Evidence map›Paper›PMID 28142047›Full record

ArticleJournal of epidemiology2017

A population-based cohort study suggests an increased risk of multiple sclerosis incidence in patients with type 2 diabetes mellitus.

Wen-Hsuan Hou, Chung-Yi Li, Hsin-Hui Chang, Yu Sun, Chiang-Chin Tsai

Open access · goldAbstract read
In one paragraph

Article in Journal of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 10% of its field
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Associations between tooth loss, denture use, and dementia in older Taiwanese adults.Journal of the Chinese Medical Association : JCMA · 2025
    Article
  10. Article
  11. The p66International journal of molecular sciences · 2023
    Review
  12. Review
  13. Article
  14. Article
  15. The prevalence of comorbidities in patients with multiple sclerosis: population-based registry data.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
    Article
  16. Proposed minimal essential co-expression and physical interaction networks involved in the development of cognition impairment in human mid and late life.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors at 5 institutions in 1 country.

Wen-Hsuan HouMaster Program in Long-Term Care, College of Nursing, Taipei Medical University, Taipei, Taiwan; School of Gerontology Health Management, College of Nursing, Taipei Medical University, Taipei, Taiwan; Department of Physical Medicine and Rehabilitation, Taipei Medical University Hospital, Taipei, Taiwan.
Chung-Yi LiDepartment and Institute of Public Health, College of Medicine, National Cheng Kung University, Tainan City, Taiwan; Department of Public Health, College of Public Health, China Medical University, Taichung City, Taiwan.
Hsin-Hui ChangDepartment and Institute of Public Health, College of Medicine, National Cheng Kung University, Tainan City, Taiwan.
Yu SunDepartment of Neurology, En Chu Kong Hospital, Sanxia District, New Taipei City, Taiwan.
Chiang-Chin TsaiDepartment of Surgery, Tainan Sin-Lau Hospital, Tainan, Taiwan; Department of Health Care Administration, Chang Jung Christian University, Tainan, Taiwan. Electronic address: d4233@sinlau.org.tw.
Chang Jung Christian University · TWChina Medical University · TWEn Chu Kong Hospital · TWNational Cheng Kung University · TWTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo prospectively investigate the incidence and relative risks of multiple sclerosis (MS) in patients with type 2 diabetes (T2DM). MATERIALS AND

methodsPatients with T2DM (n = 614,623) and age- and sex-matched controls (n = 614,021) were followed from 2000 to 2008 to identify cases of newly diagnosed MS (ICD-9-CM: 340). The person-year approach with Poisson assumption was used to evaluate the incidence density. We estimated the covariate-adjusted hazard ratio (HR) of MS incidence in relation to T2DM diabetes using a multiple Cox proportional hazard regression model.

resultsOver 9 years of follow-up, 175 T2DM patients were newly diagnosed with MS, and 114 matched controls had the same first-ever diagnosis, representing a covariate-adjusted HR of 1.44 (95% confidence interval [CI], 1.08-1.94). The sex-specific adjusted HR for both men and women with T2DM was also elevated at 1.34 (95% CI, 0.81-2.23) and 1.51 (95% CI, 1.05-2.19), respectively. Women aged ≤50 years had the greatest risk of MS (HR 2.16; 95% CI, 1.02-4.59).

conclusionThis study demonstrated a moderate but significant association of T2DM with MS incidence, and the association was not confounded by socio-demographic characteristics or certain MS-related co-morbidities.

Indexed as

AdultAgedAge DistributionCase-Control StudiesCohort StudiesDiabetes Mellitus, Type 2FemaleFollow-Up StudiesHumansIncidenceInternational Classification of DiseasesMaleMiddle AgedMultiple SclerosisPopulation SurveillanceProportional Hazards ModelsCohort studiesCox proportional hazard modelDiabetes mellitusMultiple sclerosis

Identifiers

PMID28142047
PMCPMC5394222
OpenAlexW2582418772

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.