Statistical analysis of in vitro data for risk assessment - exemplified for a case of Ames test data

Ames test data of experiments with smoke of six cigarette types were used for dose-response analysis and for derivation of a measure of mutagenic potency. Each cigarette type had been tested using a smoking machine and four dilutions of the smoke of each of seven cycles (one to seven cigarettes). Three plates had been exposed per cigarette number/smoke dilution combination and three control plates had been simultaneously exposed to clean air with each set of smoke-exposed plates. It was the aim of the statistical analysis to determine the slopes of dose-response relationships of various cigarette types and to compare them using statistical tests. Basically, the following procedure is recommended: (1) calculate a dose measure on the basis of the number of smoked cigarettes per cycle and dilution air flow. (2) Use the absolute count values of the individual plates as effect variable. (3) Describe the dose-response relations of the individual cigarette types on the basis of all available data with a polynomial model by means of Poisson regression analysis accounting for overdispersion. (4) Identify the linear dose-response region using the likelihood ratio test and restrict the data set to this region. (5) Use the slope of the linear model in the restricted data set as the basis of the mutagenicity measure. (6) Compare the slope for the individual cigarette type with the slope for a reference cigarette by means of multivariate Poisson regression using the likelihood ratio test and accounting for overdispersion. It is finally recommended to express the mutagenic potency as percentages related to the reference cigarette K2R4F. This type of cigarette was set here equal to 100%; the following values are then obtained for some commercially available cigarette types: type A 25%, type B 90%, type C 119%, type D 13%, type E 59%. The differences are statistically significant.