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M. J. Van Der Veen, A. Van Der Heide, A. A. Kruize and J. W. Bijlsma, “Infection Rate and Use of Antibiotics in Patients with Rheumatoid Arthritis Treated with Methotrexate,” Annals of the Rheumatic Diseases, Vol. 53, No. 4, 1994, pp. 224-228. doi:10.1136/ard.53.4.224

has been cited by the following article:

  • TITLE: TNF-α Antagonist and Infection in Rheumatoid Arthritis

    AUTHORS: Julia F. Simard, Murray A. Mittleman, Nancy A. Shadick, Elizabeth W. Karlson

    KEYWORDS: Inverse Probability Weighting; Anti-TNF; Infection; Rheumatoid Arthritis

    JOURNAL NAME: Open Journal of Rheumatology and Autoimmune Diseases, Vol.2 No.2, May 7, 2012

    ABSTRACT: Background: Anti-TNF treatment may increase infection risk, although this has been difficult to study because the timing of anti-TNF treatment is driven by disease activity, which may influence infection susceptibility leading to confounding that varies over time. We evaluated the association between anti-TNF initiation in rheumatoid arthritis (RA) patients on disease modifying anti-rheumatic drugs (DMARD) and infection using multiple approaches adjusting for time-varying confounding. Methods: 383 anti-TNF-na?ve RA patients on ≥ 1 non-biologic-DMARD at enrollment from the Brigham and Women’s Rheumatoid Arthritis Sequential Study (BRASS) were followed up to two years. Pooled logistic regressions estimated the association between anti-TNF and infection by including time-varying covariates in the adjusted models and inverse probability treatment weighting (IPTW). Results: Adjustment for time-varying disease activity and other suspected confounders yielded non-statistically significant positive associations between anti-TNF start and infection regardless of analytic approach (RRmvar_adj = 2.1, 95% CI: 0.8 - 5.8). Conclusions: Incorporating changing clinical status, and treatment indications and consequences, yielded consistently (though not significantly) elevated relative risks of infection associated with anti-TNF initiation. Due to limited statistical power, we cannot draw firm conclusions. However, we have illustrated multiple approaches adjusting for potential time-varying confounding in longitudinal studies and hope to replicate the approaches in larger studies.