Kong Maiying, Lee J Jack
Department of Biostatistics, University of Texas M.D. Anderson Cancer Center, Unit 447, 1515 Holcombe Boulevard, Houston, Texas 77030, USA.
Biometrics. 2008 Jun;64(2):396-405. doi: 10.1111/j.1541-0420.2007.00882.x. Epub 2007 Sep 26.
When multiple drugs are administered simultaneously, investigators are often interested in assessing whether the drug combinations are synergistic, additive, or antagonistic. Existing response surface models are not adequate to capture the complex patterns of drug interactions. We propose a two-component semiparametric response surface model with a parametric function to describe the additive effect of a combination dose and a nonparametric function to capture the departure from the additive effect. The nonparametric function is estimated using the technique developed in thin plate splines, and the pointwise bootstrap confidence interval for this function is constructed. The proposed semiparametric model offers an effective way of formulating the additive effect while allowing the flexibility of modeling a departure from additivity. Example and simulations are given to illustrate that the proposed model provides an excellent estimation for different patterns of interactions between two drugs.
当同时使用多种药物时,研究人员通常有兴趣评估药物组合是协同、相加还是拮抗的。现有的响应面模型不足以捕捉药物相互作用的复杂模式。我们提出了一种双组分半参数响应面模型,该模型具有一个参数函数来描述联合剂量的相加效应,以及一个非参数函数来捕捉与相加效应的偏差。使用薄板样条中开发的技术估计非参数函数,并构建该函数的逐点自助置信区间。所提出的半参数模型提供了一种有效的方法来制定相加效应,同时允许对偏离相加性进行灵活建模。给出了实例和模拟,以说明所提出的模型为两种药物之间不同的相互作用模式提供了出色的估计。