Risk Factor Analysis of Pulmonary Metastasis in Middle-Aged and Elderly Patients with Chondrosarcoma and Establishment and Validation of a Nomogram

Background and Objectives Pulmonary metastasis in middle-aged and elderly patients with chondrosarcoma often leads to poor prognosis. This study aimed to identify the independent risk factors for pulmonary metastasis in this population and to develop and validate a clinical prediction model (nomogram) for accurately estimating the probability of pulmonary metastasis. Methods A total of 659 eligible chondrosarcoma patients (aged 40 years or older) were identified retrospectively from the Surveillance, Epidemiology, and End Results (SEER) database, covering the period from 2004 to 2015. Univariate logistic regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression were used to identify the risk factors for pulmonary metastasis. The selected risk factors, together with their respective weights, were visually represented in a nomogram. The predictive performance and clinical utility of the nomogram were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results Tumor grade, T stage, N stage, and surgical status were identified as independent risk factors for pulmonary metastasis. The area under the ROC curve (AUC) was 0.914 for the training cohort and 0.849 for the validation cohort. The calibration curve demonstrated good agreement between the model’s predicted probabilities and observed outcomes, while the DCA and CIC confirmed the nomogram’s significant clinical value. Conclusion Tumor grade, T stage, N stage, and surgical status are important independent risk factors influencing pulmonary metastasis in middle-aged and elderly patients with chondrosarcoma. The nomogram constructed in this study provides clinicians with a rapid, user-friendly tool for predicting the probability of pulmonary metastasis in this patient population, and its accuracy and clinical applicability have been validated.