KDIGO 2012 Clinical Practice Guideline

KDIGO2012Clinical Practice Guideline ckd classification rules out creati-nine clearance24hours urine collection?A.Ognibene,G.Grandi,M.Lorubbio,S.Rapi,B.Salvadori, A.Ter-reni,F.VeroniPII:S0009-9120(15)00310-0DOI:doi:10.1016/j.clinbiochem.2015.07.030Reference:CLB9097To appear in:Clinical BiochemistryReceived date:11February2015Revised date:12July2015Accepted date:26July2015Please cite this article as:Ognibene A,Grandi G,Lorubbio M,Rapi S,Salvadori B, Terreni A,Veroni F,KDIGO2012Clinical Practice Guideline ckd classification rules out creatinine clearance24hours urine collection?,Clinical Biochemistry(2015),doi: 10.1016/j.clinbiochem.2015.07.030This is a PDFfile of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting,typesetting,and review of the resulting proof before it is published in itsfinal form.Please note that during the production process errors may be discovered which could affect the content,and all legal disclaimers thatapply to the journal pertain.A C C E P T E D M A N U S C R I P TKDIGO 2012 C LINICAL P RACTICE G UIDELINE CKD CLASSIFICATION RULES OUT CREATININE CLEARANCE 24 HOURS URINE COLLECTION ?Ognibene A., Grandi G., Lorubbio M., Rapi S., Salvadori B., Terreni A., Veroni F.Laboratorio Generale – Azienda Ospedaliero-Universitaria Careggi - Firenze ItalyCorresponding author:Agostino Ognibenea.ognibene@med.unifi.itPhone: +39 3403460965Azienda Ospedaliero-Universitaria Careggi Largo Brambilla, 350134 Firenze ItalyAbbreviations: Creatinine Clearance (CrCl); Chronic Kidney Disease (CKD); Glomerular Filtration Rate (GFR); Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPI); estimation Glomerular Filtration Rate (eGFR); Modification of Diet in Renal Disease equation (MDRD).A C C E P T E D M A N U S C R I P TAbstractObjectives: The recent guideline for the Evaluation and Management of Chronic Kidney Disease recommends assessing GFR employing equations based on serum creatinine; despite this, creatinine clearance 24-hours urine collection is used routinely in many settings. In this study we compared the classification assessed from CrCl (creatinine clearance 24h urine collection) and e-GFR calculated with CKD-EPI or MDRD formulas.Design and Methods: In this retrospective study we analyze consecutive laboratory data: creatinine clearance 24h urine collection, serum creatinine and demographic data such as sex and age from 15777 patients >18 years of age collected from 2011 to 2013 in our laboratory at Careggi Hospital. The results were then compared to the estimated GFR calculated with the equations according to the recent treatment guidelines. Consecutive and retrospective laboratory data (creatinine clearance 24h urine collection, serum creatinine and, demographic data such as sex and age) from 15777 patients >18 years of age seen at Careggi Hospital were collected.Results: Comparison between e-GFR calculated with CKD-EPI or MDRD formulas and GFR according CrCl determinations, bias [95% CI] were 11.34 [-47,4/70.1] and 11.4 [-50.2/73] respectively. The concordance for 18/65 years aged group when compared e-GFR classification between MDRD vs CKDEPI, MDRD vs CrCl and CKD-EPI vs CrCl were 0.78, 0.34, and 0.41 respectively, while in the 65/110 years aged group the concordance Kappa were 0.84, 0.38, and 0.36 respectively.Conclusions: The use of CrCl provides a different classification than the estimation of GFR using a prediction equation. The CrCl is unreliable when it is necessary to identify CKD subjects with decrease of GFR of 5 ml/min/1.73 m 2/year.A C C E P T E D M A N U S C R I P TKey words: Glomerular Filtration Rate, Creatinine, MDRD, CKD-EPI, Creatinine Clearance, Chronic Kidney Disease, estimation GFR.IntroductionGlomerular Filtration Rate (GFR) is widely accepted as the best indicator of kidney function, yet in clinical practice except nephrology it is infrequently utilised moreover the GFR so calculated is a very mediocre to use as diagnostic test. GFR calculated by the clearance of exogenous markers such as iothalamate, or iohexol and inulin is considerably time-consuming, expensive, and requires the administration of substances not feasible in routine monitoring [1].GFR can be obtained also by the clearance of endogenous substances, very often urinary clearance of creatinine, computed from 24 hours urine collection (CrCl) [2]. Unfortunately, timed urinary collections are cumbersome and susceptible to error, making the 24 hour