Practical Bayesian design and analysis for drug and device clinical trials
Practical Bayesian design and analysis for drug and device clinical trials
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DOI：
10.1080/10543400701668266
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发表时间：
2008-01-01
影响因子：
1.1
通讯作者：
Carlin, Bradley P.
中科院分区：
文献类型：
--
作者：
Hobbs, Brian P.;Carlin, Bradley P.
也许贝叶斯方法对卫生保健评估的最有价值的贡献涉及研究设计。药物和医疗器械临床试验者越来越多地面临具有复杂相关结构的数据，并且成本高昂且难以获得。在这种情况下，贝叶斯试验设计是有吸引力的，因为它们可以结合历史数据或已发表文献的信息，从而节省时间和费用，并最大限度地减少暴露于劣效治疗的受试者数量。贝叶斯设计还可以适应方案中的意外变化，并允许研究者在任何患者入组试验之前探索各种结局场景的可行性。最近，FDA器械中心鼓励采用分层贝叶斯统计方法，以便将此类有价值的历史数据纳入新器械试验的设计和分析中。这些方法的实际应用在过去十年中才变得可行，这是由于通过马尔可夫链蒙特卡罗（MCMC）方法计算的进步，特别是在流行的BUGS软件包中实现的。在本文中，我们说明了贝叶斯分析和样本量计算使用BRugs，从R调用BUGS函数。我们提供的插图在两个应用环境中，纳入现有的历史信息是至关重要的，一个关于艾滋病药物试验和其他左心室辅助装置（LVAD）的比较。
Perhaps the most valuable contribution of Bayesian methods to health care evaluation involves study design. Drug and medical device clinical trialists are increasingly confronted with data that feature complex correlation structures, and are costly and difficult to obtain. In such settings, Bayesian trial designs are attractive since they can incorporate historical data or information from published literature, thus saving time and expense and minimizing the number of subjects exposed to an inferior treatment. Bayesian designs can also adapt to unexpected changes in the protocol, and allow the investigator to explore the plausibility of various outcome scenarios before any patients are enrolled in the trial. Recently, the FDA Center for Devices has encouraged hierarchical Bayesian statistical approaches which allow for the incorporation of such valuable historical data into the design and analysis of new device trials. The practical application of these methods has only become feasible in the last decade due to advances in computing via Markov chain Monte Carlo (MCMC) methods, especially as implemented in the popular BUGS software package. In this paper we illustrate Bayesian analysis and sample size calculations using BRugs, a function for calling BUGS from R. We provide illustrations in two applied settings where incorporation of available historical information is crucial, one concerning an AIDS drug trial and the other a comparison of left ventricular assist devices (LVADs).