Adoption of CKD-EPI (2021) for Glomerular Filtration Rate Estimation: Implications for UK Practice

Abstract: Introduction: Recommendations to move to a race-free estimating equation for glomerular filtration rate (GFR) have gained increasing prominence since 2021. We wished to determine the impact of any future adoption upon the chronic kidney disease (CKD) patient population of a large teaching hospital, with a population breakdown largely similar to that of England as a whole. Methods: We compared four estimating equations (Modification of Diet in Renal Disease [MDRD], CKD-EPI [2009], CKD-EPI [2021], and European Kidney Function Consortium [EKFC]) using the Bland-Altman method. Bias and precision were calculated (in both figures and percentages) for all patients with CKD and specific subgroups determined by age, ethnic group, CKD stage, and sex. CKD stage was assessed using all four equations. Results: All equations studied had a positive bias in South Asian patients and a negative bias in black patients compared to CKD-EPI (2021). Similarly, there was a positive bias in white patients across all equations studied. Comparing CKD-EPI (2009) and EKFC, this positive bias increased as patients aged; the opposite was seen with MDRD. Between 10% and 28% of patients in our dataset changed their CKD staging depending upon the estimating equation used. Discussion: Our work confirms previous findings that the MDRD equation overestimates estimated GFR (eGFR) in South Asians and underestimates eGFR in blacks. The alternative equations also demonstrated similar bias. This may, in part, explain the health inequalities seen in ethnic minority patients in the UK. Applying our findings to the UK CKD population as a whole would result in anywhere from 260,000 to 730,000 patients having their CKD stage reclassified, which in turn will impact secondary care services. Introduction: Recommendations to move to a race-free estimating equation for glomerular filtration rate (GFR) have gained increasing prominence since 2021. We wished to determine the impact of any future adoption upon the chronic kidney disease (CKD) patient population of a large teaching hospital, with a population breakdown largely similar to that of England as a whole. Methods: We compared four estimating equations (Modification of Diet in Renal Disease [MDRD], CKD-EPI [2009], CKD-EPI [2021], and European Kidney Function Consortium [EKFC]) using the Bland-Altman method. Bias and precision were calculated (in both figures and percentages) for all patients with CKD and specific subgroups determined by age, ethnic group, CKD stage, and sex. CKD stage was assessed using all four equations. Results: All equations studied had a positive bias in South Asian patients and a negative bias in black patients compared to CKD-EPI (2021). Similarly, there was a positive bias in white patients across all equations studied. Comparing CKD-EPI (2009) and EKFC, this positive bias increased as patients aged; the opposite was seen with MDRD. Between 10% and 28% of patients in our dataset changed their CKD staging depending upon the estimating equation used. Discussion: Our work confirms previous findings that the MDRD equation overestimates estimated GFR (eGFR) in South Asians and underestimates eGFR in blacks. The alternative equations also demonstrated similar bias. This may, in part, explain the health inequalities seen in ethnic minority patients in the UK. Applying our findings to the UK CKD population as a whole would result in anywhere from 260,000 to 730,000 patients having their CKD stage reclassified, which in turn will impact secondary care services. Introduction: Recommendations to move to a race-free estimating equation for glomerular filtration rate (GFR) have gained increasing prominence since 2021. We wished to determine the impact of any future adoption upon the chronic kidney disease (CKD) patient population of a large teaching hospital, with a population breakdown largely similar to that of England as a whole. Methods: We compared four estimating equations (Modification of Diet in Renal Disease [MDRD], CKD-EPI [2009], CKD-EPI [2021], and European Kidney Function Consortium [EKFC]) using the Bland-Altman method. Bias and precision were calculated (in both figures and percentages) for all patients with CKD and specific subgroups determined by age, ethnic group, CKD stage, and sex. CKD stage was assessed using all four equations. Results: All equations studied had a positive bias in South Asian patients and a negative bias in black patients compared to CKD-EPI (2021). Similarly, there was a positive bias in white patients across all equations studied. Comparing CKD-EPI (2009) and EKFC, this positive bias increased as patients aged; the opposite was seen with MDRD. Between 10% and 28% of patients in our dataset changed their CKD staging depending upon the estimating equation used. Discussion: Our work confirms previous findings that the MDRD equation overestimates estimated GFR (eGFR) in South Asians and underestimates eGFR in blacks. The alternative equations also demonstrated similar bias. This may, in part, explain the health inequalities seen in ethnic minority patients in the UK. Applying our findings to the UK CKD population as a whole would result in anywhere from 260,000 to 730,000 patients having their CKD stage reclassified, which in turn will impact secondary care services.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Adoption of CKD-EPI (2021) for Glomerular Filtration Rate Estimation: Implications for UK Practice ; volume:149 ; number:3 ; year:2025 ; pages:133-148 ; extent:16
Nephron ; 149, Heft 3 (2025), 133-148 (gesamt 16)

Urheber
Roy, Reuben
Raman, Maharajan
Dark, Paul M.
Kalra, Philip A.
Green, Darren

DOI
10.1159/000541689
URN
urn:nbn:de:101:1-2503122321527.849965789350
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:35 MESZ

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Beteiligte

  • Roy, Reuben
  • Raman, Maharajan
  • Dark, Paul M.
  • Kalra, Philip A.
  • Green, Darren

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