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DOI: 10.1055/a-2313-4996
Effect of optical diagnosis training on recognition and treatment of submucosal invasive colorectal cancer in community hospitals: a prospective multicenter intervention study
Abstract
Background Recognition of submucosal invasive colorectal cancer (T1 CRC) is difficult, with sensitivities of 35 %–60 % in Western countries. We evaluated the real-life effects of training in the OPTICAL model, a recently developed structured and validated prediction model, in Dutch community hospitals.
Methods In this prospective multicenter study (OPTICAL II), 383 endoscopists from 40 hospitals were invited to follow an e-learning program on the OPTICAL model, to increase sensitivity in detecting T1 CRC in nonpedunculated polyps. Real-life recognition of T1 CRC was then evaluated in 25 hospitals. Endoscopic and pathologic reports of T1 CRCs detected during the next year were collected retrospectively, with endoscopists unaware of this evaluation. Sensitivity for T1 CRC recognition, R0 resection rate, and treatment modality were compared for trained vs. untrained endoscopists.
Results 1 year after e-learning, 528 nonpedunculated T1 CRCs were recorded for endoscopies performed by 251 endoscopists (118 [47 %] trained). Median T1 CRC size was 20 mm. Lesions were mainly located in the distal colorectum (66 %). Trained endoscopists recognized T1 CRCs more frequently than untrained endoscopists (sensitivity 74 % vs. 62 %; mixed model analysis odds ratio [OR] 2.90, 95 %CI 1.54–5.45). R0 resection rate was higher for T1 CRCs detected by trained endoscopists (69 % vs. 56 %; OR 1.73, 95 %CI 1.03–2.91).
Conclusion Training in optical recognition of T1 CRCs in community hospitals was associated with increased recognition of T1 CRCs, leading to higher en bloc and R0 resection rates. This may be an important step toward more organ-preserving strategies.
Publication History
Received: 07 April 2023
Accepted: 24 April 2024
Accepted Manuscript online:
24 April 2024
Article published online:
11 June 2024
© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
Georg Thieme Verlag KG
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