Linking Trials to Publications: Enhancing Recall by Identifying Trial Registry Mentions in Full-Text

We have developed a free, public web-based tool, Trials to Publications, https://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi, which employs a machine learning model to predict which publications are likely to present clinical outcome results from a given registered trial in ClinicalTrials.gov. The tool has reasonably high precision, yet in a recent study we found that when registry mentions are not explicitly listed in metadata, textual clues (in title, abstract or other metadata) could identify only roughly 1/3-1/2 of the publications with high confidence. This finding has led us to expand the scope of the tool, to search for explicit mentions of registry numbers that are located within the full-text of publications. We have now retrieved ClinicalTrials.gov registry number mentions (NCT numbers) from the full-text of 3 online biomedical article collections (open access PubMed Central, EuroPMC, and OpenAlex), as well as retrieving biomedical citations that are mentioned within the ClinicalTrials.gov registry itself. These methods greatly increase the recall of identifying linked publications, and should assist those carrying out evidence syntheses as well as those studying the meta-science of clinical trials. HighlightsO_LIThose conducting systematic reviews, other evidence syntheses, and meta-science analyses often need to examine published evidence arising from clinical trials. Finding publications linked to a given trial is a difficult manual process, but several automated tools have been developed. The Trials to Publications tool is the only free, public, currently maintained web-based tool that predicts publications linked to a given trial in ClinicalTrials.gov. C_LIO_LIA recent analysis indicated that the Trials to Publications tool has good precision but limited recall. In the present paper, we greatly enhanced the recall by identifying registry mentions in full-text of articles indexed in open access PubMed Central, EuroPMC and OpenAlex. C_LIO_LIThe tool now has reasonably comprehensive coverage of registry mentions, both for identifying articles that present trial outcome results and for other types of articles that are linked to, or that discuss, the trials. This should greatly save effort during web searches of the literature. C_LI