Statistical analysis of skin tumor data from Tg.AC mouse bioassays.

New strategies for identifying chemical carcinogens and assessing risk have been proposed based on the Tg.AC (zetaglobin promoted v-Ha-ras) transgenic mouse. Preliminary studies suggest that the Tg. AC mouse bioassay may be an effective means of quickly evaluating the carcinogenic potential of a test agent. The skin of the Tg.AC mouse is genetically initiated, and the induction of epidermal papillomas in response to dermal or oral exposure to a chemical agent acts as a reporter phenotype of the activity of the test chemical. In Tg.AC mouse bioassays, the test agent is typically applied topically for up to 26 weeks, and the number of papillomas in the treated area is counted weekly. Statistical analyses are complicated by within-animal and serial dependency in the papilloma counts, survival differences between animals, and missing data. In this paper, we describe a statistical model for the analysis of skin tumor data from a Tg.AC mouse bioassay. The model separates effects on papilloma latency and multiplicity and accommodates important features of the data, including variability in expression of the transgene and dependency in the tumor counts. Methods are described for carcinogenicity testing and risk assessment. We illustrate our approach using data from a study of the effect of 2,3,7, 8-tetrachlorodibenzo-p-dioxin (TCDD) exposure on tumorigenesis.

Duke Scholars

Author David B. Dunson Statistical Science