Evidence map›Paper›PMID 33927255›Full record

ArticleScientific reports2021

Low serum neurofilament light chain values identify optimal responders to dimethyl fumarate in multiple sclerosis treatment.

Paulette Esperanza Walo-Delgado, Susana Sainz de la Maza, Noelia Villarrubia, Enric Monreal, Silvia Medina, Mercedes Espiño, José Ignacio Fernández-Velasco, Eulalia Rodríguez-Martín, Ernesto Roldán, Daniel Lourido and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.1field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Article
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 at 2 institutions in 1 country.

Paulette Esperanza Walo-DelgadoImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
Susana Sainz de la MazaNeurology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Madrid, Spain.
Noelia VillarrubiaImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain. noelia.villarrubia@salud.madrid.org.ORCID 0000-0002-2114-8632
Enric MonrealNeurology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Madrid, Spain.
Silvia MedinaImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
Mercedes EspiñoImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
José Ignacio Fernández-VelascoImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
Eulalia Rodríguez-MartínImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
Ernesto RoldánImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
Daniel LouridoRadiology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Madrid, Spain.
Alfonso MurielClinical Biostatistics Unit, Ramón y Cajal University Hospital, IRYCIS, University of Alcalá, CIBERESP, Madrid, Spain.
Jaime Masjuan-VallejoNeurology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Madrid, Spain.
Lucienne Costa-FrossardNeurology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Madrid, Spain.
Luisa María VillarImmunology Department, Ramón y Cajal University Hospital, IRYCIS, REEM, Ctra. Colmenar Km. 9.100, 28034, Madrid, Spain.
Instituto Cajal · ESUniversidad de Alcalá · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Serum neurofilament light chains (sNfL) are biomarkers of disease activity in multiple sclerosis (MS), but their value to predict response to treatment, and their association with patient immunological profile, need to be further explored. We studied 80 relapsing-remitting MS patients initiating dimethyl fumarate (DMF) treatment. sNfL levels were explored at baseline and at 3, 6 and 12 months by single molecule array. Blood lymphocyte subsets were measured at baseline and at 6 months by flow cytometry. Patients were followed a year and classified as NEDA (no evidence of disease activity) or ODA (ongoing disease activity). NEDA patients had lower sNfL levels at baseline (p = 0.0001), and after three (p = 0.004) and six (p = 0.03) months of DMF treatment. Consequently, low baseline sNfL values (≤ 12 pg/ml) increased the probability of NEDA (OR 5.8; CI 1.82-15.6; p = 0.002, after correcting by disease activity in the previous year), and associated with significant reductions of central memory CD4+ T lymphocytes, interferon-gamma+ CD8+ T lymphocytes, Natural Killer T cells, and memory B cells upon DMF treatment, being the highest differences in memory B cells (p < 0.0001). This shows that low baseline sNfL values identify MS patients with higher probability of optimal response to DMF and of a reduction in effector immune cells.

Indexed as

AdultBiomarkersB-LymphocytesDimethyl FumarateFemaleHumansImmunosuppressive AgentsLongitudinal StudiesMaleMiddle AgedMultiple Sclerosis, Relapsing-RemittingNeurofilament ProteinsProspective StudiesT-LymphocytesTreatment OutcomeBiomarkersDimethyl FumarateImmunosuppressive Agentsneurofilament protein LNeurofilament Proteins

Identifiers

PMID33927255
PMCPMC8085019
OpenAlexW3158028747

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.