Evidence map›Paper›PMID 39328985›Full record

ArticleNeuroimage. Reports2024

Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial.

Thomas Williams, Nevin John, Alberto Calvi, Alessia Bianchi, Floriana De Angelis, Anisha Doshi, Sarah Wright, Madiha Shatila, Marios C Yiannakas, Fatima Chowdhury and 14 more

Registry-linked trialAbstract read
In one paragraph

Article in Neuroimage. Reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03387670 (A Phase 3 Randomised, Double Blind, Clinical Trial Investigating the Effectiveness of Repurposed Simvastatin Compared to Placebo, in Secondary Progressive Multiple Sclerosis, in Slowing the Progression of Disability), which is not on this map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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.

NCT03387670 phase3completednot on this map

A Phase 3 Randomised, Double Blind, Clinical Trial Investigating the Effectiveness of Repurposed Simvastatin Compared to Placebo, in Secondary Progressive Multiple Sclerosis, in Slowing the Progression of Disability

TypeinterventionalSponsorUniversity College, LondonRan2018 to 2024Enrolled964ConditionsSecondary Progressive Multiple Sclerosis (SPMS)ArmsSimvastatin, Placebo
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

24 authors.

Thomas WilliamsNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Nevin JohnNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Alberto CalviNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Alessia BianchiNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Floriana De AngelisNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Anisha DoshiNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Sarah WrightNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Madiha ShatilaNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Marios C YiannakasNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Fatima ChowdhuryNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Jon StuttersNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Antonio RicciardiNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Ferran PradosNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
David MacManusNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Francesco GrussuNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Anita KarsaDepartment of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Becky SamsonNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Marco BattistonNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Claudia A M Gandini Wheeler-KingshottNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Karin ShmueliDepartment of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Olga CiccarelliNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Frederik BarkhofNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
Jeremy ChatawayNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.
UCL MS-STAT2 investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Deep grey matter pathology is a key driver of disability worsening in people with multiple sclerosis. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique which quantifies local magnetic susceptibility from variations in phase produced by changes in the local magnetic field. In the deep grey matter, susceptibility has previously been validated against tissue iron concentration. However, it currently remains unknown whether susceptibility is abnormal in older progressive MS cohorts, and whether it correlates with disability. Objectives: To investigate differences in mean regional susceptibility in deep grey matter between people with secondary progressive multiple sclerosis (SPMS) and healthy controls; to examine in patients the relationships between deep grey matter susceptibility and clinical and imaging measures of disease severity. Methods: Baseline data from a subgroup of the MS-STAT2 trial (simvastatin vs. placebo in SPMS, NCT03387670) were included. The subgroup underwent clinical assessments and an advanced MRI protocol at 3T. A cohort of age-matched healthy controls underwent the same MRI protocol. Susceptibility maps were reconstructed using a robust QSM pipeline from multi-echo 3D gradient-echo sequence. Regions of interest (ROIs) in the thalamus, globus pallidus and putamen were segmented from 3D T1-weighted images, and lesions segmented from 3D fluid-attenuated inversion recovery images. Linear regression was used to compare susceptibility from ROIs between patients and controls, adjusting for age and sex. Where significant differences were found, we further examined the associations between ROI susceptibility and clinical and imaging measures of MS severity. Results: 149 SPMS (77% female; mean age: 53 yrs; median Expanded Disability Status Scale (EDSS): 6.0 [interquartile range 4.5-6.0]) and 33 controls (52% female, mean age: 57) were included.Thalamic susceptibility was significantly lower in SPMS compared to controls: mean (SD) 28.6 (12.8) parts per billion (ppb) in SPMS vs. 39.2 (12.7) ppb in controls; regression coefficient: -12.0 [95% confidence interval: -17.0 to -7.1], p < 0.001. In contrast, globus pallidus and putamen susceptibility were similar between both groups.In SPMS, a 10 ppb lower thalamic susceptibility was associated with a +0.13 [+0.01 to +0.24] point higher EDSS (p < 0.05), a -2.4 [-3.8 to -1.0] point lower symbol digit modality test (SDMT, p = 0.001), and a -2.4 [-3.7 to -1.1] point lower Sloan low contrast acuity, 2.5% (p < 0.01).Lower thalamic susceptibility was also strongly associated with a higher T2 lesion volume (T2LV, p < 0.001) and lower normalised whole brain, deep grey matter and thalamic volumes (all p < 0.001). Conclusions: The reduced thalamic susceptibility found in SPMS compared to controls suggests that thalamic iron concentrations are lower at this advanced stage of the disease. The observed relationships between lower thalamic susceptibility and more severe physical, cognitive and visual disability suggests that reductions in thalamic iron may correlate with important mechanisms of clinical disease progression. Such mechanisms appear to intimately link reductions in thalamic iron with higher T2LV and the development of thalamic atrophy, encouraging further research into QSM-derived thalamic susceptibility as a biomarker of disease severity in SPMS.

Indexed as

Deep grey matterIronMultiple sclerosisQuantitative susceptibility mappingThalamus

Identifiers

PMID39328985
PMCPMC11422291

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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 Socratic graph.