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个体生物等效性测定中的受试者与制剂相互作用:偏差与发生率

Subject-by-formulation interaction in determinations of individual bioequivalence: bias and prevalence.

作者信息

Endrenyi L, Tothfalusi L

机构信息

University of Toronto, Department of Pharmacology, Ontario, Canada.

出版信息

Pharm Res. 1999 Feb;16(2):186-90. doi: 10.1023/a:1018899504711.

Abstract

PURPOSE

  1. To determine properties of the estimated variance component for the subject-by-formulation interaction (sigma D2) in investigations of individual bioequivalence (IBE), and 2, to evaluate the prevalence of interactions in replicate-design studies published by FDA.

METHODS

Four-period crossover studies evaluating IBE were simulated repeatedly. Generally, the true bioequivalence of the two formulations, including sigma D2 = 0, was assumed. sigma D2 was then estimated in a linear mixed-effect model by restricted maximum likelihood (REML). The same method was applied for estimating sigma D2 for the data sets of FDA.

RESULTS

  1. sigma D estimated by REML was positively biased. The bias and dispersion of the estimated sigma D increased approximately linearly with the estimated within-subject standard deviation for the reference formulation (sigma WR). Only a small proportion of the estimated sigma D exceeded the estimated sigma WR. 2. Distributions of the estimated sigma D were evaluated. At sigma WR = 0.30, a level of estimated sigma D = 0.15 was exceeded, by random chance, with a probability of about 25%. 3. Importantly, the behaviour of the sigma D2 values estimated from the FDA data sets was similar to that exhibited by the simulated estimates of sigma D2 which were generated under the conditions of true bioequivalence.

CONCLUSIONS

  1. sigma D estimated by REML is biased; the bias increases proportionately with the estimated sigma WR. Consequently, exceeding a fixed level of sigma D (e.g., 0.15) does not indicate substantial interaction. 2. The data sets of FDA are compatible with the hypothesis of sigma D2 = 0. Consequently, they do not demonstrate the prevalence of subject-by-formulation interaction. Therefore, it could be sufficient and reasonable to evaluate bioequivalence from 2-period crossover studies.
摘要

目的

  1. 确定个体生物等效性(IBE)研究中受试者与制剂相互作用的估计方差分量(σD2)的性质;2. 评估美国食品药品监督管理局(FDA)发表的重复设计研究中相互作用的发生率。

方法

对评估 IBE 的四周期交叉研究进行反复模拟。通常,假定两种制剂的真正生物等效性,包括 σD2 = 0。然后通过限制最大似然法(REML)在线性混合效应模型中估计 σD2。对 FDA 的数据集估计 σD2 采用相同方法。

结果

  1. REML 估计的 σD 存在正偏差。估计的 σD 的偏差和离散度随参比制剂的受试者内标准差估计值(σWR)近似线性增加。估计的 σD 中只有一小部分超过估计的 σWR。2. 对估计的 σD 的分布进行了评估。在 σWR = 0.30 时,估计的 σD = 0.15 的水平因随机因素而被超过的概率约为 25%。3. 重要的是,从 FDA 数据集估计的 σD2 值的行为与在真正生物等效性条件下生成的 σD2 模拟估计值所表现出的行为相似。

结论

  1. REML估计的σD有偏差;偏差随估计的σWR成比例增加。因此,超过固定水平的σD(例如0.

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