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

By Samantha Cruz Rivera, Xiaoxuan Liu, A. Chan, A. Denniston, Melanie Calvert, H. Ashrafian, Andrew Beam, Gary S Collins, A. Darzi, J. J. Deeks and 30 more. British medical journal, 2020

1,148 citations recorded by the source corpus.

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.

Subfields: Economics and Econometrics, Health Informatics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/79849910571cd5bb0f5960343915e282d7b699ec

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Citations in the corpus

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare (2023, neutral): “TRIPOD-AI [16], CLAIM [58], CONSORTAI [49], DECIDE-AI [77], PROBAST-AI [16], CLEAR [39]).”
Artificial Intelligence–Based Chatbots for Promoting Health Behavioral Changes: Systematic Review (2023, positive): “AI techniques specific to AI chatbot interventions were also appraised using the CONSORT-AI (Consolidated Standards of Reporting Trials–Artificial Intelligence) extension guidance for AI studies [20].”
Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review (2022, methodology): “AIPM-speci ﬁ c guidelines have been developed as extensions to the CONSORT and SPIRIT guidelines for reporting on clinical trials and their protocols respectively 64,65 .”
The Fallacy of AI Functionality (2022, background): “In fact, healthcare is the ﬁeld where AI product failures appear to be the most visible, in part due to the rigor of pre-established evaluation processes [20, 119, 160, 205].”
Harnessing multimodal data integration to advance precision oncology (2021, methodology): “SPIRIT-AI and CONSORT-AI are consensus guidelines for AI in clinical trial protocols and reports, respectively, that extend the SPIRIT and CONSORT guidelines for randomized clinical trials 134–136 .”