Data Science Core

项目总结 数据科学核心(DSC)的广泛目标是推动和应用现代数据科学 方法支持风湿病精准医学实践。我们定义了精确度 作为发现机械锚定和临床相关疾病亚群的医学 可以遵循哪些最优策略。精准医学统计方法我们 开发和应用将改善对个人疾病状况的临床评估， 以及相互竞争的干预措施的可能好处，从而使患者受益 风湿病。在过去的资助期间，由P30 Pi Antony Rosen和P30领导的一个团队 DSC主任Scott Zeger设计并实施了JH精密医学分析 基于云的数据系统平台(PMAP)：(1)每晚接收所有JHM临床数据的下载 数据并将数据投影到安全的临床队列数据库中；(2)提供环境 用于协作的现代统计分析；以及(3)提供工具以从 电子病历记录与特定患者的决定相关的分析结果。 PMAP已在硬皮病和肌炎中心实施。在.期间 在未来的一段时间里，PMAP将在每个风湿病卓越中心活跃起来，以便 当前的临床队列数据库将构成下一阶段研究的信息基础 P30程序。这种新颖的基础设施使数字信号交换中心的开发和应用成为可能 新的统计工具，确定疾病亚组，对他们的最佳治疗 已评估。通过这种方式，JHM Rheumatology将发现 学习型医疗保健系统。 数据科学核心的具体目标是：(1)提供研究设计和分析 支持调查人员生成、管理、分析和解释复杂数据 使用现代统计和计算方法；(2)开发和应用多元层次结构 纵向数据集的模型(MHM)，以识别预测疾病的患者子集 轨迹和重大临床事件；以及(3)应用现代统计分析方法 严格评估治疗效果和安全性的观察性和实验性研究， 认识到个体对治疗的反应可能存在异质性， 使用观测数据解决因果问题所固有的潜在偏见。

PROJECT SUMMARY The broad goal of the Data Science Core (DSC) is to advance and apply modern data science methods to support the practice of precision medicine in rheumatology. We define precision medicine as discovering mechanistically anchored and clinically relevant disease subgroups for which optimal strategies can be followed. The precision medicine statistical methods we develop and apply will improve the clinical assessment of an individual's disease status, trajectory, and likely benefits of competing interventions and thereby benefit people living with rheumatic diseases. During the past funding period, a team led by P30 PI Antony Rosen and DSC Director Scott Zeger, designed and implemented the JH Precision Medicine Analytics Platform (PMAP), a cloud-based data system: (1) receives a nightly download of all JHM clinical data and projects the data into a secure clinical cohort database; (2) provides an environment for collaborative, modern statistical analyses; and (3) provides tools to visualize from within the Electronic Medical Record those analytic results relevant to a particular patient's decisions. PMAP has already been implemented in the Scleroderma and Myositis Center. During the coming period, PMAP will become active in each rheumatology Center of Excellence so that current clinical cohort databases will form the information foundation for the next phase of this P30 program. This novel infrastructure makes it possible for the DSC to develop and apply novel statistical tools that identify disease subgroups, for whom optimal treatments can be evaluated. In this way, JHM Rheumatology will discover the key data science tools required by a learning healthcare system. The Specific Aims of the Data Science Core are to: (1) provide study design and analysis support that enables investigators to generate, manage, analyze, and interpret complex data using modern statistical and computing methods; (2) develop and apply multivariate hierarchical models (MHMs) to longitudinal datasets to identify patient subsets predictive of disease trajectories and major clinical events; and (3) apply modern statistical analytic approaches to observational and experimental studies that rigorously estimate treatment efficacy and safely, acknowledging the likely heterogeneity among individuals in their responses to treatments and the potential biases inherent in using observational data to address causal questions.