Abstract
Since 1957, over 70 equations based on creatinine and/or cystatin C levels have been developed to estimate glomerular filtration rate (GFR). However, whether these equations accurately reflect renal function is debated. In this Perspectives article, we discuss >70 studies that compared estimated GFR (eGFR) with measured GFR (mGFR), involving ~40,000 renal transplant recipients and patients with chronic kidney disease (CKD), type 2 diabetes mellitus or polycystic kidney disease. Their results show that eGFR often differed from mGFR by ±30% or more, that eGFR values incorrectly staged CKD in 30–60% of patients, and that eGFR and mGFR gave different rates of GFR decline. Errors were unpredictable, and comparable for equations based on creatinine and/or cystatin C. We argue, therefore, that the persistence of these errors (despite intensive research) suggests that the problem lies with using creatinine and/or cystatin C as markers of renal function, rather than with the mathematical methods used for GFR estimation.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Change history
18 December 2018
In the version of this article originally published online, the middle initials of Aiko P. J. de Vries, an author on the manuscript, were omitted. The omission has been corrected in the PDF and HTML versions of the article.
References
Perrone, R. D., Madias, N. E. & Levey, A. S. Serum creatinine as an index of renal function: new insights into old concepts. Clin. Chem. 38, 1933–1953 (1992).
Kaji, D., Strauss, I. & Kahn, T. Serum creatinine in patients with spinal cord injury. Mt. Sinai J. Med. 57, 160–164 (1990).
Rule, A. D. et al. Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease. Ann. Intern. Med. 141, 929–937 (2004).
Levey, A. S. et al. A new equation to estimate glomerular filtration rate. Ann. Intern. Med. 150, 604–612 (2009).
Björk, J. et al. Prediction of relative glomerular filtration rate in adults: new improved equations based on Swedish Caucasians and standardized plasma-creatinine assays. Scand. J. Clin. Lab. Invest. 67, 678–695 (2007).
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. 71, 232–239 (2011).
Effersøe, P. Relationship between endogenous 24-hour creatinine clearance and serum creatinine concentration in patients with chronic renal disease. Acta Med. Scand. 156, 429–434 (1957).
Edwards, K. D. & Whyte, H. M. Plasma creatinine level and creatinine clearance as tests of renal function. Australas. Ann. Med. 8, 218–224 (1959).
Jelliffe, R. W. Estimation of creatinine clearance when urine cannot be collected. Lancet 1, 975–976 (1971).
Mawer, G. E., Lucas, S. B., Knowles, B. R. & Stirland, R. M. Computer-assisted prescribing of kanamycin for patients with renal insufficiency. Lancet 1, 12–15 (1972).
Jelliffe, R. W. Letter: creatinine clearance: bedside estimate. Ann. Intern. Med. 79, 604–605 (1973).
Cockcroft, D. W. & Gault, M. H. Prediction of creatinine clearance from serum creatinine. Nephron 16, 31–41 (1976).
Levey, A. S., Greene, T., Kusek, J. W. & Beck, G. J. A simplified equation to predict glomerular filtration rate from serum creatinine [abstract]. J. Am. Soc. Nephrol. 11, 115A (2000).
Pottel, H. et al. An estimated glomerular filtration rate equation for the full age spectrum. Nephrol. Dial. Transplant. 31, 798–806 (2016).
Grubb, A., Simonsen, O., Sturfelt, G., Truedsson, L. & Thysell, H. Serum concentration of cystatin C, factor D and β2-microglobulin as a measure of glomerular filtration rate. Acta Med. Scand. 218, 499–503 (1985).
Ma, Y. C. et al. Improved GFR estimation by combined creatinine and cystatin C measurements. Kidney Int. 72, 1535–1542 (2007).
Stevens, L. A. 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. 51, 395–406 (2008).
Inker, L. A. et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N. Engl. J. Med. 367, 20–29 (2012).
Schaeffner, E. S. et al. Two novel equations to estimate kidney function in persons aged 70 years or older. Ann. Intern. Med. 157, 471–481 (2012).
