Endoscopic prediction of advanced histology in colorectal lesions sized <10 mm using the Japan Narrow-band imaging Expert Team classification.
Dig Endosc
; 32(5): 785-790, 2020 Jul.
Article
em En
| MEDLINE
| ID: mdl-31630442
ABSTRACT
BACKGROUND AND AIM:
Endoscopic diagnosis of advanced histology in colorectal lesions sized <10 mm is essential for appropriate selection of resection methods. The Japan Narrow-band imaging Expert Team (JNET) classification has been recently validated for the evaluation of colorectal lesions. Our objective was to investigate the diagnostic value of the JNET classification for advanced histology in colorectal lesions sized <10 mm.METHODS:
We enrolled 680 patients with 1472 colorectal lesions sized <10 mm diagnosed according to the JNET classification and who subsequently underwent endoscopic or surgical resection between January and December 2017. We retrospectively examined the relationship between the JNET findings and pathological histology. Multivariate analysis was carried out to assess the predictive power of the JNET findings and clinical characteristics of lesions.RESULTS:
Advanced histology was present in 29 (2.0%) lesions. Advanced histology was absent in 68 lesions diagnosed as JNET type 1, whereas 1389 lesions diagnosed as JNET type 2A included 19 lesions of advanced histology (1.4%) with high-grade dysplasia alone. Eleven lesions diagnosed as JNET type 2B comprised eight lesions of advanced histology (72.7%) with four high-grade dysplasia and four submucosal invasive cancer, and two lesions diagnosed as JNET type 3 were submucosal invasive cancer. Multivariate analysis showed that JNET type 2B + 3 was a stronger predictive factor for advanced histology than other clinical risk factors.CONCLUSION:
Narrow-band imaging with magnification according to the JNET classification may be a useful modality for identification of advanced histology in colorectal lesions sized <10 mm.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias Colorretais
/
Colonoscopia
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País como assunto:
Asia
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article