Use of the CKD-EPI equation for estimation of GFR in an Australian cohort

Accuracy and precision of the CKD-EPI and MDRD predictive equations compared with glomerular filtration rate measured by inulin clearance in a Saudi population

BACKGROUND

Predictive equations for estimating glomerular filtration rate (GFR) in different clinical conditions should be validated by comparing with the measurement of GFR using inulin clearance, a highly accurate measure of GFR.

OBJECTIVES

Our aim was to validate the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations by comparing it to the GFR measured using inulin clearance in chronic kidney disease (CKD) patients.

DESIGN

Cross-sectional study performed in adult Saudi patients with CKD.

SETTING

King Saud University Affiliated Hospital, Riyadh, Saudi Arabia in 2014.

PATIENTS AND METHODS

We compared GFR measured by inulin clearance with the estimated GFR calculated using CKD-EPI and MDRD predictive formulas.

MAIN OUTCOME MEASURE(S)

Correlation, bias, precision and accuracy between the estimated GFR and inulin clearance.

RESULTS

Comparisons were made in 31 participants (23 CKD and 8 transplanted), including 19 males (mean age 42.2 [15] years and weight 68.7 [18] kg). GFR using inulin was 51.54 (33.8) mL/min/1.73 m2 in comparison to inulin clearance, the GFR by the predictive equations was: CKD-EPI creatinine 52.6 (34.4) mL/ min/1.73 m2 (P=.490), CKD-EPI cystatin C 41.39 (30.30) mL/min/1.73 m2 (P=.002), CKD creatinine-cystatin C 45.03 (30.9) mL/min/1.73 m2 (P=.004) and MDRD GFR 48.35 (31.5) mL/min/1.73 m2 (P=.028) (statistical comparisons vs inulin). Bland-Altman plots demonstrated that GFR estimated by the CKD-EPI creatinine was the most accurate compared with inulin clearance, having a mean difference (estimated bias) and limits of agreement of -1.1 (15.6,-17.7). By comparison the mean differences for predictive equations were: CKD-EPI cystatin C 10.2 (43.7,-23.4), CKD creatinine-cystatin C 6.5 (29.3,-16.3) and MDRD 3.2 (18.3,-11.9). except for CKD-EPI creatinine, all of the equations underestimated GFR in comparison with inulin clearance.

CONCLUSIONS

When compared with inulin clearance, the CKD-EPI creatinine equation is the most accurate, precise and least biased equation for estimation of GFR in the Saudi population and in all subgroups by age, stage of CKD and transplantation status.

LIMITATIONS

Small sample size and the study did not include patients with comorbid diseases such as diabetes, hepatitis C virus infection, and other co-morbidities as well as old age ( > 80 years).

Biomarkers in chronic kidney disease, from kidney function to kidney damage

Chronic kidney disease (CKD) typically evolves over many years, with a long latent period when the disease is clinically silent and therefore diagnosis, evaluation and treatment is based mainly on biomarkers that assess kidney function. Glomerular filtration rate (GFR) remains the ideal marker of kidney function. Unfortunately measuring GFR is time consuming and therefore GFR is usually estimated from equations that take into account endogenous filtration markers like serum creatinine (SCr) and cystatin C (CysC). Other biomarkers such as albuminuria may precede kidney function decline and have demonstrated to have strong associations with disease progression and outcomes. New potential biomarkers have arisen with the promise of detecting kidney damage prior to the currently used markers. The aim of this review is to discuss the utility of the GFR estimating equations and biomarkers in CKD and the different clinical settings where these should be applied. The CKD-Epidemiology Collaboration equation performs better than the modification of diet in renal disease equation, especially at GFR above 60 mL/min per 1.73 m². Equations combining CysC and SCr perform better than the equations using either CysC or SCr alone and are recommended in situations where CKD needs to be confirmed. Combining creatinine, CysC and urine albumin to creatinine ratio improves risk stratification for kidney disease progression and mortality. Kidney injury molecule and neutrophil gelatinase-associated lipocalin are considered reasonable biomarkers in urine and plasma to determine severity and prognosis of CKD.

Accuracy of the MDRD (Modification of Diet in Renal Disease) study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly

BACKGROUND

Glomerular filtration rate (GFR) is a measure of kidney function, commonly estimated using equations that adjust serum creatinine concentration for age, race, and sex. The Modification of Diet in Renal Disease (MDRD) Study equation is widely used, but underestimates GFR at higher levels. The serum creatinine-based Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI(cr)) equation generally provides more accurate estimation at GFR >60 mL/min/1.73 m(2). Newer equations have been reported using cystatin C concentration either alone (CKD-EPI(cys)) or in combination with creatinine concentration (CKD-EPI(cr-cys)). None of these equations has been well validated in older people. We tested the accuracy of these equations in people 74 years or older compared with GFR measured by a reference method.

STUDY DESIGN

Diagnostic test evaluation in a prospective cohort.

SETTING & PARTICIPANTS

Participants (n = 394; median age, 80 [range, 74-97] years) recruited from nephrology clinics and the community.

INDEX TEST

GFR estimated using the MDRD Study, CKD-EPI(cr), CKD-EPI(cys) and CKD-EPI(cr-cys) equations.

REFERENCE TEST

GFR measured using an iohexol clearance method.

RESULTS

Median measured GFR was 53.4 (range, 7.2-100.9) mL/min/1.73 m(2). MDRD Study-, CKD-EPI(cr)-, and CKD-EPI(cr-cys)-estimated GFRs overestimated GFR (median differences of 3.5 [P< 0.001], 1.7 [P < 0.001], and 0.8 [P = 0.02] mL/min/1.73 m(2), respectively); the CKD-EPI(cys) equation was unbiased. Accuracy (percentage of estimates within 30% of measured GFR [P(30)]) was 81%, 83%, 86%, and 86% for the MDRD Study, CKD-EPI(cr), CKD-EPI(cys), and CKD-EPI(cr-cys) equations, respectively. Accuracy of the MDRD Study equation was inferior (P = 0.004) to the CKD-EPI(cr) equation at GFR >60 mL/min/1.73 m(2).

LIMITATIONS

Those of non-European ancestry were not included. For practical reasons, only a 4-hour sampling protocol was used for iohexol clearance.

CONCLUSIONS

The CKD-EPI(cr) equation appeared less biased and was more accurate than the MDRD Study equation. No equation achieved an ideal P(30) in the overall population. Our data suggest that GFR estimation is as satisfactory in older people of European ancestry as it has been reported to be in younger individuals.

Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate

CONTEXT

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking.

OBJECTIVE

To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics.

DESIGN, SETTING, AND PARTICIPANTS

A meta-analysis of data from 1.1 million adults (aged ≥ 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012.

MAIN OUTCOME MEASURES

All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years).

RESULTS

Estimated GFR was classified into 6 categories (≥90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7% to 6.3%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95% CI, 0.74-0.86) for all-cause mortality, 0.73 (95% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and ≥65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts.

CONCLUSION

The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.