Refining prognosis in advanced renal cell carcinoma: international real-world validation of the Meet-URO score in first-line immunotherapy combinations

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Abstract
Background: Effective risk stratification is essential for guiding treatment decisions in patients with metastatic renal cell carcinoma (mRCC). The Meet-URO score is a novel prognostic model that integrates the International Metastatic RCC Database Consortium (IMDC) criteria with neutrophil-to-lymphocyte ratio (NLR) and the presence of bone metastases. Developed in the immunotherapy era, it has demonstrated superior prognostic accuracy compared to the IMDC score across various clinical settings and treatment strategies. Its validation in the context of first-line immune-based combinations has been awaited. Methods: External validation of Meet-URO was performed using a large retrospective real-world cohort of mRCC patients treated with first-line immune-based combinations. Secondary analyses included a comparison with the IMDC score for predicting overall survival (OS) and progression-free survival (PFS). Additionally, restricted mean survival time (RMST) was assessed. Results: A total of 1,418 patients were included in the analysis: 54% received ICI–ICI regimen (nivolumab plus ipilimumab), while 46% received the ICI–TKI combination. At baseline, 52.5% of patients had an NLR ≥ 3.2, and 32% had bone metastases. After a median follow-up of 26.8 months, the median OS and median PFS were 34.7 and 11.3 months, respectively. Meet-URO demonstrated effective prognostic stratification, identifying patient groups with markedly different outcomes (median OS 11.5-51.4 months; 3-year OS 26-66%; RMST 20.0-42.8 months). Compared to IMDC, Meet-URO showed a significantly better OS (c-index 0.675 vs 0.643; Δc = 0.032, P < .001) and PFS (c-index 0.60 vs 0.58; P < .001) prediction performance. Conclusions: Meet-URO demonstrated robust prognostic accuracy. Its integration into routine clinical practice and use as a stratification factor in clinical trials may support more personalized treatment strategies and enhance clinical trial design.

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