ReviewContemporary clinical trials communications2024
Freely accessible software for recruitment prediction and recruitment monitoring of clinical trials: A systematic review.
Review in Contemporary clinical trials communications, 2024. 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.
- Meeting clinical recruitment milestones in an academic center: a data-driven, visual approach.JAMIA open · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The successful completion of clinical trials ultimately depends on realistic recruitment predictions. Statistical methods for recruitment prediction implemented in a free-of-charge open-source software could be routinely used by researchers worldwide to design clinical trials. However, the availability of such software implementations is currently unclear. Methods: Two independent reviewers conducted a systematic review following PRISMA guidelines. Eligible articles included English publications focused on statistical methods for recruitment prediction and monitoring that referred to software implementations. The list of articles retrieved from well-established data bases was enriched by backtracking of references provided by eligible articles. The current software availability and open-source status were tabulated. Results: We found 21 eligible articles, 7 of which (33 %) provide freely accessible software. Ultimately, only one article provides a link to an easy-to-comprehend, well-documented, and currently directly applicable free-of-charge open-source software. The lack of availability is mainly caused by blocked access and outdated links. Conclusions: While several software implementations exist for recruitment prediction, only a small fraction is freely accessible. These results highlight the need for future efforts to achieve free access to well-documented software implementations supporting researchers in routinely using statistical methods to arrive at realistic recruitment predictions in clinical trials.
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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.