Evidence map›Paper›PMID 28155580›Full record

ArticleMultiple sclerosis (Houndmills, Basingstoke, England)2017

Age Related Multiple Sclerosis Severity Score: Disability ranked by age.

Ali Manouchehrinia, Helga Westerlind, Elaine Kingwell, Feng Zhu, Robert Carruthers, Ryan Ramanujam, Maria Ban, Anna Glaser, Stephen Sawcer, Helen Tremlett and 1 more

Abstract read
In one paragraph

Article in Multiple sclerosis (Houndmills, Basingstoke, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
97citing papers in PubMed, 4 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

97 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Trial
  7. Article
  8. Article
  9. Article
  10. Tobacco smoking disrupts bile acid and tryptophan metabolism in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026
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  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
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  18. Article
  19. Predictors of Ability to Work in Multiple Sclerosis.CPT: pharmacometrics & systems pharmacology · 2025
    Article
  20. Article

37 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

11 authors.

Ali ManouchehriniaDepartment of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden.
Helga WesterlindInstitute of Environmental Medicine (IMM), Karolinska Institutet, Stockholm, Sweden.
Elaine KingwellDivision of Neurology, Faculty of Medicine, UBC Hospital, The University of British Columbia, Vancouver, BC, Canada.
Feng ZhuDivision of Neurology, Faculty of Medicine, UBC Hospital, The University of British Columbia, Vancouver, BC, Canada.
Robert CarruthersDivision of Neurology, Faculty of Medicine, UBC Hospital, The University of British Columbia, Vancouver, BC, Canada.
Ryan RamanujamDepartment of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden.
Maria BanDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Anna GlaserDepartment of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden.
Stephen SawcerDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Helen TremlettDivision of Neurology, Faculty of Medicine, UBC Hospital, The University of British Columbia, Vancouver, BC, Canada.
Jan HillertDepartment of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Multiple Sclerosis Severity Score (MSSS) is obtained by normalising the Expanded Disability Status Scale (EDSS) score for disease duration and has been a valuable tool in cross-sectional studies.

objectiveTo assess whether use of age rather than the inherently ambiguous disease duration was a feasible approach.

methodWe pooled disability data from three population-based cohorts and developed an Age Related Multiple Sclerosis Severity (ARMSS) score by ranking EDSS scores based on the patient's age at the time of assessment. We established the power to detect a difference between groups afforded by the ARMSS score and assessed its relative consistency over time.

resultsThe study population included 26058 patients from Sweden ( n = 11846), Canada ( n = 6179) and the United Kingdom ( n = 8033). There was a moderate correlation between EDSS and disease duration ( r = 0.46, 95% confidence interval (CI): 0.45-0.47) and between EDSS and age ( r = 0.44, 95% CI: 0.43-0.45). The ARMSS scores showed comparable power to detect disability differences between groups to the updated and original MSSS.

conclusionSince age is typically unbiased and readily obtained, and the ARMSS and MSSS were comparable, the ARMSS may provide a more versatile tool and could minimise study biases and loss of statistical power caused by inaccurate or missing onset dates.

Indexed as

Age FactorsPersons with DisabilitiesSeverity of Illness IndexAdolescentAdultAgedCanadaFemaleHumansMaleMiddle AgedMultiple SclerosisSwedenTime FactorsUnited KingdomYoung Adultdisabilitydisease severityEDSSMSSSmultiple sclerosis

Identifiers

PMID28155580
PMCPMC5700773

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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.