Abstract
Background: The recently established international cystatin C calibrator makes it possible to develop non-laboratory specific glomerular filtration rate (GFR) estimating (eGFR) equations. This study compares the performance of the arithmetic mean of the revised Lund-Malmö creatinine and CAPA cystatin C equations (MEANLM-REV+CAPA), the arithmetic mean of the Chronic Kidney Disease Epidemiology Collaboration equation (CKD-EPI) creatinine and cystatin C equations (MEANCKD-EPI), and the composite CKD-EPI equation (CKD-EPICREA+CYSC) with the corresponding single marker equations using internationally standardized calibrators for both cystatin C and creatinine.
Methods: The study included 1200 examinations in 1112 adult Swedish patients referred for measurement of GFR (mGFR) 2008–2010 by plasma clearance of iohexol (median 51 mL/min/1.73 m2). Bias, precision (interquartile range, IQR) and accuracy (percentage of estimates ±30% of mGFR; P30) were compared.
Results: Combined marker equations were unbiased and had higher precision and accuracy than single marker equations. Overall results of MEANLM-REV+CAPA/MEANCKD-EPI/CKD-EPICREA+CYSC were: median bias –2.2%/–0.5%/–1.6%, IQR 9.2/9.2/8.8 mL/min/1.73 m2, and P30 91.3%/91.0%/91.1%. The P30 figures were about 7–14 percentage points higher than the single marker equations. The combined equations also had a more stable performance across mGFR, age and BMI intervals, generally with P30 ≥90% and never <80%. Combined equations reached P30 of 95% when the difference between eGFRCREA and eGFRCYSC was <10% but decreased to 82% at a difference of ≥40%.
Conclusions: Combining cystatin C and creatinine assays improves GFR estimations with P30 ≥90% in adults. Reporting estimates of both single and combined marker equations in clinical settings makes it possible to assess the validity of the combined equation based on the agreement between the single marker equations.
Acknowledgments
Librarian Elisabeth Sassersson for excellent service regarding literature references.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Financial support: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
Appendix
Calculation of iohexol clearance (=measured GFR)
GFR was calculated from the iohexol concentration with corrections for lack of complete uniform distribution and non-immediate mixing and using Bröchner-Mortensen’s correction [15] to achieve results corresponding to multi-compartment kinetics of iohexol. Initial GFR was calculated as follows:
where t=time interval between injection and sampling (min). ln=natural logarithm. Qtot=injected amount of iohexol (mg). Ct=iohexol concentration (mg/mL) at time (t) after injection and V=distribution volume (mL) calculated as a function of body weight (kilogram) [44]:
To correct for lack of complete uniform distribution of iohexol the correction factor (m) for distribution volume was calculated [20]:
The corrected distribution volume (V*=V/m) was used calculate the final GFR:
Body surface area equation of DuBois and DuBois [21].
Equations for estimating GFR
In all GFR estimating equations below plasma (serum) creatinine (pCr) is expressed in μmol/L (to convert pCr from μmol/L to mg/dL, divide by 88.4), cystatin C (pCysC) in mg/L, age in years and estimated GFR in mL/min/1.73 m2 body surface area. ln=natural logarithm.
