Gout and Cardiovascular Comorbidities: Disentangling the Interplay with Advanced Methods to Address Measurement Issues

Yoshida，K. - 痛风和心血管合并症：用先进的方法解决测量问题。2019 - 11 - 01 - 01 项目摘要 候选人：我是一名副流行病学家，也是临床科学部医学讲师。 布里格姆妇女医院（BWH）和哈佛医学院的流变学、炎症和免疫学 学校（HMS）。我的长期目标是发展一个独立的研究事业，作为一个以病人为导向的研究者 有助于风湿性疾病临床研究的方法学进步。我有一个记录， 严格的定量方法的应用、发展和传播。我的背景包括 临床流变学、药物流行病学和生物统计学。这种指导性的研究经验将整合 我在临床研究中的方法研究技能，重点关注痛风和心血管（CV）合并症。我 将接受丹尼尔博士的指导。所罗门是一位成熟的患者结局研究者，他在以下方面拥有专长： 风湿性疾病，包括痛风，以及一个专家共同导师组成的团队博士。 （方法学），Brendan M.埃弗雷特（CV流行病学）和Hyon K. Choi（痛风流行病学）。 环境：我得到了BWH部门和部门的大力支持，确保85%的时间得到保护 在5 - 10年期间，就所述项目进行与拟议项目有关的研究和职业发展活动， 年奖励期。我有财政支持，以补充我的工资和研究相关的费用，从司- 还有我的主要导师的资金我可以访问高性能计算资源 通过BWH和HMS，以及进入Canakinumab抗炎血栓结局研究 （CANTOS）数据通过格林博士的支持。合作伙伴研究患者数据登记处使医疗保险 索赔联动和有针对性地招募痛风患者进行患者调查。 研究：该项目的总体目标是应用，开发和传播最先进的定量 方法，以解决经常遇到的测量问题，在风湿病学，更具体地说，在痛风。 三个相关的临床重要问题是从痛风和合并症的相互作用中得出的;所有三个目标 评估测量问题的影响。目标1："痛风与CV合并症的横断面相关性" 批判性地评估了错误分类对理解痛风和CV并发症的人群负担的影响， bidities。关于"痛风和心血管事件的因果关系调查"的目标2严格量化了错误测量的影响- 痛风发作与炎症生物标志物介导的血清学潜在因果关系分析 尿酸和随后的CV事件。目标3："以患者为中心考虑痛风和CV疾病负担" 正式评估现有的多指标在测量患者的生活经验的有效性 痛风，通过患者报告的结果表示。对于我的第一个R01，我计划开发和验证自动化的 多变量指数估计器，用于电子健康记录中的常规护理数据， 在目标1和2中获得的误测量校正以及来自链接数据集的初步数据（例程 数据和患者调查）。 1

Yoshida, K. - Gout and Cardiovascular Comorbidities: Disentangling the Interplay with Advanced Methods to Address Measurement Issues. -- 2019-11-01 PROJECT SUMMARY Candidate: I am an Associate Epidemiologist and Instructor in Medicine in the Section of Clinical Sciences, Division of Rheumatology, Inflammation, and Immunity at Brigham and Women’s Hospital (BWH) and Harvard Medical School (HMS). My long-term goal is to develop an independent research career as a patient-oriented researcher contributing to the methodological advancement of clinical research in rheumatic diseases. I have a track record in the application, development, and dissemination of rigorous quantitative methodologies. My background includes clinical rheumatology, pharmacoepidemiology, and biostatistics. This mentored research experience will integrate my methodological research skills into clinical research focusing on gout and cardiovascular (CV) comorbidities. I will receive mentorship from Dr. Daniel H. Solomon, an established patient outcomes researcher with expertise in rheumatic diseases, including gout, as well as a team of expert co-mentors consisting of Drs. Robert J. Glynn (methodology), Brendan M. Everett (CV epidemiology), and Hyon K. Choi (gout epidemiology). Environment: I have strong support from my Department and Division at BWH, which ensures 85% protected time for the stated project for research and career development activities related to the proposed project during the 5- year award period. I have financial support to supplement my salary and research-related expenses from the Divi- sion, the Section, and my primary mentor’s funding. I have access to high-performance computing resources through BWH and HMS, as well as access to the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) data through Dr. Glynn’s support. The Partners Research Patient Data Registry enables Medicare claims linkage and targeted enrollment of gout patients for patient surveys. Research: The overarching goal of the project is to apply, develop, and disseminate state-of-the-art quantitative methods to address measurement issues frequently encountered in rheumatology, and more specifically in gout. Three related clinically important questions are drawn from the interplay of gout and comorbidities; all three aims assess the impact of measurement issues. Aim 1 on “the cross-sectional association of gout and CV comorbidities” critically assesses the impact of misclassification in understanding the population burden of gout and CV comor- bidities. Aim 2 on “causal investigation of gout and CV events” rigorously quantifies the influence of mismeasure- ment of gout flares and inflammatory biomarkers in mediation analysis of the potential causal link between serum uric acid and subsequent CV events. Aim 3 on “patient-centered consideration of gout and CV disease burden” formally evaluates the validity of existing multimorbidity indices in measuring the lived experience of patients with gout, represented through patient-reported outcomes. For my first R01, I plan to develop and validate an automated multimorbidity index estimator for routine care data in the electronic health record, utilizing the knowledge and skills in mismeasurement correction obtained in Aims 1 and 2 as well as preliminary data from linked datasets (routine data and patient survey) built in Aim 3. 1