MDRD vs. CKD-EPI in comparison to 51Chromium EDTA: a cross sectional study of Malaysian CKD cohort

Maisarah Jalalonmuhali, Soo Kun Lim, Mohammad Nazri Md Shah, Kok Peng Ng, Maisarah Jalalonmuhali, Soo Kun Lim, Mohammad Nazri Md Shah, Kok Peng Ng

Abstract

Background: Accurate measurement of renal function is important: however, radiolabelled gold standard measurement of GFR is highly expensive and can only be used on a very limited scale. We aim to compare the performance of Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equations in the multi-ethnic population attending University Malaya Medical Centre (UMMC).

Methods: This is a cross-sectional study recruiting patients, who attend UMMC Nephrology clinics on voluntary basis. 51-Chromium EDTA (51Cr-EDTA) plasma level was used to measure the reference GFR. The serum creatinine was determined by IDMS reference modified Jaffe kinetic assay (CrJaffe). The predictive capabilities of MDRD and CKD-EPI based equations were calculated. Data was analysed using SPSS version 20 and correlation, bias, precision and accuracy were determined.

Results: A total of 113 subjects with mean age of 58.12 ± 14.76 years and BMI of 25.99 ± 4.29 kg/m2 were recruited. The mean reference GFR was 66.98 ± 40.65 ml/min/1.73m2, while the estimated GFR based on MDRD and CKD-EPI formula were 62.17 ± 40.40, and 60.44 ± 34.59, respectively. Both MDRD and CKD-EPI were well-correlated with reference GFR (0.806 and 0.867 respectively) and statistically significant with p < 0.001. In the overall cohort, although MDRD had smaller bias than CKD-EPI (4.81 vs. 6.54), CKD-EPI was more precise (25.22 vs. 20.29) with higher accuracy within 30% of measured GFR (79.65 vs. 86.73%).

Conclusion: The CKD-EPI equation appeared to be more precise and accurate than the MDRD equation in estimating GFR in our cohort of multi-ethnic populations in Malaysia.

Keywords: CKD-EPI; Comparison; Glomerular filtration rate; MDRD.

Conflict of interest statement

Ethics approval and consent to participate

The study was approved by the University Malaya Medical Centre Medical Ethics Committee (UMEC) (IRB reference number 823.5) in accordance with the Helsinki Declaration. Participation in this study was on voluntary basis and a written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Bland and Altman analysis of GFR estimates. In this analysis, the differences between estimated and measured GFR are plotted against the average of the estimated and measured GFR for each individual patient. 1a. MDRD equation and measured GFR. 1b. CKD-EPI equation and measured GFR

