Prediction of Progression in Polycystic Kidney Disease Using the Kidney Failure Risk Equation and Ultrasound Parameters.

BACKGROUND

The kidney failure risk equation (KFRE) is a validated risk algorithm for predicting the risk of kidney failure in chronic kidney disease (CKD) patients regardless of etiology. Patients with autosomal dominant polycystic kidney disease (AD-PCKD) experience long disease trajectories and as such identifying individuals at risk of kidney failure would aid in intervention.

OBJECTIVE

To examine the utility of the KFRE in predicting adverse kidney outcomes compared with existing risk factors in a cohort of patients with AD-PCKD.

METHODS

Retrospective cohort study of AD-PCKD patients referred to a tertiary care center with a baseline kidney ultrasound and a KFRE calculation. Cox proportional hazards were used to examine the association of the KFRE and composite of an eGFR decline of >30% or the need for dialysis/transplantation. Discrimination and calibration of a parsimonious fully adjusted model and a model containing only total kidney volume (TKV) with and without the addition of the KFRE was determined.

RESULTS

Of 340 patients with AD-PCKD eligible, 221 (65%) met inclusion criteria. Older age, cardiac disease, cancer, higher systolic blood pressure, albuminuria, lower eGFR and a higher initial TKV were more common in patients with a higher KFRE. A total of 120 events occurred over a median patient follow-up time of 3.2 years. KFRE was independently associated with the composite kidney outcome. Addition of the KFRE significantly improved discrimination and calibration in a TKV only model and a fully adjusted model.

CONCLUSIONS

In a diverse, referral population with AD-PCKD, the KFRE was associated with adverse kidney outcomes and improved risk prediction.