Optimizing withdrawal strategies for anti-TNF-α therapies in rheumatoid arthritis
Rheumatoid arthritis (RA) is a chronic autoimmune disease that significantly impacts patients' quality of life. While treatment options have expanded over the years, including the introduction of tumor necrosis factor-alpha (TNFα) inhibitors (TNFi), optimizing withdrawal strategies for these ag...
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Published in | Expert opinion on biological therapy Vol. 24; no. 8; p. 815 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
02.08.2024
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Subjects | |
Online Access | Get more information |
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Summary: | Rheumatoid arthritis (RA) is a chronic autoimmune disease that significantly impacts patients' quality of life. While treatment options have expanded over the years, including the introduction of tumor necrosis factor-alpha (TNFα) inhibitors (TNFi), optimizing withdrawal strategies for these agents remains a challenge.
This review examines the current evidence on TNFi withdrawal strategies in RA, focusing on factors influencing withdrawal decisions such as disease activity monitoring, treatment response, patient characteristics, and biomarkers. A comprehensive literature search was conducted, including randomized controlled trials, observational studies, and expert guidelines. The pathophysiology of RA, current pharmacological agents, and the treat-to-target strategy are discussed to provide a holistic understanding of RA management.
Withdrawal strategies could be suitable for certain patients, keeping in mind that several factors influence withdrawal decisions, including treatment response, disease activity and monitoring, and patient characteristics. The decision to withdraw TNFi must balance the benefits against the potential risks of disease flare and long-term treatment-related adverse effects. Combining DMARDs and TNFi early improves outcomes, supporting tapering strategies for cost-effectiveness and flare prevention. Future directions, including precision medicine approaches, patient-centered care models, and health economics analyses, are proposed to further optimize RA management and improve patient outcomes. |
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ISSN: | 1744-7682 |
DOI: | 10.1080/14712598.2024.2384000 |