Soy Dolors, Beal Stuart L, Sheiner Lewis B
Department of Biopharmaceutical Sciences, School of Pharmacy, University of California San Francisco, 94143-0626, USA.
Clin Pharmacol Ther. 2004 Nov;76(5):441-51. doi: 10.1016/j.clpt.2004.07.010.
Our objective was to develop a population 1-compartment pharmacokinetic (PK) method of analysis to deal with suspect or missing prior dosage history.
Population PK data from a 1-compartment model with first-order elimination and absorption, described by PK parameters clearance, volume of distribution, and absorption rate constant, are simulated. A PK sample is drawn just before a test dose (Dt), followed by a (varying) number of additional samples over 1 interdose interval (tau). For 60% of the subjects, the true history of the scheduled dose (Ds) preceding Dt differs from that prescribed, whereas doses taken before Ds do not. Two settings are evaluated: considerable accumulation of drug in the body (typical drug half-life t1/2 approximately equal to tau) and very little such accumulation (t1/2 approximately equal to tau/5). Precision and bias of several PK analysis methods--Missing Dose Method (MDM), Missing Dose Mixture Method (MDMM) and Extrapolation-Subtraction Method (ESM), all of which essentially do not use prior dose history--are compared with those of the Prescribed Dose Method (PDM), which assumes nominal dosage, and an Ideal Method (IDM), which uses true (but unknown) pre-test dose history.
At t1/2 approximately equal to tau, MDM and MDMM are the most precise methods. The accuracy of ESM and PDM is poor. At t1/2 approximately equal to tau/5, no significant differences, in terms of precision or bias, are observed between methods. Misspecification of the structural or statistical model seems not to influence these results. The results of analysis of a real (caffeine) data set are compatible with the findings from the simulations.
When a test dose is given and a predose baseline observation is taken as part of an "intensive" PK study during outpatient therapy of a 1-compartment drug, an analysis that assumes that the nominal dose history is correct is not robust to past dosage history misspecification, whereas methods that do not do this are robust and reliable.
我们的目的是开发一种群体一室药代动力学（PK）分析方法，以处理可疑或缺失的既往用药史。
模拟了由清除率、分布容积和吸收速率常数等PK参数描述的具有一级消除和吸收的一室模型的群体PK数据。在给予试验剂量（Dt）之前抽取一个PK样本，随后在1个给药间隔（tau）内采集（数量不等的）额外样本。对于60%的受试者，Dt之前预定剂量（Ds）的真实用药史与规定的不同，而Ds之前服用的剂量则无差异。评估了两种情况：药物在体内有大量蓄积（典型药物半衰期t1/2约等于tau）和几乎没有这种蓄积（t1/2约等于tau/5）。将几种PK分析方法——漏服剂量法（MDM）、漏服剂量混合法（MDMM）和外推-减法（ESM）（这些方法基本上不使用既往用药史）的精密度和偏倚与假定名义剂量的规定剂量法（PDM）以及使用真实（但未知）试验前用药史的理想方法（IDM）进行比较。
在t1/2约等于tau时，MDM和MDMM是最精确的方法。ESM和PDM的准确性较差。在t1/2约等于tau/5时，各方法在精密度或偏倚方面未观察到显著差异。结构或统计模型的错误设定似乎不影响这些结果。对一个真实（咖啡因）数据集的分析结果与模拟结果相符。
当给予试验剂量并在一室药物门诊治疗期间作为“强化”PK研究的一部分进行给药前基线观察时，假定名义剂量史正确的分析方法对过去用药史的错误设定不稳健，而不做此假定的方法则稳健且可靠。
