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

痛风和心血管合并症：用先进方法理清相互作用，解决测量问题

• 批准号: 10451675
• 负责人: Kazuki Yoshida
• 金额: $ 14.62万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-01-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10451675
• 关键词: Accounting; Acute; Address; Ambulatory Care; Anti-Inflammatory Agents; Award; Biological; Biological Markers; Biometry; Blood Vessels; Cardiovascular Diseases; Cardiovascular system; Chronic; Clinic; Clinical; Clinical Research; Clinical Sciences; Data; Data Collection; Data Set; Development; Diagnosis; Electronic Health Record; Enrollment; Ensure; Environment; Epidemiologist; Epidemiology; Event; Financial Support; Flare; Funding; General Population; Goals; Gout; Healthcare; Heart failure; High Performance Computing; Hospitals; Hyperuricemia; Immunity; Inflammation; Inflammatory; Inflammatory Arthritis; Investigation; Knowledge; Learning; Link; Masks; Measurement; Measures; Mediating; Mediation; Mediator of activation protein; Medicare claim; Medicine; Mentors; Mentorship; Metabolic; Metabolic Diseases; Methodology; Methods; Modeling; National Health and Nutrition Examination Survey; Nature; Outcome Study; Patient Outcomes Assessments; Patient Self-Report; Patient-Focused Outcomes; Patients; Pharmacoepidemiology; Physicians; Population; Prevalence; Reporting; Research; Research Methodology; Research Personnel; Research Project Grants; Rheumatism; Rheumatology; Role; Self-Correction; Serum; Sex Differences; Statistical Data Interpretation; Statistical Methods; Surveys; Thrombosis; Time; Training; Uncertainty; Uric Acid; Validation; Wages; Woman; Work; burden of illness; cardiovascular disorder epidemiology; career; career development; comorbidity; computing resources; data registry; experience; improved; indexing; instructor; medical schools; men; method development; multiple chronic conditions; patient oriented; prospective; research and development; routine care; skills; tool; trend

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

Yoshida, K. - 痛风和心血管合并症：用先进方法解决测量问题的相互作用 - 2019-11-01。 项目概要 候选人：我是临床科学部的流行病学副学家和医学讲师 布莱根妇女医院 (BWH) 和哈佛医学院的风湿病、炎症和免疫科 我的长期目标是作为一名以患者为中心的研究人员发展独立的研究生涯。 我在风湿病临床研究方法学方面的进步做出了贡献。 我的背景包括严格的定量方法的应用、开发和传播。 这种指导性的研究经验将整合临床风湿病学、药物流行病学和生物统计学。 我对痛风和心血管 (CV) 合并症临床研究的方法学研究技能。 将接受 Daniel H. Solomon 博士的指导，Daniel H. Solomon 博士是一位资深的患者结果研究员，在以下领域拥有专业知识 包括痛风在内的风湿性疾病，以及由 Robert J. Glynn 博士组成的专家联合导师团队。 （方法学）、Brendan M. Everett（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，确保了 85% 的受保护时间 对于所述项目，在 5-5 年内与拟议项目相关的研究和职业发展活动 年度奖励期间，我有财政支持来补充我的工资和研究相关费用。 我可以使用高性能计算资源。 通过 BWH 和 HMS，以及访问 Canakinumab 抗炎血栓形成结果研究 (CANTOS) 数据通过 Glynn 博士的支持实现了 Medicare。 索赔链接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 解决风湿病学，特别是痛风中经常遇到的测量问题的方法。 从痛风和合并症的相互作用中得出三个相关的临床重要问题； 评估测量问题的影响“痛风和心血管合并症的横截面关联”。 批判性地评估了错误分类对理解痛风和心血管疾病的人口负担的影响 关于“痛风和心血管事件的因果调查”的目标 2 严格量化了错误测量的影响。 痛风发作和炎症生物标志物在血清之间潜在因果关系的中介分析中的作用 目标 3“以患者为中心考虑痛风和心血管疾病负担”。 正式评估现有多发病指数在衡量患有以下疾病的患者的生活经历方面的有效性 痛风，通过患者报告的结果来表示。对于我的第一个 R01，我计划开发和验证自动化。 利用知识和技能，对电子健康记录中的常规护理数据进行多病指数估计 目标 1 和 2 中获得的误测校正以及来自链接数据集的初步数据（常规 数据和患者调查）建立在目标 3 中。 1

项目成果

Clinical characteristics of non-radiographic versus radiographic axial spondyloarthritis in Asia and non-radiographic axial spondyloarthritis in other regions: results of the cross-sectional ASAS-COMOSPA study.

亚洲非放射学中轴​​型脊柱关节炎与放射学中轴​​型脊柱关节炎以及其他地区非放射学中轴​​型脊柱关节炎的临床特征：ASAS-COMOSPA 横断面研究的结果。

• 发表时间: 2021
• 影响因子: 6.2
• 作者: Kishimoto, Mitsumasa;Ono, Keisuke;Fukui, Sho;Kawaai, Satoshi;Deshpande, Gautam A;Yoshida, Kazuki;Ichikawa, Naomi;Kaneko, Yuko;Kawasaki, Taku;Matsui, Kazuo;Morita, Mitsuhro;Tada, Kurisu;Takizawa, Naoho;Tamura, Naoto;Taniguchi, Atsuo;Taniguch
• 通讯作者: Taniguch

Prescribing Patterns of Hydroxychloroquine and Glucocorticoids Among Lupus Patients After New-Onset End-Stage Renal Disease.

新发终末期肾病后狼疮患者的羟氯喹和糖皮质激素处方模式。

• 发表时间: 2022-12
• 影响因子: 4.7
• 作者: Broder, Anna;Mowrey, Wenzhu B;Valle, Ana;Kim, Mimi;Feldman, Candace H;Yoshida, Kazuki;Costenbader, Karen H
• 通讯作者: Costenbader, Karen H

Canakinumab's Effect Against Subsequent Gout Flares and High-Sensitivity C-Reactive Protein Levels: A Causal Mediation Analysis.

卡那奴单抗对随后的痛风发作和高敏 C 反应蛋白水平的影响：因果中介分析。

• 发表时间: 2023-04
• 影响因子: 4.7
• 作者: Yoshida, Kazuki;Glynn, Robert J;Choi, Hyon K;Everett, Brendan M;Li, Yi;MacFadyen, Jean G;Ridker, Paul M;Solomon, Daniel H
• 通讯作者: Solomon, Daniel H

Acute Calcium Pyrophosphate Crystal Arthritis Flare Rate and Risk Factors for Recurrence.

急性焦磷酸钙晶体关节炎发作率和复发的危险因素。

• 发表时间: 2020
• 作者: Yates, Katherine A;Yoshida, Kazuki;Xu, Chang;Lyu, Houchen;Norvang, Vibeke;Solomon, Daniel H;Tedeschi, Sara K
• 通讯作者: Tedeschi, Sara K

Classifying Pseudogout Using Machine Learning Approaches With Electronic Health Record Data.

使用机器学习方法和电子健康记录数据对伪痛风进行分类。

• 发表时间: 2021
• 影响因子: 4.7
• 作者: Tedeschi, Sara K;Cai, Tianrun;He, Zeling;Ahuja, Yuri;Hong, Chuan;Yates, Katherine A;Dahal, Kumar;Xu, Chang;Lyu, Houchen;Yoshida, Kazuki;Solomon, Daniel H;Cai, Tianxi;Liao, Katherine P
• 通讯作者: Liao, Katherine P