Evidence map›Paper›PMID 37011917›Full record

ArticleClinical endoscopy2023

Exploring quality indicators for the detection of Helicobacter pylori-naïve gastric cancer: a cross-sectional nationwide survey.

Fumiaki Ishibashi, Toshiaki Hirasawa, Hiroya Ueyama, Yohei Minato, Sho Suzuki

Abstract read
In one paragraph

Article in Clinical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. A mathematical simulation model to determine the optimal endoscopic screening strategy for detection of H. pylori-naïve gastric neoplasms.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2024
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Fumiaki IshibashiDepartment of Gastroenterology, International University of Health and Welfare Ichikawa Hospital, Chiba.
Toshiaki HirasawaDepartment of Gastroenterology, Cancer Institute Hospital, Tokyo, Japan.
Hiroya UeyamaDepartment of Gastroenterology, Juntendo University School of Medicine, Tokyo, Japan.
Yohei MinatoDepartment of Gastrointestinal Endoscopy, NTT Medical Center Tokyo, Tokyo, Japan.
Sho SuzukiDepartment of Gastroenterology, International University of Health and Welfare Ichikawa Hospital, Chiba.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimsDiagnosis of Helicobacter pylori-naïve gastric cancer (HPNGC) is becoming increasingly important. This study aimed to explore the quality indicators for HPNGC detection.

methodsWe conducted a cross-sectional, nationwide, web-based survey of gastrointestinal endoscopists in Japan. In addition to questions about the number of HPNGC cases detected in a year and basic information, the questionnaire also consisted of 28 questions: (1) 18 about HPNGC awareness, (2) six about diagnostic proactiveness, and (3) four about interest in HPNGC.

resultsValid responses were obtained from 712 endoscopists. The Japan Gastroenterological Endoscopy Society-certified endoscopists had a significantly higher HPNGC detection rate than the nonspecialists (0.42% vs. 0.32%, respectively; p=0.008). The results of the multiple regression analysis showed that Japan Gastroenterological Endoscopy Society certification and high awareness and interest scores were independent predictors of the HPNGC detection rate (p=0.012, p<0.001, p=0.024, respectively). Principal component analysis showed that the endoscopists who attended conferences for collecting information on HPNGC had a higher level of awareness.

conclusionTo improve the detection of HPNGC, it is necessary to increase the awareness of the disease. It is hoped that relevant societies will play an important role in endoscopists' education.

Indexed as

EndoscopyHelicobacter pyloriStomach neoplasms

Identifiers

PMID37011917
PMCPMC10393563

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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.