Analytic Core (Core D)

摘要：核心D-分析核心。严谨地整合、分析和解释广泛的 来自核心和项目的数据分析是哈佛大学老龄化大脑研究(HABS)的核心。数据核心 为这些功能提供数据库和统计支持。核心已经开发和优化：(一) 用于数据输入、质量保证、存储、备份、安全和查询系统的DataCentral数据库，如 以及与原始和经过处理的图像文件的链接，(2)生物统计分析的数据分发，以支持 项目目标，以及(Iii)防止无意中的偏见而致盲。核心还支持、设计和实现 有助于定义和量化危重疾病病理、脑网络、 生物标志物及其相互作用，并参与选择样本的子集以进行额外的 程序或具体分析，根据需要。我们还开发了大脑病理的汇总测量方法 可用于项目内部和跨项目的各种分析的网络中断，解决方法 需要对老化大脑中的多个非线性过程进行事件间隔时间和纵向分析， 并开发模型来解决因果推理的问题。数据核心的具体目标是：1.数据 完整性和一体化，包括数据录入、质量控制和存储；数据访问和分发； 和数据共享；2.统计支持、监督和分析，这涉及对 项目和核心，包括模拟指导的研究设计和数据分析，以及使用现代 因果推断中的流行病学方法为模型构建、中介分析和调整提供信息 3.发展创新的统计模型和方法，其中 包括PIB、FTP、功能连通性和认知测量的联合建模；错位的治疗 生物标记物测量.对延迟输入进行调整的经审查的事件间隔数据的模拟.导出 有效预防试验人群和终点；开发新的方法来调整 变化中变化分析设置中的选择偏差。总体而言，数据的首要责任 核心是：管理项目中继续收集的庞大而复杂的数据阵列，包括 神经影像数据、临床数据、基因和生物流体数据；将所有数据元素集成到一个数据库中； 并使用最佳分析来监督和促进每个项目以及跨项目的统计分析 方法：研究方法。分析核心支持将确保计划项目实现公正和稳健的结果， 提高对阿尔茨海默病病程的理解，并将其转化为未来有效的临床 审判。

SUMMARY: CORE D- ANALYTIC CORE. The rigorous integration, analysis and interpretation of a wide array of data from the Cores and Projects is central to the Harvard Aging Brain Study (HABS). The Data Core provides the database and statistical support for these functions. The Core has developed and optimized: (i) the DataCentral database for data entry, quality assurance, storage, backup, security, and query systems, as well as linkage to raw and processed image files, (ii) data distribution for biostatistical analyses to support the project aims, and (iii) blinding to prevent inadvertent bias. The Core also supports, designs, and implements analyses that contribute to the definition and quantification of critical disease pathologies, brain networks, biomarkers, and their interactions, and participates in the selection of subsets of the sample for additional procedures or specific analyses, as needed. We also develop summary measures of brain pathologies and network disruption that can be used in a wide variety of analyses within and across projects, address methods needed for time-to-event and longitudinal analyses across multiple nonlinear processes within the aging brain, and develop models to address questions of causal inference. The Specific Aims of the Data Core are: 1. Data Integrity and Integration, which includes data entry, quality control, and storage; data access and distribution; and data sharing; 2. Statistical Support, Oversight, and Analysis, which involves statistical support for the Projects and Cores including simulation-guided study design and data analysis, and use of modern epidemiologic methods in causal inference to inform model construction, mediation analyses, and adjustment for selection bias and confounding, and 3. Development of Innovative Statistical Models and Methods, which includes joint modeling of PiB, FTP, functional connectivity and cognitive measures; treatment of misaligned biomarker measurements; modeling of censored time-to-event data that adjusts for delayed entry; derivation of efficient prevention trial populations and endpoints; and development of new methods for adjusting for selection bias in the setting of change-in-change analyses. Overall, the overarching responsibilities of the Data Core are to: manage the large and complex array of data that continues to be collected in the project, including neuroimaging data, clinical data, genetic, and biofluid data; integrate all data elements into a single database; and oversee and facilitate the statistical analyses for each Project--and across projects--using optimal analytic methods. Analytic Core support will ensure that the Program Project achieves unbiased and robust results that improve understanding of the course of Alzheimer’s disease and its translation into future efficient clinical trials.