Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jan-Dec:24:15330338251329848.
doi: 10.1177/15330338251329848. Epub 2025 Mar 25.

External Validation of the GRade, Age, Nodes and Tumor (GRANT) Score for Patients with Surgically Treated Papillary Renal Cell Carcinoma

Michele Maffezzoli  1 , Alessio Signori  2 , Davide Campobasso  3 , Giulia Claire Giudice  1 , Nicola Simoni  4 , Massimo De Filippo  5 , Enrico Maria Silini  6 , Sebastiano Buti  1   7
Affiliations

External Validation of the GRade, Age, Nodes and Tumor (GRANT) Score for Patients with Surgically Treated Papillary Renal Cell Carcinoma

Michele Maffezzoli et al. Technol Cancer Res Treat. 2025 Jan-Dec.

Abstract

IntroductionStratifying the risk of recurrence for surgically treated papillary renal cell carcinoma (pRCC) could be challenging. Prognostic models are crucial for patient counselling and individualized surveillance. The GRANT score is one of the models suggested by guidelines to predict prognosis of surgically treated pRCC. This study aims to externally validate the GRANT score using a three-risk group stratification in a large cohort of pRCC patients.Materials and MethodsThe present analysis utilized retrospective data from pRCC patients who underwent radical or partial nephrectomy. The GRANT score parameters included tumor grade, age, pathological T-stage, and N-stage. Patients were stratified into three risk groups (0-1 vs 2 vs 3-4 risk factors). Cancer-specific survival (CSS) was assessed using the Kaplan-Meier method, and differences between groups were evaluated using the log-rank test. Harrell's c-index was used to measure model accuracy, and restricted mean survival time (RMST) was calculated for up to 120 months.ResultsA total of 1942 patients were included. The median follow-up was 64.6 months. At 60 months, CSS was 93.2% (95%CI 91.7%-94.6%) for group 1, 60.8% (95%CI 54.0%-78.6%) for group 2, and 26% (95%CI 15.7%-42.9%) for group 3, with significant differences between each group (p < 0.001). The median CSS was not reached for group 1 (95%CI NR-NR), 86.0 months in group 2 (95%CI 65-NR), and 22.8 months in group 3 (95%CI 16.4-48.0). The c-index for CSS was 0.732. The RMST at 120 months was 113.3 months for group 1, 75.9 months for group 2, and 56.6 months for group 3, with a statistically significant difference (p < 0.001).ConclusionThe GRANT score effectively stratified surgically treated pRCC patients into three risk groups, demonstrating good prognostic accuracy. This validation supports the GRANT score's utility as a reliable and easy-to-use prognostic tool.

Keywords: papillary; prognosis; prognostic factors; renal cancer; surgery; surgical treatment.

PubMed Disclaimer

Conflict of interest statement

Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Representative kaplan–meier curve illustrating cancer-specific survival for each GRANT group.
See this image and copyright information in PMC

References

    1. Ullah A, Yasinzai AQK, Daino N, et al. Papillary renal cell carcinoma: Demographics, survival analysis, racial disparities, and genomic landscape. J Kidney Cancer VHL. 2023;10(4):33-42. doi:10.15586/jkcvhl.v10i4.294. Published 2023 Dec 26. - DOI - PMC - PubMed
    1. Mendhiratta N, Muraki P, Sisk AJ, Shuch B. Papillary renal cell carcinoma: Review. Urol Oncol. 2021;39(6):327-337. doi:10.1016/j.urolonc.2021.04.013 - DOI - PubMed
    1. Klatte T, Rossi SH, Stewart GD. Prognostic factors and prognostic models for renal cell carcinoma: A literature review. World J Urol. 2018;36(12):1943-1952. doi:10.1007/s00345-018-2309-4 - DOI - PubMed
    1. Correa AF, Jegede O, Haas NB, et al. Predicting renal cancer recurrence: Defining limitations of existing prognostic models with prospective trial-based validation. J Clin Oncol. 2019;37(23):2062-2071. doi:10.1200/JCO.19.00107 - DOI - PMC - PubMed
    1. Usher-Smith JA, Li L, Roberts L, et al. Risk models for recurrence and survival after kidney cancer: A systematic review. BJU Int. 2022;130(5):562-579. doi:10.1111/bju.15673 - DOI - PubMed

MeSH terms

LinkOut - more resources