Nomogram application to predict overall and cancer-specific survival in osteosarcoma

Area of Science:

• Oncology
• Biostatistics
• Cancer Research

Background:

• Osteosarcoma survival prediction remains challenging.
• Accurate prognostic tools are essential for guiding treatment decisions.
• The Surveillance, Epidemiology, and End Results (SEER) database offers a valuable resource for population-based cancer research.

Purpose of the Study:

• To develop and validate a prognostic nomogram for predicting overall survival (OS) and cancer-specific survival (CSS) in osteosarcoma patients.
• To identify independent prognostic factors influencing survival in osteosarcoma.
• To provide an individualized survival prediction tool for osteosarcoma patients.

Main Methods:

• Analysis of 2,195 osteosarcoma patients from the SEER database (1983-2014).
• Identification of prognostic factors using univariate and multivariate Cox regression analyses.
• Construction and validation of a nomogram using training and external cohorts, assessed by concordance indices (C-indices).

Main Results:

• Key prognostic factors identified include age at diagnosis, tumor site, histology, tumor size, tumor stage, surgery use, and tumor grade.
• The nomogram demonstrated good predictive accuracy with C-indices of 0.763 for OS and 0.764 for CSS in the training cohort.
• External validation showed comparable accuracy with C-indices of 0.739 for OS and 0.740 for CSS, with excellent calibration.

Conclusions:

• A robust prognostic nomogram was developed for predicting OS and CSS in osteosarcoma patients.
• The nomogram provides accurate and individualized survival predictions.
• This tool can aid clinicians in patient management and treatment planning for osteosarcoma.