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Year : 2014  |  Volume : 6  |  Issue : 2  |  Page : 116-121

Clinico-pathological prognostic factors of renal cell carcinoma: A 15-year review from a single center in Greece

Department of Urology, G. Hatzikosta General Hospital, 45001, Ioannina, Greece

Correspondence Address:
Nikolaos Grivas
Department of Urology, G. Hatzikosta General Hospital, Makriyianni Avenue, 45001, Ioannina
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DOI: 10.4103/0974-7796.130552

PMID: 24833821

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Aim: To investigate the prognostic significance of certain clinical and pathological factors of renal cell cancer. Materials and Methods: One hundred and fourteen patients who underwent radical nephrectomy between 1996 and 2011 in our hospital were examined. Parameters including age, gender, mode of presentation, hematological and pathological parameters were evaluated for their role as predictors of disease-free and overall survival. Results: Median follow-up was 69 months. Predominant histological type, pathological stage, and nuclear grade were clear cell carcinoma, pT1, and Fuhrman II, respectively. Five-year overall and disease-free survival were 86% and 82%, respectively. Only nuclear grade ( P = 0.02) and preoperative anemia ( P < 0.01) were correlated with overall survival, while pathological stage, nuclear grade, anemia, and neutrophil-to-lymphocyte ratio of 2.7 or greater were associated with disease-free survival ( P = 0.02, P = 0.038, P < 0.01, P = 0.049, respectively). In the multivariate setting, anemia ( P = 0.04) and pathological stage ( P = 0.026) were the only independent statistically significant predictors of disease-free survival, while anemia ( P = 0.018) and neutrophil to lymphocyte ratio ( P = 0.034) were the only factors correlated with overall survival. Conclusions: Due to the wide application of various imaging studies, patients with kidney cancer are diagnosed more often with localized disease and favorable pathological features. Fuhrman nuclear grade, pathological stage, preoperative anemia, and neutrophil to lymphocyte ratio are strongly associated with survival. In localized disease, such information could be used to guide the intensity of follow-up and identify high-risk patients who can be targeted for adjuvant therapy trials.

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