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Independent study demonstrates amyloid probability score accurately indicates amyloid pathology

BACKGROUND: The amyloid probability score (APS) is the model read‐out of the analytically validated mass spectrometry‐based PrecivityAD(®) blood test that incorporates the plasma Aβ42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired in...

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Autores principales: Fogelman, Ilana, West, Tim, Braunstein, Joel B., Verghese, Philip B., Kirmess, Kristopher M., Meyer, Matthew R., Contois, John H., Shobin, Eli, Ferber, Kyle L., Gagnon, Jake, Rubel, Carrie E., Graham, Danielle, Bateman, Randall J., Holtzman, David M., Huang, Shuguang, Yu, Joanne, Yang, Sha, Yarasheski, Kevin E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187729/
https://www.ncbi.nlm.nih.gov/pubmed/36975407
http://dx.doi.org/10.1002/acn3.51763
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author Fogelman, Ilana
West, Tim
Braunstein, Joel B.
Verghese, Philip B.
Kirmess, Kristopher M.
Meyer, Matthew R.
Contois, John H.
Shobin, Eli
Ferber, Kyle L.
Gagnon, Jake
Rubel, Carrie E.
Graham, Danielle
Bateman, Randall J.
Holtzman, David M.
Huang, Shuguang
Yu, Joanne
Yang, Sha
Yarasheski, Kevin E.
author_facet Fogelman, Ilana
West, Tim
Braunstein, Joel B.
Verghese, Philip B.
Kirmess, Kristopher M.
Meyer, Matthew R.
Contois, John H.
Shobin, Eli
Ferber, Kyle L.
Gagnon, Jake
Rubel, Carrie E.
Graham, Danielle
Bateman, Randall J.
Holtzman, David M.
Huang, Shuguang
Yu, Joanne
Yang, Sha
Yarasheski, Kevin E.
author_sort Fogelman, Ilana
collection PubMed
description BACKGROUND: The amyloid probability score (APS) is the model read‐out of the analytically validated mass spectrometry‐based PrecivityAD(®) blood test that incorporates the plasma Aβ42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired individuals being evaluated for Alzheimer's disease. PURPOSE: This study aimed to provide additional independent evidence that the pre‐established APS algorithm, along with its cutoff values, discriminates between amyloid positive and negative individuals. METHODS: The diagnostic performance of the PrecivityAD test was analyzed in a cohort of 200 nonrandomly selected Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL) study participants, who were either cognitively impaired or healthy controls, and for whom a blood sample and amyloid PET imaging were available. RESULTS: In a subset of the dataset aligned with the Intended Use population (patients aged 60 and older with CDR ≥0.5), the pre‐established APS algorithm predicted amyloid PET with a sensitivity of 84.9% (CI: 72.9–92.1%) and specificity of 96% (CI: 80.5–99.3%), exclusive of 13 individuals for whom the test was inconclusive. INTERPRETATION: The study shows individuals with a high APS are more likely than those with a low APS to have abnormal amounts of amyloid plaques and be on an amyloid accumulation trajectory, a dynamic and evolving process characteristic of progressive AD pathology. Exploratory data suggest APS retains its diagnostic performance in healthy individuals, supporting further screening studies in the cognitively unimpaired.
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spelling pubmed-101877292023-05-17 Independent study demonstrates amyloid probability score accurately indicates amyloid pathology Fogelman, Ilana West, Tim Braunstein, Joel B. Verghese, Philip B. Kirmess, Kristopher M. Meyer, Matthew R. Contois, John H. Shobin, Eli Ferber, Kyle L. Gagnon, Jake Rubel, Carrie E. Graham, Danielle Bateman, Randall J. Holtzman, David M. Huang, Shuguang Yu, Joanne Yang, Sha Yarasheski, Kevin E. Ann Clin Transl Neurol Research Articles BACKGROUND: The amyloid probability score (APS) is the model read‐out of the analytically validated mass spectrometry‐based PrecivityAD(®) blood test that incorporates the plasma Aβ42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired individuals being evaluated for Alzheimer's disease. PURPOSE: This study aimed to provide additional independent evidence that the pre‐established APS algorithm, along with its cutoff values, discriminates between amyloid positive and negative individuals. METHODS: The diagnostic performance of the PrecivityAD test was analyzed in a cohort of 200 nonrandomly selected Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL) study participants, who were either cognitively impaired or healthy controls, and for whom a blood sample and amyloid PET imaging were available. RESULTS: In a subset of the dataset aligned with the Intended Use population (patients aged 60 and older with CDR ≥0.5), the pre‐established APS algorithm predicted amyloid PET with a sensitivity of 84.9% (CI: 72.9–92.1%) and specificity of 96% (CI: 80.5–99.3%), exclusive of 13 individuals for whom the test was inconclusive. INTERPRETATION: The study shows individuals with a high APS are more likely than those with a low APS to have abnormal amounts of amyloid plaques and be on an amyloid accumulation trajectory, a dynamic and evolving process characteristic of progressive AD pathology. Exploratory data suggest APS retains its diagnostic performance in healthy individuals, supporting further screening studies in the cognitively unimpaired. John Wiley and Sons Inc. 2023-03-28 /pmc/articles/PMC10187729/ /pubmed/36975407 http://dx.doi.org/10.1002/acn3.51763 Text en © 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Fogelman, Ilana
West, Tim
Braunstein, Joel B.
Verghese, Philip B.
Kirmess, Kristopher M.
Meyer, Matthew R.
Contois, John H.
Shobin, Eli
Ferber, Kyle L.
Gagnon, Jake
Rubel, Carrie E.
Graham, Danielle
Bateman, Randall J.
Holtzman, David M.
Huang, Shuguang
Yu, Joanne
Yang, Sha
Yarasheski, Kevin E.
Independent study demonstrates amyloid probability score accurately indicates amyloid pathology
title Independent study demonstrates amyloid probability score accurately indicates amyloid pathology
title_full Independent study demonstrates amyloid probability score accurately indicates amyloid pathology
title_fullStr Independent study demonstrates amyloid probability score accurately indicates amyloid pathology
title_full_unstemmed Independent study demonstrates amyloid probability score accurately indicates amyloid pathology
title_short Independent study demonstrates amyloid probability score accurately indicates amyloid pathology
title_sort independent study demonstrates amyloid probability score accurately indicates amyloid pathology
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187729/
https://www.ncbi.nlm.nih.gov/pubmed/36975407
http://dx.doi.org/10.1002/acn3.51763
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