The Glomerular Filtration Rate: From the Diagnosis of Kidney Function to a Public Health Tool

The prevalence of chronic kidney disease (CKD) continues to increase worldwide, as well as the associated morbidity and mortality and the consequences on the patients' quality of life and countries' economies. CKD often evolves without being recognized by patients and physicians, although the diagnosis is based on two simple laboratory data: the estimated glomerular filtration rate (eGFR) and urine analysis. To measure GFR, the knowledge about the physiologic processes at the nephron level, the concept of clearance, and the identification of creatinine as a suitable endogenous marker for measuring the creatinine clearance (CrCl) had to be previously developed. On those bases, different equations to calculate CrCl (Cockcroft and Gault, 1976), or estimated GFR (four variables MDRD, 1999; CKD-Epi, 2009, among others) were generated. They all include creatinine and some demographic data, such as sex and age. However, to compare results throughout life or among laboratories, the creatinine determination must be standardized. In addition, the accuracy of these equations remains controversial in certain subgroups of patients. For these reasons, other mathematical models to improve CrCl estimation have been developed, such as when urine cannot be collected, in debilitated elderly patients and patients with trauma, diabetes, or obesity. Currently, eGFR in adults can be measured and reported immediately, using isotope dilution mass spectrometry traceable creatinine-based equations. In conclusion, based on knowledge obtained from renal physiology, eGFR can be used in the clinic for the diagnosis and early treatment of CKD, as well as a public instrument to estimate the prevalence.

Comparison of the Cockcroft-Gault, MDRD and CKD-EPI equations for estimating ganciclovir clearance

AIMS

Accurately estimating kidney function is essential for the safe administration of renally cleared drugs such as ganciclovir. Current practice recommends adjusting renally eliminated drugs according to the Cockcroft-Gault equation. There are no data on the utility of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations in ganciclovir dosing. To evaluate which renal function equation best predicts ganciclovir clearance.

METHODS

The performance of the Cockcroft-Gault equation, isotope dilution mass spectrometry (IDMS)-traceable 4-variable MDRD study (MDRD4-IDMS) equation and CKD-EPI equation in determining ganciclovir clearance were assessed retrospectively in patients treated with ganciclovir from 2004-2015. The MDRD4-IDMS and CKD-EPI equations adjusted to individual body surface area (MDRD4-IDMS·BSA and CKD-EPI·BSA, respectively) were also evaluated. Patients with intravenous ganciclovir peak and trough concentrations in their medical records were included in the study. Ganciclovir clearance was calculated from serum concentrations using a one-compartment model. The five equations were compared based on their predictive ability, the coefficient of determination, through a linear regression analysis. The results were validated in a group of patients.

RESULTS

One hundred patients were included in the final analysis. Seventy-four patients were analysed in the learning group and 26 in the validation group. The coefficient of determination was 0.281 for Cockcroft-Gault, 0.301 for CKD-EPI·BSA, 0.308 for MDRD4-IDMS·BSA, 0.324 for MDRD4-IDMS and 0.360 for CKD-EPI. Subgroup analysis also showed that CKD-EPI is a better predictor of ganciclovir clearance. Analysis of the validation group confirmed these results.

CONCLUSIONS

The CKD-EPI equation correlates better with ganciclovir clearance than the Cockcroft-Gault and MDRD4-IDMS equations, even the clinical difference between the equations is scarce.