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Träfflista för sökning "WFRF:(Huizinga TWJ) srt2:(2015-2019)"

Sökning: WFRF:(Huizinga TWJ) > (2015-2019)

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  • Baecklund, Eva, 1956-, et al. (författare)
  • Anti-cyclic citrullinated peptide antibodies, other common autoantibodies, and smoking as risk factors for lymphoma in patients with rheumatoid arthritis
  • 2018
  • Ingår i: Scandinavian Journal of Rheumatology. - : Informa UK Limited. - 0300-9742 .- 1502-7732. ; 47:4, s. 270-275
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVES: Patients with rheumatoid arthritis (RA) are at increased risk of lymphoma. There is no biomarker to indicate future lymphoma risk in RA and it is not known whether factors associated with an increased risk of RA also confer an increased risk of lymphoma. We investigated whether anti-cyclic citrullinated peptide (CCP) antibodies, other autoantibodies, and smoking, are associated with lymphoma development in RA.METHOD: subclasses of anti-CCP antibodies and for 15 antinuclear antibody (ANA)-associated specific autoantibodies. Relative risks were estimated as crude and adjusted odds ratios (adjOR) with 95% confidence intervals (CIs) using logistic regression.RESULTS: We found no association between anti-CCP IgG ≥ 25 units/mL (adjOR 1.4, 95% CI 0.7-2.7), anti-CCP IgG ≥ 500 units/mL (adjOR 1.4, 95% CI 0.7-3.0), anti-CCP Ig of other isotypes, other autoantibodies (adjOR any vs none 0.6, 95% CI 0.3-1.2), or cigarette smoking (adjOR ever vs never 1.1, 95% CI 0.5-2.2) and lymphoma risk among patients with RA.CONCLUSION: In this study, neither anti-CCP antibodies (IgG, IgG1–4, IgM, or IgA), nor other common autoantibodies, nor smoking predicted lymphoma risk in RA
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  • Sieberts, SK, et al. (författare)
  • Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis
  • 2016
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7, s. 12460-
  • Tidskriftsartikel (refereegranskat)abstract
    • Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
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