Efficacy of AD04, an aluminum-based vaccine adjuvant, in patients with early Alzheimer's disease: Post hoc analysis of AFF006 (NCT01117818), a proof-of-concept, phase 2 randomized controlled trial
Bibliographic record
Abstract
BackgroundThe AFF006 trial (NCT01117818) provided unexpected evidence of benefits of the vaccine adjuvant AD04 (aluminum oxyhydroxide) in patients with early Alzheimer's disease (AD), compared with AD02, a vaccine consisting of a peptide that mimics the N-terminal region of human amyloid-β (Aβ) conjugated with keyhole limpet hemocyanin.ObjectiveThe objective of this post hoc analysis was to assess whether this unexpected benefit of AD04 was an artifact of multiple testing (i.e., type I error inflation) or a robust result.MethodsIn this post hoc assessment, we used permutation testing to estimate type I error inflation due to the evaluation of multiple outcomes in AFF006. Efficacy was assessed using a patient-level global statistical test combining composite endpoints of cognition, function, and global AD. In addition, we examined the observed treatment benefits of AD04 in the context of effects observed in trials of aducanumab, donanemab, and lecanemab, monoclonal anti-Aβ antibodies that received regulatory approval for AD.ResultsThe global statistical test suggested a treatment benefit of AD04 versus ineffective AD02 arms, even after accounting for multiplicity (primary methodology p-value, 0.03; permutation test p-value, 0.02). The observed effect estimates for AD04 compared favorably with approved monoclonal antibodies.ConclusionsPost-hoc analyses are hypothesis generating rather than confirmatory. Adjusting for multiplicity using permutation testing can determine whether post-hoc effects are worth pursuing, or unlikely to be confirmed. These analyses have motivated a follow-up prospective randomized controlled trial, ADVANCE (EudraCT 2022-003532-73), in which optimized AD04 dosing will be compared to placebo in early 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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".