Evidence map›Paper›PMID 27648465›Full record

ReviewNeurology(R) neuroimmunology & neuroinflammation2016

The topographical model of multiple sclerosis: A dynamic visualization of disease course.

Stephen C Krieger, Karin Cook, Scott De Nino, Madhuri Fletcher

Abstract readReview
In one paragraph

Review in Neurology(R) neuroimmunology & neuroinflammation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 2 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

71 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  20. Microglia and Multiple Sclerosis.Advances in neurobiology · 2024
    Review

11 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

4 authors.

Stephen C KriegerCorinne Goldsmith Dickinson Center for MS (S.C.K.), Icahn School of Medicine at Mount Sinai, New York; and Harrison and Star (K.C., S.D.N., M.F.), New York, NY.
Karin CookCorinne Goldsmith Dickinson Center for MS (S.C.K.), Icahn School of Medicine at Mount Sinai, New York; and Harrison and Star (K.C., S.D.N., M.F.), New York, NY.
Scott De NinoCorinne Goldsmith Dickinson Center for MS (S.C.K.), Icahn School of Medicine at Mount Sinai, New York; and Harrison and Star (K.C., S.D.N., M.F.), New York, NY.
Madhuri FletcherCorinne Goldsmith Dickinson Center for MS (S.C.K.), Icahn School of Medicine at Mount Sinai, New York; and Harrison and Star (K.C., S.D.N., M.F.), New York, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Relapses and progression contribute to multiple sclerosis (MS) disease course, but neither the relationship between them nor the spectrum of clinical heterogeneity has been fully characterized. A hypothesis-driven, biologically informed model could build on the clinical phenotypes to encompass the dynamic admixture of factors underlying MS disease course. In this medical hypothesis, we put forth a dynamic model of MS disease course that incorporates localization and other drivers of disability to propose a clinical manifestation framework that visualizes MS in a clinically individualized way. The topographical model encapsulates 5 factors (localization of relapses and causative lesions; relapse frequency, severity, and recovery; and progression rate), visualized utilizing dynamic 3-dimensional renderings. The central hypothesis is that, like symptom recrudescence in Uhthoff phenomenon and pseudoexacerbations, progression clinically recapitulates prior relapse symptoms and unmasks previously silent lesions, incrementally revealing underlying lesion topography. The model uses real-time simulation software to depict disease course archetypes and illuminate several well-described but poorly reconciled phenomena including the clinical/MRI paradox and prognostic significance of lesion location and burden on disease outcomes. Utilization of this model could allow for earlier and more clinically precise identification of progressive MS and predictive implications can be empirically tested.

Identifiers

PMID27648465
PMCPMC5015541

What OpenQuestion holds

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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.