Faculty Bibliography

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. A population-based, cross-sectional study was undertaken using computerized medical records from the Health Improvement Network Study population including individuals in the age group of 45-65 years with psoriasis and practice-matched controls. The diagnosis and extent of psoriasis were determined using provider-based questionnaires. Metabolic syndrome was defined using the National Cholesterol Education Program Adult Treatment Panel III criteria. A total of 44,715 individuals were included: 4,065 with psoriasis and 40,650 controls. In all, 2,044 participants had mild psoriasis (10% BSA). Psoriasis was associated with metabolic syndrome, adjusted odds ratio (adj. OR 1.41, 95% confidence interval (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 independently of other metabolic syndrome components. These findings suggest that screening for metabolic disease should be considered for psoriasis, especially when it is severe.

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 patients with psoriasis and to determine if the database can be used to determine the natural history of the disease. 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 45-64 years, with a psoriasis diagnostic Read Code and surveyed their general practitioners (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 4634 of 4900 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 = 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.

Efalizumab was approved for moderate to severe psoriasis in 2003 based on studies in approximately 2700 patients, of whom only 218 were exposed to the drug for more than 1 year. In 2009, after more than 46,000 patients were exposed to efalizumab, the drug was withdrawn from the market after 3 confirmed and 1 suspected case of progressive multifocal leukoencephalopathy (PML) were spontaneously reported. As PML is very rare, it is extremely unlikely that the 4 reported cases were due to chance and given that PML occurs primarily in patients who are immunosuppressed, the association is likely causal. The identification of PML as a serious, but statistically rare risk of efalizumab demonstrates the strengths and weaknesses of the current drug approval and pharmacovigilance processes for fully measuring the safety of a drug. Patients and clinicians need to be aware of the relative completeness and limitations of existing safety data of a drug when selecting a treatment.