Using Win Odds to Improve Commit-to-Phase-3 Decision-Making in Oncology

Area of Science:

• Clinical Trials
• Oncology
• Biostatistics

Background:

• Deciding to advance oncology drugs to phase 3 clinical trials is complex.
• Understanding relationships between registration endpoints (e.g., overall survival) and surrogate endpoints (e.g., progression-free survival, objective response) is crucial but often limited.

Purpose of the Study:

• To present a novel decision-making framework for committing to phase 3 oncology trials.
• To introduce and evaluate the 'three-endpoint win odds' as a metric for improved decision-making.

Main Methods:

• Developed a decision-making framework based on the three-endpoint win odds.
• Interpreted win odds as the reciprocal of the average hazard ratio for overall survival.
• Simulated correlated patient-level oncology endpoints using a multi-state disease model.
• Validated the method with simulation studies and a clinical trial case study.

Main Results:

• The win odds framework provides a robust method for decision-making in oncology drug development.
• Simulation studies confirmed the performance of the win odds method.
• The multi-state model successfully generated clinically realistic data for analysis.

Conclusions:

• The win odds framework offers a superior approach to commit-to-phase-3 decisions in oncology compared to existing methods.
• This framework enhances the understanding and prediction of overall survival based on early clinical trial endpoints.