Prediction of Kidney Drug Clearance: A Comparison of Tubular Secretory Clearance and Glomerular Filtration Rate.
2020
BACKGROUND Although proximal tubular secretion is the primary mechanism of kidney drug elimination, current kidney drug dosing strategies are on the basis of eGFR. METHODS In a dedicated pharmacokinetic study to compare GFR with tubular secretory clearance for predicting kidney drug elimination, we evaluated stable outpatients with eGFRs ranging from 21 to 140 ml/min per 1.73 m2. After administering single doses of furosemide and famciclovir (metabolized to penciclovir), we calculated their kidney clearances on the basis of sequential plasma and timed urine measurements. Concomitantly, we quantified eight endogenous secretory solutes in plasma and urine using liquid chromatography-tandem mass spectrometry and measured GFR by iohexol clearance (iGFR). We computed a summary secretion score as the scaled average of the secretory solute clearances. RESULTS Median iGFR of the 54 participants was 73 ml/min per 1.73 m2. The kidney furosemide clearance correlated with iGFR (r=0.84) and the summary secretion score (r=0.86). The mean proportionate error (MPE) between iGFR-predicted and measured furosemide clearance was 30.0%. The lowest MPE was observed for the summary secretion score (24.1%); MPEs for individual secretory solutes ranged from 27.3% to 48.0%. These predictive errors were statistically indistinguishable. Penciclovir kidney clearance was correlated with iGFR (r=0.83) and with the summary secretion score (r=0.91), with similar predictive accuracy of iGFR and secretory clearances. Combining iGFR with the summary secretion score yielded only modest improvements in the prediction of the kidney clearance of furosemide and penciclovir. CONCLUSIONS Secretory solute clearance measurements can predict kidney drug clearances. However, tight linkage between GFR and proximal tubular secretory clearance in stable outpatients provides some reassurance that GFR, even when estimated, is a useful surrogate for predicting secretory drug clearances in such patients.
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