O1‐02‐02: THE ANTI‐AMYLOID TREATMENT IN ASYMPTOMATIC ALZHEIMER'S DISEASE (A4) STUDY: REPORT OF SCREENING DATA RESULTS
Bibliographic record
Abstract
The A4 Study is a secondary prevention trial of an anti-amyloid antibody in clinically normal (CN) individuals age 65-85 with elevated brain amyloid on screening PET scan. Here we report the demographic, cognitive, APOE genotype and amyloid PET data from the A4 screening process. CN participants (CDR=0; MMSE 25-30) were screened at 67 centers in the United States, Canada, Australia, and Japan. Screening assessments obtained prior to Amyloid PET imaging included cognitive testing with the Preclinical Alzheimer Cognitive Composite (PACC), a participant and study partner reported functional assessment, the Cognitive Function Index (CFI), and APOE genotyping. A quantitative SUVr/visual read algorithm of F-Florbetapir Amyloid PET classified participants as Elevated Amyloid (Aβ+), eligible to continue in screening, or Not Elevated (Aβ-). 6762 participants (14% minority) were screened. Amyloid PET was acquired on 4487 participants, with 1323 (29.5%) classified as Aβ+ (mean SUVr=1.33±0.18). Aβ+ participants were slightly older than Aβ-, with no differences in sex, education, marital or retirement status (Table 1). Minority participants across multiple races were less likely to be Aβ+. Aβ+ were more likely to have a family history of dementia (74% Aβ+ vs. 68% Aβ-) and more likely to carry at least one APOEε4 allele (58% Aβ+ vs. 25% Aβ-). Aβ+ showed worse performance on screening PACC (p< 0.0001, adjusted for age, gender, and education; Table 2). Aβ+ participants and their study partners reported higher scores on CFI (p<0.0001). A4 completed enrollment in December 2017 with 1169 Aβ+ randomized participants. Aβ+ participants eligible for the A4 Study show similar demographic characteristics to AD dementia populations with nearly 60% APOEε4 carriers. Despite the relatively narrow range of normal cognitive performance required for A4 eligibility, Aβ+ performed significantly lower on screening cognitive tests and had higher rates of self- and study partner-reported cognitive functional decline. The A4 Study demonstrates the feasibility of enrolling a preclinical AD population in a large prevention trial that will test whether an anti-amyloid agent can slow cognitive decline during the preclinical stage of AD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".