Feng, J. F. et al. Multicenter study of creatinine- and/or cystatin C-based equations for estimation of glomerular filtration rates in Chinese patients with chronic kidney disease. PLOS ONE 8, e57240 (2013).
Pottel, H. et al. Estimating glomerular filtration rate for the full age spectrum from serum creatinine and cystatin C. Nephrol. Dial. Transplant. 32, 497–507 (2017).
Björk, J. et al. Comparison of glomerular filtration rate estimating equations derived from creatinine and cystatin C: validation in the age, gene/environment susceptibility-Reykjavik elderly cohort. Nephrol. Dial. Transplant. 33, 1380–1388 (2018).
Inker, L. A. et al. GFR estimation using β-trace protein and β2-microglobulin in CKD. Am. J. Kidney Dis. 67, 40–48 (2016).
Nankivell, B. J., Gruenewald, S. M., Allen, R. D. & Chapman, J. R. Predicting glomerular filtration rate after kidney transplantation. Transplantation 59, 1683–1689 (1995).
Ibrahim, H. et al. An alternative formula to the Cockcroft–Gault and the modification of diet in renal diseases formulas in predicting GFR in individuals with type 1 diabetes. J. Am. Soc. Nephrol. 16, 1051–1060 (2005).
MacIsaac, R. J. et al. Estimating glomerular filtration rate in diabetes: a comparison of cystatin-C− and creatinine-based methods. Diabetologia 49, 1686–1689 (2006).
Lewis, J. et al. Comparison of cross-sectional renal function measurements in African Americans with hypertensive nephrosclerosis and of primary formulas to estimate glomerular filtration rate. Am. J. Kidney Dis. 38, 744–753 (2001).
Xie, P., Huang, J. M., Li, Y., Liu, H. J. & Qu, Y. The modified CKD-EPI equation may be not more accurate than CKD-EPI equation in determining glomerular filtration rate in Chinese patients with chronic kidney disease. J. Nephrol. 30, 397–402 (2017).
Yang, M. et al. Performance of the creatinine and cystatin C-based equations for estimation of GFR in Chinese patients with chronic kidney disease. Clin. Exp. Nephrol. 21, 236–246 (2017).
Changjie, G. et al. Evaluation of glomerular filtration rate by different equations in Chinese elderly with chronic kidney disease. Int. Urol. Nephrol. 49, 133–141 (2017).
Guo, X. et al. Improved glomerular filtration rate estimation using new equations combined with standardized cystatin C and creatinine in Chinese adult chronic kidney disease patients. Clin. Biochem. 47, 1220–1226 (2014).
Li, J. T. et al. Relative performance of two equations for estimation of glomerular filtration rate in a Chinese population having chronic kidney disease. Chin. Med. J. 125, 599–603 (2012).
Liu, X. et al. Comparison of prediction equations to estimate glomerular filtration rate in Chinese patients with chronic kidney disease. Intern. Med. J. 42, e59–e67 (2012).
Matsuo, S. et al. Revised equations for estimated GFR from serum creatinine in Japan. Am. J. Kidney Dis. 53, 982–992 (2009).
Praditpornsilpa, K. et al. The need for robust validation for MDRD-based glomerular filtration rate estimation in various CKD populations. Nephrol. Dial. Transplant. 26, 2780–2785 (2011).
Grubb, A. 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. 60, 974–986 (2014).
MacIsaac, R. J. et al. The Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation does not improve the underestimation of glomerular filtration rate (GFR) in people with diabetes and preserved renal function. BMC Nephrol. 16, 198 (2015).
Rossing, P., Rossing, K., Gaede, P., Pedersen, O. & Parving, H. H. Monitoring kidney function in type 2 diabetic patients with incipient and overt diabetic nephropathy. Diabetes Care 29, 1024–1030 (2006).
Fontsere, N. et al. Are prediction equations for glomerular filtration rate useful for the long-term monitoring of type 2 diabetic patients? Nephrol. Dial. Transplant. 21, 2152–2158 (2006).
