Dataset Information

Beta Trace Protein does not outperform Creatinine and Cystatin C in estimating Glomerular Filtration Rate in Older Adults.

ABSTRACT: Despite intense research the optimal endogenous biomarker for glomerular filtration rate (GFR) estimation has not been identified yet. We analyzed if ß-trace protein (BTP) improved GFR estimation in elderly. 566 participants aged 70+ from the population-based Berlin Initiative Study were included in a cross-sectional validation study. BTP, standardized creatinine and cystatin C were measured in participants with iohexol clearance measurement as gold standard method for measured GFR (mGFR). In a double logarithmic linear model prediction of mGFR by BTP was assessed. Analyses with BTP only and combined with creatinine and cystatin C were performed. Additionally, performance of GFR estimating equations was compared to mGFR. We found that the combination of all three biomarkers showed the best prediction of mGFR (r²?=?0.83), whereat the combination of creatinine and cystatin C provided only minimally diverging results (r²?=?0.82). Single usage of BTP showed worst prediction (r²?=?0.67) within models with only one biomarker. Subgroup analyses (arterial hypertension, diabetes, body mass index ?23 and >30) demonstrated a slight additional benefit of including BTP into the prediction model for diabetic, hypertensive and lean patients. Among BTP-containing GFR equations the Inker BTP-based equation showed superior performance. Especially the use of cystatin C renders the addition of BTP unnecessary.

SUBMITTER: Ebert N

PROVIDER: S-EPMC5627233 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Beta Trace Protein does not outperform Creatinine and Cystatin C in estimating Glomerular Filtration Rate in Older Adults.

Ebert Natalie N Koep Camilla C Schwarz Kristin K Martus Peter P Mielke Nina N Bartel Jan J Kuhlmann Martin M Gaedeke Jens J Toelle Markus M van der Giet Markus M Schuchardt Mirjam M Schaeffner Elke E

Scientific reports 20171004 1

Despite intense research the optimal endogenous biomarker for glomerular filtration rate (GFR) estimation has not been identified yet. We analyzed if ß-trace protein (BTP) improved GFR estimation in elderly. 566 participants aged 70+ from the population-based Berlin Initiative Study were included in a cross-sectional validation study. BTP, standardized creatinine and cystatin C were measured in participants with iohexol clearance measurement as gold standard method for measured GFR (mGFR). In a ...[more]

PMID: 28978997

Similar Datasets

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:BackgroundWe recently published and validated the new serum creatinine (Scr)-based full-age-spectrum equation (FAS crea ) for estimating the glomerular filtration rate (GFR) for healthy and kidney-diseased subjects of all ages. The equation was based on the concept of normalized Scr and shows equivalent to superior prediction performance to the currently recommended equations for children, adolescents, adults and older adults.MethodsBased on an evaluation of the serum cystatin C (ScysC) distribution, we defined normalization constants for ScysC ( Q cysC = 0.82 mg/L for ages <70 years and Q cysC = 0.95 mg/L for ages ≥70 years). By replacing Scr/ Q crea in the FAS crea equation with ScysC/ Q cysC , or with the average of both normalized biomarkers, we obtained new ScysC-based (FAS cysC ) and combined Scr-/ScysC-based FAS equations (FAS combi ). To validate the new FAS cysC and FAS combi we collected data on measured GFR, Scr, ScysC, age, gender, height and weight from 11 different cohorts including n = 6132 unique white subjects (368 children, aged ≤18 years, 4295 adults and 1469 older adults, aged ≥70 years).ResultsIn children and adolescents, the new FAS cysC equation showed significantly better performance [percentage of patients within 30% of mGFR (P30) = 86.1%] than the Caucasian Asian Paediatric Adult Cohort equation (P30 = 76.6%; P < 0.0001), or the ScysC-based Schwartz equation (P30 = 68.8%; P < 0.0001) and the FAS combi equation outperformed all equations with P30 = 92.1% (P < 0.0001). In adults, the FAS cysC equation (P30 = 82.6%) performed equally as well as the Chronic Kidney Disease Epidemiology Collaboration equation (CKD-EPI cysC ) (P30 = 80.4%) and the FAS combi equation (P30 = 89.9%) was also equal to the combined CKD-EPI equation (P30 = 88.2%). In older adults, FAS cysC was superior (P30 = 88.2%) to CKD-EPI cysC (P30 = 84.4%; P < 0.0001) and the FAS combi equation (P30 = 91.2%) showed significantly higher performance than the combined CKD-EPI equation (P30 = 85.6%) (P < 0.0001).ConclusionThe FAS equation is not only applicable to all ages, but also for all recommended renal biomarkers and their combinations.

