Hierarchical models for sharing information across populations in phase I dose-escalation studies

Author:

Cunanan Kristen M1,Koopmeiners Joseph S2

Affiliation:

1. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA

2. Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA

Abstract

The primary goal of a phase I clinical trial in oncology is to evaluate the safety of a novel treatment and identify the maximum tolerated dose, defined as the maximum dose with a toxicity rate below some pre-specified threshold. Researchers are often interested in evaluating the performance of a novel treatment in multiple patient populations, which may require multiple phase I trials if the treatment is to be used with background standard-of-care that varies by population. An alternate approach is to run parallel trials but combine the data through a hierarchical model that allows for a different maximum tolerated dose in each population but shares information across populations to achieve a more accurate estimate of the maximum tolerated dose. In this manuscript, we discuss hierarchical extensions of three commonly used models for the dose–toxicity relationship in phase I oncology trials. We then propose three dose-finding guidelines for phase I oncology trials using hierarchical modeling. The proposed guidelines allow us to fully realize the benefits of hierarchical modeling while achieving a similar toxicity profile to standard phase I designs. Finally, we evaluate the operating characteristics of a phase I clinical trial using the proposed hierarchical models and dose-finding guidelines by simulation. Our simulation results suggest that incorporating hierarchical modeling in phase I dose-escalation studies will increase the probability of correctly identifying the maximum tolerated dose and the number of patients treated at the maximum tolerated dose, while decreasing the rate of dose-limiting toxicities and number of patients treated above the maximum tolerated dose, in most cases.

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3