报告题目:Statistical Methods for Precision Medicine with Time-to-Event Endpoints

报 告 人:赵利辉(美国西北大学)

报告时间:2019年9月2日(周一) 下午4:00-5:00

报告地点:知新楼B-1238

报告摘要:

When comparing a new treatment to a control with a time-to-event endpoint in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. Furthermore, standard methods of summarizing the treatment difference are based on Kaplan-Meier curves, the logrank test and the point and interval estimates via Cox's proportional hazards model. However, when the proportional hazards assumption is violated, the logrank test may not have sufficient power to detect the difference between two event time distributions, and the resulting hazard ratio estimate is difficult, if not impossible, to interpret as a treatment contrast. In this research, we propose a systematic, effective way to identify a promising subpopulation, for which the new treatment is expected to have a desired survival benefit, using the data from a current study involving similar comparator treatments. We illustrate the methods with the data from a randomized clinical trial.

报告人简介:

赵利辉博士是美国西北大学范伯格医学院预防医学系副教授。他于2001和2004年在南开大学获得数学学士和统计硕士学位,并于2009年在加拿大西蒙弗雷泽大学获得统计学博士。之后他加入美国哈佛大学生物统计系做博士后,直到2011年他开始在西北大学范伯格医学院预防医学系做助理教授, 并于2018年升为副教授。赵博士的主要研究领域为生存分析,临床试验设计与分析,以及精准医疗的统计方法。

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