Objectives To describe risk factors for inflammatory bowel disease (IBD) development in a cohort of children with juvenile idiopathic arthritis (JIA). Methods JIA patients who developed IBD were identified from the international Pharmachild register. Characteristics were compared between IBD and non-IBD patients and predictors of IBD were determined using multivariable logistic regression analysis. Incidence rates of IBD events on different disease-modifying anti-rheumatic drugs (DMARDs) were calculated, differences between therapies were expressed as relative risks (RR). Results Out of 8,942 patients, 48 (0.05%) developed IBD. These were more often male (47.9% vs 32.0%) and HLA-B27 positive (38.2% vs 21.0%) and older at JIA onset (median 8.94 vs 5.33 years) than patients without IBD development. They also had more often a family history of autoimmune disease (42.6% vs 24.4%) and enthesitis-related arthritis (ERA) (39.6% vs 10.8%). The strongest predictors of IBD on multivariable analysis were ERA (OR: 3.68, 95% CI: 1.41–9.40) and a family history of autoimmune disease (OR: 2.27, 95% CI: 1.12–4.54). Compared with methotrexate monotherapy, the incidence of IBD on etanercept monotherapy (RR: 7.69, 95% CI: 1.99–29.74), etanercept with methotrexate (RR: 5.70, 95% CI: 1.42–22.77) and infliximab (RR: 7.61, 95% CI: 1.27–45.57) therapy was significantly higher. Incidence on adalimumab was not significantly different (RR: 1.45, 95% CI: 0.15–13.89). Conclusion IBD in JIA was associated with ERA and a family history of autoimmune disease. An increased IBD incidence was observed for etanercept therapy regardless of concomitant methotrexate use.

Objective To build a prediction model for uveitis in children with JIA for use in current clinical practice. Methods Data from the international observational Pharmachild registry were used. Adjusted risk factors as well as predictors for JIA-associated uveitis (JIA-U) were determined using multivariable logistic regression models. The prediction model was selected based on the Akaike information criterion. Bootstrap resampling was used to adjust the final prediction model for optimism. Results JIA-U occurred in 1102 of 5529 JIA patients (19.9%). The majority of patients that developed JIA-U were female (74.1%), ANA positive (66.0%) and had oligoarthritis (59.9%). JIA-U was rarely seen in patients with systemic arthritis (0.5%) and RF positive polyarthritis (0.2%). Independent risk factors for JIA-U were ANA positivity [odds ratio (OR): 1.88 (95% CI: 1.54, 2.30)] and HLA-B27 positivity [OR: 1.48 (95% CI: 1.12, 1.95)] while older age at JIA onset was an independent protective factor [OR: 0.84 (9%% CI: 0.81, 0.87)]. On multivariable analysis, the combination of age at JIA onset [OR: 0.84 (95% CI: 0.82, 0.86)], JIA category and ANA positivity [OR: 2.02 (95% CI: 1.73, 2.36)] had the highest discriminative power among the prediction models considered (optimism-adjusted area under the receiver operating characteristic curve = 0.75). Conclusion We developed an easy to read model for individual patients with JIA to inform patients/parents on the probability of developing uveitis.

Objectives Burden of comorbidities are largely unknown in JIA. From 2000, national and international patient registries were established to monitor biologic treatment, disease activity and adverse events in patients with JIA. The aim of this analysis was to investigate in parallel, for the first time, three of the largest JIA registries in Europe/internationally—UK JIA Biologic Registers (BCRD/BSPAR-ETN), German biologic registers (BiKeR/JuMBO), multinational Pharmachild—to quantify the occurrence of selected comorbidities in patients with JIA. Methods Information on which data the registers collect were compared. Patient characteristics and levels of comorbidity were presented, focusing on four key conditions: uveitis, MAS, varicella, and history of tuberculosis. Incidence rates of these on methotrexate/biologic therapy were determined. Results 8066 patients were registered into the three JIA registers with similar history of the four comorbidities across the studies; however, varicella vaccination coverage was higher in Germany (56%) vs UK/Pharmachild (16%/13%). At final follow-up, prevalence of varicella infection was lower in Germany (15%) vs UK/Pharmachild (37%/50%). Prevalence of TB (0.1–1.8%) and uveitis (15–19%) was similar across all registers. The proportion of systemic-JIA patients who ever had MAS was lower in Germany (6%) vs UK (15%) and Pharmachild (17%). Conclusion This analysis is the first and largest to investigate the occurrence of four important comorbidities in three JIA registries in Europe and the role of anti-rheumatic drugs. Combined, these three registries represent one of the biggest collection of cases of JIA worldwide and offer a unique setting for future JIA outcome studies.

Background Little is known about the association between juvenile idiopathic arthritis (JIA) and autoimmune thyroid disease (AITD) and therefore there are no indications for AITD screening in this population, which is possible using standard blood tests. The objective of this study is to determine the prevalence and predictors of symptomatic AITD in JIA patients from the international Pharmachild registry. Methods Occurrence of AITD was determined from adverse event forms and comorbidity reports. Associated factors and independent predictors for AITD were determined using univariable and multivariable logistic regression analyses. Results The prevalence of AITD after a median observation period of 5.5 years was 1.1% (96/8965 patients). Patients who developed AITD were more often female (83.3% vs. 68.0%), RF positive (10.0% vs. 4.3%) and ANA positive (55.7% vs. 41.5%) than patients who did not. AITD patients were furthermore older at JIA onset (median 7.8 years vs. 5.3 years) and had more often polyarthritis (40.6% vs. 30.4%) and a family history of AITD (27.5% vs. 4.8%) compared to non-AITD patients. A family history of AITD (OR = 6.8, 95% CI: 4.1 – 11.1), female sex (OR = 2.2, 95% CI: 1.3 – 4.3), ANA positivity (OR = 2.0, 95% CI: 1.3 – 3.2) and older age at JIA onset (OR = 1.1, 95% CI: 1.1 – 1.2) were independent predictors of AITD on multivariable analysis. Based on our data, 16 female ANA positive JIA patients with a family history of AITD would have to be screened during ±5.5 years using standard blood tests to detect one case of AITD. Conclusions This is the first study to report independent predictor variables for symptomatic AITD in JIA. Female ANA positive JIA patients with positive family history are at increased risk of developing AITD and thus might benefit from yearly serological screening.