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Updated: May 3, 2026

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
Published on: March 29, 2019
Comparative Analysis of Risk Stratifications for Non-Muscle-Invasive Bladder Cancer According to the Classifications
Moeto Shimoda1, Hiroki Ito2, Tetsuya Aoki1
1Department of Urology, Yokosuka Kyosai Hospital, Yokosuka, Japan.
Introduction:
Risk stratification systems for non-muscle-invasive bladder cancer (NMIBC) differ among the National Comprehensive Cancer Network (NCCN)/American Urological Association (AUA), European Association of Urology (EAU), and Japanese Urological Association (JUA) guidelines, and their comparative ability to predict clinical outcomes in real-world practice remains unclear.
Patients And Methods:
We retrospectively analyzed 591 patients who underwent transurethral resection of bladder tumor and classified them into risk categories according to the NCCN, EAU, and JUA guidelines, comparing recurrence and progression outcomes among classifications.
Results:
During median follow-up of 64.1 months, intravesical recurrence (32.1%), T stage progression (4.5%), grade progression (2.5%), undergoing radical nephroureterectomy (2.7%), and radical cystectomy (5.3%) were observed, respectively. Grade progression from low-grade to high-grade disease was significantly associated with increasing EAU risk (P = .026) but not with NCCN or JUA classifications. Among pTa tumors, progression to ≥ pT1 occurred more frequently in higher risk groups across all classifications (all, P < .05), whereas progression from pT1 to pT2 was not significantly stratified by any system. Early intravesical recurrence increased with higher risk in all classifications (all, P < .05), with the strongest discrimination observed for the NCCN system. In multivariable Cox proportional hazards analyses, the NCCN classification demonstrated the highest discriminative performance for predicting intravesical recurrence.
Conclusions:
The NCCN, EAU, and JUA risk classifications are all clinically relevant for NMIBC, but their predictive performance varies by endpoint, indicating the importance of selecting the classification according to the specific outcome of interest.
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