BACKGROUND: This study aimed to assess the prognostic value of a various of diagnostic immunohistochemical (IHC) markers and develop an IHC-based classifier to predict the disease-free survival (DFS) of patients with bladder cancer (BC) undergoing radical cystectomy (RC).METHODS: IHC was performed on tumor specimens from 366 patients with transitional cell BC. The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to develop a multi-marker classifier for predicting DFS of patients with BC. The Kaplan–Meier estimate was performed to assess DFS, and univariate and multivariate Cox regression models were used to identify independent risk factors to predict DFS of patients with BC.RESULTS: Based on the LASSO Cox regression model, nine prognostic markers were identified in the training cohort. Patients were stratified into low- and high-risk groups using the IHC-based classifier. In the training cohort, the 10-year DFS was significantly better in low-risk patients (70.7%) compared with high-risk patients (17.9%) (p<0.001); in the validation cohort, the 10-year DFS was 85.7% for the low-risk group and 20.4% for the high-risk group (p<0.001). Multivariable Cox regression analyses showed that the high-risk group based on the nine-IHC-based classifier was associated with poorer DFS adjusted by clinicopathological characteristics. Finally, a nomogram comprising the nine-IHC classifier and clinicopathological factors was developed for clinical application.CONCLUSION: The nine-IHC-based classifier is a reliable prognostic tool, which can eventually guide clinical decision making regarding treatment strategy and follow-up scheduling of BC.