Evidence map›Paper›PMID 39961655›Full record

ArticleJournal of neurology, neurosurgery, and psychiatry2025

Predictors of early disability accumulation in newly diagnosed multiple sclerosis: clinical, imaging and cerebrospinal fluid measures.

Markus Lauerer, Tun Wiltgen, Carolin Brückner, Christina Engl, Katrin Giglhuber, Sebastian Lambrecht, Viola Pongratz, Achim Berthele, Christiane Gasperi, Jan S Kirschke and 3 more

Abstract read
In one paragraph

Article in Journal of neurology, neurosurgery, and psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

13 authors.

Markus LauererDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-5711-0054
Tun WiltgenDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Carolin BrücknerDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Christina EnglDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Katrin GiglhuberDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Sebastian LambrechtDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Viola PongratzDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Achim BertheleDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Christiane GasperiDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Jan S KirschkeDepartment of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-7557-0003
Claus ZimmerDepartment of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Bernhard HemmerDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-5985-6784
Mark MühlauDepartment of Neurology, School of Medicine and Health, Technical University of Munich, Munich, Germany mark.muehlau@tum.de.ORCID http://orcid.org/0000-0002-9545-2709

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA growing arsenal of treatment options for relapsing multiple sclerosis (RMS) emphasises the need for early prognostic biomarkers. While evidence for individual markers exists, comprehensive analyses at the time of diagnosis are sparse.

methodsBrain and spinal cord lesion numbers, cerebrospinal fluid parameters, initial symptoms, and Expanded Disability Status Scale (EDSS) score were determined at the time of diagnosis. Confirmed disability accumulation (CDA), defined as a sustained EDSS increase over 6 months, was determined during a 5-year follow-up. All-subsets multivariable logistic regression was performed to identify predictors of CDA. Model performance was assessed via receiver operating characteristic analysis, and individual risks were calculated. Analyses were repeated with progression independent of relapse activity (PIRA) as an outcome.

results113/417 (27.1%) people with RMS experienced CDA on follow-up. Intrathecal IgG synthesis, a higher number of spinal cord lesions, age and polysymptomatic manifestation were identified as independent predictors of CDA. The resulting prediction model yielded an area under the curve (AUC) of 0.75 with a 95% CI of 0.70 to 0.80. Individuals exceeding the optimal thresholds for the three most significant predictors had a 61.8% likelihood of experiencing CDA, whereas those below all three thresholds had a CDA rate of 4.5%. The only significant baseline predictor differentiating PIRA from relapse-associated worsening was a higher number of spinal cord lesions (AUC=0.64, 95% CI 0.54 to 0.74).

conclusionsIntrathecal IgG synthesis, spinal cord lesion number, age and polysymptomatic manifestation are independent predictors of early CDA in newly diagnosed RMS.

Indexed as

Multiple SclerosisMultiple Sclerosis, Relapsing-RemittingAdultBiomarkersBrainDisability EvaluationDisease ProgressionFemaleHumansImmunoglobulin GMagnetic Resonance ImagingMaleMiddle AgedPrognosisSpinal CordBiomarkersImmunoglobulin GCLINICAL NEUROLOGYCSFMRIMULTIPLE SCLEROSISNEUROIMMUNOLOGY

Identifiers

PMID39961655
PMCPMC12418557

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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.