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Abstract:
Background: Outcome misclassification is acknowledged but rarely corrected for in drug safety causal inference studies using observational data. Quantitative bias analysis (QBA) is a method for outcome misclassification correction, but its performance characteristics have not been systematically evaluated in pharmacovigilance applications across distributed database networks.
Objective: To evaluate the performance associated with the use of 2 types of QBA for outcome misclassification correction across a distributed database network.
Methods: METHODS
Results: RESULTS
Discussion: DISCUSSION
Key points:
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