Biomarkers for prediction of TNFα blockers response in rheumatoid arthritis

被引:35
作者
Marotte, Hubert [1 ]
Miossec, Pierre
机构
[1] Hop Edouard Herriot, Clin Immunol Unit, Dept Immunol, F-69437 Lyon 03, France
关键词
Predictive biomarker; TNF alpha blocker; Rheumatoid arthritis; TUMOR-NECROSIS-FACTOR; MESSENGER-RNA EXPRESSION; C-REACTIVE PROTEIN; GENE POLYMORPHISM; CLINICAL-RESPONSE; INFLIXIMAB THERAPY; PERIPHERAL-BLOOD; DIFFERENTIAL RESPONSE; MONOCLONAL-ANTIBODY; MARKERS;
D O I
10.1016/j.jbspin.2010.02.026
中图分类号
R5 [内科学];
学科分类号
100201 [内科学];
摘要
Tumor necrosis factor alpha (TNF alpha) is a pro-inflammatory cytokine that plays pivotal roles in regulating the inflammatory response in rheumatoid arthritis (RA). Intensive studies on TNF alpha-driven inflammation processes have led to the development of TNF alpha blockers for RA treatment. However, response to these therapies is heterogeneous with roughly two-thirds of patient response and one-third non-response. Given the destructive nature of RA, the risk of adverse effects, and considerable costs for TNF alpha blocker therapy, there is a strong need to identify predictors of response prior to start the TNF alpha blocker therapy. Here we review several studies focused on predicting the response to TNF alpha blockers. Demographic, clinical, radiological, blood, genetic or synovial tissue biomarkers were studied to find some predictive biomarkers of TNF alpha blocker response. Unfortunately, results from these studies are heterogeneous. Discrepancy between these studies can be explained in part to the heterogeneity between the studies. As difference in the response criteria used, the delay of efficacy for the primary endpoint, and the genetic background of each population were all observed. Nevertheless, a high local and systemic level of TNF alpha prior to TNF alpha blocker therapy seems to be associated with a good clinical response. However, to validate these results, additional studies using independent and large cohorts are needed. (C) 2010 Societe francaise de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:297 / 305
页数:9
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