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Evaluation of methods based on creatinine and cystatin C to estimate glomerular filtration rate in chronic kidney disease

  • Nephrology - Original Paper
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Abstract

Purpose

Estimated glomerular filtration rate (GFR) is a useful tool for the detection of chronic kidney disease (CKD). Several methods have been proposed, but findings can vary in specific groups such as patients with diabetes, elderly and high and low body mass index and, also, with the stage of CKD. The objective of this study was comparing the accuracy of the currently used equations for estimating GFR with that of the gold standard technetium-(99m)-diethylene triamine pentaacetic acid (99mTc-DTPA).

Methods

We performed a cross-sectional study of 129 patients with all five CKD stages. GFR was estimated using the following: 24-h urine creatinine clearance, Cockcroft–Gault equation, MDRD equation, CKD-EPI equation, Hoek’s cystatin C equation, and isotopic 99mTc-DTPA (as gold standard). We evaluated agreement in the whole study population and according to age, sex, weight, and diabetes.

Results

All methods had good agreement. The best agreement was observed with the cystatin C [intraclass coefficient correlation (ICC) 95 % confidence interval (95 % CI), 0.87 (0.82–0.91)], followed by CKD-EPI [ICC 0.83 (0.77–0.88)]. Twenty-four-hour urine creatinine clearance showed the worst agreement in patients older than 65 years [ICC 0.70 (0.56–0.79)]. The Cockcroft–Gault equation showed the worst agreement in younger than 65 years [ICC 0.64 (0.42–0.79)]. The best agreement for classification in the correct CKD stage was with the cystatin C equation [κ = 0.80 (0.74–0.87)]. GFR was overestimated with all methods in CKD stages 4 and 5.

Conclusions

The methods used in clinical practice are adequate for classification of CKD. Cystatin C is the most accurate method, followed by CKD-EPI. The Cockcroft–Gault equation is not accurate in young patients. Twenty-four-hour urine creatinine clearance loses accuracy in patients aged older than 65 years.

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References

  1. Steintz K, Türkand H (1940) The determination of the glomerular filtration by the endogenous creatinine clearance. J Clin Invest 19:285–298

    Article  Google Scholar 

  2. Shannon JA (1935) The renal excretion of creatinine in man. J Clin Invest 14:403–410

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. White SL, Polkinghorne KR, Atkins RC, Chadban SJ (2010) Comparison of the prevalence and mortality risk of CKD in Australia using the CKD epidemiology collaboration (CKD-EPI) and modification of diet in renal disease study GFR estimating equations: the AusDiab (Australian diabetes obesity and lifestyle study). Am J Kidney Dis 55:660–670

    Article  PubMed  Google Scholar 

  4. Hojs R, Bevc S, Ekart R, Gorenjak M, Puklavec L (2008) Serum cystatin C-based equation compared to serum creatinine-based equations for estimation of glomerular filtration rate in patients with chronic kidney disease. Clin Nephrol 70:10–17

    Article  CAS  PubMed  Google Scholar 

  5. Jonsson AS, Flodin M, Hansson LO, Larsson A (2007) Estimated glomerular filtration rate (eGFRCystC) from serum cystatin C shows strong agreement with iohexol clearance in patients with low GFR. Scand J Clin Lab Invest 67:801–809

    Article  CAS  PubMed  Google Scholar 

  6. Petersen LJ, Petersen JR, Talleruphuus U, Moller ML, Ladefoged SD, Mehlsen J, Jensen HA (1999) Glomerular filtration rate estimated from the uptake phase of 99 m Tc- DTPA renography in chronic renal failure. Nephrol Dial Transplant 14:1673–1678

    Article  CAS  PubMed  Google Scholar 

  7. Fleiss JL (1986) The design and analysis of clinical experiments. Wiley, New York

    Google Scholar 

  8. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    Article  CAS  PubMed  Google Scholar 

  9. de Ullibarri Galparsoro López, Pita Fernández S (1999) Medidas de concordancia: el índice de Kappa. Cad Aten Primaria 6:169–171

    Google Scholar 

  10. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Article  CAS  PubMed  Google Scholar 

  11. Michels WM, Grootendorst K, Verduijn M, Elliot EG, Dekker FW, Krediet RT (2010) Performance of the Cockcroft-Gault, MDRD, and new CKD-EPI formulas in relation to GFR, age and body size. Clin J Am Soc Nephrol 5:1003–1009

    Article  PubMed Central  PubMed  Google Scholar 

  12. Barbour GL, Crumb CK, Boyd CM, Reeves RD, Rastogi SP, Patterson RM (1976) Comparison of inulin, iothalamate, and 99 mTc-DTPA for measurement of glomerular filtration rate. J Nucl Med 17:317–320

    CAS  PubMed  Google Scholar 

  13. Russell CD, Bischoff PG, Rowell KL, Kontzen F, Lloyd LK, Tauxe WN et al (1983) Quality control of Tc-99m DTPA for measurement of glomerular filtration: concise communication. J Nucl Med 24:722–727

    CAS  PubMed  Google Scholar 

  14. Bevc S, Hojs R, Ekart R, Gorenjak M, Puklavec L (2001) Simple cystatin C formula compared to sophisticated CKD-EPI formulas for estimation of glomerular filtration rate in the elderly. Ther Apher Dial 15:261–268

    Article  Google Scholar 

  15. Delanaye P, Pieroni L, Abschoff C, Lutteri L, Chapelle JP, Krzesinski JM et al (2008) Analytical study of three cystatin C assays and their impact on cystatin C-based GFR-prediction equations. Clin Chim Acta 398:118–124

