Abstract
INTRODUCTION: The study aims to develop and internally validate a novel risk stratification model specifically designed to predict 1-year intravesical recurrence (IVR) following radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC), integrating readily available clinicopathologic parameters. MATERIAL AND METHODS: We retrospectively analyzed 87 patients who underwent RNU for UTUC between 2012 and 2024. Patients were stratified according to IVR status at 12 months postoperatively. Univariate and LASSO logistic regression analyses were conducted to identify independent predictors. A simplified risk score was derived from regression coefficients. Model performance was assessed using area under the ROC curve (AUC), calibration plots, and bootstrap validation. Clinical utility was evaluated with decision curve analysis (DCA). RESULTS: One-year IVR occurred in 34 patients (39.1%). Seven independent predictors were identified: tumor multifocality, ureteral tumor location, history of non-muscle-invasive bladder cancer, chronic kidney disease, preoperative ureteroscopy, intravesical bladder cuff excision, and positive surgical margins. The final model showed excellent discriminative performance (AUC = 0.854) and good calibration. Patients were stratified into low (0-2 points), intermediate (3-5), and high-risk (6-9) groups, with IVR rates of 11.1%, 53.7%, and 80.0%, respectively (p for trend <0.001). DCA demonstrated a favorable net benefit across a wide range of thresholds. CONCLUSIONS: We present a novel, internally validated scoring system that integrates routine clinicopathologic parameters to predict early IVR following RNU for UTUC. This tool may support urologists in implementing risk-adapted cystoscopic surveillance protocols and identifying candidates for early intravesical therapy. External validation is warranted prior to clinical implementation.