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Creatinine-or cystatin C-based equations to estimate glomerular filtration in the general population: impact on the epidemiology of chronic kidney disease.

ABSTRACT: BACKGROUND: Chronic kidney disease (CKD) is a major issue in public health. Its prevalence has been calculated using estimation of glomerular filtration rate (GFR) by the creatinine-based equations developed in the Modified Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) study. Recently, new equations based either on cystatin C (CKD-EPI Cys) or both cystatin and creatinine (CKD-EPI mix) have been proposed by the CKD-EPI consortium. The aim of this study was to measure the difference in the prevalence of stage 3 CKD, defined as an estimated GFR less than 60 mL/min/1.73 m2, in a population using these four equations. METHODS: CKD screening was performed in the Province of Liège, Belgium. On a voluntary basis, people aged over 50 years have been screened. GFR was estimated by the four equations. Stage 3 CKD was defined as a GFR less than 60 mL/min/1.73 m2. RESULTS: The population screened consisted of 4189 people (47% were men, mean age 63?±?7y). Their mean serum creatinine and plasma cystatin C levels were 0.88?±?0.21 mg/dL and 0.85?±?0.17 mg/L, respectively. The prevalence of CKD in this population using the MDRD, the CKD-EPI, the CKD-EPI Cys and the CKD-EPI mix equations was 13%, 9.8%, 4.7% and 5%, respectively. The prevalence of CKD was significantly higher with the creatinine-based (MDRD and the CKD-EPI) equations compared to the new cystatin C-based equations. CONCLUSIONS: Prevalence of CKD varies strongly depending on the method used to estimate GFR. Such discrepancies are of importance and must be confirmed and explained by additional studies, notably by studies using GFR measured with a reference method. TRIAL REGISTRATION: B70720071509.

SUBMITTER: Delanaye P

PROVIDER: S-EPMC3637126 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Creatinine-or cystatin C-based equations to estimate glomerular filtration in the general population: impact on the epidemiology of chronic kidney disease.

Delanaye Pierre P Cavalier Etienne E Moranne Olivier O Lutteri Laurence L Krzesinski Jean-Marie JM Bruyère Olivier O

BMC nephrology 20130312

<h4>Background</h4>Chronic kidney disease (CKD) is a major issue in public health. Its prevalence has been calculated using estimation of glomerular filtration rate (GFR) by the creatinine-based equations developed in the Modified Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) study. Recently, new equations based either on cystatin C (CKD-EPI Cys) or both cystatin and creatinine (CKD-EPI mix) have been proposed by the CKD-EPI consortium. The aim of t ...[more]

PMID: 23496839

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Project description:ObjectiveTo establish equations for the estimation of glomerular filtration rates (eGFRs) based on serum creatinine (SCr) and/or serum cystatin C (SCysC) in Chinese patients with chronic kidney disease (CKD), and to compare the new equations with both the reference GFR (rGFR) and the literature equations to evaluate their applicability.MethodsThe 788 Chinese CKD patients were randomly divided into two groups, the training group and the testing group, to establish new eGFR-formulas based on serum CysC and to validate the established formulas, respectively. (99m)Tc-DTPA clearance (as the rGFR), serum Cr, and serum CysC were determined for all patients, and GFR was calculated using the Cockcroft-Gault equation (eGFR1), the MDRD formula (eGFR2), the CKD-EPI formulas (eGFR3, eGFR4), and the Chinese eGFR Investigation Collaboration formulas (eGFR5, eGFR6). The accuracy of each eGFR was compared with the rGFR.ResultsThe training and testing groups' mean GFRs were 50.84±31.36 mL/min/1.73 m(2) and 54.16±29.45 mL/min/1.73 m(2), respectively. The two newly developed eGFR formulas were fitted using iterative computation: [Formula: see text] and [Formula: see text]. Significant correlation was observed between each eGFR and the rGFR. However, proportional errors and constant errors were observed between rGFR and eGFR1, eGFR2, eGFR4, eGFR5 or eGFR6, and constant errors were observed between eGFR3 and rGFR, as revealed by the Passing & Bablok plot analysis. The Bland-Altman analysis illustrated that the 95% limits of agreement of all equations exceeded the previously accepted limits of <60 mL/min •1.73 m(2), except the equations of eGFR7 and eGFR8.ConclusionThe newly developed formulas, eGFR7 and eGFR8, provide precise and accurate GFR estimation using serum CysC detection alone or in combination with serum Cr detection. Differences in detection methods should be carefully considered when choosing literature eGFR equations to avoid misdiagnosis and mistreatment.

