Alzheimer's disease (AD) is characterized by a progressive decline in cognition and daily function, leading to a greater need for caregiver support. Clinical disease is segmented into a preclinical stage, mild cognitive impairment, and mild, moderate, and severe stages of Alzheimer's dementia. Although AD trials enroll participants at various stages of illness, treatment efficacy is often assessed using endpoints based on measures of outcomes that are held fixed across disease stages. We hypothesize that matching the primary outcomes measured in the endpoint hierarchy to the stage of disease targeted by the trial will increase the likelihood of detecting true treatment benefits.
We discuss current approaches to assessing clinical outcomes in AD trials, followed by a consideration of how effect detection can be improved by linking the stage of AD to the endpoints that most likely reflect stage-specific disease progression.
Failing to account for stage-specific relevance and sensitivity of clinical outcomes may be one factor that contributes to trial failures in AD. Given the history of failure, experts have begun to scrutinize the relevance and sensitivity of outcomes as a potentially modifiable barrier to successful trials. To this end, we present a framework for refining trial endpoint selection and evaluation.