Estimating glomerular filtration rate with new equations: can one size ever fit all?

Abstract

Glomerular filtration rate (GFR) is thought to be the best overall indicator of kidney health. On an individual patient basis, a working knowledge of GFR is important to understand the future risk for chronic kidney disease (CKD) progression, enhanced risk for cardiovascular disease and death, and for optimal medical management including the dosing of certain drugs. Although GFR can be directly measured using exogenous compounds that are eliminated by the kidney, these methods are not scalable for repeated and routine use in clinical care. Thus, in most circumstances GFR is estimated, termed estimated GFR (eGFR), using serum biomarkers that are eliminated by the kidney. Of these, serum creatinine, and to a lesser extent cystatin C, are most widely employed. However, the resulting number is simply a population average for an individual of that age and sex with a given serum creatinine and/or cystatin C, while the range of potential GFR values is actually quite large. Thus, it is important to consider characteristics of a given patient that might make this estimate better or worse in a particular case. In some circumstances, cystatin C or creatinine might be the better choice. Ultimately it is difficult, if not impossible, to have an eGFR equation that performs equally well in all populations. Thus, in certain cases it might be appropriate to directly measure GFR for high consequence medical decision-making, such as approval for kidney donation or prior to certain chemotherapeutic regimens. In all cases, the eGFR thresholds of CKD stage should not be viewed as absolute numbers. Thus, clinical care should not be determined solely by CKD stage as determined by eGFR alone, but rather by the combination of an individual patient’s likely kidney function together with their current clinical situation.

Keywords:

• Chronic kidney disease
• creatinine
• cystatin C
• estimated GFR
• glomerular filtration rate

Authors’ contribution

Research conception and design: All authors.

Data acquisition: All authors.

Data analysis and interpretation: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript: All authors.

Supervision: John Lieske

Approval of the final manuscript: All authors.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors reported there is no funding associated with the work featured in this article.