Background: The aim of this study was to establish a nomogram model to evaluate the prognosis of early-onset kidney cancer (EOKC) in terms of overall survival (OS) and cancer-specific survival (CSS).
Methods: Patients with EOKC diagnosed between 2004 and 2015 were collected from Surveillance, Epidemiology and End Results (SEER) and randomly assigned to the training and validation set at a ratio of 2 to 1. Important variables for constructing nomograms were screened by univariate and multivariate Cox analysis. The nomogram model was evaluated using concordance index (C-index), decision curve analysis (DCA) curves, and receiver operating characteristic (ROC) curves.
Results: A total of 12,526 EOKC patients were included in the study. OS nomogram was constructed based on gender, age, race, grade, AJCC stage, TNM stage, histology, chemotherapy and radiotherapy. CSS nomogram was constructed based on listed above except gender. In the external validation, the C-index for the OS nomogram was 0.855 (95% CI 0.834– 0.976), and the C-index for the CSS nomogram was 0.938 (0.925– 0.951). High-quality calibration curves were noted in both OS and CSS nomogram models. ROC and DCA curves showed that nomograms had better predictive performance than TNM stage and SEER stage.
Conclusion: The nomogram model provides an applicable tool for evaluating the OS and CSS prognosis of EOKC.
Keywords: early-onset kidney cancer, nomogram, OS, CSS, SEER