Longitudinal Methods for Cardiovascular Disease Research

心血管疾病研究的纵向方法

• 批准号: 8471762
• 负责人: Robyn Leagh McClelland
• 金额: $ 18.56万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-06-07 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8471762
• 关键词: Accounting; Address; Antihypertensive Agents; Area; Atherosclerosis; Biological Markers; Blood Pressure; Calcified; Calcium; Cardiovascular Diseases; Cardiovascular system; Characteristics; Cholesterol; Clinical; Cohort Studies; Collection; Complex; Coronary artery; Data; Detection; Development; Disease; Disease Progression; Epidemiology; Event; Fostering; Funding; Goals; Grant; HIV; Health; Incidence; Individual; Intervention; Lesion; Lipids; Malignant Neoplasms; Measurement; Measures; Methodology; Methods; Modeling; Names; National Heart, Lung, and Blood Institute; Outcome; Participant; Patients; Pharmaceutical Preparations; Probability; Process; Reading; Research; Research Personnel; Risk; Risk Factors; Scanning; Statistical Methods; Stratification; Techniques; Technology; Time; United States National Institutes of Health; X-Ray Computed Tomography; base; cardiovascular risk factor; cohort; design; disorder risk; heart imaging; improved; innovation; interest; model development; novel; prospective; tool

DESCRIPTION (provided by applicant): The study of cardiovascular disease (CVD) is complex and involves rapidly evolving technologies that enable detection and quantification of subclinical disease over time. Improved analysis of cardiovascular cohort data will result in better identification of epidemiological predictors of cardiovascular disease, improved risk stratification and fewer misleading studies due to inappropriate analysis. The aims of this project are designed to address current methodological problems facing cardiovascular disease researchers. Our goal is to develop novel statistical tools that can help answer new scientific questions using data that has previously been collected by existing NIH-funded studies. We will illustrate our methods with data from two NHLBI-funded prospective cohort studies: The Multi-Ethnic Study of Atherosclerosis (MESA) and The Cardiovascular Health Study (CHS), although the methods and models are generally applicable to many studies. Our grant will address statistical problems across two broad aspects of cardiovascular research where innovative analysis will allow for better use of the information contained in cardiovascular cohort studies. First, we propose new models to handle the methodologic challenge of medication use when studying biomarker associations. Secondly, we develop improved methods for analysis of coronary artery calcium that allow us make better use of the information from existing scans.

描述（由申请人提供）：心血管疾病（CVD）的研究很复杂，涉及迅速发展的技术，可以随着时间的推移检测和定量亚临床疾病。改进的心血管队列数据分析将使人们更好地识别心血管疾病的流行病学预测因素，改善风险分层以及由于不适当的分析而导致的误导性研究较少。该项目的目的旨在解决心血管疾病研究人员面临的当前方法论问题。我们的目标是开发新颖的统计工具，可以使用现有的NIH资助研究以前收集的数据来帮助回答新的科学问题。我们将使用来自NHLBI资助的前瞻性队列研究的数据来说明我们的方法：动脉粥样硬化的多种族研究（MESA）和心血管健康研究（CHS），尽管这些方法和模型通常适用于许多研究。我们的赠款将解决心血管研究的两个广泛方面的统计问题，在该问题中，创新分析将使您可以更好地利用心血管同伴研究中包含的信息。首先，我们建议在研究生物标志物关联时处理用药使用方法的新模型。其次，我们开发了改进的分析冠状动脉钙的方法，使我们可以更好地利用现有扫描中的信息。