Evidence map›Paper›PMID 34704393›Full record

Trial reportAnnals of clinical and translational neurology2021

Measuring treatment response to advance precision medicine for multiple sclerosis.

Peter A Calabresi, Ludwig Kappos, Gavin Giovannoni, Tatiana Plavina, Irene Koulinska, Michael R Edwards, Bernd Kieseier, Carl de Moor, Elias S Sotirchos, Elizabeth Fisher and 2 more

Open access · goldAbstract readClinical Trial, Phase IIIRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Annals of clinical and translational neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Pathways to cures for multiple sclerosis: A research roadmap.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022
    Article
  5. Neurofilaments contribution in clinic: state of the art.Frontiers in aging neuroscience · 2022
    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

12 authors at 4 institutions in 4 countries.

Peter A CalabresiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0002-7776-6472
Ludwig KapposNeurologic Clinic and Policlinic, Departments of Medicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland.ORCID 0000-0003-4175-5509
Gavin GiovannoniBlizzard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Tatiana PlavinaBiogen, Cambridge, Massachusetts, USA.
Irene KoulinskaBiogen, Cambridge, Massachusetts, USA.
Michael R EdwardsBiogen, Cambridge, Massachusetts, USA.
Bernd KieseierBiogen, Cambridge, Massachusetts, USA.
Carl de MoorBiogen, Cambridge, Massachusetts, USA.
Elias S SotirchosDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0002-8812-1637
Elizabeth FisherBiogen, Cambridge, Massachusetts, USA.
Richard A RudickBiogen, Cambridge, Massachusetts, USA.
Alfred SandrockBiogen, Cambridge, Massachusetts, USA.
Biogen (United States) · USJohns Hopkins University · USQueen Mary University of London · GBUniversity of Basel · CH

Funding

Biogen
6 · The paper itself

Abstract

objectiveTo assess the independent contributions of clinical measures (relapses, Expanded Disability Status Scale [EDSS] scores, and neuroperformance measures) and nonclinical measures (new brain magnetic resonance imaging [MRI] activity and serum neurofilament light chain [sNfL] levels) for distinguishing natalizumab-treated from placebo-treated patients.

methodsWe conducted post hoc analyses using data from the AFFIRM trial of natalizumab for multiple sclerosis. We used multivariable regression analyses with predictors (EDSS progression, no relapse, new or enlarging MRI activity, brain atrophy, sNfL levels, and neuroperformance worsening) to identify measures that independently discriminated between treatment groups.

resultsThe multivariable model that best distinguished natalizumab from placebo was no new or enlarging T2 or gadolinium-enhancing activity on MRI (odds ratio; 95% confidence interval: 7.2; 4.7-10.9), year 2 sNfL levels <97.5th percentile (4.1; 2.6-6.2), and no relapses in years 0-2 (2.1; 1.5-3.0). The next best-fitting model was a two-component model that included no MRI activity and sNfL levels <97.5th percentile at year 2. There was little difference between the three- and two-component models.

interpretationNonclinical measures (new MRI activity and sNfL levels) discriminate between treatment and placebo groups similarly to or better than clinical outcomes composites and have implications for patient monitoring.

Indexed as

Outcome Assessment, Health CareAdultFemaleFollow-Up StudiesHumansImmunologic FactorsMagnetic Resonance ImagingMaleMiddle AgedMultiple Sclerosis, Relapsing-RemittingNatalizumabNeurofilament ProteinsPrecision MedicineImmunologic FactorsNatalizumabneurofilament protein LNeurofilament Proteins

Identifiers

PMID34704393
PMCPMC8607451
OpenAlexW3208730487

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.