Karlsson Kristin E, Grahnén Anders, Karlsson Mats O, Jonsson E Niclas
Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Br J Clin Pharmacol. 2007 Sep;64(3):266-77. doi: 10.1111/j.1365-2125.2007.02887.x. Epub 2007 Apr 10.
In the literature, five potential benefits of randomizing clinical trials on concentration levels, rather than dose, have been proposed: (i) statistical study power will increase; (ii) study power will be less sensitive to high variability in the pharmacokinetics (PK); (iii) the power of establishing an exposure-response relationship will be robust to correlations between PK and pharmacodynamics (PD); (iv) estimates of the exposure-response relationship are likely to be less biased; and (v) studies will provide a better control of exposure in situations with toxicity issues. The main aim of this study was to investigate if these five statements are valid when the trial results are evaluated using a model-based analysis.
Quantitative relationships between drug dose, concentration, biomarker and clinical end-point were defined using pharmacometric models. Three randomization schemes for exposure-controlled trials, dose-controlled (RDCT), concentration-controlled (RCCT) and biomarker-controlled (RBCT), were simulated and analysed according to the models.
(i) The RCCT and RBCT had lower statistical power than RDCT in a model-based analysis; (ii) with a model-based analysis the power for an RDCT increased with increasing PK variability; (iii) the statistical power in a model-based analysis was robust to correlations between CL and EC(50) or E(max); (iv) under all conditions the bias was negligible (<3%); and (v) for studies with equal power RCCT could produce either more or fewer adverse events compared with an RDCT.
Alternative randomization schemes may not have the proposed advantages if a model-based analysis is employed.
文献中提出了对临床试验进行浓度水平而非剂量随机化的五个潜在益处：（i）统计研究效能将提高；（ii）研究效能对药代动力学（PK）的高变异性不太敏感；（iii）建立暴露-反应关系的效能对PK和药效学（PD）之间的相关性具有稳健性；（iv）暴露-反应关系的估计可能偏差较小；（v）在存在毒性问题的情况下，研究将能更好地控制暴露。本研究的主要目的是调查当使用基于模型的分析评估试验结果时，这五个说法是否成立。
使用药代动力学模型定义药物剂量、浓度、生物标志物和临床终点之间的定量关系。根据模型模拟并分析了暴露对照试验的三种随机化方案，即剂量对照（RDCT）、浓度对照（RCCT）和生物标志物对照（RBCT）。
（i）在基于模型的分析中，RCCT和RBCT的统计效能低于RDCT；（ii）通过基于模型的分析，RDCT的效能随PK变异性增加而提高；（iii）基于模型的分析中的统计效能对CL与EC(50)或E(max)之间的相关性具有稳健性；（iv）在所有条件下，偏差均可忽略不计（<3%）；（v）对于具有同等效能的研究，与RDCT相比，RCCT可能产生更多或更少的不良事件。
如果采用基于模型的分析，替代随机化方案可能不具有所提出的优势。
