A Bayesian Case Study in Oncology Phase I Combination Dose-Finding Using Logistic Regression with Covariates
A Bayesian Case Study in Oncology Phase I Combination Dose-Finding Using Logistic Regression with Covariates
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DOI：
10.1080/10543400902802409
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发表时间：
2009-01-01
影响因子：
1.1
通讯作者：
Branson, Michael
中科院分区：
文献类型：
--
作者：
Bailey, Stuart;Neuenschwander, Beat;Branson, Michael
提出了一种寻找最大耐受剂量（MTD）的贝叶斯方法。该方法是灵活的，允许纳入协变量，并基于剂量限制性毒性（DLT）概率的综合推断总结提供透明的剂量建议。一个案例研究提出了两种肿瘤药物，尼罗替尼和伊马替尼的I期联合。本文描述了在研究过程中获得的数据和做出的决定。概述了MTD对的最终确定，以及关于研究内和研究结束数据的使用和可解释性的讨论。
A Bayesian approach to finding the maximum tolerated dose (MTD) is presented. The approach is flexible, allowing inclusion of covariates, and enables transparent dose recommendations based on comprehensive inferential summaries on the probability of dose-limiting toxicities (DLT). A case study is presented for a Phase I combination of two oncology drugs, nilotinib and imatinib. Data obtained and decisions made during the study are described. Final determination of the MTD pair is outlined, along with discussion regarding the use and interpretability of within- and end-of-study data.