Refining vancomycin protein binding estimates: identification of clinical factors that influence protein binding.

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Butterfield JM, Patel N, Pai MP, Rosano TG, Drusano GL, Lodise TP

Refining vancomycin protein binding estimates: identification of clinical factors that influence protein binding.

Antimicrob Agents Chemother. 2011 Sep;55(9):4277-82. doi: 10.1128/AAC.01674-10. Epub 2011 Jun 13.

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21670191 [ View in PubMed
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Abstract

While current data indicate only free (unbound) drug is pharmacologically active and is most predictive of response, pharmacodynamic studies of vancomycin have been limited to measurement of total concentrations. The protein binding of vancomycin is thought to be approximately 50%, but considerable variability surrounds this estimate. The present study sought to determine the extent of vancomycin protein binding, to identify factors that modulate its binding, and to create and validate a prediction tool to estimate the extent of protein binding based on individual clinical factors. This single-site prospective cohort study included hospitalized adult patients treated with vancomycin and with a vancomycin serum concentration determination available. Linear regression was used to predict the free vancomycin concentration (f[vanco]) and to determine the clinical factors modulating vancomycin protein binding. Among the 50 patients in the study, the mean protein binding was 41.5%. The strongest predictor of f[vanco] was the total vancomycin concentration (total [vanco]), and this was modified by dialysis and total protein of >/=6.7 g/dl as covariates. The algebraic expression from the final prediction model was f[vanco] = 0.643 + 0.560 x total [vanco] - {0.067 x total [vanco] x D} - {0.071 x total [vanco] x TP} where D = 1 if dialysis dependent or 0 if not dialysis dependent, and TP = 1 if total protein is >/=6.7 g/dl or 0 if total protein is <6.7 g/dl. The R(2) of the final prediction model was 0.959 (P < 0.001). Validation of our model was performed in 13 patients, and the predictive performance was highly favorable (R(2) was 0.9, and bias and precision were 0.18 and 0.18, respectively). Prediction models such as ours can be utilized in future pharmacokinetics and pharmacodynamics studies evaluating the exposure-response profile and to determine the pharmacodynamic target of interest as it relates to the free concentration.

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