urine collections for the measurement of creatinine clearance no longer recommended routinely to estimate the level of kidney function [3].During the last decades, serum creatinine has been the most frequently employed marker to estimate GFR and serial measurements of creatinine are very useful for determining changes in kidney function. The K/DOQI guidelines emphasize the necessity to assess GFR employing equations based on serum creatinine and not to rely on serum creatinine concentration alone [1]. Specifically in the last few years, attention has been focused on two creatinine-based equations that are widely studied and applied, the Modification of Diet in Renal Disease (MDRD) [4] and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations [5]. The first one, the MDRD formula, was developed in 1999 and re-expressed in 2007; it estimates GFR adjusted for body-surface area using age and gender as variables and using a standardized method forA C C E P T E D M A N U S C R I P Tthe measurement of serum creatinine [6]. The second one, the CKD-EPI equation, was developed in order to create a more accurate and precise formula than the MDRD, especially when actual GFR is > 60 mL/min per 1.73 m2 [7,8,9].GFR estimation became of extreme importance especially after the publication of the guidelines by KDIGO 2012, Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease (CKD) that updates the 2002 KDOQI Clinical Practice Guidelines for Chronic Kidney Disease [1, 10]. Particular emphasize is given to the change from 5 to 6 categories based on GFR levels to predict risk for outcomes of CKD. In this retrospective study we analyze data collected during three years (2011-13) in our laboratory. Specifically, from the database of the laboratory were extracted all CrCl tests performed during the above period of time. The results were then compared to the equations estimated GFR (e-GFR) in order to verify the concordance between methods, following the recent classification of CKD.Material and methodsStudy populationConsecutive and retrospective laboratory data such as creatinine clearance 24h urine collection (CrCl), serum creatinine (Scr) and demographic data such as sex and age from 15777 patients >18 years of age seen at Careggi Hospital between January 2011 and December 2013 were collected. These data were imported into Microsoft Excel, which was used to perform the eGFR (CKD-EPI and MDRD) calculations.Laboratory assayAll serum and urine creatinine were measured by IDMS-traceable assay on the ADVIA 2400 systems (Siemens Diagnostics) using a creatininase/creatinase based enzymatic method (ECRE_2, Siemens Diagnostics).eGFR algorithmsA C C E P T E D M A N U S C R I P TGFR was estimated using the MDRD study equation (175 × standardized Scr −1.154 × age −0.203 ×1.212[if patient is black] × 0.742 [if patient is female]) and the CKD-EPI equation (CKD-EPI = 141 × min(Scr/k, 1)α × max(Scr/k,1)-1.209 × 0.993age × 1.018 [if patient is female] × 1.159 [if patient is black], where age is in years, k is 0.7 for females and 0.9 for males, α is −0.329 for females and −0.411 for males, min indicates the minimum of Scr/k or 1, and max indicates the maximum of Scr/k or 1). GFR is expressed in ml/min/1.73 m 2[5,6]. CrCl was calculated from urinary creatinine × urinary volume (24h) / serum creatinine. To allow comparison, CrCl were normalized to standard values of 1.73 m 2 BSA, and expressed in ml/min/1.73 m 2.Six GFR category according to KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease were: G1 (>90 ml/min/1.73 m 2), G2 (60-89 ml/min/1.73 m 2), G3a (45-59 ml/min/1.73 m 2), G3b (30-44 ml/min/1.73 m 2), G4 (15-29 ml/min/1.73 m 2), G5 (<15 ml/min/1.73 m 2) [10].Statistical analysisTo compare the effectiveness of the two equations studied we used a Bland and Altman plot. In particular the method calculates the mean difference between two methods of measurement and the 95% limits of agreement as the mean difference (1.96 SD) [11]. Paired-Samples T Test was used to compare the means; Cohen's and Fleiss Kappa were used measuring agreement between classifications [12]. An α <0.05 was considered statistically significant. The statistical analyses were performed with SPSS version 11.0.ResultsTable 1 shows the main characteristic of the study population, all parameters were statistically significant between two sexes except CrCl. Figure 1 shows Bland Altman plots for the comparison between e-GFR calculated with