Evidence map›Paper›PMID 29500303›Full record

ReviewCold Spring Harbor perspectives in medicine2019

Biomarkers in Multiple Sclerosis.

Anu Paul, Manuel Comabella, Roopali Gandhi

Open access · bronzeAbstract readReview
In one paragraph

Review in Cold Spring Harbor perspectives in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 3 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

80 citing papers in PubMed, 3 syntheses or guidelines pooled it, 152 citations in OpenAlex.

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20 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 3 countries.

Anu Paul *Department of Neurology, Ann Romney Center for Neurological Diseases, Brigham and Women's Hospital, Boston, Massachusetts 02115.
Manuel Comabella *Department of Neurology, MS Centre of Catalonia, Vall d'Hebron University Hospital, Barcelona 08035, Spain.
Roopali Gandhi *Department of Neurology, Ann Romney Center for Neurological Diseases, Brigham and Women's Hospital, Boston, Massachusetts 02115.
Brigham and Women's Hospital · USVall d'Hebron Hospital Universitari · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease with a complex clinical course characterized by inflammation, demyelination, and axonal degeneration. Diagnosis of MS most commonly includes finding lesions in at least two separate areas of the central nervous system (CNS), including the brain, spinal cord, and optic nerves. In recent years, there has been a remarkable increase in the number of available treatments for MS. An optimal treatment is usually based on a personalized approach determined by an individual patient's prognosis and treatment risks. Biomarkers that can predict disability progression, monitor ongoing disease activity, and assess treatment response are integral in making important decisions regarding MS treatment. This review describes MS biomarkers that are currently being used in clinical practice; it also reviews and consolidates published findings from clinically relevant potential MS biomarkers in recent years. The work also discusses the challenges of validating and application of biomarkers in MS clinical practice.

Indexed as

Antibodies, NeutralizingBiological Specimen BanksBiomarkersBrain DiseasesEarly DiagnosisGenetic MarkersHumansMagnetic Resonance ImagingMultiple SclerosisPolyomavirus InfectionsPrognosisResearch DesignRisk AssessmentAntibodies, NeutralizingBiomarkersGenetic Markers

Identifiers

PMID29500303
PMCPMC6396336
OpenAlexW2792356388

What OpenQuestion holds

Textmetadata
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.