Evidence map›Paper›PMID 35449476›Full record

ArticleSurgical endoscopy2022

Usefulness of magnifying endoscopy with acetic acid and narrow-band imaging for the diagnosis of duodenal neoplasms: proposal of a diagnostic algorithm.

Hiroshi Miura, Kyosuke Tanaka, Yuhei Umeda, Yohei Ikenoyama, Hiroki Yukimoto, Yasuhiko Hamada, Reiko Yamada, Junya Tsuboi, Misaki Nakamura, Masaki Katsurahara and 2 more

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Article in Surgical endoscopy, 2022. 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
0.8field-weighted citation impact, top 29% of its field
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, 5 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Hiroshi Miura *Department of Endoscopy, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
Kyosuke Tanaka *Department of Endoscopy, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan. kyosuket@med.mie-u.ac.jp.ORCID http://orcid.org/0000-0002-1402-7832
Yuhei UmedaDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Yohei IkenoyamaDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Hiroki YukimotoDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Yasuhiko HamadaDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Reiko YamadaDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Junya TsuboiDepartment of Endoscopy, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
Misaki NakamuraDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Masaki KatsuraharaDepartment of Endoscopy, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
Noriyuki HorikiDepartment of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, Tsu, Japan.
Hayato NakagawaDepartment of Endoscopy, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
Mie University · JPMie University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to clarify the features of superficial non-ampullary duodenal epithelial tumors (SNADETs) on magnifying endoscopy with narrow-band imaging (M-NBI) and magnifying endoscopy with acetic acid and narrow-band imaging (M-AANBI), and evaluate the efficacy of M-NBI/M-AANBI to distinguish high-grade adenomas or adenocarcinomas (HGA/AC) from low-grade adenomas (LGA).

methodsClinicopathological data on 62 SNADETs in 58 patients who underwent preoperative M-NBI/M-AANBI and endoscopic resection were retrospectively reviewed. The pathological results were classified into two categories, LGA and HGA/AC. We evaluated microvascular patterns (MVPs) and microsurface patterns (MSPs) observed by M-NBI and MSPs observed by M-AANBI for characterizing LGA and HGA/AC. The kappa value was calculated to assess the interobserver and intraobserver agreements of evaluation of M-AANBI images.

resultsPathologically, 38 lesions (61.3%) were LGA and 24 lesions (38.7%) were HGA/AC. HGA/AC tended to have irregular MVP and/or MSP on M-NBI. M-NBI diagnostic performance to distinguish HGA/AC from LGA showed 62.5% sensitivity, 68.4% specificity, and 66.1% accuracy. SNADETs had irregular MSP on M-AANBI. Three irregularity grades (iG) of MSP were observed by M-AANBI as follows: iG1, mild; iG2, moderate; iG3, significant. HGA/AC lesions had a significantly higher rate of iG3 than LGA lesions (p < 0.001). The iG2 was associated with HGA/AC in elevated lesions and LGA in depressed lesions. The diagnostic performance of M-AANBI was as follows: 95.8% sensitivity, 97.4% specificity, and 96.8% accuracy. The diagnostic accuracy of M-AANBI was significantly higher than that of M-NBI (p < 0.001). The kappa value for interobserver agreement on the diagnosis and irregularity grading of M-AANBI images was 0.742 and 0.719, respectively. These data indicate substantial interobserver agreement. Based on the above-mentioned results, we developed a M-AANBI diagnostic algorithm for SNADETs.

conclusionThe diagnostic algorithm for SNADETs using M-AANBI may be useful for differentiating between LGA and HGA/AC.

Indexed as

AdenocarcinomaAdenomaDuodenal NeoplasmsStomach NeoplasmsAcetic AcidAlgorithmsEndoscopy, GastrointestinalHumansNarrow Band ImagingRetrospective StudiesAcetic AcidAcetic acidAlgorithmDuodenal neoplasmsEndoscopic mucosal resectionEndoscopyNarrow-band imaging

Identifiers

PMID35449476
OpenAlexW4224279959

What OpenQuestion holds

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Read underepoch 390

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.