Predictors of arthritis in pediatric patients with lupus.

BACKGROUND: Arthritis is one of the most common manifestations of systemic lupus erythematosus (SLE). Although typically non-erosive and non-deforming, children with SLE arthritis can have significant morbidity with decreased quality of life. Our goal was to identify potential clinical and laboratory predictors of arthritis in a cohort of pediatric patients with SLE. METHODS: We performed a cohort study of incident and prevalent patients with SLE aged ≤ 19 years. In cross sectional analysis, we compared demographic and clinical characteristics at initial clinic presentation between patients with arthritis noted at any time during follow-up and those without arthritis. We performed time to event analysis using Cox proportional hazard ratios to identify predictors of arthritis, clustering for repeated measures. RESULTS: Forty seven children and adolescents with SLE were followed in the cohort, 91 % female and 68 % Black. In cross-sectional analyses, presence of malar rash was associated with arthritis. In longitudinal analyses, controlling for gender and race, increased age (HR: 1.4, 95 % CI: 1.1-1.7), malar rash (HR: 2.1, 95 % CI: 1.1-3.6), and presence of RNP antibodies (HR: 1.9, 95 % CI: 1.1-3.4) were predictive of arthritis. When controlling for gender, race, and medication use, anemia (HR: 8.5, 95 % CI: 2.9-24.2) and thrombocytopenia (HR: 6.1, 95 % CI: 2.4-15.6) were associated with increased risk of arthritis. CONCLUSIONS: We identified markers predictive of arthritis in a longitudinal cohort of children with SLE. The recognition of these markers may help clinicians identify patients at risk for arthritis before its onset thus improving quality of life in children with SLE.

Predictors of kidney disease in a cohort of pediatric patients with lupus.

INTRODUCTION: Children with systemic lupus erythematosus (SLE) have an increased prevalence of kidney disease compared to their adult counterparts. Our goal was to identify potential clinical and laboratory predictors of renal disease. METHODS: We performed a cohort study of incident and prevalent patients with SLE aged ≤19 years. Retrospective data from initial presentation until study enrollment was also collected. Laboratory and clinic data were recorded from each clinic visit including disease activity indices, autoantibodies, urinalyses, blood counts, and metabolic profile. Kidney disease was defined as the presence of abnormal renal biopsy or by American College of Rheumatology case definition for lupus nephritis. Logistic regression analyses were used to determine the association between clinical and laboratory data with kidney disease in those who had renal involvement within 30 days of SLE diagnosis. We also performed a time to event analysis to identify antecedents of renal disease. RESULTS: Forty-seven children and adolescents with SLE were followed in the cohort, 91% female and 68% black. All of the males in the cohort developed renal disease, and all within one month of the diagnosis of SLE. In logistic regression, low serum albumin (odds ratio (OR): 4.8, 95% CI: 1.9-12.5) and positive dsDNA antibodies (OR: 3.2, 95% CI: 1.7-5.9) were associated with kidney disease. In longitudinal analyses, isolated sterile pyuria (hazard ratio (HR): 3, 95% CI: 1.1-6.4) and low serum albumin (HR: 3.4, 95% CI: 1.7-6.9) were predictors of future kidney disease. The presence of antibodies against Ro were protective against renal disease (HR: 0.2, 95% CI: 0.05-0.5). CONCLUSION: We identified variables associated with kidney disease, both at initial diagnosis of SLE and in longitudinal follow-up in a cohort of children with SLE. The recognition of these abnormal laboratory values may help clinicians identify patients at risk for kidney disease before its onset thus preventing long-term complications.