Comparison between Three Different Equations for the Estimation of Glomerular Filtration Rate in Omani Patients with Type 2 Diabetes Mellitus

Abstract

Objectives:

Estimated glomerular filtration rate (eGFR) is an important component of a patient’s renal function profile. The Modification of Diet in Renal Disease (MDRD) equation and the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation are both commonly used. The aim of this study was to compare the performance of the original MDRD₁₈₆, revised MDRD₁₇₅ and CKD-EPI equations in calculating eGFR in type 2 diabetes mellitus (T2DM) patients in Oman.

Methods:

The study included 607 T2DM patients (275 males and 332 females, mean age ± standard deviation 56 ± 12 years) who visited primary health centres in Muscat, Oman, during 2011 and whose renal function was assessed based on serum creatinine measurements. The eGFR was calculated using the three equations and the patients were classified based on chronic kidney disease (CKD) stages according to the National Kidney Foundation Kidney Disease Outcomes Quality Initiative guidelines. A performance comparison was undertaken using the weighted kappa test.

Results:

The median eGFR (mL/min/1.73 m²) was 92.9 for MDRD₁₈₆, 87.4 for MDRD₁₇₅ and 93.7 for CKD-EPI. The prevalence of CKD stage 1 was 55.4%, 44.7% and 57% while for stages 2 and 3 it was 43.2%, 54% and 41.8%, based on MDRD₁₈₆, MDRD₁₇₅ and CKD-EPI, respectively. The agreement between MDRD₁₈₆ and CKD-EPI (к 0.868) was stronger than MDRD₁₈₆ and MDRD₁₇₅ (к 0.753) and MDRD₁₇₅ and CKD-EPI (к 0.730).

Conclusion:

The performances of MDRD₁₈₆ and CKD-EPI were comparable. Considering that CKD-EPI-based eGFR is known to be close to isotopically measured GFR, the use of MDRD₁₈₆ rather than MDRD₁₇₅ may be recommended.

Advances in Knowledge

• - Several estimated glomerular filtration rate (eGFR) equations have been implemented and updated in clinical practice for improving diagnostic care in renal medicine.

• - This study examines the impact of different eGFR equations on the prevalence of chronic kidney disease (CKD) in diabetic patients attending primary health centres in Muscat, Oman. The most effective is the Modification of Diet in Renal Disease (MDRD) equation MDRD₁₈₆ rather than MDRD₁₇₅.

Application to Patient Care

• - eGFR in renal profiles facilitates the early detection of renal impairment which will allow for early therapy in diabetic patients.

• - eGFR equations yield comparable results in established CKD (stage 4 and 5); however, the results are usually variable in early CKD (stages 1, 2 and 3).

• - This study provides data indicating that the most appropriate eGFR equation for the classification of CKD in diabetic patients is MDRD₁₈₆ rather than MDRD₁₇₅.

Serum creatinine-based equations for calculating estimated glomerular filtration rate (eGFR) have an established role in the assessment of renal function; these equations have improved the detection and management of chronic kidney disease (CKD), particularly in the last decade. The eGFR relates better to kidney function than serum creatinine, which is less useful as a single criterion of kidney function.1,2 Several equations are available for the calculation of eGFR, with the most commonly used ones being the Cockroft-Gault formula (1976), the Modification of Diet in Renal Disease (MDRD) equation (1999) and the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation (2009).3

In order to calculate the eGFR, the Cockcroft-Gault formula requires serum creatinine levels, age, gender and weight.4 It was originally based on the 1886 Jaffe assay for creatinine measurement; hence, it should be interpreted cautiously when the new creatinine methods are used. The need for weight and body surface area correction has limited its routine implementation.5 The MDRD equation is based on serum creatinine measurements, age and gender. In addition, it takes into account ethnicity (for African Americans) with results adjusted to a body surface area of 1.73 m².6–9 It is a popular equation that has been adopted for the classification of CKD in clinical practice by many international entities.1,7,8 Moreover, in 2006 the Department of Health in England recommended all National Health Service laboratories to report eGFR based on MDRD with every serum creatinine result, with a similar approach being adopted in North America, Europe and Australia.5,10,11

