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Channeling Bias in the Analysis of Risk of Myocardial Infarction, Stroke, Gastrointestinal Bleeding, and Acute Renal Failure with the Use of Paracetamol Compared with Ibuprofen

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  • Rachel B. Weinstein

    (Janssen Research and Development, LLC)

  • Patrick B. Ryan

    (Janssen Research and Development, LLC)

  • Jesse A. Berlin

    (Johnson and Johnson)

  • Martijn J. Schuemie

    (Janssen Research and Development, LLC)

  • Joel Swerdel

    (Janssen Research and Development, LLC)

  • Daniel Fife

    (Janssen Research and Development, LLC)

Abstract

Introduction Observational studies estimating severe outcomes for paracetamol versus ibuprofen use have acknowledged the specific challenge of channeling bias. A previous study relying on negative controls suggested that using large-scale propensity score (LSPS) matching may mitigate bias better than models using limited lists of covariates. Objective The aim was to assess whether using LSPS matching would enable the evaluation of paracetamol, compared to ibuprofen, and increased risk of myocardial infarction, stroke, gastrointestinal (GI) bleeding, or acute renal failure. Study design and setting In a new-user cohort study, we used two propensity score model strategies for confounder controls. One replicated the approach of controlling for a hand-picked list. The second used LSPSs based on all available covariates for matching. Positive and negative controls assessed residual confounding and calibrated confidence intervals. The data source was the Clinical Practices Research Datalink (CPRD). Results A substantial proportion of negative controls were statistically significant after propensity score matching on the publication covariates, indicating considerable systematic error. LSPS adjustment was less biased, but residual error remained. The calibrated estimates resulted in very wide confidence intervals, indicating large uncertainty in effect estimates once residual error was incorporated. Conclusions For paracetamol versus ibuprofen, when using LSPS methods in the CPRD, it is only possible to distinguish true effects if those effects are large (hazard ratio > 2). Due to their smaller hazard ratios, the outcomes under study cannot be differentiated from null effects (represented by negative controls) even if there were a true effect. Based on these data, we conclude that we are unable to determine whether paracetamol is associated with an increased risk of myocardial infarction, stroke, GI bleeding, and acute renal failure compared to ibuprofen, due to residual confounding.

Suggested Citation

  • Rachel B. Weinstein & Patrick B. Ryan & Jesse A. Berlin & Martijn J. Schuemie & Joel Swerdel & Daniel Fife, 2020. "Channeling Bias in the Analysis of Risk of Myocardial Infarction, Stroke, Gastrointestinal Bleeding, and Acute Renal Failure with the Use of Paracetamol Compared with Ibuprofen," Drug Safety, Springer, vol. 43(9), pages 927-942, September.
  • Handle: RePEc:spr:drugsa:v:43:y:2020:i:9:d:10.1007_s40264-020-00950-3
    DOI: 10.1007/s40264-020-00950-3
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    References listed on IDEAS

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    1. Rachel B. Weinstein & Patrick Ryan & Jesse A. Berlin & Amy Matcho & Martijn Schuemie & Joel Swerdel & Kayur Patel & Daniel Fife, 2017. "Channeling in the Use of Nonprescription Paracetamol and Ibuprofen in an Electronic Medical Records Database: Evidence and Implications," Drug Safety, Springer, vol. 40(12), pages 1279-1292, December.
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