Permutation Test Software for Randomized Clinical Trials

用于随机临床试验的排列测试软件

• 批准号: 6444337
• 负责人: Jonathan Levine
• 金额: $ 36.24万
• 依托单位: LINCOLN TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-04-01 至 2004-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6444337
• 关键词: artificial intelligence; clinical trials; computer human interaction; computer program /software; computer system design /evaluation; experimental designs; human data; mathematics; statistics /biometry

The randomized clinical trial (RCT) is arguably the linchpin of the drug development process, and the results of an RCT are almost always analyzed using some form of statistical hypothesis test. The most frequently used hypothesis tests assume a population model for statistical inference, even though a randomization model is more consistent with real-world characteristics of RCTs. Approximate p- values returned by population-model tests can, under certain circumstances, be misleading, resulting in effective drugs being declared ineffective, or ineffective drugs being declared effective. To support analysis of RCTs using the appropriate randomization model, sophisticated software for conducting randomization-based permutation tests is needed. Ongoing advances in computing technology have created a favorable climate for widespread use of such software. The goal of this research is to develop flexible and robust software for carrying out randomization-based permutation tests for single- or multi- clinic RCTs. A subset of this functionality has been successfully implemented in a Phase I pre-prototype ("RTAnalyzer"). Phase II seeks to build a full-scale prototype capable of handling a wide variety of trial designs, including designs using adaptive randomization. The Phase II project includes collaborations with two experts in the field of permutation testing: Dr. William Rosenberger and Dr. Bonnie LaFleur. PROPOSED COMMERCIAL APPLICATION: Software that can use general permutation tests to analyze clinical trial data would have clear commercial value to clinical research organizations in academia, Government, and the pharmaceutical, biotechnology, and medical device industries. Key applications are the analysis of clinical trials with unusual randomization schemes, trials with unusual patterns of treatment response, and trials where standard distributional assumptions are invalid.

随机临床试验（RCT）可以说是药物开发过程的关键，RCT的结果几乎总是使用某种形式的统计假设检验进行分析。最常用的假设检验假设一个群体模型进行统计推断，即使随机化模型更符合RCT的真实特征。在某些情况下，群体模型检验返回的近似p值可能会产生误导，导致有效药物被宣布为无效，或无效药物被宣布为有效。为了支持使用适当的随机化模型对RCT进行分析，需要用于进行基于随机化的排列检验的复杂软件。计算技术的不断进步已经为这种软件的广泛使用创造了有利的环境。本研究的目标是开发灵活和强大的软件，用于对单诊所或多诊所RCT进行基于随机化的排列检验。该功能的一个子集已在第一阶段预原型（“RTAnalyzer”）中成功实现。第二阶段旨在建立一个全面的原型，能够处理各种各样的试验设计，包括使用自适应随机化的设计。第二阶段项目包括与置换测试领域的两位专家合作：William Rosenberger博士和Bonnie LaFleur博士。拟定商业应用：可以使用通用排列测试来分析临床试验数据的软件对学术界、政府以及制药、生物技术和医疗器械行业的临床研究组织具有明显的商业价值。主要应用是分析具有不寻常的随机化方案的临床试验，具有不寻常的治疗反应模式的试验，以及标准分布假设无效的试验。