Comparative Analysis of the New Chronic Kidney Disease Epidemiology Collaboration and the Modification of Diet in Renal Disease Equations for Estimation of Glomerular Filtration Rate in HIV Type 1-Infected Subjects

Abstract

Recently, a new Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula was presented as a better alternative to the modification of diet in renal disease (MDRD) formula for GFR estimation (eGFR) in patients with relatively well-preserved kidney function. The main objective of our study was to compare the eGFR results arrived by the new CKD-EPI to the older MDRD equation in antiretroviral (ARV)-naive and ARV-treated HIV-1-infected patients. The study was performed in 287 adult HIV-1-infected patients and was an evaluation comparing eGFR results based on age, gender, race, and serum creatinine. The biggest difference in estimated glomerular filtration rate (eGFR) measured by the two formulas was seen in ARV-naive men with well-preserved kidney function (p = 0.001). Moreover, we found a significant negative correlation between mean difference in eGFR measured by the two equations and the age of the studied subjects (r = −0.37, p < 0.001). No correlation was observed between mean difference in eGFR and HIV viral load (r = −0.15, p = 0.2). Independent of the equation used, a significant decrease of eGFR in ARV-treated in comparison to ARV-untreated HIV-1-infected patients was seen (p < 0.001). In conclusion, in HIV-1-infected subjects, especially in ARV-naive men with well-preserved kidney function, eGFR measured by MDRD and CKD-EPI formulas varies strongly following the method used. Such discrepancies may be important in everyday clinical practice and must be confirmed by additional studies using GFR measured with a reference method.

Introduction

I n the past decade, renal disorders have become more important comorbidities in the management of HIV-infected patients. There has also been observed a strong association between decreased kidney function and increased risk of cardiovascular disease and heart failure.^1,2 The prevalence rate of chronic kidney disease (CKD) in the HIV-positive population ranges from 2% to 30%, increasing significantly with age.^3
–5 In Afro-Americans, above 60% of CKD is related to HIV-associated nephropathy, yet most white patients develop CKD due to concomitant metabolic or cardiovascular diseases such as diabetes mellitus, hypertension, or atherosclerosis. The other known factors that may influence CKD development are genetic factors, exposure to nephrotoxic drugs, or hepatitis C virus coinfection.⁶

Serum creatinine and estimated glomerular filtration rate (eGFR) measured by serum creatinine-based equations, such as the Cockroft–Gault equation, reexpressed the modification of diet in renal disease (MDRD) equation and the Mayo Clinic quadratic equation are still the most popular methods of renal function estimation in routine clinical practice. Nevertheless, these formulas have some important limitations that influence their final results. First, serum creatinine level depends on age, gender, muscle mass, ethnicity, pregnancy, drugs used, and concomitant diseases. Second, they are not very useful in patients with small changes in GFR and therefore their sensitivity is greatest in patients with already observed loss of renal function and GFR <60 ml/min/1.73 m².⁷ Consequently, they are less accurate in populations with normal or near normal GFR.

In 2009, a new eGFR formula, described by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), was presented. The authors developed this new equation as a better alternative to presently used screening tests in patients with relatively well-preserved kidney function.⁸ The next studies confirmed the usefulness of the CKD-EPI equation in subjects with GFR >60ml/min/1.73 m² and chronic kidney disease, autosomal dominant polycystic kidney disease, Fabry disease, kidney and heart transplant recipients, as well as in patients with coronary artery disease with normal serum creatinine undergoing percutaneous coronary interventions.^9

–14 Stevens et al. showed that presence of diabetes and body weight had no influence on CKD-EPI sensitivity.¹⁵ These data were confirmed in a general middle-aged population without kidney disease.¹⁶ The CKD-EPI equation seems to be also more accurate in GFR assessment in African, Asian, and Indian populations.^17
–19 Moreover, the CKD-EPI equation has a performance similar to the MDRD equation for people with lower levels of GFR, and therefore can be used for these people as well.²⁰

Presently, the MDRD equation is recommended as a “gold standard” and is widely used in clinical practice in eGFR measurements in HIV-infected populations. However, there are no data concerning the usefullness of the CKD-EPI formula in this group of patients. The goal of our study was to compare the eGFR results arrived by new CKD-EPI and MDRD equations in HIV-1-infected patients.