References

    1. BL Goh and LM Ong (Eds). Twenty second Report of the Malaysian Dialysis and Transplant 2014, Kuala Lumpur 2015.
    1. United States Renal Data System. 2016 USRDS annual data report: Epidemiology of kidney disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2016.
    1. National Kidney Foundation K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis. 2002;39(2):S1–266. doi: 10.1016/S0272-6386(02)70081-4.
    1. Hilson AJW, Mistry RD, Maisey MN. Tc-99m-DTPA for the measurement of glomerular filtration rate. Brit J Radiol. 1976;49:794–796. doi: 10.1259/0007-1285-49-585-794.
    1. Fleming JS, Wilkinson J, Oliver RM, Ackery DM, Blake GM, Waller DG. Comparison of radionuclide estimation of glomerular filtration rate using tectnetium99m diethylene-triaminepentaacetic acid and chromium 51 ethylenediamine-tetraacetic acid. Eur J Nucl Med. 1991;18:391–395. doi: 10.1007/BF02258429.
    1. Poggio ED, Wang X, Greene T, Van Lente F, Hall PM. Performance of the modification of diet in renal disease and Cockcroft-gault equations in the estimation of GFR in health and in chronic kidney disease. J Am Soc Nephrol. 2005;16:459–466. doi: 10.1681/ASN.2004060447.
    1. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–612. doi: 10.7326/0003-4819-150-9-200905050-00006.
    1. Levey AS, Adler S, Caggiula AW, England BK, Greene T, Hunsicker LG, et al. Effects of dietary protein restriction on the progression of advanced renal disease in the modification of diet in renal disease study. Am J Kidney Dis. 1996;27(5):652–663. doi: 10.1016/S0272-6386(96)90099-2.
    1. Stevens LA, Coresh J, Deysher AE, Feldman HI, Lash JP, Nelson R, et al. Evaluation of the MDRD study equation in a large diverse population. J Am Soc Nephrol. 2007;18(10):2749–2757. doi: 10.1681/ASN.2007020199.
    1. Imai E, Horio M, Nitta K, Yamagata K, Iseki K, Hara S, et al. Estimation of glomerular filtration rate by the MDRD study equation modified for Japanese patients with chronic kidney disease. Clin Exp Nephrol. 2007;11(1):41–50. doi: 10.1007/s10157-006-0453-4.
    1. Zuo L, Ma YC, Zhou YH, Wang M, GB X, Wang HY. Application of GFR-estimating equations in Chinese patients with chronic kidney disease. Am J Kidney Dis. 2005;45(3):463–472. doi: 10.1053/j.ajkd.2004.11.012.
    1. Ma YC, Zuo L, Chen JH, Luo Q, XQ Y, Li Y, et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol. 2006;17(10):2937–2944. doi: 10.1681/ASN.2006040368.
    1. Juutilainen A, Kastarinen H, Antikainen R, Peltonen M, Salomaa V, Tuomilehto J, et al. Comparison of the MDRD study and the CKD-EPI study equations in evaluating trends of estimated kidney function at population level: findings from the national FINRISK study. Nephrol Dial Transplant. 2012;8(27):3210–3217. doi: 10.1093/ndt/gfs047.
    1. Du Bois D, Du Bois EFA. Formula to estimate the approximate surface area if height and weight be known. Arch Intern Med. 1916;17(6):863–871. doi: 10.1001/archinte.1916.00080130010002.
    1. Bröchner-Mortensen JA. Simple method for the determination of glomerular filtration rate. Scand J Clin Lab Invest. 1972;30:271–274. doi: 10.3109/00365517209084290.
    1. Burtis CA, Ashwood ER. Tietz fundamentals of clinical chemistry, 5th ed. Philadelphia: WB Saunders. 2001;23-25:419–420.
    1. Stevens LA, Zhang Y, Schmid CH. Evaluating the performance of GFR estimating equations. J Nephrol. 2008;21(6):797–807.
    1. Stevens LA, Schmid CH, Greene T, Zhang Y, Beck GJ, Froissart M. . Comparative performance of the CKD epidemiology collaboration (CKD-EPI) and the modification of diet in renal disease (MDRD) study equations for estimating GFR levels above 60 ml/min/1.73m2. Am J Kidney Dis. 2010;56(3):486–495. doi: 10.1053/j.ajkd.2010.03.026.
    1. Greer RC, Powe NR, Jaar BG, Troll MU, Boulware LE. Effect of primary care physicians’ use of estimated glomerular filtration rate on the timing of their subspecialty referral decisions. BMC Nephrol. 2011; 10.1186/1471-2369-12-1.
    1. Mulay AV, Gokhale SM. Comparison of serum creatinine-based estimating equations with gates protocol for predicting glomerular filtration rate in Indian population. Indian J Nephrol. 2017;27(2):124–128. doi: 10.4103/0971-4065.200515.
    1. Jeong TD, Lee W, Chun S, Lee SK, Ryu JS, Min WK, et al. Comparison of the MDRD study and CKD-EPI equations for the estimation of the glomerular filtration rate in the Korean general population: the fifth Korea National Health and nutrition examination survey (KNHANES V-1), 2010. Kidney Blood Press Res. 2013;37:443–450. doi: 10.1159/000355724.
    1. Jessani S, Levey AS, Bux R, Inker LA, Islam M, Chaturvedi N, et al. Estimation of GFR in south Asians: a study from the general population in Pakistan. Am J Kidney Dis. 2014;63:49–58. doi: 10.1053/j.ajkd.2013.07.023.

Source: PubMed

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