Evidence map›Paper›PMID 34487400›Full record

ArticleEuropean journal of neurology2021

Central nervous system atrophy predicts future dynamics of disability progression in a real-world multiple sclerosis cohort.

Charidimos Tsagkas, Yvonne Naegelin, Michael Amann, Athina Papadopoulou, Christian Barro, M Mallar Chakravarty, Laura Gaetano, Jens Wuerfel, Ludwig Kappos, Jens Kuhle and 4 more

Abstract read
In one paragraph

Article in European journal of neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Charidimos TsagkasNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.ORCID 0000-0002-2586-6316
Yvonne NaegelinNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Michael AmannNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Athina PapadopoulouNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Christian BarroNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.ORCID 0000-0002-7795-7383
M Mallar ChakravartyDepartment of Psychiatry, McGill University, Montreal, QC, Canada.
Laura GaetanoF. Hoffmann-La Roche Ltd, Basel, Switzerland.
Jens WuerfelMedical Image Analysis Center AG, Basel, Switzerland.
Ludwig KapposNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Jens KuhleNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Cristina GranzieraNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Till SprengerNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
Stefano MagonPharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland.
Katrin ParmarNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeIn an era of individualized multiple sclerosis (MS) patient management, biomarkers for accurate prediction of future clinical outcomes are needed. We aimed to evaluate the potential of short-term magnetic resonance imaging (MRI) atrophy measures and serum neurofilament light chain (sNfL) as predictors of the dynamics of disability accumulation in relapse-onset MS.

methodsBrain gray and white matter, thalamic, striatal, pallidal and cervical spinal cord volumes, and lesion load were measured over three available time points (mean time span 2.24 ± 0.70 years) for 183 patients (140 relapsing-remitting [RRMS] and 43 secondary-progressive MS (SPMS); 123 female, age 46.4 ± 11.0 years; disease duration 15.7 ± 9.3 years), and their respective annual changes were calculated. Baseline sNfL was also measured at the third available time point for each patient. Subsequently, patients underwent annual clinical examinations over 5.4 ± 3.7 years including Expanded Disability Status Scale (EDSS) scoring, the nine-hole peg test and the timed 25-foot walk test.

resultsHigher annual spinal cord atrophy rates and lesion load increase predicted higher future EDSS score worsening over time in SPMS. Lower baseline thalamic volumes predicted higher walking speed worsening over time in RRMS. Lower baseline gray matter, as well as higher white matter and spinal cord atrophy rates, lesion load increase, baseline striatal volumes and baseline sNfL, predicted higher future hand dexterity worsening over time. All models showed reasonable to high prediction accuracy.

conclusionThis study demonstrates the capability of short-term MRI metrics to accurately predict future dynamics of disability progression in a real-world relapse-onset MS cohort. The present study represents a step towards the utilization of structural MRI measurements in patient care.

Indexed as

Multiple SclerosisMultiple Sclerosis, Chronic ProgressiveMultiple Sclerosis, Relapsing-RemittingAdultAtrophyBrainDisability EvaluationDisease ProgressionFemaleGray MatterHumansMagnetic Resonance ImagingMiddle AgedatrophybiomarkersMRImultiple sclerosisprediction models

Identifiers

PMID34487400
PMCPMC9292558

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LicenceCC BY-NC-ND
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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.