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ABIDEing with automated cerebrospinal fluid assays: update of an MCI to dementia prediction model

  • Amsterdam UMC
  • Vrije Universiteit Amsterdam
  • Northwest Academie
  • University College London
  • Maastricht University
  • Heidelberg University 
  • Friedrich-Alexander University Erlangen-Nürnberg
  • German Center for Neurodegenerative Diseases
  • University of Göttingen
  • University of Bonn
  • Free University of Berlin
  • University of Geneva
  • Ana Aslan International Academy of Aging
  • Carol Davila University of Medicine and Pharmacy
  • Karolinska Institutet
  • King's College London
  • Örebro University
  • Lund University
  • Sorbonne Université
  • Aristotle University of Thessaloniki
  • Medical University of Łódź
  • University of Perugia
  • CHU de Toulouse
  • University of Oxford
  • IRCCS Centro San Giovanni di Dio Fatebenefratelli - Brescia
  • University of Eastern Finland
  • University of Coimbra
  • University of Lisbon
  • University of Algarve
  • Université de Caen Normandie
  • PhIND - Physiopathologie et Imagerie des Troubles Neurologiques
  • University of Wisconsin-Madison
  • Instituto de Investigación Biomédica de Lleida Fundació Dr. Pifarré
  • Hospital Universitari Santa Maria

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Abstract

BACKGROUND: Automated cerebrospinal fluid (CSF) biomarker assays have largely replaced manual immunoassays for measuring amyloid pathology. Their relevance is increasing as amyloid-targeting therapies (ATTs) are becoming available for amyloid-positive mild cognitively impaired (MCI) individuals. Therefore, we refitted and validated the ABIDE model, predicting progression from MCI to dementia, with CSF measurements from the automated Elecsys platform. Additionally, we evaluated the performance in an amyloid-positive subpopulation, potentially eligible for ATTs. METHOD: We combined data from MCI participants of seven single-centre and multicentre observational cohorts: Amsterdam Dementia Cohort (n =648), Alzheimer's Disease Neuroimaging Initiative (n =544), BioFINDER (n =212), European Medical Information Framework for Alzheimer's Disease (n =809), Lleida (n =88), National Alzheimer's Coordinating Centre (n =63), and Wisconsin Alzheimer's Disease Cohort (n =9). Participants were included with MCI at baseline, a baseline Mini-Mental State Examination, either a magnetic resonance imaging hippocampal volume or CSF Aβ1-42 and pTau181 measurements, and at least six months of follow-up. Elecsys was used in 737 (31%) participants. A Cox model was used to predict time to dementia using the variables in the previous ABIDE model (Maurik et al. 2019). Model discrimination and calibration were evaluated with leave-one-cohort-out cross-validation. Calibration was assessed in the pooled cohort (PC) and amyloid-positive (APos) subgroup, stratified by predicted risk: PC/APos1 (<P16), PC/APos2 (P16-P50), PC/APos3 (P50-P86), PC/APos4 (>P86). RESULT: Of 2372 MCI participants (Table 1; 70±8yrs, 57%F; 41% amyloid-positive) with a median follow-up of 2.1yrs, 997 (42%; 563 [58%] amyloid-positive) developed dementia (IQR:1.3-3.2yrs). The refitted coefficients resemble the prior model, except for a larger effect of the Aβ1-42*pTau interaction (Table 2). Discrimination was similar to the prior ABIDE model, with Harrell's C of 0.70 (95%CI:0.69-0.71), and calibration was good in the pooled cohort, amyloid-positive subgroup (Figure 1), and across CSF assays. In the amyloid-positive subgroup, all four risk groups had a substantial progression risk with a median predicted progression time of 6.3yrs (95%CI:6.1-6.6) in APos1, 3.7yrs (95%CI:3.5-4.0) in APos2, 3.0yrs (95%CI:2.8-3.0) in APos3, and 2.0yrs (95%CI:2.0-2.1) in APos4. CONCLUSION: We updated the ABIDE model for predicting MCI to dementia progression with automated CSF measurements. The model was well calibrated in amyloid-positive patients and may support clinical discussions regarding the initiation of ATTs.
Original languageEnglish
Pages (from-to)e108352
JournalAlzheimer s & dementia
Volume21
DOIs
Publication statusPublished - 1 Dec 2025

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