Rate of β‐amyloid accumulation varies with baseline amyloid burden: Implications for anti‐amyloid drug trials
Bibliographic record
Abstract
Abstract Introduction This study examined a longitudinal trajectory of β‐amyloid (Aβ) accumulation at the predementia stage of Alzheimer's disease in the context of clinical trials. Methods Analyzed were baseline (BL) and 2 years' follow‐up 18F‐florbetapir positron emission tomography data of 246 Aβ‐positive subjects with normal cognition and mild cognitive impairment. We studied the relationship between annual accumulation rates of 18F‐florbetapir and BL standard uptake value ratios in whole gray matter (SUVRGM). Results Subjects with BL SUVRGM of 0.56 to 0.92 (n = 134) appeared to accumulate Aβ approximately 1.5 times faster than remaining subjects. In subjects with SUVRGM above 0.95, most regions with the highest annual accumulation rate were outside the established set of Alzheimer's disease typical regions. Conclusion There are global and regional variations in annual accumulation rate at the predementia stage of Alzheimer's disease. When taken into account, the sample size in anti‐amyloid trials can be substantially reduced. Critically, treated and placebo groups should be matched for BL SUVRGM.
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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 | 0.062 | 0.137 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".