Impact of chronic urticaria on systemic lupus erythematosus: A nationwide population-based study in Taiwan.
Su Boon YongKuan-Wen SuHuang-Hsi ChenJing-Yang HuangHsing-Ju WuJames Cheng-Chung WeiPublished in: The Journal of dermatology (2018)
Chronic urticaria (CU) may be closely pathogenically related to systemic lupus erythematosus (SLE). This study aims to investigate the association between CU and SLE patients in Taiwan. A nationwide population-based cohort study from 1997 to 2013 was conducted. Investigated subjects were selected from the Taiwan National Health Insurance Research Database using the International Classification of Disease, Ninth Revision code. Participants consisted of 13 845 subjects newly diagnosed with CU from 2003 to 2013. We estimated the incidence risk of SLE among patients with CU by time-to-event analysis. Patients with CU were more likely to be female, and had a significant difference in urbanization and length of hospital stays (P < 0.0001). The incidence rates of SLE for the CU and control groups were 3.55 and 1.68, respectively. The crude hazard ratio of SLE among subjects with CU was 2.113 compared with the non-urticarial control group. After adjusting the demographic, length of hospital stay and comorbidity, the adjusted hazard ratio (aHR) of SLE was still significantly higher in the CU group (aHR = 2.113) compared with the control group. The use of non-steroidal anti-inflammatory drugs or corticosteroids may decrease the risk of SLE in patients with CU (P = 0.0216 and 0.0120, respectively). In conclusion, CU is associated with a higher risk of incidental SLE in this population-based, nationwide, cohort study. Inflammation and immune dysregulation are considered two potential mechanisms. Clinically, patients with urticaria should be carefully evaluated for risk of future SLE.
Keyphrases
- systemic lupus erythematosus
- disease activity
- newly diagnosed
- aqueous solution
- health insurance
- metal organic framework
- rheumatoid arthritis
- healthcare
- anti inflammatory drugs
- end stage renal disease
- machine learning
- chronic kidney disease
- ejection fraction
- high resolution
- cross sectional
- peritoneal dialysis
- acute care
- climate change
- prognostic factors