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Measuring and estimating GFR and treatment effect in ADPKD patients: results and implications of a longitudinal cohort study.

ABSTRACT: Trials failed to demonstrate protective effects of investigational treatments on glomerular filtration rate (GFR) reduction in Autosomal Dominant Polycystic Kidney Disease (ADPKD). To assess whether above findings were explained by unreliable GFR estimates, in this academic study we compared GFR values centrally measured by iohexol plasma clearance with corresponding values estimated by Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) and abbreviated Modification of Diet in Renal Disease (aMDRD) formulas in ADPKD patients retrieved from four clinical trials run by a Clinical Research Center and five Nephrology Units in Italy. Measured baseline GFRs and one-year GFR changes averaged 78.6±26.7 and 8.4±10.3 mL/min/1.73 m(2) in 111 and 71 ADPKD patients, respectively. CKD-Epi significantly overestimated and aMDRD underestimated baseline GFRs. Less than half estimates deviated by <10% from measured values. One-year estimated GFR changes did not detect measured changes. Both formulas underestimated GFR changes by 50%. Less than 9% of estimates deviated <10% from measured changes. Extent of deviations even exceeded that of measured one-year GFR changes. In ADPKD, prediction formulas unreliably estimate actual GFR values and fail to detect their changes over time. Direct kidney function measurements by appropriate techniques are needed to adequately evaluate treatment effects in clinics and research.

SUBMITTER: Ruggenenti P

PROVIDER: S-EPMC3291245 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Measuring and estimating GFR and treatment effect in ADPKD patients: results and implications of a longitudinal cohort study.

Ruggenenti Piero P Gaspari Flavio F Cannata Antonio A Carrara Fabiola F Cella Claudia C Ferrari Silvia S Stucchi Nadia N Prandini Silvia S Ene-Iordache Bogdan B Diadei Olimpia O Perico Norberto N Ondei Patrizia P Pisani Antonio A Buongiorno Erasmo E Messa Piergiorgio P Dugo Mauro M Remuzzi Giuseppe G

PloS one 20120228 2

Trials failed to demonstrate protective effects of investigational treatments on glomerular filtration rate (GFR) reduction in Autosomal Dominant Polycystic Kidney Disease (ADPKD). To assess whether above findings were explained by unreliable GFR estimates, in this academic study we compared GFR values centrally measured by iohexol plasma clearance with corresponding values estimated by Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) and abbreviated Modification of Diet in Renal Dise ...[more]

PMID: 22393413

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Project description:OBJECTIVE:Most predictive models of kidney disease progression have not incorporated structural data. If structural variables have been used in models, they have generally been only semi-quantitative. METHODS:We examined the predictive utility of quantitative structural parameters measured on the digital images of baseline kidney biopsies from the NEPTUNE study of primary proteinuric glomerulopathies. These variables were included in longitudinal statistical models predicting the change in estimated glomerular filtration rate (eGFR) over up to 55 months of follow-up. RESULTS:The participants were fifty-six pediatric and adult subjects from the NEPTUNE longitudinal cohort study who had measurements made on their digital biopsy images; 25% were African-American, 70% were male and 39% were children; 25 had focal segmental glomerular sclerosis, 19 had minimal change disease, and 12 had membranous nephropathy. We considered four different sets of candidate predictors, each including four quantitative structural variables (for example, mean glomerular tuft area, cortical density of patent glomeruli and two of the principal components from the correlation matrix of six fractional cortical areas-interstitium, atrophic tubule, intact tubule, blood vessel, sclerotic glomerulus, and patent glomerulus) along with 13 potentially confounding demographic and clinical variables (such as race, age, diagnosis, and baseline eGFR, quantitative proteinuria and BMI). We used longitudinal linear models based on these 17 variables to predict the change in eGFR over up to 55 months. All 4 models had a leave-one-out cross-validated R2 of about 62%. CONCLUSIONS:Several combinations of quantitative structural variables were significantly and strongly associated with changes in eGFR. The structural variables were generally stronger than any of the confounding variables, other than baseline eGFR. Our findings suggest that quantitative assessment of diagnostic renal biopsies may play a role in estimating the baseline risk of succeeding loss of renal function in future clinical studies, and possibly in clinical practice.

