Bladder Cancer: StagingPD41-05 FINAL PATHOLOGIC STAGE AFTER NEOADJUVANT CHEMOTHERAPY AND RADICAL CYSTECTOMY FOR BLADDER CANCER: DOES PT0 PREDICT BETTER SURVIVAL THAN PTA/PTIS/PT1?
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INTRODUCTION AND OBJECTIVES
Pathologic response after neoadjuvant chemotherapy (NAC) for muscle invasive bladder cancer is used widely as a surrogate endpoint for overall survival(OS). Controversy persists, however, whether the absence of residual cancer (pT0) or the presence of only non-muscle invasive residual cancer (pT1, pTis, pTa) is the optimal surrogate endpoint. We aimed to assess OS dependent on these pathologic responses in a large multicenter patient cohort.
METHODS
We retrospectively reviewed records of patients with urothelial cancer who received NAC and underwent cystectomy at 19 contributing institutions from 2000-2013. Patients with cT2-4aN0M0 and eventual pN0 disease were selected for this analysis. Estimated OS was compared between pT0 and pT1/pTa/pTis patients. A Multivariable Cox proportional hazards regression model for overall mortality was generated to evaluate hazard ratios (HRs) for variables of interest (age, gender, number of cycles and
RESULTS
Of 1645 patients undergoing NAC and RC during the study period, 242 were pT0N0 and 200 were pT1/pTis/pTaN0. The KM median estimate of overall survival for pT0 and pT1/pTa/pTis patients was 175.4 mo. (95%CI [153.2-197.6]) and 115.4 mo. (95%CI [83.3-147.4]), respectively (p=0.04). In multivariable cox regression analysis, pT1/pTa/pTis patients were at higher risk of death compared to pT0 patients (HR 2.5 95%CI (1.2-5.4)). Utilization of non-cisplatin based NAC had a higher HR for death compared
CONCLUSIONS
pT0N0 stage on the final cystectomy specimen is a strong predictor of survival in patients receiving NAC and RC. In comparison, HR for death increased by more than two-fold with residual pT1/pTa/pTisN0 disease in the RC specimen. These findings suggest that these outcomes are worthy of distinction when counselling patients and in the context of clinical trials, but both predict excellent long-term survival.
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