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

项目摘要/摘要 这是为阿米·A·沙阿医学博士颁发的以患者为中心的研究中的K24职业中期研究员奖的建议。 约翰霍普金斯大学医学院的MHS博士说。沙阿博士是一名医学副教授 风湿科，风湿病精准医学卓越中心副主任 他也是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 在她的职业生涯和学术生涯中，她专注于系统性硬化症(硬皮病)和 研究癌症和自身免疫之间的关系。硬皮病是一个复杂的、多系统的疾病 在相同诊断的患者中表现出非常不同的风湿性疾病。存在异质性 在症状、疾病轨迹、事件发生时间和对治疗的反应方面。虽然许多风险因素一直是 在人群水平上被确定为特定硬皮病并发症，这些并不容易翻译 到病人层面的临床实践。这是由于许多因素造成的，包括：(I)捕获困难 多变量患者特定疾病轨迹，(Ii)器官系统之间复杂相互作用的模拟 参数随时间的变化，以及(Iii)利用从其他患者的轨迹获得的知识 硬皮病亚群特征。在这项提案中，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来生成 硬皮病主要临床事件的个性化风险评估。她将利用一种创新的战略来申请 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主要 将事件转化为患者级别的数据可视化工具，该工具可以实时更新，她将测试这些新的 这些发现可能会影响提供者的风险评估以及未来的诊断和治疗决策。最后， 她将利用表型轨迹作为平台，在基线上识别候选生物标记物 硬皮病的长期疾病进展，因为这可能提供对以下患者亚组的洞察 受益于密集的筛查和治疗策略。这些目标将成为实现以下目标的杰出工具 沙阿博士的学员的职业发展和成长，开辟了新的研究领域，开发了小说 硬皮病的精准医学方法。

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.