Mariat, C. et al. Assessing renal graft function in clinical trials: can tests predicting glomerular filtration rate substitute for a reference method? Kidney Int. 65, 289–297 (2004).
Mariat, C. et al. Predicting glomerular filtration rate in kidney transplantation: are the K/DOQI guidelines applicable? Am. J. Transplant. 5, 2698–2703 (2005).
Bosma, R. J., Doorenbos, C. R., Stegeman, C. A., van der Heide, J. J. & Navis, G. Predictive performance of renal function equations in renal transplant recipients: an analysis of patient factors in bias. Am. J. Transplant. 5, 2193–2203 (2005).
Gaspari, F. et al. Performance of different prediction equations for estimating renal function in kidney transplantation. Am. J. Transplant. 4, 1826–1835 (2004).
Ruggenenti, P. et al. Measuring and estimating GFR and treatment effect in ADPKD patients: results and implications of a longitudinal cohort study. PLOS ONE 7, e32533 (2012).
Gaspari, F. et al. The GFR and GFR decline cannot be accurately estimated in type 2 diabetics. Kidney Int. 84, 164–173 (2013).
Iliadis, F. et al. Glomerular filtration rate estimation in patients with type 2 diabetes: creatinine- or cystatin C-based equations? Diabetologia 54, 2987–2994 (2011).
Shemesh, O., Golbetz, H., Kriss, J. P. & Myers, B. D. Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney Int. 28, 830–838 (1985).
Laterza, O. F., Price, C. P. & Scott, M. G. Cystatin C: an improved estimator of glomerular filtration rate? Clin. Chem. 48, 699–707 (2002).
Crim, M. C., Calloway, D. H. & Margen, S. Creatine metabolism in men: urinary creatine and creatinine excretions with creatine feeding. J. Nutr. 105, 428–438 (1975).
Heymsfield, S. B., Arteaga, C., McManus, C., Smith, J. & Moffitt, S. Measurement of muscle mass in humans: validity of the 24-hour urinary creatinine method. Am. J. Clin. Nutr. 37, 478–494 (1983).
Bleiler, R. E. & Schedl, H. P. Creatinine excretion: variability and relationships to diet and body size. J. Lab. Clin. Med. 59, 945–955 (1962).
Irving, R. A., Noakes, T. D., Irving, G. A. & Van Zyl-Smit, R. The immediate and delayed effects of marathon running on renal function. J. Urol. 136, 1176–1180 (1986).
Rennie, M. J. et al. Effect of exercise on protein turnover in man. Clin. Sci. 61, 627–639 (1981).
Horber, F. F., Scheidegger, J. & Frey, F. J. Overestimation of renal function in glucocorticosteroid treated patients. Eur. J. Clin. Pharmacol. 28, 537–541 (1985).
Friedman, R. B., Anderson, R. E., Entine, S. M. & Hirshberg, S. B. Effects of diseases on clinical laboratory tests. Clin. Chem. 26, 1D–476D (1980).
Miller, B. F., Leaf, A., Mamby, A. R. & Miller, Z. Validity of the endogenous creatinine clearance as a measure of glomerular filtration rate in the diseased human kidney. J. Clin. Invest. 31, 309–313 (1952).
Baldwin, D. S., Sirota, J. H. & Villarreal, H. Diurnal variations of renal function in congestive heart failure. Proc. Soc. Exp. Biol. Med. 74, 578–581 (1950).
Chesley, L. C. Renal excretion at low urine volumes and the mechanism of oliguria. J. Clin. Invest. 17, 591–597 (1938).
Jones, J. D. & Burnett, P. C. Creatinine metabolism in humans with decreased renal function: creatinine deficit. Clin. Chem. 20, 1204–1212 (1974).
Mitch, W. E., Collier, V. U. & Walser, M. Creatinine metabolism in chronic renal failure. Clin. Sci. 58, 327–335 (1980).
Miller, W. G. et al. Creatinine measurement: state of the art in accuracy and interlaboratory harmonization. Arch. Pathol. Lab. Med. 129, 297–304 (2005).
