Statistical analysis of heterogeneous pharmacokinetic data from the literature.
To obtain the reliable pharmacokinetic quantities necessary for the adjustment of individual drug dosages, the pharmacokinetic data in the literature must be analysed by various appropriate statistical methods. Generally, pharmacokinetic quantities have been calculated from small sample sizes and published in different ways (the coefficient of variation of an estimated pharmacokinetic quantity is often higher than 40 percent). In the present study data were therefore structured and clustered according to the important influence variables. The important influence variables were obtained by known multivariate statistical methods. To obtain optimal estimators (uniformly minimum variance unbiased estimators) for the quantities inside the clusters, goodness of fit tests must be performed. Skewed distributions and samples with heterogeneous variances must be subjected to transformation procedures to obtain normally distributed values with homogeneous variances. The population-derived estimate of the a priori knowledge of pharmacokinetic quantities can be obtained by a statistical algorithm proposed in this paper. Information on the quantities half-life, total body clearance and volume of distribution of vancomycin were extracted from over 200 publications. These data were analysed with the proposed statistical algorithm, yielding population-based estimates for half-life, clearance and volume of vancomycin, taking into consideration the detected influence variables--renal function and the age of the patient. Important dependencies between different variables are discussed.
Zellner
D
D
Medical Department, University of Ulm, Germany.
Frankewitsch
T
T
Simon
S
S
Keller
F
F
D000367:Age Factors; D000465:Algorithms; D001827:Body Height; D001835:Body Weight; D003627:Data Interpretation, Statistical; D005260:Female; D006207:Half-Life; D006801:Humans; D008297:Male; D010599:Pharmacokinetics; D014640:Vancomycin / Q000493:pharmacokinetics
D014640:Vancomycin