Accurate Risk Estimation of Beta-amyloid Positivity to Identify Prodromal Alzheimer’s Disease: Cross-validation Study of Practical Algorithms
THE JOURNAL OF THE ALZHEIMER’S ASSOCIATION
Palmqvist S, Insel PS, Zetterberg H, Blennow K, Brix B, Stomrud E, Mattsson N and Hansson O
Alzheimers Dement. 2018
DOI: https://doi.org/10.1016/j.jalz.2018.08.014
This study was peformed using a Simoa® Homebrew assay.
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 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.