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Defining a Reference Set to Support Methodological Research in Drug Safety

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Abstract

Background

Methodological research to evaluate the performance of methods requires a benchmark to serve as a referent comparison. In drug safety, the performance of analyses of spontaneous adverse event reporting databases and observational healthcare data, such as administrative claims and electronic health records, has been limited by the lack of such standards.

Objectives

To establish a reference set of test cases that contain both positive and negative controls, which can serve the basis for methodological research in evaluating methods performance in identifying drug safety issues.

Research Design

Systematic literature review and natural language processing of structured product labeling was performed to identify evidence to support the classification of drugs as either positive controls or negative controls for four outcomes: acute liver injury, acute kidney injury, acute myocardial infarction, and upper gastrointestinal bleeding.

Results

Three-hundred and ninety-nine test cases comprised of 165 positive controls and 234 negative controls were identified across the four outcomes. The majority of positive controls for acute kidney injury and upper gastrointestinal bleeding were supported by randomized clinical trial evidence, while the majority of positive controls for acute liver injury and acute myocardial infarction were only supported based on published case reports. Literature estimates for the positive controls shows substantial variability that limits the ability to establish a reference set with known effect sizes.

Conclusions

A reference set of test cases can be established to facilitate methodological research in drug safety. Creating a sufficient sample of drug-outcome pairs with binary classification of having no effect (negative controls) or having an increased effect (positive controls) is possible and can enable estimation of predictive accuracy through discrimination. Since the magnitude of the positive effects cannot be reliably obtained and the quality of evidence may vary across outcomes, assumptions are required to use the test cases in real data for purposes of measuring bias, mean squared error, or coverage probability.

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Acknowledgments

The Observational Medical Outcomes Partnership is funded by the Foundation for the National Institutes of Health (FNIH) through generous contributions from the following: Abbott, Amgen Inc., AstraZeneca, Bayer Healthcare Pharmaceuticals, Inc., Biogen Idec, Bristol-Myers Squibb, Eli Lilly & Company, GlaxoSmithKline, Janssen Research and Development, Lundbeck, Inc., Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Pfizer Inc., Pharmaceutical Research Manufacturers of America (PhRMA), Roche, Sanofi-aventis, Schering-Plough Corporation, and Takeda. Drs. Ryan and Schuemie are employees of Janssen Research and Development. Dr. Schuemie received a fellowship from the Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration. Drs. Duke, Schuemie and Hartzema have previously received funding from FNIH. Emily Welebob and Sarah Valentine have no conflicts of interest to declare.

This article was published in a supplement sponsored by the Foundation for the National Institutes of Health (FNIH). The supplement was guest edited by Stephen J.W. Evans. It was peer reviewed by Olaf H. Klungel who received a small honorarium to cover out-of-pocket expenses. S.J.W.E has received travel funding from the FNIH to travel to the OMOP symposium and received a fee from FNIH for the review of a protocol for OMOP. O.H.K has received funding for the IMI-PROTECT project.from the Innovative Medicines Initiative Joint Undertaking (http://www.imi.europa.eu) under Grant Agreement no 115004, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.

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Authors and Affiliations

  1. Janssen Research and Development LLC, 1125 Trenton-Harbourton Road, Room K30205, PO Box 200, Titusville, NJ, 08560, USA

    Patrick B. Ryan

  2. Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands

    Martijn J. Schuemie

  3. Indiana University School of Medicine, Indianapolis, IN, USA

    Jon Duke

  4. Regenstrief Institute, Indianapolis, IN, USA

    Jon Duke

  5. College of Pharmacy, University of Florida, Gainesville, Florida, USA

    Sarah Valentine & Abraham G. Hartzema

  6. Observational Medical Outcomes Partnership, Foundation for the National Institutes of Health, Bethesda, MD, USA

    Patrick B. Ryan, Martijn J. Schuemie, Emily Welebob & Abraham G. Hartzema

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  1. Patrick B. Ryan
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  6. Abraham G. Hartzema
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Correspondence to Patrick B. Ryan.

Additional information

The OMOP research used data from Truven Health Analytics (formerly the Health Business of Thomson Reuters), and includes MarketScan® Research Databases, represented with MarketScan Lab Supplemental (MSLR, 1.2 m persons), MarketScan Medicare Supplemental Beneficiaries (MDCR, 4.6 m persons), MarketScan Multi-State Medicaid (MDCD, 10.8 m persons), MarketScan Commercial Claims and Encounters (CCAE, 46.5 m persons). Data also provided by Quintiles® Practice Research Database (formerly General Electric’s Electronic Health Record, 11.2 m persons) database. GE is an electronic health record database while the other four databases contain administrative claims data.

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Ryan, P.B., Schuemie, M.J., Welebob, E. et al. Defining a Reference Set to Support Methodological Research in Drug Safety. Drug Saf 36 (Suppl 1), 33–47 (2013). https://doi.org/10.1007/s40264-013-0097-8

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