title: Design and sample size for evaluating combinations of drugs of linear and loglinear dose-response curves.
abstract: The study of drug combinations has become important in drug development due to its potential for efficacy at lower, less toxic doses and the need to move new therapies rapidly into clinical trials. The goal is to identify which combinations are additive, synergistic, or antagonistic. Although there exists statistical framework for finding doses and sample sizes needed to detect departure from additivity, e.g., the power maximized F-test, different classes of drugs of different does-response shapes require different derivation for calculating sample size and finding doses. Motivated by two anticancer combination studies that we are involved with, this article proposes dose-finding and sample size method for detecting departures from additivity of two drugs with linear and log-linear single dose-response curves. The first study involves combination of two drugs, where one single drug dose-response curve is linear and the other is log-linear. The second study involves combinations of drugs whose single drug dose-response curves are linear. The experiment had been planned with the common fixed ratio design before we were consulted, but the resulting data missed the synergistic combinations. However, the experiment based on the proposed design was able to identify the synergistic combinations as anticipated. Thus we shall summarize the analysis of the data collected according to the proposed design and discuss why the commonly used fixed ratio method failed and the implications of the proposed method for other combination studies.
authors.affiliation: Division of Biostatistics, University of Maryland Greenebaum Cancer Center, Baltimore, Maryland 21201, USA.
authors.forename: Hong-Bin
authors.initials: HB
authors.lastname: Fang
authors.forename: Guo-Liang
authors.initials: GL
authors.lastname: Tian
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.forename: Ming
authors.initials: M
authors.lastname: Tan
mesh_terms: D000704:Analysis of Variance; D000970:Antineoplastic Agents / Q000494:pharmacology* / Q000633:toxicity; D045744:Cell Line, Tumor; D002470:Cell Survival / Q000187:drug effects; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D004357:Drug Synergism; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D012107:Research Design / Q000706:statistics & numerical data*; D018401:Sample Size
chemical_list: D000970:Antineoplastic Agents