15 May 2020 : Database Analysis
A Population-Based Analysis of Distant Metastasis in Stage IV Gastric Cancer
Yiran Zhang1BEF, Yile Lin2CD, Jincai Duan2CD, Ke Xu2BF, Min Mao3AG, Xin Wang4AG*DOI: 10.12659/MSM.923867
Med Sci Monit 2020; 26:e923867
Abstract
BACKGROUND: Distant metastasis (DM) is a crucial problem in management of patients with gastric cancer. Identification of the risk factors for development of DM and the prognostic factors for patients with DM is essential in development of individualized treatment of patients at the advanced stage with specific metastasis.
MATERIAL AND METHODS: Records of patients with gastric cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Survival duration of patients with specific DM was estimated, and the prognostic factors were investigated using the Cox proportional hazard regression model. The logistic regression model was used to reveal the inherent risk factors for development of DM.
RESULTS: Eventually, 32.6% (11,918 out of 36,588) of gastric cancer patients were diagnosed with DM between 2010 and 2015, among whom 5,361, 1,778, 1,495, and 231 patients were diagnosed with liver, lung, bone, and brain metastasis, respectively. The median overall survival for patients with DM was 5.0 (95% CI: 4.8–5.2) months, with a 5-year survival rate of 3.9%. Primary tumor site, histology types, tumor grade, T stage, N stage, surgery, chemotherapy, and the number of metastases were associated with worse survival. Younger age and higher tumor grade were positively associated with the development of DM.
CONCLUSIONS: Initial DM was found in 32.6% of patients with gastric cancer. Homogenous and heterogenous predictive factors were identified for patients with a specific metastatic site, which can be used in targeted screening and individualized treatment.
Keywords: Neoplasm Metastasis, Prognosis, Risk Factors, SEER Program, Stomach Neoplasms, Brain Neoplasms, Kaplan-Meier Estimate, Liver Neoplasms, Lung Neoplasms, Male, Neoplasm Staging, Proportional Hazards Models, Survival Rate
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