Abstract
Although the overall global incidence of gastric cancer has been declining, the number of new cases in people under the age of 50 is increasing, which is related to metastasis, late pathological stages, and poor prognosis. There is a scarcity of large-scale studies to evaluate and predict distant metastasis in patients with early-onset gastric cancer. From January 2010 to December 2019, data on early-onset GC patients undergoing surgery were gathered from the Surveillance, Epidemiology, and End Results (SEER) database. We investigated the independent risk factors for distant metastasis in patients with early-onset gastric cancer. Based on these risk factors, we developed a nomogram to predict distant metastasis. The model underwent internal validation on the test set and external validation on 205 patients from the First Affiliated Hospital of Sun Yat-sen University and the seventh Affiliated Hospital of Sun Yat-sen University. The novel nomogram model was then evaluated using the receiver operating characteristic (ROC) curve, calibration, the area under the curve (AUC), and decision curve analysis (DCA). The training set nomogram score was used to classify the different risk clusters of distant metastasis. Our study enrolled 2217 patients after establishing the inclusion and exclusion criteria, with 1873 having no distant metastasis and 344 having distant metastasis. The tumor size, total lymph nodes, whether or not receiving radiotherapy and chemotherapy, T stage, and N stage were significant predictors of advanced distant metastasis (p < 0.05). The AUC of the ROC analysis demonstrated our model's high accuracy. Simultaneously, the prediction model shows high stability and clinical practicability in the calibration curve and DCA analysis. We developed an innovative nomogram containing clinical and pathological characteristics to predict distant metastasis in patients younger than 50 years old with gastric cancer. The tool can alert clinicians about distant metastasis and help them develop more effective clinical treatment plans.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have