医学
肿瘤坏死因子α
巴斯代人
内科学
专家意见
外科
银屑病性关节炎
关节炎
重症监护医学
作者
Julien Paccou,Elisabeth Solau‐Gervais,Éric Houvenagel,Julia Salleron,H. Luraschi,Peggy Philippe,B Duquesnoy,R.M. Flipo
出处
期刊:Rheumatology
[Oxford University Press]
日期:2010-12-02
卷期号:50 (4): 714-720
被引量:47
标识
DOI:10.1093/rheumatology/keq377
摘要
Anti-TNF-α agents are remarkably effective in the treatment of SpAs. However, 30% of patients withdraw from anti-TNF-α agents yearly because of inadequate efficacy or side effects. The objective of this study was to assess in current practice the response to a second and a third anti-TNF-α.Retrospectively, all records of patients who had received at least two anti-TNF-α agents have been studied. For axial forms, treatment was considered effective if 3 months after switching the patient had a favourable expert opinion or showed an improvement in BASDAI of at least 2 on a scale of 0-10 or an improvement of 50% (BASDAI 50). For peripheral forms, the treatment was considered effective if the patient had a favourable expert opinion or if a clinical improvement of >30% of the swollen and tender joint counts was established. The reasons for switching were: (i) primary non-responder; (ii) loss of efficacy; and (iii) occurrence of side effects. To identify response predictor factors bivariate analysis was performed.Three hundred and seventy-seven patients under anti-TNF-α agents were treated and 99 patients had received at least two anti-TNF-α agents. Twenty-eight of these 99 patients had been treated with three anti-TNF-α agents. Following the failure of a first anti-TNF-α, the response to a second agent was satisfactory in 80.8%. Patients who had received a third anti-TNF-α following failure of the first two also showed a satisfactory response in 82.1%. The reason for switching from the first or second agent was not predictive of the response.In the event of failure or intolerance to anti-TNF-α in the treatment of SpAs, performing a first or second switch produces a satisfactory therapeutic response.
科研通智能强力驱动
Strongly Powered by AbleSci AI