Use of estimated glomerular filtration rate for drug dosing in the chronic kidney disease patient

Curr Opin Nephrol Hypertens. 2011 Sep;20(5):482-91. doi: 10.1097/MNH.0b013e328348c11f.

Abstract

Purpose of review: Assessment of kidney function is necessary to stage chronic kidney disease (CKD) and appropriately dose medications. The Cockcroft-Gault equation provides an estimate of creatinine clearance (eClCr) and is the method commonly referenced in pharmacokinetic studies. The Modification of Diet in Renal Disease (MDRD) and CKD-Epidemiology Collaboration (EPI) equations provide an estimate of glomerular filtration rate (eGFR), with the MDRD eGFR now automatically reported by most clinical laboratories. This review describes the differences in the Cockcroft-Gault, MDRD, and CKD-EPI equations and considerations when applying estimates from these equations for drug dosing.

Recent findings: Studies evaluating drug-dosing regimens using eClCr and eGFR differ in their results depending on the population in which the equation is applied, the adjustment factors used to account for body size, and the number of dosing levels for a particular medication. The largest study to evaluate drug regimen design by method concluded that either the eGFR or Cockcroft-Gault estimates could be used for drug dosing. Differences in methodology among studies are a key factor in evaluating these results and will be highlighted in this review.

Summary: The Cockcroft-Gault, MDRD, and CKD-EPI equations provide reasonable estimates of kidney function; however, clinicians must understand the limitations when using these estimates for drug regimen design.

Publication types

  • Review

MeSH terms

  • Age Factors
  • Biomarkers / blood
  • Body Surface Area
  • Body Weight
  • Chronic Disease
  • Creatinine / blood
  • Drug Dosage Calculations*
  • Glomerular Filtration Rate*
  • Humans
  • Kidney / physiopathology*
  • Kidney Diseases / blood
  • Kidney Diseases / diagnosis*
  • Kidney Diseases / physiopathology
  • Models, Biological*
  • Pharmacokinetics
  • Predictive Value of Tests
  • Severity of Illness Index

Substances

  • Biomarkers
  • Creatinine