General Principles of GFR Interpretation in the Elderly

In the United States, chronic kidney disease (CKD)—defined by reduced GFR <60 mL/min per 1.73 m2, or presence of kidney damage—is very common in the elderly population. The prevalence of CKD is estimated to be 46.8 percent in those older than 70 years (1). However, the significance of reduced GFR in the elderly has been debated, and some suggest that reduced GFR is secondary to (expected) age-related changes in kidney function and is not evidence of true kidney disease. Regardless of the label, elderly patients with reduced levels of GFR are at higher risk for adverse outcomes and complications, and they require modification of drug dosages. Issues related to the accuracy and interpretation of GFR estimates in the kidney are discussed here.

Accuracy of eGFR in estimating mGFR in elderly

Measured GFR is considered the gold standard for evaluation of kidney function; however, it is difficult to perform in routine practice, and estimated GFR (eGFR) is more commonly used. The estimating equations are developed from serum levels of endogenous filtration markers, such as creatinine or cystatin C, in combination with other variables that act as surrogates for unmeasured non-GFR determinants of the filtration markers. The most commonly used eGFR creatinine equations are the Modification of Diet in Renal Disease (MDRD) study equation and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation (1, 2). The MDRD study equation is widely used, but it underestimates GFR at higher levels, thereby overestimating the prevalence of CKD. The CKD-EPI creatinine equation improves on these limitations for adults of all ages, and the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 guidelines on the evaluation and management of CKD recommends reporting eGFR from creatinine (35).

Creatinine-based eGFR is not always sufficiently accurate for all clinical decision making. For example, it and other filtration markers should not be used in the non–steady state. More importantly, the levels of filtration markers are determined by factors other than GFR. For creatinine, its main non-GFR determinants are muscle mass and protein intake, both of which may be abnormal in the elderly and vary within an individual with changes in health status. For example, in a previously healthy 80-year-old man, a decline in GFR may be masked by weight loss and decreased oral intake. KDIGO recommends the use of a confirmatory test with measured GFR using an exogenous marker, a measured creatinine clearance, or eGFR based on cystatin C in such patients for whom accurate levels of GFR would change management (35).

Recent studies have shown that equations based on the combination of creatinine and cystatin C provide more accuracy and precision in GFR estimation than either alone (68), and this has been demonstrated in at least two elderly populations (mean age 80 years) (9, 10). One of these studies compared the CKD-EPI equations with other equations also developed using standardized assays for creatinine and cystatin C and showed that the CKD-EPI creatinine, cystatin C, and combined creatinine-cystatin C equations were better than or equivalent to other equations, supporting the KDIGO recommendation to use CKD-EPI equations in the elderly population (9).

Use of GFR estimates in the elderly population

Estimates of GFR are commonly used in practice to detect CKD, evaluate the progression of kidney disease, predict a patient’s prognosis, and determine the level of kidney function for drug dosing.

Detection of CKD

The use of more accurate equations leads to more accurate detection and staging of CKD. A large meta-analysis of diverse populations from the Chronic Kidney Disease-Prognosis Consortium (CKD-PC) found that the CKD-EPI creatinine equation more accurately classified individuals into the correct GFR stages than did the MDRD study equation in the general population and in the subgroup with ages ≥65 years (11). Similarly, another meta-analysis of similar cohorts showed that the CKD-EPI creatinine–cystatin C and cystatin C equations reclassified patients with CKD more accurately than did the CKD-EPI creatinine equation in the general population and in the subgroup with ages ≥65 years (12).

Assessment of progression

Change in GFR is the primary way in which progression of kidney disease is evaluated. Despite concerns that changes in GFR may not be sufficiently accurate in the elderly, given possible changes in non-GFR determinants, two large meta-analyses showed that declines in eGFR had strong and consistent associations with subsequent kidney failure and mortality, and these associations were consistent across different ages and with other clinical characteristics (13, 14).

Prediction of prognosis

Lower eGFR levels are associated with risk for adverse events such as cardiovascular disease (CVD), mortality, and ESRD. Data from CKD-PC showed that risk for all outcomes increased at levels below 75 mL/min/1.73 m2 (15). In a subsequent publication, CKD-PC showed a significant positive interaction between age and GFR for all-cause mortality and CVD mortality, suggesting that lower eGFR had stronger adverse effects at younger ages and weaker effects at older ages (16). Nevertheless, GFR <60 mL/min/1.73 m2 remains a significant risk factor for mortality and ESRD in older age. Of note, the absolute risk for mortality and CVD mortality with low eGFR was much higher at older age than in younger age categories, and in the elderly population consideration of both absolute and relative risks is critical to understanding risk factors.

