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<p>We have previously described a free, public web-based tool, Trials to Publications, <a href="https://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi">https://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi</a>, which employs a machine-learning model based on title, abstract, and other metadata features to predict which publications are likely to present clinical outcome results from a given registered trial in ClinicalTrials.gov. We have now updated and expanded the scope of the tool, by extracting mentions of ClinicalTrials.gov registry numbers (NCT numbers) from the full-text of 3 online biomedical article collections (open access PubMed Central (PMC), EuroPMC, and OpenAlex), as well as retrieving biomedical publications that are mentioned within the ClinicalTrials.gov registry itself. These mentions greatly increase the number of linked publications identified by the tool and should assist those carrying out evidence syntheses as well as those studying the metascience of clinical trials.</p>

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Enhancing the scope of the Trials to Publications tool by identifying ClinicalTrial.gov registry mentions in full-text

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月25日

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  • Arthur W. Holt,
  • Neil R. Smalheiser

摘要

We have previously described 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 based on title, abstract, and other metadata features to predict which publications are likely to present clinical outcome results from a given registered trial in ClinicalTrials.gov. We have now updated and expanded the scope of the tool, by extracting mentions of ClinicalTrials.gov registry numbers (NCT numbers) from the full-text of 3 online biomedical article collections (open access PubMed Central (PMC), EuroPMC, and OpenAlex), as well as retrieving biomedical publications that are mentioned within the ClinicalTrials.gov registry itself. These mentions greatly increase the number of linked publications identified by the tool and should assist those carrying out evidence syntheses as well as those studying the metascience of clinical trials.