Modernizing adverse events analysis in oncology clinical trials using alternative approaches: rationale and design of...

Area of Science:

• Oncology
• Clinical Research
• Biostatistics

Background:

• Adverse event (AE) analysis is critical for evaluating cancer treatment safety.
• New therapeutics like targeted therapies and immune checkpoint inhibitors require continuous administration, challenging traditional AE assessment methods.
• Classical methods (worst grade, time-to-event) fail to capture the duration and evolution of AEs in long-term treatments.

Purpose of the Study:

• To highlight the limitations of current adverse event analysis methods in oncology.
• To discuss the value of alternative approaches for assessing safety profiles over extended treatment durations.
• To present the rationale and design of the MOTIVATE trial (NCT03447483) for modeling toxicity evolution using the prevalence function.

Main Methods:

• Review of classical adverse event analysis methods (worst grade, time-to-event).
• Discussion of alternative approaches: prevalence function, Q-TWiST, ToxT, and recurrent event analysis.
• Description of the MOTIVATE trial design, focusing on the prevalence function for toxicity evolution modeling.

Main Results:

• Current methods inadequately assess safety profiles for long-term cancer therapies.
• Alternative methods offer improved insights into AE duration and evolution.
• The MOTIVATE trial is designed to apply the prevalence function to immunotherapy-induced toxicities.

Conclusions:

• Modernizing adverse event analysis in oncology is essential.
• Time-dependent and recurrent event approaches are crucial for evaluating novel therapeutics.
• The MOTIVATE trial will provide valuable data on toxicity evolution in immunotherapy patients.