Evidence map›Paper›PMID 41922867›Full record

Observational studyJournal of neurology2026

Cross-sectional brain volumetric measures and disability outcomes in relapsing-remitting multiple sclerosis.

Michael T G Hayes, Heidi N Beadnall, Daniel Merlo, Mastura Monif, Chao Zhu, Michael Barnett, Katherine Buzzard, Dana Horakova, Tomas Kalincik, Guy Laureys and 11 more

Abstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

21 authors.

Michael T G HayesDepartment of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC, 3004, Australia. michael.hayes@monash.edu.ORCID http://orcid.org/0000-0003-0614-1800
Heidi N BeadnallBrain and Mind Centre, The University of Sydney, Sydney, NSW, 2050, Australia.ORCID http://orcid.org/0000-0003-3734-4133
Daniel MerloDepartment of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC, 3004, Australia.ORCID http://orcid.org/0000-0001-8766-3453
Mastura MonifDepartment of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC, 3004, Australia.ORCID http://orcid.org/0000-0001-6404-9768
Chao ZhuDepartment of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC, 3004, Australia.ORCID http://orcid.org/0000-0003-3951-7501
Michael BarnettBrain and Mind Centre, The University of Sydney, Sydney, NSW, 2050, Australia.
Katherine BuzzardDepartment of Neurology, Box Hill Hospital, Box Hill, VIC, 3128, Australia.
Dana HorakovaDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, 121 08, Prague, Czech Republic.
Tomas KalincikClinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Melbourne, VIC, 3010, Australia.
Guy LaureysDepartment of Neurology, Ghent University Hospital, 9000, Ghent, Belgium.
Elaine LuiDepartment of Medical Imaging, Royal Melbourne Hospital, Melbourne, VIC, 3050, Australia.
Jeannette Lechner-ScottUniversity of Newcastle, Newcastle, NSW, 2308, Australia.
Ai-Lan NguyenClinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Melbourne, VIC, 3010, Australia.
Francesco PattiDepartment of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia", University of Catania, 95124, Catania, Italy.
Diana M Simaicometrix, 3012, Louvain, Belgium.
Dirk Smeetsicometrix, 3012, Louvain, Belgium.
Manuela VaneckovaDepartment of Radiology, First Faculty of Medicine, Charles University and General University Hospital, 121 08, Prague, Czech Republic.
Wim Van Heckeicometrix, 3012, Louvain, Belgium.
Vincent Van PeschDepartment of Laboratory Medicine, Cliniques Universitaires Saint-Luc, 1200, Brussels, Belgium.
Anneke van der WaltDepartment of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC, 3004, Australia.ORCID http://orcid.org/0000-0002-4278-7003
Helmut ButzkuevenDepartment of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC, 3004, Australia.ORCID http://orcid.org/0000-0003-3940-8727

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutomated cross-sectional magnetic resonance imaging (MRI) measures of brain volume are becoming available in clinical practice; however, their prognostic utility in multiple sclerosis remains unclear.

objectivesWe investigated associations between cross-sectional brain and brain lesion volume measures and subsequent disability outcomes in relapsing-remitting multiple sclerosis (RRMS).

methodsWe conducted a multicentre international cohort study using data collected prospectively in the MSBase Registry. MRI analysis was performed using icobrain ms. Associations between MRI volumetric measurements and confirmed disability worsening (CDW), progression independent of relapse activity (PIRA), secondary progressive multiple sclerosis (SPMS) and confirmed disability improvement (CDI) were examined using multivariable Cox proportional hazards models.

resultsA total of 1598 patients were included and 68.6% received high-efficacy disease-modifying therapy during follow-up. Normalised lateral ventricular volume (mL) was significantly associated with all disability outcomes, including PIRA (hazard ratio 1.007; 95% confidence interval 1.002 - 1.012; p = 0.009). Higher normalised whole brain, grey matter and white matter volumes were all significantly associated with a lower hazard of CDW and higher hazard of achieving CDI. Higher normalised white matter volume was also significantly associated with a lower hazard of PIRA. Higher T1-weighted black hole lesion volume was significantly associated with an increased hazard of conversion to SPMS; lesion volume measures were otherwise not significantly associated with disability outcomes.

conclusionsAutomated MRI measures of brain volume from a single time point demonstrated prognostic utility in a highly treated cohort of people with RRMS. The results suggest that normalised lateral ventricular volume is a particularly informative prognostic marker across multiple disability outcomes.

Indexed as

BrainMultiple Sclerosis, Relapsing-RemittingAdultCohort StudiesCross-Sectional StudiesDisability EvaluationDisease ProgressionFemaleGray MatterHumansMagnetic Resonance ImagingMaleMiddle AgedOrgan SizePrognosisRegistriesBrain atrophyLateral ventricle volumeMRIMultiple sclerosisPrognosis

Identifiers

PMID41922867
PMCPMC13043540

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.