Panteghini, M. Enzymatic assays for creatinine: time for action. Clin. Chem. Lab. Med. 46, 567–572 (2008).
Peake, M. & Whiting, M. Measurement of serum creatinine — current status and future goals. Clin. Biochem. Rev. 27, 173–184 (2006).
Myers, G. L. et al. Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program. Clin. Chem. 52, 5–18 (2006).
Delanaye, P., Cavalier, E., Depas, G., Chapelle, J. P. & Krzesinski, J. M. New data on the intraindividual variation of cystatin C. Nephron. Clin. Pract. 108, c246–c248 (2008).
Abrahamson, M. et al. Structure and expression of the human cystatin C gene. Biochem. J. 268, 287–294 (1990).
Grubb, A. Diagnostic value of analysis of cystatin C and protein HC in biological fluids. Clin. Nephrol. 38 (Suppl. 1), S20–S27 (1992).
de Vries, A. P. & Rabelink, T. J. A possible role of cystatin C in adipose tissue homeostasis may impact kidney function estimation in metabolic syndrome. Nephrol. Dial. Transplant. 28, 1628–1630 (2013).
Delanaye, P. et al. Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 1: how to measure glomerular filtration rate with iohexol? Clin. Kidney J. 9, 682–699 (2016).
Delanaye, P. et al. Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 2: why to measure glomerular filtration rate with iohexol? Clin. Kidney J. 9, 700–704 (2016).
Chantler, C. & Barratt, T. M. Estimation of glomerular filtration rate from plasma clearance of 51-chromium edetic acid. Arch. Dis. Child. 47, 613–617 (1972).
Brochner-Mortensen, J. & Rodbro, P. Selection of routine method for determination of glomerular filtration rate in adult patients. Scand. J. Clin. Lab. Invest. 36, 35–43 (1976).
Hall, P. M. & Rolin, H. Iothalamate clearance and its use in large-scale clinical trials. Curr. Opin. Nephrol. Hypertens. 4, 510–513 (1995).
Equalis. External quality assessment (EQA) schemes: Iohexol (024). equalis https://www.equalis.se/en/products-and-services/external-quality-assessment-eqa/eqa-schemes/g-l/iohexol-024/ (2014).
Lin, L., Hedayat, A. & Wu, W. Statistical Tools for Measuring Agreement (Springer Science+Business Media, 2012).
Lin, L. I. A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255–268 (1989).
Lin, L., Hedayat, A., Sinha, B. & Yang, M. Statistical methods in assessing agreement: models, issues, and tools. J. Am. Stat. Assoc. 97, 257–270 (2002).
Bland, J. M. & Altman, D. G. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1, 307–310 (1986).
Luis-Lima, S. et al. Estimated glomerular filtration rate in renal transplantation: the nephrologist in the mist. Transplantation 99, 2625–2633 (2015).
Ahlstrom, M. G., Kjaer, A., Gerstoft, J. & Obel, N. Agreement between estimated and measured renal function in an everyday clinical outpatient setting of human immunodeficiency virus-infected individuals. Nephron 136, 318–327 (2017).
Selistre, L. et al. Comparison of the Schwartz and CKD-EPI equations for estimating glomerular filtration rate in children, adolescents, and adults: a retrospective cross-sectional study. PLOS Med. 13, e1001979 (2016).
Fan, L. et al. Glomerular filtration rate estimation using cystatin C alone or combined with creatinine as a confirmatory test. Nephrol. Dial. Transplant. 29, 1195–1203 (2014).
Evans, M. et al. Glomerular filtration rate-estimating equations for patients with advanced chronic kidney disease. Nephrol. Dial. Transplant. 28, 2518–2526 (2013).
van Deventer, H. E., Paiker, J. E., Katz, I. J. & George, J. A. A comparison of cystatin C− and creatinine-based prediction equations for the estimation of glomerular filtration rate in black South Africans. Nephrol. Dial. Transplant. 26, 1553–1558 (2011).
