Abstract

Endoscopic resection is becoming an option in the management of gastric GI stromal tumors (GISTs). Although no consensus has been reached, patients with high malignancy potential GISTs are generally considered to be surgical candidates. However, no systematic preoperative evaluation strategy has yet been developed. The current study was performed to develop a preoperative multivariate model to predict the malignant potential of gastric GISTs. This study consisted of 2 stages. First, a multivariate prediction model for gastric GISTs smaller than 5 cm was developed using a multivariate logistic regression analysis in a retrospective cohort. Next, the prediction model was validated further in a validation cohort of gastric GISTs. In the developing stage, 275 patients were included. The multivariate analysis demonstrated that independent risk factors for high malignancy potential gastric GISTs smaller than 5 cm were tumor size≥2 cm (according to cutoff value), an irregular tumor shape, and mucosal ulceration (P< .05). Based on accordant regression coefficients, 3 risk factors were weighted with point values: 1 point for mucosal ulceration, 2 points for an irregular tumor shape, and 3 points for tumor size≥2 cm. In the validation stage, 186 patients were included. The area under the curve of the prediction model was .80 (95% confidence interval, .73-.85), which was significantly higher than that of tumor size alone (P= .034). The independent risk factors for high malignancy potential gastric GISTs smaller than 5 cm were tumor size larger than 2 cm, an irregular tumor shape, and mucosal ulceration. These factors could be used to predict malignancy potential of gastric GISTs in a simple combination.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.