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CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equation seems more suitable for Chinese patients with chronic kidney disease than other equations.

ABSTRACT: The aim of this study was to identify the optimal equation that accurately estimates the glomerular filtration rate (GFR) and the chronic kidney disease (CKD) stage in the Chinese population.A total of 1296 Chinese patients aged 18-65 years old were enrolled in this study. The estimated GFRs (eGFRs) calculated separately by three Diet in Renal Disease (MDRD) equations and three Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were compared with the reference GFR (rGFR) measured by the 99Tcm-DTPA renal dynamic imaging method.By Bland-Altman analysis, eGFRcys and eGFRscr_cys performed similarly, showing the tightest limits of agreement among the six equations. They also achieved the first and second highest 30% and 50% accuracies. Using a combination of the serum creatinine and cystatin C levels (eGFRscr_cys) could improve the bias (-0.3 for eGFRscr_cys) of the equation and achieve the highest diagnostic accuracy for renal insufficiency (AUC60, 0.953; P < 0.05, except for eGFR_MDRD). All equations predicted stage 3 CKD with moderate accuracy (49.7-51.4%) and stage 5 CKD with good accuracy (90.2-96.4%). For stage 1 CKD, eGFRcys showed a higher percentage of misclassification than the other equations. All equations seemed to perform poorly at predicting stage 2 and 4 CKD, as compared to the other CKD stages. eGFRscr_cys was the best-performing equation in terms of accurate classification of the CKD stage based on the overall performance (kappa value, 0.423).For a Chinese population, the CKD-EPIscr_cys equation seems more suitable for estimating the GFR than the other equations. Each equation had its own advantages in predicting different CKD stages.

SUBMITTER: Chi XH

PROVIDER: S-EPMC5504640 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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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:CONTEXT:The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE:To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS:A meta-analysis of data from 1.1 million adults (aged ? 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES:All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS:Estimated GFR was classified into 6 categories (?90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7% to 6.3%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95% CI, 0.74-0.86) for all-cause mortality, 0.73 (95% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and ?65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION:The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of 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.

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CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equation seems more suitable for Chinese patients with chronic kidney disease than other equations.

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