Blog entry by Meguid El Nahas
Longitudinal changes in estimated and measured GFR in type 1 diabetes.
Estimation of GFR from serum concentrations of creatinine and cystatin C has been refined using cross-sectional data from large numbers of people. However, the ability of the improved estimating equations to identify changes in GFR within individuals over time has not been rigorously evaluated, particularly within the normal range of GFR. In cross-sectional and longitudinal analyses of 1441 participants in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study with type 1 diabetes, we compared GFRestimated from creatinine (eGFR(Cr)), cystatin C (eGFR(Cys)), or both (eGFR(Cr+Cys)) with iothalamate GFR (iGFR), including changes in each over time. Mean (SD) iGFR was 122.7 (21.0) ml/min per 1.73 m(2). In cross-sectional analyses, eGFR(Cr+Cys) estimated iGFR with the highest correlation (r=0.48 versus 0.39-0.42), precision, and accuracy. In longitudinal analyses, change in eGFR(Cr+Cys) best estimated change in iGFR; however, differences between estimates were small, and no estimate accurately classified change in iGFR. Over a median 23 years of follow-up, mean rate of change in eGFR was similar across estimates of eGFR(Cr), eGFR(Cys), and eGFR(Cr+Cys) (-1.37, -1.11, and -1.29 ml/min per 1.73 m(2) per year, respectively). Associations of BP and hemoglobin A1c with change in eGFR were strongest for eGFR(Cys) and eGFR(Cr+Cys). Together, these results suggest that the addition of cystatin C to creatinine to estimate GFR may improve identification of the causes and consequences of GFR loss in type 1 diabetes, but may not meaningfully improve the tracking of GFR in clinical care.
Comments from Professor Pierre Delanaye:
An extremely interesting study as the authors looked at the patients with type 1 DM with a "normal" GFR (average 123 ml / min) and changes in GFR with time comparing measured GFR to eGFR.
977 patients had GFR measured by iothalamate at least more than once on an average of 3.1 years (average between 1 and 6 years follow-up). The formulas used are those of the CKD-EPI consortium. The results show that all formulations (eGFR) are not suitable to reflect the slope of true GFR decline with time.
Cystatin C based equations brings a little more compared to creatinine based equations but thats probably clinically insignificant.
The most illustrative result seems to me that: 297 patients had a measured GFR that decreased by >15 ml/min.
By contrast:CKD-EPI based on creatinine showed that only 46 patients had a GFR decline of >15 ml/min, CKD-EPI based on cystatin C gave 54 patients and CKD-EPI combining Cr + CysC gave 47 patients.
The agreement between measured GFR and eGFR was poor in terms of revealing individuals with T1DM who had a decline in GFR.
This implies that whilst eGFR formulas may agree with measured GFR to a certain extent in cross-sectional studies, they are very poor in estimating changes in GFR with time.
This important observation confirms a growing body of evidence that the estiamtion of changes in GFR with time whether in longitudinal observational studeis or in interventions clinical trials is misleading.
eGFR in this study serioulsy underestimated patients with progressive decline in kidney function.
This agrees with the observationsmade by Ruggenenti et al in 2012 who showed that in patients with ADPKD the MDRD as well as the CKD EPI eGFR formulas underestimated GFR changes by 50%. The authors stressed that direct kidney function measurements by appropriate techniques are needed to adequately evaluate treatment effects in clinics and research.
It is time to review our underestanding and evaluation of the progression of CKD and related progression intervention trials relying on eGFR, with a critical eye based on the above observations.
Increasingly, I ask myself what is eGFR useful for...????
Not accurate in individuals with normal or near normal GFR as they underestimate true GFR...
Not accurate in CKD4-5 as they overestimate true GFR...
Not accurate in predicting CKD progression as they underestimate progressors...
Not accurate in predicting timing of RRT...
Useless in AKI...
Not very helpful after renal transplantation...
It seems to me that eGFR is only useful for "Spreadsheet Nephrologists/Biostatisticians" who want to publish weak and unvalidated data dressed up as "high science"...in Nephrology journals that are too uncritical to accept their manuscripts...
For me as a clinical nephrologist, I can live happily without eGFR!