4.3 Review

A Comprehensive Review on the Predictive Performance of the Sheiner-Tozer and Derivative Equations for the Correction of Phenytoin Concentrations

期刊

ANNALS OF PHARMACOTHERAPY
卷 50, 期 4, 页码 311-325

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/1060028016628166

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Sheiner-Tozer; phenytoin; precision and bias determination

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Objective: In settings where free phenytoin concentrations are not available, the Sheiner-Tozer equationCorrected total phenytoin concentration = Observed total phenytoin concentration/[(0.2 x Albumin) + 0.1]; phenytoin in mu g/mL, albumin in g/dLand its derivative equations are commonly used to correct for altered phenytoin binding to albumin. The objective of this article was to provide a comprehensive and updated review on the predictive performance of these equations in various patient populations. Data Sources: A literature search of PubMed, EMBASE, and Google Scholar was conducted using combinations of the following terms: Sheiner-Tozer, Winter-Tozer, phenytoin, predictive equation, precision, bias, free fraction. Study Selection and Data Extraction: All English-language articles up to November 2015 (excluding abstracts) were evaluated. Data Synthesis: This review shows the Sheiner-Tozer equation to be biased and imprecise in various critical care, head trauma, and general neurology patient populations. Factors contributing to bias and imprecision include the following: albumin concentration, free phenytoin assay temperature, experimental conditions (eg, timing of concentration sampling, steady-state dosing conditions), renal function, age, concomitant medications, and patient type. Although derivative equations using varying albumin coefficients have improved accuracy (without much improvement in precision) in intensive care and elderly patients, these equations still require further validation. Conclusions: Further experiments are also needed to yield derivative equations with good predictive performance in all populations as well as to validate the equations' impact on actual patient efficacy and toxicity outcomes. More complex, multivariate predictive equations may be required to capture all variables that can potentially affect phenytoin pharmacokinetics and clinical therapeutic outcomes.

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