Improved Design of Prodromal Alzheimer's Disease Trials through Cohort Enrichment and Surrogate Endpoints
Year: 2013
Type: article
Abstract: Alzheimer's disease (AD) trials initiated during or before the prodrome are costly and lengthy because patients are enrolled long before clinical symptoms are apparent, when disease progression is slow. We hypothesized that design of such trials could be improved by: 1) selecting individuals at moderate near-term risk of progression to AD dementia (the current clinical standard) and 2) by using short-term surrogate endpoints that predict progression to AD dementia. We used a longitudinal cohort of older, initially non-demented, community-dwelling participants (n = 358) to derive selection criteria and surrogate endpoints and tested them in an independent national data set (n = 6,243). To identify a "mid-risk" subgroup, we applied conditional tree-based survival models to Clinical Dementia Rating (CDR) scale scores and common neuropsychological tests. In the validation cohort, a time-to-AD dementia trial applying these mid-risk selection criteria to a pool of all non-demented individuals could achieve equivalent power with 47% fewer participants than enrolling at random from that pool. We evaluated surrogate endpoints measureable over two years of follow-up based on cross-validated concordance between predictions from Cox models and observed time to AD dementia. The best performing surrogate, rate of change in CDR sum-of-boxes, did not reduce the trial duration required for equivalent power using estimates from the validation cohort, but alternative surrogates with better ability to predict time to AD dementia should be able to do so. The approach tested here might improve efficiency of prodromal AD trials using other potential measures and could be generalized to other diseases with long prodromal phases.
Source: Journal of Alzheimer s Disease
DOI: 10.3233/jad-122212
Institutions: Harvard University, Massachusetts General Hospital
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: National Alzheimer's Coordinating Center, Synaptic loss and plasticity in aging and Alzheimer's disease, Neurologic Alterations in Alzheimer's Disease, Statistical Methods for Analysis of Failure Time Data, Massachusetts Alzheimer's Disease Research Center, Age-related changes of cognition in health and disease, Massachusetts Alzheimer's Disease Research Center (MADRC)
OpenAlex ID: W2104220566