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).

中文翻译：

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使用替代方法使肿瘤临床试验中的不良事件分析现代化：MOTIVATE 试验的基本原理和设计。

在肿瘤学临床研究中，不良事件的分析和报告具有重要意义。对新疗法安全性的一致描述对于确定如何使用它与其抗肿瘤活性同样重要。新疗法的出现导致患者管理发生重大变化，靶向疗法或免疫检查点抑制剂连续给药数月甚至数年。然而，经典的不良事件分析方法已不足以正确评估其安全性。事实上，最差等级方法和事件发生时间分析无法捕捉持续时间或延长治疗持续时间引起的不良事件的演变。许多作者强调了这个问题，并认为应通过考虑时间维度和不良事件的复发性来对临床试验的安全性数据进行现代化分析。本文旨在说明当前方法的局限性，并讨论替代方法的价值，例如流行函数、Q-TWiST、ToxT 和复发事件方法。还介绍了 MOTIVATE 试验的基本原理和设计，该试验旨在使用接受免疫治疗的患者的患病率函数模拟毒性随时间的演变（ClinicalTrials.gov 标识符：NCT03447483；注册日期：2018 年 2 月 27 日）。本文旨在说明当前方法的局限性，并讨论替代方法的价值，例如流行函数、Q-TWiST、ToxT 和复发事件方法。还介绍了 MOTIVATE 试验的基本原理和设计，该试验旨在使用接受免疫治疗的患者的患病率函数模拟毒性随时间的演变（ClinicalTrials.gov 标识符：NCT03447483；注册日期：2018 年 2 月 27 日）。本文旨在说明当前方法的局限性，并讨论替代方法的价值，例如流行函数、Q-TWiST、ToxT 和复发事件方法。还介绍了 MOTIVATE 试验的基本原理和设计，该试验旨在使用接受免疫治疗的患者的患病率函数模拟毒性随时间的演变（ClinicalTrials.gov 标识符：NCT03447483；注册日期：2018 年 2 月 27 日）。