ArticleSurgical endoscopy2024
Development and validation of a preoperative risk nomogram prediction model for gastric gastrointestinal stromal tumors.
Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 3 citations in OpenAlex.
- Development and validation of an endoscopic ultrasound-based nomogram for differentiating small gastric stromal tumours from non-gastric stroma tumours.Surgical endoscopy · 2026Article
- Intratumoral and Peritumoral Radiomics based on Contrast-enhanced CT Images: Biomarkers to Predict the Risk-Grade of Gastrointestinal Stromal TumorsCurrent medical imaging · 2026Article
- Prediction of Ki-67 expression and malignant potential in gastrointestinal stromal tumors: novel models based on CE-CT and serological indicators.BMC cancer · 2024Article
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4 authors at 3 institutions in 1 country.
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Abstract
BACKGROUND AND STUDY
aimsGastrointestinal stromal tumors (GIST) carry a potential risk of malignancy, and the treatment of GIST varies for different risk levels. However, there is no systematic preoperative assessment protocol to predict the malignant potential of GIST. The aim of this study was to develop a reliable and clinically applicable preoperative nomogram prediction model to predict the malignant potential of gastric GIST. PATIENTS AND
methodsPatients with a pathological diagnosis of gastric GIST from January 2015 to December 2021 were screened retrospectively. Univariate and multivariate logistic analyses were used to identify independent risk factors for gastric GIST with high malignancy potential. Based on these independent risk factors, a nomogram model predicting the malignant potential of gastric GIST was developed and the model was validated in the validation group.
resultsA total of 494 gastric GIST patients were included in this study and allocated to a development group (n = 345) and a validation group (n = 149). In the development group, multivariate logistic regression analysis revealed that tumor size, tumor ulceration, CT growth pattern and monocyte-to- lymphocyte ratio (MLR) were independent risk factors for gastric GIST with high malignancy potential. The AUC of the model were 0.932 (95% CI 0.890-0.974) and 0.922 (95% CI 0.868-0.977) in the development and validation groups, respectively. The best cutoff value for the development group was 0.184, and the sensitivity and specificity at this value were 0.895 and 0.875, respectively. The calibration curves indicated good agreement between predicted and actual observed outcomes, while the DCA indicated that the nomogram model had clinical application.
conclusionsTumor size, tumor ulceration, CT growth pattern and MLR are independent risk factors for high malignancy potential gastric GIST, and a nomogram model developed based on these factors has a high ability to predict the malignant potential of gastric GIST.
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