CC BY-NC-ND 4.0 · Endosc Int Open 2025; 13: a25097278
DOI: 10.1055/a-2509-7278
Original article

Cost-effectiveness analysis of artificial intelligence-aided colonoscopy for adenoma detection and characterization in Spain

Marco Bustamante-Balén
1   Digestive Endoscopy Unit, Gastroenterology Department, La Fe University Hospital, Valencia, Spain (Ringgold ID: RIN16273)
2   Health Research Institute La Fe, IIS La Fe, Valencia, Spain (Ringgold ID: RIN551222)
,
Beatriz Merino Rodríguez
3   Endoscopy Unit, Department of Gastroenterology, Gregorio Marañón General University Hospital, Madrid, Spain
,
Luis Barranco
4   Endoscopy Unit, Digestive Department, Hospital del Mar, Barcelona, Spain (Ringgold ID: RIN16548)
,
Julen Monje
5   Health Economics & Outcomes Research Unit, Medtronic Ibérica S.A., Madrid, Spain (Ringgold ID: RIN69584)
,
María Álvarez
5   Health Economics & Outcomes Research Unit, Medtronic Ibérica S.A., Madrid, Spain (Ringgold ID: RIN69584)
,
Sofía de Pedro
6   Pharmacoeconomics & Outcomes Research Iberia (PORIB), Madrid, Spain
,
Itziar Oyagüez
6   Pharmacoeconomics & Outcomes Research Iberia (PORIB), Madrid, Spain
,
Nancy Van Lent
7   Health Economics & Outcomes Research, Medtronic International Trading Sarl, Tolochenaz, Switzerland (Ringgold ID: RIN30907)
,
6   Pharmacoeconomics & Outcomes Research Iberia (PORIB), Madrid, Spain
› Author Affiliations
Supported by: Medtronic Iberica S.A.

Abstract

Background and study aims

The aim of this study was to assess the cost-effectiveness of an intelligent endoscopy module for computer-assisted detection and characterization (CADe/CADx) compared with standard practice, from a Spanish National Health System perspective.

Methods

A Markov model was designed to estimate total costs, life years gained (LYG), and quality-adjusted life years (QALYs) over a lifetime horizon with annual cycles. A hypothetical cohort of 1,000 patients eligible for colonoscopy (mean age 61.32 years) was distributed between Markov states according to polyp size, location, and histology based on national screening program data. CADe/CADx efficacy was determined based on adenoma miss rates and natural disease evolution was simulated according to annual transition probabilities. Detected polyp management involved polypectomy and histopathology in standard practice, whereas with CADe/CADx leave-in-situ strategy was applied for ≤ 5 mm rectosigmoid non-adenomas and resect-and-discard strategy for the rest of ≤ 5mm polyps. Unit costs (€,2024) included the diagnostic procedure and polyp and colorectal cancer (CRC) management. A 3% annual discount rate was applied to costs and outcomes. Model inputs were validated by an expert panel.

Results

CADe/CADx was more effective (16.37 LYG and 14.32 QALYs) than standard practice (16.33 LYG and 14.27 QALYs) over a lifetime horizon. Total cost per patient was €2,300.76 with CADe/CADx and €2,508.75 with colonoscopy alone. In a hypothetical cohort of 1,000 patients, CADe/CADx avoided 173 polypectomies, 370 histopathologies, and 7 CRC cases. Sensitivity analyses confirmed model robustness.

Conclusions

The results of this analysis suggest that CADe/CADx would result in a dominant strategy versus standard practice in patients undergoing colonoscopy in Spain.

Supplementary Material



Publication History

Received: 01 August 2024

Accepted after revision: 17 December 2024

Accepted Manuscript online:
02 January 2025

Article published online:
14 March 2025

© 2025. 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/).

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Bibliographical Record
Marco Bustamante-Balén, Beatriz Merino Rodríguez, Luis Barranco, Julen Monje, María Álvarez, Sofía de Pedro, Itziar Oyagüez, Nancy Van Lent, María Mareque. Cost-effectiveness analysis of artificial intelligence-aided colonoscopy for adenoma detection and characterization in Spain. Endosc Int Open 2025; 13: a25097278.
DOI: 10.1055/a-2509-7278