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M. E. Weinblatt and A. L. Maier, “Disease-Modifying Agents and Experimental Treatments of Rheumatoid Arthritis,” Clinical Orthopaedics and Related Research, Vol. 265, 1991, pp. 103-115.

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.