Optimizing Outcome Measures for Clin. Trials in Pre-Clinical Alzheimer's Disease

摘要 该补助金将开发统计方法，用于获得临床试验和纵向研究的最佳终点。 认知老化，轻度认知障碍和阿尔茨海默病的队列研究，并将发表新的 使用这些方法获得的统计学上有效的临床试验结果测量。有待制定的方法 这笔赠款将大大提高临床试验的效率，降低成本，增加 确定有效治疗的可能性。具体目标是： 具体目标1。推导并应用仪器总分的最佳计算方法。 这是我们早期工作的延伸，使用项目反应理论来找到项目的最佳评分， 计算仪器总分。我们早期的工作是在横截面数据上训练重新评分算法。 该扩展将在纵向数据上进行训练。我们的试验数据表明， 通过拟定方法选择手术工具所需的样本量。 具体目标2。推导并应用复合量表的最佳构建方法。 结合认知和功能测量的复合量表有望显着提高效率 轻度认知障碍的临床试验，是一个活跃的研究领域。我们得出了一个最佳的 公式，并可以证明上级性能相对于当前的方法与真实的数据和模拟。 具体目标3。通过应用所开发的方法来证明重新制定结局指标 在目的1和2中，将其用于不同但相关的进行性疾病，额颞叶痴呆（FTD）。 这项工作旨在证明我们的方法对其他疾病领域的普遍适用性。此外，委员会认为， 在执行本赠款开发的软件将公布的方法，并将 适用于任何慢性疾病的仪器开发，其数量性状用作 临床试验的终点。 这项拨款完全是出于观察慢性进行性疾病的临床试验是 昂贵得令人望而却步。在阿尔茨海默病研究中，这限制了我们测试新疗法的能力， 找到治愈这种疾病的方法对于不太常见的疾病，如FTD和进行性核上性麻痹， 随着临床试验研究对象的可用性， 进一步限制了我们测试治疗方法的能力。参加临床试验的每个受试者都是宝贵的资源。这 赠款旨在促进方法，以最佳方式利用从参加研究的受试者获得的所有信息。 临床试验，并增加确定有效治疗的可能性。

ABSTRACT This grant will develop statistical methods for deriving optimal endpoints for clinical trials and longitudinal cohort studies of cognitive aging, mild cognitive impairment, and Alzheimer's disease, and will publish new statistically efficient clinical trial outcome measures derived using these methods. Methods to be developed in this grant will substantially improve the efficiency of clinical trials, reducing the cost and increasing the probability that effective treatments will be identified. The Specific Aims are: Specific Aim 1. To derive and apply methods for optimal calculation of instrument total scores. This is an extension of our earlier work using Item Response Theory to find the optimal scoring of items when calculating an instrument total score. Our earlier work trained the rescoring algorithm on cross-sectional data. The extension will be to train on longitudinal data. We have pilot data demonstrating a 25% reduction in required sample size for select instruments by the proposed method. Specific Aim 2. To derive and apply methods for optimal construction of composite scales. Composite scales combining cognitive and functional measures promise to dramatically improve the efficiency of clinical trials of mild cognitive impairment and is an area of active research. We have derived an optimal formula and can demonstrate superior performance relative to current methods with real data and simulations. Specific Aim 3. To demonstrate de novo outcome measure development by applying the methods developed in Aims 1 and 2 to a different but related progressive disease, frontotemporal dementia (FTD). This exercise is intended to demonstrate the generalizability of our methods to other disease areas. Moreover, software developed in performance of this grant will be posted as the methods are published and will be applicable to instrument development for any chronic disease for which quantitative traits are used as endpoints for clinical trials. This grant is entirely motivated by the observation that clinical trials of chronic progressive disease are prohibitively expensive. In Alzheimer's disease research this has limited our ability to test new treatments and find a cure for the disease. For less common diseases such as FTD and progressive supranuclear palsy the need for more efficient endpoints is even more pressing, as the availability of study subjects for clinical trials further limits our ability to test treatments. Every subject enrolled in a clinical trial is a precious resource. This grant is intended to advance methods to optimally utilize all information obtained from subjects enrolled in clinical trials and increase the probability that effective treatments are identified.