The revised Lund-Malmö creatinine equation (LM-REVCREA) [1]
The final CAPA cystatin C equation (CAPACYSC) [13]
CKD-EPI creatinine equation for Caucasians (CKD-EPICREA) [2]
CKD-EPI cystatin C equation (CKD-EPICYSC) [12]
CKD-EPI creatinine-cystatin C equation for Caucasians (CKD-EPICREA+CYSC) [12]
References
1. Björk J, Grubb A, Sterner G, Nyman U. Revised equations for estimating glomerular filtration rate based on the Lund-Malmö Study cohort. Scand J Clin Lab Invest 2011;71:232–9.10.3109/00365513.2011.557086Search in Google Scholar PubMed
2. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–12.10.7326/0003-4819-150-9-200905050-00006Search in Google Scholar PubMed PubMed Central
3. Björk J, Jones I, Nyman U, Sjöström P. Validation of the Lund-Malmö, Chronic Kidney Disease Epidemiology (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations to estimate glomerular filtration rate in a large Swedish clinical population. Scand J Urol Nephrol 2012;46:212–22.10.3109/00365599.2011.644859Search in Google Scholar PubMed
4. Swedish Council on Health Technology Assessment. Estimation of renal function. SBU Report 214, 2012. Available from: http://www.sbu.se/214. Accessed July 31, 2014.Search in Google Scholar
5. Nyman U, Grubb A, Larsson A, Hansson LO, Flodin M, Nordin G, et al. The revised Lund-Malmo GFR estimating equation outperforms MDRD and CKD-EPI across GFR, age and BMI intervals in a large Swedish population. Clin Chem Lab Med 2014;52:815–24.10.1515/cclm-2013-0741Search in Google Scholar PubMed
6. Tidman M, Sjöström P, Jones I. A Comparison of GFR estimating formulae based upon s-cystatin C and s-creatinine and a combination of the two. Nephrol Dial Transplant 2008;23:154–60.10.1093/ndt/gfm661Search in Google Scholar PubMed
7. Nyman U, Grubb A, Sterner G, Björk J. Different equations to combine creatinine and cystatin C to predict GFR. Arithmetic mean of existing equations performs as well as complex combinations. Scand J Clin Lab Invest 2009;69:619–27.10.1080/00365510902946992Search in Google Scholar PubMed
8. Stevens LA, Coresh J, Schmid CH, Feldman HI, Froissart M, Kusek J, et al. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. Am J Kidney Dis 2008;51:395–406.10.1053/j.ajkd.2007.11.018Search in Google Scholar PubMed PubMed Central
9. Blirup-Jensen S, Grubb A, Lindstrom V, Schmidt C, Althaus H. Standardization of Cystatin C: development of primary and secondary reference preparations. Scand J Clin Lab Invest Suppl 2008;241:67–70.10.1080/00365510802150067Search in Google Scholar PubMed
10. Grubb A, Blirup-Jensen S, Lindstrom V, Schmidt C, Althaus H, Zegers I. First certified reference material for cystatin C in human serum ERM-DA471/IFCC. Clin Chem Lab Med 2010;48:1619–21.10.1515/CCLM.2010.318Search in Google Scholar PubMed
11. Zegers I, Auclair G, Schimmel H, Emons H, Blirup-Jensen S, Schmidt C, et al. Certification of cystatin C in the human serum reference material ERM-DA471/IFFCC. European Commission, Joint Research Centre, Institute for Reference Materials and Measurements, EUR 24408 EN, European Communities, Luxembourg. 2010. Available from: https://irmm.jrc.ec.europa.eu/refmat_pdf/ERM-DA471_report.pdf. Accessed July 31, 2014.Search in Google Scholar
12. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012;367:20–9.10.1056/NEJMoa1114248Search in Google Scholar PubMed PubMed Central
13. Grubb A, Horio M, Hansson LO, Björk J, Nyman U, Flodin M, et al. Generation of a new cystatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibrator. Clin Chem 2014;60:974–86.10.1373/clinchem.2013.220707Search in Google Scholar PubMed
