Increasing epidemiological evidence suggests independent associations between psoriasis and cardiovascular and metabolic disease. Our objective was to test the hypothesis that directly-assessed psoriasis severity relates to the prevalence of metabolic syndrome and its components. Population-based, cross-sectional study using computerized medical records from The Health Improvement Network Study population included individuals aged 45-65 years with psoriasis and practice-matched controls. Psoriasis diagnosis and extent were determined using provider-based questionnaires. Metabolic syndrome was defined using National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III criteria. 44,715 individuals were included: 4,065 with psoriasis and 40,650 controls. 2,044 participants had mild psoriasis (≤2% body surface area (BSA)), 1,377 had moderate (3-10% BSA), and 475 had severe psoriasis (>10% BSA). Psoriasis was associated with metabolic syndrome, adjusted odds ratio (OR) 1.41 (95% CI 1.31-1.51), varying in a “dose-response” manner, from mild (adj. OR 1.22, 95% CI 1.11-1.35) to severe psoriasis (adj. OR 1.98, 95% CI 1.62-2.43). Psoriasis is associated with metabolic syndrome and the association increases with increasing disease severity. Furthermore, associations with obesity, hypertriglyceridemia and hyperglycemia increase with increasing disease severity independent of other metabolic syndrome components. These findings suggest that screening for metabolic disease should be considered for psoriasis, especially when extensive.

Background Psoriasis is a common disease frequently studied in large databases. To date the validity of psoriasis information has not been established in The Health Improvement Network (THIN). Objectives To investigate the validity of THIN for identifying psoriasis patients and to determine if the database can be used to determine the natural history of disease. Patients/Methods First we conducted a cross sectional study to determine if psoriasis prevalence in THIN is similar to expected. Second we created a cohort of 4900 patients, aged 45–65, with a psoriasis diagnostic Read Code and surveyed their GPs to confirm the diagnosis clinically. Third we created models to determine if psoriasis descriptors (extent, severity, duration, and dermatologist confirmation) could be accurately captured from database records. Results Psoriasis prevalence was 1.9%, and showed the characteristic age distribution expected. GP questionnaires were received for 4,634 of 4,900 cohort patients (95% response rate), and psoriasis diagnoses were confirmed in 90% of patients. Duration of disease in the database showed substantial agreement with physician query (kappa = 0.69). GPs confirmed that the psoriasis diagnosis was corroborated by a dermatologist in 91% of patients whose database records contained a dermatology referral code associated with a psoriasis code. We achieved good discrimination between patients with and without extensive disease based on the number of psoriasis codes received per year (Area Under Curve, AUC = 0.8). Conclusions THIN is a valid data resource for studying psoriasis and can be used to identify characteristics of the disease such as duration and confirmation by a dermatologist.

The prevalence of PsA in THIN is consistent with previous population-based estimates. Limitations include a definition of PsA based on a diagnostic code rather than Classification Criteria for Psoriatic Arthritis (CASPAR) criteria. Given the large population of PsA patients, THIN is an important resource for the study of PsA.

No abstract

No abstract