Prediction model for recurrence probabilities after intravesical chemotherapy in patients with intermediate-risk non-muscle-invasive bladder cancer, including external validation.

ABSTRACT: To develop a model to predict recurrence for patients with intermediate-risk (IR) non-muscle-invasive bladder cancer (NMIBC) treated with intravesical chemotherapy which can be challenging because of the heterogeneous characteristics of these patients.Data from three Dutch trials were combined. Patients treated with intravesical chemotherapy with characteristics according to the IR definition of the EAU guideline 2013 were included. Uni- and multivariable Cox regression with selection methods were used to identify predictors of recurrence at 1, 2, and 5 years. An easy-readable table for recurrence probabilities was developed. An external validation was done using data from Spanish patients.A total of 724 patients were available for analyses, of which 305 were primary patients. Recurrences occurred in 413 patients (57%). History of recurrences, history of intravesical treatment, grade 2, multiple tumors, and adjuvant treatment with epirubicin were relevant predictors for recurrence-free survival with hazard ratios of 1.48, 1.38, 1.22, 1.56, and 1.27, respectively. A table for recurrence probabilities was developed using these five predictors. Based on the probability of recurrence, three risk groups were identified. Patients in each of the separate risk groups should be scheduled for less or more aggressive treatment. The model showed sufficient discrimination and good predictive accuracy. External validation showed good validity.In our model, we identified five relevant predictors for recurrence-free survival in IR-NMIBC patients treated with intravesical chemotherapy. These recurrence predictors allow the urologists to stratify patients in risk groups for recurrence that could help in deciding for an individualized treatment approach.

SUBMITTER: Lammers RJ 

PROVIDER: S-EPMC4729802 | biostudies-other | 2016 Feb

REPOSITORIES: biostudies-other