14. Bäck SE, Krutzen E, Nilsson-Ehle P. Contrast media as markers for glomerular filtration: a pharmacokinetic comparison of four agents. Scand J Clin Lab Invest 1988;48:247–53.10.3109/00365518809167491Search in Google Scholar PubMed
15. Bröchner-Mortensen J. A simple method for the determination of glomerular filtration rate. Scand J Clin Lab Invest 1972;30:271–4.10.3109/00365517209084290Search in Google Scholar PubMed
16. Bird NJ, Peters C, Michell AR, Peters AM. Comparison of GFR measurements assessed from single versus multiple samples. Am J Kidney Dis 2009;54:278–88.10.1053/j.ajkd.2009.03.026Search in Google Scholar PubMed
17. Nilsson-Ehle P. Iohexol clearance for the determination of glomerular filtration rate: 15 years’ experience in clinical practice. eJIFCC 2002;13. Available from: http://www.ifcc.org/ifccfiles/docs/130201005.pdf. Accessed July 31, 2014.Search in Google Scholar
18. Sterner G, Frennby B, Hultberg B, Almen T. Iohexol clearance for GFR-determination in renal failure – single or multiple plasma sampling? Nephrol Dial Transplant 1996;11:521–5.10.1093/ndt/11.3.521Search in Google Scholar
19. Krutzen E, Back SE, Nilsson-Ehle I, Nilsson-Ehle P. Plasma clearance of a new contrast agent, iohexol: a method for the assessment of glomerular filtration rate. J Lab Clin Med 1984;104:955–61.Search in Google Scholar
20. Jacobsson L. A method for the calculation of renal clearance based on a single plasma sample. Clin Physiol 1983;3: 297–305.10.1111/j.1475-097X.1983.tb00712.xSearch in Google Scholar PubMed
21. DuBois D, DuBois E. A formula to estimate the approximate surface area if height and weight be known. Arch Intern Med 1916;17:863–71.10.1001/archinte.1916.00080130010002Search in Google Scholar
22. Stevens LA, Zhang Y, Schmid CH. Evaluating the performance of equations for estimating glomerular filtration rate. J Nephrol 2008;21:797–807.Search in Google Scholar
23. Spinler SA, Nawarskas JJ, Boyce EG, Connors JE, Charland SL, Goldfarb S. Predictive performance of ten equations for estimating creatinine clearance in cardiac patients. Iohexol Cooperative Study Group. Ann Pharmacother 1998;32:1275–83.10.1345/aph.18122Search in Google Scholar PubMed
24. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Part 5. Evaluation of laboratory measurements for clinical assessment of kidney disease. Guideline 4. Estimation of GFR. Am J Kidney Dis 2002;39:S76–92.10.1053/ajkd.2002.30944Search in Google Scholar
25. Efron B, Tibshirani RJ. An introduction to the bootstrap. New York: Chapman and Hall, 1993.10.1007/978-1-4899-4541-9Search in Google Scholar
26. Grubb A, Nyman U, Björk J. Improved estimation of glomerular filtration rate (GFR) by comparison of eGFRcystatin C and eGFRcreatinine. Scand J Clin Lab Invest 2012;72:73–7.10.3109/00365513.2011.634023Search in Google Scholar PubMed PubMed Central
27. Soveri I, Berg UB, Bjork J, Elinder CG, Grubb A, Mejare I, et al. Measuring GFR: a systematic review. Am J Kidney Dis [Epub ahead of print 2014 May 17].Search in Google Scholar
28. Golledge J, Ewels C, Muller R, Walker PJ. Association of chronic kidney disease categories defined with different formulae with major adverse events in patients with peripheral vascular disease. Atherosclerosis 2014;232:289–97.10.1016/j.atherosclerosis.2013.11.034Search in Google Scholar PubMed
29. Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S. Performance of GFR equations in Japanese subjects. Clin Exp Nephrol 2013;17:352–8.10.1007/s10157-012-0704-5Search in Google Scholar PubMed
30. Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S. GFR estimation using standardized serum cystatin C in Japan. Am J Kidney Dis 2013;61:197–203.10.1053/j.ajkd.2012.07.007Search in Google Scholar PubMed
