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用于分析失真药效学数据的模拟

Simulation for the analysis of distorted pharmacodynamic data.

作者信息

Hashimoto Y, Ozaki J, Koue T, Odani A, Yasuhara M, Hori R

机构信息

Department of Pharmacy, Kyoto University Hospital, Kyoto University, Japan.

出版信息

Pharm Res. 1994 Apr;11(4):545-8. doi: 10.1023/a:1018918600265.

Abstract

A simulation study was conducted to compare the performance of alternative approaches for analyzing the distorted pharmacodynamic data. The pharmacodynamic data were assumed to be obtained from the natriurertic peptide-type drug, where the diuretic effect arises from the hyperbolic (Emax) dose-response model and is biased by the dose-dependent hypotensive effect. The nonlinear mixed effect model (NONMEM) method enabled assessment of the effects of hemodynamics on the diuretic effects and also quantification of intrinsic diuretic activities, but the standard two-stage (STS) and naive pooled data (NPD) methods did not give accurate estimates. Both the STS and the NONMEM methods performed well for unbiased data arising from a one-compartment model with saturable (Michaelis-Menten) elimination, whereas the NPD method resulted in inaccurate estimates. The findings suggest that nonlinearity and/or bias problems result in poor estimation by NPD and STS analyses and that the NONMEM method is useful for analyzing such nonlinear and distorted pharmacodynamic data.

摘要

进行了一项模拟研究,以比较分析失真药效学数据的替代方法的性能。假设药效学数据是从利钠肽类药物获得的,其中利尿作用源于双曲线(Emax)剂量反应模型,并受到剂量依赖性降压作用的影响而产生偏差。非线性混合效应模型(NONMEM)方法能够评估血流动力学对利尿作用的影响,并对内在利尿活性进行量化,但标准两阶段(STS)和单纯合并数据(NPD)方法无法给出准确估计值。对于具有饱和(米氏)消除的一室模型产生的无偏数据,STS和NONMEM方法均表现良好,而NPD方法导致估计不准确。研究结果表明,非线性和/或偏差问题导致NPD和STS分析的估计效果不佳,且NONMEM方法对于分析此类非线性和失真的药效学数据很有用。

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