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New improved Aggregator: predicting which clinical trial articles derive from the same registered clinical trial.

ABSTRACT: Objectives:To identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence. Materials and Methods:We updated our previous model by creating larger, more recent, and more diverse positive and negative training sets consisting of article pairs that were (or not) linked to the same ClinicalTrials.gov trial registry number. Features were extracted from PubMed metadata; pairwise similarity scores were modeled using logistic regression and used to form clusters of articles that are likely to arise from the same registered clinical trial. Results:Articles from the same trial were identified with high accuracy (F1?=?0.859), nominally better than the previous model (F1?=?0.843). Predicted clusters showed a low error rate of splitting of 8-11% (ie, when 2 articles belonged to the same trial but were assigned to different clusters). Performance was similar whether only randomized controlled trial articles or a more diverse set of clinical trial articles were processed. Discussion:Metadata are surprisingly accurate in predicting when 2 articles derive from the same underlying clinical trial. Conclusion:We have continued confidence in the Aggregator tool which can be accessed publicly at http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/RCT_Tagger.cgi.

SUBMITTER: Smalheiser NR

PROVIDER: S-EPMC7660960 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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New improved Aggregator: predicting which clinical trial articles derive from the same registered clinical trial.

Smalheiser Neil R NR Holt Arthur W AW

JAMIA open 20201028 3

<h4>Objectives</h4>To identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence.<h4>Materials and methods</h4>We updated our previous model by creating larger, more recent, and more diverse positive and negative training sets consisting of article pairs that were (or not) linked to the same ClinicalTrials.gov trial registry number. Features were extracted from PubMed metadata; pairwise simi ...[more]

PMID: 33215068

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Project description:BackgroundResearchers should examine existing evidence to determine the need for a new study. It is unknown whether developers evaluate existing evidence to justify new cardiovascular clinical prediction rules (CPRs).ObjectiveWe aimed to assess whether authors of cardiovascular CPRs cited existing CPRs, why some authors did not cite existing CPRs, and why they thought existing CPRs were insufficient.MethodDerivation studies of cardiovascular CPRs from the International Register of Clinical Prediction Rules for Primary Care were evaluated. We reviewed the introduction sections to determine whether existing CPRs were cited. Using thematic content analysis, the stated reasons for determining existing cardiovascular CPRs insufficient were explored. Study authors were surveyed via e-mail and post. We asked whether they were aware of any existing cardiovascular CPRs at the time of derivation, how they searched for existing CPRs, and whether they thought it was important to cite existing CPRs.ResultsOf 85 derivation studies included, 48 (56.5%) cited existing CPRs, 33 (38.8%) did not cite any CPR, and four (4.7%) declared there was none to cite. Content analysis identified five categories of existing CPRs insufficiency related to: (1) derivation (5 studies; 11.4% of 44), (2) construct (31 studies; 70.5%), (3) performance (10 studies; 22.7%), (4) transferability (13 studies; 29.5%), and (5) evidence (8 studies; 18.2%). Authors of 54 derivation studies (71.1% of 76 authors contacted) responded to the survey. Twenty-five authors (46.3%) reported they were aware of existing CPR at the time of derivation. Twenty-nine authors (53.7%) declared they conducted a systematic search to identify existing CPRs. Most authors (90.7%) indicated citing existing CPRs was important.ConclusionCardiovascular CPRs are often developed without citing existing CPRs although most authors agree it is important. Common justifications for new CPRs concerned construct, including choice of predictor variables or relevance of outcomes. Developers should clearly justify why new CPRs are needed with reference to existing CPRs to avoid unnecessary duplication.

Dataset Information

New improved Aggregator: predicting which clinical trial articles derive from the same registered clinical trial.

Publications

New improved Aggregator: predicting which clinical trial articles derive from the same registered clinical trial.

Similar Datasets

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