Abstract
INTRODUCTION
Combining Alzheimer’s disease blood biomarkers may improve prediction of amyloid positivity (A+) compared with single biomarkers.
METHODS
Logistic regression models using plasma phosphorylated tau 217 (p-tau217), amyloid beta (Aβ) 42, and Aβ40 were developed in cognitively impaired (CI) participants from Mayo Clinic Rochester (MCR) and validated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Mayo Clinic Florida (MCF) cohorts. Performance was measured by area under the curve (AUC) and Probability of Amyloid Positivity Score (PAPS).
RESULTS
Plasma p-tau217 alone showed high AUC (95% confidence intervals) across cohorts MCR, 0.928 (0.900–0.953); ADNI, 0.938 (0.915–0.959); MCF, 0.935 (0.893–0.970). Adding Aβ42 to regression models yielded marginal model improvement MCR, 0.940 (0.915–0.963); ADNI, 0.945 (0.922–0.965); MCF, 0.960 (0.925–0.986). Utilization of two cutpoints (≥ 90% sensitivity and specificity), yielded ≤ 10% intermediate results for p-tau217, and ≤ 8% for p-tau217+Aβ42. Addition of Aβ40 did not improve models’ performance.
DISCUSSION
An immunoassay-based p-tau217 PAPS model accurately predicted amyloid positivity across independent CI cohorts and achieved confirmatory-test performance with two cutpoints. The added value of Aβ42 was modest and cohort dependent, supporting the potential of use of p-tau217–based PAPS in clinical workflows.
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This post is Copyright: | November 4, 2026
Neuro-Dementia