A hybrid design for dose‐finding oncology clinical trials. Issue 9 (21st July 2022) - Liao, Jason J. Z.; Zhou, Feng; Zhou, Heng; Petruzzelli, Lilli; Hou, Kevin; Asatiani, Ekaterine
Abstract: 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. Abstract : What's new? For novel cancer therapeutics, identifying the maximum tolerated dose (MTD) and the ideal dose for Phase II clinical trials are major goals of Phase I dose‐finding studies. Here, to better optimize dose selection, the authors present a hybrid approach to making dose estimates based on mode‐assisted design and a dose‐toxicity model. In a real trial example and simulation scenarios, the hybrid design limited the risk of overdosing toxicity and, owing to calibration for an intermediate dose, yielded a recommend dose more on par with true MTD. The results highlight the utility of the hybrid design for Phase I dose‐finding trials.