A nomogram to predict prognosis in Ewing sarcoma of bone

Area of Science:

• Oncology
• Biostatistics
• Cancer Research

Background:

• Ewing sarcoma (ES) is a rare bone and soft tissue cancer.
• Accurate survival prediction is crucial for optimizing treatment strategies in ES patients.

Purpose of the Study:

• To develop and validate a nomogram for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with Ewing sarcoma.
• To provide a reliable tool for clinicians to assess prognosis and guide treatment decisions for ES patients.

Main Methods:

• Utilized data from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2013).
• Split data into training (n=479) and validation (n=137) cohorts.
• Employed Kaplan-Meier method, Cox proportional hazard model, and Cox regression for analysis and nomogram development.
• Validated the nomogram using internal bootstrap resampling and the validation set.

Main Results:

• A nomogram incorporating age, race, stage, tumor site, tumor size, and chemotherapy was identified.
• The nomogram demonstrated good discriminatory power with C-indices of 0.754 for OS and 0.759 for CSS.
• Calibration plots confirmed strong agreement between predicted and observed survival rates.

Conclusions:

• The developed nomogram is a reliable and effective tool for predicting Ewing sarcoma patient survival.
• This tool can assist medical oncologists and surgeons in selecting appropriate medical examinations and optimizing treatment plans.
• The nomogram facilitates personalized medicine approaches for Ewing sarcoma management.