Low predictive accuracy of the Kattan postoperative nomogram for renal cell carcinoma recurrence in a population of French patients

BACKGROUND. The aim of the current study was to establish the predictive accuracy of the Kattan postoperative nomogram for nonmetastatic renal cell carcinoma (RCC) by comparing predictions with actual disease recurrence in patients who underwent surgery in a single center in France. METHODS. Between 1985 and 2000, 844 patients were treated for RCC. The following data were collated: age, symptoms, histology, tumor size, grade, TNM 1997 stage, recurrence, and progression. For each patient a prognostic score (predicted probability) for recurrence‐free survival (RFS) at 5 years was calculated using the Kattan nomogram. The discriminating ability of the model was assessed by Harrell's concordance index (c‐index). Bootstrapping was used to assess confidence intervals. Furthermore, survival was then estimated by the Kaplan‐Meier method and Cox proportional hazards regression analysis. RESULTS. In all, 565 patients (median age, 62 years) were included. At the time of the last follow‐up, 81 patients had died and 101 had experienced RCC recurrence. The c‐index for RFS (Kattan nomogram) was only 0.607 (95% confidence interval [CI]: 0.576–0.635). The 5‐year RFS rate and cancer‐specific survival rate were 81.5% and 84.7%, respectively. Of the 4 variables included in the nomogram, only TNM stage was associated with recurrence in a multivariate analysis (Cox analysis) (P = .022). CONCLUSIONS. There was a discrepancy between predicted RFS as estimated by the Kattan nomogram and the likelihood of being recurrence‐free at 5 years according to the Cox analysis in the current population of patients. However, until new dynamic models become available clinicians may still improve their predictive ability by using the current nomogram. Cancer 2006. © 2006 American Cancer Society. The Kattan postoperative nomogram for nonmetastatic renal cell carcinoma is the most widely used prognostic tool to predict recurrence. Although the Kattan model is known as the best among all other available models, it may be of low accuracy in external representative patient cohorts, outside its training population.