Incyte Corporation, Wilmington, Delaware, USA.
Merck & Co., Inc., North Wales, Pennsylvania, USA.
Int J Cancer. 2022 Nov 1;151(9):1602-1610. doi: 10.1002/ijc.34203. Epub 2022 Jul 21.
Identifying the maximum tolerated dose (MTD) and recommending a Phase II dose for an investigational treatment is crucial in cancer drug development. A suboptimal dose often leads to a failed late-stage trial, while an overly toxic dose causes harm to patients. There is a very rich literature on trial designs for dose-finding oncology clinical trials. We propose a novel hybrid design that maximizes the merits and minimizes the limitations of the existing designs. Building on two existing dose-finding designs: a model-assisted design (the modified toxicity probability interval) and a dose-toxicity model-based design, a hybrid design of the modified toxicity probability interval design and a dose-toxicity model such as the logistic regression model is proposed, incorporating optimal properties from these existing approaches. The performance of the hybrid design was tested in a real trial example and through simulation scenarios. The hybrid design controlled the overdosing toxicity well and led to a recommended dose closer to the true MTD due to its ability to calibrate for an intermediate dose. The robust performance of the proposed hybrid design is illustrated through the real trial dataset and simulations. The simulation results demonstrated that the proposed hybrid design can achieve excellent and robust operating characteristics compared to other existing designs and can be an effective model for determining the MTD and recommended Phase II dose in oncology dose-finding trials. For practical feasibility, an R-shiny tool was developed and is freely available to guide clinicians in every step of the dose finding process.
确定最大耐受剂量（MTD）并为研究性治疗推荐 II 期剂量对于癌症药物开发至关重要。剂量不足往往导致晚期试验失败，而毒性过大的剂量则会对患者造成伤害。在肿瘤临床试验剂量探索的试验设计方面有非常丰富的文献。我们提出了一种新颖的混合设计，最大限度地发挥现有设计的优点，同时最小化其局限性。在两种现有的剂量探索设计（改良毒性概率区间设计和基于剂量毒性模型的设计）的基础上，提出了改良毒性概率区间设计和基于剂量毒性模型（如逻辑回归模型）的混合设计，合并了这些现有方法的最优特性。混合设计的性能在真实试验示例和模拟场景中进行了测试。混合设计通过调整中间剂量，很好地控制了过度剂量毒性，从而推荐了更接近真实 MTD 的剂量。通过真实试验数据集和模拟结果说明了所提出的混合设计具有稳健的性能。模拟结果表明，与其他现有设计相比，所提出的混合设计可以实现卓越且稳健的操作特性，并且可以成为肿瘤学剂量探索试验中确定 MTD 和推荐 II 期剂量的有效模型。为了实现实际可行性，开发了一个 R-shiny 工具，免费提供给临床医生，以指导他们在剂量探索过程的每一步。