Stevens, L. A. et al. Evaluation of the modification of diet in renal disease study equation in a large diverse population. J. Am. Soc. Nephrol. 18, 2749–2757 (2007).
Murata, K. et al. Relative performance of the MDRD and CKD-EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations. Clin. J. Am. Soc. Nephrol. 6, 1963–1972 (2011).
Froissart, M., Rossert, J., Jacquot, C., Paillard, M. & Houillier, P. Predictive performance of the modification of diet in renal disease and Cockcroft–Gault equations for estimating renal function. J. Am. Soc. Nephrol. 16, 763–773 (2005).
Hojs, R., Bevc, S., Ekart, R., Gorenjak, M. & Puklavec, L. Kidney function estimating equations in patients with chronic kidney disease. Int. J. Clin. Pract. 65, 458–464 (2011).
Wang, X. et al. Validation of creatinine-based estimates of GFR when evaluating risk factors in longitudinal studies of kidney disease. J. Am. Soc. Nephrol. 17, 2900–2909 (2006).
Xie, D. et al. A comparison of change in measured and estimated glomerular filtration rate in patients with nondiabetic kidney disease. Clin. J. Am. Soc. Nephrol. 3, 1332–1338 (2008).
Padala, S. et al. Accuracy of a GFR estimating equation over time in people with a wide range of kidney function. Am. J. Kidney Dis. 60, 217–224 (2012).
Lee, D., Levin, A., Roger, S. D. & McMahon, L. P. Longitudinal analysis of performance of estimated glomerular filtration rate as renal function declines in chronic kidney disease. Nephrol. Dial. Transplant. 24, 109–116 (2009).
Hossain, F., Kendrick-Jones, J., Ma, T. M. & Marshall, M. R. The estimation of glomerular filtration rate in an Australian and New Zealand cohort. Nephrology (Carlton) 17, 285–293 (2012).
Ebert, N. et al. Cystatin C standardization decreases assay variation and improves assessment of glomerular filtration rate. Clin. Chim. Acta 456, 115–121 (2016).
Poggio, E. D., Wang, X., Greene, T., Van Lente, F. & Hall, P. M. 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. 16, 459–466 (2005).
Bevc, S., Hojs, R., Ekart, R., Gorenjak, M. & Puklavec, L. Simple cystatin C formula compared to serum creatinine-based formulas for estimation of glomerular filtration rate in patients with mildly to moderately impaired kidney function. Kidney Blood Press. Res. 35, 649–654 (2012).
Bevc, S., Hojs, R., Ekart, R., Gorenjak, M. & Puklavec, L. 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 (2011).
Hojs, R., Bevc, S., Ekart, R., Gorenjak, M. & Puklavec, L. Serum cystatin C as an endogenous marker of renal function in patients with mild to moderate impairment of kidney function. Nephrol. Dial. Transplant. 21, 1855–1862 (2006).
Barroso, S., Martinez, J. M., Martin, M. V., Rayo, I. & Caravaca, F. Accuracy of indirect estimates of renal function in advanced chronic renal failure patients. Nefrologia 26, 344–350 (2006).
Lopes, M. B. et al. Estimation of glomerular filtration rate from serum creatinine and cystatin C in octogenarians and nonagenarians. BMC Nephrol. 14, 265 (2013).
Brown, M. A. et al. Inaccuracies in estimated glomerular filtration rate in one Australian renal centre. Nephrology (Carlton) 16, 486–494 (2011).
Li, H. X., Xu, G. B., Wang, X. J., Zhang, X. C. & Yang, J. M. Diagnostic accuracy of various glomerular filtration rates estimating equations in patients with chronic kidney disease and diabetes. Chin. Med. J. 123, 745–751 (2010).
El-Minshawy, O. M. & El-Bassuoni, E. Validation of El-Minia equation for estimation of glomerular filtration rate in different stages of chronic kidney disease. Iran. J. Kidney Dis. 6, 262–268 (2012).
Tent, H. et al. Performance of MDRD study and CKD-EPI equations for long-term follow-up of nondiabetic patients with chronic kidney disease. Nephrol. Dial. Transplant. 27 (Suppl. 3), 89–95 (2012).
