Population-based outcome of muscle-invasive bladder cancer following radical cystectomy: who can benefit from adjuvant chemotherapy?

BACKGROUND

The benefit of adjuvant chemotherapy remains controversial in muscle-invasive bladder cancer (MIBC) after radical cystectomy. The present study's primary objective was to construct a predictive tool for the reasonable application of adjuvant chemotherapy.

METHODS

All of the patients analyzed in the present study were recruited from the Surveillance Epidemiology and End Results program between 2004 and 2015. Propensity score matching (PSM) was used to reduce inherent selection bias. Cox proportional hazards models were applied to identify the independent prognostic factors of overall survival (OS) and cancer-specific survival (CSS), which were further used to construct prognostic nomogram and risk stratification systems to predict survival outcomes. The prognostic nomogram's performance was assessed by concordance index (C-index), receiver-operating characteristic (ROC) and calibration curves. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit of the prognostic nomogram.

RESULTS

A total of 6,384 patients with or without adjuvant chemotherapy were included after PSM. Several independent predictors for OS and CSS were identified and further applied to establish a nomogram for 3-, 5- and 10-year, respectively. The nomogram showed favorable discriminative ability for the prediction of OS and CSS, with a C-index of 0.709 [95% confidence interval (CI): 0.699-0.719] for OS and 0.728 (95% CI: 0.718-0.738) for CSS. ROC and calibration curves showed satisfactory consistency. The DCA revealed high clinical positive net benefits of the prognostic nomogram. The different risk stratification systems showed that adjuvant chemotherapy resulted in better OS (P<0.001) and CSS (P<0.001) than without adjuvant chemotherapy for high-risk patients; while the OS (P=0.350) and CSS (P=0.260) for low-risk patients were comparable.

CONCLUSIONS

We have constructed a predictive model and different risk stratifications for selecting a population that could benefit from postoperative adjuvant chemotherapy. Adjuvant chemotherapy was found to be beneficial for high-risk patients, while low-risk patients should be carefully monitored.