Investigation of end-stage kidney disease risk prediction in an ethnically diverse cohort of people with type 2 diabetes: use of kidney failure risk equation.

INTRODUCTION

The four variable kidney failure (KF) risk equation (KFRE) is recommended to estimate KF risk (ie, need for dialysis or kidney transplantation). Earlier referral to clinical kidney services for people with high-risk of kidney failure can ensure appropriate care, education and support are in place pre-emptively. There are limited data on investigating the performance of KFRE in estimating risk of end-stage kidney disease (ESKD) in people with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD). The primary ESKD endpoint event was defined as estimated glomerular filtration rate (eGFR) <10 mL/min/1.73 m and secondary endpoint eGFR <15 mL/min/1.73 m.

RESEARCH DESIGN AND METHODS

We studied 7296 people (30% women, 41% African-Caribbean, 45% Caucasian) with T2DM and CKD (eGFR median (range) 48 (15-59) mL/min/1.73 m) were included at two hospitals in London (median follow-up 10.2 years). Time to ESKD event was the endpoint and Concordance index (C-index) was used to assess KFRE's discrimination of those experiencing ESKD from those who did not. Mean (integrated calibration index (ICI)) and 90th percentile (E90) of the difference between observed and predicted risks were used as calibration metrics.

RESULTS

Of the cohort 746 (10.2%) reached ESKD primary event (135 (1.9%) and 339 (4.5%) over 2 and 5 years, respectively). Similarly, 1130 (15.5%) reached the secondary endpoint (270 (3.7%) and 547 (7.5%) over 2 and 5 years, respectively). The C-index for the primary endpoint was 0.842 (95% CI 0.836 to 0.848) and 0.816 (95% CI 0.812 to 0.820) for 2 and 5 years, respectively. KFRE 'under-predicted' ESKD risk overall and by ethnic group. Likewise, the C-index for secondary endpoint was 0.843 (0.839-0.847) and 0.801 (0.798-0.804) for 2 and 5 years, respectively. KFRE performance analysis performed more optimally with the primary endpoint with 50% enhancement of the calibration metrics than with the secondary endpoint. KFRE recalibration improved ICI by 50% and E90 by more than 78%.

CONCLUSIONS

Although derived for predicting KF, KFRE also demonstrated good discrimination for ESKD outcome. Further studies are needed to identify variables/biomarkers that may improve KFRE's performance/calibration and to aid the development of other predictive models to enable early identification of people at risk of advanced stages of CKD prior to onset of KF.