Journal article
Revising the ABIDE MCI to dementia prediction model for automated cerebrospinal fluid assays
- Abstract:
- INTRODUCTION: Automated cerebrospinal fluid (CSF) biomarker assays have largely replaced manual immunoassays for measuring amyloid pathology in CSF. We refitted and validated the ABIDE model, predicting progression from mild cognitive impairment (MCI) to dementia, with CSF measurements from the automated Elecsys platform. METHODS: We included 2413 MCI participants (998 [41%] amyloid‐positive) from seven observational cohorts. Elecsys was used in 958 (40%) participants. The parameters of the previous ABIDE Cox model were re‐estimated. Model discrimination and calibration were evaluated with leave‐one‐cohort‐out cross‐validation. RESULTS: During follow‐up, 1034 (42%; 585 [58%] amyloid‐positive) participants developed dementia. Discrimination was good with Harrell's C of 0.70 (95% confidence interval [CI]: 0.66–0.73). Calibration was good in the total population and amyloid‐positive subgroup, with substantial predicted progression risks for all amyloid‐positive participants. DISCUSSION: We refitted the ABIDE model, predicting MCI to dementia progression, with automated CSF measurements. The model was well calibrated in amyloid‐positive patients and may support clinical discussions regarding ATTs.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 947.7KB, Terms of use)
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- Publisher copy:
- 10.1002/alz.71192
Authors
+ Knut and Alice Wallenberg Foundation
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- Funder identifier:
- https://ror.org/004hzzk67
+ Canadian Institutes of Health Research
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- Funder identifier:
- https://ror.org/01gavpb45
+ Alzheimer's Drug Discovery Foundation
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- Funder identifier:
- https://ror.org/0185drb55
+ National Institute of Biomedical Imaging and Bioengineering
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- Funder identifier:
- https://ror.org/00372qc85
- Publisher:
- Wiley
- Journal:
- Alzheimer's & Dementia: The Journal of the Alzheimer's Association More from this journal
- Volume:
- 22
- Issue:
- 2
- Article number:
- e71192
- Publication date:
- 2026-02-09
- Acceptance date:
- 2025-12-30
- DOI:
- EISSN:
-
1552-5279
- ISSN:
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1552-5260
- Language:
-
English
- Keywords:
- Pubs id:
-
2370524
- Local pid:
-
pubs:2370524
- Source identifiers:
-
3740530
- Deposit date:
-
2026-02-09
- ARK identifier:
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Terms of use
- Copyright date:
- 2026
- Licence:
- CC Attribution (CC BY)
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