Objectives: To investigate real-world trajectories toward minimal disease activity (MDA) in psoriatic arthritis (PsA) patients starting their first biologic or targeted synthetic DMARD (bDMARD/tsDMARD) and identify baseline predictors of each trajectory. Methods: This is a retrospective observational study of 289 patients with PsA (CASPAR criteria) from two Italian tertiary centers (2020-2023), all not in MDA at baseline and with ≥24 months follow-up. MDA status was assessed every 6 months. Patients were categorized into four trajectories based on MDA achievement and maintenance: Super Responders, Delayed Responders, Fluctuating Responders, and Non-Responders. Clinical features and treatment patterns were compared, and multivariable logistic regression identified predictors of trajectory membership. Results: Mean age was 52.4 ± 12.3 years, disease duration 7.3 ± 5.1 years, and baseline DAPSA 23.4 ± 11.6. Most patients started TNF-α inhibitors (70.9%), and 60.9% achieved MDA at 24 months. Trajectory distribution was: Super Responders (23.2%), Delayed Responders (21.8%), Fluctuating Responders (37.0%), and Non-Responders (18.0%). Super Responders were predominantly male, with lower baseline disease activity and fewer metabolic comorbidities. Non-Responders were more often female, overweight/obese, and had higher fibromyalgia rates. Predictors of Super Responder status included male sex (OR 2.26) and absence of metabolic comorbidities (OR 2.29); higher baseline DAPSA decreased odds (OR 0.92). Predictors of Non-Responder status were female sex (OR 2.56), fibromyalgia (OR 5.30), and overweight/obesity (OR 2.04). No significant predictors of the other trajectory groups were found. Conclusions: Patients with PsA initiating bDMARD/tsDMARDs exhibit diverse disease trajectories. Identified predictors may inform trajectory-based risk stratification and optimize treat-to-target approaches.
Fatica, M., Perrotta, F.m., Conigliaro, P., Chimenti, M.s., Lubrano, E. (2026). Predicting the course: Real-world trajectories toward minimal disease activity in psoriatic arthritis. AUTOIMMUNITY REVIEWS, 25(5), 1-8 [10.1016/j.autrev.2026.104055].
Predicting the course: Real-world trajectories toward minimal disease activity in psoriatic arthritis
Fatica, Mauro;Conigliaro, Paola;Chimenti, Maria Sole;
2026-04-05
Abstract
Objectives: To investigate real-world trajectories toward minimal disease activity (MDA) in psoriatic arthritis (PsA) patients starting their first biologic or targeted synthetic DMARD (bDMARD/tsDMARD) and identify baseline predictors of each trajectory. Methods: This is a retrospective observational study of 289 patients with PsA (CASPAR criteria) from two Italian tertiary centers (2020-2023), all not in MDA at baseline and with ≥24 months follow-up. MDA status was assessed every 6 months. Patients were categorized into four trajectories based on MDA achievement and maintenance: Super Responders, Delayed Responders, Fluctuating Responders, and Non-Responders. Clinical features and treatment patterns were compared, and multivariable logistic regression identified predictors of trajectory membership. Results: Mean age was 52.4 ± 12.3 years, disease duration 7.3 ± 5.1 years, and baseline DAPSA 23.4 ± 11.6. Most patients started TNF-α inhibitors (70.9%), and 60.9% achieved MDA at 24 months. Trajectory distribution was: Super Responders (23.2%), Delayed Responders (21.8%), Fluctuating Responders (37.0%), and Non-Responders (18.0%). Super Responders were predominantly male, with lower baseline disease activity and fewer metabolic comorbidities. Non-Responders were more often female, overweight/obese, and had higher fibromyalgia rates. Predictors of Super Responder status included male sex (OR 2.26) and absence of metabolic comorbidities (OR 2.29); higher baseline DAPSA decreased odds (OR 0.92). Predictors of Non-Responder status were female sex (OR 2.56), fibromyalgia (OR 5.30), and overweight/obesity (OR 2.04). No significant predictors of the other trajectory groups were found. Conclusions: Patients with PsA initiating bDMARD/tsDMARDs exhibit diverse disease trajectories. Identified predictors may inform trajectory-based risk stratification and optimize treat-to-target approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


