LAUSR

To build a nomogram model for predicting the survival risk of teens and adults with osteosarcoma based on the TARGET database, patients with osteosarcoma were collected via the TARGET database, and the survival curves of the patients were plotted using the Kaplan-Meier method in SPSS 24.0. Least absolute shrinkage and selection operator (LASSO) univariate regression analysis was performed to identify risk factors that influence osteosarcoma survival. A model (nomogram) for predicting the survival risk of adolescent and adult patients with osteosarcoma was built or plotted using the rms26 package as implemented in R (ver. 3.5.3). The predictive accuracy and discriminating power of the nomogram were determined by the C-index and calibration curves. A total of 94 patients with osteosarcoma were included. Classification of cases based on the tumor site revealed 59 cases involving the femur (62.8%), 5 involving the fibula (5.3%), 6 humerus (6.4%), 2 radius (2.1%), 19 tibia (20.2%), and 3 ulna (3.2%). Classification of cases based on surgical method showed 81 cases involving limb sparing (86.2%), 9 cases of amputation (9.6%), and 4 without surgery (4.2%). Among the 94 cases, bone metastasis occurred in 3 cases (3.2%) and lung metastasis in 14 cases (14.9%). Among all survivors, the median rate of survival is 8.6 years (95% CI: 8.0210.92); the three-year and five-year survival rates are 64.6% and 52.6%, respectively. The LASSO regression analysis showed that metastasis site, definitive surgery, and histologic response were potential risk predictors. The C-index of the nomogram plotted was 0.729, and the C-index of the validated sample was 0.742. The nomogram used in this study allows physicians to objectively and accurately predict the prognosis and survival of osteosarcoma patients. In order to determine whether the method is applicable to other groups of patients, additional studies need to be conducted.