Project description:BACKGROUND:The Kidney Disease Improving Global Outcomes (KDIGO) guideline recommends use of a cystatin C-based estimated glomerular filtration rate (eGFR) to confirm creatinine-based eGFR between 45 and 59 mL · min(-1) · (1.73 m(2))(-1). Prior studies have demonstrated that comorbidities such as solid-organ transplant strongly influence the relationship between measured GFR, creatinine, and cystatin C. Our objective was to evaluate the performance of cystatin C-based eGFR equations compared with creatinine-based eGFR and measured GFR across different clinical presentations. METHODS:We compared the performance of the CKD-EPI 2009 creatinine-based estimated GFR equation (eGFRCr) and the newer CKD-EPI 2012 cystatin C-based equations (eGFRCys and eGFRCr-Cys) with measured GFR (iothalamate renal clearance) across defined patient populations. Patients (n = 1652) were categorized as transplant recipients (n = 568 kidney; n = 319 other organ), known chronic kidney disease (CKD) patients (n = 618), or potential kidney donors (n = 147). RESULTS:eGFRCr-Cys showed the most consistent performance across different clinical populations. Among potential kidney donors without CKD [stage 2 or higher; eGFR >60 mL · min(-1) · (1.73 m(2))(-1)], eGFRCys and eGFRCr-Cys demonstrated significantly less bias than eGFRCr; however, all 3 equations substantially underestimated GFR when eGFR was <60 mL · min(-1) · (1.73 m(2))(-1). Among transplant recipients with CKD stage 3B or greater [eGFR <45 mL · min(-1) · (1.73 m(2))(-1)], eGFRCys was significantly more biased than eGFRCr. No clear differences in eGFR bias between equations were observed among known CKD patients regardless of eGFR range or in any patient group with a GFR between 45 and 59 mL · min(-1) · (1.73 m(2))(-1). CONCLUSIONS:The performance of eGFR equations depends on patient characteristics that are readily apparent on presentation. Among the 3 CKD-EPI equations, eGFRCr-Cys performed most consistently across the studied patient populations.

Project description:Accurate estimation of glomerular filtration rate (GFR) is important for diagnosis and risk stratification in chronic kidney disease and for selection of living donors. Ethnic differences have required correction factors in the originally developed creatinine-based GFR estimation equations for populations around the world. Existing equations have not been validated in the vegetarian Indian population. We examined the performance of creatinine and cystatin-based GFR estimating equations in Indians.GFR was measured by urinary clearance of inulin. Serum creatinine was measured using IDMS-traceable Jaffe's and enzymatic assays, and cystatin C by colloidal gold immunoassay. Dietary protein intake was calculated by measuring urinary nitrogen appearance. Bias, precision and accuracy were calculated for the eGFR equations.A total of 130 participants (63 healthy kidney donors and 67 with CKD) were studied. About 50% were vegetarians, and the remainder ate meat 3.8 times every month. The average creatinine excretion were 14.7 mg/kg/day (95% CI: 13.5 to 15.9 mg/kg/day) and 12.4 mg/kg/day (95% CI: 11.2 to 13.6 mg/kg/day) in males and females, respectively. The average daily protein intake was 46.1 g/day (95% CI: 43.2 to 48.8 g/day). The mean mGFR in the study population was 51.66?±?31.68 ml/min/1.73m2. All creatinine-based eGFR equations overestimated GFR (p?<?0.01 for each creatinine based eGFR equation). However, eGFR by CKD-EPICys was not significantly different from mGFR (p?=?0.38). The CKD-EPICys exhibited lowest bias [mean bias: -3.53?±?14.70 ml/min/1.73m2 (95% CI: -0.608 to -0.98)] and highest accuracy (P30: 74.6%). The GFR in the healthy population was 79.44 ± 20.19 (range: 41.90-134.50) ml/min/1.73m2.Existing creatinine-based GFR estimating equations overestimate GFR in Indians. An appropriately powered study is needed to develop either a correction factor or a new equation for accurate assessment of kidney function in the Indian population.

