K. Au, G. Reed, J. R. Curtis, J. M. Kremer, J. D. Greenberg, V. Strand, et al., “Extended Report: High Disease Activity Is Associated with an Increased Risk of Infection in Patients with Rheumatoid Arthritis,” Annals of the Rheumatic Diseases, Vol. 70, No. 5, 2011, pp. 785-791. doi:10.1136/ard.2010.128637
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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.
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Madeleine Singwe-Ngandeu, Mickael Essouma, Alain Patrick Menanga, Vicky Jocelyne Ama Moor, Caroline Ngoufack, Sandrine Sa’a Lontsi, Yolande Vanessa Ayi Efoua, Thierry Ntandzi
DOI:
10.4236/ojra.2016.61003
3,160 Downloads 3,930 Views Citations
Pub. Date:
February
19,
2016
