Consortium on Translational Research in Early Detection of Liver Cancer:Data Management and Coordinating Center (DMCC)

肝癌早期检测转化研究联盟：数据管理和协调中心（DMCC）

• 批准号: 10734730
• 负责人: Ziding Feng
• 金额: $ 73.8万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-17 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10734730
• 关键词: Address; Artificial Intelligence; Bioinformatics; Biological Markers; Biological Specimen Banks; Biological Specimen database; Biometry; Cancer Burden; Cancer Center; Cancer Detection; Center for Translational Science Activities; Cirrhosis; Clinical; Clinical Data; Cohort Studies; Collaborations; Collection; Common Data Element; Communication; Computer Analysis; Consultations; Country; Dana-Farber Cancer Institute; Data; Data Collection; Data Coordinating Center; Data Management Resources; Data Science; Data Set; Databases; Discipline; Early Detection Research Network; Early Diagnosis; Ensure; Evaluation; Evaluation Studies; Image; Information Technology; Infrastructure; Lead; Leadership; Liver; Malignant Neoplasms; Malignant neoplasm of liver; Manuals; Mission; Modeling; Monitor; Nodule; Output; Patients; Procedures; Prospective Studies; Prospective, cohort study; Protocols documentation; Public Health; Qualifying; Randomized; Research; Research Design; Research Personnel; Research Support; Retrospective Studies; Risk; Sampling; Science; Scientist; Screening for Hepatocellular Cancer; Secure; Services; Specimen; Statistical Data Interpretation; Statistical Methods; System; Testing; Time; Translational Research; United States; University of Texas M D Anderson Cancer Center; Work; anticancer research; artificial intelligence method; biomarker evaluation; cancer biomarkers; computational intelligence; computerized data processing; data management; data repository; data sharing; experience; improved; informatics tool; innovation; instrument; meetings; operation; programs; protocol development; research study; risk stratification; success; symposium; validation studies; web site

PROJECT SUMMARY ABSTRACT The key to success of the Consortium on Translational Research in Early Detection of Liver Cancer (Consortium) lies in good communication among scientists in multiple disciplines, efficient evaluation and prioritization of promising biomarkers, and rigorous validation studies to demonstrate their potential clinical utilities in improving the surveillance and early detection of liver cancer and stratifying the risk of liver cancer in patients with cirrhosis. The overall aims of the proposed Data Management and Coordinating Center (DMCC) are to (i) enhance communication and collaboration among Consortium investigators; (ii) coordinate Consortium collaborative research and provide statistical support; (iii) develop and maintain integrated research and biorepository databases for Consortium studies; and (iv) support and facilitate trans-Consortium collaborative research. Under the direction of the Consortium Steering Committee, the DMCC will 1) perform network coordination and promote collaborations among scientific investigators by providing support for Consortium meetings and conference calls, developing and maintaining all Consortium documents, including the Manual of Operations and Procedures (MOP), and by maintaining and enhancing the Consortium’s secure website; 2) support Consortium collaborative studies by working with Consortium investigators on study design, protocol development, data forms, and study manuals; coordinating and monitoring studies; tracking specimen sharing, blinding, and randomization; and performing QA/QC and study evaluation; 3) maintain and enhance the COMPASS Data Management System (CDMS) used to facilitate Consortium collaborative activities. CDMS provides online, end- to-end data management solutions, including investigator and study coordinator communications, regulatory compliance, remote subject registration, clinical data capture, biospecimen sample management, imaging data repository, and document management. CDMS can provide online visibility of analytical datasets for all participating researchers, and statistical and informatic tools relevant to Consortium research; 4) support and facilitate trans-Consortium collaborative studies by promoting team science, monitoring study procedures, and using cutting edge statistical, computational, and Artificial Intelligence methods to ensure efficient yet rigorous study design and maximize research outputs. Our research strategy is built from this guiding principle: provide the highest quality service to the Consortium while remaining innovative and providing scientific leadership to help the Consortium achieve its mission. Our qualifications include being the DMCC for the Early Detection Research Network since its inception, serving as lead statisticians for the two largest ongoing cirrhosis cohort studies in this country, and being responsible for two FDA-cleared Imaging AI products and many statistical innovations in early detection research.

项目摘要摘要 在早期检测肝癌（财团）中转化研究成功的成功的关键 科学家在多个学科，有效的评估和优先级别的科学家之间进行了良好的沟通 有希望的生物标志物和严格的验证研究，以证明其潜在的临床实用性在改善 肝硬化患者的肝癌的监测和早期发现以及对肝癌的风险进行分层。 拟议的数据管理和协调中心（DMCC）的总体目的是（i）增强 财团调查员之间的沟通和协作； （ii）协调联盟合作 研究并提供统计支持； （iii）开发和维护综合研究和生物验证 财团研究的数据库； （iv）支持和促进跨托管协作研究。 在财团指导委员会的指导下，DMCC将1）进行网络协调和 通过为财团会议提供支持，促进科学研究人员之间的合作 电话会议，开发和维护所有财团文件，包括运营手册和 程序（MOP），并通过维护和增强财团的安全网站； 2）支持财团 通过与财团研究人员合作研究设计，协议开发，数据的协作研究 形式和学习手册；协调和监测研究；跟踪标本共享，盲和 随机化；并进行质量检查/QC和研究评估； 3）维护和增强指南针数据 管理系统（CDM）用于促进财团协作活动。 CDM在线提供，结束 - 待命数据管理解决方案，包括研究人员和研究协调员通信，监管 合规性，远程主题注册，临床数据捕获，生物测得样本管理，成像数据 存储库和文档管理。 CDM可以为所有人提供分析数据集的在线可见性 参与研究人员，以及与财团研究相关的统计和信息性工具； 4）支持和 通过促进团队科学，监测研究程序和 使用尖端统计，计算和人工智能方法来确保有效而严格 研究设计并最大化研究成果。 我们的研究策略是根据这一指导原则构建的：为财团提供最高质量的服务 同时保持创新并提供科学领导才能帮助财团实现其使命。我们的 资格包括自成立以来是早期检测研究网络的DMCC， 该国两个最大持续的肝硬化队列研究的铅统计数据，并负责 早期检测研究中的两项FDA被清除成像AI产品和许多统计创新。