CKD-EPI or MDRD formulas and GFR according to CrCl determinations; mean bias [95% CI] were 11.34[-47.4, 70.1] and 11.4[-50.2, 73] respectively. Moreover when compared differences between e-GFR calculated with CKD-EPI or MDRDA C C E P T E D M A N U S C R I P Tformulas and GFR according CrCl determinations <60 ml/min, mean bias [95% CI] were -3.78[- 36.4, 28.8] and -2.7[-39.6, 34.1] respectively, while when CrCl determinations were >60 ml/min mean bias [95% CI] were 20.6[-43.6, 83.7] and 19.6[-47.6, 86.7] respectively (plots not showed).Figure 2 illustrates the standard error of the mean (SEM) of the differences of the CKD-EPI and MDRD with the mean of the two results, CrCl and CKD-EPI or CrCl and MDRD respectively. The differences were plotted in relation to age groups (A and B plot) and in relation to levels of GFR used for classification in 6 groups described in the recent guidelines for the progression of CKD (C and D plot). In tables 2, are shown the results of cross tabulation between the classification according to the KDIGO criteria, MDRD vs CKD-EPI and CrCl, and CKD-EPI vs CrCl; the concordance between classification tested with Cohen’s Kappa were 0.8, 0.35, and 0.4 respectively.Moreover in figure 3 were showed the comparison of e-GFR classification between CKD-EPI vs CrCl and MDRD vs CKD-EPI in two clusters of age 18/65 (10890/15777) and 65/110 years (4887/15777). The concordance Kappa for the 18/65 years aged group when compared e-GFR classification between CKD-EPI vs CrCl was 0.41 and 0.78 for MDRD vs CKD-EPI, while in the 65/110 years aged group was 0.36 and 0.84 respectively. Finally the overall concordance between MDRD, CKD-EPI and CrCl calculated by Fleiss Kappa test, was 0.52 when considered globally, while when considering separately each class were: 0.62 for G1, 0.41 for G2, 0.41 for G3a, 0.51 for G3b, 0.65 for G4 and 0.75 for G5.ConclusionsThis retrospective study compares three different methods to estimate GFR, two use the formulas MDRD and CKD-EPI and the other is an analytical determination CrCl; all are routinely used to assess kidney function [13].A C C E P T E D M A N U S C R I P TUnfortunately, for the peculiar characteristics of the study and the lack of the clinical outcome, we cannot here determine which of the methods is the most accurate. The main objective of the study is to verify the concordance of the three methods MDRD, CKD-EPI and CrCl, available in the clinical laboratory to estimate GFR.e-GFR is really a numerically-modified serum creatinine adjusted to minimize population variation from age, gender, and race. We know that the factors which may determine the extremely wide scatter seen between all e-GFR calculations, are numerous [14]. Surely the role of the clinical laboratory will be decisive for reducing the analytical bias but also to create the laboratory reports sufficient for the correct interpretation of the data [15]. As well known, small analytic changes in serum creatinine create major shifts in the distributions of eGFR, which can cause large differences in the classification of patients [14,15]. It is also true that while changes in Scr will certainly affect eGFR calculation, both the physiological and analytical changes in Scr are much smaller than the physiological and analytical variation of GFR measurements, whether by inulin or iothalamate. CrCl has at least one advantage over the others in that the blood concentration remains essentially constant during the clearance measurement.In this study, the creatinine enzymatic IDMS-traceable assay used allowed to minimize the analytical bias on the study of agreement between the three methods than non-enzymatic creatinine determination [16].The comparison of the differences from the Bland-Altman analysis shows a high bias of e-GFR obtained from the formulas MDRD or CKD-EPI when compared with CrCl (figure 1). The bias and the distribution of the differences is larger when we consider e-GFR> 90 and in subjects aged <71 years. When we consider the classes with e-GFR <90, the differences are lower but nevertheless the concordance in classification between the CrCl and e-GFR equations is very poor (table 2 and figure 3).The differences between the various age groups and between the levels of GFR are similar both for CKD-EPI for the MDRD compared with CrCl.A C C E P T E D M A N U S C R I P TInterestingly a lower variability of the differences for the CKD-EPI equation, for classes and G3a G3b, and