4.6 Article

Methodology reporting improved over time in 176,469 randomized controlled trials

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JOURNAL OF CLINICAL EPIDEMIOLOGY
卷 162, 期 -, 页码 19-28

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.jclinepi.2023.08.004

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Randomized controlled trials; Reporting guidelines; CONSORT; Text mining; Machine learning; Meta-research

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This study provides large-scale quantitative support for the hypothesis that RCT methodology reporting has improved over time. While there has been an increase in the reporting of some method information, there is still room for improvement. The differences in the proportion of items reported between disciplines are small.
Objectives: To describe randomized controlled trial (RCT) methodology reporting over time.Study Design and Setting: We used a deep learning-based sentence classification model based on the Consolidated Standards of Reporting Trials (CONSORT) statement, considered minimum requirements for reporting RCTs. We included 176,469 RCT reports published between 1966 and 2018. We analyzed the reporting trends over 5-year time periods, grouping trials from 1966 to 1990 in a single stratum. We also explored the effect of journal impact factor (JIF) and medical discipline.Results: Population, Intervention, Comparator, Outcome (PICO) items were commonly reported during each period, and reporting increased over time (e.g., interventions: 79.1% during 1966-1990 to 87.5% during 2010-2018). Reporting of some methods information has increased, although there is room for improvement (e.g., sequence generation: 10.8-41.8%). Some items are reported infrequently (e.g., allocation concealment: 5.1-19.3%). The number of items reported and JIF are weakly correlated (Pearson's r (162,702) 5 0.16, P < 0.001). The differences in the proportion of items reported between disciplines are small (<10%).Conclusion: Our analysis provides large-scale quantitative support for the hypothesis that RCT methodology reporting has improved over time. Extending these models to all CONSORT items could facilitate compliance checking during manuscript authoring and peer review, and support metaresearch.

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