期刊
CLINICAL TRIALS
卷 6, 期 3, 页码 205-216出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/1740774509104992
关键词
-
资金
- National Cancer Institute [CA16672]
Background The Bayesian approach is being used increasingly in medical research. In particular, it has become a standard in designing clinical trials at the University of Texas M. D. Anderson Cancer Center. Purpose/Methods To address the extent and nature of Bayesian trials conducted at M. D. Anderson, we reviewed the protocols registered in the Protocol Document Online System between 2000 and early 2005. We summarize our findings and give details for three innovative trials that typify those in which a Bayesian approach has played a major role at the center. Results Of 964 protocols reviewed, 59% were conducted solely at M. D. Anderson and the rest were multicenter trials. Bayesian designs and analyses were used in about 20% (195/964) of the protocols that we reviewed. Of the 520 protocols identified as phase I or II drug trials, about 34% were Bayesian. Most of the 195 Bayesian trials were designed by M. D. Anderson statisticians. The Bayesian design features most commonly used were the continuous reassessment method in phase I (toxicity) trials, adaptive randomization in phase II trials, and designs to monitor efficacy and toxicity simultaneously. We also provide an insider's view regarding some practical considerations that have made the design and implementation of so many Bayesian trials possible. Limitations We reviewed only a subset of all M. D. Anderson protocols, but did not exclude any available in electronic form. Conclusions The large number of Bayesian trials conducted at M. D. Anderson testifies to the receptivity to the Bayesian approach within the center, including principal investigators, regulatory review committees, and patients. Statisticians who take a Bayesian perspective can successfully work to establish a culture of innovation in clinical trial design. Clinical Trials 2009; 6: 205-216. http://ctj.sagepub.com
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据