Abstract: BACKGROUND: Spinal osteosarcoma is a rare and highly aggressive malignant tumor. Most existing studies are based on small sample sizes and have inconsistent results, making it difficult to provide reliable clinical guidance. Especially in China, due to the low incidence of spinal osteosarcoma and limited related research, clinicians lack effective prognostic tools during treatment.
OBJECTIVE: To construct and validate a nomogram model for predicting the survival of spinal osteosarcoma patients based on the Surveillance, Epidemiology, and End Results (SEER) database, providing scientific evidence for clinical decision-making, particularly for optimizing treatment plans for Chinese patients.   
METHODS: This study conducted a retrospective analysis of patient data diagnosed with spinal osteosarcoma from the SEER database between 2000 and 2021. First, independent prognostic factors associated with specific mortality from spinal osteosarcoma were identified through univariate and multivariate Cox proportional hazards models. Subsequently, these independent prognostic factors were used to construct a nomogram model for predicting survival rates of spinal osteosarcoma patients using the “rms” package in RStudio. The model’s discrimination was assessed using the C-index. Predictive ability was validated through receiver operating characteristic curves and area under the curve values. Calibration was evaluated by calibration plots, and clinical value was measured using decision curve analysis. Additionally, Kaplan-Meier survival analysis was performed to assess the rationality of the nomogram groupings.   
RESULTS AND CONCLUSION: (1) The final model included six variables: chemotherapy, tumor size, histological type, grade, race, and surgical intervention. (2) The C-indices of the model in the training and validation sets were 0.685 and 0.673, respectively, indicating good discrimination. (3) Calibration curves showed high consistency between predicted survival probabilities and actual survival probabilities. (4) Decision curve analysis indicated that the model provided significant net benefits across a wide range of mortality risks. (5) Kaplan-Meier survival analysis revealed significant differences in prognosis between high-risk and low-risk groups. (6) The constructed nomogram model accurately predicts the 1-year, 2-year, and 3-year survival rates of spinal osteosarcoma patients, demonstrating high clinical applicability. This model not only provides an effective survival prediction tool for American patients but also offers important insights for optimizing treatment plans for spinal osteosarcoma patients in China. Future research should further validate the model’s applicability in different populations and explore the impact of novel treatment methods on the prognosis of spinal osteosarcoma, aiming to improve the survival rates and quality of life of patients in China.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: spinal osteosarcoma, nomogram model, survival, Cox regression, prognostic factor, Kaplan-Meier survival analysis, engineered tissue construction