Comparative effectiveness research (CER) and observational analyses of safety and off-target effects of drugs lie at the heart of patient-centered outcomes research. Emulating the design and analysis of a target trial using a cohort design (causal CER methods) reduces potential for several major biases in observational CER. Large cohort studies often use electronic medical record (EMR) data without validating key variables due to feasibility constraints. Using a case-control design provides the opportunity to reduce measurement bias by validating measures of eligibility, exposure, confounders, and outcome using resource-intensive data collection methods such as medical record review within a much smaller population compared with the entire cohort. However, causal CER methods for case-control studies do not yet exist, leaving researchers to choose between using either advanced analytical methods with potentially lower-quality data from a cohort design or a conventional case-control design with higher-quality data.
