A diagnostic nomogram for synchronous lung metastasis at initial diagnosis in osteosarcoma: A retrospective SEER database study

Objective This study aimed to establish a diagnostic nomogram for identifying synchronous lung metastasis at initial diagnosis in osteosarcoma patients, and to descriptively analyze overall survival patterns in patient subgroups. Methods A total of 1149 eligible osteosarcoma cases diagnosed between 2010 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Candidate predictors were screened by univariate logistic regression ( p < 0.10) and entered into backward stepwise multivariate logistic regression (retention p < 0.05) to construct a diagnostic nomogram. Discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), calibration by calibration plot, and clinical utility by decision curve analysis (DCA) with bootstrapping validation. Secondary survival analysis used Kaplan-Meier curves and log-rank tests to describe overall survival patterns. Results Synchronous lung metastases were found in 213 patients (18.5%) at diagnosis. The nomogram incorporated age, race, sex, lymph node stage, grade, tumour size, tumour site, and histology. It achieved an AUC of 0.754 (95% confidence interval 0.719 - 0.799) and a bootstrap-calibrated C-index of 0.745. Calibration was satisfactory, and DCA demonstrated superior net benefit compared with traditional staging approaches, including AJCC stage, grade alone, size alone, and N stage alone. In exploratory survival analysis, patients with synchronous metastasis had significantly poorer overall survival, and primary tumour surgery was associated with prolonged median survival. Conclusion The diagnostic nomogram, incorporating tumour grade, site, size, and lymph node stage, provides a reliable tool for estimating the probability of synchronous lung metastasis at initial diagnosis, which may assist clinicians in guiding initial staging intensity and treatment planning. However, owing to the cross-sectional design of the SEER database, this model is not designed for predicting future metastatic progression.