Optimal designs for active controlled dose-finding trials with efficacy-toxicity outcomes

• 成果类型: Article
• 署名作者: Schorning, K.; Dette, H.; Kettelhake, K.; Wong, W. K.; Bretz, F.
• 署名单位: Ruhr University Bochum; University of California System; University of California Los Angeles; Novartis
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asx057
• 发表日期: 2017
• 页码: 10031010
• 关键词: locally optimal designs; la garza phenomenon; nonlinear models; regression; placebo

摘要

We derive optimal designs to estimate efficacy and toxicity in active controlled dose-finding trials when the bivariate continuous outcomes are described using nonlinear regression models. We determine upper bounds on the required number of different doses and provide conditions under which the boundary points of the design space are included in the optimal design. We provide an analytical description of minimally supported optimal designs and show that they do not depend on the correlation between the bivariate outcomes.