In the original MDRD equation (MDRD₁₈₆), a constant factor of 186 was used which was later revised and re-expressed by the same authors, Levey et al., to a constant factor of 175 (MDRD₁₇₅). This was mainly due to the standardisation of creatinine assays against the isotope dilution-mass spectrometry reference method.7–9 The MDRD equation works reasonably well at eGFR ≤60 mL/min/1.73 m², but underestimates GFR in subjects with a GFR ≥60 mL/min/1.73 m²; thus, it has limited accuracy in this range.9 However, despite the improved standardisation of the creatinine assay, this limitation did not improve when using the new revised MDRD₁₇₅ as compared to the gold-standard isotopically-based method.12 The MDRD equation was revisited again by Levey et al. in 2009, who then derived a new equation, the CKD-EPI equation.12 This new equation appears to be more accurate in estimating the GFR in the range of low serum creatinine. It yields GFR values with better agreement for eGFR than MDRD when compared with radio-labelled methods.12,13

The objective of this study was to compare the performance of the original MDRD₁₈₆, revised MDRD₁₇₅ and CKD-EPI equations for the calculation of eGFR, and their impact on classifying CKD stages in patients with type 2 diabetes mellitus (T2DM) attending primary health centres (PHCs) in Muscat, Oman.

Methods

This retrospective study was based on data from patients’ electronic records. All adult Omani T2DM patients registered in PHCs were considered candidates for inclusion in the study. The process involved multi-stage random selection of PHCs followed by the random selection of patients. The data were mainly for Omani adult patients aged ≥25 years who were diagnosed with T2DM between 1 January and 31 December 2011 (N = 607). The data included information such as age, gender, weight, height, duration of diabetes mellitus (DM), medications and serum creatinine levels. All duplicate tests were subsequently excluded. For those patients with more than one reported creatinine result, the most recent value was taken for analysis. Ethical approval for the study was obtained from the Ministry of Health Research and Ethical Review & Approval Committee in December 2011.

For all patients, the laboratory measurement of serum creatinine was performed using a Synchron LX20 analyser (Beckman Coulter, Inc., Brea, California, USA). Serum creatinine was analysed by the kinetic alkaline picrate methodology which is traceable to the reference method based on isotope dilution-mass spectrometry (IDMS). For each patient, eGFR was calculated using MDRD₁₈₆, MDRD₁₇₅ and CKD-EPI [Table 1]. A factor of 1.0 was considered for ethnicity since no evidence was available for a correction factor related to the local population being studied, and there were no participants of African American ethnicity to allow the use of the factor 1.212.7–9 The patients were classified according to their eGFR values (in mL/min/1.73 m²) into five CKD stages as per the National Kidney Foundation Kidney Disease Outcomes Quality Initiative guidelines: normal or CKD stage 1 - eGFR ≥90; CKD stage 2 - eGFR 60–89; CKD stage 3 - eGFR 30–59; CKD stage 4 - eGFR 15–29, and CKD stage 5 - eGFR <15.10

Table 1:

Serum creatinine-based formulae for the calculation of estimated glomerular renal filtration rate

MDRD formulae:

Original four-variable MDRD186 formula 7:

eGFR (mL/min/1.73 m2) = 186 (S.Cr in μmol/L × 0.011312)−1.154 × (age)−0.203 × (0.742 if female) × (1.212 if African American/black)

*Revised four-variable MDRD175 formula 9:

eGFR (mL/min/1.73 m2) = 175 (S.Cr in μmol/L × 0.011312)−1.154 × (age)−0.203 × (0.742 if female) × (1.212 if African American/black)

CKD-EPI formulae12:

For female with Cr <62 μmol/L:

eGFR (mL/min/1.73 m2) = 144 × (Cr/61.6)−0.329 × (0.993)age

For female with Cr >62 μmol/L:

eGFR (mL/min/1.73 m2) = 144 × (Cr/61.6) −1.209 × (0.993)age

For male with Cr <80 μmol/L:

eGFR (mL/min/1.73 m2) = 141 × (Cr/79.2) −0.411 × (0.993)age

For male with Cr >80 μmol/L:

eGFR (mL/min/1.73 m2) = 141 × (Cr/79.2) −1.209 × (0.993)age

MDRD = modification of diet in renal disease; eGFR = estimated glomerular filtration rate; S.Cr = serum creatinine; CKD-EPI = chronic kidney disease-epidemiology; Cr = creatinine.