Materials and Methods

The study was performed in 287 adult HIV-1-infected patients [234 males and 53 females; aged from 20 to 69 years old, mean age 39.46 years; 182 on combined antiretroviral therapy (cART)] receiving care in the Department of Hepatology and Acquired Immunodeficiences in Warsaw. Seven patients (2.4%) were black. Plasma HIV-1 RNA was evaluated using the Amplicor system (Roche Diagnostics and Abbott). We used data from 1520 serum creatinine measurements over a 4-year observation period (2006–2009). All studied laboratory tests went to the same laboratory of Warsaw's Hospital for Infectious Diseases and were mandated every 3–6 month as standard laboratory control tests of the HIV infection evolution and/or the assessment of cART adverse events. eGFR was calculated using MDRD and CKD-EPI formulas based on age, gender, race, and serum creatinine.^21,22 There were no subjects with acute renal failure included in the study.

Measured values were expressed as means and standard deviations (±SD). The nonparametric Mann–Whitney U-test and the paired t-test were performed to find any significant differences in eGFR arrived by the MDRD and CKD-EPI equations between the studied groups. For correlation analyses, the Spearmann nonparametric correlation was used. A p value <0.05 was considered significant. Statistical analyses were performed with Statistica 8.0 for Windows software (Statsoft Inc., Tulsa, OK).

Results

As shown in Table 1, the mean eGFR obtained by the CKD-EPI formula was significantly lower than the mean eGFR calculated by the MDRD formula in the total studied HIV-infected population. Moreover, the same trend was observed in males, antiretroviral (ARV)-naive subjects, as well as in persons with eGFR >60 ml/min/1.73 m². When we divided patients according to their cART status, we found no difference in eGFR measured by the two equations between the male and female groups among ARV-treated subjects. However, in ARV-naive patients, a significant decrease in eGFR measured by the CKD-EPI equation was observed in the male group (Table 2).

Table 1.

Differences in eGFR Arrived by the MDRD and CKD-EPI Equation in Total Studied Population and in Selected Subgroups (Mean ± SD)

	eGFR by MDRD (ml/min/1.73 m ² )	eGFR by CKD-EPI (ml/min/1.73 m ² )	Difference in eGFR ^a	p values
Total population, n = 1520^b	96.33 ± 46.97	92.97 ± 28.98	−3.36 ± 17.99	0.02^c
Males, n = 1282	96.13 ± 47.35	92.15 ± 29.50	−3.99 ± 17.85	0.01^c
Females, n = 238	97.40 ± 44.94	97.42 ± 25.62	0.02 ± 19.32	0.1
ARV-naive subjects, n = 499	107.12 ± 58.94	99.71 ± 31.65	−7.41 ± 27.29	0.01^c
ARV-treated subjects, n = 1021	91.06 ± 38.78	89.68 ± 26.99	−1.38 ± 11.79	0.3
eGFR >60 ml/min/1.73 m², n = 1322^d	104.85 ± 44.14	100.91 ± 21.16	−3.95 ± 22.98	0.003^c
eGFR <60 ml/min/1.73 m², n = 198^d	39.43 ± 14.31	40.00 ± 15.18	0.58 ± 0.87	0.7

The difference in eGFR is CKD-EPI minus MDRD.

n, number of total serum creatinine measurements during the observation period.

Statistically significant.

By the MDRD equation.

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

Table 2.

Differences in eGFR Arrived by the MDRD and CKD-EPI Equation Depending on Cart Status and Gender (Mean ± SD)

	eGFR by MDRD (ml/min/1.73 m ² )	eGFR by CKD-EPI (ml/min/1.73 m ² )	Difference in eGFR ^a	p values
ARV-naive males, n = 433^b	108.35 ± 59.17	99.90 ± 32.88	−8.45 ± 26.29	0.009^c
ARV-naive females, n = 66	99.04 ± 57.22	98.47 ± 22.05	−0.57 ± 35.17	0.9
ARV-treated males, n = 807	89.09 ± 38.79	87.53 ± 26.90	−1.56 ± 11.89	0.3
ARV-treated females, n = 165	96.60 ± 40.07	96.65 ± 27.29	0.05 ± 12.78	0.9

The difference in eGFR is CKD-EPI minus MDRD.

n, number of total serum creatinine measurements during the observation period.

