Analysis Resource Core

分析资源核心

• 批准号: 10221907
• 负责人: SCOTT L. ZEGER
• 金额: $ 52.73万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10221907
• 关键词: 2019-nCoV; Affect; Age; Biological; COVID-19; COVID-19 pandemic; Clinical; Clinical Research; Collaborations; Data; Disease Progression; Ethnic Origin; Gender; Health Services; Hospitals; Human; Immune; Immune response; Immune system; Immunity; Intervention; Laboratory Study; Measures; Outcome; Pathogenesis; Patients; Race; Registries; Reproducibility; Research; Research Personnel; Research Project Grants; Resources; Role; Severity of illness; Social Impacts; Specific qualifier value; Statistical Data Interpretation; Statistical Methods; Statistical Models; Subgroup; Testing; Therapeutic; Time; Woman; age difference; design; economic impact; ethnic difference; gender difference; immune function; intersectionality; laboratory experiment; men; mortality; precision medicine; racial difference; sex; social

JH-EPICS Analysis Resource Core Summary The JH-EPICS Analysis Resource Core (ARC) will provide statistical modeling and analysis support to investigators in this U54 proposal. In addition, the ARC will provide guidance in the framing and testing of hypotheses about the intersectionality of gender, age, racial, and ethnic differences in immune mechanisms in COVID-19. In both roles, the ARC will assure that the U54 research is valid, transparent, and reproducible. Current evidence shows that the COVID-19 pandemic has differential effects on men and women, including in relation to disease severity and mortality and negative social and economic impacts. It is vital that we explore how sex and gender intersect with other biological and social stratifiers if we are to have effective and appropriate therapeutic treatment and interventions. In its statistical analysis role, the ARC will develop and implement statistical models and methods for comparing longitudinal trajectories among subgroups of the Johns Hopkins COVID-19 registry using multiple measures of immune function. We will support the three Research Projects to devise tests of specific hypotheses about baseline and time-varying factors that affect disease progression. In its intersectionality function, the Core will provide expert guidance to both Projects to test hypotheses about the intersectionality of gender (social construct), sex (biological construct), race, ethnicity, and age differences with the effects of SARS-CoV-2 on the human immune system. In collaboration with the U54 investigators, the ARC will: 1. Acquire, manage, and curate data from laboratory experiments and from the Johns Hopkins CROWN (COVID-19 Precision Medicine Analytics Platform) Registry of all COVID-19 patients who receive health services within the Johns Hopkins network of 5 hospitals. 2. Frame the investigators’ scientific questions in statistical terms, then design laboratory and/or clinical studies that produce the strongest possible evidence to answer the questions posed. 3. Design and implement statistical analyses and collaborate on interpretation of results so as to produce valid, transparent, and reproducible scientific findings. Validity will be assured by distinguishing hypothesis generating from hypothesis testing analyses. Each hypothesis testing analysis will have a pre-specified statistical analysis plan in advance of working with the data. 4. Analyze the role of sex and gender and the intersection of sex and gender with other biological and social stratifiers, such as age, race, and ethnicity, on COVID-19 immunologic responses and clinical outcomes. These analyses will be integrated into Research Projects 1-3.

JH-EPICS分析资源核心摘要 JH-EPICS分析资源核心（ARC）将提供统计建模和分析支持， 在这个U 54提案中的调查员。此外，ARC还将在以下方面提供指导： 关于免疫机制中性别、年龄、种族和民族差异的交叉性的假设， 2019冠状病毒病。在这两个角色中，ARC将确保U 54研究的有效性、透明性和可重复性。 目前的证据表明，COVID-19大流行对男性和女性的影响不同，包括 与疾病严重程度和死亡率的关系以及负面的社会和经济影响。我们必须探索 性和性别如何与其他生物和社会分层因素交叉， 适当的治疗和干预措施。在其统计分析作用中，ARC将开发和 实施统计模型和方法，用于比较 约翰霍普金斯COVID-19登记处使用多种免疫功能指标。我们将支持三个 研究项目：设计关于基线和时变因素的具体假设的测试， 疾病进展。在其交叉性职能中，核心小组将为这两个项目提供专家指导， 测试关于性别（社会结构），性别（生物结构），种族， 种族和年龄差异与SARS-CoV-2对人体免疫系统的影响。合作 与U 54研究人员一起，ARC将：1。从实验室实验中获取、管理和整理数据 以及来自约翰霍普金斯皇冠（COVID-19精准医学分析平台）登记处的所有 在约翰霍普金斯5家医院网络内接受医疗服务的COVID-19患者。2.陷害 研究者的科学问题，然后设计实验室和/或临床研究， 提供最有力的证据来回答所提出的问题。3.设计和实施统计 分析并合作解释结果，以产生有效、透明和可重复的结果 科学发现。通过区分假设生成和假设检验来确保有效性 分析。每项假设检验分析将在 处理数据。4.分析性和性别的作用以及性和性别与 其他生物和社会分层因素，如年龄、种族和民族，对COVID-19免疫学的影响 反应和临床结果。这些分析将纳入研究项目1-3。