^*Recommended for creatinine assay standardised against isotope dilution-mass spectrometry.

The data for each PHC was entered separately using Microsoft Excel (Microsoft Corp., Redmond, Washington, USA). A final integrated Excel worksheet was exported to the Statistical Package for the Social Sciences (SPSS), Version 16 (IBM, Corp., Chicago, Illinois, USA) for final analysis. The demographic and clinical data were expressed as mean, median, standard deviation (SD) and range (minimum–maximum). For calculating the prevalence, a pre-determined cut-off value was used to identify the abnormal levels which had been taken from the international guidelines for each parameter. The number of abnormal results were divided by the population size in that group and then multiplied by 100 to yield the prevalence percentage. A comparison between the CKD stages calculated from the three eGFR equations was undertaken using the weighted kappa test for agreement: a kappa statistic (к) of 0.21–0.40 was considered fair agreement; 0.41–0.60 a moderate agreement; 0.61–0.80 a substantial agreement, and 0.81–1.00 a near-perfect agreement.14

Results

The patients in this study (N = 607) included 275 males (45.3%) and 332 females (54.7%) aged 26–92 years with a mean age ± SD of 56 ± 12 years. They had a mean DM duration of 6.9 ± 0.2 years, a body mass index of 30 ± 0.34, a glycated haemoglobin (HbA_1C) level of 8 ± 0.09 and an albumin-to-creatinine ratio of 8.8 ± 1.97. The median value for serum creatinine (μmol/L) was 71 (range 33–339) and the eGFR (mL/min/1.73 m²) was 92.9 for MDRD₁₈₆, 87.4 for MDRD₁₇₅ and 93.7 for CKD-EPI [Table 2].

Table 2:

Different parameters in the diabetic population (N = 607)

Variables	Median	Mean ± SD	Range
Age in years	56.0	56.1 ± 12.5	26–92
Creatinine in μmol/L	71.0	75.7 ± 32.0	33–399
MDRD186 in mL/min/1.73 m2	92.9	93.8 ± 27.6	13–188
MDRD175 in mL/min/1.73 m2	87.4	88.3 ± 25.9	13–177
CKD-EPI in mL/min/1.73 m2	93.7	89.3 ± 21.3	11–131

SD = standard deviation; MDRD = modification of diet in renal disease; CKD-EPI = chronic kidney disease-epidemiology.

The distribution of CKD stages based on the three equations is shown in Table 3. Of the diabetic patients screened, 90.5%, 87% and 89.5% had an eGFR of ≥60 mL/min/1.73 m² (CKD stages 1 and 2) and 9.5%, 13% and 10.5% had an eGFR of <60 mL/min/1.73 m² (CKD stages 3, 4 and 5) based on MDRD₁₈₆, MDRD₁₇₅ and CKD-EPI equations, respectively. The difference mainly involved CKD stages 1, 2 and 3. The distribution of patients was nearly the same between the three equations in CKD stages 4 and 5.

Table 3:

Prevalence of chronic kidney disease stages based on eGFR by MDRD and CKD-EPI formulae (N = 607)

eGFR in mL/min/1.73 m2	MDRD186 n (%)	MDRD175 n (%)	CKD-EPI n (%)
≥90	337 (55.4)	271 (44.7)	346 (57)
60–89	213 (35.1)	257 (42.3)	197 (32.5)
30–59	49 (8.1)	71 (11.7)	56 (9.3)
15–29	7 (1.2)	6 (1.0)	6 (1.0)
<15	1 (0.2)	2 (0.3)	2 (0.3)

eGFR = estimated glomerular filtration rate; MDRD = modification of diet in renal disease; CKD-EPI = chronic kidney disease-epidemiology.