in different age groups than the MDRD equation. This enhanced linearity is probably the result of a more effective normalization equation for estimating GFR (Figure 2).KDIGO (Kidney Disease: Improving Global Outcomes) in 2012 published an updated guideline[10] of “The National Kidney Foundation–Kidney Disease Outcomes Quality Initiative (NKFKDOQI) for evaluation, classification, and stratification of chronic kidney disease (CKD) published in 2002[1]. In particular, in this update of the guidelines the categories of the classification of CKD increased from 5 to 6 distinguishing stage 3 CKD in stage 3a (GFR of 45-59 mL / min / 1.73 m 2) and 3b (GFR of 30-44 mL /min/1.73 m 2). This distinction received approval from the scientific world, justified by the high risk in these categories of mortality and other negative outcomes [19, 20].Guidelines KDOQI and the latest updates KDIGO state that CrCl does not add any information compared to estimated GFR using a prediction equation. This new classification requires, regarding eGFR, greater accuracy but also a lower imprecision. CrCl, besides the overestimation of about 15% of CrCl due tubular secretion, is inconvenient and time consuming, but also imprecise and inaccurate, errors mainly due to reduced muscle mass and erroneous urine sampling [21].In the present study, there is an obvious lack of concordance between CrCl and e-GFR using a prediction equation. The low statistical concordance is more evident especially when we consider G2, G3a and G3b stages, in the table 2, and graphical representation of the concordance in the figure 3 showed the main differences in GFR estimation. These stages represent the groups that more likely will have a progression to renal damage with the highest incidence of risk of adverse events.The e-GFR obtained with the MDRD equation is underestimated in about 25% of the subjects, especially in classes G2, G3a, and G3b when compared with CKD-EPI e-GFR. This phenomenon is more evident when considering the subjects younger than 65 years of age (figure 3).A C C E P T E D M A N U S C R I P TIn light of these results we conclude that the use of CrCl provides a different classification than the estimation of GFR using a prediction equation. Stevens et al. [19] emphasizes the need to better understand the definitions of CKD progression and how they affect clinical practice and trials. The recent guidelines de facto excluded the CrCl for the evaluation and follow-up of patients with CKD, but there are n’t recommendations that advise against the use.Has been demonstrated that serial determinations of CrCl (each month for six months), have a variation greater than serial determinations of creatinine or cystatin C in healthy subjects [22].Then, in addition to the overestimation of CrCl due tubular secretion, the analytical variability of CrCl makes it inadequate and unreliable, especially when it is necessary to identify CKD subjects with progression of disease in presence of a decrease of GFR of 5 ml/min/1.73 m 2/year as recommended in recent guidelines.References[1] National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidneydisease. Am J Kidney Dis 2002;39:S1-S266.[2] Van Lente F, Suit P. Assessment of renal function by serum creatinine and creatinineclearance: glomerular filtration rate estimated by four procedures. Clin Chem 1989;35:2326-30.[3] Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function--measured andestimated glomerular filtration rate. N Engl J Med 2006;354:2473-83.A C C E PT EDM A NU SC R I P T[4]Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.. Ann Intern Med 1999;130:461-70.[5]Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF,Feldman HI, Kusek JW et al. CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604-12.[6]Levey A.S., Coresh J., Greene T., Marsh J., Lesley A.S., et al. for Chronic Kidney DiseaseEpidemiology Collaboration. Expressing the Modification of Diet in Renal Disease Study Equation for Estimating Glomerular Filtration Rate with Standardized Serum Creatinine Values. Clin Chem 2007;53:766-72. [7]Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S. Modificaton of the CKD epidemiology collaboration (CKD-EPI) equation for Japanase: accuracy and use for population estimates. Am J Kidney Dis 2010;56:32-8[8]Mathew TH, Johnson DW, Jones GR; Australasian Creatinine Consensus Working Group. Chronic kidney disease and automatic reporting of estimated glomerular filtration rate: revised recommendations. Med J Aust 2007;187:459–63.