Comparison of predictive accuracy of four prognostic models for nonmetastatic renal cell carcinoma after nephrectomy: a multicenter European study

Abstract

Background: The objective of the current study was to compare, in a large multicenter study, the discriminating accuracy of four prognostic models developed to predict the survival of patients undergoing nephrectomy for nonmetastatic renal cell carcinoma (RCC).

Methods: A total of 2404 records of patients from 6 European centers were retrospectively reviewed. For each patient, prognostic scores were calculated according to four models: the Kattan model, the University of California at Los Angeles integrated staging system (UISS) model, the Yaycioglu model, and the Cindolo model. Survival curves were estimated by the Kaplan-Meier method and compared by the log-rank test. Discriminating ability was assessed by the Harrell c-index for censored data. The primary end point was overall survival (OS), and the secondary end points were cancer-specific survival (CSS) and disease recurrence-free survival (RFS).

Results: At last follow-up, 541 subjects had died of any causes, with a 5-year OS rate of 80%. The 5-year CSS and RFS rates were 85% and 78%, respectively. All models discriminated well (P < 0.0001). The c-indexes for OS were 0.706 for the Kattan nomogram, 0.683 for the UISS model, and 0.589 and 0.615 for the Yaycioglu and Cindolo models, respectively. The Kattan nomogram was found to improve discrimination substantially in the UISS intermediate-risk patients.

Conclusions: The current study appears to better define the general applicability of prognostic models for predicting survival in patients with nonmetastatic RCC treated with nephrectomy. The results suggest that postoperative models discriminate substantially better than preoperative ones. The Kattan model was consistently found to be the most accurate, although the UISS model was only slightly less well performing. The Kattan model can be useful in the UISS intermediate-risk patients.