Singleton RK, Heath AK, Clasen JL, et al. - Researchers assessed a published renal cell carcinoma (RCC) risk prediction model (including age, gender, BMI, and smoking status) among participants (n = 192,172) from the EPIC cohort (including 588 incident RCC cases), focusing on discrimination (C-statistic) as well as calibration (noted likelihood as a function of predicted probability). A flexible parametric survival model was employed to construct an expanded model incorporating age, gender, BMI, and smoking status, with the addition of self-reported history of hypertension and measured blood pressure. Well-calibrated probabilities and good discrimination were provided by the previously published model. Slightly improved discrimination was yielded by the model developed by researchers. Overall, although findings showed good performances of the models for predicting incident RCC, these currently are not sufficiently powerful to detect people at substantial risk of RCC in a general population.