Abstract
INTRODUCTION AND OBJECTIVES: To determine the applicability of the current prognostic models to predict disease recurrencefree survival (RFS) and cancer-specific survival (CSS) after nephrectomy in nonmetastatic renal cell carcinoma (RCC) in a Mediterranean Caucasian population. METHODS: We retrospectively reviewed the clinical and pathological variables of 305 patients treated with nephrectomy (partial or radical) for RCC. Three models were used to predict RFS (Kattan nomogram, Sorbellini model and Leibovich model), and three ones to predict CSS: the University of California at Los Angeles Integrated Staging System (UISS) model, the Stage, Size, Grade and Necrosis (SSIGN) model and the Karakiewicz nomogram. Survival was estimated using the Kaplan-Meier method. The predictive ability of the different scores was evaluated using the Harrell concordance index. RESULTS: With a median follow-up of 50.7 months, 41 patients (15.1%) died of RCC and in 54 (19.9%) the disease progressed. The 5-years CSS and RFS rates were 84.9% and 77.5%, respectively. Among the features included in the models, the Eastern Cooperative Oncology Group Performance Score (ECOG PS), pathological T (pT) stage, tumor size in surgical specimen, nuclear grade and pathological necrosis were significantly associated with RFS and CSS on univariate analysis. The ECOG PS, pT stage and nuclear grade also influenced in the multivariate analysis (Table 1). The c-indexes for RFS at 5 years were 0.626 for the Kattan nomogram and 0.696 for the Sorbellini model. The Leibovich nomogram presented c-indexes for RFS at 1, 3 and 5 years of 0.807, 0.728 and 0.721 respectively. The c-indexes for CSS were 0.774, 0.773, 0.772, 0.760 and 0.760 at 1, 2, 3, 4 and 5 years respectively for the UISS model, 0.831, 0.819 and 0.795 at 1, 3 and 5 years respectively for the SSIGN nomogram, and 0.752, 0.753 and 0.767 at 1, 2 and 5 years respectively for the Karakiewicz model. CONCLUSIONS: The current prognostic models are therefore validated in the Mediterranean Caucasian population with nonmetastatic RCC treated by surgery. The Leibovich nomogram was found to be most accurate to predict RFS, and SSIGN model to predict CSS. The most influential features in our population, both in RFS and CSS, were nuclear grade, ECOG PS and pT stage.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.