Validation of a new prognostic model to easily predict outcome in renal cell carcinoma: The GRANT score applied to the ASSURE trial population

Background: Prognostic scores have been developed to estimate the risk of recurrence and the probability of survival after nephrectomy for renal cell carcinoma (RCC). The use of these tools, despite being helpful to plan a customized schedule of follow-up, to the patient's tailored counselling and to select individuals who could potentially benefit from adjuvant treatment, currently is not routine, due to their relative complexity and to the lack of histological data (i.e. necrosis).Patients and methods: We developed a simple score called GRade, Age, Nodes and Tumor (GRANT) based on four easily obtained parameters: Fuhrman grade, age, pathological nodal status and pathological tumor size. Patients with 0 or 1 factor are classified as favorable risk, whereas patients with two or more risk factors as unfavorable risk. The large population of RCC patients from the ASSURE adjuvant trial was used as independent dataset for this external validation, to investigate the prognostic value of the new score in terms of disease-free survival and overall survival and to evaluate its possible application as predictive tool. Statistical analyses were carried out by the Department of Biostatistics & Computational Biology, Dana-Farber Cancer Institute (Boston, USA) for the ASSURE trial patients' population.Results: The performance of the new model is similar to that of the already validated score systems, but its strength, compared with the others already available, is the ease and clarity of its calculation, with great speed of use during the clinical practice. Limitations are the use of the Fuhrman nuclear grade, not valid for rare histologies, and the TNM classification modifications over time.Conclusion: The GRANT score demonstrated its potential usefulness for clinical practice.