Original Investigation
Pathogenesis and Treatment of Kidney Disease
Comparison of Drug Dosing Recommendations Based on Measured GFR and Kidney Function Estimating Equations

https://doi.org/10.1053/j.ajkd.2009.03.008Get rights and content

Background

Kidney disease alters the pharmacokinetic disposition of many medications, requiring dosage adjustment to maintain therapeutic serum concentrations. The Cockcroft-Gault (CG) equation is used for pharmacokinetic studies and drug dosage adjustments, but the Modification of Diet in Renal Disease (MDRD) Study equation is more accurate and more often reported by clinical laboratories than the CG equation.

Study Design

Diagnostic test study.

Settings & Participants

Pooled data set for 5,504 participants from 6 research studies and 4 clinical populations with measured glomerular filtration rate (GFR).

Index Test

Estimated kidney function using the MDRD Study and CG equations incorporating actual (CG) or ideal body weight (CGIBW) and standardized serum creatinine concentrations.

Reference Test

Measured GFR assessed by using iodine-125–iothalamate urinary clearance.

Outcome

Concordance of assigned kidney function categories designated by the Food and Drug Administration (FDA) Guidance for Industry for pharmacokinetic studies and recommended dosages of 15 medications cleared by the kidneys.

Results

Concordance of kidney function estimates with measured GFR for FDA-assigned kidney function categories was 78% for the MDRD Study equation compared with 73% for the CG equation (P < 0.001) and 66% for the CGIBW equation (P < 0.001). Concordance between the MDRD Study equation and CG and CGIBW equations was 78% and 75%, respectively (P < 0.001). Concordance of kidney function estimates with measured GFR for recommended drug dosages was 88% for MDRD Study equation compared with 85% for the CG equation (P < 0.001) and 82% for the CGIBW equation (P < 0.001), with lower concordance when dosing recommendations for drugs included narrow GFR ranges. Concordance rates between the CG and CGIBW equations and MDRD Study equation were 89% and 88%, respectively (P < 0.05).

Limitations

Results based on simulation rather than pharmacokinetic studies. Outcome was drug dosage recommendations, rather than observed drug efficacy and safety.

Conclusions

The MDRD Study equation can also be used for pharmacokinetic studies and drug dosage adjustments. As more accurate GFR-estimating equations are developed, they should be used for these purposes.

Section snippets

Sources of Data

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) is a research group formed to develop and validate improved estimating equations for GFR by pooling data from research studies and clinical populations (hereafter referred to as “studies”), which include individuals with diverse clinical characteristics with and without kidney disease across a wide range of GFRs. Methods for identification of and inclusion criteria for these studies have been previously described.2 The population

Study Population

Clinical characteristics of the 5,504 participants included in the study population are listed in Table 2. Mean age of the cohort is 47 ± 15 years. Approximately a third of the cohort was African American, a similar number had diabetes, and 5% were kidney transplant recipients. Mean measured GFR was 75 ± 44 mL/min; eGFR from the MDRD Study equation and estimated creatinine clearances from the CG and CGIBW equations were 69 ± 38, 75 ± 42, and 62 ± 36 mL/min, respectively. All pairwise

Discussion

Accurate estimates of kidney function are essential for optimal dosing of drugs cleared by the kidney. Overestimates of kidney function may lead to administration of inappropriately large doses and possible toxicity, and conversely, underestimates may lead to subtherapeutic dosing, treatment failures, and prolonged illness. In this study, we showed that the MDRD Study equation had the greatest rate of concordance with measured GFR for both assignment of kidney function categories recommended by

Acknowledgements

A list of the Investigators of CKD-EPI Aims 1 and 2, organized by institution, follows. Tufts Medical Center, Boston, MA: Andrew S. Levey, MD; Lesley A. Stevens, MD, MS; Christopher H. Schmid, PhD; and Yaping (Lucy) Zhang, MS. Cleveland Clinic Foundation, Cleveland, OH: Frederick Van Lente, PhD; and Liang Li, PhD. University of Utah, Salt Lake City, UT: Tom Greene, PhD. Johns Hopkins University, Baltimore, MD: Josef Coresh, MD, PhD, MHS; Jane Manzi, PhD; Brad Astor, PhD, MPH; and Elizabeth

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    Originally published online as doi: 10.1053/j.ajkd.2009.03.008 on May 18, 2009.

    A list of the CKD-EPI investigators and collaborators appears at the end of this article.

    Because an author of this manuscript is an editor for AJKD, the peer-review and decision-making processes were handled entirely by an Associate Editor (Kamal Badr, MD, Lebanese American University) who served as Acting Editor-in-Chief. Details of the journal's procedures for potential editor conflicts are given in the Editorial Policies section of the AJKD website.

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