Harnessing multivariate patient- and population-level disease trajectories to predict major clinical events in scleroderma

利用多变量患者和人群水平的疾病轨迹来预测硬皮病的主要临床事件

基本信息

批准号：
10351424
负责人：
Ami Aalok Shah
金额：
$ 16.94万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-03-15 至 2027-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10351424
关键词：
Address Algorithms Autoantibodies Autoantigens Autoimmunity Back Biologic Characteristic Biological Markers Blood Vessels Cancer Model Characteristics Clinical Clinical Data Complex Computing Methodologies Data Data Analyses Data Display Decision Making Diagnosis Diagnostic Diffuse Disease Disease Progression Event Foundations Future Genes Growth and Development function Heterogeneity Immune response Individual Kidney Knowledge Learning Logistic Regressions Malignant Neoplasms Medical Medicine Methodology Methods Midcareer Investigator Award in Patient-Oriented Research Modeling Monitor Mutation Outcome Pathogenesis Pathway interactions Patient risk Patients Phenotype Population Precision Medicine Initiative Predictive Analytics Probability Prognosis Provider Pulmonary Heart Disease Rheumatism Rheumatology Risk Risk Estimate Risk Factors Scholarship Scleroderma Skin Somatic Mutation Subgroup Symptoms Systemic Scleroderma Systolic Pressure Testing Therapeutic Time Universities Update Ventricular Visualization Visualization software Vital capacity anti-cancer biomarker discovery body system cancer risk candidate marker career career development clinical care clinical decision-making clinical practice clinically relevant cohort complex data cross reactivity cytokine data visualization implementation science improved individual patient innovation insight medical schools mid-career faculty multidimensional data novel novel marker patient oriented research patient population patient subsets precision medicine prediction algorithm primary outcome programs response risk prediction risk stratification screening skills skin disorder tool treatment response treatment strategy trend

项目摘要

PROJECT SUMMARY / ABSTRACT This is a proposal for a K24 Midcareer Investigator Award in Patient-Oriented Research for Ami A. Shah, MD, MHS of Johns Hopkins University School of Medicine. Dr. Shah is an Associate Professor of Medicine in the Division of Rheumatology, Deputy Director for the Rheumatology Precision Medicine Centers of Excellence clinical programs, and Co-Director of the Johns Hopkins Scleroderma Center. Dr. Shah has spent the majority of her career and scholarship focused on patient-oriented research in systemic sclerosis (scleroderma) and in investigating the relationship between cancer and autoimmunity. Scleroderma is a complex, multisystem rheumatic disease that manifests very differently among patients with the same diagnosis. There is heterogeneity in symptoms, trajectory of disease, timing of events, and response to therapy. While many risk factors have been identified for specific scleroderma complications at the population level, these have not been easily translatable to clinical practice at the patient level. This has been due to many factors including difficulty (i) capturing multivariate patient-specific disease trajectories, (ii) modeling the complex interplay between organ system parameters over time, and (iii) utilizing knowledge gained from trajectories of other patients who share scleroderma subgroup characteristics. In this proposal, the applicant seeks to harness rich clinical data through the Johns Hopkins precision medicine platform and develop novel computational methods to generate personalized risk estimates of major clinical events in scleroderma. She will utilize an innovative strategy to apply and test these new insights in a clinical setting. By embedding estimated trajectories and probabilities of major events into a patient level data visualization tool that updates in “real-time,” she will test whether these new discoveries can influence provider risk estimation and future diagnostic and therapeutic decision-making. Lastly, she will utilize phenotypic trajectories as a platform to identify candidate biomarkers at baseline that associate with long-term disease progression in scleroderma, as this may provide insight into patient subgroups who could benefit from intensive screening and treatment strategies. These aims will serve as an outstanding vehicle for career development and growth for Dr. Shah’s mentees, opening new fields of inquiry and developing novel precision medicine approaches in scleroderma.

项目概要/摘要这是一项为 Ami A. Shah 医学博士申请 K24 职业生涯中期研究员奖以患者为导向的研究的提案， Shah 博士是约翰·霍普金斯大学医学院的 MHS 医学副教授。风湿病科，风湿病精准医学卓越中心副主任约翰霍普金斯大学硬皮病中心联合主任 Shah 博士花费了大部分时间。她的职业生涯和学术生涯主要集中在以患者为中心的系统性硬化症（硬皮病）和研究癌症和自身免疫之间的关系是一个复杂的、多系统的。具有相同诊断的患者之间表现差异很大的风湿性疾病存在异质性。症状、疾病轨迹、事件发生时间以及对治疗的反应。在人群水平上确定了特定的硬皮病并发症，但这些并发症并不容易转化这是由于许多因素造成的，包括 (i) 捕获困难。多变量患者特定疾病轨迹，(ii) 模拟器官系统之间复杂的相互作用随时间变化的参数，以及（iii）利用从共享的其他患者的轨迹中获得的知识在该提案中，申请人力求通过丰富的临床数据来获取硬皮病亚组特征。约翰霍普金斯大学精准医学平台并开发新颖的计算方法来生成她将利用创新策略来应用硬皮病主要临床事件的个性化风险评估。并通过嵌入主要的估计轨迹和概率来测试这些新见解。将事件导入“实时”更新的患者级数据可视化工具中，她将测试这些新数据是否有效发现可以影响提供者的风险评估以及未来的诊断和治疗决策。她将利用表型轨迹作为平台来识别与相关的基线候选生物标志物硬皮病的长期疾病进展，因为这可以深入了解哪些患者亚组可以这些目标将受益于强化筛查和治疗策略。沙阿博士的学员的职业发展和成长，开辟新的探究领域并开发新颖的硬皮病的精准医学方法。