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Diagnostic yield of the Japan NBI Expert Team (JNET) classification for endoscopic diagnosis of superficial colorectal neoplasms in a large-scale clinical practice database.
United European Gastroenterol J 2019; 7(7):914-923UE

Abstract

Background

Magnifying Narrow Band Imaging (NBI) during colonoscopy is a reliable method for differential and depth diagnoses of colorectal lesions. This study examined the diagnostic yield of magnifying NBI based on the Japan NBI Expert Team (JNET) classification in a clinical setting using a large-scale clinical practice database. Types 1, 2A, 2B and 3 correspond to the histopathological classifications of hyperplastic polyp/sessile-serrated polyp, low-grade intramucosal neoplasia, high-grade intramucosal neoplasia/shallow submucosal invasive cancer, and deep submucosal invasive cancer, respectively.

Methods

The prospective records of colonoscopy reports and pathological data of 1558 consecutive superficial colorectal lesions removed by colonoscopy were retrospectively analysed. After excluding 156 lesions, the documented JNET classifications of the remaining 1402 colorectal lesions were analysed. Diagnostic yield was analysed and also compared between expert endoscopists and nonexpert endoscopists.

Results

The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were respectively 75%, 96%, 74%, 96% and 93% for type 1; 91%, 70%, 92%, 67% and 87% for type 2A; 42%, 95%, 26%, 98% and 93% for type 2B; and 35%, 100%, 93%, 98% and 98% for type 3. Nonexpert and expert endoscopists alike had specificity, NPV and accuracy >90% for types 1, 2B and 3, and a sensitivity and PPV >90% for type 2A. Type 2B had a low sensitivity of 42% because it included various histological features.

Conclusions

The JNET classification proved useful in a clinical setting both for expert and nonexpert endoscopists, as was expected from the original JNET definition, but type 2B requires further investigation using pit pattern diagnosis.

Authors+Show Affiliations

Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan. Division of Gastroenterology and Hepatology, Toho University Omori Medical Center, Tokyo, Japan.Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.Molecular Pathology Division, National Cancer Center Research Institute, Tokyo, Japan.Division of Gastroenterology and Hepatology, Toho University Omori Medical Center, Tokyo, Japan.Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

31428416

Citation

Kobayashi, Shunsuke, et al. "Diagnostic Yield of the Japan NBI Expert Team (JNET) Classification for Endoscopic Diagnosis of Superficial Colorectal Neoplasms in a Large-scale Clinical Practice Database." United European Gastroenterology Journal, vol. 7, no. 7, 2019, pp. 914-923.
Kobayashi S, Yamada M, Takamaru H, et al. Diagnostic yield of the Japan NBI Expert Team (JNET) classification for endoscopic diagnosis of superficial colorectal neoplasms in a large-scale clinical practice database. United European Gastroenterol J. 2019;7(7):914-923.
Kobayashi, S., Yamada, M., Takamaru, H., Sakamoto, T., Matsuda, T., Sekine, S., ... Saito, Y. (2019). Diagnostic yield of the Japan NBI Expert Team (JNET) classification for endoscopic diagnosis of superficial colorectal neoplasms in a large-scale clinical practice database. United European Gastroenterology Journal, 7(7), pp. 914-923. doi:10.1177/2050640619845987.
Kobayashi S, et al. Diagnostic Yield of the Japan NBI Expert Team (JNET) Classification for Endoscopic Diagnosis of Superficial Colorectal Neoplasms in a Large-scale Clinical Practice Database. United European Gastroenterol J. 2019;7(7):914-923. PubMed PMID: 31428416.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Diagnostic yield of the Japan NBI Expert Team (JNET) classification for endoscopic diagnosis of superficial colorectal neoplasms in a large-scale clinical practice database. AU - Kobayashi,Shunsuke, AU - Yamada,Masayoshi, AU - Takamaru,Hiroyuki, AU - Sakamoto,Taku, AU - Matsuda,Takahisa, AU - Sekine,Shigeki, AU - Igarashi,Yoshinori, AU - Saito,Yutaka, Y1 - 2019/04/26/ PY - 2019/01/18/received PY - 2019/03/18/accepted PY - 2019/8/21/entrez PY - 2019/8/21/pubmed PY - 2019/8/21/medline KW - Colorectal neoplasms KW - Japan NBI Expert Team (JNET) classification KW - Narrow Band Imaging (NBI) KW - endoscopic diagnosis KW - magnifying NBI SP - 914 EP - 923 JF - United European gastroenterology journal JO - United European Gastroenterol J VL - 7 IS - 7 N2 - Background: Magnifying Narrow Band Imaging (NBI) during colonoscopy is a reliable method for differential and depth diagnoses of colorectal lesions. This study examined the diagnostic yield of magnifying NBI based on the Japan NBI Expert Team (JNET) classification in a clinical setting using a large-scale clinical practice database. Types 1, 2A, 2B and 3 correspond to the histopathological classifications of hyperplastic polyp/sessile-serrated polyp, low-grade intramucosal neoplasia, high-grade intramucosal neoplasia/shallow submucosal invasive cancer, and deep submucosal invasive cancer, respectively. Methods: The prospective records of colonoscopy reports and pathological data of 1558 consecutive superficial colorectal lesions removed by colonoscopy were retrospectively analysed. After excluding 156 lesions, the documented JNET classifications of the remaining 1402 colorectal lesions were analysed. Diagnostic yield was analysed and also compared between expert endoscopists and nonexpert endoscopists. Results: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were respectively 75%, 96%, 74%, 96% and 93% for type 1; 91%, 70%, 92%, 67% and 87% for type 2A; 42%, 95%, 26%, 98% and 93% for type 2B; and 35%, 100%, 93%, 98% and 98% for type 3. Nonexpert and expert endoscopists alike had specificity, NPV and accuracy >90% for types 1, 2B and 3, and a sensitivity and PPV >90% for type 2A. Type 2B had a low sensitivity of 42% because it included various histological features. Conclusions: The JNET classification proved useful in a clinical setting both for expert and nonexpert endoscopists, as was expected from the original JNET definition, but type 2B requires further investigation using pit pattern diagnosis. SN - 2050-6406 UR - https://www.unboundmedicine.com/medline/citation/31428416/Diagnostic_yield_of_the_Japan_NBI_Expert_Team__JNET__classification_for_endoscopic_diagnosis_of_superficial_colorectal_neoplasms_in_a_large_scale_clinical_practice_database_ L2 - http://journals.sagepub.com/doi/full/10.1177/2050640619845987?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub=pubmed DB - PRIME DP - Unbound Medicine ER -