Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study

Area of Science:

• Oncology
• Biostatistics
• Medical Informatics

Background:

• Osteosarcoma (OS) is a primary bone malignancy with poor prognosis in metastatic cases.
• Limited tools exist for assessing OS metastasis, necessitating improved predictive models.
• Developing a reliable nomogram can aid in early detection and management of metastatic osteosarcoma.

Purpose of the Study:

• To establish a predictive nomogram for evaluating metastasis in osteosarcoma patients.
• To identify key risk factors associated with osteosarcoma metastasis.
• To validate the performance of the developed nomogram.

Main Methods:

• Retrospective analysis of osteosarcoma cases from the Surveillance, Epidemiology, and End Results (SEER) database.
• Univariate and multivariate logistic regression analyses to identify risk factors.
• Construction and validation of a nomogram using concordance index (C-index) and calibration curves.

Main Results:

• Analysis included 1015 osteosarcoma cases.
• Identified age, primary site, grade, T stage, and surgery as significant risk factors for metastasis.
• The nomogram demonstrated good predictive performance with C-indices of 0.754 (training) and 0.716 (validation).

Conclusions:

• A reliable nomogram for predicting osteosarcoma metastasis has been successfully developed.
• The nomogram utilizes basic patient information for accessible clinical application.
• This tool can assist clinicians in predicting metastasis and guiding postoperative treatment strategies.