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.
Keywords
Endoscopy Lower GI Tract - Colorectal cancer - Polyps, Adenomas - CRC screening - Endoscopic resection (polypectomy, ESD, EMRc) - Computer-assisted detection (CADe) - Computer-assisted characterization (CADx) - Leave-in-situ - Resect-and-discard
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
