Evidence map›Paper›PMID 28193256›Full record

ArticleAlzheimer's research & therapy2017

Unbiased estimates of cerebrospinal fluid β-amyloid 1-42 cutoffs in a large memory clinic population.

Daniela Bertens, Betty M Tijms, Philip Scheltens, Charlotte E Teunissen, Pieter Jelle Visser

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Italian intersocietal recommendations for restructuring the diagnostic-therapeutic pathway for the implementation and appropriate use of anti-amyloid monoclonal antibodies in Alzheimer's disease.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
  10. A modelling approach to derive population-specific cutoff for plasma p-Tau217.The journal of prevention of Alzheimer's disease · 2025
    Article
  11. Associations between the EAT-Lancet planetary health diet and incident dementia.The journal of prevention of Alzheimer's disease · 2025
    Article
  12. Article
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  14. Observational
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  16. An accurate fully automated panel of plasma biomarkers for Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Daniela BertensDepartment of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Betty M TijmsDepartment of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Philip ScheltensDepartment of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Charlotte E TeunissenDepartment of Clinical Chemistry, Neurochemistry Lab and Biobank, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Pieter Jelle VisserDepartment of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands. pj.visser@vumc.nl.ORCID http://orcid.org/0000-0001-8008-9727

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe sought to define a cutoff for β-amyloid 1-42 in cerebrospinal fluid (CSF), a key marker for Alzheimer's disease (AD), with data-driven Gaussian mixture modeling in a memory clinic population.

methodsWe performed a combined cross-sectional and prospective cohort study. We selected 2462 subjects with subjective cognitive decline, mild cognitive impairment, AD-type dementia, and dementia other than AD from the Amsterdam Dementia Cohort. We defined CSF β-amyloid 1-42 cutoffs by data-driven Gaussian mixture modeling in the total population and in subgroups based on clinical diagnosis, age, and apolipoprotein E (APOE) genotype. We investigated whether abnormal β-amyloid 1-42 as defined by the data-driven cutoff could better predict progression to AD-type dementia than abnormal β-amyloid 1-42 defined by a clinical diagnosis-based cutoff using Cox proportional hazards regression.

resultsIn the total group of patients, we found a cutoff for abnormal CSF β-amyloid 1-42 of 680 pg/ml (95% CI 660-705 pg/ml). Similar cutoffs were found within diagnostic and APOE genotype subgroups. The cutoff was higher in elderly subjects than in younger subjects. The data-driven cutoff was higher than our clinical diagnosis-based cutoff and had a better predictive accuracy for progression to AD-type dementia in nondemented subjects (HR 7.6 versus 5.2, p < 0.01).

conclusionsMixture modeling is a robust method to determine cutoffs for CSF β-amyloid 1-42. It might better capture biological changes that are related to AD than cutoffs based on clinical diagnosis.

Indexed as

AgedAmyloid beta-PeptidesApolipoproteins EBiomarkersCognition DisordersCross-Sectional StudiesDementiaFemaleFollow-Up StudiesHumansMaleMiddle AgedPeptide FragmentsProportional Hazards ModelsProspective StudiesAmyloid beta-Peptidesamyloid beta-protein (1-42)Apolipoproteins EBiomarkersPeptide FragmentsAlzheimer’s diseaseCerebrospinal fluidDiagnosisMCI

Identifiers

PMID28193256
PMCPMC5307885

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.