Traditional phase I dose finding cancer clinical trial designs aim to determine the maximum tolerated dose (MTD) of the investigational cytotoxic agent based on a single toxicity outcome, assuming a monotone dose-response relationship. However, this assumption might not always hold for newly emerging therapies such as immuno-oncology therapies and molecularly targeted therapies, making conventional dose finding trial designs based on toxicity no longer appropriate. To tackle this issue, numerous early phase dose finding clinical trial designs have been developed to identify the optimal biological dose (OBD), which takes both toxicity and efficacy outcomes into account. In this article, we review the current model-assisted dose finding designs, BOIN-ET, BOIN12, UBI, TEPI-2, PRINTE, STEIN, and uTPI to identify the OBD and compare their operating characteristics. Extensive simulation studies and a case study using a CAR T-cell therapy phase I trial have been conducted to compare the performance of the aforementioned designs under different possible dose-response relationship scenarios. The simulation results demonstrate that the performance of different designs varies depending on the particular dose-response relationship and the specific metric considered. Based on our simulation results and practical considerations, STEIN, PRINTE, and BOIN12 outperform the other designs from different perspectives.

翻译：传统的一期癌症剂量探索临床试验设计基于单一毒性结局，并假设剂量-反应关系呈单调性，旨在确定研究性细胞毒性药物的最大耐受剂量。然而，对于免疫肿瘤疗法和分子靶向疗法等新兴疗法，这一假设可能并不总是成立，使得基于毒性的传统剂量探索试验设计不再适用。为解决这一问题，已开发出多种早期阶段剂量探索临床试验设计，以确定同时考虑毒性与疗效结局的最佳生物剂量。本文综述了当前用于识别最佳生物剂量的模型辅助剂量探索设计，包括BOIN-ET、BOIN12、UBI、TEPI-2、PRINTE、STEIN和uTPI，并比较了它们的操作特性。我们通过广泛的模拟研究以及一项使用CAR T细胞疗法一期试验的案例研究，比较了上述设计在不同可能的剂量-反应关系场景下的性能。模拟结果表明，不同设计的性能表现因具体的剂量-反应关系和所考察的特定指标而异。基于我们的模拟结果和实际考量，STEIN、PRINTE和BOIN12在不同维度上优于其他设计。