Abstract
BACKGROUND: Clinical behavior of non-muscle-invasive bladder cancer (NMIBC) is largely unpredictable, and even patients treated according to European Association of Urology recommendations have a heterogeneous prognosis. High-grade T1 (HGT1) bladder cancer is the highest-risk subtype of NMIBC, with an almost 40% rate of recurrence and 20% of progression at 5 years. Nomograms predicting risk of recurrence, progression, and cancer-specific survival (CSS) are not available specifically within HGT1 bladder cancer, and the identification of robust prognostic biomarkers to better guide therapeutic strategies in this subgroup of patients is of paramount importance. Strategies to identify putative biomarkers in liquid biopsies from blood and urine collected from patients with bladder cancer have been intensively studied in the last few years. SUBJECTS, MATERIALS, AND METHODS: We here report the final analysis of a single-center prospective study aimed to investigate the impact of circulating tumor cells (CTCs) on CSS and overall survival (OS) in 102 patients with HGT1 bladder cancer, in a median follow-up of 63 months. RESULTS: We here demonstrate that the presence of even a single CTC is predictive of shorter CSS and OS, as compared with the standard predictive variables. Points of attention in this multivariable analysis are the long-term follow-up and the adequate number of outcome events. CONCLUSION: The accurate risk stratification provided by CTCs might be essential for determining the best surveillance strategy for patients after diagnosis. A closer follow-up, an early radical surgery, or even a systemic treatment might be recommended in patients with super-high-risk non-muscle-invasive bladder cancer. IMPLICATIONS FOR PRACTICE: Circulating tumor cells identify patients with super-high-risk non-muscle-invasive bladder cancer who require closer monitoring for local recurrence and/or progression of disease. This super-high-risk subgroup of patients might also require more aggressive treatment interventions, which should be evaluated in large prospective cohorts.