Development and validation of a nomogram model based on vascular entry sign for predicting lymphovascular invasion in gastric cancer

Background To evaluate the predictive value of a nomogram based on the vascular entry sign for lymphovascular invasion in gastric cancer. Methods A total of 135 patients with histopathologically confirmed gastric cancer from August 2021 to November 2022 were enrolled. All patients underwent contrast-enhanced CT scans. Utilizing a random number method, patients were randomly assigned to either a training dataset (n = 96) or a validation dataset (n = 39) in a 7:3 ratio. CT images and clinical characteristics of the patients were collected. Both univariate and multivariate analyses were conducted to identify independent factors influencing lymphovascular invasion in gastric cancer. A nomogram model was developed, and its diagnostic performance and clinical utility were assessed using receiver operating characterist (ROC) curves, calibration curves, and decision curve analysis (DCA). Results The multivariate analysis revealed that the vascular entry sign, clinical T stage, and clinical N stage independently influenced the occurrence of factors for lymphovascular invasion in gastric cancer (P < 0.05). A predictive nomogram model was developed for determining LVI status in gastric cancer. The AUC of the nomogram model in the training dataset and validation dataset were 0.878 (95% CI: 0.808-0.948) and 0.866 (95% CI: 0.723-1.000), respectively. The calibration curve and decision curve showed that the model had good reliability and good clinical validity. Conclusion The model established based on the factors of vascular entry sign, clinical T stage, and clinical N stage can effectively predict lymphovascular invasion in gastric cancer.