Project description:ImportanceEstimating glomerular filtration rate (GFR) is useful in many clinical conditions. However, very few studies have evaluated the performance of GFR-estimating equations in older adults at various degrees of kidney impairment.ObjectiveTo determine the performance of plasma-creatinine-based equations Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI), Lund-Malmö Revised, (LMR), full age spectrum (FAS), and Berlin Initiative Study (BIS) 1 in older adults across a broad spectrum of GFRs.Design, setting, and participantsSingle-center cross-sectional study performed in France including 2247 participants aged 65 to 90 years who underwent inulin GFR measurements from July 1, 2003, to July 30, 2017, for suspected or established renal dysfunction, for renal risk, before kidney donation, or after kidney transplant.Main outcomes and measuresThe main outcome measure was GRF measured by inulin clearance. Equation performance criteria considered bias (difference between estimated and measured GFR), precision (interquartile range of the median difference), and accuracy P30 (percentage of estimated GFRs lying between [measured GFR - 30% of measured GFR] and [measured GFR + 30% of measured GFR]).ResultsThe mean (SD) age of the 2247 participants was 71.5 (5) years and 1192 (53.0%) were male. The difference in median (95% CI) bias was significant between CKD-EPI vs LMR (-4.0 [-4.0 to -3.5 mL/min/1.73 m2; P?<?.001]) and CKD-EPI vs FAS (-2.0 [-3.5 to -2.5] mL/min/1.73 m2, P?<?.001) but not significant between CKD-EPI vs BIS 1 (0.0 [-1.5 to 0.5], P?=?.07, Mood test). In patients aged 65 to 74 years with measured GFR<45 mL/min/1.73 m2, the difference in median P30 (95% CI) was not significant between CKD-EPI vs LMR (P?=?.08) and CKD-EPI vs FAS (P?=?.48) but significant vs BIS 1 (P?=?.004, McNemar test). In subjects 75 years and older, with measured GFR less than 45 mL/min/1.73 m2, LMR and BIS 1 were more accurate than CKD-EPI and FAS (P30?=?74.5 [70.0-79.5] and 73.0 [68.0-78.0] vs 69.0 [64.5-74.0] and 69.0 [65.5-72.0]). In all patients, despite small statistical differences, the performance of CKD-EPI equation was not clinically different from that of LMR, FAS, or BIS 1.Conclusions and relevanceIn a referral group of patients 65 years and older who had GFR estimated using CDK-EPI, LMR, BIS 1, and FAS equations, a comparison with renal inulin clearance found that none of the equations had a superior diagnostic performance. Each had limitations regarding accuracy.

Project description:BackgroundEquations to estimate GFR have not been well validated in the elderly and may misclassify persons with chronic kidney disease (CKD). We measured GFR and compared the performance of the Modification of Diet in Renal Disease (MDRD), the Chronic Kidney Disease-Epidemiology Collaboration (CKD-Epi) and the Berlin Initiative Study (BIS) equations based on creatinine and/or cystatin C in octogenarians and nonagenarians.MethodsUsing cross-sectional analysis we assessed 95 very elderly persons (mean 85 years) living in the community. GFR was measured by iohexol (mGFR) and compared with estimates using six equations: MDRD, CKD-Epi_creatinine, CKD-Epi_cystatin, CKD-Epi_creatinine-cystatin, BIS_creatinine and BIS_creatinine-cystatin.ResultsMean mGFR was 55 (range,19-86) ml/min/1.73 m(2). Bias was smaller with the CKD-Epi_creatinine-cystatin and the CKD-Epi_creatinine equations (-4.0 and 1.7 ml/min/1.73 m(2)). Accuracy (percentage of estimates within 30% of mGFR) was greater with the CKD-Epi_creatinine-cystatin, BIS_creatinine-cystatin and BIS_creatinine equations (85%, 83% and 80%, respectively). Among the creatinine-based equations, the BIS_creatinine had the greatest accuracy at mGFR < 60 ml/min/1.73 m(2) and the CKD-Epi_creatinine was superior at higher GFRs (79% and 90%, respectively). The CKD-Epi_creatinine-cystatin, BIS_creatinine-cystatin and CKD-Epi_cystatin equations yielded the greatest areas under the receiver operating characteristic curve at GFR threshold = 60 ml/min/1.73 m 2 (0.88, 0.88 and 0.87, respectively). In participants classified based on the BIS_creatinine, CKD-Epi_cystatin, or BIS_creatinine-cystatin equations, the CKD-Epi_creatinine-cystatin equation tended to improve CKD classification (net reclassification index: 12.7%, p = 0.18; 6.7%, p = 0.38; and 15.9%; p = 0.08, respectively).ConclusionsGFR-estimating equations CKD-Epi_creatinine-cystatin and BIS_creatinine-cystatin showed better accuracy than other equations using creatinine or cystatin C alone in very elderly persons. The CKD-Epi_creatinine-cystatin equation appears to be advantageous in CKD classification. If cystatin C is not available, both the BIS_cr equation and the CKD-Epi_cr equation could be used, although at mGFR < 60 ml/min/1.73 m(2), the BIS_cr equation seems to be the best alternative.

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.

Dataset Information

Beta Trace Protein does not outperform Creatinine and Cystatin C in estimating Glomerular Filtration Rate in Older Adults.

Publications

Beta Trace Protein does not outperform Creatinine and Cystatin C in estimating Glomerular Filtration Rate in Older Adults.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets