Validation to correct for outcome misclassification bias

This is the authors' abstract. We don't add key points for this paper.

Key Points1. Outcome validation is often requested by regulators to address misclassification bias in database studies of drug safety and comparative effectiveness.2. Validation studies commonly report only one positive predictive value (PPV) estimate.3. Since a high value of PPV does not imply misclassification bias is negligible, and a low value of PPV does not imply misclassification bias is important, this approach does not adequately address outcome misclassification bias.4. Validation should be designed to inform quantitative bias analysis that corrects results for misclassification bias.5. To correct for misclassification bias, quantitative bias analysis requires parameters for false positive errors and false negative errors in each comparison group.