Nomogram to predict overall survival for patients with non-metastatic cervical esophageal cancer: a SEER-based population study.

Abstract

BackgroundCervical esophageal cancer (CEC) is an uncommon malignancy with poor prognosis, and there is no specific model that can be used to accurately predict the survival of patients with CEC.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with non-metastatic CEC from 2004 to 2015. Overall survival (OS) and disease-specific survival (DSS) rates were calculated using the Kaplan-Meier method. Predictive factors were analyzed by Cox’s proportional hazards regression, and a nomogram was created to predict survival probability using R software.ResultsWe identified 601 patients with CEC, 94.3% of whom had squamous cell carcinoma (SCC). The median follow-up time was 71 months. The median OS and DSS for the overall population were 15 and 18 months, respectively. There was a statistically significant decrease in surgical rates over time, from 16.7% in 2004 to 8% in 2015 (P=0.035). Comprehensive strategies consisting of two or three treatment modalities were correlated with significantly better OS and DSS (P<0.001 for both). We randomly assigned half of the patients to the training cohort (n=300) and the other half to the validation cohort (n=301). Multivariate Cox regression analysis was performed using the training cohort. Age, sex, tumor size, stages in the 7th edition of the American Joint Committee on Cancer (AJCC) staging system, and treatment with surgery, radiotherapy, or chemotherapy were identified as independent risk factors for OS. These factors were incorporated into the development of a nomogram for predicting 1-, 3-, and 5-year OS rates. The C-index of the nomogram was 0.743, which was statistically higher than that of the AJCC staging system. The internal validation, using bootstrap resampling and external validation, demonstrated the accuracy of the nomogram.ConclusionsWe developed and validated the first nomogram for CEC. This nomogram could be used to predict the OS of CEC patients with a relatively high accuracy.