Based on the weighted kappa analysis (к 0.753), the agreement between MDRD₁₈₆ and MDRD₁₇₅ was found to be considerable. The MDRD₁₇₅ overestimated 66 (19.6%) and 22 (10.3%) patients as CKD stages 2 and 3, respectively, who had been labelled as CKD stages 1 and 2, respectively, using MDRD₁₈₆. The MDRD₁₈₆ and CKD-EPI showed near-perfect agreement (к 0.868). There were 13 (3.9%) and 8 (3.8%) patients with CKD stages 1 and 2 using MDRD₁₈₆ who were reclassified into CKD stage 2 and 3 by CKD-EPI, respectively. On the other hand, 22 patients (10.3%) with CKD stage 2 using MDRD₁₈₆ were reclassified as CKD stage 1 using CKD-EPI [Table 4]. The agreement between MDRD₁₈₆ and CKD-EPI (к 0.868) was better than between MDRD₁₇₅ and CKD-EPI (к 0.730). There was also a clear underestimation of GFR using MDRD₁₇₅ compared to CKD-EPI and MDRD₁₈₆ for patients with eGFR ≥60 mL/min/1.73 m². CKD-EPI reclassified 79 (30.7%) patients from CKD stage 2 using MDRD₁₇₅ into CKD stage 1, and another 15 (21.1%) patients were reclassified as CKD stage 2 from stage 3 [Table 5]. Similarly, the MDRD₁₈₆ equation reclassified 66 (25.7%) and 22 (31.0%) patients as CKD stages 1 and 2 who had been in stages 2 and 3, respectively, according to the MDRD₁₇₅ equation.

Table 4:

Comparison of the prevalence of chronic kidney disease stages based on eGFR by MDRD₁₈₆ as compared with MDRD₁₇₅ and CKD-EPI formulae in the study patients (N = 607)

	eFGR in mL/min/1.73 m2	MDRD186 n (%)
		≥90	60–89	30–59	15–29	<15	Total	к
MDRD175	≥90	271 (80)	-	-	-	-	271	0.753
	60–89	66 (20)	191 (87)	-	-	-	257
	30–59	-	22 (10.3)	49 (100)	-	-	71
	15–29	-	-	-	6 (86)	-	6
	<15	-	-	-	1 (14)	1 (100)	2
	Totals	337	213	49	7	1	607
CKD-EPI	≥90	324 (96)	22 (10.3)	-	-	-	346	0.868
	60–89	13 (4)	183 (85.9)	1 (2)	-	-	197
	30–59	-	8 (3.8)	48 (98)	-	-	56
	15–29	-	-	-	6 (86)	-	6
	<15	-	-	-	1 (14)	1 (100)	2
	Totals	337	213	49	7	1	607

eGFR = estimated glomerular filtration rate; MDRD = modification of diet in renal disease; к = kappa statistic; CKD-EPI = chronic kidney disease-epidemiology.

Table 5:

Comparison of the prevalence of chronic kidney disease stages based on eGFR by MDRD₁₇₅ as compared with MDRD₁₈₆ and CKD-EPI formulae in the study patients (N = 607)

	eFGR in mL/min/1.73 m2	MDRD175 n (%)
		≥90	60–89	30–59	15–29	<15	Total	к
CKD-EPI	≥90	267 (98.5)	79 (30.7)	-	-	-	346	0.753
	60–89	4 (1.5)	178 (69.3)	15 (21.1)	-	-	197
	30–59	-	-	56 (78.8)	-	-	56
	15–29	-	-	-	6 (100)	-	6
	<15	-	-	-		2 (100)	2
	Totals	271	257	71	6	2	607
MDRD186	≥90	271 (100)	66 (25.7)	-	-	-	337	0.868
	60–89	-	191 (74.3)	22 (31)	-	-	213
	30–59	-	-	49 (69)	-	-	49
	15–29	-	-	-	6 (100)	1 (50)	7
	<15	-	-	-	-	1 (50)	2
	Totals	271	257	71	6	2	607

eGFR = estimated glomerular filtration rate; MDRD = modification of diet in renal disease; к = kappa statistic; CKD-EPI = chronic kidney disease-epidemiology.