Methven, S., Gasparini, A., Carrero, J. J., Caskey, F. J. & Evans, M. Routinely measured iohexol glomerular filtration rate versus creatinine-based estimated glomerular filtration rate as predictors of mortality in patients with advanced chronic kidney disease: a Swedish Chronic Kidney Disease Registry cohort study. Nephrol. Dial. Transplant. 32 (Suppl. 2), 170–179 (2017).
Gaspari, F. et al. Glomerular filtration rate determined from a single plasma sample after intravenous iohexol injection: is it reliable? J. Am. Soc. Nephrol. 7, 2689–2693 (1996).
Ku, E. et al. Change in measured GFR versus eGFR and CKD outcomes. J. Am. Soc. Nephrol. 27, 2196–2204 (2016).
Maple-Brown, L. J. et al. Performance of formulas for estimating glomerular filtration rate in indigenous Australians with and without type 2 diabetes: the eGFR Study. Diabet. Med. 31, 829–838 (2014).
Rigalleau, V. et al. A simplified Cockcroft–Gault formula to improve the prediction of the glomerular filtration rate in diabetic patients. Diabetes Metab. 32, 56–62 (2006).
Wood, A. J. et al. Estimating glomerular filtration rate: performance of the CKD-EPI equation over time in patients with type 2 diabetes. J. Diabetes Complications 30, 49–54 (2016).
Beauvieux, M. C. et al. New predictive equations improve monitoring of kidney function in patients with diabetes. Diabetes Care 30, 1988–1994 (2007).
Silveiro, S. P. et al. Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation pronouncedly underestimates glomerular filtration rate in type 2 diabetes. Diabetes Care 34, 2353–2355 (2011).
Perkins, B. A. et al. Detection of renal function decline in patients with diabetes and normal or elevated GFR by serial measurements of serum cystatin C concentration: results of a 4-year follow-up study. J. Am. Soc. Nephrol. 16, 1404–1412 (2005).
Bjornstad, P., Cherney, D. Z. & Maahs, D. M. Update on estimation of kidney function in diabetic kidney disease. Curr. Diab. Rep. 15, 57 (2015).
Masson, I. et al. MDRD versus CKD-EPI equation to estimate glomerular filtration rate in kidney transplant recipients. Transplantation 95, 1211–1217 (2013).
Masson, I. et al. GFR estimation using standardized cystatin C in kidney transplant recipients. Am. J. Kidney Dis. 61, 279–284 (2013).
Gera, M. et al. Assessment of changes in kidney allograft function using creatinine-based estimates of glomerular filtration rate. Am. J. Transplant. 7, 880–887 (2007).
Fauvel, J. P., Hadj-Aissa, A., Buron, F., Morelon, E. & Ducher, M. Performance of estimated glomerular filtration rates to monitor change in renal function in kidney transplant recipients. Nephrol. Dial. Transplant. 28, 3096–3100 (2013).
Hossain, M. A., Attia, A. & Shoker, A. Measurement error in estimated GFR slopes across transplant chronic kidney disease stages. Am. J. Nephrol. 31, 151–159 (2010).
Buron, F. et al. Estimating glomerular filtration rate in kidney transplant recipients: performance over time of four creatinine-based formulas. Transplantation 92, 1005–1011 (2011).
Attia, A., Zahran, A. & Shoker, A. Comparison of equations to estimate the glomerular filtration rate in post-renal transplant chronic kidney disease patients. Saudi J. Kidney Dis. Transpl. 23, 453–460 (2012).
Goerdt, P. J., Heim-Duthoy, K. L., Macres, M. & Swan, S. K. Predictive performance of renal function estimate equations in renal allografts. Br. J. Clin. Pharmacol. 44, 261–265 (1997).
Harzallah, K. et al. Creatinine clearance estimation after kidney transplantation: an analysis of three methods. Transplant. Proc. 39, 2571–2573 (2007).
