贝叶斯概率
区间(图论)
置信区间
统计
最大耐受剂量
相(物质)
临床研究设计
毒性
计算机科学
数学
医学
计量经济学
心理学
临床试验
内科学
化学
组合数学
有机化学
作者
Kai Chen,Li Wang,Ying Yuan
标识
DOI:10.1080/19466315.2024.2368802
摘要
Conventionally, dose finding trials are based on dose-limiting toxicity (DLT) that only captures the most severe toxicities, e.g., treatment related grade 3 or higher toxicity according to the NCI Common Terminology Criteria for Adverse Events. However, this approach is often problematic for certain novel targeted therapies and immunotherapies, which may not induce DLT within a clinically active dose range and are often characterized by low grade toxicities. This important issue has been highlighted and discussed in the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forums, and is also an important consideration of the Project Optimus initiated by FDA to "reform the dose optimization and dose selection paradigm in oncology drug development." In this paper, we propose an easy-to-implement model-assisted Bayesian design, known as multiple toxicity keyboard (MT-Keyboard) design, to incorporate toxicity grades and types into dose finding. The MT-Keyboard design is able to accommodate binary, quasi-binary and continuous toxicity endpoints that are constructed to account for toxicity grades and types. We further extend the MT-Keyboard design, referred to as TITE-MT-Keyboard, to accommodate late-onset toxicity using the approximated likelihood approach. Simulation shows that the MT-Keyboard and TITE-MT-Keyboard designs have desirable operating characteristics, comparable to or better than some existing designs. A web-based software to implement the design will be freely available at www.trialdesign.org.
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