Which Methods for Determining Glomerular Filtration Rate Most Strongly Associate with Risk of Progression of Kidney Disease?

EDITORIAL

Estimation of glomerular filtration rate (eGFR) by measurement of creatinine has become the mainstay approach to clinical assessment of kidney function. eGFR is used for screening for acute kidney injury (AKI), diagnosis and monitoring of chronic kidney disease (CKD), as an indication for initiation of hemodialysis (HD), and for assessment of kidney function in order to determine whether patients can tolerate imaging contrast or whether certain nephrotoxic medicines are safe to administer. Measurement of creatinine and estimation of GFR have thus become one of the most widely used and useful tests in the modern clinical chemistry laboratory.

Renal filtration rate and kidney function was originally measured by administering renally filtered (and not secreted) substances, such as inulin, and measuring their clearance in the urine compared to circulating concentrations. (1) This approach, although accurate, has not been applicable for routine clinical use. In 1948, Jan Brod and Jonas Sirota at New York University College of Medicine proposed that renal filtration rate and function could be evaluated based upon urinary clearance of endogenous creatinine, allowing doctors to measure kidney function without having to administer inulin or other exogenous substances. (2) Their original validation studies demonstrated that renal clearance of endogenous creatinine was approximately equal to that of exogenous inulin, and that creatinine was primarily filtered by the glomerulus and not resorbed or actively secreted. Thus, measuring serum and urine creatinine allowed for a reasonable estimation of renal filtration rate. The only limitation of their method was that it required accurate measurement of urinary creatinine excretion through a 24-hour timed collection of urine, lessening its practicability. In 1976, Cockcroft and Gault proposed that creatinine clearance could instead be estimated based upon circulating creatinine concentrations alone, without measurement of urinary creatinine clearance. (3) This concept was based upon the assumption that most adults produced approximately 1 gram of creatinine per day, and thus instead of directly measuring urinary creatinine excretion rate, they simply assumed all patients excreted similar amounts of creatinine within a 24-hour period. They were aware, however, that a number of factors modify this assumption because of differences in creatinine production rate. In order to accommodate these differences, the Cockcroft-Gault equation included modifiers for age, weight, and gender. In 1999, Levey and other investigators participating in the Modification of Diet in Renal Disease (MDRD) study published a new equation traceable to glomerular filtration rate measured by iothalamate clearance. (4) The new equation expressed glomerular filtration rate as milliliters of blood per minute per 1.73m² of body surface area in order to adjust for expected differences in total creatinine clearance due to differences in size of the patient. The new equation also included an adjustment for African-American patients because of the fact that blacks were known to produce greater amounts of endogenous creatinine on a daily basis. With these modifications and, the MDRD eGFR equation was shown to be a more accurate estimate of GFR than measured creatinine clearance and the Cockcroft-Gault equation. (4) Later, in 2009 Levey and others published an updated equation for estimated GFR (CKD-EPI) which was based upon a larger data set, and which adjusted for age, sex, gender, ethnicity, and also incorporated a spline factor for creatinine values greater or less than 1.0 mg/dL. (5) This equation was shown to be more accurate than MDRD algorithm, particularly in patients with GFR>60 mL/min/1.73m².

Although Cockcroft-Gault, MDRD, and CKD-EPI methods for estimating filtration rate based upon serum creatinine concentration have all been clinically useful approaches, they each suffer from significant bias and frequent discordance between measured and estimated GFR value within individual patients. For example, 19.4% of MDRD values and 15.9% of CKD-EPI estimated values deviate from measured GFR by more than 30%. (5) This drove the need to develop additional biomarker approaches or strategies. Cystatin C is a small molecular weight protein that is constitutively synthesized by most nucleated cells and freely filtered by the glomerulus before being catabolized in the renal tubules. Cystatin C-derived estimated GFR (eGFRcys) has been shown to be significantly more accurate than creatinine-based estimates, and equations which use both creatinine and Cystatin C have been shown to be even more accurate, with only 8.5% of values deviating by more than 30% from measured GFR. (6)

Despite this slow steady progress towards an optimal test for estimation of GFR, the analytical accuracy and reliability of even the best available eGFR methods is still comparatively poor compared to assays used in other clinical areas (e.g. serum electrolytes, albumin, immunoglobulins, troponin T, AST/ALT). It is not unreasonable to expect that diagnostic assays should normally be within 30% of the gold standard value 100% of the time! There may be intrinsic challenges to developing a perfect GFR estimate based upon creatinine or cystatin C measurements, however. Creatinine assays based on the Jaffe method have been shown to be limited in their accuracy and precision. (7) Creatinine- based eGFR measurements may be affected by Asian or Hispanic race, muscular vs. obese body habitus, chronic illness, meatenriched or vegetarian diet. (8) Cystatin C-based eGFR measurements may be affected by corticosteroid use, weight, height, smoking status, the level of C-reactive protein, and relatively common genetic variants of the cystatin C gene. (8, 9) It may be that new renally-excreted candidate biomarkers that accumulate in patients with reduced kidney function should be considered. In this week’s edition of Clinical Chemistry, Freed and colleagues have presented the latest iteration of estimated GFR based upon measurement of a panel of novel circulating serum biomarkers of renal filtration. By taking advantage of the optimal analytical specificity and precision of high performance liquid chromatography and tandem mass spectrometry (LCMS/MS), they have developed an assay for simultaneously measuring four biomarkers that are each independently correlated (positively and negatively) with renal filtration rates. By combining all four markers into a single linear model, they were able to estimate GFR with greater accuracy than creatinine or cystatin C-based methods. Importantly, their method did not show better accuracy than the combined creatinine and cystatin C eGFR estimates, but when creatinine and cystatin C values are also incorporated into their model, it produced the most accurate eGFR values of any of the other approaches (only 7% of values deviating by >30% from measured).

The authors of this well-executed study conclude that their new method may be clinically useful for confirming routine creatinine-based eGFR measurement when the values are close to clinical decision points. Although this is a reasonable suggestion, further studies are needed before this could be recommended in the clinical setting. Since routine measurement by their LCMS/MS assay is currently challenging to implement in most local hospital settings, it could be argued that patients with abnormal eGFR values based upon creatinine measurements alone instead deserve to have their GFR measured directly. Future studies are also needed to understand how this novel biomarker panel may relate to renal physiology, disease progression, how well it predicts clinical adverse outcomes related to kidney disease, and how it may be implemented into routine clinical care. It may be that retention of these specific renally-excreted metabolites are more predictive of clinical outcomes and response to specific therapies. Thus, instead of looking for assays which are best correlated with measured GFR, we should be asking which of the many methods of determining GFR and assessing kidney function are most strongly associated with risk of progression of kidney disease.