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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and External Validation of a Nomogram for Predicting Overall Survival in Stomach Cancer: A
1Department of Oncology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China.
Objective:
The study was to develop and externally validate a prognostic nomogram to effectively predict the overall survival of patients with stomach cancer.
Methods:
Demographic and clinical variables of patients with stomach cancer in the Surveillance, Epidemiology, and End Results (SEER) database from 2007-2016 were retrospectively collected. Patients were then divided into the Training Group (n = 4,456) for model development and the Testing Group (n = 4,541) for external validation. Univariate and multivariate Cox regressions were used to explore prognostic factors. The concordance index (C-index) and the Kolmogorov-Smirnov (KS) value were used to measure the discrimination, and the calibration curve was used to assess the calibration of the nomogram.
Results:
Prognostic factors including age, race, marital status, TNM stage, surgery, chemotherapy, grade, and the number of regional nodes positive were used to construct a nomogram. The C-index was 0.790 and the KS value was 0.45 for the Training Group, and the C-index was 0.789 for the Testing Group, all suggesting the good performance of the nomogram.
Conclusion:
We have developed an effective nomogram with ten easily acquired prognostic factors. The nomogram could accurately predict the overall survival of patients with stomach cancer and performed well on external validation, which would help improve the individualized survival prediction and decision-making, thereby improving the outcome and survival of stomach cancer.
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