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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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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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. |
format | Online Article Text |
id | pubmed-10187729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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