The novel dynamic nomogram and risk classification system constructed for predicting post-surgical overall survival and mortality risk in primary chondrosarcoma: a population study based on SEER database

Background Surgery is the predominant method to improve the prognosis of primary chondrosarcoma patients. We aimed to construct the first reliable nomogram to predict the post-surgical overall survival (OS) of primary chondrosarcoma patients. Methods We downloaded all primary chondrosarcoma patients treated with surgery between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database, and randomized them into training set (60%) and validation set (40%). Cox proportional regression analysis was applied to the training set to identify independent prognostic variables, and then constructed a nomogram for predicting 3-, 5-, and 8-year OS. The Harrell's concordance index (C-index), receiver operating characteristic curve (ROC), the area under curve (AUC), calibration curve and decision curve analysis (DCA) was used to assess the predictive efficacy and clinical applicability of the nomogram. The nomogram was also compared with The American Joint Committee on Cancer (AJCC) staging system. Results A total of 1005 post-surgical primary chondrosarcoma patients were included in this study. We finally identified five independent prognostic variables to construct the nomogram, being age, grade, tumor size, disease stage and histological type. The C-index results showed that the prediction performance of the nomogram was significantly better than the AJCC staging system. In the training set, (C-index: 0.805, 95% CI 0.879–0.730 vs 0.686, 95% CI 0.606–0.766); in the validation set, (C-index: 0.811, 95% CI 0.895–0.727 vs 0.697, 95% CI 0.647–0.799). Additionally, the AUC values generated by the ROC were all greater than 0.8, which also indicated the excellent predictive performance of the nomogram. The calibration curves showed that the predicted survival rate was highly similar to the actual. Time-dependent ROC and DCA showed that the nomogram has better predictive performance and net clinical benefits than the AJCC staging system. Finally, a risk stratification system based on nomogram was constructed. Conclusion We successfully constructed and validated the first nomogram that could reliably predict 3-, 5-, and 8-year post-surgical OS in primary chondrosarcoma patients. Furthermore, the web-based dynamic nomogram could be more conveniently applied to clinic, providing assistance to surgeons and patients.