STATISTICAL EVALUATION OF UMBRELLA DOSE-RESPONSE RELATIONSHIPS(Categorical Data Analysis)

In the drug development process, it is essential to assess the relationship (mechanism) between dose and response of a biological system following drug administration. This mechanism is known as the "dose-response relationship". Then, dose-response relationships are often evaluated based on a monotonic hypothesis. However, in practice, we may often encounter non-monotonic dose-response relationships, such as the umbrella relationship, which then makes interpretation of the relationships somewhat problematic. In this paper, to assess such umbrella dose-response relationships, the cumulative dose logit model is proposed and applied to an example. To evaluate properties of this model, some Monte-Carlo studies are performed. The results of the cumulative dose logit model are compared with those of the quadratic logit model. This indicates that the cumulative dose logit model provides more stable estimates than the quadratic logit model in estimating the maximum effective dose. It is suggested that the cumulative dose logit model is appropriate for assessing non-monotonic dose-response relationships.