Prognostic Nomogram and a Risk Classification System for Predicting Overall Survival of Elderly Patients with...

Area of Science:

• Oncology
• Biostatistics
• Geriatric Medicine

Background:

• Fibrosarcoma presents a significant challenge in elderly patients, necessitating improved prognostic tools.
• Accurate prediction of overall survival is crucial for effective treatment planning in this demographic.

Purpose of the Study:

• To develop a nomogram model for predicting overall survival in elderly fibrosarcoma patients.
• To establish a risk classification system to stratify patients based on mortality risk.

Main Methods:

• Retrospective analysis of 357 elderly fibrosarcoma patients from the Surveillance, Epidemiology, and End Results (SEER) database (1975-2015).
• Utilized univariate and multivariate Cox regression to identify independent prognostic factors (age, surgery, grade, chemotherapy, tumor stage).
• Validated model performance using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis.

Main Results:

• The nomogram demonstrated good discrimination, with Area Under the Curve (AUC) values ranging from 0.769 to 0.837 across different time points (3, 5, 10 years) in training and validation sets.
• Calibration and decision curve analyses confirmed high predictive accuracy and clinical utility.
• A three-tiered risk classification system was successfully developed to differentiate mortality risk groups.

Conclusions:

• The developed nomogram model and risk classification system offer valuable tools for optimizing treatment strategies in elderly fibrosarcoma patients.
• These tools can aid clinicians in making informed decisions to potentially improve patient prognosis and outcomes.