We consider a formal statistical design that allows simultaneous enrollment of a main cohort and a backfill cohort of patients in a dose-finding trial. The goal is to accumulate more information at various doses to facilitate dose optimization. The proposed design, called Bi3+3, combines the simple dose-escalation algorithm in the i3+3 design and a model-based inference under the framework of probability of decisions (POD), both previously published. As a result, Bi3+3 provides a simple algorithm for backfilling patients to lower doses in a dose-finding trial once these doses exhibit safety profile in patients. The POD framework allows dosing decisions to be made when some backfill patients are still being followed with incomplete toxicity outcomes, thereby potentially expediting the clinical trial. At the end of the trial, Bi3+3 uses both toxicity and efficacy outcomes to estimate an optimal biological dose (OBD). The proposed inference is based on a dose-response model that takes into account either a monotone or plateau dose-efficacy relationship, which are frequently encountered in modern oncology drug development. Simulation studies show promising operating characteristics of the Bi3+3 design in comparison to existing designs.
翻译:我们提出了一种正式的统计设计,允许在计量找药试验中同时招募主要队列和回填队列的患者。目的是在不同剂量下积累更多的信息以促进剂量优化。所提出的设计称为Bi3+3,它结合了i3+3设计中的简单剂量递增算法和基于概率决策框架下的基于模型的推断,两者均已发表。因此,当某些剂量在患者中展现出安全性后,Bi3+3提供了一个回填患者到更低剂量的简单算法。POD框架使得当一些回填患者仍在进行中并且毒性结果不完整时,可以做出剂量决策,从而可能加快临床试验的进展。在试验结束时,Bi3+3使用毒性和疗效结果来估计最优生物剂量(OBD)。所提出的推断基于剂量-反应模型,该模型考虑了现代肿瘤药物开发中常见的单调或平台剂量-疗效关系。模拟研究显示,与现有设计相比,Bi3+3设计具有有前途的操作特性。