ArticleCancer cell international2021
A novel method of grading gastric intestinal metaplasia based on the combination of subtype and distribution.
Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Reproducible Topographic Phenotypes and Three-Phase Anatomical Evolution of Gastric Intestinal Metaplasia.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Article
- History of chronic gastritis: How our perceptions have changed.World journal of gastroenterology · 2024Review
- Chronic Autoimmune Gastritis: Modern Diagnostic Principles.Diagnostics (Basel, Switzerland) · 2021Review
- Correction to: A novel method of grading gastric intestinal metaplasia based on the combination of subtype and distribution.Cancer cell international · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStudies have shown the value of subtypes and distribution of gastric intestinal metaplasia (GIM) for prediction of gastric cancer. We aim to combine GIM subtypes and distribution to form a new scoring system for GIM.
methodsThis was a cross-sectional study. No GIM, type I, II, and III GIM of gastric antrum and corpus scored 0-3 points respectively. Then the severity of the whole stomach was calculated in two ways: 1. The gastric antrum and corpus scores were added together, with a score ranging from 0 to 6, which named "Subtype Distribution Score of Gastric Intestinal Metaplasia (SDSGIM)". 2. Direct classification according to a table corresponding to that of OLGIM. We compared the SDSGIM among benign lesions, dysplasia, and cancer and drew receiver operating characteristic (ROC) curve to determine the optimal cut-off value. According to the cut-off value and the classification from the table, the predictive ability of these two methods were calculated.
results227 patients were included. For SDSGIM, benign lesion group was significantly different from dysplasia or cancer group. Area under curve of ROC curve was 0.889 ± 0.023. The optimal cut-off value was 3. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of SDSGIM for malignancy were 89.5%, 78.0%, 74.6%, 91.2% and 82.8%. And those for the second classification method were 84.2%, 82.6%, 77.7%, 87.9%, and 83.3% respectively.
conclusionsThis study firstly combined GIM subtypes with its distribution forming a novel scoring system, which showed high prediction accuracy for malignant lesions.
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