Department of Biostatistics, Institut Claudius Regaud, IUCT-O Toulouse, Toulouse.
Department of Biostatistics, Institut Paoli Calmette, Marseille.
Ann Oncol. 2016 Aug;27(8):1633-8. doi: 10.1093/annonc/mdw218. Epub 2016 May 23.
In the era of personalized medicine, molecularly targeted therapies (MTT) have modified the outcome of some cancer types. The price of tumor control needs to be balanced with toxicity since these new therapies are administered continuously for several months or sometimes for several years. For cytotoxic drugs, the incidence of adverse event (AE) was traditionally reported as frequency and intensity. This simple measure is not sufficient to capture the recurrent nature and duration of AE. This paper presents two methods to better describe the toxicity burden across the time: prevalence and Q-TWiST.
Limitation of worst-grade method and advantages of prevalence and Q-TWiST in the analysis of toxicity were illustrated using data from a phase II trial and a hypothetically simulated clinical trial.
Prevalence integrates the recurrent nature of AE. Using prevalence, it is possible to obtain a time profile of AE. Q-TWiST method evaluates the weighted time spent in each health state and also considers the recurrent nature of side-effects in order to assess the 'risk-benefit' ratio of a treatment. When interpreting Q-TWiST results, it is necessary to take into account overall survival and progression-free survival and to define a clinically relevant difference according to the setting.
The two methods presented here capture different effects. They are helpful for physicians in their treatment choice (balance benefit risk), to counsel patients and to optimize supportive care. In order to ensure consistency and provide critical information required for medical decision-making, it is important to encourage the use of alternative statistical methods in the analysis of toxicities associated with MTT.
NCT00541008.
在个性化医学时代，分子靶向治疗（MTT）已经改变了某些癌症类型的治疗效果。肿瘤控制的代价需要与毒性相平衡，因为这些新的治疗方法需要连续使用数月甚至数年。对于细胞毒性药物，不良事件（AE）的发生率传统上是通过频率和强度来报告的。这种简单的方法不足以捕捉 AE 的复发性质和持续时间。本文提出了两种更好地描述随时间变化的毒性负担的方法：流行率和 Q-TWiST。
通过一个 II 期临床试验和一个假设的模拟临床试验的数据，说明了限制最差等级法的局限性和流行率和 Q-TWiST 在毒性分析中的优势。
流行率综合了 AE 的复发性质。使用流行率，可以获得 AE 的时间分布。Q-TWiST 方法评估了每个健康状态的加权时间，并且还考虑了副作用的复发性质，以便评估治疗的“风险-效益”比。在解释 Q-TWiST 结果时，需要考虑总生存和无进展生存，并根据设定定义临床相关差异。
本文提出的两种方法捕捉到了不同的效果。它们有助于医生在治疗选择中（平衡利弊）、向患者提供咨询和优化支持性护理。为了确保一致性并提供与 MTT 相关的毒性分析所需的关键信息，鼓励在分析中使用替代统计方法非常重要。
NCT00541008。
