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

Halil Kilicoglu, Lan Jiang, Linh Hoang, Evan Mayo-Wilson, Christiaan H. Vinkers, Willem M. Otte

Research output: Contribution to journalArticlepeer-review


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) = 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.

Original languageEnglish (US)
Pages (from-to)19-28
Number of pages10
JournalJournal of Clinical Epidemiology
StatePublished - Oct 2023


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

ASJC Scopus subject areas

  • Epidemiology


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