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

项目总结/摘要 这是一个K24中期职业研究者奖在以患者为导向的研究为Ami A的建议。Shah，医学博士， 约翰霍普金斯大学医学院MHS。沙阿博士是一个医学副教授在 流变学分部，流变学精准医学卓越中心副主任 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时间 她的职业生涯和奖学金的重点是以病人为导向的研究系统性硬化症（硬皮病）和 研究癌症和自身免疫之间的关系硬皮病是一种复杂的多系统疾病 风湿性疾病，表现出非常不同的患者之间具有相同的诊断。存在异质性 症状、疾病轨迹、事件发生的时间以及对治疗的反应。虽然许多风险因素 在人群水平上确定了特定的硬皮病并发症，这些并不容易翻译 到病人层面的临床实践。这是由于许多因素，包括：（i）捕获 多变量患者特异性疾病轨迹，（ii）模拟器官系统之间的复杂相互作用 参数随时间的变化，以及（iii）利用从共享的其他患者的轨迹获得的知识， 硬皮病亚组特征。在该提案中，申请人寻求通过以下方式利用丰富的临床数据： 约翰霍普金斯精密医学平台，并开发新的计算方法，以产生 硬皮病主要临床事件的个性化风险评估。她将利用创新的策略， 并在临床环境中测试这些新的见解。通过嵌入估计的轨迹和概率的主要 她将测试这些新的事件是否会在患者级别的数据可视化工具中“实时”更新， 这些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，以确定候选生物标志物在基线， 硬皮病的长期疾病进展，因为这可能提供对可能 受益于密集的筛查和治疗策略。这些目标将作为一个出色的工具， Shah博士的学员的职业发展和成长，开辟新的研究领域，开发新的 硬皮病的精准治疗方法

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.