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

Abstract

In oncology clinical research, the analysis and reporting of adverse events is of major interest. A consistent depiction of the safety profile of a new treatment is as crucial in establishing how to use it as its antitumor activity. The advent of new therapeutics has led to major changes in the management of patients and targeted therapies or immune checkpoint inhibitors are administered continuously for months or even years. However, the classical methods of adverse events analysis are no longer adequate to properly assess their safety profile. Indeed, the worst grade method and time-to-event analysis cannot capture the duration or the evolution of adverse events induced by extended treatment durations. Many authors have highlighted this issue and argue that the analysis of safety data from clinical trials should be modernized by considering the dimension of time and the recurrent nature of adverse events. This paper aims to illustrate the limitations of current methods and discusses the value of alternative approaches such as the prevalence function, Q-TWiST, the ToxT and the recurrent event approaches. The rationale and design of the MOTIVATE trial, which aims to model the evolution of toxicities over time using the prevalence function in patients treated by immunotherapy, is also presented ( ClinicalTrials.gov Identifier: NCT03447483; Date of registration: 27 February 2018).

Keywords: Adverse events analysis; Immune checkpoint inhibitor; MOTIVATE trial; Oncology clinical trials; Prevalence; Targeted therapy.