ArticleArthritis research & therapy2024
Changes in type VI collagen degradation reflect clinical response to treatment in rheumatoid arthritis patients treated with tocilizumab.
Article in Arthritis research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
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Abstract
objectivesRheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation in multiple articular joints, causing pain, joint damage, and loss of joint function. Despite the successful development of disease-modifying therapies, the heterogeneity of RA means that a significant proportion of patients respond poorly to treatment. This highlights the need for personalized medicine and predictive biomarkers to optimize treatment efficacy, safety, and cost. This study aimed to explore the relationship between type VI collagen (Col VI) remodeling and clinical response to anti-IL-6 receptor treatment.
methodsType VI collagen degradation was quantified using the C6M biomarker, a fragment of type VI collagen degraded by MMPs. Longitudinal differences in average biomarker levels between placebo and treatment groups were estimated using linear mixed models. The predictive capacity of the marker based on change from baseline to 4 weeks was analyzed using logistic regression.
resultsBoth 4 mg and 8 mg doses of Tocilizumab (TCZ) reduced serum C6M concentrations compared to the placebo. Furthermore, C6M levels were more reduced in patients responding to treatment compared to early non-responders. A lower early reduction in C6M was associated with reduced odds of ACR treatment response and lowered disease activity.
conclusionThese findings suggest that quantifying type VI collagen turnover may aid in identifying patients less likely to respond to treatment, indicating a new path towards optimizing patient care. Further studies are needed to validate these findings and explore the underlying mechanisms driving the observed relationships.
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