[9]White SL, Polkinghorne KR, Atkins RC, Chadban SJ. Comparison of the prevalence and mortality risk of CKD Australia using CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes Obesity and Lifestyle) Study. Am J Kidney Dis 2010;55:660-70.A C C E PT EDM A NU SC R I P T[10]KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int. Supp 2013;3:1-150.[11]Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;2:307-10.[12]Hale CA1, Fleiss JL. Interval estimation under two study designs for kappa with binaryclassifications.. Biometrics 1993;49:523-4.[13]International Federation of Clinical Chemistry and Laboratory Medicine; Working Group on Standardization of Glomerular Filtration Rate Assessment (WG-GFRA), Panteghini M, Myers GL, Miller WG, Greenberg N.The importance of metrological traceability on the validity of creatinine measurement as an index of renal function. Clin Chem Lab Med 2006;44:1287-92.[14]Botev R, Mallie JP, Wetzels JF, Couchoud C, Schück O. The clinician and estimation of glomerular filtration rate by creatinine-based formulas: current limitations and quo vadis. Clin J Am Soc Nephrol. 2011; 6: 937-50[15] Toffaletti, John G. Clarifying the Fog of Natural and Manmade Renal Function Tests: Creatinine, Clearances, Glomerular Filtration Rate, and Estimated Glomerular Filtration Rate. Point of Care 2011;10:45-50A C C E PT EDM A NU SC R I P T[16]Klee GG, Schryver PG, Saenger AK, Larson TS.Effects of analytic variations in creatinine measurements on the classification of renal disease using estimated glomerular filtration rate (eGFR). Clin Chem Lab Med 2007;45:737-41.[17]Myers GL, Miller WG, Coresh J, Fleming J, Greenberg N, Greene T, et al. National Kidney Disease Education Program Laboratory Working Group. Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program. Clin Chem 2006;52:5-18.[18] Kuster N, Cristol JP, Cavalier E, Bargnoux AS, Halimi JM, Froissart M, et al. Société Française de Biologie Clinique (SFBC). 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;20:89-95.[19]Lesley A. Inker, Brad C. Astor, Chester H. Fox, Tamara Isakova, James P. Lash, Carmen A. Peralta, et al, KDOQI US Commentary on the 2012 KDIGO Clinical Practice Guideline for the Evaluation and Management of CKD. Am J Kidney Dis 2014;63:713-35[20]Paul E. Stevens, and Adeera Levin, for the Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members* Evaluation and Management of Chronic Kidney Disease: Synopsis of the Kidney Disease: Improving Global Outcomes 2012 Clinical Practice Guideline. Ann Intern Med 2013;158:825-30.[21]Burkhardt H1, Bojarsky G, Gretz N, Gladisch R. Creatinine clearance, Cockcroft-Gault formula and cystatin C: estimators of true glomerular filtration rate in the elderly? Gerontology 2002;48:140-6.A C C E PT EDM A NU SC R I P T[22]Toffaletti JG, McDonnell EH. Variation of serum creatinine, cystatin C, and creatinine clearance tests in persons with normal renal function. Clin Chim Acta. 2008;395:115-9.Legend to figure:Figure 1: Bland –Altman analysis, comparison between GFR according CrCl determinations and e-GFR calculated with CKD-EPI equation (right) bias were 11.34[95% CI -47.4;70.1] or MDRD equation (left), bias 11.4 [95% CI -50.2;73].Figure 2: Standard Error of the Mean (SEM) of the differences of the CKD-EPI and MDRD withthe mean of the two results, CrCl and CKD-EPI or CrCl and MDRD respectively. The SEM of thedifferences was in relation to age groups (A and B plot) and in relation to levels of GFR (C and D plot), in x axis N represent the number of subjects for each class of age or GFR categories.Figure 3: Comparison of GFR estimation between MDRD vs CrCl (A), CKD-EPI vs CrCl (B) and MDRD vs CKD-EPI in the subjects of 18-65 (C) and 65-110 (D) years of age, according KDIGO stages. In Y axis is reported number of subjects.ANU STable1: Characteristics of the studied population, data are expressed as mean ±SD.Table 2: Number of subjects included in the categories specified by the KDIGO guidelines 2012, according to the estimation of GFR with: CrCl, CKD-EPI and MDRD.A CC15Figure 1T16Figure 2 95% C I S E M (m l /m i n /1.73 m 2)95% C I S E M (m l /m i n /1.73 m 2)Figure 317A C C E PT EDM A NU SC R I P THighlights1 - Clearance of creatinine computed from 24-hour urine collection2 - KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of ChronicKidney Disease3 - Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations .。