Curve-free phase I/II clinical trial designs for molecularly targeted agents and immunotherapy

项目摘要/摘要 该建议的主要目标是开发透明的、fl可扩展的和有效的fiI/II期临床试验设计。 确定分子靶向制剂(MTA)和免疫疗法(IT)的最佳剂量。常规第一阶段/第二阶段 临床试验设计经常使用复杂的参数模型来描述联合毒性-ef-fi分布- 并进行审判。然而，这些参数模型在实际应用中很难证明是正确的，而且存在一定的误区 参数模型的偏差可能会导致I/II阶段试验的表现非常不理想。此外，它是Diffi邪教 对于进行试验的医生来说，临床上解释这些复杂模型的参数，以及 如此巨大的学习成本阻碍了将新颖的统计设计转化为现实世界的试验实施。 为了解决这些问题，在本提案中，我们将提出透明的无曲线I/II期临床试验设计。 建议的设计没有对剂量-反应关系或毒性-效应fi的准确性进行参数假设。 因此，在任何有临床意义的剂量-反应曲线下都表现得很好。简明扼要 临床上可解释的模型表达和剂量-fi编码算法使所提出的设计具有高度的可移植性。 从统计界到临床界。建议的设计也是高度可扩展的fl 因为它们既适用于单一药物试验，也适用于药物联合试验，且均可快速观察到 结果或延迟结果。初步的仿真研究表明，所提出的设计具有很高的实用价值 EFfi在最佳剂量选择和患者分配方面具有优势。此外，我们将开发用户友好的Web应用程序，以 促进拟议设计在临床实践中的广泛应用。

Project Summary/Abstract The primary goal of this proposal is to develop transparent, flexible and efficient phase I/II clinical trial designs identifying optimal doses for molecularly targeted agents (MTA) and immunotherapy (IT). Conventional phase I/II clinical trial designs often use sophisticated parametric models to characterize the joint toxicity-efficacy distribu- tions and to conduct the trials. However, the parametric models are hard to justify in practice, and misspecification of parametric models can lead to substantially undesirable performances of phase I/II trials. Moreover, it is difficult for the physicians conducting the trials to clinically interpret the parameters of these sophisticated models, and such great learning costs impede the translation of novel statistical designs into real-world trial implementation. To solve these issues, in this proposal we will propose transparent curve-free phase I/II clinical trial designs. The proposed designs make no parametric assumptions on either dose-response relationship or toxicity-efficacy correlation and therefore performs robustly under any clinically meaningful dose-response curves. The concise clinically interpretable model expression and dose-finding algorithm make the proposed designs highly transla- tional from the statistical community to the clinical community. The proposed designs are also highly flexible because they are applicable for both single-agent trial and drug-combination trial with either quickly observable outcomes or delayed outcomes. The preliminary simulation studies show that the proposed designs are highly efficient in optimal dose selection and patient allocation. In addition, we will develop user-friendly web apps to facilitate the widespread application of the proposed designs in clinical practice.