ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2021
[Japan narrow-band imaging Expert Team type 2B colorectal cancer: consistency between endoscopic prediction and pathological diagnosis].
Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- The Korean Rectal Cancer Multidisciplinary Committee Clinical Practice Guidelines for Rectal Cancer version 2.0.Annals of coloproctology · 2026Guideline
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo explore the potential factors that affect the accuracy of endoscopic diagnosis for Japan narrow-band imaging (NBI) Expert Team (JNET) type 2B colorectal lesions.
objectiveThe clinical data were collected from 261 patients with JNET type 2B colorectal lesions diagnosed in Nanfang Hospital between July, 2018 and July, 2021. We analyzed the macroscopic type, size, location or pit pattern classification of the lesions for their potential influence of the diagnostic accuracy of JNET type 2B lesions.
objectiveThe 261 lesions included 91 low-grade intramucosal neoplasia lesions (34.9%), 132 high-grade intramucosal neoplasia lesions (50.6%), 13 submucosal invasive cancer lesions (5.0%), and 25 deep submucosal invasive cancer lesions (9.6%). The coincidence rate between endoscopic prediction and pathological diagnosis of these lesions was 55.6% (145/ 261). The macroscopic type and size of the lesions were significantly associated with the diagnostic accuracy of JNET type 2B lesions (
objectiveBoth the macroscopic type and size affect the accuracy of endoscopic diagnosis of JNET type 2B colorectal lesions. JNET classification combined with pit pattern types can have better accuracy in predicting the pathological diagnosis of these lesions.
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