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  • Title: Early predictors of severe course of uveitis in oligoarticular juvenile idiopathic arthritis.
    Author: Zulian F, Martini G, Falcini F, Gerloni V, Zannin ME, Pinello L, Fantini F, Facchin P.
    Journal: J Rheumatol; 2002 Nov; 29(11):2446-53. PubMed ID: 12415607.
    Abstract:
    OBJECTIVE: To determine whether demographic, clinical, and laboratory variables at onset of arthritis can predict the development and the severity of anterior uveitis (AU) in oligoarticular juvenile idiopathic arthritis (JIA). METHODS: In a retrospective study, a cohort of 366 patients with oligoarticular onset JIA from 3 pediatric rheumatology centers were evaluated. Patients were classified in 3 groups: severe uveitis (SU) with a mean >/= 2 uveitis relapses/year with complications or need for immunosuppressive therapy; mild uveitis (MU) with a mean </= 1 uveitis relapse/year with no complications; and no uveitis. Variables that were significant with univariate tests or were clinically relevant for each outcome underwent multivariate logistic regression analysis. RESULTS: There were 316 patients available for analyses: 66 in the SU group, 64 in the MU group, and 186 in the no uveitis group. Multivariate analysis showed the following factors to be significant as predictors of AU onset: low age at onset (OR 0.96), a2-globulin plasma concentration (OR 1.34), and HLA-A19 (OR 2.87), B22 (OR 4.51) and DR9 (OR 2.33), while HLA-DR1 conferred protection (OR 0.13). This model was not good in predicting which patient would develop uveitis (sensitivity 55%, specificity 26%). Time interval between onset of arthritis and the first AU and elevated a2-globulin level in the serum were the best predictors of AU severity (OR 1.62 and 0.85, respectively). When applied prospectively, the model revealed good sensitivity (89.2%), specificity (76.1%), and efficiency (86.3%). CONCLUSION: Clinical and laboratory variables measurable at onset of arthritis can be used to predict severity of the course of AU in oligoarticular JIA, but not its onset. More accurate prediction can shorten or lengthen the intervals between ophthalmologic evaluations and can change the therapeutic approach undertaken on the basis of expected disease severity.
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