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A semiparametric response surface model for assessing drug interaction.

Kong M, Lee JJ

Department of Biostatistics, University of Texas M.D. Anderson Cancer Center, Unit 447, 1515 Holcombe Boulevard, Houston, Texas 77030, USA.

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.

Published 16 May 2008 in Biometrics, 64(2): 396-405.
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