Evidence map›Paper›PMID 39789214›Full record

ArticleScientific reports2025

Impact of narrow band imaging in prediction of histology of advanced colorectal neoplasia.

Tomas Grega, Klara Kmochova, Katerina Hejcmanova, Ondrej Ngo, Nadija Brodyuk, Ondrej Majek, Jan Bures, Petr Urbanek, Miroslav Zavoral, Stepan Suchanek

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Tomas GregaDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia. tomas.grega@uvn.cz.ORCID 0000-0002-2490-8078
Klara KmochovaDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia.
Katerina HejcmanovaInstitute of Biostatistics and Analyses Masaryk University, Brno, Czechia.
Ondrej NgoInstitute of Biostatistics and Analyses Masaryk University, Brno, Czechia.
Nadija BrodyukDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia.
Ondrej MajekInstitute of Biostatistics and Analyses Masaryk University, Brno, Czechia.
Jan BuresDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia.
Petr UrbanekDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia.
Miroslav ZavoralDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia.
Stepan SuchanekDepartment of Internal Medicine, 1st Faculty of Medicine Charles University, Military University Hospital, Prague, Czechia.

Funding

Agentura Pro Zdravotnický Výzkum České Republiky NU22-08-00424lékařská fakulta Univerzity Karlovy CooperatioMinisterstvo Obrany České Republiky DZVRO - MO1012
6 · The paper itself

Abstract

We assessed the diagnostic performance of the Narrow-Band Imaging (NBI) International Colorectal Endoscopic Classification (NICE) and the Japan NBI Expert Team classification (JNET) in predicting histological outcomes of advanced colorectal lesions. Additionally, we evaluated the sensitivity and positive predictive value (PPV) of the JNET and NICE classifications individually for high-grade lesions (including HGD adenomas, intramucosal carcinomas, and T1 carcinomas). This was a retrospective analysis of prospectively collected data, involving 211 patients (130 men, mean age 60 years) who underwent colonoscopy with endoscopic resection of advanced colorectal neoplasia (lesions ≥ 10 mm). Lesions were classified using both NICE and JNET criteria, and final histopathological results were used for comparison. Of the 257 lesions analyzed, the NICE classification accurately classifies a large proportion of lesions (93.8%). In JNET classification we observed 77.4% correctly classified lesions. Specifically, the sensitivity and positive predictive value (PPV) of the NICE classification for high-grade lesions were 100% and 24.4%, respectively. For the JNET classification, the sensitivity and PPV for high-grade lesions were 56.6% and 57.7%, respectively. The JNET classification, with a positive predictive value of 57.7% for high-grade colorectal lesions (including HGD adenomas, intramucosal carcinomas, and T1 carcinomas), should be used for decision-making regarding appropriate subsequent endoscopic therapy.

Indexed as

ColonoscopyColorectal NeoplasmsNarrow Band ImagingAdenomaAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesSensitivity and SpecificityColonoscopyColon tumourDiagnostic accuracyJNET classificationNarrow-band imagingNICE classification

Identifiers

PMID39789214
PMCPMC11718093

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.