Kukla, A. et al. GFR-estimating models in kidney transplant recipients on a steroid-free regimen. Nephrol. Dial. Transplant. 25, 1653–1661 (2010).
Maillard, N. et al. Cystatin C-based equations in renal transplantation: moving toward a better glomerular filtration rate prediction? Transplantation 85, 1855–1858 (2008).
Poge, U. et al. MDRD equations for estimation of GFR in renal transplant recipients. Am. J. Transplant. 5, 1306–1311 (2005).
Poge, U. et al. Cystatin C-based calculation of glomerular filtration rate in kidney transplant recipients. Kidney Int. 70, 204–210 (2006).
Poge, U., Gerhardt, T., Stoffel-Wagner, B., Sauerbruch, T. & Woitas, R. P. Validation of the CKD-EPI formula in patients after renal transplantation. Nephrol. Dial. Transplant. 26, 4104–4108 (2011).
Poggio, E. D. et al. Assessing glomerular filtration rate by estimation equations in kidney transplant recipients. Am. J. Transplant. 6, 100–108 (2006).
Raju, D. L., Grover, V. K. & Shoker, A. Limitations of glomerular filtration rate equations in the renal transplant patient. Clin. Transplant. 19, 259–268 (2005).
Risch, L. & Huber, A. R. Assessing glomerular filtration rate in renal transplant recipients by estimates derived from serum measurements of creatinine and cystatin C. Clin. Chim. Acta 356, 204–211 (2005).
White, C. et al. Estimating glomerular filtration rate in kidney transplantation: a comparison between serum creatinine and cystatin C-based methods. J. Am. Soc. Nephrol. 16, 3763–3770 (2005).
White, C. et al. Chronic kidney disease stage in renal transplantation classification using cystatin C and creatinine-based equations. Nephrol. Dial. Transplant. 22, 3013–3020 (2007).
Yeo, Y. et al. Suitability of the IDMS-traceable MDRD equation method to estimate GFR in early postoperative renal transplant recipients. Nephron Clin. Pract. 114, c108–c117 (2010).
Zahran, A., Qureshi, M. & Shoker, A. Comparison between creatinine and cystatin C-based GFR equations in renal transplantation. Nephrol. Dial. Transplant. 22, 2659–2668 (2007).
Orskov, B. et al. Estimating glomerular filtration rate using the new CKD-EPI equation and other equations in patients with autosomal dominant polycystic kidney disease. Am. J. Nephrol. 31, 53–57 (2010).
Spithoven, E. M. et al. Tubular secretion of creatinine in autosomal dominant polycystic kidney disease: consequences for cross-sectional and longitudinal performance of kidney function estimating equations. Am. J. Kidney Dis. 62, 531–540 (2013).
[No authors listed.] Chapter 2: definition, identification, and prediction of CKD progression. Kidney Int. Suppl. 3, 63–72 (2013).
Caroli, A. et al. Effect of longacting somatostatin analogue on kidney and cyst growth in autosomal dominant polycystic kidney disease (ALADIN): a randomised, placebo-controlled, multicentre trial. Lancet 382, 1485–1495 (2013).
European Medicines Agency. Guideline on the clinical investigation of medicinal products to prevent development/slow progression of chronic renal insufficiency. EMA http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2016/10/WC500214980.pdf (2016).
British Transplantation Society. Guidelines for living donor kidney transplantation. BTS https://bts.org.uk/wp-content/uploads/2018/07/FINAL_LDKT-guidelines_June-2018.pdf (2018).
The Renal Association. Clinical practice guideline post-operative care in the kidney transplant recipient. renal https://renal.org/wp-content/uploads/2017/06/FINAL-Post-Operative-Care-Guideline.pdf (2017).
Schaeffner, E. Determining the glomerular filtration rate — an overview. J. Ren. Nutr. 27, 375–380 (2017).
Soveri, I. et al. Measuring GFR: a systematic review. Am. J. Kidney Dis. 64, 411–424 (2014).
Gaspari, F. et al. Safety of iohexol administration to measure glomerular filtration rate in different patient populations: a 25-year experience. Nephron 140, 1–8 (2018).
