Araujo Daniel V, Oliva Marc, Li Kecheng, Fazelzad Rouhi, Liu Zhihui Amy, Siu Lillian L
Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, ON, Canada; Department of Medical Oncology, Hospital de Base, São José Do Rio Preto, SP, Brazil.
Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, ON, Canada; Department of Medical Oncology, Institut Catala d' Oncologia, L'Hospitalet de Llobregat, Barcelona, Spain.
Eur J Cancer. 2021 Oct 14;158:85-98. doi: 10.1016/j.ejca.2021.09.016.
Phase 1 dose-escalation trials are crucial to drug development by providing a framework to assess the toxicity of novel agents in a stepwise and monitored fashion. Despite widely adopted, rule-based dose-escalation methods (such as 3 + 3) are limited in finding the maximum tolerated dose (MTD) and tend to treat a significant number of patients at subtherapeutic doses. Newer methods of dose escalation, such as model-based and model-assisted designs, have emerged and are more accurate in finding MTD. However, these designs have not yet been broadly embraced by investigators. In this review, we summarise the advantages and disadvantages of contemporary dose-escalation methods, with emphasis on model-assisted designs, including time-to-event designs and hybrid methods involving optimal biological dose (OBD). The methods reviewed include mTPI, keyboard, BOIN, and their variations. In addition, the challenges of drug development (and dose-escalation) in the era of immunotherapeutics are discussed, where many of these agents typically have a wide therapeutic window. Fictional examples of how the dose-escalation method chosen can alter the outcomes of a phase 1 study are described, including the number of patients enrolled, the trial's timeframe, and the dose level chosen as MTD. Finally, the recent trends in dose-escalation methods applied in phase 1 trials in the immunotherapeutics era are reviewed. Among 856 phase I trials from 2014 to 2019, a trend towards the increased use of model-based and model-assisted designs over time (OR = 1.24) was detected. However, only 8% of the studies used non-rule-based dose-escalation methods. Increasing familiarity with such dose-escalation methods will likely facilitate their uptake in clinical trials.
1期剂量递增试验对于药物开发至关重要,它提供了一个框架,以逐步且受监测的方式评估新型药物的毒性。尽管基于规则的剂量递增方法(如3+3)被广泛采用,但在确定最大耐受剂量(MTD)方面存在局限性,并且倾向于在亚治疗剂量下治疗大量患者。更新的剂量递增方法,如基于模型和模型辅助设计,已经出现,并且在确定MTD方面更准确。然而,这些设计尚未被研究人员广泛接受。在本综述中,我们总结了当代剂量递增方法的优缺点,重点是模型辅助设计,包括事件时间设计和涉及最佳生物学剂量(OBD)的混合方法。所审查的方法包括mTPI、键盘法、BOIN及其变体。此外,还讨论了免疫治疗时代药物开发(和剂量递增)的挑战,其中许多药物通常具有较宽的治疗窗。描述了选择剂量递增方法如何改变1期研究结果的虚构示例,包括入组患者数量、试验时间框架以及选为MTD的剂量水平。最后,回顾了免疫治疗时代1期试验中应用的剂量递增方法的最新趋势。在2014年至2019年的856项1期试验中,检测到随着时间推移基于模型和模型辅助设计的使用增加的趋势(OR = 1.24)。然而,只有8%的研究使用了非基于规则的剂量递增方法。对这类剂量递增方法的日益熟悉可能会促进它们在临床试验中的应用。