Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway; Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway; Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Department of Gastroenterology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Sichuan, China.
Clin Gastroenterol Hepatol. 2023 Apr;21(4):949-959.e2. doi: 10.1016/j.cgh.2022.08.022. Epub 2022 Aug 28.
Artificial intelligence (AI) tools aimed at improving polyp detection have been shown to increase the adenoma detection rate during colonoscopy. However, it is unknown how increased polyp detection rates by AI affect the burden of patient surveillance after polyp removal.
We conducted a pooled analysis of 9 randomized controlled trials (5 in China, 2 in Italy, 1 in Japan, and 1 in the United States) comparing colonoscopy with or without AI detection aids. The primary outcome was the proportion of patients recommended to undergo intensive surveillance (ie, 3-year interval). We analyzed intervals for AI and non-AI colonoscopies for the U.S. and European recommendations separately. We estimated proportions by calculating relative risks using the Mantel-Haenszel method.
A total of 5796 patients (51% male, mean 53 years of age) were included; 2894 underwent AI-assisted colonoscopy and 2902 non-AI colonoscopy. When following U.S. guidelines, the proportion of patients recommended intensive surveillance increased from 8.4% (95% CI, 7.4%-9.5%) in the non-AI group to 11.3% (95% CI, 10.2%-12.6%) in the AI group (absolute difference, 2.9% [95% CI, 1.4%-4.4%]; risk ratio, 1.35 [95% CI, 1.16-1.57]). When following European guidelines, it increased from 6.1% (95% CI, 5.3%-7.0%) to 7.4% (95% CI, 6.5%-8.4%) (absolute difference, 1.3% [95% CI, 0.01%-2.6%]; risk ratio, 1.22 [95% CI, 1.01-1.47]).
The use of AI during colonoscopy increased the proportion of patients requiring intensive colonoscopy surveillance by approximately 35% in the United States and 20% in Europe (absolute increases of 2.9% and 1.3%, respectively). While this may contribute to improved cancer prevention, it significantly adds patient burden and healthcare costs.
旨在提高息肉检测准确率的人工智能 (AI) 工具已被证实可提高结肠镜检查中的腺瘤检出率。然而，目前尚不清楚 AI 提高的息肉检出率如何影响息肉切除后患者监测的负担。
我们对 9 项随机对照试验（中国 5 项、意大利 2 项、日本 1 项、美国 1 项）进行了汇总分析，比较了使用和不使用 AI 检测辅助的结肠镜检查。主要结局是建议进行强化监测（即 3 年间隔）的患者比例。我们分别分析了美国和欧洲建议的 AI 和非 AI 结肠镜检查的间隔时间。我们使用 Mantel-Haenszel 法计算相对风险来估计比例。
共纳入 5796 例患者（51%为男性，平均年龄 53 岁）；2894 例接受 AI 辅助结肠镜检查，2902 例接受非 AI 结肠镜检查。当遵循美国指南时，建议进行强化监测的患者比例从非 AI 组的 8.4%（95%CI，7.4%-9.5%）增加到 AI 组的 11.3%（95%CI，10.2%-12.6%）（绝对差异，2.9%[95%CI，1.4%-4.4%]；风险比，1.35[95%CI，1.16-1.57]）。当遵循欧洲指南时，它从 6.1%（95%CI，5.3%-7.0%）增加到 7.4%（95%CI，6.5%-8.4%）（绝对差异，1.3%[95%CI，0.01%-2.6%]；风险比，1.22[95%CI，1.01-1.47]）。
在美国，使用 AI 进行结肠镜检查将需要强化结肠镜监测的患者比例增加了约 35%；在欧洲，增加了 20%（绝对增加 2.9%和 1.3%）。虽然这可能有助于提高癌症预防效果，但它显著增加了患者负担和医疗保健成本。
