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Population pharmacokinetics of flucytosine: comparison and validation of three models using STS, NPEM, and NONMEM.

机译:氟胞嘧啶的群体药代动力学:使用STS,NPEM和NONMEM的三个模型的比较和验证。

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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.
机译:本研究的目的是使用三种分析方法比较和验证三种氟胞嘧啶(5-FC)药代动力学模型,以阐明哪种模型最准确地描述了5-FC药代动力学,以及哪种方法最适合此目的。回顾性地,收集了总共88名重症监护病房(ICU)患者的两组相似的人口统计学和临床​​数据,分别用于计算和验证5-FC药代动力学。分析了三种药代动力学模型:具有肾消除功能的一室(肾脏模型),具有肾代谢消除功能的一室(混合模型)和具有肾消除功能的两室(两室模型)。使用标准的两阶段方法(STS),NONMEM和NPEM计算群体的药代动力学参数。此外,NONMEM建立了协变量模型。对10个计算的药代动力学模型的验证表明,NONMEM最适合预测5-FC群体的药代动力学。根据AIC值,偏倚和精度,使用两室模型并消除肾脏(k(elr)= 0.000858 +/- 0.000143 l / h / mL / min,k12 = 0.0313 +/- 0.0168 h,可获得最佳结果(-1),k21 = 0.0353 +/- 0.0145 h(-1)和Vd = 0.541 +/- 0.084 L / kg;偏差= -13.16; 95%CI = -16.77; -9.55;精度= 30.50; 95 %CI = 27.47; 33.26)或由NONMEM建立的两室协变量模型[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),k21 = 0.0375 +/- 0.0147 h(-1);偏差= -8.29; 95%CI = -11.63; -4.95;精度= 26.77; 95%CI = 24.24; 29.07]。总之,这项研究表明,具有肾脏消除功能的两室模型最能说明5-FC人群的药代动力学,NONMEM能够建立两室协变量模型,该模型可以很好地预测我们ICU患者人群中的5-FC水平。此外,NONMEM似乎是我们人群中最合适的人群药代动力学方法,为此,它比NPEM或STS方法提供了更可靠和准确的结果。

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