Cargando…

A novel method of grading gastric intestinal metaplasia based on the combination of subtype and distribution

BACKGROUND: Studies 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. METHODS: This was a cross-sectional study. No GIM, type I, II, and III...

Descripción completa

Detalles Bibliográficos
Autores principales: Wei, Ning, Zhong, Zhiheng, Shi, Ruihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7816327/
https://www.ncbi.nlm.nih.gov/pubmed/33472622
http://dx.doi.org/10.1186/s12935-021-01758-6
Descripción
Sumario:BACKGROUND: Studies 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. METHODS: This 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. RESULTS: 227 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. CONCLUSIONS: This study firstly combined GIM subtypes with its distribution forming a novel scoring system, which showed high prediction accuracy for malignant lesions.