Accuracy of a GFR Estimating Equation Over Time in People With a Wide Range of Kidney Function
ABSTRACT Change in glomerular filtration rate (GFR) is important for clinical decision making. GFR estimates from serum creatinine level provide an unbiased but imprecise estimate of GFR at single time points. However, the accuracy of estimated GFR over time is not well known.
Longitudinal study of diagnostic test accuracy.
4 clinical trials with longitudinal measurements of GFR and serum creatinine on the same day, including individuals with and without kidney disease with a wide range of kidney function, diverse racial backgrounds, and varied clinical characteristics.
GFR estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.
GFR measured using urinary clearance of (125)I-iothalamate.
Data included 19,735 GFR measurements in 3,531 participants during a mean follow-up of 2.6 years. Mean values at baseline for measured and estimated GFR and error (measured GFR - estimated GFR) were 73.1 (95% CI, 71.6 to 74.5), 72.7 (95% CI, 71.5 to 74.0), and 0.14 (95% CI, -0.35 to 0.63) mL/min/1.73 m(2), respectively. Mean rates of change in measured and estimated GFR and error were -2.3 (95% CI, -2.4 to -2.1), -2.2 (95% CI, -2.4 to -2.1), and -0.09 (95% CI, -0.24 to 0.05) mL/min/1.73 m(2) per year (P < 0.001, P < 0.001, and P = 0.2, respectively). Variability (ie, standard deviation) among participants in rate of change in measured GFR, estimated GFR, and error was 4.3, 3.4, and 3.3 mL/min/1.73 m(2) per year, respectively. Only 15% of participants had a rate of change in error >3 mL/min/1.73 m(2) per year, and only 2% had a rate of change in error >5% per year.
Participants' characteristics were not available over time.
The accuracy of GFR estimates did not change over time. Clinicians should interpret changes in estimated GFR over time as reflecting changes in measured GFR rather than changes in errors in the GFR estimates in most individuals.
- SourceAvailable from: Jonathan J Deeks
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- "Rate of change in eGFR will be established by linear regression  utilising all available (maximum 7) eGFR time points, and will be compared with the difference between final and baseline reference GFR values. Differences in large error rates (greater than 3 mL/min/1.73 "
ABSTRACT: Uncertainty exists regarding the optimal method to estimate glomerular filtration rate (GFR) for disease detection and monitoring. Widely used GFR estimates have not been validated in British ethnic minority populations.Methods/design: Iohexol measured GFR will be the reference against which each estimating equation will be compared. The estimating equations will be based upon serum creatinine and/or cystatin C. The eGFR-C study has 5 components:1)A prospective longitudinal cohort study of 1300 adults with stage 3 chronic kidney disease followed for 3 years with reference (measured) GFR and test (estimated GFR [eGFR] and urinary albumin-to-creatinine ratio) measurements at baseline and 3 years. Test measurements will also be undertaken every 6 months. The study population will include a representative sample of south-Asians and African-Caribbeans. People with diabetes and proteinuria (ACR >=30 mg/mmol) will comprise 20-30% of the study cohort.2)A sub-study of patterns of disease progression of 375 people (125 each of Caucasian, Asian and African-Caribbean origin; in each case containing subjects at high and low risk of renal progression). Additional reference GFR measurements will be undertaken after 1 and 2 years to enable a model of disease progression and error to be built.3)A biological variability study to establish reference change values for reference and test measures.4)A modelling study of the performance of monitoring strategies on detecting progression, utilising estimates of accuracy, patterns of disease progression and estimates of measurement error from studies 1), 2) and 3).5)A comprehensive cost database for each diagnostic approach will be developed to enable cost-effectiveness modelling of the optimal strategy.The performance of the estimating equations will be evaluated by assessing bias, precision and accuracy. Data will be modelled as a linear function of time utilising all available (maximum 7) time points compared with the difference between baseline and final reference values. The percentage of participants demonstrating large error with the respective estimating equations will be compared. Predictive value of GFR estimates and albumin-to-creatinine ratio will be compared amongst subjects that do or do not show progressive kidney function decline. The eGFR-C study will provide evidence to inform the optimal GFR estimate to be used in clinical practice.Trial registration: ISRCTN42955626.BMC Nephrology 01/2014; 15(1):13. DOI:10.1186/1471-2369-15-13 · 1.52 Impact Factor
