Extended results of the Alzheimer's disease anti‐inflammatory prevention trial
Bibliographic record
Abstract
BACKGROUND: Epidemiologic evidence suggests that nonsteroidal anti-inflammatory drugs (NSAIDs) delay onset of Alzheimer's dementia (AD), but randomized trials show no benefit from NSAIDs in patients with symptomatic AD. The Alzheimer's Disease Anti-inflammatory Prevention Trial (ADAPT) randomized 2,528 elderly persons to naproxen or celecoxib versus placebo for 2 years (standard deviation = 11 months) before treatments were terminated. During the treatment interval, 32 cases of AD revealed increased rates in both NSAID-assigned groups. METHODS: We continued the double-masked ADAPT protocol for 2 additional years to investigate incidence of AD (primary outcome). We then collected cerebrospinal fluid (CSF) from 117 volunteer participants to assess their ratio of CSF tau to Aβ(1-42.) RESULTS: Including 40 new events observed during follow-up of 2,071 randomized individuals (92% of participants at treatment cessation), there were 72 AD cases. Overall, NSAID-related harm was no longer evident, but secondary analyses showed that increased risk remained notable in the first 2.5 years of observations, especially in 54 persons enrolled with cognitive impairment--no dementia (CIND). These same analyses showed later reduction in AD incidence among asymptomatic enrollees who were given naproxen. CSF biomarker assays suggested that the latter result reflected reduced Alzheimer-type neurodegeneration. CONCLUSIONS: These data suggest a revision of the original ADAPT hypothesis that NSAIDs reduce AD risk, as follows: NSAIDs have an adverse effect in later stages of AD pathogenesis, whereas asymptomatic individuals treated with conventional NSAIDs such as naproxen experience reduced AD incidence, but only after 2 to 3 years. Thus, treatment effects differ at various stages of disease. This hypothesis is consistent with data from both trials and epidemiological studies.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".