Background: While the role of adjuvant therapy for MIBC is being evaluated in randomized trials of patients (pts) following RC with or without neoadjuvant chemotherapy (NC), pts receiving adjuvant chemotherapy (AC) have been excluded. Understanding the prognosis of a broad spectrum of pts undergoing RC with or without perioperative chemotherapy may aid patient selection, stratification and interpretation of nonrandomized data. We conducted a retrospective analysis of the NCDB to construct a comprehensive prognostic nomogram in this broad population. Methods: Data from NCDB was obtained for all patients diagnosed with clinical (c)-T2-T4aN0M0 urothelial carcinoma of bladder who underwent RC in the US from 2004-2013. Those who underwent RC > 6 months (mo) after initiating NC, received AC > 4 mo after RC were excluded to allow only those receiving optimal therapy. Pts with unknown race and number of lymph nodes (LNs) examined were also excluded. Multivariate analyses were conducted to determine the impact on survival of: clinical stage, pathologic (p)-stage, treatment group (RC alone, NC, AC), age, year of diagnosis, Charlson Comorbidity Index (CCI), race, number of examined LNs examined and sex. Results: A total of 10,256 pts were evaluable for analysis: 6864 in the RC group, 1380 in the AC group and 2012 in the NC group. On multivariate analysis, the following variables were significantly (p < 0.001) associated with survival: treatment group, age ( < 65 vs. ≥ 65 years), CCI, p-stage and number of examined LNs. Calibration was performed and the c-index was 0.79 (95% CI: 0.76-0.81). Limitations of a retrospective analysis apply. Conclusions: A comprehensive prognostic nomogram to predict the survival of pts with MIBC undergoing RC with or without NC or AC was proposed. The estimation of residual risk of mortality after RC alone or with AC or NC aids optimal stratification of pts in more inclusive randomized trials of subsequent adjuvant therapy. The nomogram also highlights the impact of comorbidities and age, and helps interpret non-randomized data evaluating perioperative regimens.