Population attributable fractions and joint effects of key risk factors for multiple sclerosis.
Identifieur interne : 002090 ( PubMed/Corpus ); précédent : 002089; suivant : 002091Population attributable fractions and joint effects of key risk factors for multiple sclerosis.
Auteurs : Iaf Van Der Mei ; R M Lucas ; B V Taylor ; P C Valery ; T. Dwyer ; T J Kilpatrick ; M P Pender ; D. Williams ; C. Chapman ; P. Otahal ; A-L PonsonbySource :
- Multiple sclerosis (Houndmills, Basingstoke, England) [ 1477-0970 ] ; 2016.
English descriptors
- KwdEn :
- Adolescent, Adult, Antibodies, Viral (blood), Australia (epidemiology), Case-Control Studies, Epstein-Barr Virus Nuclear Antigens (immunology), Female, Gene-Environment Interaction, HLA-DR Serological Subtypes (genetics), HLA-DR Serological Subtypes (immunology), Humans, Immunoglobulin G (blood), Incidence, Infectious Mononucleosis (epidemiology), Logistic Models, Male, Middle Aged, Multiple Sclerosis (diagnosis), Multiple Sclerosis (epidemiology), Multiple Sclerosis (genetics), Multiple Sclerosis (immunology), Multivariate Analysis, Odds Ratio, Polymorphism, Single Nucleotide, Prevalence, Risk Assessment, Risk Factors, Seasons, Smoking (adverse effects), Smoking (epidemiology), Sunlight, Time Factors, Young Adult.
- MESH :
- chemical , blood : Antibodies, Viral, Immunoglobulin G.
- adverse effects : Smoking.
- diagnosis : Multiple Sclerosis.
- epidemiology : Australia, Infectious Mononucleosis, Multiple Sclerosis, Smoking.
- chemical , genetics : HLA-DR Serological Subtypes, Multiple Sclerosis.
- chemical , immunology : Epstein-Barr Virus Nuclear Antigens, HLA-DR Serological Subtypes, Multiple Sclerosis.
- Adolescent, Adult, Case-Control Studies, Female, Gene-Environment Interaction, Humans, Incidence, Logistic Models, Male, Middle Aged, Multivariate Analysis, Odds Ratio, Polymorphism, Single Nucleotide, Prevalence, Risk Assessment, Risk Factors, Seasons, Sunlight, Time Factors, Young Adult.
Abstract
We examined the combined effect of having multiple key risk factors and the interactions between the key risk factors of multiple sclerosis (MS).
DOI: 10.1177/1352458515594040
PubMed: 26199349
Links to Exploration step
pubmed:26199349Le document en format XML
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<term>Australia (epidemiology)</term>
<term>Case-Control Studies</term>
<term>Epstein-Barr Virus Nuclear Antigens (immunology)</term>
<term>Female</term>
<term>Gene-Environment Interaction</term>
<term>HLA-DR Serological Subtypes (genetics)</term>
<term>HLA-DR Serological Subtypes (immunology)</term>
<term>Humans</term>
<term>Immunoglobulin G (blood)</term>
<term>Incidence</term>
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<term>Logistic Models</term>
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<term>Middle Aged</term>
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<term>Multiple Sclerosis (epidemiology)</term>
<term>Multiple Sclerosis (genetics)</term>
<term>Multiple Sclerosis (immunology)</term>
<term>Multivariate Analysis</term>
<term>Odds Ratio</term>
<term>Polymorphism, Single Nucleotide</term>
<term>Prevalence</term>
<term>Risk Assessment</term>
<term>Risk Factors</term>
<term>Seasons</term>
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<front><div type="abstract" xml:lang="en">We examined the combined effect of having multiple key risk factors and the interactions between the key risk factors of multiple sclerosis (MS).</div>
</front>
</TEI>
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<DateCreated><Year>2016</Year>
<Month>03</Month>
<Day>18</Day>
</DateCreated>
<DateCompleted><Year>2016</Year>
<Month>12</Month>
<Day>19</Day>
</DateCompleted>
<DateRevised><Year>2016</Year>
<Month>12</Month>
<Day>30</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1477-0970</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>22</Volume>
<Issue>4</Issue>
<PubDate><Year>2016</Year>
<Month>Apr</Month>
</PubDate>
</JournalIssue>
<Title>Multiple sclerosis (Houndmills, Basingstoke, England)</Title>
<ISOAbbreviation>Mult. Scler.</ISOAbbreviation>
</Journal>
<ArticleTitle>Population attributable fractions and joint effects of key risk factors for multiple sclerosis.</ArticleTitle>
<Pagination><MedlinePgn>461-9</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1177/1352458515594040</ELocationID>
<Abstract><AbstractText Label="AIM" NlmCategory="OBJECTIVE">We examined the combined effect of having multiple key risk factors and the interactions between the key risk factors of multiple sclerosis (MS).</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We performed an incident case-control study including cases with a first clinical diagnosis of central nervous system demyelination (FCD) and population-based controls.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Compared to those without any risk factors, those with one, two, three, and four or five risk factors had increased odds of being an FCD case of 2.12 (95% confidence interval (CI), 1.11-4.03), 4.31 (95% CI, 2.24-8.31), 7.96 (95% CI, 3.84-16.49), and 21.24 (95% CI, 5.48-82.40), respectively. Only HLA-DR15 and history of infectious mononucleosis interacted significantly on the additive scale (Synergy index, 3.78; p = 0.03). The five key risk factors jointly accounted for 63.8% (95% CI, 43.9-91.4) of FCD onset. High anti-EBNA IgG was another important contributor.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">A high proportion of FCD onset can be explained by the currently known risk factors, with HLA-DR15, ever smoking and low cumulative sun exposure explaining most. We identified a significant interaction between HLA-DR15 and history of IM in predicting an FCD of CNS demyelination, which together with previous observations suggests that this is a true interaction.</AbstractText>
<CopyrightInformation>© The Author(s), 2015.</CopyrightInformation>
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<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>van der Mei</LastName>
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<AffiliationInfo><Affiliation>Menzies Research Institute, Australia Ingrid.vanderMei@utas.edu.au.</Affiliation>
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