Background: The challenges in the development of new therapeutic agents for Alzheimer’s Disease (AD) become apparent through the high number of failed late phase trials. Despite an increasing interest in biomarkers, cognition remains the primary regulatory accepted clinical outcome. The most frequently used test, ADAS-cog, consists of a broad spectrum of tasks that test different components of cognition. The total ADAS-cog score is obtained by rating a subject’s performance in each of the subtests and summing up the resulting subscores to yield an overall assessment. In turn, pharmacometric models traditionally describe Alzheimer’s disease progression using this summary score. An alternative approach, explored in this work, is to model each subscore separately and link the model subcomponents to a common unobserved variable “cognitive disability”. In psychometrics, this method is used to study the sensitivity of items in standardized educational tests, and the approach is referred to as item response theory (IRT).
Aim: The presentation demonstrates the application of IRT to ADAS-cog score modeling and discusses benefits of this modeling technique.