Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

Alexander P. L. Martindale, Carrie D. Llewellyn, Richard O. Visser, Benjamin Ng, Victoria Ngai, Aditya U. Kale, Lavinia Ferrante Ruffano, Robert M. Golub, Gary S. Collins, David Moher, Melissa D. McCradden, Lauren Oakden-Rayner, Samantha Cruz Rivera, Melanie Calvert, Christopher J. Kelly, Cecilia S. Lee, Christopher Yau, An-Wen Chan, Pearse A. Keane, Andrew L. Beam, Alastair K. Denniston and Xiaoxuan Liu ()
Additional contact information
Alexander P. L. Martindale: Brighton and Sussex Medical School
Carrie D. Llewellyn: Brighton and Sussex Medical School
Richard O. Visser: Brighton and Sussex Medical School
Benjamin Ng: Sandwell and West Birmingham NHS Trust
Victoria Ngai: University College London Medical School
Aditya U. Kale: University of Birmingham
Lavinia Ferrante Ruffano: University of York
Robert M. Golub: Northwestern University Feinberg School of Medicine
Gary S. Collins: University of Oxford
David Moher: Ottawa Hospital Research Institute
Melissa D. McCradden: The Hospital for Sick Children
Lauren Oakden-Rayner: University of Adelaide
Samantha Cruz Rivera: University of Birmingham
Melanie Calvert: University of Birmingham
Christopher J. Kelly: Google Health
Cecilia S. Lee: University of Washington
Christopher Yau: University of Oxford
An-Wen Chan: Women’s College Hospital. University of Toronto
Pearse A. Keane: Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology
Andrew L. Beam: Harvard. T.H. Chan School of Public Health
Alastair K. Denniston: University of Birmingham
Xiaoxuan Liu: University of Birmingham

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77–94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines.

Date: 2024
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DOI: 10.1038/s41467-024-45355-3

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