Abstract
Alzheimers Dement (Amst). 2026 Sep 17;18(3):e70486. doi: 10.1002/dad2.70486. eCollection 2026 Jul-Sep.
ABSTRACT
INTRODUCTION: Blood biomarkers like phosphorylated tau (p-tau)217 offer high diagnostic accuracy for Alzheimer's disease (AD) but face implementation challenges in low-prevalence settings. We evaluated the Altoida NeuroMarker Platform as a digital cognitive triage tool before plasma p-tau217 testing.
METHODS: XGBoost models were trained to predict mild cognitive impairment (MCI) and p-tau217 status in 688 individuals across Australia, Spain, and the United States using the Altoida NeuroMarker. p-tau217 status was dichotomized using a threshold of 0.04 pg/mL (LucentAD). We modeled a two-step workflow (Altoida, plasma p-tau217) to enrich downstream biomarker testing, assuming 30% prevalence of AD pathology.
RESULTS: The Altoida NeuroMarker accurately identified MCI (receiver operating characteristic area under the curve [ROC AUC] = 0.89 ± 0.01) and p-tau217 elevation (ROC AUC = 0.77 ± 0.08). Predicted MCI was significantly associated with elevated pTau217 (p = 0.004). When used upstream, the Altoida NeuroMarker ruled out 64.4% of participants (negative predictive value 90.2%), shifting the pre-test probability of AD pathology to 66.6%, and improving the modeled positive predictive value of plasma p-tau217 from 81.7% to 95.3%.
DISCUSSION: This workflow outlines a scalable path to enrich blood-based biomarker testing after digital cognitive screening.
PMID:42757183 | PMC:PMC13584318 | DOI:10.1002/dad2.70486