Outcome following onset of juvenile idiopathic inflammatory arthritis: II. Predictors of outcome in juvenile arthritis

被引:34
作者
Adib, N [1 ]
Silman, A [1 ]
Thomson, W [1 ]
机构
[1] Univ Manchester, Sch Med, Sch Epidemiol & Hlth Sci, Arthrit Res Campaign Epidemiol Unit, Manchester M13 9PT, Lancs, England
关键词
juvenile arthritis; outcome; predictors; remission; function; bone erosion;
D O I
10.1093/rheumatology/keh621
中图分类号
R5 [内科学];
学科分类号
1002 [临床医学]; 100201 [内科学];
摘要
Objective. To assess the relative contributions of demographic, clinical and laboratory variables in predicting outcome in juvenile idiopathic inflammatory arthritis (JIA), based on a review of the existing literature. Methods. Electronic reference database searches for the previous 10 yr were conducted and studies examining the role of major potential predictors of main outcomes were identified. Where possible, subjects were grouped by JIA disease subtype. In addition to demographic variables, the following disease-related predictors were assessed: nature of joint involvement, acute-phase response, and presence of autoantibodies. These were then analysed for three main outcomes of interest: remission as assessed by disease activity; functional impairment; and structural damage as assessed by radiological joint erosions. Results. In general, female gender, polyarticular and symmetrical joint involvement, elevated inflammatory markers and rheumatoid factor positivity were the most consistent predictors of a poor outcome, although the studies were frequently inconsistent in both the direction and the magnitude of the effects. Conclusions. These data are too variable to accurately identify those predictors associated with poor outcome following the onset of JIA. Although some of this variation may be the result of true differences between study populations, the vast majority of inconsistencies are explainable by the absence of standardized classification systems, outcome definitions, therapeutic approach and research tools. More comprehensive prospective evaluation is required before robust prediction models can be generated.
引用
收藏
页码:1002 / 1007
页数:6
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