Model selection and averaging of nonlinear mixed-effect models for robust phase III dose selection.

ABSTRACT: Population model-based (pharmacometric) approaches are widely used for the analyses of phase IIb clinical trial data to increase the accuracy of the dose selection for phase III clinical trials. On the other hand, if the analysis is based on one selected model, model selection bias can potentially spoil the accuracy of the dose selection process. In this paper, four methods that assume a number of pre-defined model structure candidates, for example a set of dose-response shape functions, and then combine or select those candidate models are introduced. The key hypothesis is that by combining both model structure uncertainty and model parameter uncertainty using these methodologies, we can make a more robust model based dose selection decision at the end of a phase IIb clinical trial. These

SUBMITTER: Aoki Y 

PROVIDER: S-EPMC5686275 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature