Do Bayesian Adaptive Trials Offer Advantages for CER?

贝叶斯自适应试验是否为 CER 提供优势？

• 批准号: 8036399
• 负责人: C. DANIEL MULLINS
• 金额: $ 149.99万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-20 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8036399
• 关键词: Address; Antihypertensive Agents; Berry; Cardiovascular Diseases; Cardiovascular system; Case Study; Clinical; Clinical Trials; Clinical Trials Design; Collaborations; Combined Modality Therapy; Data; Data Collection; Decision Making; Drops; Event; Evidence Based Medicine; Feedback; Future; Generations; Goals; Health; Healthcare Systems; Institute of Medicine (U.S.); Knowledge; Lead; Learning; Marketing; Measures; Medical; Medical Device; Methodology; Methods; Nature; Outcome; Patient Care; Patients; Performance; Policies; Population Heterogeneity; Principal Investigator; Randomized; Randomized Clinical Trials; Reporting; Research; Research Infrastructure; Risk; Safety; Sample Size; Series; Simulate; Source; Specific qualifier value; Sum; Testing; Time; Uncertainty; United States; active comparator; alternative treatment; base; clinical practice; clinically relevant; comparative effectiveness; comparative trial; cost; design; effectiveness research; experience; improved; innovation; insight; patient oriented; prevent; prospective; public health relevance; simulation; standard of care; statistics; systematic review; treatment strategy

DESCRIPTION (provided by applicant): We propose an innovative approach to designing and conducting randomized clinical trials (RCTs) for comparative effectiveness research (CER). Evidence from "pragmatic" RCTs can inform real-world decisions by comparing clinically relevant alternatives across a wide array of patient-centric outcomes in typical patient care settings serving diverse populations. Unfortunately, they typically increase the time and cost compared to the "explanatory" trials used to gain marketing approval. One example of a well designed and executed active comparator trial was the ALLHAT study, which cost over $130 million and took more than five years to complete. ALLHAT was very informative, yet raises the question of whether future trials of this nature could be designed more efficiently. Without alterations to how trials in the United States are conceived, designed, conducted, and analyzed, the nation risks spending large sums of money answering questions that are less impactful on clinical and policy decision making due to delayed reporting or incomplete comparisons. Bayesian adaptive RCT designs can reduce the sample size, time, and cost of obtaining decision-relevant information by formally incorporating external evidence and incorporating prospectively defined adaptations in order to focus the data collection on the primary aims. Despite successful use in regulatory trials, Bayesian adaptive methods have not yet been rigorously applied to pragmatic CER trials. We believe that exploring their value through a "proof of concept" will enhance scientific knowledge and help overcome the methodological inertia that tends to prevent the use of innovative approaches. Aim 1 is to demonstrate the applicability of Bayesian adaptive clinical trial design methods for CER by developing a series of 18 potential re-designs of the ALLHAT study. This aim includes a systematic review of evidence that was available prior to when ALLHAT was designed to inform the generation of "priors," which reflect probabilistic representations of what was known or hypothesized regarding antihypertensive treatments and includes designing adaptive features. Aim 2 is to evaluate the efficiency and performance of Bayesian adaptive designs through simulation using actual ALLHAT patient data. Aim 3 is to develop a clinically-motivated decision theoretic approach to Bayesian adaptive designs to address additional relevant research questions. The result will be a demonstration of the benefits - as well as some of the trade-offs - of a Bayesian adaptive approach to CER trial design and analysis. PUBLIC HEALTH RELEVANCE: CER is intended to help patients, prescribers, and other medical decision makers select the most appropriate treatments. Traditional clinical trials have strong internal validity, but may not be ideal for decision makers considering alternative treatments that were not "standard of care" when the clinical trial was designed. Bayesian adaptive clinical trial designs introduce efficiencies that retain internal validity while enabling active comparative trials to capture relevant and timely evidence to improve decision making that significantly impacts patients' health and safety.

描述（由申请人提供）：我们提出了一种创新的方法来设计和实施比较有效性研究（CER）的随机临床试验（rct）。来自“实用”随机对照试验的证据可以通过比较临床相关的替代方案，在为不同人群服务的典型患者护理环境中以患者为中心的结果。不幸的是，与用于获得市场批准的“解释性”试验相比，它们通常会增加时间和成本。设计和执行良好的主动比较试验的一个例子是ALLHAT研究，该研究耗资1.3亿多美元，花了五年多时间才完成。ALLHAT提供了非常丰富的信息，但提出了一个问题，即是否可以更有效地设计这种性质的未来试验。如果不改变美国试验的构思、设计、实施和分析方式，国家就有可能花费大量资金来回答由于报告延迟或比较不完整而对临床和政策决策影响较小的问题。贝叶斯自适应RCT设计可以通过正式纳入外部证据和纳入前瞻性定义的适应来减少样本量、时间和获取决策相关信息的成本，以便将数据收集集中在主要目标上。尽管在监管试验中成功使用，贝叶斯自适应方法尚未严格应用于实用的CER试验。我们认为，通过“概念验证”来探索它们的价值将增强科学知识，并有助于克服方法论上的惯性，这种惯性往往会阻碍创新方法的使用。目的1是通过对ALLHAT研究进行一系列18个可能的重新设计，来证明贝叶斯自适应临床试验设计方法在CER中的适用性。这一目标包括对设计ALLHAT之前可获得的证据进行系统回顾，以告知“先验”的产生，“先验”反映了已知或假设的降压治疗的概率表示，并包括设计适应性特征。目的2是通过模拟使用实际ALLHAT患者数据来评估贝叶斯自适应设计的效率和性能。目的3是为贝叶斯自适应设计开发一种临床动机决策理论方法，以解决其他相关研究问题。结果将证明贝叶斯自适应方法对CER试验设计和分析的好处——以及一些权衡。

项目成果

Do Bayesian adaptive trials offer advantages for comparative effectiveness research? Protocol for the RE-ADAPT study.

• DOI: 10.1177/1740774513497293
• 发表时间: 2013-10
• 期刊: Clinical trials (London, England)
• 作者: Connor JT;Luce BR;Broglio KR;Ishak KJ;Mullins CD;Vanness DJ;Fleurence R;Saunders E;Davis BR
• 通讯作者: Davis BR