    Article  CAS  PubMed  Google Scholar 

  16. Eriksen BO, Mathisen UD, Melson T, Ingebretsen OC, Jenssen TG, Njolstad I et al (2010) Cystatin C is not a better estimation of GFR than creatinine in the general population. Kidney Int 78:1305–1311

    Article  CAS  PubMed  Google Scholar 

  17. Shlipak MG, Matsushita K, Ärnlöv J, Inker LA, Katz R, Polkinghorne KR et al (2013) Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med 5(369):932–943

    Article  Google Scholar 

  18. Sun J, Jiang T, Zeng Z, Chen P (2010) Performance evaluation of a particle-enhanced turbidimetric cystatin c assay using the Abbot Aeroset analyser and assessment of cystatin C based equations for estimating glomerular filtration rate in chronic kidney disease. Nephrol Dial Transplant 25:1489–1496

    Article  CAS  PubMed  Google Scholar 

  19. Pucci L, Triscornia S, Lucchesi D, Fotino C, Pellegrini G, Pardini E et al (2007) Cystatin C and estimates of renal function: searching for a better measure of kidney function in diabetic patients. Clin Chem 53:480–488

    Article  CAS  PubMed  Google Scholar 

  20. Obermüller N, Geiger H, Weipert C, Urbschat A (2013) Current developments in early diagnosis of acute kidney injury. Int Urol Nephrol. (Epub ahead of print)

  21. Svensson AS, Kovesdy CP, Kvitting JP, Rosén M, Cederholm I, Szabó Z et al (2013) Comparison of serum cystatin C and creatinine changes after cardiopulmonary bypass in patients with normal preoperative kidney function. Int Urol Nephrol. (Epub ahead of print)

  22. Abouchacra S, Chaaban A, Hakim R, Gebran N, El-Jack H, Rashid F et al (2012) Renal biomarkers for assessment of kidney function in renal transplant recipients: how do they compare? Int Urol Nephrol 44:1871–1876

    Article  CAS  PubMed  Google Scholar 

  23. Macisaac RJ, Tsalamandris C, Thomas MC, Premaratne E, Panagiotopoulos S, Smith TJ et al (2007) The accuracy of cystatin C and commonly used creatinine-based methods for detecting moderate and mild chronic kidney disease in diabetes. Diabetes Med 24:443–448

    Article  CAS  Google Scholar 

  24. Jonsson AS, Flodin M, Hansson LO, Larsson A (2007) Estimated glomerular filtration rate (eGFRCystC) from serum cystatin C shows strong agreement with iohexol clearance in patients with low GFR. Scand J Clin Lab Invest 67:801–809

    Article  CAS  PubMed  Google Scholar 

  25. Trimarchi H, Muryan A, Martino D, Toscano A, Iriarte R, Campolo-Girard V et al (2012) Creatinine-vs. cystatin C-based equations compared with 99mTcDTPA scintigraphy to assess glomerular filtration rate in chronic kidney disease. J Nephrol 25:1003–1015

    Article  CAS  PubMed  Google Scholar 

  26. Delanaye P, Cavalier E, Mariat C, Maillard N, Krzesinki JM (2010) MDRD or CKD-EPI study equations for estimating prevalence of stage 3 CKD in epidemiological studies: which difference? Is this difference relevant? BMC Nephrology 1(11):8

    Article  Google Scholar 

  27. Sit D, Basturk T, Yildirim S, Karagoz F, Bozkurt N, Gunes A (2013) Evaluation of the serum cystatin C values in prediction of indications for hemodialysis in patients with chronic renal failure. Int Urol Nephrol. (Epub ahead of print)

  28. Pei X, Liu Q, He J, Bao L, Yan C, Wu J et al (2012) Are cystatin C-based equations superior to creatinine-based equations for estimating GFR in Chinese elderly population? Int Urol Nephrol 44:1877–1884

    Article  CAS  PubMed  Google Scholar 

  29. Stevens LA, Claybon MA, Schmid CH, Chen J, Horio M, Imai E et al (2011) Evaluation of the chronic kidney disease epidemiology collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney Int 79:555–562

    Article  PubMed  Google Scholar 

  30. Nyman U, Grubb A, Sterner G, Bjork J (2011) The CKD-EPI and MDRD equations to estimate GFR. Validation in the Swedish Lund-Malmö Study cohort. Scand J Clin Lab Invest 71:129–138

    PubMed  Google Scholar 

  31. Rognant N, Lemoine S, Laville M, Hadj-Aissa A, Dubourg L (2011) Performance of the chronic kidney disease epidemiology collaboration equation to estimate glomerular filtration rate in diabetic patients. Diabetes Care 34:1320–1322

    Article  PubMed Central  PubMed  Google Scholar 

  32. Stevens LA, Padala S, Levey AS (2010) Advances in glomerular filtration rate estimating equations. Curr Opin Nephrol Hypertens 19:298–307

    Article  PubMed Central  PubMed  Google Scholar 

  33. Goldberg TH, Finkelstein MS (1987) Difficulties in estimating glomerular filtration rate in the elderly. Arch Int Med 147:1430–1433

    Article  CAS  Google Scholar 

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Correspondence to Borja Quiroga.

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Vega, A., García de Vinuesa, S., Goicoechea, M. et al. Evaluation of methods based on creatinine and cystatin C to estimate glomerular filtration rate in chronic kidney disease. Int Urol Nephrol 46, 1161–1167 (2014). https://doi.org/10.1007/s11255-013-0607-8

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  • DOI: https://doi.org/10.1007/s11255-013-0607-8

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