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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：
10592246
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/10592246
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 Decision Making Diagnosis Diagnostic Diffusion 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 System Systemic Scleroderma Systolic Pressure Testing Therapeutic Time Universities Update Ventricular Visualization Visualization software Vital capacity anti-cancer biomarker discovery body system cancer risk candidate identification candidate marker carcinogenesis 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 subsets precision medicine prediction algorithm primary outcome programs progression risk 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