Statistical Methods to Jointly Model Multiple Pain Outcome Measures

联合建模多种疼痛结果指标的统计方法

• 批准号: 10622820
• 负责人: Eva Petkova
• 金额: $ 9.6万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10622820
• 关键词: Acute; Award; Bioinformatics; Biological; Biological Markers; Biological Specimen Banks; Biometry; Clinic; Clinical; Clinical Research; Clinical Trials; Clinical Trials Design; Code; Collaborations; Collection; Communities; Complex; Data; Data Collection; Data Coordinating Center; Data Management Resources; Data Storage and Retrieval; Deposition; Development; Doctor of Philosophy; Exposure to; Fostering; Foundations; Funding; Future; Genomics; Goals; Government; Growth; Health; Health Professional; Helping to End Addiction Long-term; Human Resources; Institutes; Institution; Knowledge; Leadership; Learning; Link; Mathematics; Measures; Medical Research; Mentors; Mentorship; Methodology; Methods; Modality; Modeling; Modernization; Monitor; National Institute of Neurological Disorders and Stroke; Outcome Measure; Pain; Pain Research; Pain management; Parents; Performance; Phase; Phase II Clinical Trials; Procedures; Process; Radiology Specialty; Reporting; Reproducibility; Research; Research Personnel; Resources; Running; Sampling; Secure; Sensory; Site; Standardization; Statistical Data Interpretation; Statistical Methods; Statistical Models; Structure; Students; Techniques; Testing; Therapeutic; Time; Training; Treatment Efficacy; Treatment outcome; Welding; Work; actigraphy; advanced system; chronic pain; clinical biomarkers; clinical center; clinical investigation; clinical pain; complex data; computerized tools; dashboard; data integration; data management; data modeling; data repository; data sharing; design; doctoral student; experience; improved; innovation; microbiome; models and simulation; multidimensional data; neuroimaging; novel; pain outcome; parent grant; pre-clinical; pre-doctoral; precision medicine; programs; protocol development; quality assurance; radiological imaging; repository; research and development; sharing platform; simulation; skills; statistics; user-friendly

The Data Coordinating Center (DCC) of the Early Phase Pain Investigation Clinical Network (EPPIC-Net) will be the data and biospecimen manager for pain research within the HEAL Partnership. As such, it will host, manage, standardize, curate, and provide a sharing platform for data and biospecimens for HEAL initiatives, such as the Acute to Chronic Pain Signature initiative and the BACPAC, in addition to EPPIC-Net studies. The DCC will develop and maintain a databank for depositing pre-clinical, clinical, neuroimaging, microbiome, genomics, and other omics biomarker data, will link these data with a repository for biological samples, and will create a platform for teams to work together to analyze and interpret data. Further, the DCC will provide leadership in the statistical design and analysis of EPPIC-Net studies, and will deploy advanced systems and processes for data collection, management, quality assurance, and reporting. The DCC will create, sustain, and continually advance a robust organization for the rapid design, implementation, and performance of high- quality rigorous Phase II clinical trials to test promising therapeutics for pain. The proposed DCC brings together experts from statistics, clinical trials design and simulation, data management, neuroimaging, bioinformatics, genomics, and radiology, and leverages decades of experience instituting and running large data sharing consortia and data coordinating centers. Our aims are to further the goals of EPPIC-Net and the HEAL initiative through: 1) Integration of the DCC within the EPPIC-Net structure and facilitation of the alliance with HEAL partners; 2) Provision of biostatistical expertise, support, and leadership to EPPIC-Net studies; 3) Provision of legacy and de novo secure data storage and comprehensive data management for EPPIC-Net studies; 4) Institution of a pain-related expandable biospecimen repository; and 5) Establishment of the EPPIC- Net DataExchange and BiospecimenExchange to foster the development of non-addictive treatments for pain. The DCC will be structured around four cores: 1) an Administrative Core; 2) a Statistical Core; 3) a Data Core; and 4) a Biospecimen Core. This DCC will work with the EPPIC-Net Clinical Coordinating Center (CCC) and with the Specialized Clinical Centers (SCC, a hub and its spokes/clinics) to educate clinicians and staff in good clinical trial practices for reproducibility of research, and to train them in the data management system and procedures employed in the network. The DCC will provide sites with user-friendly dashboards to monitor their own performance and will promote collegial and supportive relationships with the sites’ personnel to cultivate rigorous and enthusiastic engagement in the conduct of the studies. The DCC will use state-of-the-art concepts and techniques in the acquisition, transfer, storing, management, standardization, linking, and curation of the clinical and biomarker data to launch and maintain the EPPIC Exchange encompassing the DataExchange, and the BiospecimenExchange. The EPPIC Exchange represents the final product delivered by the DCC -- a resource with capability for continual growth, that will be shared by the pain research community.

早期疼痛调查临床网络（EPPIC-Net）的数据协调中心（DCC）将