) sequential stratification that exact matches on a subset of covariates (SS-Selected). These comparisons are made in the context of a deep sampling frame (50:1) and a shallow sampling frame (5:1) of eligible comparators. A simulation study was employed to estimate the relative performance of these approaches.

resultsIn 1,000 simulations each, tvPS retained more than 99.9% of treated patients in both the deep and shallow sampling frames, while a smaller proportion of treated patients were retained for SS-Full (91.6%) and SS-Selected (98.2%) in the deep sampling frame. In the shallow sampling frame, sequential stratification retained many fewer treated patients (73.9% SS-Full, 92.0% SS-Selected) than tvPS yet coverage, precision and bias were comparable for tvPS, SS-Full and SS-Selected in the deep and shallow sampling frames.

conclusionTime-varying propensity scores have comparable performance to sequential stratification in terms of coverage, bias, and precision, with superior match completeness. While performance was generally comparable across methods, greater match completeness makes tvPS an attractive option for longitudinal matching studies where external validity is highly valued.

Indexed as

Propensity ScoreBariatric SurgeryComputer SimulationFemaleHumansLongitudinal StudiesMaleRetrospective StudiesTime FactorsBiasConfoundingMatchingPrecisionSequential stratificationTime varying propensity scores

Identifiers

PMID39538155
PMCPMC11562661

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