Drug Safety

, Volume 36, Supplement 1, pp 133–142 | Cite as

Empirical Performance of LGPS and LEOPARD: Lessons for Developing a Risk Identification and Analysis System

  • Martijn J. Schuemie
  • David Madigan
  • Patrick B. Ryan
Original Research Article



The availability of large-scale observational healthcare data allows for the active monitoring of safety of drugs, but research is needed to determine which statistical methods are best suited for this task. Recently, the Longitudinal Gamma Poisson Shrinker (LGPS) and Longitudinal Evaluation of Observational Profiles of Adverse events Related to Drugs (LEOPARD) methods were developed specifically for this task. LGPS applies Bayesian shrinkage to an estimated incidence rate ratio, and LEOPARD aims to detect and discard associations due to protopathic bias. The operating characteristics of these methods still need to be determined.


Establish the operating characteristics of LGPS and LEOPARD for large scale observational analysis in drug safety.

Research Design

We empirically evaluated LGPS and LEOPARD in five real observational healthcare databases and six simulated datasets. We retrospectively studied the predictive accuracy of the methods when applied to a collection of 165 positive control and 234 negative control drug-outcome pairs across four outcomes: acute liver injury, acute myocardial infarction, acute kidney injury, and upper gastrointestinal bleeding.


In contrast to earlier findings, we found that LGPS and LEOPARD provide weak discrimination between positive and negative controls, although the use of LEOPARD does lead to higher performance in this respect. Furthermore, the methods produce biased estimates and confidence intervals that have poor coverage properties.


For the four outcomes we examined, LGPS and LEOPARD may not be the designs of choice for risk identification.


Coverage Probability Incidence Rate Ratio Nabumetone Acute Liver Injury Risk Identification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The Observational Medical Outcomes Partnership is funded by the Foundation for the National Institutes of Health 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. Schuemie and Ryan 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. Dr. Madigan has 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 ( 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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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Martijn J. Schuemie
    • 1
    • 4
  • David Madigan
    • 2
    • 4
  • Patrick B. Ryan
    • 3
    • 4
  1. 1.Department of Medical InformaticsErasmus University Medical Center RotterdamRotterdamThe Netherlands
  2. 2.Department of StatisticsColumbia UniversityNew YorkUSA
  3. 3.Janssen Research and Development LLCTitusvilleUSA
  4. 4.Observational Medical Outcomes PartnershipFoundation for the National Institutes of HealthBethesdaUSA

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