Project description:Estimates of glomerular filtration rate (GFR) that are based on serum creatinine are routinely used; however, they are imprecise, potentially leading to the overdiagnosis of chronic kidney disease. Cystatin C is an alternative filtration marker for estimating GFR.Using cross-sectional analyses, we developed estimating equations based on cystatin C alone and in combination with creatinine in diverse populations totaling 5352 participants from 13 studies. These equations were then validated in 1119 participants from 5 different studies in which GFR had been measured. Cystatin and creatinine assays were traceable to primary reference materials.Mean measured GFRs were 68 and 70 ml per minute per 1.73 m(2) of body-surface area in the development and validation data sets, respectively. In the validation data set, the creatinine-cystatin C equation performed better than equations that used creatinine or cystatin C alone. Bias was similar among the three equations, with a median difference between measured and estimated GFR of 3.9 ml per minute per 1.73 m(2) with the combined equation, as compared with 3.7 and 3.4 ml per minute per 1.73 m(2) with the creatinine equation and the cystatin C equation (P=0.07 and P=0.05), respectively. Precision was improved with the combined equation (interquartile range of the difference, 13.4 vs. 15.4 and 16.4 ml per minute per 1.73 m(2), respectively [P=0.001 and P<0.001]), and the results were more accurate (percentage of estimates that were >30% of measured GFR, 8.5 vs. 12.8 and 14.1, respectively [P<0.001 for both comparisons]). In participants whose estimated GFR based on creatinine was 45 to 74 ml per minute per 1.73 m(2), the combined equation improved the classification of measured GFR as either less than 60 ml per minute per 1.73 m(2) or greater than or equal to 60 ml per minute per 1.73 m(2) (net reclassification index, 19.4% [P<0.001]) and correctly reclassified 16.9% of those with an estimated GFR of 45 to 59 ml per minute per 1.73 m(2) as having a GFR of 60 ml or higher per minute per 1.73 m(2).The combined creatinine-cystatin C equation performed better than equations based on either of these markers alone and may be useful as a confirmatory test for chronic kidney disease. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.).

Project description:BackgroundSerum creatinine (S-Cr)-based prediction equations are commonly used for estimating glomerular filtration rate (GFR). However, S-Cr concentration is also affected by other factors such as tubular secretion, muscle mass, diet, gender and age. Serum cystatin C (S-Cys C)-based prediction equations have been proposed as an improved potential alternative as S-Cys C levels are not influenced by many of the factors that affect creatinine concentration other than GFR. This may be of great benefit to patients with low muscle mass such as those infected with human immunodeficiency virus who are at increased risk for the development of renal impairment. The aim of this study was to develop and evaluate a S-Cys C-based prediction equation for different stages of renal disease in black South Africans.MethodsOne hundred patients with varying degrees of renal function were enrolled in the study. The plasma clearance of (51)Cr-EDTA, a gold standard method, was used to measure GFR (mGFR). In addition, serum was analysed for S-Cr and S-Cys C on each participant. This dataset was split into a development dataset (n = 50) and a test dataset (n = 50). The development dataset was used to formulate a S-Cys C- and S-Cr-based prediction equation using multiple linear regression analysis. These equations together with the four-variable MDRD and CKD-EPI equation were then tested on the test dataset.ResultsIn the test dataset, accuracy within 15% of measured GFR was 68% for the S-Cys C equation and 48% for the S-Cr equation. Root mean square error for S-Cr eGFR was 10.7 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 25.5 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2). Root mean square error for S-Cys C eGFR was 10.2 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 11.9 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2).ConclusionsIn this study, S-Cys C-based prediction equations appear to be more precise than those of S-Cr for those patients with mGFR > 60 mL/min/1.73 m(2) and may therefore be of benefit in the earlier detection of renal impairment.

Dataset Information

Creatinine-or cystatin C-based equations to estimate glomerular filtration in the general population: impact on the epidemiology of chronic kidney disease.

Publications

Creatinine-or cystatin C-based equations to estimate glomerular filtration in the general population: impact on the epidemiology of chronic kidney disease.

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