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. 2020 Sep 9:370:m3210.
doi: 10.1136/bmj.m3210.

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension

Samantha Cruz Rivera  1   2 , Xiaoxuan Liu  2   3   4   5   6 , An-Wen Chan  7 , Alastair K Denniston  8   2   3   4   5   9 , Melanie J Calvert  1   2   6   10   11   12 ; SPIRIT-AI and CONSORT-AI Working Group
Collaborators, Affiliations

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension

Samantha Cruz Rivera et al. BMJ. .

Abstract

The SPIRIT 2013 (The Standard Protocol Items: Recommendations for Interventional Trials) statement aims to improve the completeness of clinical trial protocol reporting, by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there is a growing recognition that interventions involving artificial intelligence need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes.The SPIRIT-AI extension is a new reporting guideline for clinical trials protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI. Both guidelines were developed using a staged consensus process, involving a literature review and expert consultation to generate 26 candidate items, which were consulted on by an international multi-stakeholder group in a 2-stage Delphi survey (103 stakeholders), agreed on in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants).The SPIRIT-AI extension includes 15 new items, which were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations around the handling of input and output data, the human-AI interaction and analysis of error cases.SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer-reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

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Conflict of interest statement

Support: MJC is a National Institute for Health Research (NIHR) Senior Investigator and receives funding from the NIHR Birmingham Biomedical Research Centre, the NIHR Surgical Reconstruction and Microbiology Research Centre and NIHR ARC West Midlands at the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, Health Data Research UK, Innovate UK (part of UK Research and Innovation), the Health Foundation, Macmillan Cancer Support, UCB Pharma. MK ElZarrad is supported by the US Food and Drug Administration (FDA). D Paltoo is supported in part by the Office of the Director at the National Library of Medicine (NLM), National Institutes of Health (NIH). MJC, AD and JJD are NIHR Senior Investigators. The views expressed in this article are those of the authors, Delphi participants, and stakeholder participants and may not represent the views of the broader stakeholder group or host institution, NIHR or the Department of Health and Social Care, or the NIH or FDA. DM is supported by a University of Ottawa Research Chair. AL Beam is supported by a National Institutes of Health (NIH) award 7K01HL141771-02. SJV receives funding from the Engineering and Physical Sciences Research Council, UK Research and Innovation (UKRI), Accenture, Warwick Impact Fund, Health Data Research UK and European Regional Development Fund. S Rowley is an employee for the Medical Research Council (UKRI). Competing interests: MJC has received personal fees from Astellas, Takeda, Merck, Daiichi Sankyo, Glaukos, GlaxoSmithKline, and the Patient-Centered Outcomes Research Institute (PCORI) outside the submitted work. PA Keane is a consultant for DeepMind Technologies, Roche, Novartis, Apellis, and has received speaker fees or travel support from Bayer, Allergan, Topcon, and Heidelberg Engineering. CJ Kelly is an employee of Google LLC and owns Alphabet stock. A Esteva is an employee of Salesforce. CRM. R Savage is an employee of Pinpoint Science. JM was an employee of AstraZeneca PLC at the time of this study.

Figures

Fig 1
Fig 1
CONSORT 2010 flow diagram - adapted for AI clinical trials
See this image and copyright information in PMC

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