Evidence map›Paper›PMID 29687310›Full record

ReviewCurrent treatment options in neurology2018

Genotype and Phenotype in Multiple Sclerosis-Potential for Disease Course Prediction?

Vilija G Jokubaitis, Yuan Zhou, Helmut Butzkueven, Bruce V Taylor

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Clinical trials in multiple sclerosis: potential future trial designs.Therapeutic advances in neurological disorders · 2019
    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

4 authors.

Vilija G JokubaitisDepartment of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia.
Yuan ZhouMenzies Institute for Medical Research, University of Tasmania, Hobart, Australia.
Helmut ButzkuevenDepartment of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia.
Bruce V TaylorMenzies Institute for Medical Research, University of Tasmania, Hobart, Australia. bruce.taylor@utas.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis review will examine the current evidence that genetic and/or epigenetic variation may influence the multiple sclerosis (MS) clinical course, phenotype, and measures of MS severity including disability progression and relapse rate. RECENT

findingsThere is little evidence that MS clinical phenotype is under significant genetic control. There is increasing evidence that there may be genetic determinants of the rate of disability progression. However, studies that can analyse disability progression and take into account all the confounding variables such as treatment, clinical characteristics, and environmental factors are by necessity longitudinal, relatively small, and generally of short duration, and thus do not lend themselves to the assessment of hundreds of thousands of genetic variables obtained from GWAS. Despite this, there is recent evidence to support the association of genetic loci with relapse rate. Recent progress suggests that genetic variations could be associated with disease severity, but not MS clinical phenotype, but these findings are not definitive and await replication. Pooling of study results, application of other genomic techniques including epigenomics, and analysis of biomarkers of progression could functionally validate putative severity markers.

Indexed as

GenotypeMultiple sclerosisPhenotypeSeverity

Identifiers

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.