Patients with psoriatic arthritis and comorbid metabolic syndrome show a difficult-to-treat phenotype: another mosaic tile in the definition of a still undefined subset of patients.

Abstract

Objective: Psoriatic arthritis (PsA) is a chronic inflammatory condition associated with psoriasis and characterised by heterogeneous clinical manifestations, including peripheral and axial arthritis, enthesitis and dactylitis. A subset of patients exhibits a 'difficult-to-treat' (D2T) phenotype, necessitating complex therapeutic strategies. Metabolic syndrome (MetS) is highly prevalent in PsA patients and has been implicated in increased disease activity.This study aimed to evaluate the impact of MetS on the development of D2T phenotype in PsA and its potential implications for disease management.

Methods: A cross-sectional study was conducted on PsA patients recruited from the Rheumatology Clinic at Fondazione Policlinico Campus Bio-Medico of Rome. Patients fulfilling the Classification Criteria for Psoriatic Arthritis criteria were assessed for disease activity and the presence of MetS according to National Cholesterol Education Programme Adult Treatment Panel III criteria. D2T PsA was defined based on the Rheumatoid Arthritis European Alliance of Associations for Rheumatolog criteria revised for PsA by Perrotta et al. Statistical analyses, including logistic regression and path analysis, were performed to explore associations between MetS and D2T PsA.

Results: Among 182 PsA patients, 42.94% met MetS criteria. The D2T subset (n=66) demonstrated a significantly higher prevalence of MetS (81.82% vs 29.37%, p<0.0001). Logistic regression revealed a strong association between MetS and D2T PsA (OR 7.56, 95% CI 2.53 to 22.56, p<0.0001), and path analysis confirmed MetS as an independent predictor of D2T phenotype.

Conclusions: MetS is strongly associated with a D2T phenotype in PsA, suggesting that metabolic comorbidities contribute to disease severity and treatment resistance. Addressing metabolic dysfunction may be crucial in optimising therapeutic outcomes in PsA management.