Project description:BackgroundThe biomarker discovery field is replete with molecular signatures that have not translated into the clinic despite ostensibly promising performance in predicting disease phenotypes. One widely cited reason is lack of classification consistency, largely due to failure to maintain performance from study to study. This failure is widely attributed to variability in data collected for the same phenotype among disparate studies, due to technical factors unrelated to phenotypes (e.g., laboratory settings resulting in "batch-effects") and non-phenotype-associated biological variation in the underlying populations. These sources of variability persist in new data collection technologies.MethodsHere we quantify the impact of these combined "study-effects" on a disease signature's predictive performance by comparing two types of validation methods: ordinary randomized cross-validation (RCV), which extracts random subsets of samples for testing, and inter-study validation (ISV), which excludes an entire study for testing. Whereas RCV hardwires an assumption of training and testing on identically distributed data, this key property is lost in ISV, yielding systematic decreases in performance estimates relative to RCV. Measuring the RCV-ISV difference as a function of number of studies quantifies influence of study-effects on performance.ResultsAs a case study, we gathered publicly available gene expression data from 1,470 microarray samples of 6 lung phenotypes from 26 independent experimental studies and 769 RNA-seq samples of 2 lung phenotypes from 4 independent studies. We find that the RCV-ISV performance discrepancy is greater in phenotypes with few studies, and that the ISV performance converges toward RCV performance as data from additional studies are incorporated into classification.ConclusionsWe show that by examining how fast ISV performance approaches RCV as the number of studies is increased, one can estimate when "sufficient" diversity has been achieved for learning a molecular signature likely to translate without significant loss of accuracy to new clinical settings.

Project description:Background and objectiveseGFR equations have been evaluated in kidney transplant recipients with variable performance. We assessed the performance of the Modification of Diet in Renal Disease equation and the Chronic Kidney Disease Epidemiology Collaboration equations on the basis of creatinine, cystatin C, and both (eGFR creatinine-cystatin C) compared with measured GFR by iothalamate clearance and evaluated their non-GFR determinants and associations across 15 cardiovascular risk factors.Design, setting, participants, & measurementsA cross-sectional cohort of 1139 kidney transplant recipients >1 year after transplant was analyzed. eGFR bias, precision, and accuracy (percentage of estimates within 30% of measured GFR) were assessed. Interaction of each cardiovascular risk factor with eGFR relative to measured GFR was determined.ResultsMedian measured GFR was 55.0 ml/min per 1.73 m(2). eGFR creatinine overestimated measured GFR by 3.1% (percentage of estimates within 30% of measured GFR of 80.4%), and eGFR Modification of Diet in Renal Disease underestimated measured GFR by 2.2% (percentage of estimates within 30% of measured GFR of 80.4%). eGFR cystatin C underestimated measured GFR by -13.7% (percentage of estimates within 30% of measured GFR of 77.1%), and eGFR creatinine-cystatin C underestimated measured GFR by -8.1% (percentage of estimates within 30% of measured GFR of 86.5%). Lower measured GFR associated with older age, women, obesity, longer time after transplant, lower HDL, lower hemoglobin, lower albumin, higher triglycerides, higher proteinuria, and an elevated cardiac troponin T level but did not associate with diabetes, smoking, cardiovascular events, pretransplant dialysis, or hemoglobin A1c. These risk factor associations differed for five risk factors with eGFR creatinine, six risk factors for eGFR Modification of Diet in Renal Disease, ten risk factors for eGFR cystatin C, and four risk factors for eGFR creatinine-cystatin C.ConclusionsThus, eGFR creatinine and eGFR creatinine-cystatin C are preferred over eGFR cystatin C in kidney transplant recipients because they are less biased, more accurate, and more consistently reflect the same risk factor associations seen with measured GFR.

Dataset Information

Measuring and estimating GFR and treatment effect in ADPKD patients: results and implications of a longitudinal cohort study.

Publications

Measuring and estimating GFR and treatment effect in ADPKD patients: results and implications of a longitudinal cohort study.

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