pTau181 plasma biomarker performance as an inclusion criterion for Alzheimer’s Disease clinical trials
Bibliographic record
Abstract
Abstract Background Advances in ultrasensitive detection techniques for blood biomarkers allow the quantification of AD‐specific phosphorylated Tau proteins, including Tau phosphorylated at threonine 181 (pTau181) in patient plasma. pTau blood‐based biomarker have shown great promise as inclusion criteria and secondary endpoint evaluation in clinical trials. Method The University of British Columbia (UBC) CARD biobank plasma samples from clinically diagnosed AD and non‐AD patients were used to establish clinical and analytical validity of the pTau181 plasma assay per FDA fit‐for‐purpose guildelines (Neurcode USA, Inc.). We assessed the analytical measurement interval, clinical reportable range, linearity, intra‐laboratory precision, specimen stability, interference, and clinical performance. Result The pTau181 plasma assay provides a robust and accurate biomarker approach for independent determination of AD, with an AUC of 0.9 in our validation study cohort. The cut‐point (≥ 30 ng/L) had 100% sensitivity and 88% specificity for AD diagnosis in autopsy‐confirmed samples. The plasma pTau181 assay appears to be performing well as additional screening metric for inclusion of mild‐to‐moderate AD subjects in Phase 3 clinical trials (i.e. RETHINK‐ALZ and REFOCUS‐ALZ). 89% of the clinical sites participating in the REFOCUS‐ALZ study and 80% of sites participating in the RETHINK‐ALZ had at least 70% of screened subjects meeting this criterion. Conclusion AD plasma biomarker (pTau181) quantified using an RUO assay has great potential both as a diagnostic tool and to streamline clinical trials in 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 | 0.041 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".