Survival nomogram for osteosarcoma patients: SEER data retrospective analysis with external validation.

Area of Science:

• Oncology
• Biostatistics
• Clinical Medicine

Background:

• Osteosarcoma prognosis prediction is crucial for effective patient management.
• Existing prognostic models may lack accuracy or comprehensive validation.
• Developing a reliable predictive tool is essential for individualized treatment planning.

Purpose of the Study:

• To develop and validate a nomogram for predicting overall survival in osteosarcoma patients.
• To identify independent clinicopathological prognostic factors for osteosarcoma.
• To provide a tool for clinicians to assess prognosis and guide treatment decisions.

Main Methods:

• Retrospective analysis of 1362 osteosarcoma patients from SEER and Clinical Medicine Center databases.
• Univariate and multivariate Cox regression analyses to identify prognostic factors.
• Nomogram construction and validation using calibration plots, C-index, AUC, and DCA.

Main Results:

• Key predictors identified: age, sex, tumor size, primary site, grade, M stage, and surgery.
• The nomogram demonstrated good prediction ability with high C-index (0.80 training, 0.79 validation) and AUC values.
• Calibration plots and DCA confirmed the model's accuracy and clinical applicability.

Conclusions:

• The developed nomogram is a reliable tool for predicting osteosarcoma patient survival.
• It aids in identifying high-risk patients and supports individualized treatment recommendations.
• This predictive model can enhance clinical decision-making in osteosarcoma management.