An easy-to-use tool that is capable of finding patients with psoriasis at high risk for developing psoriatic arthritis (PsA) may facilitate earlier diagnosis and intervention. This study aimed to develop and evaluate a risk prediction model for PsA development in a prospective cohort of patients with psoriasis who were free of PsA at baseline. Participants underwent annual rheumatologic assessments for new-onset PsA. Data on demographics, psoriasis characteristics, comorbidities, medicine usage, and symptoms were collected for the model’s development, and the model looked at stiffness, lesions on nail beds, psoriasis severity, fatigue, pain, and use of systemic non-biologic therapy or phototherapy as predictors. Calibration plots demonstrated acceptable alignment between predicted and observed PsA incidence.

These findings suggest that PsA risk over clinically relevant timeframes can be estimated with sensible accuracy using clinical variables in psoriasis populations, supporting the utility of risk-based screening strategies in dermatology and rheumatology settings.

Reference: Eder L, Lee K-A, Chandran V, et al. Derivation of a multivariable Psoriatic Arthritis Risk Estimation Tool (PRESTO): a step towards prevention. Ann Rheum Dis. 2023;82(4):507-514. doi:10.1136/ard-2022-223709