School of Pharmacy, University of Otago, PO Box 56, Dunedin 9054, New Zealand.
Br J Clin Pharmacol. 2011 Jun;71(6):807-14. doi: 10.1111/j.1365-2125.2010.03891.x.
The population analysis approach is an important tool for clinical pharmacology in aiding the dose individualization of medicines. However, due to their statistical complexity the clinical utility of population analyses is often overlooked. One of the key reasons to conduct a population analysis is to investigate the potential benefits of individualization of drug dosing based on patient characteristics (termed covariate identification). The purpose of this review is to provide a tool to interpret and extract information from publications that describe population analysis. The target audience is those readers who are aware of population analyses but have not conducted the technical aspects of an analysis themselves. Initially we introduce the general framework of population analysis and work through a simple example with visual plots. We then follow-up with specific details on how to interpret population analyses for the purpose of identifying covariates and how to interpret their likely importance for dose individualization.
群体分析方法是临床药理学中辅助个体化用药的重要工具。然而,由于其统计学的复杂性,群体分析的临床实用性往往被忽视。进行群体分析的一个主要原因是研究基于患者特征的药物剂量个体化的潜在益处(称为协变量识别)。本综述的目的是提供一种工具,用于解释和提取描述群体分析的出版物中的信息。目标读者是那些已经了解群体分析但尚未自己进行分析技术方面的读者。我们首先介绍群体分析的一般框架,并通过可视化图进行简单示例。然后,我们将详细介绍如何解释群体分析以识别协变量,以及如何解释它们对剂量个体化的可能重要性。