Empirical Performance of the Case–Control Method: Lessons for Developing a Risk Identification and Analysis System
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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.
Establish the operating characteristics of the case–control method for large scale observational analysis in drug safety.
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.
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.
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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