Prognostic factors and survival prediction in hepatocellular carcinoma: development and validation of a novel nomogram based on the SEER database.

Background: Current staging systems for hepatocellular carcinoma (HCC) still have limitations in clinical practice. Our study aimed to explore the prognostic factors and develop a new nomogram to predict the cancer-specific survival (CSS) for patients with HCC. Methods: A total of 6,166 HCC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly grouped into the training cohort (70%) and validation cohort (30%). Multivariate Cox analysis was used to identify prognostics factors for CSS of patients, then we incorporated these variables and presented a new nomogram to predict 2- and 5-year CSS. The performance of the nomogram was assessed with respect to its calibration, concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), and decision curve analysis (DCA). Results: Multivariate Cox analysis revealed that American Joint Committee on Cancer (AJCC) stage, race, grade, surgery, chemotherapy, radiation, tumor size, bone metastasis (BM), and alpha-fetoprotein (AFP) were independently associated with CSS. The prediction nomogram which contained these predictors showed good performance, with a C-index of 0.802 [95% confidence interval (CI), 0.792-0.812] in the training cohort and 0.801 (95% CI, 0.787-0.815) in the validation cohort. The calibration curves demonstrated good agreement between the actual observation and the nomogram prediction. Furthermore, the nomogram showed improved discriminative capacity (AUC, 0.873 and 0.875 for 2- and 5-year CSS in validation set) compared to the 7 Conclusions: This study presents a novel nomogram that incorporates the important prognostic factors of HCC, which can be conveniently used to accurately predict the 2- and 5-year CSS of patients with HCC, thus assisting individualized clinical decision making.