Jiménez José L, Tighiouart Mourad
Novartis Pharma A.G., Basel, Switzerland.
Cedars-Sinai Medical Center, Los Angeles, USA.
J R Stat Soc Ser C Appl Stat. 2022 Nov;71(5):1996-2013. doi: 10.1111/rssc.12598. Epub 2022 Oct 26.
Phase I-II cancer clinical trial designs are intended to accelerate drug development. In cases where efficacy cannot be ascertained in a short period of time, it is common to divide the study in two stages: i) a first stage in which dose is escalated based only on toxicity data and we look for the maximum tolerated dose (MTD) set and ii) a second stage in which we search for the most efficacious dose within the MTD set. Current available approaches in the area of continuous dose levels involve fixing the MTD after stage I and discarding all collected stage I efficacy data. However, this methodology is clearly inefficient when there is a unique patient population present across stages. In this article, we propose a two-stage design for the combination of two cytotoxic agents assuming a single patient population across the entire study. In stage I, conditional escalation with overdose control (EWOC) is used to allocate successive cohorts of patients. In stage II, we employ an adaptive randomization approach to allocate patients to drug combinations along the estimated MTD curve, which is constantly updated. The proposed methodology is assessed with extensive simulations in the context of a real case study.
I-II期癌症临床试验设计旨在加速药物研发。在无法在短时间内确定疗效的情况下，通常将研究分为两个阶段：i）第一阶段，仅根据毒性数据增加剂量，寻找最大耐受剂量（MTD）；ii）第二阶段，在MTD范围内寻找最有效剂量。当前连续剂量水平领域的现有方法包括在第一阶段确定MTD后，丢弃所有收集到的第一阶段疗效数据。然而，当各阶段存在单一患者群体时，这种方法显然效率低下。在本文中，我们假设整个研究中有单一患者群体，提出了一种两种细胞毒性药物联合使用的两阶段设计。在第一阶段，使用带过量控制的条件递增法（EWOC）分配连续的患者队列。在第二阶段，我们采用自适应随机化方法，将患者沿着不断更新的估计MTD曲线分配到药物组合中。在一个实际案例研究的背景下，通过广泛的模拟对所提出的方法进行了评估。
