Zhiqiang Yang1,2, Yunjin Bai1, Maoying Liu3, Xu Hu2, Ping Han1. 1. Department of Urology, West China Hospital, Sichuan University, Chengdu, People's Republic of China. 2. West China School of Medicine/West China Hospital, Sichuan University, Chengdu, People's Republic of China. 3. Anyue Hengkang Hospital, Anyue County, People's Republic of China.
Abstract
PURPOSE: To establish a prognostic model to estimate the cancer-specific survival (CSS) for urothelial carcinoma of bladder (UCB) patients after radical cystectomy (RC). METHODS: A total of 8650 candidates (2004-2011) obtained from the Surveillance, Epidemiology, and End Results (SEER) database were randomly split into development cohort (n = 4323) and validation cohort (n = 4327). We performed Cox regression analysis to identify prognostic factors and Kaplan-Meier analysis to assess survival outcome. A nomogram predicting CSS was constructed. Its performance was validated by calibration curves, the receiver operating characteristic (ROC) curves, concordance index (C-index), decision curve analysis (DCA), the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI). RESULTS: The nomogram incorporated marital status, T stage, N stage, tumor size, and chemotherapy. In validation cohort, C-index of the nomogram was 0.707. AUC of the nomogram and AJCC stage were 0.767 versus 0.674. Calibration plots for 3- and 5-year CSS displayed good concordance. DCA curves of the nomogram exhibited larger benefits than the AJCC stage. The NRI and IDI indicated the nomogram outperformed AJCC stage. CONCLUSIONS: We have established a prognostic nomogram with improved discriminative ability and clinical benefits for UCB patients after RC. The nomogram alongside an easy access web tool may assist clinicians in optimizing the postoperative management.
PURPOSE: To establish a prognostic model to estimate the cancer-specific survival (CSS) for urothelial carcinoma of bladder (UCB) patients after radical cystectomy (RC). METHODS: A total of 8650 candidates (2004-2011) obtained from the Surveillance, Epidemiology, and End Results (SEER) database were randomly split into development cohort (n = 4323) and validation cohort (n = 4327). We performed Cox regression analysis to identify prognostic factors and Kaplan-Meier analysis to assess survival outcome. A nomogram predicting CSS was constructed. Its performance was validated by calibration curves, the receiver operating characteristic (ROC) curves, concordance index (C-index), decision curve analysis (DCA), the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI). RESULTS: The nomogram incorporated marital status, T stage, N stage, tumor size, and chemotherapy. In validation cohort, C-index of the nomogram was 0.707. AUC of the nomogram and AJCC stage were 0.767 versus 0.674. Calibration plots for 3- and 5-year CSS displayed good concordance. DCA curves of the nomogram exhibited larger benefits than the AJCC stage. The NRI and IDI indicated the nomogram outperformed AJCC stage. CONCLUSIONS: We have established a prognostic nomogram with improved discriminative ability and clinical benefits for UCB patients after RC. The nomogram alongside an easy access web tool may assist clinicians in optimizing the postoperative management.
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