Adjusting for intercurrent events using Bayesian joint models for longitudinal outcomes in clinical trials

Key Points

• Improved precision of treatment effect estimates results from addressing intercurrent events effectively.
• The model accounts for event-related truncation during longitudinal follow-up, thereby enhancing reliability.
• Application of Bayesian joint models allows for better design and analysis in clinical trials.
• This approach highlights the importance of accurately managing incomplete outcome measurement.

Abstract