Validation of the GRade, Age, Nodes and Tumor (GRANT) score within the Surveillance Epidemiology and End Results (SEER) database: A new tool to predict survival in surgically treated renal cell carcinoma patients

Author:

Buti SebastianoORCID,Karakiewicz Pierre I.,Bersanelli MelissaORCID,Capitanio UmbertoORCID,Tian Zhe,Cortellini Alessio,Taguchi Satoru,Briganti Alberto,Montorsi Francesco,Leonardi Francesco,Bandini MarcoORCID

Abstract

Abstract The purpose of the present study was to validate the new GRade, Age, Nodes and Tumor (GRANT) score for renal cell carcinoma (RCC) prognostication within a large population of patients. Within the Surveillance, Epidemiology, and End Results database, we identified patients with either clear-cell or papillary RCC, who underwent nephrectomy between 2001 and 2015. Harrell’s C-Index, calibration plot and decision curve analysis were used to validate the GRANT model using a five-risk group stratification (0 vs. 1 vs. 2 vs. 3 vs. 4 risk factors). The primary endpoint was overall survival (OS) at 60 months. The analyses were repeated according to the histologic subgroup. The overall population included 73217 cases; 60900 with clear-cell RCC and 12317 with papillary histology, respectively. According to a five-risk group stratification, 23985 patients (32.8%) had no risk factor (0), 35019 (47.8%) had only one risk factor (1), 13275 (18.1%) had risk score 2, 854 (1.2%) had 3 risk factors and 84 (0.1%) of cases had a GRANT score of 4, respectively. At 60 months, OS rates as determined by the GRANT score were respectively 94% (score 0) vs. 86% (score 1) vs. 76% (score 2) vs. 46% (score 3) vs. 16% (score 4). In both histologic subtypes, the GRANT score yielded good calibration and high net benefit. OS C-Index values were 0.677 and 0.650 for clear-cell and papillary RCC at 60 months after surgery, respectively. In conclusion, the GRANT score was validated with a five-risk group stratification in a huge population from the SEER database, offering a further demonstration of its reliability for prognostication in RCC.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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