Frequency and Prognosis of Pulmonary Metastases in Newly Diagnosed Gastric Cancer

Purpose: The purpose of this study was to analyze the frequency and prognosis of pulmonary metastases in newly diagnosed gastric cancer using population-based data from SEER. Methods: Patients with gastric cancer and pulmonary metastases (GCPM) at the time of diagnosis in advanced gastric cancer were identified using the Surveillance, Epidemiology and End Result (SEER) database of the National Cancer Institute from 2010 to 2014. Multivariable logistic regression was performed to identify predictors of the presence of GCPM at diagnosis. Receiver operator characteristics analysis was performed to significant predictors on multivariable logistic regression and was then assessed with Delong's test. Multivariable Cox regression was developed to identify factors associated with all-cause mortality and gastric cancer-specific mortality. Survival curves were obtained according to the Kaplan-Meier method and compared using the log-rank test. Results: We identified 1,104 patients with gastric cancer and pulmonary metastases at the time of diagnosis, representing 6.02% of the entire cohort and 15.19% of the subset with metastatic disease to any distant site. Among the entire cohort, multivariable logistic regression identified six factors (younger, upper 1/3 of stomach, intestinal-type, T4 staging, N1 staging, and presence of more extrapulmonary metastases to liver, bone, and brain) as positive predictors of the presence of pulmonary metastases at diagnosis. The value of AUC for the multivariable logistic regression model was 0.775. Median survival among the entire cohort with GCPM was 3.0 months (interquartile range: 1.0–9.0 mo). Multivariable Cox model in SEER cohort confirmed five factors (diagnosis at previous period, black race, adverse pathology grade, absence of chemotherapy, and presence of more extrapulmonary metastases to liver, bone, and brain) as negative predictors for overall survival. Conclusions: The findings of this study provided population-based estimates of the frequency and prognosis for GCPM at time of diagnosis. The multivariable logistic regression model had an acceptable performance to predict the presence of PM. These findings may provide preventive guidelines for the screening and treatment of PM in GC patients. Patients with high risk factors should be paid more attention before and after diagnosis.