Prospective Cohort Study of Psoriatic Arthritis Risk in Patients With Psoriasis in a Real-World Psoriasis Registry.

Document Type


Publication Date


Publication Title

Journal of the American Academy of Dermatology


washington; swedish


Background: Characteristics that predict psoriatic arthritis (PsA) onset among patients with psoriasis (PsO) may inform diagnosis and treatment.

Objective: To develop a model to predict 2-year risk of developing PsA among patients with PsO.

Methods: This was a prospective cohort study of patients in the CorEvitas Psoriasis Registry without PsA at enrollment and with 24-month follow-up. Unregularized and regularized logistic regression models were developed and tested using descriptive variables to predict dermatologist-identified PsA at 24 months. Model performance was compared using area under the receiver-operating-characteristic curve (AUC), sensitivity, and specificity.

Results: A total of 1489 patients were included. Nine unique predictive models were developed and tested. The optimal model, including Psoriasis Epidemiology Screening Tool (PEST), body mass index (BMI), modified Rheumatic Disease Comorbidity Index, work status, alcohol use, and patient-reported fatigue predicted onset of PsA within 24 months (AUC = 68.9%, sensitivity = 82.9%, specificity = 48.8%). A parsimonious model including PEST and BMI had similar performance (AUC = 68.8%; sensitivity = 92.7%, specificity = 36.5%).

Limitations: PsA misclassification bias by dermatologists.

Conclusion: PEST and BMI were important factors in predicting development of PsA in patients with PsO over 2 years, and thereby foundational for future PsA risk model development.

Keywords: body mass index; cohort studies; comorbidity; dermatology; epidemiologic studies; probabilistic models; prospective studies; psoriasis; psoriatic arthritis; registries; rheumatic diseases; risk assessment; screening; statistical model.

Clinical Institute

Orthopedics & Sports Medicine