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Propensity Scores in Pharmacoepidemiology: Beyond the Horizon

  • Pharmacoepidemiology (S Toh, Section Editor)
  • Published:
Current Epidemiology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Propensity 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 Findings

Propensity 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.

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Funding

Ian Schmid reports grants from the US Department of Education Institute of Education Sciences during the conduct of the study. Elizabeth A. Stuart reports grants from the National Institute of Mental Health during the conduct of the study, grants from the Patient Centered Outcomes Research Institute, and grants from the US Department of Education, Institute of Education Sciences, outside the submitted work.

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Authors and Affiliations

  1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA

    John W. Jackson

  2. Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA

    John W. Jackson, Ian Schmid & Elizabeth A. Stuart

  3. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA

    Elizabeth A. Stuart

  4. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA

    Elizabeth A. Stuart

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  1. John W. Jackson
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Correspondence to Elizabeth A. Stuart.

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This article is part of the Topical Collection on Pharmacoepidemiology

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Jackson, J.W., Schmid, I. & Stuart, E.A. Propensity Scores in Pharmacoepidemiology: Beyond the Horizon. Curr Epidemiol Rep 4, 271–280 (2017). https://doi.org/10.1007/s40471-017-0131-y

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