Abstract
The SPIRIT 2013 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 has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials–Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials–Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that 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 for 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.
| Translated title of the contribution | Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension |
|---|---|
| Original language | Spanish |
| Journal | Revista Panamericana de Salud Publica/Pan American Journal of Public Health |
| Volume | 48 |
| DOIs | |
| State | Published - 2024 |
Funding
M.J.C. es investigador senior del National Institute for Health Research (NIHR) y recibe fondos del National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre; NIHR Surgical Reconstruction and Microbiology Research Centre y NIHR ARC West Midlands en la University of Birmingham y el University Hospitals Birmingham NHS Foundation Trust; Health Data Research UK; Innovate UK (parte de Investigaci\u00F3n y Desarrollo del Reino Unido); Health Foundation; Macmillan Cancer Support; y UCB Pharma. A.D. y J.D. tambi\u00E9n son investigadores senior del NIHR. S.J.V. recibe fondos de Engineering and Physical Sciences Research Council, UK Research and Innovation (UKRI), Accenture, Warwick Impact Fund, Health Data Research UK y el European Regional Development Fund. S.R. es empleado del Medical Research Council (UKRI). D.M. recibe apoyo de University of Ottawa Research Chair. A.B. recibe apoyo de los National Institutes of Health (NIH) (asignaci\u00F3n 7K01HL141771-02). M.K.E. recibe apoyo de la U.S. Food and Drug Administration (FDA), y D.P. recibe apoyo parcial de la Oficina del Director de la National Library of Medicine (NLM), US National Institutes of Health (NIH).
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health