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.

项目摘要 /摘要这是为Ami A. Shah，医学博士颁发的K24中级护理研究员奖的提案约翰霍普金斯大学医学院的MHS。 Shah博士是医学副教授风湿病学系，风湿病学精密医学卓越中心副主任临床计划和约翰·霍普金斯硬皮病中心的联合主任。沙阿博士花了大部分她的职业和奖学金的重点是面向患者的系统性硬化症研究（硬皮病）和研究癌症与自身免疫之间的关系。硬皮病是一个复杂的多系统在具有相同诊断的患者中表现出大不不同的风湿病。有异质性在症状，疾病轨迹，事件时机和对治疗的反应中。虽然许多风险因素已经在人群水平的特定硬皮病并发症中鉴定出来，这些并不容易翻译在患者一级进行临床实践。这是由于许多因素包括困难（i）捕获多变量患者特异性疾病轨迹，（ii）对器官系统之间的复杂相互作用进行建模随着时间的推移参数，以及（iii）使用其他共享患者的轨迹获得的知识硬皮病亚组特征。在此提案中，申请人试图通过约翰·霍普金斯精密医学平台并开发出新的计算方法来生成硬皮病主要临床事件的个性化风险估计。她将利用创新策略应用并在临床环境中测试这些新见解。通过嵌入估计的轨迹和主要的可能性将事件变成患者级别的数据可视化工具，该工具在“实时”中更新，她将测试这些新的发现可以影响提供者的风险估计以及未来的诊断和治疗决策。最后，她将利用表型轨迹作为一个平台，以识别基线的候选生物标志物随着硬皮病的长期疾病进展，因为这可能会洞悉可能受益于密集筛查和治疗策略。这些目标将成为 Shah博士的职业发展和成长硬皮病的精密医学方法。