TY - JOUR
T1 - Combined gastric and colorectal cancer endoscopic screening may be cost-effective in Europe with the implementation of artificial intelligence
T2 - An economic evaluation
AU - Libanio, Diogo
AU - Antonelli, Giulio
AU - Marijnissen, Fleur
AU - Spaander, Maanon C.W.
AU - Hassan, Cesare
AU - Dinis-Ribeiro, Mario
AU - Areia, Miguel
N1 - Publisher Copyright:
© 2024 Lippincott Williams and Wilkins. All rights reserved.
PY - 2024/2
Y1 - 2024/2
N2 - Background/aims Endoscopic screening for gastric cancer (GC) is not recommended in low-intermediate incidence countries. Artificial intelligence (AI) has high accuracy in GC detection and might increase the cost-effectiveness of screening strategies. We aimed to assess the cost-effectiveness of AI for GC detection in settings with different GC incidence and different accuracies of AI systems. Methods Cost-effectiveness analysis (using Markov model) comparing different screening strategies (no screening versus single esophagogastroduodenoscopy (EGD) at 50 years versus stand-alone EGD every 5/10 years versus combined EGD and screening colonoscopy once or twice per decade in Netherlands, Italy and Portugal) with variable AI accuracy settings. The primary outcome was the incremental cost-effectiveness ratio of the different strategies versus no screening. Deterministic and probabilistic sensitivity analyses were conducted. Results Without AI, one single EGD at 50 years (Netherlands, Italy, Portugal), EGD combined with screening colonoscopy once per decade (Italy and Portugal) and EGD combined with screening colonoscopy twice per decade (Portugal) are cost-effective when compared with no screening. If AI increases the accuracy of EGD by at least 1% in comparison to the accuracy of white-light endoscopy accuracy (89%), combined screening twice per decade also becomes cost-effective in Italy. If AI accuracy reaches at least 96%, combined screening once per decade is also cost-effective in the Netherlands. Discussion In European countries, AI-assisted EGD may improve the cost-effectiveness of GC screening with combined EGD and screening colonoscopy. The actual effect of AI on cost-effectiveness may vary dependent on the accuracy and costs of the AI system.
AB - Background/aims Endoscopic screening for gastric cancer (GC) is not recommended in low-intermediate incidence countries. Artificial intelligence (AI) has high accuracy in GC detection and might increase the cost-effectiveness of screening strategies. We aimed to assess the cost-effectiveness of AI for GC detection in settings with different GC incidence and different accuracies of AI systems. Methods Cost-effectiveness analysis (using Markov model) comparing different screening strategies (no screening versus single esophagogastroduodenoscopy (EGD) at 50 years versus stand-alone EGD every 5/10 years versus combined EGD and screening colonoscopy once or twice per decade in Netherlands, Italy and Portugal) with variable AI accuracy settings. The primary outcome was the incremental cost-effectiveness ratio of the different strategies versus no screening. Deterministic and probabilistic sensitivity analyses were conducted. Results Without AI, one single EGD at 50 years (Netherlands, Italy, Portugal), EGD combined with screening colonoscopy once per decade (Italy and Portugal) and EGD combined with screening colonoscopy twice per decade (Portugal) are cost-effective when compared with no screening. If AI increases the accuracy of EGD by at least 1% in comparison to the accuracy of white-light endoscopy accuracy (89%), combined screening twice per decade also becomes cost-effective in Italy. If AI accuracy reaches at least 96%, combined screening once per decade is also cost-effective in the Netherlands. Discussion In European countries, AI-assisted EGD may improve the cost-effectiveness of GC screening with combined EGD and screening colonoscopy. The actual effect of AI on cost-effectiveness may vary dependent on the accuracy and costs of the AI system.
UR - http://www.scopus.com/inward/record.url?scp=85180593436&partnerID=8YFLogxK
U2 - 10.1097/MEG.0000000000002680
DO - 10.1097/MEG.0000000000002680
M3 - Article
C2 - 38131423
AN - SCOPUS:85180593436
SN - 0954-691X
VL - 36
SP - 155
EP - 161
JO - European Journal of Gastroenterology and Hepatology
JF - European Journal of Gastroenterology and Hepatology
IS - 2
ER -