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Empirical performance of the case-control method: lessons for developing a risk identification and analysis system.

BACKGROUND: Considerable attention now focuses on the use of large-scale observational healthcare data for understanding drug safety. In this context, analysts utilize a variety of statistical and epidemiological approaches such as case-control, cohort, and self-controlled methods. The operating characteristics of these methods are poorly understood.

OBJECTIVE: Establish the operating characteristics of the case-control method for large scale observational analysis in drug safety.

RESEARCH DESIGN: We empirically evaluated the case-control approach in 5 real observational healthcare databases and 6 simulated datasets. We retrospectively studied the predictive accuracy of the method when applied to a collection of 165 positive controls and 234 negative controls across 4 outcomes: acute liver injury, acute myocardial infarction, acute kidney injury, and upper gastrointestinal bleeding.

RESULTS: In our experiment, the case-control method provided weak discrimination between positive and negative controls. Furthermore, the method yielded positively biased estimates and confidence intervals that had poor coverage properties.

CONCLUSIONS: For the four outcomes we examined, the case-control method may not be the method of choice for estimating potentially harmful effects of drugs.

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