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Biomarker testing in MCI patients—deciding who to test
BACKGROUND: We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value. METHODS: MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progressi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7792312/ https://www.ncbi.nlm.nih.gov/pubmed/33413634 http://dx.doi.org/10.1186/s13195-020-00763-7 |
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author | van Maurik, Ingrid S. Rhodius-Meester, Hanneke F. M. Teunissen, Charlotte E. Scheltens, Philip Barkhof, Frederik Palmqvist, Sebastian Hansson, Oskar van der Flier, Wiesje M. Berkhof, Johannes |
author_facet | van Maurik, Ingrid S. Rhodius-Meester, Hanneke F. M. Teunissen, Charlotte E. Scheltens, Philip Barkhof, Frederik Palmqvist, Sebastian Hansson, Oskar van der Flier, Wiesje M. Berkhof, Johannes |
author_sort | van Maurik, Ingrid S. |
collection | PubMed |
description | BACKGROUND: We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value. METHODS: MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progression probabilities to dementia were predicted using previously published models with and without CSF data (amyloid-beta1-42 (Abeta), phosphorylated tau (p-tau)). We incrementally augmented the proportion of patients undergoing CSF, starting with the 10% patients with prognostic probabilities based on clinical data around the median (percentile 45–55), until all patients received CSF. The optimal proportion was defined as the proportion where the stepwise algorithm showed similar prognostic discrimination (Harrell’s C) and accuracy (three-year Brier scores) compared to CSF testing of all patients. We used the BioFINDER study (n = 221) for validation. RESULTS: The optimal proportion of MCI patients to receive CSF testing selected by the stepwise approach was 50%. CSF testing in only this proportion improved the performance of the model with clinical data only from Harrell’s C = 0.60, Brier = 0.198 (Harrell’s C = 0.61, Brier = 0.197 if the information on magnetic resonance imaging was available) to Harrell’s C = 0.67 and Brier = 0.190, and performed similarly to a model in which all patients received CSF testing. Applying the stepwise approach in the BioFINDER study would again select half of the MCI patients and yielded robust results with respect to prognostic performance. INTERPRETATION: CSF biomarker testing adds prognostic value in half of the MCI patients. As such, we achieve a CSF saving recommendation while simultaneously retaining optimal prognostic accuracy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-020-00763-7. |
format | Online Article Text |
id | pubmed-7792312 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77923122021-01-11 Biomarker testing in MCI patients—deciding who to test van Maurik, Ingrid S. Rhodius-Meester, Hanneke F. M. Teunissen, Charlotte E. Scheltens, Philip Barkhof, Frederik Palmqvist, Sebastian Hansson, Oskar van der Flier, Wiesje M. Berkhof, Johannes Alzheimers Res Ther Research BACKGROUND: We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value. METHODS: MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progression probabilities to dementia were predicted using previously published models with and without CSF data (amyloid-beta1-42 (Abeta), phosphorylated tau (p-tau)). We incrementally augmented the proportion of patients undergoing CSF, starting with the 10% patients with prognostic probabilities based on clinical data around the median (percentile 45–55), until all patients received CSF. The optimal proportion was defined as the proportion where the stepwise algorithm showed similar prognostic discrimination (Harrell’s C) and accuracy (three-year Brier scores) compared to CSF testing of all patients. We used the BioFINDER study (n = 221) for validation. RESULTS: The optimal proportion of MCI patients to receive CSF testing selected by the stepwise approach was 50%. CSF testing in only this proportion improved the performance of the model with clinical data only from Harrell’s C = 0.60, Brier = 0.198 (Harrell’s C = 0.61, Brier = 0.197 if the information on magnetic resonance imaging was available) to Harrell’s C = 0.67 and Brier = 0.190, and performed similarly to a model in which all patients received CSF testing. Applying the stepwise approach in the BioFINDER study would again select half of the MCI patients and yielded robust results with respect to prognostic performance. INTERPRETATION: CSF biomarker testing adds prognostic value in half of the MCI patients. As such, we achieve a CSF saving recommendation while simultaneously retaining optimal prognostic accuracy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-020-00763-7. BioMed Central 2021-01-07 /pmc/articles/PMC7792312/ /pubmed/33413634 http://dx.doi.org/10.1186/s13195-020-00763-7 Text en © The Author(s) 2021 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 van Maurik, Ingrid S. Rhodius-Meester, Hanneke F. M. Teunissen, Charlotte E. Scheltens, Philip Barkhof, Frederik Palmqvist, Sebastian Hansson, Oskar van der Flier, Wiesje M. Berkhof, Johannes Biomarker testing in MCI patients—deciding who to test |
title | Biomarker testing in MCI patients—deciding who to test |
title_full | Biomarker testing in MCI patients—deciding who to test |
title_fullStr | Biomarker testing in MCI patients—deciding who to test |
title_full_unstemmed | Biomarker testing in MCI patients—deciding who to test |
title_short | Biomarker testing in MCI patients—deciding who to test |
title_sort | biomarker testing in mci patients—deciding who to test |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7792312/ https://www.ncbi.nlm.nih.gov/pubmed/33413634 http://dx.doi.org/10.1186/s13195-020-00763-7 |
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