STATISTICAL-ANALYSIS OF IN-VIVO TUMOR-GROWTH EXPERIMENTS

We review and compare statistical methods for the analysis of in vivo tumor growth experiments. The methods most commonly used are deficient in that they have either low power or misleading type I error rates. We propose a set of multivariate statistical modeling methods that cor rect these problems, illustrating their application with data from a s tudy of the effect of alpha-difluoromethylornithine on growth of the B T-20 human breast tumor in nude mice. All the methods find significant differences between the alpha-difluoromethylornithine dose groups, bu t recommended sample sizes for a subsequent study are much smaller wit h the multivariate methods. We conclude that the multivariate methods are preferable and present guidelines for their use.