Evidence map›Paper›PMID 38420491›Full record

ArticleHeliyon2024

Predictive factors and treatment challenges in malignant progression of relapsing-remitting multiple sclerosis.

Masoud Ghiasian, Rashed Bawand, Sulmaz Jabarzadeh, Abbas Moradi

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Masoud GhiasianDepartment of Neuroimmunology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.
Rashed BawandDepartment of General Medicine, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.
Sulmaz JabarzadehDepartment of Neurology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.
Abbas MoradiDepartment of Social Medicine, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Our objective was to uncover the predictive factors that can help anticipate the malignant progression of individuals with Relapsing-Remitting Multiple Sclerosis (RRMS). Additionally, we sought to analyze and compare the response to treatment between patients with benign and malignant forms of RRMS. Methods: This cohort study included RRMS patients categorized as benign (≥10 years since disease onset, Expanded Disability Status Scale (EDSS) ≤ 1) or malignant (≤5 years since disease onset, EDSS ≥6). Patients' data, including demographics, medical history, treatment, and MRI (Magnetic Resonance Imaging) scans, were collected and statistically analyzed. Results: Among the 254 patients diagnosed with RRMS, 174 were found to have benign RRMS, while the remaining 80 were diagnosed with malignant RRMS. Notably, patients with malignant RRMS exhibited a significantly higher mean age of onset (32.00 ± 7.96 vs. 25.70 ± 17.19; Conclusion: Our study identifies prognostic factors for malignant progression in RRMS, including older age of onset, male gender, increased relapses and hospitalizations, multifocal attacks, higher plaque load, and black hole lesions. The current escalation strategy for DMTs is insufficient for managing malignant RRMS, requiring alternative approaches for improved outcomes. In other words, MS is a spectrum rather than a single disease, and some patients progress to a malignant phenotype of MS that is not effectively treated by the current approach.

Indexed as

Benign MSDisease-modifying therapiesEscalationMalignant MSPrognosisRelapsing-Remitting Multiple Sclerosis (RRMS)

Identifiers

PMID38420491
PMCPMC10900812

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Registered trials

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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.