Kidney Failure Prediction: Multicenter External Validation of KFRE Model in Patients with CKD Stages 3-4 in Peru

Abstract

Objectives: To externally validate the 4-variable Kidney Failure Risk Equation (KFRE) in the Peruvian population for predicting kidney failure at 2 and 5 years. Design: A retrospective cohort study. Setting: 17 primary care centers from the Health's Social Security of Peru. Participants: Patients older than 18 years, diagnosed with chronic kidney disease (CKD) stage 3a-3b-4 and 3b-4, between January 2013 and December 2017. Patients were followed until they developed kidney failure, died, were lost, or ended the study (December 31, 2019), whichever came first. Primary and Secondary Outcome Measures: Performance of the KFRE model was assessed based on discrimination and calibration measures considering the competing risk of death. Results: We included 7519 patients in stages 3a-4 and 2,798 patients in stages 3b-4. The estimated cumulative incidence of kidney failure, accounting for competing event of death, at two years and five years was 1.52% and 3.37% in stages 3a-4 and 3.15% and 6.86% in stages 3b-4. KFRE discrimination at 2 and 5 years was high, with Time-Dependent Area Under the Curve (AUC-td) and C-index > 0.8 for all populations. Regarding calibration in-the-large, the Observed-to-Expected (O/E) ratio and the calibration intercept indicated that KFRE underestimates the overall risk at two years and overestimates it at 5-years in all populations. Conclusions: The 4-variable KFRE models have good discrimination but poor calibration in the Peruvian population. The model underestimates the risk of kidney failure in the short term and overestimates it in the long term. Further research should focus on updating or recalibrating the KFRE model to better predict kidney failure in the Peruvian context before recommending its use in clinical practice.