Development of nomogram and discussion of radiotherapy effect for osteosarcoma survival

Abstract

This study aimed to develop a predictive system for prognostic evaluation of osteosarcoma patients. We obtained osteosarcoma sample data from 1998 to 2016 using SEER*Stat software version 8.3.8, and established a multivariable Cox regression model using R-4.0.3 software. Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The diagnosis of the model was completed through influential cases, proportionality, and multicollinearity. The predictive ability of the model was tested using area under the curve (AUC), calibration curves, and Brier scores. Finally, the bootstrap method was used to internally verify the model. In total, data from 3566 patients with osteosarcoma were included in this study. The multivariate Cox regression model was used to determine the independent prognostic variables. A nomogram and Kaplan–Meier survival curve were established. The AUC and Brier scores indicated that the model had a good predictive calibration. In addition, we found that the radiotherapy appears to be a risk factor of patients with osteosarcoma and made a discussion. We developed a prognostic evaluation system for patients with osteosarcoma for 1-, 3-, and 5-year overall survival with good predictive ability using sample data extracted from the SEER database. This has important clinical significance for the early identification and treatment of high-risk groups of osteosarcoma patients.