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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and external validation of nomograms predicting disease-free and cancer-specific survival after radical
Giuseppe Simone1,2, Marco Bianchi3, Diana Giannarelli4
1Department of Urology, "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy. puldet@gmail.com.
Purpose:
To develop two nomograms predicting disease-free survival (DFS) and cancer-specific survival (CSS) and to externally validate them in multiple series.
Methods:
Prospectively collected data from a single-centre series of 818 consecutive patients who underwent RC and PLND were used to build the nomogram. External validation was performed in 3,173 patients from 7 centres worldwide. Time to recurrence and to cancer-specific death were addressed with univariable and multivariable analyses. Nomograms were built to predict 2-, 5- and 8-year DFS and CSS probabilities. Predictive accuracy was quantified using the concordance index.
Results:
Age, pathologic T stage, lymph-node density and extent of PLND were independent predictors of DFS and CSS (p < 0.05). Discrimination accuracies for DFS and CSS at 2, 5 and 8 years were 0.81, 0.8, 0.79 and 0.82, 0.81, 0.8, respectively, with a slight overestimation at calibration plots beyond 24 months. In the external series, predictive accuracies for DFS and CSS at 2, 5 and 8 years were 0.83, 0.82, 0.82 and 0.85, 0.85, 0.83 for European centres; 0.73, 0.72, 0.71 and 0.80, 0.74, 0.68 for African series; 0.76, 0.74, 0.71 and 0.79, 0.76, 0.73 for American series.
Conclusions:
These nomograms developed from a contemporary series are simple clinical tools and provide optimal oncologic outcome prediction in all external cohorts.
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