Abstract

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.

Original languageEnglish
JournalAlzheimer's and Dementia
DOIs
Publication statusAccepted/In press - 2022

Subject classification (UKÄ)

  • Neurosciences

Keywords

  • diagnosis
  • gray zones
  • plasma biomarkers
  • random error
  • test-retest variability

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