从连接网络COVID-19研究中学到的NHLBI生物数据催化剂(BDC)临床试验数据协调和共享的最佳实践。

IF 2.1 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Journal of Clinical and Translational Science Pub Date : 2025-03-26 eCollection Date: 2025-01-01 DOI:10.1017/cts.2025.52
Jeran K Stratford, Huaqin Helen Pan, Alex Mainor, Edvin Music, Joshua Froess, Alex C Cheng, Alexandra Weissman, David T Huang, Elizabeth C Oelsner, Sonia M Thomas
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引用次数: 0

摘要

协作和透明地共享COVID-19临床试验和大规模观察性研究数据,以加速科学发现和为临床实践提供信息,这一点至关重要。负责任的数据共享需要解决与数据隐私和机密性、数据链接、数据质量、变量协调、数据格式和全面的元数据文档相关的挑战,以产生高质量、上下文丰富、可查找、可访问、可互操作和可重用(FAIR)的数据集。本文探讨了通过NHLBI BioData Catalyst®(BDC)生态系统共享国家心肺血液研究所(NHLBI) COVID-19临床试验(包括适应性平台试验)和队列研究数据集所获得的经验和教训,重点关注协调这些数据集以进行更广泛的研究使用的挑战和成功。我们的研究结果强调了建立标准化数据格式、采用通用数据元素以及创建和维护稳健的数据治理结构以应对共同挑战(即,由知情同意导致的数据隐私和数据共享限制)的重要性。这些努力产生了一套来自5项临床试验和13项队列研究的全面且可互操作的数据集,这些数据集将在下游分析和合作中重用。通过对联盟数据的经验得出的原则和策略可以为推进协作和有效的数据共享奠定基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Best practices for clinical trials data harmonization and sharing on NHLBI bioData catalyst (BDC) learned from CONNECTS network COVID-19 studies.

The need for collaborative and transparent sharing of COVID-19 clinical trial and large-scale observational study data to accelerate scientific discovery and inform clinical practice is critical. Responsible data-sharing requires addressing challenges associated with data privacy and confidentiality, data linkage, data quality, variable harmonization, data formats, and comprehensive metadata documentation to produce a high-quality, contextually rich, findable, accessible, interoperable, and reusable (FAIR) dataset. This communication explores the experiences and lessons learned from sharing National Heart Lung and Blood Institute (NHLBI) COVID-19 clinical trial (including adaptive platform trials) and cohort study datasets through the NHLBI BioData Catalyst® (BDC) ecosystem, focusing on the challenges and successes of harmonizing these datasets for broader research use. Our findings highlight the importance of establishing standardized data formats, adopting common data elements and creating and maintaining robust data governance structures that address common challenges (i.e., data privacy and data-sharing limitations resulting from informed consent). These efforts resulted in a set of comprehensive and interoperable datasets from 5 clinical trials and 13 cohort studies that will enable downstream reuse in analyses and collaborations. The principles and strategies outlined, derived through experience with consortia data, can lay the groundwork for advancing collaborative and efficient data sharing.

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来源期刊
Journal of Clinical and Translational Science
Journal of Clinical and Translational Science MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
2.80
自引率
26.90%
发文量
437
审稿时长
18 weeks
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