Development and validation of a SEER-based auxiliary nomogram for clinical features associated with pulmonary metastasis status in pediatric osteosarcoma.

Background: Osteosarcoma is the most common primary malignant bone tumor in children and adolescents. Pulmonary metastasis is a severe metastatic manifestation of pediatric osteosarcoma and is strongly associated with poor prognosis. Identifying clinical features associated with pulmonary metastasis may help improve risk stratification and individualized clinical management. This study aimed to identify clinical features associated with pulmonary metastasis status at initial diagnosis in pediatric osteosarcoma and to develop and internally validate an auxiliary nomogram using data from the Surveillance, Epidemiology, and End Results (SEER) database for clinical risk stratification. Methods: Clinicopathological and treatment-related data of pediatric osteosarcoma patients diagnosed from 2004 to 2018 were extracted from the SEER database. Pulmonary metastasis status recorded at initial diagnosis was used as the outcome. Patients were randomly divided into training and validation cohorts. Variables associated with pulmonary metastasis were identified using univariate and multivariate logistic regression analyses, and a SEER-based auxiliary risk-stratification nomogram was constructed. Surgery and radiotherapy were interpreted as treatment-pattern variables rather than causal or pre-diagnostic predictors. Model performance was evaluated using calibration curves, the concordance index (C-index), receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Results: There were 1,362 pediatric patients randomly divided into the training cohort (n=965) and validation cohort (n=397). In the training cohort, multivariate logistic regression analysis identified four variables independently associated with pulmonary metastasis status, including T stage, N stage, surgery, and radiotherapy. A SEER-based auxiliary nomogram was constructed to identify clinical features associated with pulmonary metastasis status and to support risk stratification in pediatric osteosarcoma. The C-index values were 0.699 and 0.736 in the training and validation cohorts, respectively. The area under the ROC curve (AUC) values of the training and validation cohorts indicated acceptable discriminatory ability. Conclusions: This study developed a SEER-based auxiliary nomogram for identifying clinical features associated with pulmonary metastasis in pediatric osteosarcoma. Surgery and radiotherapy should be interpreted as treatment-pattern variables rather than causal or pre-diagnostic predictors. Further prospective studies incorporating imaging, pathological, molecular, and treatment-timing data are needed to validate and refine this model.