Minerva urology and nephrology · 2026
External validation and comparison of nomograms for prediction of long-term disease recurrence and survival for bladder cancer patients who undergo radical cystectomy.
СтатьяВалидационное исследованиеСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Benijts Rodrigue, Akand Murat, Tipirdamaz Mustafa, Mennes Jonas, Baekelandt Loïc, Everaerts Wouter, Albersen Maarten, VAN Poppel Hein, Joniau Steven, VAN DER Aa Frank
Аннотация
BACKGROUND: This study aimed to compare existing nomograms and identify which models best predict long-term survival outcomes, namely disease-free survival (DFS) or recurrence-free survival (RFS), and cancer-specific survival (CSS), in patients undergoing radical cystectomy (RC) for bladder cancer (BC).
METHODS: Six nomograms (three for DFS, three for CSS) were selected from 20 studies and evaluated using data from 730 RC patients treated at University Hospitals Leuven. Discriminatory performance was assessed using area under the curve (AUC) of receiver operating characteristics (ROC) curve, along with sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. Calibration was analyzed using the Hosmer-Lemeshow (HL) test and calibration plots, while clinical utility was assessed through decision curve analysis (DCA). Statistical significance was set at P<0.05.
RESULTS: All nomograms effectively predicted 5-year DFS and CSS. The AUC values for DFS nomograms were 0.74 (95% Confidence interval [CI]: 0.70-0.78) for Simone et al., 0.74 (95% CI: 0.70-0.77) for Cicione et al., and 0.73 (95% CI: 0.69-0.77) for Karakiewicz et al. For CSS nomograms, the AUC values were 0.78 (95% CI: 0.74-0.82) for Simone et al., 0.78 (95% CI: 0.74-0.82) for Cicione et al., and 0.77 (95% CI: 0.74-0.81) for Shariat et al. Among DFS nomograms, Simone et al. showed the highest sensitivity (0.64, 95% CI: 0.58-0.69), while Karakiewicz et al. had the highest specificity (0.81, 95% CI: 0.78-0.88). Among CSS nomograms, sensitivity was highest for Shariat et al. (0.84, 95% CI: 0.81-0.88), while specificity was highest for Simone et al. (0.72, 95% CI: 0.67-0.78). Accuracy, PPV, NPV, and Brier scores were comparable across all DFS and CSS nomograms. The Cicione et al. nomogram demonstrated the best calibration for DFS, while the Simone et al. nomogram had the least systematic bias in absolute calibration. For CSS, all three nomograms exhibited similar discrimination and predictive accuracy, with the Cicione et al. and Shariat et al. models showing slightly better calibration than the Simone et al. nomogram. DCA confirmed the clinical usefulness of all DFS and CSS nomograms.
CONCLUSIONS: All evaluated nomograms showed comparable accuracy in predicting 5-year DFS or CSS, supporting their use in clinical practice. Nonetheless, their limitations should be considered when applying them to individual patient-specific decision-making.
METHODS: Six nomograms (three for DFS, three for CSS) were selected from 20 studies and evaluated using data from 730 RC patients treated at University Hospitals Leuven. Discriminatory performance was assessed using area under the curve (AUC) of receiver operating characteristics (ROC) curve, along with sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. Calibration was analyzed using the Hosmer-Lemeshow (HL) test and calibration plots, while clinical utility was assessed through decision curve analysis (DCA). Statistical significance was set at P<0.05.
RESULTS: All nomograms effectively predicted 5-year DFS and CSS. The AUC values for DFS nomograms were 0.74 (95% Confidence interval [CI]: 0.70-0.78) for Simone et al., 0.74 (95% CI: 0.70-0.77) for Cicione et al., and 0.73 (95% CI: 0.69-0.77) for Karakiewicz et al. For CSS nomograms, the AUC values were 0.78 (95% CI: 0.74-0.82) for Simone et al., 0.78 (95% CI: 0.74-0.82) for Cicione et al., and 0.77 (95% CI: 0.74-0.81) for Shariat et al. Among DFS nomograms, Simone et al. showed the highest sensitivity (0.64, 95% CI: 0.58-0.69), while Karakiewicz et al. had the highest specificity (0.81, 95% CI: 0.78-0.88). Among CSS nomograms, sensitivity was highest for Shariat et al. (0.84, 95% CI: 0.81-0.88), while specificity was highest for Simone et al. (0.72, 95% CI: 0.67-0.78). Accuracy, PPV, NPV, and Brier scores were comparable across all DFS and CSS nomograms. The Cicione et al. nomogram demonstrated the best calibration for DFS, while the Simone et al. nomogram had the least systematic bias in absolute calibration. For CSS, all three nomograms exhibited similar discrimination and predictive accuracy, with the Cicione et al. and Shariat et al. models showing slightly better calibration than the Simone et al. nomogram. DCA confirmed the clinical usefulness of all DFS and CSS nomograms.
CONCLUSIONS: All evaluated nomograms showed comparable accuracy in predicting 5-year DFS or CSS, supporting their use in clinical practice. Nonetheless, their limitations should be considered when applying them to individual patient-specific decision-making.