Postoperative perforation risk after endoscopic removal of gastric gastrointestinal stromal tumors: Development and validation of a predictive nomogram
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND Gastrointestinal stromal tumors are the most common mesenchymal tumors of the gastrointestinal tract, and gastric gastrointestinal stromal tumors (gGISTs) account for the majority of these tumors. Currently, endoscopic removal (ER) is increasingly adopted as a minimally invasive treatment. However, postoperative perforation remains a critical complication, necessitating robust prediction tools. AIM To identify the risk factors and develop a validated nomogram for predicting perforation after ER of gGISTs. METHODS This retrospective study analyzed the patients undergoing ER at Fuyang People’s Hospital from 2019 to 2024. Clinical data, including tumor size, location, and procedural details, were collected and analyzed. The risk factors were identified via univariate and multivariate logistic regression, and a nomogram was developed. Both internal and external validations were performed, and the model performance was assessed by receiver operating characteristic curves and calibration plots. RESULTS Among 301 patients, the perforation rate was 6.3%. Multivariate analysis identified tumor size (odds ratio = 4.699, 95% confidence interval: 2.382-9.267, P = 0.001) and cardia/fundus location (odds ratio = 3.492, 95% confidence interval: 1.121-10.875, P = 0.031) as independent predictors. A nomogram was constructed and achieved good predictive performance in both the training (area under the curve = 0.881) and validation sets (area under the curve = 0.878). CONCLUSION This study identified that tumor size and location were independent risk factors, and provides a clinically actionable nomogram for evaluating and predicting postoperative perforation risk in gGISTs treated with ER, facilitating preprocedural planning and risk monitoring.
Authors: Dong-Mei Zhang, Pan-Pan Li, Min-Hui Zhang, Zong-Xian Zhao, Ya-Bo Zhou
Language: English
Subfield: Gastroenterology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4415212088