# Assessment of Meet-URO and CANLPH Prognostic Models in Metastatic RCC: Insights from a Single-Institution Cohort Predominantly Treated with TKIs

**Authors:** Ömer Faruk Kuzu, Nuri Karadurmuş, Nebi Batuhan Kanat, Dilruba İlayda Özel Bozdağ, Berkan Karadurmuş, Esmanur Kaplan Tüzün, Hüseyin Atacan, Nurlan Mammadzada, Emre Hafızoğlu, Gizem Yıldırım, Musa Barış Aykan, Selahattin Bedir, İsmail Ertürk

PMC · DOI: 10.3390/diagnostics16030428 · Diagnostics · 2026-02-01

## TL;DR

This study evaluates two new prognostic models for metastatic kidney cancer patients mainly treated with TKIs, showing they can help predict survival outcomes.

## Contribution

The study evaluates the performance of Meet-URO and CANLPH models in a real-world mRCC cohort treated with TKI monotherapy.

## Key findings

- Meet-URO and CANLPH both showed strong prognostic stratification for overall and progression-free survival.
- CAR was the strongest individual predictor of survival compared to NLR and PHR.
- Both models may enhance clinical decision-making in resource-limited settings.

## Abstract

Background/Objectives: Accurate prognostic assessment remains crucial in metastatic renal cell carcinoma (mRCC), especially as treatment options have expanded beyond vascular endothelial growth factor (VEGF)-targeted therapies to include immune checkpoint inhibitors (ICIs) and ICI–TKI combinations. The widely used IMDC classification shows important limitations in the modern therapeutic era, highlighting the need for complementary prognostic tools. In this context, the Meet-URO and CANLPH scores—incorporating clinical, inflammatory, and nutritional markers—have emerged as promising alternatives. To evaluate and compare the prognostic performance of the Meet-URO and CANLPH scoring systems in a real-world mRCC cohort predominantly treated with first-line tyrosine kinase inhibitor (TKI) monotherapy due to limited access to ICI-based combinations. Methods: This retrospective single-center study included 112 patients with mRCC. The Meet-URO score was calculated for all patients, while the CANLPH score was assessed in 56 patients with complete laboratory data. CAR, NLR, and PHR were computed using baseline pre-treatment measurements. Overall survival (OS) and progression-free survival (PFS), the latter defined exclusively for first-line therapy, were estimated using the Kaplan–Meier method. Correlations between inflammatory markers and survival outcomes were analyzed using Spearman’s rho. Results: Meet-URO demonstrated clear prognostic stratification across all five categories, with the most favorable outcomes in score group 2 and progressively poorer OS and PFS in higher-risk groups. CANLPH also showed meaningful survival discrimination, with the highest inflammatory group (score 3) exhibiting markedly reduced OS and PFS. CAR was the strongest individual predictor of survival, while NLR and PHR showed weaker associations. Conclusions: Both Meet-URO and CANLPH provide strong, complementary prognostic information in mRCC, even in a cohort largely treated with TKI monotherapy. Their integration into routine risk assessment may enhance clinical decision-making, particularly in resource-limited settings.

## Full-text entities

- **Genes:** VEGFA (vascular endothelial growth factor A) [NCBI Gene 7422] {aka L-VEGF, MVCD1, VEGF, VPF}
- **Diseases:** inflammatory (MESH:D007249), RCC (MESH:D002292), mRCC (MESH:C538445)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

26 references — full list in the complete paper: https://tomesphere.com/paper/PMC12896847/full.md

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Source: https://tomesphere.com/paper/PMC12896847