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A nomogram for determining the disease-specific survival in Ewing sarcoma: a population study
Jun Zhang1,2,3, Zhenyu Pan1,2,4, Jin Yang1,2
1Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
BMC Cancer
|July 7, 2019
Summary
A new nomogram accurately predicts disease-specific survival in Ewing sarcoma (ES) patients using age, race, disease extent, tumor size, and surgery. This tool aids in determining prognosis and treatment outcomes for ES.
Area of Science:
- Oncology
- Biostatistics
- Cancer Research
Background:
- Ewing sarcoma (ES) poses significant challenges in predicting patient survival.
- Accurate prognostic tools are crucial for effective treatment planning and patient management.
Purpose of the Study:
- To develop and validate a nomogram for predicting disease-specific survival in Ewing sarcoma patients.
- To identify independent prognostic factors influencing survival outcomes in ES.
Main Methods:
- Utilized the Surveillance, Epidemiology, and End Results (SEER) database (1990-2015).
- Employed multivariate Cox regression analysis on a training set to identify prognostic factors.
- Constructed and validated a nomogram predicting 3-, 5-, and 10-year survival rates using concordance indexes, calibration plots, IDI, NRI, and DCA.
Main Results:
- A nomogram was established incorporating age, race, disease extent, tumor size, and surgery.
- The nomogram demonstrated superior predictive accuracy (C-indexes of 0.684 and 0.704 in training and validation cohorts) compared to models without surgical therapy.
- The nomogram showed good discrimination and calibration, with improved NRI and IDI, indicating clinical utility via DCA.
Conclusions:
- A reliable nomogram was developed for predicting prognosis and treatment outcomes in US-based Ewing sarcoma patients.
- The nomogram requires external data validation for broader applicability, particularly outside the US.
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