Sterner, G. et al. Determining ‘true’ glomerular filtration rate in healthy adults using infusion of inulin and comparing it with values obtained using other clearance techniques or prediction equations. Scand. J. Urol. Nephrol. 42, 278–285 (2008).
Luis-Lima, S. et al. Iohexol plasma clearance simplified by dried blood spot testing. Nephrol. Dial. Transplant. 33, 1597–1603 (2018).
Acknowledgements
The authors acknowledge research support from the DIABESITY working group of the ERA-EDTA, the IMBRAIN (CIBICAN) project (FP7-RE6-POT-2012-CT2012-31637-IMBRAIN) funded under the 7th Framework Programme (capacities); Instituto de Salud Carlos III (ISCIII) grants PI13/00342 and PI16/01814 to E.P. and A.T., REDINREN RD16/0009 and PI10/02428 grants to E.P. and A.T.; and funding from the IRSIN (Instituto Reina Sofia de Investigacion) and FEDER (both to A.T.). S.L.L. is a research fellow supported by ISCIII grant CM15/00214 for Río Hortega specialized health-care post-training contracts. E.P. is a researcher supported by the ISCIII Ramón y Cajal Programme and Fundación Caja Canarias grant DIAB05. The authors thank F. G. Rinne for preparation of the figures, N. N. Mena for performing the iohexol method in the Laboratory of Renal Function, and M. L. McLean for technical assistance.
Reviewer information
Nature Reviews Nephrology thanks E. Cavalier, L. Dubourg and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Author information
Authors and Affiliations
Contributions
E.P., F.C. and F.G. researched data for the article, made substantial contributions to discussions of its content, wrote the manuscript and reviewed or edited the manuscript before submission. P.R., A.d.V. and G.R. made substantial contributions to discussions of the article content, wrote the manuscript and reviewed or edited the manuscript before submission. S.L.-L. researched data for the article, contributed substantially to discussions of its content, and reviewed or edited the manuscript before submission. A.J. researched data for the article and contributed substantially to discussions of its content. A.T. substantially contributed to discussions of the article content.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Glossary
- Accuracy
-
The degree of closeness of the determined value (in this case, estimated glomerular filtration rate) to the true value (measured glomerular filtration rate) under prescribed conditions. Accuracy is also sometimes termed trueness.
- Bias
-
The difference between an estimated value (such as estimated glomerular filtration rate) and a true value (measured glomerular filtration rate), which is also termed error. A statistic is biased if it is calculated in such a way that it is systematically different from the parameter being estimated.
- Coefficient of variation
-
The variation obtained when measurements are repeated under the same conditions. A low value indicates that the technique is both accurate and precise.
- Precision
-
The closeness of agreement (that is, the degree of scatter) in a series of determinations (that is, estimated glomerular filtration rate values) obtained from multiple sampling of the same homogenous sample under the prescribed conditions.
- Reproducibility
-
The precision of results compared between two laboratories. Reproducibility also refers to the precision of a particular method when used under the same operating conditions over a short period of time.
Rights and permissions
About this article
Cite this article
Porrini, E., Ruggenenti, P., Luis-Lima, S. et al. Estimated GFR: time for a critical appraisal. Nat Rev Nephrol 15, 177–190 (2019). https://doi.org/10.1038/s41581-018-0080-9
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41581-018-0080-9
This article is cited by
-
Machine-learning model for predicting oliguria in critically ill patients
Scientific Reports (2024)
-
Evaluation of eGFR methods in a sub-Saharan African community-based pediatric population
Pediatric Nephrology (2024)
-
Glomerular filtration rate measurement during platinum treatment for urothelial carcinoma: optimal methods for clinical practice
International Journal of Clinical Oncology (2024)
-
Combined Heart Kidney Transplantation Versus Heart Transplant in Patients with Renal Failure: Contemporary Insights and Future Perspectives
Current Cardiology Reports (2024)
-
The error of estimated GFR in predialysis care
Scientific Reports (2024)