Outcomes in patients with metastatic gastric cancer: a surveillance, epidemiology, and end results program (SEER) database analysis

Abstract

Owing to tumor heterogeneity and individual physiological variations, there remains a necessity to enhance the current prognosis prediction system for metastatic gastric cancer (MGC). This study aimed to establish a prognostic model for patients diagnosed with MGC. Pertinent information pertaining to MGC patients was extracted and assessed from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016. The Kaplan-Meier method and Cox regression analysis were employed to identify potential prognostic factors. Furthermore, a nomogram model containing possible prognostic factors associated with overall survival (OS) was constructed using R software. A total of 2975 patients from the SEER database were included in this investigation. N-stage, grade, surgery, radiotherapy, chemotherapy, brain metastasis, bone metastasis, liver metastasis, and lung metastasis were identified as independent prognostic factors for OS. These variables were subsequently incorporated into the nomogram model. Calibration curves demonstrated a good correlation between nomogram predictions and actual observations. The nomogram model exhibits the potential to estimate the individualized survival of MGC patients.