Risk for other comorbid conditions

Several studies have demonstrated that lower GFR in old adults is associated with risk for bloodstream infection (17), global cognitive performance (18, 19), and frailty and diminished physical function in the elderly (2022). These are strongly related to patient safety because they increase the risk of falls, disability, and worsening comorbidities and are important determinants of quality of life and longevity.

Dose adjustment of medication

Older adults are at a higher risk for the development of advanced diseases and comorbidities and, as such, frequently require multiple medications. KDIGO recommends that prescribers use the most accurate method for GFR estimation when drug dosing. The Cockcroft and Gault equation is inaccurate in the era of standardized creatinine assays and is no longer recommended for use (23, 24). Many still use that equation with the misconception that the use of weight overcomes the limitation of creatinine generation, but it does not; in fact, the sharp decline in eGFR with age (i.e., the “140-age” term) that occurs with the Cockcroft and Gault equation leads to a large underestimation of GFR in the very old.


The GFR is fundamental to understanding the nature and severity of kidney disease. There is now solid evidence that eGFR is accurate in the elderly and is appropriate to use to detect and stage CKD, to determine the prognosis and complications of CKD, and to determine the dosing of medications. Creatinine-based estimates are the first-line test and should be confirmed by clearance measurements of cystatin-based estimates of mGFR in appropriate clinical circumstances.



Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150:604–612.


Levey AS, et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999; 130:461–470.


Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013; 3:1–150.


Levey AS, Becker C, Inker LA. Glomerular filtration rate and albuminuria for detection and staging of acute and chronic kidney disease in adults: a systematic review. JAMA 2015; 313:837–846.


Inker LA, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014; 63:713–735.


Inker LA, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367:20–29.


Anderson AH, et al. Estimating GFR among participants in the Chronic Renal Insufficiency Cohort (CRIC) Study. Am J Kidney Dis 2012; 60:250–261.


Schaeffner ES, et al. Two novel equations to estimate kidney function in persons aged 70 years or older. Ann Intern Med 2012; 157:471–481.


Fan L, et al. Comparing GFR estimating equations using cystatin C and creatinine in elderly individuals. J Am Soc Nephrol 2014 [Epub ahead of print].


Kilbride HS, et al. Accuracy of the MDRD (Modification of Diet in Renal Disease) study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly. Am J Kidney Dis 2013; 61:57–66.


Matsushita K, et al. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate. JAMA 2012; 307:1941–1951.


Shlipak MG, et al. Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med 2013; 369:932–943.


Lambers Heerspink HJ, et al. GFR decline and subsequent risk of established kidney outcomes: a meta-analysis of 37 randomized controlled trials. Am J Kidney Dis 2014; 64:860–866.


Coresh J, et al. Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality. JAMA 2014; 311:2518–2531.


Matsushita K, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010; 375:2073–2081.


Hallan SI, et al. Age and association of kidney measures with mortality and end-stage renal disease. JAMA 2012; 308:2349–2360.


James MT, et al. Risk of bloodstream infection in patients with chronic kidney disease not treated with dialysis. Arch Intern Med 2008; 168:2333–2339.


Yaffe K, et al. Higher levels of cystatin C are associated with worse cognitive function in older adults with chronic kidney disease: the chronic renal insufficiency cohort cognitive study. J Am Geriatr Soc 2014; 62:1623–1629.


Kurella M, et al. Cognitive impairment in chronic kidney disease. J Am Geriatr Soc 2004; 52:1863–1869.


Greco A, et al. Frailty, disability and physical exercise in the aging process and in chronic kidney disease. Kidney Blood Press Res 2014; 39:164–168.


Kim JC, Kalantar-Zadeh K, Kopple JD. Frailty and protein-energy wasting in elderly patients with end stage kidney disease. J Am Soc Nephrol 2013; 24:337–351.


Anand S, Johansen KL, Kurella Tamura M. Aging and chronic kidney disease: the impact on physical function and cognition. J Gerontol A Biol Sci Med Sci 2014; 69:315–322.


Stevens LA, Levey AS. Use of the MDRD study equation to estimate kidney function for drug dosing. Clin Pharmacol Ther 2009; 86:465–467.


National Kidney Disease Educational Program. CKD and Drug Dosing: Information for Providers. Accessed May 22, 2015.