ArticleAlzheimer's research & therapy2025
Individualized prediction of clinical progression to dementia using plasma biomarkers in non-demented elderly.
Article in Alzheimer's research & therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Comparative Analysis of Plasma Biomarkers of Alzheimer's Disease and Frontotemporal Dementia: The Dual Role of Soluble Fractalkine as a Biomarker of Frontotemporal Dementia and Its Neuroprotective Effects in Cortical Neurons "In Vitro".Life (Basel, Switzerland) · 2026Article
- Plasma biomarkers for Alzheimer disease: the road from laboratory results to clinical practice.Nature reviews. Neurology · 2026Article
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19 authors.
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Abstract
backgroundWe aimed to develop individualized predictions for risk of developing any-cause dementia and Alzheimer's disease (AD) dementia, in individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI), using plasma phosphorylated-tau-181 (pTau181), phosphorylated-tau-217 (pTau217; in a subset), amyloid beta1-42/1-40 (Aβ42/40), glial fibrillary acidic protein (GFAP) and/or neurofilament light (NfL).
methodsFrom the Amsterdam Dementia Cohort we included 314 individuals with SCD (age 61 ± 9 years, n = 184 (59%) male, MMSE 29 ± 1) and 253 individuals with MCI (age 65 ± 7 years, n = 165 (65%) male, MMSE 27 ± 2), who had annual follow-up (median duration 2.4 years). Cox proportional hazards regression models were used to calculate probabilities for progression to dementia and were externally validated in MEMENTO and AIBL cohorts.
resultsDuring follow-up 20 SCD and 99 MCI patients developed dementia. For MCI patients who progressed to any form of dementia, plasma GFAP contributed on top of age, sex, and MMSE score in the parsimonious individualized prognostic model (C-index = 0.69 [95%CI = 0.63; 0.76]). With AD-dementia as the outcome, GFAP and pTau181 were selected in the parsimonious model on top of the demographic variables (C-index = 0.71 [95%CI = 0.65; 0.76]). In the subset of 197 MCI individuals with pTau217 measurements, pTau217 was selected in the parsimonious model on top of the demographic variables (C-index = 0.75 [95%CI = 0.69; 0.79]). External validation demonstrated that the models are robust in a memory clinic setting.
conclusionsOur prediction models have utility for clinical practice to calculate progression probabilities for development of dementia in individual patients living with MCI over a 1-, 3- and 5-year time period.
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