ArticleJournal of clinical and translational science2025
Best practices for clinical trials data harmonization and sharing on NHLBI bioData catalyst (BDC) learned from CONNECTS network COVID-19 studies.
Article in Journal of clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Centralized clinical research operations reporting for a multi-network, multi-study research program: The NHLBI COVID-19 CONNECTS experience.Journal of clinical and translational science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.