Department of Gastroenterology, Porto Comprehensive Cancer Center/ RISE@CI-IPOP (Health Research Network).
MEDCIDS, Faculty of Medicine, University of Porto, Porto, Portugal.
Eur J Gastroenterol Hepatol. 2024 Feb 1;36(2):155-161. doi: 10.1097/MEG.0000000000002680. Epub 2023 Nov 15.
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.
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.
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.
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.
背景/目的:在低-中度胃癌(GC)发病率国家,不推荐进行内镜筛查。人工智能(AI)在 GC 检测方面具有很高的准确性,可能会提高筛查策略的成本效益。我们旨在评估 AI 用于不同 GC 发病率和不同 AI 系统准确性的国家中 GC 检测的成本效益。
使用 Markov 模型进行成本效益分析,比较不同的筛查策略(不筛查与 50 岁时单次食管胃十二指肠镜检查(EGD)与单独 EGD 每 5/10 年一次与联合 EGD 和筛查结肠镜检查每十年一次或两次在荷兰、意大利和葡萄牙)与可变 AI 准确性设置。主要结果是不同策略与不筛查相比的增量成本效益比。进行了确定性和概率敏感性分析。
如果没有 AI,在荷兰、意大利和葡萄牙,50 岁时进行一次 EGD、EGD 联合每十年筛查一次结肠镜检查和 EGD 联合每十年筛查两次结肠镜检查与不筛查相比具有成本效益。如果 AI 将 EGD 的准确性比白光内镜的准确性(89%)至少提高 1%,那么在意大利,联合每十年筛查两次也具有成本效益。如果 AI 准确性达到至少 96%,那么在荷兰,联合每十年筛查一次也具有成本效益。
在欧洲国家,AI 辅助 EGD 可能会提高联合 EGD 和筛查结肠镜检查的 GC 筛查的成本效益。AI 的实际成本效益效果可能取决于 AI 系统的准确性和成本。