Prediction of all-cause death and specific causes of death in patients with gastric cancer with liver metastasis: a Surveillance, Epidemiology, and End Results–based study

Abstract

BackgroundGastric cancer (GC), considered the fifth most prevalent malignancy, is the fourth leading cause of cancer death worldwide. This cancer is heterogeneous and invasive and often metastasizes to the liver. The survival of patients with GC, especially cancer-specific survival (CSS), is a matter of concern to their families and medical workers in clinical practice. However, efficient tools for early risk prediction are lacking. Thus, this study aimed to develop a nomogram for forecasting the overall survival (OS) and CSS of patients with GC with liver metastasis (GCLM) based on the Surveillance, Epidemiology, and End Results (SEER) database. MethodsInformation on individuals with GCLM was acquired from the SEER database from January 2000 to December 2015. Patients’ data were randomized into the train cohort and the test cohort. The independent factors for CSS and OS were determined by univariate and multivariate competing risk analyses and Cox proportional hazards analysis, and the nomograms for predicting CSS and OS were constructed. The receiver operating characteristic curve and calibration curve were used to measure the accuracy and calibration of nomograms. ResultsOur study included 4372 patients with GCLM, with 3060 patients in the train set and 1312 in the test set. The mean follow-up period was 12.31 months. The independent factors influencing the OS of patients with GCLM were age, bone metastasis, chemotherapy, grade, lung metastasis, stage, primary site, radiotherapy, surgical primary site, T stage, and tumor size. The concordance Index (C-index) of the constructed nomogram for OS were 0.718 (SE, 0.004) in the train set and 0.0.680 (SE, 0.006) in the test set. The independent factors affecting the CSS of patients with GCLM were age, chemotherapy, grade, lung metastasis, stage, radiotherapy, regional lymph node positive, surgical primary site, and total number of tumors. The C-index for the constructed nomogram for CSS were 0.696 (SE, 0.005) in the train set and 0.696 (SE, 0.008) in the test set. ConclusionThe constructed nomograms showed satisfactory performance in predicting the OS and CSS of patients with GCLM, which can help clinicians formulate follow-up and rehabilitation strategies conducive to survival. At the same time, it can provide more family and social support for high-risk groups.