Potential Utility of Plasma P-Tau and Neurofilament Light Chain as Surrogate Biomarkers for Preventive Clinical Trials
Bibliographic record
Abstract
OBJECTIVE: To test the utility of longitudinal changes in plasma phosphorylated tau 181 (p-tau181) and neurofilament light chain (NfL) as surrogate markers for clinical trials targeting cognitively unimpaired (CU) populations. METHODS: We estimated the sample size needed to test a 25% drug effect with 80% of power at a 0.05 level on reducing changes in plasma markers in CU participants from Alzheimer's Disease Neuroimaging Initiative database. RESULTS: We included 257 CU individuals (45.5% males; mean age = 73 [6] years; 32% β-amyloid [Aβ] positive). Changes in plasma NfL were associated with age, whereas changes in plasma p-tau181 with progression to amnestic mild cognitive impairment. Clinical trials using p-tau181 and NfL would require 85% and 63% smaller sample sizes, respectively, for a 24-month than a 12-month follow-up. A population enrichment strategy using intermediate levels of Aβ PET (Centiloid 20-40) further reduced the sample size of the 24-month clinical trial using p-tau181 (73%) and NfL (59%) as a surrogate. DISCUSSION: Plasma p-tau181/NfL can potentially be used to monitor large-scale population interventions in CU individuals. The enrollment of CU with intermediate Aβ levels constitutes the alternative with the largest effect size and most cost-effective for trials testing drug effect on changes in plasma p-tau181 and NfL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.216 | 0.244 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".