Nonparametric Overdose Control in Phase I Dose-Finding Clinical Trials
报 告 人:: Ruitao Lin
报告地点:: 数学与统计学院四楼报告厅
报告时间:: 2018年04月03日星期二09:00-10:00
报告简介:

Under the framework of Bayesian model selection, we propose a nonparametric overdose control (NOC) design for dose finding in phase I clinical trials. Each dose assignment is guided via a feasibility bound, which thereby can control the number of patients allocated to excessively toxic dose levels. We further develop a fractional NOC (fNOC) design in conjunction with a so-called fractional imputation approach, to account for late-onset toxicity outcomes. Extensive simulation studies have been conducted to show that both the NOC and fNOC designs have robust and satisfactory finite-sample performance compared with the existing dose finding designs. The proposed methods also possess several desirable properties: treating patients more safely and also neutralizing the aggressive escalation to overly toxic doses when the toxicity outcomes are late-onset. We also generalize the NOC design to handle drug-combination trials and phase I/II trials.

举办单位:数学与统计学院
发 布 人:吴双 发布时间: 2018-04-03
主讲人简介:
Ruitao Lin,美国德克萨斯大学MD Anderson Cancer Center 博士后研究员。2011年6月毕业于西南交通大学数学与应用数学系,2011年9月至2012年8月于香港科技大学金融数学系就读硕士,2016年8月博士毕业于香港大学生物统计系;分别于2016年9月-2017年8月在美国华盛顿大学Department of Biostatistics,2017年9月-2019年8月美国德克萨斯大学MD Anderson Cancer Center 从事博士后研究。 Ruitao Lin主要从事Bayesian adaptive design、Bayesian modeling、Meta-analysis、Missing data、 Empirical likelihood 等研究工作。发表学术论文10余篇。