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Risk of tuberculosis disease in patients receiving TNF-α antagonist therapy: A meta-analysis of randomized controlled
Fatemeh Khelghati1, Mohammad Rahmanian1, Elaheh Eghbal2
1Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Introduction:
Tuberculosis (TB) risk associated with tumor necrosis factor-alpha (TNF-α) antagonist therapy in patients with autoimmune diseases is a significant concern. This study aims to evaluate the risk of TB disease associated with TNF-α antagonist therapy.
Methods:
An extensive search of PubMed/MEDLINE, EMBASE, and the Cochrane CENTRAL databases was conducted to identify randomized controlled trials (RCTs) assessing TB disease risk in patients receiving TNF-α antagonist therapy available until November 1, 2024. The pooled statistic used was the weighted odds ratio (OR) and a corresponding 95 % confidence interval (CI). Statistical analysis was performed using Comprehensive Meta-Analysis software, version 3.0 (Biostat Inc., Englewood, NJ, USA).
Results:
Fifty-six RCTs, totaling 22,212 adult patients, met the specified eligibility criteria. Pooled analysis revealed an increased risk of TB disease associated with TNF-α antagonist therapy (OR 1.52, 95 % CI 1.03-2.26, p = 0.03). Subgroup analyses indicated a higher risk in patients with rheumatoid arthritis (RA) (OR 2.25, 95 % CI 1.13-4.45, p = 0.02), while no significant associations were found in patients with ankylosing spondylitis (AS) or psoriasis (Ps). Analyses by specific TNF-α antagonist drugs did not yield significant associations with risk of TB disease.
Conclusion:
Our study highlights an increased risk of TB disease associated with TNF-α antagonist therapy, particularly in patients with RA. However, the absence of significant associations in AS or Ps patients suggests disease-specific variations in risk of TB disease. Further research is needed to elucidate the long-term safety profile of TNF-α antagonist drugs and their associations with risk of TB disease in different patient populations.
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