Abstract

The objective of this study is to compare and validate three models of flucytosine (5-FC) population pharmacokinetics using three methods of analysis to elucidate which model describes 5-FC pharmacokinetics most accurately and which method is the most suitable for this purpose. Retrospectively, demographic and clinical data of two similar sets of a total of 88 intensive care unit (ICU) patients were gathered for calculation and validation of 5-FC pharmacokinetics respectively. Three pharmacokinetic models were analyzed: a one-compartment with renal elimination (renal model), a one-compartment with renal and metabolic elimination (mixed model), and a two-compartment with renal elimination (two-compartment model). Population pharmacokinetic parameters were calculated using the standard two-stage method (STS), NONMEM, and NPEM. Furthermore, a covariate model was built by NONMEM. Validation of the 10 calculated pharmacokinetic models showed that NONMEM is most suitable for predicting 5-FC population pharmacokinetics. Based upon AIC values, bias and precision, the best results are obtained using a two-compartment model with renal elimination (k(elr) = 0.000858 +/- 0.000143 l/h per mL per min, k12 = 0.0313 +/- 0.0168 h(-1), k21 = 0.0353 +/- 0.0145 h(-1), and Vd = 0.541 +/- 0.084 L/kg; bias = -13.16; 95% CI = -16.77; -9.55; precision = 30.50; 95% CI = 27.47; 33.26) or a two-compartment covariate model as built by NONMEM [Vd (L) = 0.572 x WT, Cl(5FC) (L/h) = 1.69 + 0.0273 x (Cl(cr) (mL/min) - 52.5), k12 = 0.0235 +/- 0.0107 h(-1), and k21 = 0.0375 +/- 0.0147 h(-1); bias = -8.29; 95% CI = -11.63; -4.95; precision = 26.77; 95% CI = 24.24; 29.07]. In conclusion, this study shows that a two-compartment model with renal elimination best describes 5-FC population pharmacokinetics and NONMEM is able to build a two-compartment covariate model that predicts 5-FC levels equally well in our population of ICU patients. Furthermore, NONMEM appeared to be the most suitable method of population pharmacokinetics in our population and for this purpose it offers more reliable and accurate results than NPEM or the STS method.

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