Evidence map›Paper›PMID 39556505›Full record

ArticleAnnals of clinical and translational neurology2025

Determinants of long-term paramagnetic rim lesion evolution in people with multiple sclerosis.

Jack A Reeves, Alexander Bartnik, Maryam Mohebbi, Murali Ramanathan, Niels Bergsland, Dejan Jakimovski, Gregory E Wilding, Fahad Salman, Ferdinand Schweser, Bianca Weinstock-Guttman and 5 more

Abstract read
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In one paragraph

Article in Annals of clinical and translational neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

15 authors.

Jack A ReevesBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Alexander BartnikBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Maryam MohebbiBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Murali RamanathanDepartment of Pharmaceutical Sciences, State University of New York, Buffalo, New York, USA.ORCID 0000-0002-9943-150X
Niels BergslandBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.ORCID 0000-0002-7792-0433
Dejan JakimovskiBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.ORCID 0000-0001-7114-4958
Gregory E WildingDepartment of Biostatistics, School of Public Health and Health Professions, State University of New York at Buffalo, Buffalo, New York, USA.
Fahad SalmanBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Ferdinand SchweserBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Bianca Weinstock-GuttmanJacobs Neurological Institute, Buffalo, New York, USA.
David HojnackiDepartment of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Svetlana EckertDepartment of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Francesca BagnatoNeuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0001-9544-9019
Michael G DwyerBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Robert ZivadinovBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.ORCID 0000-0002-7799-1485

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
Deep Gray Matter Iron and Disease Progression in Multiple SclerosisR01NS114227 · NINDS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI SCHWESER, FERDINAND · 2021 to 2024
$1.5M
NCATS NIH HHS UL1 TR001412NCATS NIH HHS UL1TR001412NINDS NIH HHS R01 NS114227NINDS NIH HHS R01NS114227
6 · The paper itself

Abstract

objectiveBaseline paramagnetic rim lesion (PRL) load predicts disease progression in people with multiple sclerosis (pwMS). Understanding how PRLs relate to other known MS-related factors, and the practical utility of PRLs in clinical trials, is crucial for informing clinical decision-making and guiding development of novel disease-modifying treatments (DMTs).

methodsThis study included 152 pwMS enrolled in a larger prospective, longitudinal cohort study who had 3T MRI scans and clinical assessments at baseline and 5- or 10-year follow-ups. PRLs were identified on baseline 3T quantitative susceptibility maps and classified as persisting, disappearing, or newly appearing at follow-up. The relationships between PRL evolution and clinical, radiological, environmental, and genetic characteristics were assessed, and clinical trial sample sizes were estimated using PRL appearance or disappearance as outcome measures.

resultsDMT use was associated with lower odds of new PRL appearance (for high-efficacy DMTs: odds ratio = 0.088, p = 0.024), but not disappearance. Current smoking status was associated with greater baseline PRL number (B = 0.527 additional PRLs, p = 0.013). A 24-month clinical trial in people with progressive MS for a DMT that doubles the rate of PRL rim disappearance would require an estimated 118 people with progressive MS per group at 80% statistical power.

interpretationEarly MS diagnosis and subsequent DMT initiation may reduce new chronic active inflammation. However, the utility of PRL disappearance or new PRL appearance as outcome measures in clinical trials is limited by potentially large sample sizes that are needed for moderate efficacy drugs.

Indexed as

Disease ProgressionMultiple SclerosisAdultFemaleFollow-Up StudiesHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedProspective Studies

Identifiers

PMID39556505
PMCPMC11822801

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