B-250 Analytical and Diagnostic Performance Evaluation of Plasma pTau217 in a Clinical Diagnostic Laboratory
Bibliographic record
Abstract
Abstract Background Blood-based biomarkers are a readily accessible and cost-effective screening tool for Alzheimer’s disease (AD). Phosphorylated tau 217 (pTau217) is a specific biomarker for diagnosis and differentiating of AD. It is also a reliable biomarker for facilitating more timely access to disease-modifying therapies. Here, we report the analytical and clinical performance of plasma pTau 217 using high-sensitivity methodologies in a clinical diagnostic laboratory. Methods The analytical performance, including precision, specificity, detection limits, and linearity, as well as analyte stability, was assessed. Plasma pTau217 levels were measured using ALZpath pTau217 assay on the Quanterix HD-X Simoa® platform or LUMIPULSE plasma pTau217 on the Lumipulse G1200 platform. Clinical Validation conducted at Neurocode USA & BC Neuroimmunology involving 263 samples with amyloid PET data, 219 healthy aging samples and 150 Pathology confirmed samples. Results The mean plasma pTau 217 concentrations in healthy aging samples were 0.22 ± 0.08 ng/L. ALZpath pTau217 assay has an analytical measurement range of 0.06 - 10 pg/mL, with a limit of blank (LoB) of 0.0035 ng/L, a limit of detection (LoD) of 0.0074 ng/L, and a limit of quantification (LoQ) of 0.0600 ng/L. Its linearity extends from 0.19 to 2.8 ng/L, with repeatability demonstrating intra-laboratory precision above LoQ ≤ 20% CV. Stability is maintained at 4⁰C for ≤ 1 week, at room temperature for ≤ 24 hrs, at -20⁰C for ≤ 4 weeks, and at -80⁰C for ≤ 4 weeks, with freeze/thaw cycles tolerated up to 5 times. Furthermore, no interference was detected at the maximum concentrations tested for bilirubin, hemoglobin, biotin, and heterophilic antibodies. ROC analysis yielded an AUC of 0.92 to 0.93, identifying a suitable clinical cutoff of < 0.4 ng/L. Conclusions The outstanding clinical and analytical performance of pTau217 supports its adoption as a robust screening tool in clinical practice, facilitating accurate and reliable diagnosis of AD by clinicians.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".