Dataset Information

Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study.

ABSTRACT: BACKGROUND:Estimation of glomerular filtration rate (GFR) using estimated glomerular filtration rate creatinine (eGFRcr) is central to clinical practice but has limitations. We tested the hypothesis that serum metabolomic profiling can identify novel markers that in combination can provide more accurate GFR estimates. METHODS:We performed a cross-sectional study of 200 African American Study of Kidney Disease and Hypertension (AASK) and 265 Multi-Ethnic Study of Atherosclerosis (MESA) participants with measured GFR (mGFR). Untargeted gas chromatography/dual mass spectrometry- and liquid chromatography/dual mass spectrometry-based quantification was followed by the development of targeted assays for 15 metabolites. On the log scale, GFR was estimated from single- and multiple-metabolite panels and compared with eGFR using the Chronic Kidney Disease Epidemiology equations with creatinine and/or cystatin C using established metrics, including the proportion of errors >30% of mGFR (1-P30), before and after bias correction. RESULTS:Of untargeted metabolites in the AASK and MESA, 283 of 780 (36%) and 387 of 1447 (27%), respectively, were significantly correlated (P???0.001) with mGFR. A targeted metabolite panel eGFR developed in the AASK and validated in the MESA was more accurate (1-P30 3.7 and 1.9%, respectively) than eGFRcr [11.2 and 18.5%, respectively (P??0.05) and 9.1% (P?

SUBMITTER: Coresh J

PROVIDER: S-EPMC6503300 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study.

Coresh Josef J Inker Lesley A LA Sang Yingying Y Chen Jingsha J Shafi Tariq T Post Wendy S WS Shlipak Michael G MG Ford Lisa L Goodman Kelli K Perichon Regis R Greene Tom T Levey Andrew S AS

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 20190501 5

<h4>Background</h4>Estimation of glomerular filtration rate (GFR) using estimated glomerular filtration rate creatinine (eGFRcr) is central to clinical practice but has limitations. We tested the hypothesis that serum metabolomic profiling can identify novel markers that in combination can provide more accurate GFR estimates.<h4>Methods</h4>We performed a cross-sectional study of 200 African American Study of Kidney Disease and Hypertension (AASK) and 265 Multi-Ethnic Study of Atherosclerosis (M ...[more]

PMID: 29718360

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Project description:BackgroundAccurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional surveys have not resolved questions about ANN performance.MethodsA total of 1,180 patients that had chronic kidney disease (CKD) were enrolled in the development data set, the internal validation data set and the external validation data set. Additional 222 patients that were admitted to two independent institutions were externally validated. Several ANNs were constructed and finally a Back Propagation network optimized by a genetic algorithm (GABP network) was chosen as a superior model, which included six input variables; i.e., serum creatinine, serum urea nitrogen, age, height, weight and gender, and estimated GFR as the one output variable. Performance was then compared with the Cockcroft-Gault equation, the MDRD equations and the CKD-EPI equation.ResultsIn the external validation data set, Bland-Altman analysis demonstrated that the precision of the six-variable GABP network was the highest among all of the estimation models; i.e., 46.7 ml/min/1.73 m(2) vs. a range from 71.3 to 101.7 ml/min/1.73 m(2), allowing improvement in accuracy (15% accuracy, 49.0%; 30% accuracy, 75.1%; 50% accuracy, 90.5% [P<0.001 for all]) and CKD stage classification (misclassification rate of CKD stage, 32.4% vs. a range from 47.3% to 53.3% [P<0.001 for all]). Furthermore, in the additional external validation data set, precision and accuracy were improved by the six-variable GABP network.ConclusionsA new ANN model (the six-variable GABP network) for CKD patients was developed that could provide a simple, more accurate and reliable means for the estimation of GFR and stage of CKD than traditional equations. Further validations are needed to assess the ability of the ANN model in diverse populations.

Project description:BackgroundCarboplatin remains integral for treatment of gynaecological malignancies and dosing is based on glomerular filtration rate (GFR). Measurement via radiotracer decay [nuclear medicine GFR (nmGFR)] is ideal. However, this may be unavailable. Therefore GFR is often estimated using formulae that have not been validated in patients with cancer and/or specifically for gynaecological malignancies, leading to debate over optimal estimation. Suboptimal GFR estimation may affect efficacy or toxicity.MethodsWe surveyed several UK National Health Service Trusts to assess carboplatin dosing practise. We then explored single-centre accuracy, bias and precision of various formulae for GFR estimation, relative to nmGFR, before validating our findings in an external cohort.ResultsAcross 18 Trusts, there was considerable heterogeneity in GFR estimation, including the formulae used [Cockcroft-Gault (CG) versus Wright], weight adjustment and area under the curve (AUC; 5 versus 6). We analysed 274 and 192 patients in two centres. Overall, CamGFR v2 (a novel formula for GFR estimation developed at Cambridge University Hospitals NHS Foundation Trust) excelled, showing the highest accuracy and precision. This translated into accuracy of hypothetical carboplatin dosing; nmGFR-derived carboplatin dose fell within 20% of the Cam GFR v2-derived dose in 86.5% and 87% of patients across the cohorts. Among the CG formula and its derivatives, using adjusted body weight in those with body mass index ≥25 kg/m2 [CG-adjusted body weight (CG-AdBW)] was optimal. The Wright and unadjusted CG estimators performed most poorly.ConclusionsWhen compared with nmGFR assessment, accuracy, bias and precision varied widely between GFR estimators, with the newly developed Cam GFR v2 and CG-AdBW performing best. In general, weight (or body surface area)-adjusted formulae excelled, while the unadjusted CG and Wright formulae or the use of AUC6 (versus nmGFR AUC5) produced risk of significant overdose. Thus, individual centres should validate their GFR estimation methods. In the absence of validation, CG-AdBW or CamGFR v2 is likely to perform well while unadjusted CG/Wright formulae or AUC6 dosing should be avoided.

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.

Dataset Information

Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study.

Publications

Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study.

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