Evidence map›Paper›PMID 35091754›Full record

ArticleJournal of gastroenterology2022

Differential diagnosis of superficial duodenal epithelial tumor and non-neoplastic lesion in duodenum by magnified endoscopic examination with image-enhanced endoscopy.

Atsushi Nakayama, Motohiko Kato, Teppei Masunaga, Yoko Kubosawa, Yukie Hayashi, Mari Mizutani, Yoshiyuki Kiguchi, Motoki Sasaki, Yusaku Takatori, Noriko Matsuura and 3 more

Abstract read
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In one paragraph

Article in Journal of gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

8 citing papers in PubMed, 16 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

13 authors at 1 institution in 1 country.

Atsushi NakayamaDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Motohiko KatoDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan. motohikokato@keio.jp.ORCID 0000-0002-7579-1316
Teppei MasunagaDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Yoko KubosawaDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Yukie HayashiDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Mari MizutaniDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Yoshiyuki KiguchiDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Motoki SasakiDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Yusaku TakatoriDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Noriko MatsuuraDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Makoto MutaguchiDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Kaoru TakabayashiDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Naohisa YahagiDivision of Research and Development for Minimally Invasive Treatment, Cancer Center, Keio University School of Medicine, Tokyo, Japan.
Keio University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDifferential diagnosis of superficial duodenal epithelial tumors (SDETs) and non-neoplastic lesions (NNLs) in duodenum by endoscopy is difficult. Here, we attempted to distinguish them by magnified endoscopic examination with image-enhanced endoscopy (IEE-ME).

methodsVarious IEE-ME findings of 95 SDETs who underwent endoscopic resection and 58 NNLs who underwent biopsy were retrospectively reviewed.

resultsWhen we compared the IEE-ME findings of SDETs and NNLs, the presence of demarcation line (DL) (97.9% vs. 79.3%, P = 0.0002), white opaque substance (WOS) (84.2% vs. 1.7%, P < 0.0001) and light blue crest (LBC) (93.7% vs. 32.8%, P < 0.0001) and the absence of enlarged marginal epithelium (EME) (98.9% vs. 62.1%, P < 0.0001) were significantly more frequent in SDETs than NNLs. When divided into each superficial structure, it was the most effective to evaluate the combination of WOS and LBC as SDET with open-loop structure (OLS), and the combination of DL and EME as SDET with closed-loop structure (CLS). However, LBC was excluded because of low inter- and intra-observer agreements. Finally, the sensitivity, specificity and accuracy for the diagnosis of SDETs were 88.4%, 98.3% and 92.2%, respectively, and we developed an algorithm for the differential diagnosis of duodenal lesions.

conclusionWe could distinguish SDET from NNL, diagnosed SDET as presence of WOS indicated OLS of superficial structure, and presence of DL and absence of EME indicated CLS of superficial structure.

Indexed as

DuodenumNeoplasms, Glandular and EpithelialDiagnosis, DifferentialEndoscopy, GastrointestinalHumansRetrospective StudiesDifferential diagnosisDuodenumEndoscopic diagnosisNon-neoplastic lesionSuperficial duodenal epithelial tumor

Identifiers

PMID35091754
OpenAlexW4210698827

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.