External Validation of Online Predictive Models for Prediction of Cancer-specific Mortality and All-cause Mortality in Patients with Urothelial Carcinoma of the Urinary Bladder |
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Authors: | Kyung Chul Moon MD PhD Myong Kim MD Cheol Kwak MD PhD Hyeon Hoe Kim MD PhD Ja Hyeon Ku MD PhD |
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Institution: | 1. Department of Pathology, Seoul National University College of Medicine, Seoul, Korea 2. Department of Urology, Seoul National University College of Medicine, Seoul, Korea
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Abstract: | Purpose The objective of the study was to validate the previously reported lookup Table and Bladder Cancer Research Consortium (BCRC) nomogram in predicting cancer-specific mortality (CSM) and all-cause mortality (ACM) after radical cystectomy using an external cohort from South Korea. Methods The study comprised 409 patients. Discrimination was quantified with the concordance index. The relationship between the model-derived and actual CSM and ACM was graphically explored within calibration plots. Clinical net benefit was evaluated by decision curve analysis. Results Of the 409 patients, 147 (35.9 %) had died from various causes. One hundred two deaths were attributable to bladder cancer. For CSM at 5 years, the bootstrap-corrected concordance indices of the American Joint Committee on Cancer (AJCC) staging system, lookup Table, and BCRC nomogram were 71.8 % (95 % confidence interval CI] 66.9–76.5), 73.0 % (95 % CI 67.9–78.0), and 76.2 % (95 % CI 71.6–80.9), respectively. For ACM at the same time point, the discrimination accuracies of these models were 70.7 % (95 % CI 66.7–74.6), 72.8 % (95 % CI 68.5–76.9), and 76.2 % (95 % CI 72.3–80.2), respectively. The calibration plots tended to exaggerate both survival outcomes in all models. When compared to the lookup Table as well as the AJCC staging system, the BCRC nomogram performed well across a wide range of threshold probabilities using decision curve analysis. Conclusions The BCRC nomogram was characterized by higher accuracy and larger potential clinical benefit compared to the lookup Table. However, there is a great need for additional models that consider outcomes of patients for whom the existing models do not apply. |
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