Data Management and Statistics Core

数据管理和统计核心

• 批准号: 10474597
• 负责人: Jonathan L Haines
• 金额: $ 32.02万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10474597
• 关键词: Adopted; Agreement; Alzheimer' s Disease; Alzheimer' s Disease Core Center; Alzheimer' s disease related dementia; Area; Biological Markers; Biometry; Clinical; Clinical Data; Collection; Communities; Complication; Computational Biology; Custom; Data; Data Analyses; Data Management Resources; Data Set; Databases; Enrollment; Environment; Error Sources; Family; Foundations; Funding; Generations; Genetic; Genetic Diseases; Genomics; Goals; Human Resources; Image; Individual; Informatics; Infrastructure; Institutes; Institution; Lead; Longitudinal Studies; Machine Learning; Measures; Methods; National Institute on Aging; Neurodegenerative Disorders; Paper; Participant; Policies; Positioning Attribute; Privacy; Procedures; Process; Recording of previous events; Records; Research; Research Design; Research Personnel; Resources; Sampling; Secure; Security; System; Training; Universities; data acquisition; data format; data integration; data management; data mining; data storage site; design; electronic data; electronic data sharing; experience; follow-up; genomic data; human disease; imaging genetics; improved; research study; software infrastructure; statistics; success; virtual

PROJECT SUMMARY The success of research studies in any human disease, but particularly Alzheimer's disease (AD) and AD-related dementias (ADRD), is critically dependent on the collection, generation, management, analysis, and interpretation of large, varied, and detailed data sets. The overall goal of the Data Management and Statistical Core (DMSC) is to empower AD/ADRD researchers to acquire, manage, analyze, and interpret their data. To do this, we leverage existing institutional infrastructure and provide the necessary expertise for the Cleveland Alzheimer's Disease Center (CADRC). This goal will be accomplished through three specific aims. Specific Aim 1 provides a comprehensive data management platform for the collection, aggregation, and management of the relevant data. We will leverage the infrastructure of the Cleveland Institute for Computational Biology (CICB), which has developed a safe and secure computational environment for data capture and management that is available to all the participating institutions (the SHED [Safely Held Electronic Data] data management system). The SHED uses a tier III secure computational environment along with both computational and policy access and privacy controls. The system easily integrates a wide variety of data formats and provides methods for participant and sample tracking for longitudinal studies. Comprehensive training for CADRC personnel is provided. Specific Aim 2 enhances interactivity with the other cores, investigators, and external databases. Through the efforts of the Administrative Core, participating institutions have institutional agreements to capture and share electronic data through the SHED. All investigators and staff across the CADRC institutions have controlled access to the SHED. We have put into place processes internally for interacting with each of the CADRC cores, and externally for interactions with databases and users such as the National Alzheimer's Coordinating Center (NACC) and the National Institute for Aging Genetics of Alzheimer's Disease Data Storage site (NIAGADS). Specific Aim 3 provides biostatistical, study design, and data analysis support to the CADRC. The DMSC provides support for these activities through access to a wide range of expertise including biostatistical (Drs. Tatsuoka and Feng), genomic (Drs. Haines and Feng), and imaging (Dr. Tatsuoka). Dr. Feng also brings expertise in data integration and machine learning to the CADRC. Substantial technical support will be provided by a master's level analyst. The DMSC is well positioned to accommodate the data management and data analysis needs of the CADRC, its investigators, and the broader AD/ADRD research community.

项目摘要 在任何人类疾病，特别是阿尔茨海默病（AD）和 AD相关性痴呆（ADRD）严重依赖于收集、生成、管理、分析和 解释大型、多样和详细的数据集。数据管理和统计的总体目标 核心（DMSC）是使AD/ADRD研究人员能够获取，管理，分析和解释他们的数据。到 为此，我们利用现有的机构基础设施，并为克利夫兰提供必要的专业知识， 阿尔茨海默病中心（CADRC）。这一目标将通过三个具体目标来实现。 Specific Aim 1提供了一个全面的数据管理平台，用于收集、汇总和 管理相关数据。我们将利用克利夫兰计算研究所的基础设施 生物学（CICB），它已经开发了一个安全可靠的计算环境，用于数据采集和 所有参与机构均可使用的管理（SHED [安全持有电子数据]数据 管理系统）。SHED使用第三层安全计算环境，沿着 计算和策略访问以及隐私控制。该系统可轻松集成各种数据 格式，并提供方法，参与者和样本跟踪纵向研究。全面 为CADRC人员提供培训。 Specific Aim 2增强了与其他核心、研究者和外部数据库的交互性。 通过行政核心的努力，参与机构达成了机构协议， 并通过SHED共享电子数据。CADRC机构的所有调查人员和工作人员都已 控制进入棚屋的通道我们已经在内部建立了与每个人互动的流程， CADRC核心，并在外部与数据库和用户（如国家阿尔茨海默氏症 协调中心（NACC）和国家老年痴呆症遗传学研究所数据存储 地点（NIAGADS）。 具体目标3为CADRC提供生物统计、研究设计和数据分析支持。DMSC 通过获得广泛的专业知识，包括生物统计学，为这些活动提供支持。 Tatsuoka和Feng）、基因组（Haines和Feng博士）和成像（Tatsuoka博士）。冯博士还带来了 数据集成和机器学习方面的专业知识。将提供大量技术支持 一个硕士水平的分析师。 数据管理和数据分析中心的定位是很好的，以适应数据管理和数据分析的需要， CADRC，其研究人员和更广泛的AD/ADRD研究社区。