Predictive Factors for Differentiating Gastrointestinal Stromal Tumors from Leiomyomas Based on Endoscopic Ultrasonography Findings in Patients with Gastric Subepithelial Tumors: A Multicenter Retrospective Study

Abstract

Background/Aims: The utility of endoscopic ultrasonography (EUS) for differentiating gastrointestinal stromal tumors (GISTs) and leiomyomas of the stomach is not well known. We aimed to evaluate the ability of EUS for differentiating gastric GISTs and leiomyomas. Methods: We retrospectively reviewed the medical records of patients with histopathologically proven GISTs (n=274) and leiomyomas (n=87). In two consensus meetings, the inter-observer variability in the EUS image analysis was reduced. Using logistic regression analyses, we selected predictive factors and constructed a predictive model and nomogram for differentiating GISTs from leiomyomas. A receiver operating characteristic (ROC) curve analysis was performed to measure the discrimination performance in the development and internal validation sets. Results: Multivariate analysis identified heterogeneity (odds ratio [OR], 9.48), non-cardia (OR, 19.11), and Older age (OR, 1.06) as independent predictors of GISTs. The areas wider the ROC curve of the predictive model using age, sex, and four EUS factors (homogeneity, location, anechoic spaces, and dimpling or ulcer) were 0.916 (sensitivity, 0.908; specificity, 0.793) and 0.904 (sensitivity, 0.908; specificity, 0.782) in the development and internal validation sets, respectively. Conclusions: The predictive model and nomogram using age, sex and homogeneity, tumor location, presence of anechoic spaces, and presence of dimpling or ulcer on EUS may facilitate differentiation between GISTs and leiomyomas.