Abstract
BACKGROUND: Our objective was to identify risk factors affecting overall survival (OS) and cancer-specific survival (CSS) and build nomograms to predict survival based on a large population-based cohort. METHODS: Two hundred and thirty patients diagnosed with CHCC between 2004 and 2015 were retrospectively extracted from the Surveillance, Epidemiology, and End Results (SEER) database as a training cohort. In addition, Ninety-nine patients diagnosed with CHCC between 2000 and 2017 were retrospectively extracted from Sun Yat-Sen University Cancer Center (SYSUCC) as an external validation. Nomograms for predicting probability of OS and CSS were established. Performance of the nomograms was measured by concordance index (C-index) and the area under receiver operating characteristic (ROC) curve (AUC). RESULTS: In training cohort, the 1-, 2 and 3-year OS were 67.7, 46.8 and 37.9%, and the 1-, 2 and 3-year CSS were 73.1, 52.0 and 43.0%, respectively. The established nomograms were well calibrated in both training and validation cohort, with concordance indexes (C-index) of 0.652 and 0.659, respectively for OS prediction; 0.706 and 0.763, respectively for CSS prediction. Nomograms also displayed better discriminatory compared with 8th edition tumor-node-metastasis (TNM) stage system for predicting OS and CSS. CONCLUSION: We constructed nomograms to predict OS and CSS based on a relatively large cohort. The established nomograms were well validated and could serve to improve predictions of survival risks and guide management of patients with CHCC after surgery.