样本量测定
选择(遗传算法)
计算机科学
阶段(地层学)
随机对照试验
临床试验
相(物质)
多重比较问题
样品(材料)
统计
医学
数学
人工智能
外科
内科学
生物
古生物学
色谱法
有机化学
化学
出处
期刊:Clinical Trials
[SAGE Publishing]
日期:2005-02-01
卷期号:2 (1): 5-12
被引量:8
标识
DOI:10.1191/1740774505cn061oa
摘要
Randomized phase II clinical trials can be an efficient means of evaluating several potential new treatments prior to a comparative phase III clinical trial. However, selection designs do not allow for an assessment of minimal efficacy, nor do they allow early closing of a study arm for lack of efficacy, and so are only appropriate when all arms have met minimal efficacy requirements. Classic two-stage hypothesis testing based designs such as a Simon two-stage optimal design can satisfy these requirements, when used in parallel for the multiple treatment arms. However, these can be inefficient and impractical in terms of the maximum planned sample size required for such a study. This article proposes a two-stage randomized phase II clinical trial, where the sample size is adaptive at the second stage to the number of treatment arms passing through the first stage. The study design relies on optimality criteria, which are analogous to those used by Simon for single-arm studies. The proposed design maintains similar operating characteristics to a strategy of using multiple single-arm studies, in most situations of primary interest. Furthermore, it generally has smaller actual sample size when most of the treatments are effective than using multiple single-arm studies, leading to substantial efficiencies in terms of maximum planned sample size.
科研通智能强力驱动
Strongly Powered by AbleSci AI