Using the kidney failure risk equation to predict end-stage kidney disease in CKD patients of South Asian ethnicity: an external validation study

Francesca Maher; Lucy Teece; Rupert W Major; Naomi Bradbury; James F Medcalf; Nigel J Brunskill; Sarah Booth; Laura J Gray

doi:10.1186/s41512-023-00157-x

Using the kidney failure risk equation to predict end-stage kidney disease in CKD patients of South Asian ethnicity: an external validation study

Diagn Progn Res. 2023 Oct 5;7(1):22. doi: 10.1186/s41512-023-00157-x.

Authors

Francesca Maher¹, Lucy Teece¹, Rupert W Major^{2

3}, Naomi Bradbury¹, James F Medcalf^{2

3}, Nigel J Brunskill^{2

3}, Sarah Booth¹, Laura J Gray⁴

Affiliations

¹ Department of Population Health Sciences, University of Leicester, Leicester, UK.
² Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.
³ John Walls Renal Unit, University Hospitals of Leicester NHS Trust, Leicester, UK.
⁴ Department of Population Health Sciences, University of Leicester, Leicester, UK. lg48@leicester.ac.uk.

Abstract

Background: The kidney failure risk equation (KFRE) predicts the 2- and 5-year risk of needing kidney replacement therapy (KRT) using four risk factors - age, sex, urine albumin-to-creatinine ratio (ACR) and creatinine-based estimated glomerular filtration rate (eGFR). Although the KFRE has been recalibrated in a UK cohort, this did not consider minority ethnic groups. Further validation of the KFRE in different ethnicities is a research priority. The KFRE also does not consider the competing risk of death, which may lead to overestimation of KRT risk. This study externally validates the KFRE for patients of South Asian ethnicity and compares methods for accounting for ethnicity and the competing event of death.

Methods: Data were gathered from an established UK cohort containing 35,539 individuals diagnosed with chronic kidney disease. The KFRE was externally validated and updated in several ways taking into account ethnicity, using recognised methods for time-to-event data, including the competing risk of death. A clinical impact assessment compared the updated models through consideration of referrals made to secondary care.

Results: The external validation showed the risk of KRT differed by ethnicity. Model validation performance improved when incorporating ethnicity and its interactions with ACR and eGFR as additional risk factors. Furthermore, accounting for the competing risk of death improved prediction. Using criteria of 5 years ≥ 5% predicted KRT risk, the competing risks model resulted in an extra 3 unnecessary referrals (0.59% increase) but identified an extra 1 KRT case (1.92% decrease) compared to the previous best model. Hybrid criteria of predicted risk using the competing risks model and ACR ≥ 70 mg/mmol should be used in referrals to secondary care.

Conclusions: The accuracy of KFRE prediction improves when updated to consider South Asian ethnicity and to account for the competing risk of death. This may reduce unnecessary referrals whilst identifying risks of KRT and could further individualise the KFRE and improve its clinical utility. Further research should consider other ethnicities.

Keywords: Chronic kidney disease; Competing risks; Ethnicity; External validation; Kidney failure risk equation; Primary care cohort.

Abstract

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