A comparison of the data by age and gender between the three equations is shown in Table 6. The misclassification mostly involved CKD stages 1, 2 and 3. Apparently, the misclassification between MDRD₁₈₆ and MDRD₁₇₅ included an underestimation of GFR by MDRD₁₇₅ within all age groups, but particularly in those above 45 years of age. CKD-EPI overestimated GFR among those below 65 years of age and underestimated it in those over 65 as compared to MDRD₁₈₆. Similarly, CKD-EPI reclassified CKD stage 2 into stage 1 within all age groups as compared to MDRD₁₇₅. The misclassification of CKD stages using MDRD₁₈₆ and MDRD₁₇₅ involved more males than females among those above 45 years of age. However, the misclassification by CKD-EPI from MDRD₁₇₅ apparently involved more females in the older age groups.

Table 6:

Misclassification in CKD stages according to gender comparing different estimated glomerular filtration formulae in the study patients (N = 607)

Misclassifications of CKD stages	Age group in years	MDRD186 and MDRD175		MDRD186 and CKD-EPI		MDRD175 and CKD-EPI
		Male	Female	Male	Female	Male	Female
Stage 1→2	≤35	4	-	-	-	-	-
	36–45	4	5	-	-	-	-
	46–55	10	13	-	-	-	-
	56–65	5	5	-	-	-	-
	>65	3	-	6	-	1	1
Stage 2→3	46–55	2	-	-	-	-	-
	56–65	4	3	-	-	-	-
	>65	5	8	3	5	-	1
Stage 2→1	≤35	-	-	1	-	5	-
	36–45	-	-	1	6	5	11
	46–55	-	-	4	5	14	18
	56–65	-	-	-	5	9	13
	>65	-	-	1	-	-	2
Stage 3→2	46–55	-	-	-	-	2	-
	56–65	-	-	-	-	4	-
	>65	-	-	-	-	2	3

CKD = chronic kidney disease; MDRD = modification of diet in renal disease; CKD-EPI = chronic kidney disease-epidemiology.

Discussion

During the last decade, there has been increasing interest in the use of creatinine-based eGFR equations, with MDRD being considered the most valid formula.6,15 In its original format, the MDRD₁₈₆ was recommended to be modified to the revised MDRD₁₇₅ for creatinine assays standardised to the IDMS reference method.7–9 In the current study, the median eGFR (mL/min/1.73 m²) was found to be 92.9 for MDRD₁₈₆, 87.4 for MDRD₁₇₅ and 93.7 for CKD-EPI, with the values being almost comparable for MDRD₁₈₆ and CKD-EPI. Only a few studies in the literature have compared the performance of MDRD₁₈₆ to various other GFR equations; most of them compared MDRD₁₇₅ with CKD-EPI. Chudleigh et al. compared the performance of MDRD₁₈₆ and MDRD₁₇₅ in their patient series based on the isotope gold-standard method.17 The study reported a GFR of 114.9 ± 22.4 mL/min/1.73 m² for the isotope method, an eGFR of 94.7 ± 22.0 mL/min/1.73 m² for MDRD₁₇₅ and 89.9 ± 19.0 mL/min/1.73 m² for MDRD₁₈₆ (a CKD-EPI equation was not available at that time). Based on these results, Chudleigh et al. concluded that MDRD₁₇₅ is superior to MDRD₁₈₆ as its eGFR values were nearer to the isotope method than MDRD₁₈₆.17 These data were surprising and questionable, and the numerical results for the two MDRD equations in their study could not be verified mathematically. Following the implementation of CKD-EPI, several studies showed an improved agreement of eGFR using CKD-EPI compared to using MDRD₁₇₅ based on isotope gold-standard methods.12,13,18 However, these studies did not consider or include MDRD₁₈₆ in their comparison with CKD-EPI. Nevertheless, a comparative study involving European diabetic patients concluded a significant correlation between MDRD₁₈₆ (coefficient of determination [R²] 0.818) and CKD-EPI (R² 0.814) and the isotope gold-standard method.28

