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Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods

BACKGROUND: Amyloid-β (Aβ) PET is an established predictor of conversion from mild cognitive impairment (MCI) to Alzheimer’s dementia (AD). We compared three PET (including an approach based on voxel-wise Cox regression) and one cerebrospinal fluid (CSF) outcome measures in their predictive power. M...

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Autores principales: Sörensen, Arnd, Blazhenets, Ganna, Schiller, Florian, Meyer, Philipp Tobias, Frings, Lars
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7678323/
https://www.ncbi.nlm.nih.gov/pubmed/33213489
http://dx.doi.org/10.1186/s13195-020-00721-3
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author Sörensen, Arnd
Blazhenets, Ganna
Schiller, Florian
Meyer, Philipp Tobias
Frings, Lars
author_facet Sörensen, Arnd
Blazhenets, Ganna
Schiller, Florian
Meyer, Philipp Tobias
Frings, Lars
author_sort Sörensen, Arnd
collection PubMed
description BACKGROUND: Amyloid-β (Aβ) PET is an established predictor of conversion from mild cognitive impairment (MCI) to Alzheimer’s dementia (AD). We compared three PET (including an approach based on voxel-wise Cox regression) and one cerebrospinal fluid (CSF) outcome measures in their predictive power. METHODS: Datasets were retrieved from the ADNI database. In a training dataset (N = 159), voxel-wise Cox regression and principal component analyses were used to identify conversion-related regions (Cox-VOI and AD conversion-related pattern (ADCRP), respectively). In a test dataset (N = 129), the predictive value of mean normalized (18)F-florbetapir uptake (SUVR) in AD-typical brain regions (composite SUVR) or the Cox-VOI and the pattern expression score (PES) of ADCRP and CSF Aβ(42)/Aβ(40) as predictors were compared by Cox models (corrected for age and sex). RESULTS: All four Aβ measures were significant predictors (p < 0.001). Prediction accuracies (Harrell’s c) showed step-wise significant increases from Cox-SUVR (c = 0.71; HR = 1.84 per Z-score increase), composite SUVR (c = 0.73; HR = 2.18), CSF Aβ(42)/Aβ(40) (c = 0.75; HR = 3.89) to PES (c = 0.77; HR = 2.71). CONCLUSION: The PES of ADCRP is the most predictive Aβ PET outcome measure, comparable to CSF Aβ(42)/Aβ(40), with a slight but statistically significant advantage.
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spelling pubmed-76783232020-11-20 Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods Sörensen, Arnd Blazhenets, Ganna Schiller, Florian Meyer, Philipp Tobias Frings, Lars Alzheimers Res Ther Research BACKGROUND: Amyloid-β (Aβ) PET is an established predictor of conversion from mild cognitive impairment (MCI) to Alzheimer’s dementia (AD). We compared three PET (including an approach based on voxel-wise Cox regression) and one cerebrospinal fluid (CSF) outcome measures in their predictive power. METHODS: Datasets were retrieved from the ADNI database. In a training dataset (N = 159), voxel-wise Cox regression and principal component analyses were used to identify conversion-related regions (Cox-VOI and AD conversion-related pattern (ADCRP), respectively). In a test dataset (N = 129), the predictive value of mean normalized (18)F-florbetapir uptake (SUVR) in AD-typical brain regions (composite SUVR) or the Cox-VOI and the pattern expression score (PES) of ADCRP and CSF Aβ(42)/Aβ(40) as predictors were compared by Cox models (corrected for age and sex). RESULTS: All four Aβ measures were significant predictors (p < 0.001). Prediction accuracies (Harrell’s c) showed step-wise significant increases from Cox-SUVR (c = 0.71; HR = 1.84 per Z-score increase), composite SUVR (c = 0.73; HR = 2.18), CSF Aβ(42)/Aβ(40) (c = 0.75; HR = 3.89) to PES (c = 0.77; HR = 2.71). CONCLUSION: The PES of ADCRP is the most predictive Aβ PET outcome measure, comparable to CSF Aβ(42)/Aβ(40), with a slight but statistically significant advantage. BioMed Central 2020-11-19 /pmc/articles/PMC7678323/ /pubmed/33213489 http://dx.doi.org/10.1186/s13195-020-00721-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sörensen, Arnd
Blazhenets, Ganna
Schiller, Florian
Meyer, Philipp Tobias
Frings, Lars
Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods
title Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods
title_full Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods
title_fullStr Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods
title_full_unstemmed Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods
title_short Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer’s dementia: a comparison of methods
title_sort amyloid biomarkers as predictors of conversion from mild cognitive impairment to alzheimer’s dementia: a comparison of methods
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7678323/
https://www.ncbi.nlm.nih.gov/pubmed/33213489
http://dx.doi.org/10.1186/s13195-020-00721-3
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