Joyce Hu, PharmD, University of Minnesota College of Pharmacy
The National Kidney Foundation (NKF) Workgroup strongly advocates for a paradigm shift in how clinicians assess kidney function for medication dosing. They urge shifting away from reliance on the long-established Cockcroft-Gault estimated creatinine clearance (C-G eCrCl) and instead prioritizing race-free estimated glomerular filtration rate (eGFR) equations to guide medical decision-making. They also urge that the eGFR should be individualized using the patient’s body surface area (BSA) to provide the most accurate medication dosing, particularly when a patient’s BSA differs significantly from the standardized value.
This recommendation is supported by a robust body of scientific evidence highlighting the limitations of the Cockcroft-Gault eCrCl equation. Originally developed using data from 249 white males, the C-G equation has never been validated for the diverse patient populations it is regularly applied to. Additionally, it was formulated before the standardization of serum creatinine (SCr) assays, and since modern standardized assays yield average SCr values that are roughly 12% lower, the C-G equation produces skewed results that cannot easily be accounted for. Furthermore, kidney function equations that include race as a variable (black vs. non-black) can be less reliable given that race is a social- not biological- construct, and this dichotomous approach fails to recognize diversity within and among racial groups as well as perpetuates systemic racism. Due to these flaws, a 2021 NKF and American Society of Nephrology (ASN) taskforce recommended three race-free Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations utilizing SCr and/or cystatin C. The Food and Drug Administration (FDA) has mirrored this shift, updating its 2024 industry guidance to recommend eGFR over C-G eCrCL for pharmacokinetic studies.
While adopting eGFR is a necessary step forward, its clinical application requires a crucial adjustment. By default, laboratories report eGFR as a "standardized" value, normalized to an average body surface area of 1.73 m² (expressed as mL/min/1.73 m²). Large retrospective studies demonstrate that standardized eGFR significantly underestimates actual kidney function in patients with high BSAs and overestimates it in those with low BSAs. The use of a standardized value for medication dosing can lead to inaccuracies for patients whose BSAs significantly deviate from the average. To correct these discrepancies and ensure accurate dosing, clinicians must "de-standardize" the eGFR by multiplying it by the patient's actual BSA and dividing by 1.73, yielding an individualized eGFR expressed in mL/min. This can prevent accidental underdosing in patients with obesity and overdosing in underweight patients.
As medication experts, pharmacists are uniquely positioned to champion this paradigm shift within their institutions. Moving away from the deeply ingrained C-G eCrCL equation requires systematically updating clinical protocols and utilization of external tools, such as the NKF eGFR calculator, as many electronic health records are not built to calculate an individualized eGFR. In cases where historical drug labeling creates discordant dosing recommendations between C-G eCrCL and newer eGFR equations, pharmacists will need to exercise clinical judgment, evaluate the individual patient's condition, and employ therapeutic drug monitoring when necessary. By actively leading this transition and navigating its clinical nuances, pharmacists can play a vital role in ensuring that medication dosing remains safe, effective, and aligned with the most current evidence-based standards.
Published on June 30, 2026
References
- St Peter WL, Bzowyckyj AS, Anderson-Haag T, et al. Moving forward from Cockcroft-Gault creatinine clearance to race-free estimated glomerular filtration rate to improve medication-related decision-making in adults across healthcare settings: A consensus of the National Kidney Foundation Workgroup for Implementation of Race-Free eGFR-Based Medication-Related Decisions. Am J Health Syst Pharm. 2025;82(12):644-659. doi:10.1093/ajhp/zxae317