Sociodemographic variables as predictors of antidepressant treatment outcome in major depressive disorder

Braz J Psychiatry. 2026 Mar 9. doi: 10.47626/1516-4446-2025-4665. Online ahead of print.

ABSTRACT

OBJECTIVE: The aim of this study was to evaluate the influence of sociodemographic variables on remission to an initial trial with citalopram.

METHODS: A sample of 2,682 patients with major depressive disorder was selected from the first level STAR*D trial database. Several sociodemographic variables available at baseline, as well as clinical variables, were selected a priori (based on literature review) and used to construct models that could predict remission after initiation of citalopram in a 3-month follow-up period.

RESULTS: The logistic regression model was selected as the best performing model with the highest accuracy. The sociodemographic variables were as relevant as the clinical variables when predicting the probability of remission to antidepressant treatment. In particular, sociodemographic variables linked to low socioeconomic status were the most significant in decreasing the likelihood of remission. Being older than 25 years old, Black race, and Hispanic ethnicity also had a negative influence on the likelihood of remission to antidepressant.

CONCLUSION: Certain sociodemographic characteristics, particularly those linked to low socioeconomic status, would substantially reduce the likelihood of remission to a first-line treatment for major depressive disorder. The pattern of findings would have potential clinical and therapeutic implications that warrant future research on this topic.

PMID:41802031 | DOI:10.47626/1516-4446-2025-4665