SynthesisWorld journal of gastroenterology2020
Diagnostic efficacy of the Japan Narrow-band-imaging Expert Team and Pit pattern classifications for colorectal lesions: A meta-analysis.
Synthesis in World journal of gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- Endoscopic Submucosal Dissection, Endoscopic Mucosal Resection, and Transanal Minimally Invasive Surgery for the Management of Rectal and Anorectal Lesions: A Narrative Review.Journal of clinical medicine · 2023Review
- Mucosal imaging in colon polyps: New advances and what the future may hold.World journal of gastroenterology · 2022Review
- Texture and color enhancement imaging in magnifying endoscopic evaluation of colorectal adenomas.World journal of gastrointestinal endoscopy · 2022Article
- Diagnostic Value of Endoscopic Narrow-Band Imaging Technique in Early Gastric Cancer and Precancerous Lesions.Scanning · 2022Article
- Indications and outcomes of endoscopic resection for non-pedunculated colorectal lesions: A narrative review.World journal of gastrointestinal endoscopy · 2021Review
- [Japan narrow-band imaging Expert Team type 2B colorectal cancer: consistency between endoscopic prediction and pathological diagnosis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2021Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPit pattern classification using magnifying chromoendoscopy is the established method for diagnosing colorectal lesions. The Japan Narrow-band-imaging (NBI) Expert Team (JNET) classification is a novel NBI magnifying endoscopic classification that focuses on the vessel, and surface patterns.
aimTo determine the diagnostic efficacy of each category of the JNET and Pit pattern classifications for colorectal lesions.
methodsA systematic literature search was performed using PubMed, Embase, the Cochrane Library, and Web of Science databases. The pooled sensitivity, specificity, diagnostic odds ratio, and area under the summary receiver operating characteristic curve of each category of the JNET and Pit pattern classifications were calculated.
resultsA total of 19227 colorectal lesions in 31 studies were included. The diagnostic performance of the JNET classification was equivalent to the Pit pattern classification in each corresponding category. The pooled sensitivity, specificity, and area under the curve (AUC) for each category of the JNET classification were as follows: 0.73 (95%CI: 0.55-0.85), 0.99 (95%CI: 0.97-1.00), and 0.97 (95%CI: 0.95-0.98), respectively, for Type 1; 0.88 (95%CI: 0.78-0.94), 0.72 (95%CI: 0.64-0.79), and 0.84 (95%CI: 0.81-0.87), respectively, for Type 2A; 0.56 (95%CI: 0.47-0.64), 0.91 (95%CI: 0.79-0.96), and 0.72 (95%CI: 0.68-0.76), respectively, for Type 2B; 0.51 (95%CI: 0.42-0.61), 1.00 (95%CI: 1.00-1.00), and 0.90 (95%CI: 0.87-0.93), respectively, for Type 3.
conclusionThis meta-analysis suggests that the diagnostic efficacy of the JNET classification may be equivalent to that of the Pit pattern classification. However, due to its simpler and clearer clinical application, the JNET classification should be promoted for the classification of colorectal lesions, and to guide the treatment strategy.
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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.