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Updated: Jan 26, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Nomogram to predict thymoma prognosis: A population-based study of 1312 cases
Mengnan Zhao1, Jiacheng Yin1, Xiaodong Yang1
1Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Background:
A thymoma is a common cancer within the anterior mediastinum; however, the prognostic characteristics have not been established. The aim of this study was to identify the prognostic factors and develop a nomogram for the prognostic prediction of patients with thymoma based on data from the Surveillance, Epidemiology, and End Results (SEER) database.
Methods:
Patients with thymomas diagnosed between 1983 and 2014 were selected. Overall survival (OS) was estimated using the Kaplan-Meier method with the log-rank test. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the independent prognostic factors, from which a nomogram for thymomas was created. External validation of the nomogram was performed using data from our center.
Results:
A total of 1312 patients with thymomas were enrolled. Age, tumor size, Masaoka-Koga stage, chemotherapy administered, and surgery type were independent prognostic factors for OS. A nomogram for OS was formulated based on the independent prognostic factors and validated using an internal bootstrap resampling approach, which showed that the nomogram exhibited a sufficient level of discrimination according to the C-index in training (0.713, 95% confidence interval 0.685-0.741) and (0.746, 95% confidence interval 0.625-0.867) validation cohorts.
Conclusion:
Several prognostic factors for thymomas were identified. The nomogram developed in this study accurately predicted the 5-year and 10-year OS rates of patients with thymomas based on individual characteristics. Risk stratification using the survival nomogram could optimize individual therapy and follow-up.
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