Development and Validation of a Prognostic Nomogram for Predicting Overall Survival for T1 High-Grade Patients After Radical Cystectomy: A Study Based on SEER

Abstract

Objective

To construct a prognostic model that estimates the probability of overall survival for T1 high-grade bladder cancer patients after radical cystectomy.

Patients and Methods

We enrolled 801 patients diagnosed with T1 high grade and received radical cystectomy from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2015). All patients were randomly divided into the development group (n = 561) and validation group (n = 240) with the ratio of 7:3. Cox proportional hazards regression analyses were used to filter variables and the Kaplan–Meier method to evaluate survival outcomes. The results of sensitivity analysis determined the variables in the final model. The performance of the model was internally validated by calibration curves, the receiver operating characteristic (ROC) curves, and the concordance index (C-index).

Results

The mean survival months were 56.086 in the development group and 58.21 in the validation group. Six variables including age, marital status, tumour size, tumour sites, region nodes examined, and N stage were incorporated in the final nomogram. The accuracy of the nomogram for prediction of overall survival was estimated by C-index (0.732; 0.712–0.752) and AUC (0.771 for 3-year; 0.766 for 5-year) in the development group. In the validation group, the C-index of the nomogram was 0.752 (0.723–0.781), and AUC was 0.761 for 3-year as well as 0.793 for 5-year. These results all showed better performance than the AJCC stage. Calibration plots for 3- and 5-year overall survival presented good concordance in both the development and validation group.

Conclusion

We have established a prognostic nomogram that provides a more accurate and relevant individualized probability of overall survival for patients with T1HG bladder transitional cell carcinoma after radical cystectomy. It can contribute to improving patient counselling and treatment selection.