Lee J Jack, Kong Maiying
Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX (
Stat Biopharm Res. 2009 Feb 1;1(1):4-17. doi: 10.1198/sbr.2009.0001.
Studies of interactions among biologically active agents have become increasingly important in many branches of biomedical research. We consider that the Loewe additivity model is one of the best general reference models for defining drug interactions. Based on the Loewe additivity model, synergy occurs when the interaction index is less than one, and antagonism occurs when interaction index is greater than one. Starting from the Loewe additivity model and the marginal dose-effect curve for each drug involved in a combination, we first present a procedure to estimate the interaction index and its associated confidence interval at a combination dose with observed effects. Following Chou and Talalay's method for assessing drug interaction based on the plot of interaction indices versus effects for combination doses at a fixed ray, we then construct a pointwise (1-alpha)x100% confidence bound for the curve of interaction indices versus effects. We found that these methods work better on the logarithm transformed scale than on the untransformed scale of the interaction index. We provide simulations and case studies to illustrate the performances of these two procedures, and present their pros and cons. We also provide S-Plus/R code to facilitate the implementation of these two procedures.
生物活性物质之间相互作用的研究在生物医学研究的许多分支中变得越来越重要。我们认为Loewe加和模型是定义药物相互作用的最佳通用参考模型之一。基于Loewe加和模型，当相互作用指数小于1时会出现协同作用，而当相互作用指数大于1时会出现拮抗作用。从Loewe加和模型以及组合中每种药物的边际剂量效应曲线出发，我们首先提出一种在具有观察效应的组合剂量下估计相互作用指数及其相关置信区间的方法。按照Chou和Talalay基于固定射线上组合剂量的相互作用指数与效应的关系图评估药物相互作用的方法，我们随后构建了相互作用指数与效应曲线的逐点(1-α)×100%置信界。我们发现这些方法在相互作用指数的对数变换尺度上比在未变换尺度上效果更好。我们提供模拟和案例研究来说明这两种方法的性能，并阐述它们的优缺点。我们还提供S-Plus/R代码以方便这两种方法的实施。