31. Fan L, Inker LA, Rossert J, Froissart M, Rossing P, Mauer M, et al. Glomerular filtration rate estimation using cystatin C alone or combined with creatinine as a confirmatory test. Nephrol Dial Transplant 2014;29:1195–203.10.1093/ndt/gft509Search in Google Scholar PubMed PubMed Central
32. Schaeffner ES, Ebert N, Delanaye P, Frei U, Gaedeke J, Jakob O, et al. Two novel equations to estimate kidney function in persons aged 70 years or older. Ann Intern Med 2012;157:471–81.10.7326/0003-4819-157-7-201210020-00003Search in Google Scholar PubMed
33. Grubb A. Non-invasive estimation of glomerular filtration rate (GFR). The Lund model: simultaneous use of cystatin C- and creatinine-based GFR-prediction equations, clinical data and an internal quality check. Scand J Clin Lab Invest 2010;70:65–70.10.3109/00365511003642535Search in Google Scholar PubMed PubMed Central
34. Perrone RD, Madias NE, Levey AS. Serum creatinine as an index of renal function: new insights into old concepts. Clin Chem 1992;38:1933–53.10.1093/clinchem/38.10.1933Search in Google Scholar
35. Filler G, Bokenkamp A, Hofmann W, Le Bricon T, Martinez-Bru C, Grubb A. Cystatin C as a marker of GFR – history, indications, and future research. Clin Biochem 2005;38:1–8.10.1016/j.clinbiochem.2004.09.025Search in Google Scholar PubMed
36. Fricker M, Wiesli P, Brandle M, Schwegler B, Schmid C. Impact of thyroid dysfunction on serum cystatin C. Kidney Int 2003;63:1944–7.10.1046/j.1523-1755.2003.00925.xSearch in Google Scholar PubMed
37. Risch L, Herklotz R, Blumberg A, Huber AR. Effects of glucocorticoid immunosuppression on serum cystatin C concentrations in renal transplant patients. Clin Chem 2001;47:2055–9.10.1093/clinchem/47.11.2055Search in Google Scholar
38. Bjarnadottir M, Grubb A, Olafsson I. Promoter-mediated, dexamethasone-induced increase in cystatin C production by HeLa cells. Scand J Clin Lab Invest 1995;55:617–23.10.3109/00365519509110261Search in Google Scholar PubMed
39. Kristensen K, Lindstrom V, Schmidt C, Blirup-Jensen S, Grubb A, Wide-Swensson D, et al. Temporal changes of the plasma levels of cystatin C, beta-trace protein, beta2-microglobulin, urate and creatinine during pregnancy indicate continuous alterations in the renal filtration process. Scand J Clin Lab Invest 2007;67:612–8.10.1080/00365510701203488Search in Google Scholar PubMed
40. Delanaye P, Cavalier E, Cristol JP, Delanghe JR. Calibration and precision of serum creatinine and plasma cystatin C measurement: impact on the estimation of glomerular filtration rate. J Nephrol 2014.10.1007/s40620-014-0087-7Search in Google Scholar PubMed
41. Kuster N, Cristol JP, Cavalier E, Bargnoux AS, Halimi JM, Froissart M, et al. Enzymatic creatinine assays allow estimation of glomerular filtration rate in stages 1 and 2 chronic kidney disease using CKD-EPI equation. Clin Chim Acta 2014;428:89–95.10.1016/j.cca.2013.11.002Search in Google Scholar PubMed
42. Earley A, Miskulin D, Lamb EJ, Levey AS, Uhlig K. Estimating equations for glomerular filtration rate in the era of creatinine standardization: a systematic review. Ann Intern Med 2012;156:785–95.10.7326/0003-4819-156-11-201203200-00391Search in Google Scholar
43. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int Suppl 2013;3:1–150.Search in Google Scholar
44. Granerus G, Jacobsson L. Calculation of 51-Cr-EDTA single injection clearance. Comparison between a single sample and multiple sample formula. Swed Soc Radiol Proc 1985;19:71–3.Search in Google Scholar
Supplemental Material
The online version of this article (DOI: 10.1515/cclm-2014-0578) offers supplementary material, available to authorized users.
©2015 by De Gruyter
