A practical approach for eliciting expert prior beliefs about cancer survival in phase III randomized trial
A practical approach for eliciting expert prior beliefs about cancer survival in phase III randomized trial
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DOI：
10.1016/j.jclinepi.2008.04.009
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发表时间：
2009-04-01
影响因子：
7.2
通讯作者：
Levy, Vincent
中科院分区：
文献类型：
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作者：
Hiance, Anne;Chevret, Sylvie;Levy, Vincent
目的：提出并比较实用的方法，允许引出和使用专家意见的好处效果的审查终点，如无事件生存期（EFS），用于规划的临床试验的基础上Bayesian methodology.Study设计和设置：37位专家的个人访谈。对EFS的对数风险比（HR）进行贝叶斯正态模型。我们通过使用自体干细胞移植（ASCT）与化疗（CT）治疗慢性淋巴细胞白血病（CLL）的试验来说明我们的方法。我们引出了专家对两个治疗组之间3年EFS差异的先前信念，无论是粗略的还是在差异量表上的整个重量。随后，对试验方案中报告的信息与专家先前报告的信息进行贝叶斯综合，使用：（1）基于零的假设治疗效果（怀疑）和替代（2）来自专家分布的期望差。结果：与基于试验方案数据的先验相比，专家先验与热情和怀疑信息的平均值一致，标准误接近。结论：本案例研究说明了一种合理的方法来构建基于专家的先验。它应该被认为是未来贝叶斯试验设计的一部分。(C)2009 Elsevier Inc. All rights reserved.
Objective: To propose and compare practical approaches that allow eliciting and using expert opinions about the benefit effect on a censored endpoint, such as event-free survival (EFS), used in the planning of a clinical trial based on Bayesian methodology.Study Design and Setting: Individual interviews of 37 experts. Bayesian normal models on the log hazard ratio (HR) of EFS were implemented. We illustrate our approach by using a trial of autologous stein cell transplantation (ASCT) vs. chemotherapy (CT) in chronic lymphocytic leukemia (CLL). We elicited experts' prior beliefs about the difference in 3-year EFS between the two treatment arms, either roughly or throughout weights over the difference scale. Subsequently, a Bayesian synthesis of the information reported in the trial protocol with that in the experts' prior was performed, using: (1) the postulated treatment effect based on null (skeptical) and alternative (enthusiastic) hypotheses with shared standard error; and (2) the expected difference derived from experts' distributions.Results: As compared with the priors based on the trial protocol data, expert priors agreed with some average from enthusiastic and skeptical information, with close standard errors.Conclusion: This case study illustrates a rational approach to construct an expert-based prior. It should be considered as part of the design of future Bayesian trials. (C) 2009 Elsevier Inc. All rights reserved.