A model established using marital status and other factors from the Surveillance, Epidemiology, and End Results database for early stage gastric cancer.

Abstract

Currently, the postoperative prognosis of early stage gastric cancer (GC) is difficult to accurately predict. In particular, social factors are not frequently used in the prognostic assessment of early stage GC. Therefore, this study aimed to combine the clinical indicators and social factors to establish a predictive model for early stage GC based on a new scoring system. A total of 3647 patients with early stage GC from the Surveillance, Epidemiology, and End Results database were included in this study. A Kaplan-Meier survival analysis was used to compare differences in prognosis between different marital status, as an innovative prognostic indicator. Univariate and multivariate analyses were used to screen available prediction factors and then build a nomogram using the Cox proportional hazard regression model. The univariate analysis and multivariate analysis revealed that age at diagnosis, sex, histology, stage_T, surgery, tumor size, and marital status were independent prognostic factors of overall survival. Both the C-index and calibration curves confirmed that the nomogram had a great predictive effect on patient prognosis in training and testing sets. This nomogram based on clinical indicators and marital status can effectively help patients with early stage GC in the future.