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      Cost-effectiveness of Artificial Intelligence-Aided Colonoscopy for Adenoma Detection in Colon Cancer Screening

      research-article
      , MD, CM, MSc , , MD, , Pharm D, MSc, MHSC
      Journal of the Canadian Association of Gastroenterology
      Oxford University Press
      Adenoma detection, Artificial-intelligence, CADe, Colonoscopy, Colorectal cancer

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          Abstract

          Background and Aims

          Artificial intelligence-aided colonoscopy significantly improves adenoma detection. We assessed the cost-effectiveness of the GI Genius technology, an artificial intelligence-aided computer diagnosis for polyp detection (CADe), in improving colorectal cancer outcomes, adopting a Canadian health care perspective.

          Methods

          A Markov model with 1-year cycles and a lifetime horizon was used to estimate incremental cost-effectiveness ratio comparing CADe to conventional colonoscopy polyp detection amongst patients with a positive faecal immunochemical test. Outcomes were life years (LYs) and quality-adjusted life years (QALY) gained. The analysis applied costs associated with health care resource utilization, including procedures and follow-ups, from a provincial payer’s perspective using 2022 Canadian dollars. Effectiveness and cost data were sourced from the literature and publicly available databases. Extensive probabilistic and deterministic sensitivity analyses were performed, assessing model robustness.

          Results

          Life years and QALY gains for the CADe and conventional colonoscopy groups were 19.144 versus 19.125 and 17.137 versus 17.113, respectively. CADe and conventional colonoscopies’ overall per-case costs were $2990.74 and $3004.59, respectively. With a willingness-to-pay pre-set at $50,000/QALY, the incremental cost-effectiveness ratio was dominant for both outcomes, showing that CADe colonoscopy is cost-effective. Deterministic sensitivity analysis confirmed that the model was sensitive to the incidence risk ratio of adenoma per colonoscopy for large adenomas. Probabilistic sensitivity analysis showed that the CADe strategy was cost-effective in up to 73.4% of scenarios.

          Conclusion

          The addition of CADe solution to colonoscopy is a dominant, cost-effective strategy when used in faecal immunochemical test-positive patients in a Canadian health care setting.

          Abstract

          The use of computers in medicine is growing. Studies showed that computers increase the chance of finding cancer in colonoscopy. But the equipment is more expensive. We assessed the cost of using a computer for a colonoscopy. We showed that it is less costly and more successful than colonoscopy alone. We showed that using the computer for colonoscopy lowers the cost of Canada’ Health care.

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          Most cited references42

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          Adenoma Detection Rate and Risk of Colorectal Cancer and Death

          New England Journal of Medicine, 370(14), 1298-1306
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            Quality indicators for colonoscopy.

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              • Article: not found

              Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial

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                Author and article information

                Contributors
                Journal
                J Can Assoc Gastroenterol
                J Can Assoc Gastroenterol
                jcag
                Journal of the Canadian Association of Gastroenterology
                Oxford University Press (US )
                2515-2084
                2515-2092
                June 2023
                07 April 2023
                07 April 2023
                : 6
                : 3
                : 97-105
                Affiliations
                Division of Gastroenterology, McGill University Health Center , Montreal, Quebec, Canada
                Clinical Epidemiology, McGill University , Montreal, Quebec, Canada
                Division of Gastroenterology, the University of Montreal Hospital and University of Montreal Hospital Research Center , Montreal, Quebec, Canada
                Department of Health Economics and Outcomes Research, Medtronic Canada , Brampton, Ontario, Canada
                Author notes
                Correspondence: Alan N. Barkun, MD, CM, MSc, Division of Gastroenterology, McGill University Health Center, Montreal, Quebec, Canada; Clinical Epidemiology, McGill University, Montreal, Quebec, Canada, 1650 Cedar Avenue, D7.346, Montreal, Quebec H3G1A4, Canada, e-mail: Alan.Barkun.med@ 123456ssss.gouv.qc.ca
                Author information
                https://orcid.org/0000-0003-2004-7060
                Article
                gwad014
                10.1093/jcag/gwad014
                10235593
                37538187
                9025dd18-1238-46d0-80fc-65ff6c06819d
                © The Author(s) 2023. Published by Oxford University Press on behalf of the Canadian Association of Gastroenterology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 9
                Funding
                Funded by: Medtronic Canada;
                Categories
                Original Articles
                AcademicSubjects/MED00260

                adenoma detection,artificial-intelligence,cade,colonoscopy,colorectal cancer

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