Variables associated with joint involvement and development of a prediction rule for arthritis in patients with psoriasis. An analysis of the Italian PsoReal database

Abstract

Background: Limited data exist to predict the development of psoriatic arthritis (PsA) in patients with psoriasis (PsO).

Objective: To analyze factors associated with incident PsA in patients with PsO, and to develop a predictive algorithm for progression to arthritis using a full set of variables and a restricted one applicable to administrative data.

Methods: Cohort study within the PsoReal registry in Italy. Multivariable generalized linear models were used to assess factors associated with PsA and to derive a predictive model.

Results: Among 8895 patients, 226 PsA cases were identified (incidence 1.9 per 100 patient-years). Independent predictors in the full model were as follows: female sex, age 40 to 59 years, body mass index ≥ 25, chronic-plaque PsO features, presence of palmoplantar pustulosis, hospitalization for PsO in the last 5 years, and previous use of systemic PsO therapy (area under the receiver operating characteristic curve = 0.74). Female sex, age 40 to 59 years, hospitalization for PsO, and previous use of systemic PsO therapy were independent predictors in the restricted model (area under the receiver operating characteristic curve = 0.72).

Limitations: Lack of other potential predictors for PsA.

Conclusion: Our models could be used by clinicians and health authorities when planning intervention and population surveillance. Future studies should confirm our models using larger datasets and additional variables.

Keywords: disease progression; prediction; predictive model; psoriasis; psoriatic arthritis; risk factors.