Synthesis of Longer-Term Alzheimer Disease Studies in Order to Model and Improve

描述(由申请人提供)：在过去的几十年里，阿尔茨海默病(AD)和轻度认知障碍(MCI)的2期和3期临床试验通常都不成功。疗效主要表现在6个月或更短的试验中，仅对轻度AD使用胆碱酯酶抑制剂，而不是在MCI或更长期的试验中。最近基于阿尔茨海默病神经病理学的治疗在18个月的试验中没有显示出疗效。虽然这可能反映了对生物靶标缺乏了解，从而导致对无效药物的测试，但它也反映了试验方法的不足，即如果进行测试，可能不会承认效果不太好的药物。特别是，这些试验似乎是基于对预期特征和结果的假设来选择患者样本，而这些假设可能是无效的，因为它们是基于从之前的个别试验中挑选出来的经验，进一步引发了对设计和有效性的质疑。该项目的广泛和长期目标是基于对先前试验的系统评估和前瞻性地测试设计特征，为设计试点和第二阶段试验开发合理的基础。一个更广泛的目标是通过为临床试验方法和设计提供模型和模拟来鼓励、补充和加速测试新的和创新的治疗方法的过程。实现这些目标的研究设计和方法包括将过去十年来自NIA的ADCS和ADNI的14项临床试验和研究的患者数据整合到一个通用数据库中--其中包括从1到4年的跟踪调查的5200多项。这允许使用基于假设的统计技术进行前瞻性分析，包括模拟，以更好地了解设计参数和结果，并设计更好和更具临床相关性的试验，这些试验将具有检测变化的能力。ADCS研究具有内在的相似性，可以结合在一起，包括共同的数据库结构、结果、地点、培训和程序。专家指导委员会制定指导原则和基于假设的研究计划。具体的方案涉及选择标准、衰退预测因素和评估新试验设计的模拟等问题。例如，我们将使用回归估计和回归到平均调整后的估计来检验基于伴随药物或严重程度选择患者进行试验对结果的影响，并在此之后进行试验模拟，以经验地测试有效性并计划未来的试验。这项研究的结果将对这一治疗领域的试验设计产生广泛和持久的影响，特别是对早期试验，因为设计可以在实施试验之前进行测试和改进。该项目具有很高的创新性，因为它在这一研究领域提供了新的方法来检查来自众多研究的潜在患者数据，并利用丰富的数据库来经验性地探索当前试验所依据的假设。这将导致试验方法的改进，并增加在开发早期确定有效治疗方法的可能性。 公共卫生相关性：这项研究的结果将对阿尔茨海默病、轻度认知障碍和神经退行性疾病的试验设计以及以改善认知为目标的试验产生广泛和持久的影响。它将解决作为设计决策基础的假设中的重要问题。这将导致对未来临床试验方法的更好理解和改进，并提高确定有效治疗方法的可能性，以及在开发早期确定无效治疗方法的可能性。

DESCRIPTION (provided by applicant): Phase 2 and 3 clinical trials in Alzheimer disease (AD) and mild cognitive impairment (MCI) have been generally unsuccessful over the past decades. Efficacy mainly has been demonstrated in trials of 6 months or less, only with cholinesterase inhibitors for mild AD, and not in MCI or longer-term trials. Recent therapies based on the neuropathology of AD have not demonstrated efficacy in 18 month trials. Although this may reflect lack of knowledge of the biological targets and consequently the testing of ineffective drugs, it also reflects inadequacies of trials methods such that a modestly effective drug - if tested - may likely not be recognized as effective. In particular, the trials appear to choose patient samples based on assumptions about desired characteristics and outcomes that may not be valid because they are based on selected experiences from previous individual trials, further raising questions about design and validity. This project's broad, long-term objectives are to develop rational bases for designing pilot and phase 2 trials based on systematic evaluation of previous trials and testing design features prospectively. A broader goal is to encourage, complement, and accelerate the process of testing new and innovative treatments by providing models and simulations for clinical trials methods and designs. The research design and methods for achieving the objectives involves integrating patient data from 14 clinical trials and studies from the NIA's ADCS and ADNI over the last decade - including over 5200 followed from 1 to 4 years - into a common database. This allows for prospective analyses using hypothesis-based statistical techniques including simulations to better understand design parameters, outcomes, and to design better and more clinically relevant trials that would have the ability to detect change. The ADCS studies have inherent similarities that allow for combining, including common data base structures, outcomes, sites, training, and procedures. An expert steering committee formulates guiding principles and hypothesis-based research plans. Specific protocols address issues such as selection criteria, predictors of decline, and simulations to assess new trials designs. For example, we will examine the effects on outcomes of selecting patients for trials based on concomitant medication or severity using regression estimates and regression to the mean adjusted estimates, and follow this with trials simulations to empirically test validity and to plan future trials. Results of this research will have broad and lasting impact on trials designs in this therapeutic area, and especially on early phase trials in that designs can be tested and refined prior to implementing trials. The project is highly innovative in that it provides new approaches in this research area to examine the underlying patient data from numerous studies, and takes advantage of the rich database to empirically probe the assumptions under which current trials have been instigated. This will lead to improvement in trials methods and increase the likelihood for identifying effective treatments earlier in development. PUBLIC HEALTH RELEVANCE: The results of this research will have a broad and lasting impact on trial designs for Alzheimer disease, mild cognitive impairment, and neurodegenerative disorders, and trials in which cognitive improvement is a targeted outcome. It will address important issues in the assumptions underlying the design decisions. This will lead to better understanding and improvement in the methods for future clinical trials and improve the likelihood for identifying effective treatments, as well as identifying ineffective treatments earlier in development.