Multicenter Bayesian Decision-Theoretic Clinical Trials

多中心贝叶斯决策理论临床试验

• 批准号: 7221505
• 负责人: ARI M LIPSKY
• 金额: $ 6.27万
• 依托单位: LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7221505
• 关键词: Acute; Address; Characteristics; Clinical Trials; Clinical Trials Design; Communities; Computer software; Data; Decision Analysis; Elements; Enrollment; Expert Opinion; Individual; Internet; Literature; Methods; Numbers; Outcome; Patients; Performance; Randomized; Rate; Sample Size; Sampling; Scheme; Solutions; Testing; Therapy Clinical Trials; Time; Toxicant exposure; Treatment Failure; Work; Writing; comparative; cost; design; loss of function; simulation; software systems; web interface; web-enabled

DESCRIPTION (provided by applicant): Designing, implementing, and interpreting clinical trials of therapies for the treatment of unusual but devastating acute illnesses (e.g., toxic exposures, envenomations) is difficult: eligible subjects are scarce; continuing to randomize patients evenly while comparative evidence on efficacy accumulates may not be ethical; and the proper interpretation of limited data may require expert opinion or external information. Further, the decision to terminate the trial at an interim analysis may be best addressed using decision analysis. Our broad objective is to develop Bayesian decision-theoretic clinical trial designs which use partially adaptive allocation to maximize patient benefit. Specific aims are: (1) to delineate the operational characteristics of these decision-theoretic trial designs; (2) to investigate numerical methods for more computationally efficient trial design; and (3) to construct web-enabled applications for the elicitation and synthesis of expert opinion and for the real-time distributed conduct of adaptive trials. The characteristics of trial designs generated will be tested by both Monte Carlo simulation and through the use of publicly-available software (WinBUGS). Optimal trial designs will be compared to designs obtained using more computationally efficient approximate methods (e.g., forward search methods). When this work is complete, the modular software system will be publicly available for the design and implementation of adaptive Bayesian clinical trial designs. Dr. Lipsky will concurrently serve as a statistical consultant for interdepartmental clinical trials, under the guidance of Dr. Lewis, to further his abilities in trial design and analysis.

描述（由申请人提供）：设计、实施和解释治疗不寻常但具有破坏性的急性疾病（例如，有毒物质暴露，中毒）的临床试验是困难的：符合条件的受试者很少；在有关疗效的比较证据不断积累的情况下，继续均匀地随机分配患者可能不符合伦理；对有限数据的正确解释可能需要专家意见或外部信息。此外，在中期分析中终止试验的决定可能最好使用决策分析来解决。我们的广泛目标是发展贝叶斯决策理论临床试验设计，使用部分适应性分配来最大化患者利益。具体目标是：(1)描述这些决策理论试验设计的操作特征；(2)研究提高试验设计计算效率的数值方法；(3)构建基于网络的应用程序，以获取和综合专家意见，并进行实时分布式的适应性试验。生成的试验设计的特性将通过蒙特卡罗模拟和使用公开可用的软件（WinBUGS）进行测试。将最优试验设计与使用计算效率更高的近似方法（例如，前向搜索方法）获得的设计进行比较。当这项工作完成后，模块化软件系统将公开用于自适应贝叶斯临床试验设计的设计和实施。在Lewis博士的指导下，Lipsky博士将兼任跨部门临床试验的统计顾问，以进一步提高他在试验设计和分析方面的能力。