RC-3: Biostatistics and Data Management Core (BDMC)

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ABSTRACT – RESOURCE CORE (RC) 3 The goals of the Biostatistics and Data Management Core [(BDMC, henceforth termed Research Core (RC)-3)] are to provide: 1) biostatistical support and expertise; and 2) centralized research information services to ensure ready access and superior data quality to the OAIC. The Core will greatly facilitate data sharing and integrated analyses within the OAIC. Importantly, RC3 develops and implements services not available elsewhere at UTHSCSA. Instead, it will capitalize on the aging-related biostatistical and informatics expertise of the Core team. RC3 provides three innovative and value-added features. (1) To further improve biostatistics support specifically applicable for aging research, Dr. Gelfond (Core Leader) will develop new statistical methods related to survival analysis, latent trajectory models, and comparative genomics in collaboration with OAIC investigators. Dr. Gelfond has substantial experience in directing and developing statistical analyses as well as collaborative experience with key OAIC supported faculty. These new methods are motivated by and required for optimal analyses of the developmental and pilot project data. All these methods will have broader applications in aging research. (2) The Core supports an innovative informatics Developmental Project (DP3) that will identify cohorts within the local community that can be well-suited for clinical trials focused on aging research. Additionally, DP3 will provide access to extensively and appropriately phenotyped de-identified data from UTHSCSA-affiliated clinics that will be available for retrospective studies. (3) The Core will utilize novel collaborative models, developed by the Core Leader, which will promote efficient operations and help track research productivity outcomes, such as publications and funded proposals. The RC3 has four achievable Specific Aims: 1) Provide all biostatistical support and expertise for the OAIC, including study design and planning; protocol development; creation of new analytical approaches; interpretation of study results; and preparation of reports, manuscripts, and presentations; 2) Provide OAIC projects and investigators with state-of-the-art research informatics tools for development of cohorts for trials with aging outcomes, de-identified data to support pilot data for clinical trials development, and tools for efficient clinical trial data collection and management; 3) Contribute expertise, didactics, and hands-on training for analyses of data specific to aging research, as well as education and mentorship of OAIC trainees; and 4) Ensure the success of the Core, continually assess Core utilization and quality, assess research standards and Core outcomes, and leverage assessments for Aims 1, 2, and 3.