The difference in the prevalence of CKD using the three equations can mostly be attributed to the redistribution in the prevalence of CKD stages 1, 2 and 3 as seen in the agreement analysis. The agreement between MDRD₁₈₆ and CKD-EPI is more efficient (к 0.868) than the one between MDRD₁₈₆ and MDRD₁₇₅ (к 0.753) or MDRD₁₇₅ and CKD-EPI (к 0.730). A recent meta-analysis comparing the use of the CKD-EPI equation and the MDRD equation found that, when using the revised MDRD equation, 24.4% of participants were reclassified to a higher eGFR category by the CKD-EPI equation and the prevalence of CKD stages 3 to 5 (eGFR <60 mL/min/1.73 m²) was reduced from 8.7% to 6.3%. The reclassification mainly involved CKD stage 3A to CKD stage 2.25

The distribution of gender and age within the misclassified cases was divided into two main groups: underestimated GFR and a subsequent reclassification of CKD stage, and overestimated GFR with a subsequent reclassification of CKD to a higher stage [Table 6]. When comparing MDRD₁₇₅ with MDRD₁₈₆, it was found that MDRD₁₇₅ clearly underestimated GFR in all age groups and predominantly affected males. In contrast, when comparing CKD-EPI and MDRD₁₈₆, the CKD-EPI predominantly underestimated GFR in those aged ≥65 years. The overestimation was much more pronounced when comparing CKD-EPI and MDRD₁₇₅. In a large cohort study in the UK, Carter et al. reported a median eGFR determined by CKDEPI that was significantly higher than the median GFR determined by MDRD₁₇₅ (82 versus 76 mL/min/1.73 m²,19 P <0.0001 with an overall mean bias of 5.0%) and a lower eGFR in those aged ≥70 years using CKD-EPI. However, Kilbride et al. reported that the CKD-EPI equation appears less biased and reasonably accurate in estimating GFR in both younger and older populations.20 Earley et al. recently pointed out that neither MDRD nor CKD-EPI may be optimal for all ages and populations despite the potential promise of the CKD-EPI equation.21 Moreover, the CKD-EPI equation performed as inadequately as the MDRD equation in T2DM individuals.26,28 Patients’ characteristics seem to account for the previously reported differences in the performance of CKD-EPI and MDRD equations.27 With the good agreement between MDRD₁₈₆ and CKD-EPI, which is better than the agreement between MDRD₁₇₅ and CKD-EPI, it is worth considering the use of MDRD₁₈₆ whenever MDRD equations are implemented in practice, including in primary care— particularly bearing in mind the better agreement of CKD-EPI with radiolabelled methods. In addition, the CKD-EPI equation requires a complicated technical procedure in order to be incorporated into electronic healthcare systems.

The current cross-sectional study has some limitations. The study did not include a reference method for GFR measurements. However, comparison data were based on the status of MDRD and CKD-EPI equations in relation to the reference GFR methods in the cited publications. Also, the study was based mainly on single creatinine readings that might have affected the prevalence of CKD in the current diabetic population. Additionally, the population data were from PHCs; hence, many patients with CKD stages 4 and 5 might not have been included as these cases are usually referred to tertiary care institutions. Also, the population was mainly Arab-Asian, and since Arab ethnicity was not referred to in the MDRD or CKD-EPI equation, the factor in the equation was assumed to be 1.0. Further studies may be needed to validate these equations in the Arab-Asian population, taking into consideration that validated Japanese and Chinese MDRD equations have been reported in the literature.22,23 For the Middle Eastern community, serum creatinine, age and gender have been utilised for estimating GFR using the aforementioned equations. No correction factor for ethnicity is considered which has led to the widespread acceptance of these equations by pathologists and clinicians.7,15,24

Conclusion

The performance of MDRD₁₈₆ and CKD-EPI in the calculation of GFR was, to a great extent, in agreement. Thus, calculated eGFR results using both equations were comparable. The revised MDRD₁₇₅ was found to underestimate GFR and thus increase the prevalence of CKD, particularly in stages 2 and 3, when compared with MDRD₁₈₆ and CKD-EPI. Taking into consideration that CKD-EPI-based eGFR has been reported to be near to isotopically measured GFR, the use of MDRD₁₈₆ may be recommended over MDRD₁₇₅. Also, before making any decision to change from MDRD₁₇₅ to CKD-EPI, the use of MDRD₁₈₆ should be considered.