Test-retest variability of plasma biomarkers in Alzheimer's disease and its effects on clinical prediction models

Nicholas C. Cullen, Shorena Janelidze, Niklas Mattsson-Carlgren, Sebastian Palmqvist, Tobias Bittner, Ivonne Suridjan, Alexander Jethwa, Gwendlyn Kollmorgen, Wagner S. Brum, Henrik Zetterberg, Kaj Blennow, Erik Stomrud, Oskar Hansson

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskriftPeer review


INTRODUCTION: The effect of random error on the performance of blood-based biomarkers for Alzheimer's disease (AD) must be determined before clinical implementation. METHODS: We measured test-retest variability of plasma amyloid beta (Aβ)42/Aβ40, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau (p-tau)217 and simulated effects of this variability on biomarker performance when predicting either cerebrospinal fluid (CSF) Aβ status or conversion to AD dementia in 399 non-demented participants with cognitive symptoms. RESULTS: Clinical performance was highest when combining all biomarkers. Among single-biomarkers, p-tau217 performed best. Test-retest variability ranged from 4.1% (Aβ42/Aβ40) to 25% (GFAP). This variability reduced the performance of the biomarkers (≈ΔAUC [area under the curve] −1% to −4%) with the least effects on models with p-tau217. The percent of individuals with unstable predicted outcomes was lowest for the multi-biomarker combination (14%). DISCUSSION: Clinical prediction models combining plasma biomarkers—particularly p-tau217—exhibit high performance and are less effected by random error. Individuals with unstable predicted outcomes (“gray zone”) should be recommended for further tests.

TidskriftAlzheimer's and Dementia
StatusAccepted/In press - 2022

Ämnesklassifikation (UKÄ)

  • Neurovetenskaper


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