Evidence map›Paper›PMID 42459947›Full record

ArticleMultiple sclerosis journal - experimental, translational and clinical

Cross-platform comparison of blood glial fibrillary acidic protein quantification in healthy controls and multiple sclerosis.

Anne Ladwig, Antje Torge, Kim Kristin Falk, Antonia Dammann, Melanie Schlapkohl, Klarissa Hanja Stürner, Klaus-Peter Wandinger, Robert Markewitz, Ralf Junker, Malte Ziemann and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Multiple sclerosis journal - experimental, translational and clinical. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Anne LadwigDepartment of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany.ORCID https://orcid.org/0000-0003-3193-3981
Antje TorgeInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Kim Kristin FalkInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Antonia DammannDepartment of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany.
Melanie SchlapkohlInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Klarissa Hanja StürnerDepartment of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany.ORCID https://orcid.org/0000-0003-2199-3315
Klaus-Peter WandingerInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Robert MarkewitzInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Ralf JunkerInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Malte ZiemannInstitute of Transfusion Medicine, University Hospital Schleswig-Holstein, Kiel, Germany.
Sven Ole SchusterInstitute of Transfusion Medicine, University Hospital Schleswig-Holstein, Kiel, Germany.
Johannes PielDepartment of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany.
Frank LeypoldtDepartment of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany; Institute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.
Justina DargvainieneInstitute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany.ORCID https://orcid.org/0009-0002-4114-3748

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glial fibrillary acidic protein (GFAP) is an astrocyte marker increasingly recognized as a biomarker of disease progression in multiple sclerosis (MS). While highly sensitive assays are available, cross-platform harmonization remains insufficient, limiting routine clinical implementation. Objective: To compare three fully automated GFAP assays, assess their analytical agreement and clinical performance across MS subtypes and healthy controls, and evaluate cross-platform conversion approaches. Methods: Serum samples from 435 individuals (298 healthy controls, 51 relapsing-remitting MS (RRMS), 41 primary/secondary progressive MS (PPMS/SPMS)) were analyzed using three automated platforms: Simoa HD-X (Quanterix), Elecsys (Roche), and Lumipulse G600 (Fujirebio). Correlation analyses, Passing-Bablok regression, and Lin's concordance coefficients were applied. Published regression formulas were compared with study-derived equations. Results: Strong correlations were observed across all platforms ( Conclusion: Serum GFAP measurements demonstrate high clinical comparability across automated platforms despite systematic differences in absolute values. Robust harmonization strategies and externally validated conversion models are required before broad implementation in routine MS diagnostics.

Indexed as

BiomarkersGFAPmultiple sclerosisplatform comparison

Identifiers

PMID42459947
PMCPMC13369371

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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.