Background: Systemic sclerosis (SSc) can clinically present with psychological symptoms, including pain, depression, and distress about disfigurement, physical and social functioning. The existing small studies have reported a prevalence of depression ranging from 36% to 65% among SSc patients, likely reflecting the disease impact on the patient's self-image and function.
Aim of the study: To investigate the association between SSc and depression using big data analysis methods.
Methods: We designed a nation-wide epidemiological survey relying on a large database of 2500 SSc patients and explored the relationship between SSc and depression, but also the impact of depression on the survival of SSc patients. Chi-squared and t-tests were used for univariate analysis and a logistic regression model was used for multivariate analysis.
Results: The proportion rate of depression among SSc patients was significantly higher than controls (16.2% vs 10.9%), and this proportion was even higher in female SSc patients and of low socioeconomic status. At the multivariate logistic regression, SSc was found to be an independent risk factor for depression with an OR of 1.55 (95%CI 1.29-1.88, p < 0.0001). No significant association was found between SSc-specific autoantibodies (anti-centromere, anti-Scl-70, anti-RNA polymerase III and anti-RNP) status and the risk of depression. Depression was not found to have a significant impact on the survival of SSc patients with an HR of 1.06 (0.80-1.42).
Conclusions: This study provides further support for the high prevalence of depression in SSc patients and therefore, SSc patients may benefit from a screening approach and a broad supportive care program.
Keywords: Biological markers; Depression; Epidemiology; Ethnicity/race; Mood disorders.
Copyright © 2018 Elsevier B.V. All rights reserved.