Article
Publicly available continuously updated topic-specific databases of randomised clinical trials: a scoping review
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Authors
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Kim Boesen
- University Hospital Basel and University of Basel, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Pragmatic Evidence Lab, Basel, Schweiz
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Lars G. Hemkens
- University Hospital Basel and University of Basel, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Pragmatic Evidence Lab, Basel, Schweiz
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Perrine Janiaud
- University Hospital Basel and University of Basel, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Pragmatic Evidence Lab, Basel, Schweiz
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Julian Hirt
- University Hospital Basel and University of Basel, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Pragmatic Evidence Lab, Basel, Schweiz; Eastern Switzerland University of Applied Sciences, Department of Health, Schweiz
| Published: | March 27, 2025 |
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Outline
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Background/research question: Conducting systematic reviews of clinical trials is arduous and resource consuming. One potential solution is to design databases that are continuously and automatically populated with clinical trial data from harmonised and structured datasets. We aimed to map publicly available, continuously updated, topic-specific databases of clinical trials.
Methods: We included publicly available continuously updated topic specific databases of randomised clinical trials. We systematically searched PubMed, Embase, the preprint servers medRxiv, ArXiv, and Open Science Framework, and Google. We described seven features (access model, database architecture, data input sources, retrieval methods, data extraction methods, trial presentation, and export options) and narratively summarised the results. We did not register a protocol for this review.
Results: We identified 14 continuously updated clinical trial databases, seven related to COVID-19 (first active in 2020) and seven non-COVID databases (first active in 2009). All databases, except one, were publicly funded and accessible without restrictions. They mainly employed methods similar to those from static article-based systematic reviews and retrieved data from journal publications and trial registries. No database retrieved data from other sources, such as structured machine-readable datasets. The COVID-19 databases and some non-COVID databases implemented semi-automated features of data import, which combined automated and manual data curation, whereas the non-COVID databases mainly relied on manual workflows. Most reported information was metadata, such as author names, years of publication, and link to publication or trial registry. Two databases included trial appraisal information (risk of bias assessments). Six databases reported aggregate group level results, but only one database provided individual participant data on request.
Conclusion: We identified few continuously updated trial databases, and existing initiatives mainly employ methods known from static article-based reviews. The main limitation to create truly live evidence synthesis is the access and import of machine-readable and harmonised clinical trial data.
Competing interests: The authors declare no conflict of interest.
