Evaluation of QBA methods for outcome misclassification correction in pharmacovigilance

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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:

  • Point 1.
  • Point 2.
  • Point 3.

  • Below are links for study-related artifacts that have been made available as part of this study:

    Table 3. Fitted propensity model
    Figure 2. Preference score distribution