Optimal designs for dose finding studies with an active control

• 成果类型: Article
• 署名作者: Dette, Holger; Kiss, Christine; Benda, Norbert; Bretz, Frank
• 署名单位: Ruhr University Bochum; Novartis; Shanghai University of Finance & Economics
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/rssb.12030
• 发表日期: 2014
• 页码: 265-295
• 关键词: nonparametric-estimation; models; interpolation; Extrapolation; EQUIVALENCE; Maximin; emax

摘要

Dose finding studies often compare several doses of a new compound with a marketed standard treatment as an active control. In the past, however, research has focused mostly on experimental designs for placebo controlled dose finding studies. To the best of our knowledge, optimal designs for dose finding studies with an active control have not been considered so far. As the statistical analysis for an active controlled dose finding study can be formulated in terms of a mixture of two regression models, the related design problem is different from what has been investigated before in the literature. We present a rigorous approach to the problem of determining optimal designs for estimating the smallest dose achieving the same treatment effect as the active control. We determine explicitly the locally optimal designs for a broad class of models employed in such studies. We also discuss robust design strategies and determine related Bayesian and standardized minimax optimal designs. We illustrate the results by investigating alternative designs for a clinical trial which has recently appeared in a consulting project of one of the authors.