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Accurate risk estimation of β-amyloid positivity to identify prodromal Alzheimer's disease : Cross-validation study of practical algorithms

Palmqvist, Sebastian LU orcid ; Insel, Philip S. LU ; Zetterberg, Henrik LU ; Blennow, Kaj LU ; Brix, Britta ; Stomrud, Erik LU orcid ; Mattsson, Niklas LU orcid and Hansson, Oskar LU orcid (2019) In Alzheimer's and Dementia 15(2). p.194-204
Abstract

Introduction: The aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity. Methods: The algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ42/Aβ40, tau, and neurofilament light. Results: Aβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini–Mental State Examination, and APOE (area under the receiver operating... (More)

Introduction: The aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity. Methods: The algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ42/Aβ40, tau, and neurofilament light. Results: Aβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini–Mental State Examination, and APOE (area under the receiver operating characteristics curve = 0.81 [0.77–0.85] to 0.83 [0.79–0.87]). When validated, the models performed almost identical in Alzheimer's Disease Neuroimaging Initiative (area under the receiver operating characteristics curve = 0.80–0.82) and within different age, subjective cognitive decline, and mild cognitive impairment populations. Plasma Aβ42/Aβ40 improved the models slightly. Discussion: The algorithms are implemented on http://amyloidrisk.com where the individual probability of being Aβ positive can be calculated. This is useful in the workup of prodromal Alzheimer's disease and can reduce the number needed to screen in Alzheimer's disease trials.

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; ; ; ; ; ; and
author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Alzheimer's disease, Aβ, Cerebrospinal fluid, Diagnostic accuracy, Plasma Aβ/Aβ, Position emission tomography, Prediction, Risk estimation, β-amyloid
in
Alzheimer's and Dementia
volume
15
issue
2
pages
194 - 204
publisher
Wiley
external identifiers
  • pmid:30365928
  • scopus:85057883025
ISSN
1552-5260
DOI
10.1016/j.jalz.2018.08.014
language
English
LU publication?
yes
id
7c0f61b7-f679-46d6-992b-7b3db61062c3
date added to LUP
2018-12-21 11:06:01
date last changed
2025-01-08 22:35:11
@article{7c0f61b7-f679-46d6-992b-7b3db61062c3,
  abstract     = {{<p>Introduction: The aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity. Methods: The algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ<sub>42</sub>/Aβ<sub>40</sub>, tau, and neurofilament light. Results: Aβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini–Mental State Examination, and APOE (area under the receiver operating characteristics curve = 0.81 [0.77–0.85] to 0.83 [0.79–0.87]). When validated, the models performed almost identical in Alzheimer's Disease Neuroimaging Initiative (area under the receiver operating characteristics curve = 0.80–0.82) and within different age, subjective cognitive decline, and mild cognitive impairment populations. Plasma Aβ<sub>42</sub>/Aβ<sub>40</sub> improved the models slightly. Discussion: The algorithms are implemented on http://amyloidrisk.com where the individual probability of being Aβ positive can be calculated. This is useful in the workup of prodromal Alzheimer's disease and can reduce the number needed to screen in Alzheimer's disease trials.</p>}},
  author       = {{Palmqvist, Sebastian and Insel, Philip S. and Zetterberg, Henrik and Blennow, Kaj and Brix, Britta and Stomrud, Erik and Mattsson, Niklas and Hansson, Oskar}},
  issn         = {{1552-5260}},
  keywords     = {{Alzheimer's disease; Aβ; Cerebrospinal fluid; Diagnostic accuracy; Plasma Aβ/Aβ; Position emission tomography; Prediction; Risk estimation; β-amyloid}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{194--204}},
  publisher    = {{Wiley}},
  series       = {{Alzheimer's and Dementia}},
  title        = {{Accurate risk estimation of β-amyloid positivity to identify prodromal Alzheimer's disease : Cross-validation study of practical algorithms}},
  url          = {{http://dx.doi.org/10.1016/j.jalz.2018.08.014}},
  doi          = {{10.1016/j.jalz.2018.08.014}},
  volume       = {{15}},
  year         = {{2019}},
}