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Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy
Background and study aims Artificial intelligence (AI)-assisted colonoscopy has proven to be effective compared with colonoscopy alone in an average-risk population. We aimed to evaluate the cost-utility of GI GENIUS, the first marketed real-time AI system in an Italian high-risk population. Methods...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637858/ https://www.ncbi.nlm.nih.gov/pubmed/37954109 http://dx.doi.org/10.1055/a-2136-3428 |
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author | Hassan, Cesare Povero, Massimiliano Pradelli, Lorenzo Spadaccini, Marco Repici, Alessandro |
author_facet | Hassan, Cesare Povero, Massimiliano Pradelli, Lorenzo Spadaccini, Marco Repici, Alessandro |
author_sort | Hassan, Cesare |
collection | PubMed |
description | Background and study aims Artificial intelligence (AI)-assisted colonoscopy has proven to be effective compared with colonoscopy alone in an average-risk population. We aimed to evaluate the cost-utility of GI GENIUS, the first marketed real-time AI system in an Italian high-risk population. Methods A 1-year cycle cohort Markov model was developed to simulate the disease evolution of a cohort of Italian individuals positive on fecal immunochemical test (FIT), aged 50 years, undergoing colonoscopy with or without the AI system. Adenoma or colorectal cancer (CRC) were identified according to detection rates specific for each technique. Costs were estimated from the Italian National Health Service perspective. Results Colonoscopy+AI system was dominant with respect to standard colonoscopy. The GI GENIUS system prevented 155 CRC cases (–2.7%), 77 CRC-related deaths (–2.8%), and improved quality of life (+0.027 QALY) with respect to colonoscopy alone. The increase in screening cost (+€10.50) and care for adenoma (+€3.53) was offset by the savings in cost of care for CRC (–€28.37), leading to a total savings of €14.34 per patient. Probabilistic sensitivity analysis confirmed the cost-efficacy of the AI system (almost 80% probability). Conclusions The implementation of AI detection tools in colonoscopy after patients test FIT-positive seems to be a cost-saving strategy for preventing CRC incidence and mortality. |
format | Online Article Text |
id | pubmed-10637858 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-106378582023-11-11 Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy Hassan, Cesare Povero, Massimiliano Pradelli, Lorenzo Spadaccini, Marco Repici, Alessandro Endosc Int Open Background and study aims Artificial intelligence (AI)-assisted colonoscopy has proven to be effective compared with colonoscopy alone in an average-risk population. We aimed to evaluate the cost-utility of GI GENIUS, the first marketed real-time AI system in an Italian high-risk population. Methods A 1-year cycle cohort Markov model was developed to simulate the disease evolution of a cohort of Italian individuals positive on fecal immunochemical test (FIT), aged 50 years, undergoing colonoscopy with or without the AI system. Adenoma or colorectal cancer (CRC) were identified according to detection rates specific for each technique. Costs were estimated from the Italian National Health Service perspective. Results Colonoscopy+AI system was dominant with respect to standard colonoscopy. The GI GENIUS system prevented 155 CRC cases (–2.7%), 77 CRC-related deaths (–2.8%), and improved quality of life (+0.027 QALY) with respect to colonoscopy alone. The increase in screening cost (+€10.50) and care for adenoma (+€3.53) was offset by the savings in cost of care for CRC (–€28.37), leading to a total savings of €14.34 per patient. Probabilistic sensitivity analysis confirmed the cost-efficacy of the AI system (almost 80% probability). Conclusions The implementation of AI detection tools in colonoscopy after patients test FIT-positive seems to be a cost-saving strategy for preventing CRC incidence and mortality. Georg Thieme Verlag KG 2023-11-10 /pmc/articles/PMC10637858/ /pubmed/37954109 http://dx.doi.org/10.1055/a-2136-3428 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Hassan, Cesare Povero, Massimiliano Pradelli, Lorenzo Spadaccini, Marco Repici, Alessandro Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy |
title | Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy |
title_full | Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy |
title_fullStr | Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy |
title_full_unstemmed | Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy |
title_short | Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy |
title_sort | cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in italy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637858/ https://www.ncbi.nlm.nih.gov/pubmed/37954109 http://dx.doi.org/10.1055/a-2136-3428 |
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