Abstract

Liver metastasesare associated with a poor prognosisin gastroesophageal junction (GEJ) cancer patients. The high rate of liver involvement is attributed to the unique anatomical location of the GEJ, which is close to the liver. Patients with liver metastasis typically have advanced, unresectable disease and limited treatment options. Therefore, early detection and predictionare crucial to guide appropriate treatment planning and improve the outcomes for patients with GEJ cancer at risk of liver metastases. Using data from the Surveillance, Epidemiology, and End Results (SEER) database, the present study aimed to elucidate the incidenceand risk factorsof liver metastases in GEJ cancer patients diagnosed between 2010 and 2019. This research employed univariable and multivariable logistic regression models to identify risk factors for the development of liver metastases. A predictive nomogram for liver metastases was developed and assessed. Patients' overall survival (OS) with liver metastases was analyzed using the Kaplan-Meier method. The study included 1,322 eligible patients with GEJ cancer, 181 (13.6%) of whom were diagnosed with liver metastases. The median overall survival (mOS)for patients with liver metastasis was approximately eight months, compared to a shorter mOS for patients without liver metastasis (P < 0.001). Factors significantly associated with the occurrence of liver metastasis includedN3 stage (OR: 1.84; 95% CI: (1.13-2.96); P < 0.001),surgery (OR: 0.09; 95% CI: (0.06-0.14); P < 0.001), lung metastasis (OR: 2.88; 95% CI: (1.78-4.63); P < 0.001), chemotherapy (OR: 0.54; 95% CI: (0.32-0.87); P < 0.001), and radiation therapy (OR: 0.33; 95% CI: (0.25-0.45); P < 0.001). The nomogram demonstrated good performance in predicting liver metastases in GEJ cancer patients (c-index: 0.820). The study identified lymph node status, surgical, lung metastasis, chemotherapy, and radiation as important predictors of outcomes for patients with GEJ cancer. The developed nomogram might be a valuable tool for predicting the risk of liver metastases in GEJ cancer patients, potentially enhancing clinical decision-making processes.By predictingthe risk of liver metastasis occurrence, clinicians mightintervene in patients with GEJ cancersas early as possible.

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