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World J Urol. 2013 Oct;31(5):1073-80. doi: 10.1007/s00345-013-1071-x. Epub 2013 Apr 9.

Gender differences in clinicopathological features and survival in surgically treated patients with renal cell carcinoma: an analysis of the multicenter CORONA database.

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Department of Urology, St. Elisabeth Hospital Straubing, Straubing, Germany.



To investigate gender differences in clinicopathological features and to analyze the prognostic impact of gender in renal cell carcinoma (RCC) patients undergoing surgery.


A total of 6,234 patients (eleven centers; Europe and USA) treated by radical or partial nephrectomy were included in this retrospective study (median follow-up 59 months; IQR 30-106). Gender differences in clinicopathological parameters were assessed. Multivariable Cox regression models were applied to determine the influence of parameters on disease-specific survival (DSS) and overall survival (OS).


A total of 3,751 patients of the study group were male patients (60.2 %), who were significantly younger at diagnosis and received more frequently NSS than women. Significantly, more often high-grade tumors and simultaneous metastasis were present in men. Whereas tumor size and pTN stages did not differ between genders, clear-cell and chromophobe RCC was diagnosed less frequently, but papillary RCC more often in men. Gender also independently influenced DSS (HR 0.75, p < 0.001) and OS (HR 0.80, p < 0.001) with a benefit for women. However, inclusion of gender in multivariable models did not significantly gain predictive accuracies (PA) for DSS (0.868-0.870, p = 0.628) and OS (0.775-0.777, p = 0.522). Furthermore, no significantly different DSS and OS rates were found in patients undergoing NSS.


This study demonstrates important gender differences in clinicopathological features and outcome of RCC patients with improved DSS and OS for women compared to men, even if solely patients with clear-cell RCC or M0-stage are taken into evaluation. However, inclusion of gender in multivariable models does not significantly gain PA of multivariable models.

[Indexed for MEDLINE]

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