Limited Sampling Strategies to Estimate the Area under the Concentration-time Curve
Limited Sampling Strategies to Estimate the Area under the Concentration-time Curve
复制标题
估计浓度-时间曲线下面积的有限采样策略
DOI：
--
复制
发表时间：
2012
影响因子：
1.7
通讯作者：
Y. Morishita
中科院分区：
文献类型：
--
作者：
H. Tsuruta;M. Fukumoto;L. Bax;A. Kohno;Y. Morishita
摘要背景：已经提出了超过100种有限采样策略（LSS），以减少估计浓度-时间曲线下面积（AUC）所需的血样数量。这些战略成功或失败的条件仍有待澄清。目的：我们研究现有的LSS的精度在理论上和数值模拟的Monte Carlo模拟。我们还提出了两种新的方法，更准确的AUC估计。研究方法：我们从理论上评估了以下现有的方法：i）非线性曲线拟合算法（NLF），ii）指数曲线近似（TZE）和iii）多元线性回归（MLR）的Zerozium规则。以白消安（BU）为受试药物，根据确定的BU药代动力学参数分布，建立了一组理论浓度-时间曲线，并利用这些虚拟验证曲线对现有的LSS进行了重新评价。根据评估结果，我们改进了TZE，以便不使用不切实际的参数值。我们还提出了一种新的估计方法，其中最可能的曲线是从一组预先生成的理论浓度-时间曲线中选择的。结果如下：我们基于临床特征和虚拟验证集的评估显示：i）NLF有时高估了吸收速率常数Ka，ii）当Ka较小时，TZE高估了AUC超过280%，以及iii）当消除速率常数Ke较小时，MLR低估了AUC超过30%。小。这些结果与我们对这些方法的数学评价是一致的。相比之下，我们的两种新方法具有较小的偏差和良好的精度。结论：我们的调查显示，现有的LSS诱导不同的，但具体的偏差在AUC的估计。我们的两个新的LSS，一个修改的TZE和一个使用模型浓度-时间曲线，提供了准确和精确的AUC估计。
Summary Background: Over 100 limited sampling strategies (LSSs) have been proposed to reduce the number of blood samples necessary to estimate the area under the concentration-time curve (AUC). The conditions under which these strategies succeed or fail remain to be clarified. Objectives: We investigated the accuracy of existing LSSs both theoretically and numerically by Monte Carlo simulation. We also proposed two new methods for more accurate AUC estimations. Methods: We evaluated the following existing methods theoretically: i) nonlinear curve fitting algorithm (NLF), ii) the trapezium rule with exponential curve approximation (TZE), and iii) multiple linear regression (MLR). Taking busulfan (BU) as a test drug, we generated a set of theoretical concentration-time curves based on the identified distribution of pharmacokinetic parameters of BU and re-evaluated the existing LSSs using these virtual validation profiles. Based on the evaluation results, we improved the TZE so that unrealistic parameter values were not used. We also proposed a new estimation method in which the most likely curve was selected from a set of pre-generated theoretical concentration-time curves. Results: Our evaluation, based on clinical profiles and a virtual validation set, revealed: i) NLF sometimes overestimated the absorption rate constant Ka, ii) TZE overestimated AUC over 280% when Ka is small, and iii) MLR underestimated AUC over 30% when the elimination rate constant Ke is small. These results were consistent with our mathematical evaluations for these methods. In contrast, our two new methods had little bias and good precision. Conclusions: Our investigation revealed that existing LSSs induce different but specific biases in the estimation of AUC. Our two new LSSs, a modified TZE and one using model concentration-time curves, provided accurate and precise estimations of AUC.
影响因子：
158.5
作者：
SANTOS, GW;TUTSCHKA, PJ;YEAGER, AM
通讯作者：
YEAGER, AM
药代动力学有限采样模型对于儿童癌症药物开发的重要性。
DOI：
--
发表时间：
2003
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research.
影响因子：
--
作者：
Panetta,JCarl;Iacono,LisaC;Adamson,PeterC;Stewart,ClintonF
通讯作者：
Stewart,ClintonF