Data Management and Analysis Core (DMAC) for the Air pollution disrupts Inflammasome Regulation in HEart And Lung Total Health (AIRHEALTH) Study

空气污染扰乱心肺总体健康 (AIRHEALTH) 研究中炎症小体调节的数据管理和分析核心 (DMAC)

• 批准号: 10684163
• 负责人: MANISHA DESAI
• 金额: $ 7.4万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684163
• 关键词: Address; Air Pollution; Ancillary Study; Area; Bioinformatics; Biological Markers; Biometry; Clinical; Clinical Data; Clinical Research; Clinical Trials Design; Code; Collaborations; Computer software; Custom; Data; Data Analyses; Data Analytics; Data Collection; Data Element; Data Science; Data Set; Databases; Disparate; Ensure; Goals; Health; Health Insurance Portability and Accountability Act; Health protection; Heart; Housing; Human; Human Resources; Inflammasome; Interdisciplinary Study; Internet; Joints; Knowledge; Longitudinal Studies; Lung; Manuscripts; Metadata; Methodology; Modeling; Modernization; Monitor; Participant; Pathology; Patients; Preparation; Production; Program Research Project Grants; Publications; Quality Control; Regulation; Reproducibility; Reproducibility of Results; Research; Research Design; Research Personnel; Research Project Grants; Research Subjects; Resources; Sampling; Science; Secure; Services; Site; Specific qualifier value; Statistical Data Interpretation; Statistical Methods; System; Testing; Work; bioinformatics tool; clinical phenotype; data de-identification; data integration; data integrity; data management; design; electronic data; human tissue; innovation; large datasets; longitudinal analysis; member; programs; quality assurance; sound; time orientation; timeline; tool

ABSTRACT: DATA MANAGEMENT AND ANALYTICS CORE (DMAC) Data Management and Analytics Core (DMAC) and the overall goals that provide support to the Scientific Human Biomarker Exposure Monitoring Core (HEMC) and Projects 1-3 by establishing and maintaining a secure centralized system to house, share, and manage data; designing robust studies; and analyzing clinical, mechanistic, and high-throughput data for the three PPG projects. DMAC will work with the cores and projects to ensure that analyses resulting from clinical and mechanistic study data are performed with integrity and rigor, using compatible definitions and metrics for smooth integration to provide interpretable findings and advance clinical and mechanistic research for the program. Our aims are as follows. Aim 1. Provide a state-of-the-art secure, integrated and interactive database of high-quality data generated by projects in the program that enables wide access to study investigators. The DMAC will build a system in Research Electronic Data Capture (REDCap) to house study data that extends the Parker Center's state-of-the-art biospecimen management software platform to provide a PPG platform that integrates data from Projects 1-3 and the HEMC. REDCap will integrate data from biospecimens collected for this program project with secured, associated patient metadata for research on human tissues. DMAC will conduct quality control for all PPG data and analyses to ensure data elements are clean. Aim 2. Design scientifically sound and robust studies across projects in the program. The DMAC consists of personnel with expertise in designing clinical trials, longitudinal studies, and studies that include mechanistic endpoints. The core will leverage such expertise using a team science-based approach and refining questions and hypotheses that are feasible to develop scientifically sound analysis plans using the most modern statistical tools that lend themselves to interpretable and meaningful findings, and to justify the number of samples and participants necessary to address scientific questions by considering resources available during the specified study timeline. Aim 3. Conduct analyses of clinical, mechanistic, and high throughput data. The DMAC will develop long-term collaborative relationships with PPG investigators by embedding core members into investigators' research teams to lead the data science component of studies. Using a well-established team science-based approach, core members will develop and implement statistical analysis plans to address project aims to assure findings are reproducible. The DMAC will educate PPG investigators in biostatistics and bioinformatics most pertinent to their research to promote effective collaboration in the production of interdisciplinary research publications. Together with the HEMC, the DMAC offers some of the most innovative tools for bioinformatic and statistical analysis of large data sets to make the broadest and most transformative impact in understanding clinical phenotype associations with mechanistic studies in air-pollution-associated pathology.

摘要：数据管理和分析核心（DMAC） 数据管理和分析核心（DMAC）以及为科学提供支持的总体目标 人类生物标志物暴露监测核心（HEMC）和项目1-3通过建立和维护 保护集中式系统以容纳，共享和管理数据；设计强大的研究；并分析临床 三个PPG项目的机械和高通量数据。 DMAC将与核心和项目合作 为了确保通过临床和机械研究数据进行的分析以完整性和严格性进行 使用兼容的定义和指标进行平滑集成以提供可解释的发现并提高 该计划的临床和机械研究。我们的目标如下。目标1。提供最先进的 项目中项目中生成的高质量数据的安全，集成和交互式数据库 可以广泛访问研究人员。 DMAC将在研究电子数据捕获中构建系统 （REDCAP）到达室内研究数据，以扩展帕克中心的最先进的生物传播管理 软件平台提供一个PPG平台，该平台将项目1-3和HEMC的数据集成。 redcap会 将收集的该计划项目的生物测量的数据与有安全的，相关的患者元数据集成 用于人类组织的研究。 DMAC将对所有PPG数据进行质量控制和分析以确保数据 元素很干净。目标2。在该计划中的项目中设计科学的声音和强大的研究。这 DMAC由具有设计临床试验，纵向研究和研究的人员组成 包括机械端点。核心将使用基于团队的科学方法来利用此类专业知识，并 精炼问题和假设，这些问题可行，可以使用最多制定科学的合理分析计划 现代统计工具，可以解释和有意义的发现，并证明数字合理 通过考虑可用的资源来解决科学问题所需的样本和参与者 指定的研究时间表。目标3。进行临床，机械和高吞吐量数据进行分析。这 DMAC将通过嵌入核心成员来与PPG调查人员建立长期合作关系 进入研究人员的研究团队，以领导研究的数据科学组成部分。使用一个公认的团队 基于科学的方法，核心成员将制定和实施统计分析计划以解决项目 确保发现的目的是可重现的。 DMAC将对PPG调查人员进行生物统计学和 生物信息学与他们的研究最相关，以促进有效的合作 跨学科研究出版物。与HEMC一起，DMAC提供了一些最具创新性的 大型数据集的生物信息学和统计分析的工具，以使最广泛，最具变革性 在与空气污染相关的机理研究中了解临床表型关联的影响 病理。