5/6 COMpAAAS U24: Resource in Informatics and Biostatistics (RIB)

NIAAA资助的联盟的总体目标是改善艾滋病毒/艾滋病、酒精、衰老和多方面的成果 物质使用（COMpAAAS）是建立和传播优化艾滋病毒+护理所需的证据 经历酒精和相关物质使用的医疗损害，通过协调，综合， 外部验证的观察、运筹学建模和干预研究。组合和 结合信息学、生物统计学和流行病学的互补专业知识，我们提出了一个U24 信息学和生物统计学资源（RIB），以支持和通知其他COMpAAAS组件。这 资源将解决在分析中最大化功效和最小化偏差所需的复杂挑战 解决整个财团的问题。支持的高级信息学方法包括自然语言 处理（NLP），本体论，数据库和临床决策支持，以及重要数据管理的应用 安全数据收集、存储、注释、检索和集成工具。先进的流行病学和 统计方法包括时间更新暴露技术、多重插补、倾向评分 技术，测量误差校正和竞争风险回归。常规的，但必不可少的，统计 方法包括考克斯比例风险、逻辑和线性回归、拟合优度诊断，以及 一致性/准确性度量（kappa、灵敏度、特异性等）。RIB将进一步利用 观察性和干预性研究、模拟模型和协调良好的核心网络， COMpAAAS的工作组与先进的信息学和生物统计技术，专门针对特定的 来自多个来源的大规模纵向数据的挑战，包括电子健康记录（EHR）， 临床干预、患者自我报告和组织储存库。我们的具体目标是提供1）统计 和2）COMpAAAS的信息学专业知识，以最大限度地发挥科学影响。为了实现这一目标，我们将加强 干预研究的设计、招募和随访，支持数据的适当设计和执行 分析和跨队列合作，提供先进的统计方法和酒精估计 模式或建模和识别性/性别少数群体（CHAMP）从VACS调查数据。 此外，我们将加强联盟基于网络的实验室（WBL门户）信息基础设施， 支持正在进行的研究设计、数据收集和管理、制定和测试干预措施 例如临床决策支持和电子健康工具，并加强对文本数据分析的支持。

The overall aim of the NIAAA-funded Consortium to improve OutcoMes in hiv/Aids, Alcohol, Aging, & multi- Substance use (COMpAAAS) is to build and disseminate the evidence needed to optimize care for HIV+ experiencing medical harm from alcohol and related substance use, through coordinated, integrated, and externally validated observational, operations research modeling, and intervention studies. Combining and integrating the complimentary expertise of informatics, biostatistics and epidemiology, we propose a U24 Resource for Informatics and Biostatistics (RIB) to support and inform the other COMpAAAS components. This resource will address the complex challenges required to maximize power and minimize bias in analyses addressing consortium-wide questions. Advanced informatics methods supported include natural language processing (NLP), ontologies, database and clinical decision support, and application of vital data management tools for secure data collection, storage, annotation, retrieval, and integration. Advanced epidemiological and statistical methods include time-updated exposure techniques, multiple imputation, propensity score techniques, measurement error correction, and competing risks regression. Routine, but essential, statistical methods include Cox proportional hazards, logistic and linear regression, goodness of fit diagnostics, and agreement/accuracy metrics (kappa, sensitivity, specificity, etc.). The RIB will further leverage the observational and interventional studies, simulation models, and well-coordinated network of cores and workgroups of COMpAAAS with advanced informatics and biostatistical techniques tailored to the particular challenges of large scale, longitudinal data from multiple sources including electronic health records (EHR), clinical interventions, patient self-report, and tissue repositories. Our specific aims are to provide 1) statistical and 2) informatics expertise for COMpAAAS to maximize scientific impact. To accomplish this, we will enhance the design, recruitment, and follow-up of intervention studies, support appropriate design and execution of data analyses and cross cohort collaborations, provide advanced statistical methods plus estimates of alcohol patterns for OR modeling and identify sexual/gender minority populations (CHAMP) from VACS survey data. In addition we will enhance the Consortium Web-Based Laboratory (WBL Portal) informatics infrastructure to support ongoing research design, data collection and management, development and testing of interventions such as clinical decision support and eHealth tools and enhance support for the analysis of textual data.