Giuseppe Simone1,2, Marco Bianchi3, Diana Giannarelli4, Siamak Daneshmand5, Rocco Papalia4, Mariaconsiglia Ferriero4, Salvatore Guaglianone4, Steno Sentinelli6, Renzo Colombo3, Francesco Montorsi3, Devis Collura7, Giovanni Muto7, Giacomo Novara8, Rodolfo Hurle9, Michael Rink10, Margit Fisch10, Hassan Abol-Enein11, Gus Miranda5, Mihir Desai5, Inderbir Gill5, Michele Gallucci4. 1. Department of Urology, "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy. puldet@gmail.com. 2. Department of Urology, "San Giovanni Bosco" Hospital, Turin, Italy. puldet@gmail.com. 3. Department of Urology, Vita-Salute University, Milan, Italy. 4. Department of Urology, "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy. 5. Institute of Urology, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, USA. 6. Department of Pathology, "Regina Elena" National Cancer Institute, Rome, Italy. 7. Department of Urology, "San Giovanni Bosco" Hospital, Turin, Italy. 8. Department of Surgical, Oncological and Gastroenterologic Sciences, Urology Clinic, University of Padua, Padua, Italy. 9. Department of Urology, Humanitas-Gavazzeni, Bergamo, Italy. 10. University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 11. Department of Urology, Mansoura University, Mansoura, Egypt.
Abstract
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.
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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