Association of clinical characteristics, disease activity and health-related quality of life in SLE patients with major depressive disorder. (6th February 2021) - Parperis, Konstantinos; Psarelis, Savvas; Chatzittofis, Andreas; Michaelides, Michalis; Nikiforou, Dimitra; Antoniade, Elpida; Bhattarai, Bikash
Abstract: Objective: To determine the contributing factors associated with major depressive disorder (MDD) in SLE patients and examine the association between disease-specific health-related quality of life [lupus quality of life (LupusQoL)] domains and MDD. Methods: Depression was assessed by the patient health questionnaire (PHQ)-9, and scores ≥10 indicate MDD. Demographic data, LupusQoL domains, clinical and other features of the SLE patients were described and compared between MDD (PHQ-9 ≥10) and non-MDD (PHQ-9 <10) groups using χ 2 tests for categorical variables and Wilcoxon rank sum tests for non-normal continuous variables. The risk of MDD was evaluated for the patient and physician-reported features individually using log-binomial models to estimate relative risks and 95% confidence limits. Results: Eighty-eight patients with SLE met eligibility criteria, with a mean (range) age of 48.6 (19–80), mostly female (80%) and with a mean disease duration of 13.2 years. Compared with the non-MDD group, patients with MDD ( n  = 32, 36%) were more likely to have the following SLE manifestations: mucocutaneous, vascular, ocular, pulmonary and musculoskeletal involvement. Self-rated health described as poor/fair was markedly associated with MDD ( P  < 0.001, relative risk = 0.48). Based on relative risks, higher pain visual analogue score, and patient and physician global assessment scores were also linked to MDD. The LupusQoL domain scores were notably lower in the MDD patients, with a statistically significant reduction in all LupusQoL domains. Conclusion: Predictors of MDD in SLE patients include higher scores in pain and global assessment, poor or fair self-reported health, and specific organ involvement. These findings may help clinicians to recognize and manage MDD promptly.