Evidence map›Paper›PMID 33413634›Full record

ArticleAlzheimer's research & therapy2021

Biomarker testing in MCI patients-deciding who to test.

Ingrid S van Maurik, Hanneke F M Rhodius-Meester, Charlotte E Teunissen, Philip Scheltens, Frederik Barkhof, Sebastian Palmqvist, Oskar Hansson, Wiesje M van der Flier, Johannes Berkhof

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Review
  2. Plasma AβClinical kidney journal · 2023
    Article
  3. Article
  4. Review
  5. Article
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

9 authors.

Ingrid S van MaurikAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands. i.vanmaurik@amsterdamumc.nl.ORCID 0000-0001-6919-8340
Hanneke F M Rhodius-MeesterAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands.
Charlotte E TeunissenNeurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Philip ScheltensAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands.
Frederik BarkhofDepartment of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Sebastian PalmqvistClinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
Oskar HanssonClinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
Wiesje M van der FlierAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands.
Johannes BerkhofDepartment of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe 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.

methodsMCI 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.

resultsThe 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.

interpretationCSF 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.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAmyloid beta-PeptidesBiomarkersDisease ProgressionHumansPeptide Fragmentstau ProteinsAmyloid beta-PeptidesBiomarkersPeptide Fragmentstau ProteinsBiomarkersDecision supportMCI

Identifiers

PMID33413634
PMCPMC7792312

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.