Statistically significant.

A similar comparison was made between patients with well-preserved renal function (eGFR >60 ml/min/1.73 m²) and those with eGFR <60 ml/min/1.73 m². The only significant difference between the two studied equations was observed in the male group with well-preserved renal function (Table 3). Additionally, when we compared all results from studied males and females, the mean eGFR measured by the CKD-EPI equation was significantly lower in males then in females (92.15 ± 29.50 vs. 97.42 ± 25.62 ml/min/1.73 m², respectively; p < 0.001). However, no difference was found in the mean eGFR measured by the MDRD equation (96.13 ± 47.35 ml/min/1.73 m² in males vs. 97.40 ± 44.94 ml/min/1.73 m² in females; p = 0.5). Therefore, after analyzing all obtained results, the greatest discrepancy in eGFR measured by the MDRD and CKD-EPI formulas was seen in ARV-naive men with well-preserved kidney function (118.84 ± 54.82 ml/min/1.73 m² for MDRD vs. 109.20 ± 21.04 ml/min/1.73 m² for CKD-EPI, p = 0.001).

Table 3.

Differences in eGFR Arrived by the MDRD and CKD-EPI Equation Depending on Well-Preserved or Decreased Kidney Function and Gender (Mean ± SD)

	eGFR by MDRD (ml/min/1.73 m ² )	eGFR by CKD-EPI (ml/min/1.73 m ² )	Difference in eGFR ^a	p values
Males, eGFR >60 ml/min/1.73 m², n = 1108^b,c	105.03 ± 44.42	100.36 ± 21.62	−4.66 ± 22.80	0.001^d
Females, eGFR >60 ml/min/1.73 m², n = 214^b	103.61 ± 42.94	103.36 ± 18.88	−0.25 ± 24.06	0.9
Males, eGFR <60 ml/min/1.73 m², n = 172^b	38.92 ± 14.47	39.24 ± 15.25	0.31 ± 0.78	0.8
Females, eGFR <60 ml/min/1.73 m², n = 24^b	41.98 ± 13.17	44.43 ± 14.25	2.45 ± 1.08	0.5

The difference in eGFR is CKD-EPI minus MDRD.

By the MDRD equation.

n, number of total serum creatinine measurements during the observation period.

Statistically significant.

Independently of the equation used, a significant decrease in eGFR was seen in ARV-treated in comparison to ARV-untreated HIV-1-infected patients (107.12 ± 58.94 vs. 91.06 ± 38.78 ml/min/1.73 m² by MDRD, p < 0.001, and 99.71 ± 31.65 vs. 89.68 ± 27.0 ml/min/1.73 m² by CKD-EPI, p < 0.001). The same trend was observed in untreated and treated men (108.35 ± 59.17 vs. 89.02 ± 38.79 ml/min/1.73 m² by MDRD, p < 0.001, and 99.90 ± 32.88 vs. 87.53 ± 26.90 ml/min/1.73 m² by CKD-EPI, p < 0.001). On the contrary, there was no significant difference in eGFR in treated and untreated women (99.04 ± 57.22 vs. 96.60 ± 40.07 ml/min/1.73 m² by MDRD, p = 0.8, and 98.47 ± 22.05 vs. 96.65 ± 27.29 ml/min/1.73 m² by CKD-EPI, p = 0.9). The range of HIV viral load (VL) was from undetectable to 3,850,000 copies/ml in naive and from undetectable to 528,000 copies/ml in ARV-treated subjects, respectively. No correlation was found between HIV VL and eGFR in treated (r = 0.13, p = 0.3 for MDRD and r = 0.12, p = 0.4 for CKD-EPI) and untreated subjects (r = 0.30, p = 0.3 for MDRD and r = 0.30, p = 0.3 for CKD-EPI). The HIV VL was also stratified by gender: the mean VL in males was 37,346 copies/ml and in females was 428,529 copies/ml. Similarly to the cART status, no correlation was found between HIV VL and eGFR in males (r = 0.26, p = 0.07 for MDRD and r = 0.25, p = 0.07 for CKD-EPI) and females (r = 0.30, p = 0.43 for MDRD and r = 0.20, p = 0.6 for CKD-EPI). However, we found a significant negative correlation between mean difference in eGFR measured by the MDRD and CKD-EPI equation and the age of the studied subjects (r = −0.37, p < 0.001).