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- "The change in the estimated GFR over time can be used as a reliable guide to true changes in GFR (Padala et al. 2012; Turin et al. 2013). Despite routine automatic eGFR reporting, patients continue to present at a late stage of CKD (UK Renal Registry Report 2012). "
ABSTRACT: Some patients with chronic kidney disease are still referred late for specialist care despite the evidence that earlier detection and intervention can halt or delay progression to end-stage kidney disease (ESKD). To develop a population surveillance system using existing laboratory data to enable early detection of patients at high risk of ESKD by reviewing cumulative graphs of estimated glomerular filtration rate (eGFR). A database was developed, updated daily with data from the laboratory computer. Cumulative eGFR graphs containing up to five years of data are reviewed by clinical scientists for all primary care patients or out-patients with a low eGFR for their age. For those with a declining trend, a report containing the eGFR graph is sent to the requesting doctor. A retrospective audit was performed using historical data to assess the predictive value of the graphs. In nine months, we reported 370,000 eGFR results, reviewing 12,000 eGFR graphs. On average 60 graphs per week were flagged as 'high' or 'intermediate' risk. Patients with graphs flagged as high risk had a significantly higher mortality after 3.5 years and a significantly greater chance of requiring renal replacement therapy after 4.5 years of follow-up. Five patients (7%) with graphs flagged as high risk had a sustained >25% fall in eGFR without evidence of secondary care referral. Feedback about the service from requesting clinicians was 73% positive. We have developed a system for laboratory staff to review cumulative eGFR graphs for a large population and identify patients at highest risk of developing ESKD. Further research is needed to measure the impact of this service on patient outcomes.Journal of Renal Care 09/2013; 39 Suppl 2(S2):23-9. DOI:10.1111/j.1755-6686.2013.12029.x
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- "m2 register in cross-sectional analyses. However, this bias is less with longitudinal measurements, and a recent large trial concluded that eGFR change over time is a reliable measure of CKD progression . To enhance robustness of the analyses, we compared eGRFcreat, eGRFcreat+cysC and eGFRcysC between risk groups. "
ABSTRACT: Background Diabetic nephropathy is a growing clinical problem, and the cause for >40% of incident ESRD cases. Unfortunately, few modifiable risk factors are known. The objective is to examine if albuminuria and history of diabetic nephropathy (DN) in a sibling are associated with early DN progression or mortality. Methods In this longitudinal study of adults >18 yrs with diabetes monitored for up to 9 yrs (mean 4.6 ± 1.7 yrs), 435 subjects at high risk (DN family history) and 400 at low risk (diabetes >10 yrs, normoalbuminuria, no DN family history) for DN progression were evaluated for rate of eGFR change using the linear mixed effects model and progression to ESRD. All-cause mortality was evaluated by Kaplan-Meier analyses while controlling for baseline covariates in a Cox proportional hazards model. Covariates included baseline eGFR, age, gender, race, diabetes duration, blood pressure, hemoglobin A1c and urine albumin:creatinine ratio. Propensity score matching was used to identify high and low risk group pairs with balanced covariates. Sensitivity analyses were employed to test for residual confounding. Results Mean baseline eGFR was 74 ml/min/1.73 m2 (86% of cohort >60 ml/min/1.73 m2). Thirty high risk and no low risk subjects developed ESRD. eGFR decline was significantly greater in high compared to low risk subjects. After controlling for confounders, change in eGFR remained significantly different between groups, suggesting that DN family history independently regulates GFR progression. Mortality was also significantly greater in high versus low risk subjects, but after controlling for baseline covariates, no significant difference was observed between groups, indicating that factors other than DN family history more strongly affect mortality. Analyses of the matched pairs confirmed change in eGFR and mortality findings. Sensitivity analyses demonstrated that the eGFR results were not due to residual confounding by unmeasured covariates of a moderate effect size in the propensity matching. Conclusions Diabetic subjects with albuminuria and family history of DN are vulnerable for early GFR decline, whereas subjects with diabetes for longer than 10 years, normoalbuminuria and negative family history, experience slower eGFR decline, and are extremely unlikely to require dialysis. Although we would not recommend that patients with low risk characteristics be neglected, scarce resources would be more sensibly devoted to vulnerable patients, such as the high risk cases in our study, and preferably prior to the onset of albuminuria or GFR decline.BMC Nephrology 06/2013; 14(1):124. DOI:10.1186/1471-2369-14-124 · 1.52 Impact Factor