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O1‐02‐05: PREDICTING AMYLOID BURDEN IN SCREENING FOR PRECLINICAL AD PREVENTION TRIALS
Author(s) -
Donohue Michael C.,
Raman Rema,
Sun Chung-Kai,
Langford Oliver,
Johnson Keith A.,
Aisen Paul S.,
Sperling Reisa A.
Publication year - 2018
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2018.06.2340
Subject(s) - random forest , medicine , asymptomatic , apolipoprotein e , cognitive impairment , β amyloid , machine learning , alzheimer's disease , computer science , disease
Background:Alzheimer’s disease (AD) prevention trials target an earlier stage of the disease based on the idea that earlier intervention before neuron loss and symptom onset will provide improved outcomes. The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) launched the first AD prevention trial in 2012 in a rare population of dominantly inherited AD mutation carriers who are destined to get the disease with near 100% penetrance. Recruitment was completed in 2015 into two parallel drug arms in the DIAN-TU adaptive prevention trial (DIAN-TU APT) platform. A major goal of public-private prevention trials is to make data available to the research community and this presentation will provide comprehensive results of baseline data. Methods: The metrics of establishing the DIAN-TU platform, start-up of sites, launch of the trial, screening, enrollment and close of enrollment measures were analyzed. Baseline demographic, clinical, cognitive, genetic, imaging including MRI, amyloid PIB PET, amyloid AV45 PET, tau AV1451 PET and biomarker results were analyzed according to protocol. Measures were compared to prior findings in the DIAN observational study. A process for DIANTU data requests was developed, approved, and activated in 2017. Results:The DIAN-TU APT platform was established in the first year with protocol, site, operational, and multiple partner start-up in this global trial. As sites were activated, enrollment rate increasedwith rapid enrollment by the end of the study. 194 participants enrolled to successfully meet enrollment goals within projected timelines. Screen fail rate (19%), recruitment source (47% DIAN-obs, 38% DIAN Expanded Registry), and completion rates of all baseline assessments (99-100%)were excellent. This trial provides comprehensive clinical, cognitive, imaging and biomarker data and samples that are being used in the final analyses and are available to address important scientific and medical questions. Conclusions:Clinical prevention trials in AD with multiple AD biomarkers are feasible and can be highly successful, even in a rare population. The results from comprehensive evaluations during trials can provide unique insights into the effects of interventions and promise to accelerate highly effective treatments and preventions for AD.