Discussion

This study is the first to examine the usefulness of the new CKD-EPI equation in an HIV-1-infected population. In all HIV-1-infected patients studied, eGFR measured by the CKD-EPI formula was significantly lower in comparison to the MDRD formula. Moreover, a similar difference was observed in males and in subjects with well-preserved renal function. There was no discrepancy in the eGFR measured by the two methods in populations with eGFR <60 ml/min/1.73 m². These data are in accordance with the Levey et al. study, which emphasized the usefulness of the CKD-EPI equation in persons with estimated GFR >60 ml/min/1.73 m².⁸ According to our data, we believe that the MDRD equation largely used in clinical practice may miscalculate GFR in HIV-infected patients with minimal renal dysfunction, especially in men, as has already been presented in the nonimmunocompromised population.^23,24 No difference was observed between eGFR obtained by the two studied methods in HIV-1-infected females, which contradicts the data shown by Montañés Bermúdez et al.⁹

We also compared eGFR measured by the MDRD and CKD-EPI equation in ARV-treated and ARV-untreated populations and GFR status. As a result, the greatest discrepancy in eGFR measured by the MDRD and CKD-EPI formulas was seen in ARV-naive men with well-preserved kidney function. No significant difference between the CKD-EPI and MDRD formula among HIV-infected males and females has been shown in the current literature. There may be several possible explanations for this situation. First, our male population was larger then the female group and therefore may have the power to establish the difference between equations. Second, men often started cART at more advanced stages of AIDS than women. Finally, it is possible that some genetic factors linked with chromosome X may play a protective role in renal function. Nevertheless, the role of variations in gene loci in renal diseases is still an issue that probably warrants further examination.

Although the first studies concerning HIV-related kidney diseases have shown the beneficial role of cART on improvements in renal function over time, recent published analyses present contradictory results.^4,25,26 In our study, independent of the equation used, a significant decrease in eGFR was seen in treated versus untreated HIV-infected patients. However, because of short follow-up time this decline in GFR over time is controversial. It is possible that calculated GFR accommodates the aging process and will result in a natural and expected age-related decline in GFR. Therefore, more studies among treated and untreated HIV-infected patients should be considered to confirm no influence of cART on renal function in this group of patients.

Recently it has been shown that duration of HIV infection, viral and immunological failure, as well as use of protease inhibitors are related to an increased risk of renal impairment in HIV-1-infected patients.²⁷ However, in our study, no correlation was found between HIV viral load and eGFR as well as in mean difference in eGFR obtained by the two formulas in treated and untreated subjects. Nevertheless, our results need further confirmation in larger groups because we obtained the VL of 21% of the studied population. As a result, our group was not as large, which likely significantly diminished its power.

In our study, only seven patients were black. Because they consisted of only 2.4% of the population studied, their eGFR results were added to the results of white patients. It has already been shown that the CKD-EPI equation seems to be more accurate then the MDRD equation in the eGFR assessment in African, Asian, and Indian populations.^17
–19 However, our population was too small to assess such difference between races.

Overall, the greatest weakness of our analysis was the ratio discrepancy between the studied groups. HIV-infected, ARV-naive males were the largest group and therefore had the power to establish the difference between equations. The other groups were not as large and this likely significantly diminished their power, relative to the male group with well-preserved kidney function. Therefore, the failure to find differences cannot truly be interpreted to indicate that they do not exist, and this needs to be confirmed in more numerically coherent populations.

In conclusion, the importance of our study is that there are still no data concerning the usefullness of the new CKD-EPI formula in HIV-infected patients. We found that in HIV-1-infected subjects, especially in ARV-naive men with well-preserved kidney function, eGFR measured by MDRD and CKD-EPI formulas varies strongly based on the method used. Such discrepancies may be important in everyday clinical practice and must be confirmed and explained by additional studies using GFR measured with a reference method such as the clearance of exogenous filtration markers.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

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