Abstract
Purpose To establish a prognostic model that estimates cancer-specific survival (CSS) probability for muscle-invasive bladder cancer patients undergoing partial cystectomy. Patients and Methods. 866 patients from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2015) were enrolled in our study. These patients were randomly divided into the development cohort (n = 608) and validation cohort (n = 258) at a ratio of 7 : 3. A Cox regression was performed to select the predictors associated with CSS. The Kaplan–Meier method was used to analyze the survival outcome between different risk groups. The calibration curves, receiver operating characteristic (ROC) curves, and the concordance index (C-index) were utilized to evaluate the performance of the model. Results The nomogram incorporated age, histology, T stage, N stage, M stage, regional nodes examined, and tumour size. The C-index of the model was 0.733 (0.696–0.77) in the development cohort, while this value was 0.707 (0.705–0.709) in the validation cohort. The AUC of the nomogram was 0.802 for 1-year, 0.769 for 3-year, and 0.799 for 5-year, respectively, in the development cohort, and was 0.731 for 1-year, 0.748 for 3-year, and 0.752 for 5-year, respectively, in the validation cohort. The calibration curves for 1-year, 3-year, and 5-year CSS showed great concordance. Significant differences were observed between high, medium, and low risk groups (P < 0.001). Conclusions We have constructed a highly discriminative and precise nomogram and a corresponding risk classification system to predict the cancer-specific survival for muscle-invasive bladder cancer patients undergoing partial cystectomy. The model can assist in the decision on choice of treatment, patient counselling, and follow-up scheduling.
Highlights
Bladder cancer (BC) is the most common cancer of the urinary system, and it is the cause of death of 3% of patients with cancer in the UK [1, 2]
A retrospective study demonstrated that 86% and 48% of bladder cancer-specific mortality were observed between muscle-invasive bladder cancer (MIBC) patients receiving treatment and those without, respectively [4]
A nomogram was constructed for visualized prediction of 1, 3, and 5-year survival probabilities in the development cohort. e performance of the prediction model was evaluated by the concordance index (C-index), the receiver operating characteristic (ROC) curves with the calculated area under the curve (AUC), and calibration curves. e C-index and AUC were used to access the nomogram’s predictive accuracy and discrimination ability, while the calibration curves (100 bootstrap resamples) were utilized to compare the concordance of predicted and actual outcomes of 1, 3, and 5-year survival times
Summary
Bladder cancer (BC) is the most common cancer of the urinary system, and it is the cause of death of 3% of patients with cancer in the UK [1, 2]. A retrospective study demonstrated that 86% and 48% of bladder cancer-specific mortality were observed between MIBC patients receiving treatment and those without, respectively [4]. A study enrolling 58 patients undergoing PC observed acceptable outcomes with 74% overall survival and 67% disease-free survival in highly selected patients with MIBC [9]. All these results seemed to confirm that PC was a worth trying bladder preservation method for appropriately selected MIBC patients. We were committed to constructing a prognostic nomogram to predict CSS in MIBC patients undergoing PC and suggest treatment for these patients. We evaluated the performance and internally verified the applicability of the nomogram to make the predictive model more convincing
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