Predictors of 4-Week Antidepressant Outcome in Patients with First-Episode Major Depressive Disorder: an ROC Curve Analysis.

BACKGROUND:Pretreatment characteristics of patients, symptom and function could be associated with antidepressant treatment outcome, but its predictive ability is not adequate. Our study aimed to identify predictors of acute antidepressant efficacy in patients with first-episode Major Depressive Disorder (MDD).METHODS:187 patients with first-episode MDD were included and assessed clinical symptoms, cognitive function and global functioning using the 17-item Hamilton Depression Inventory (HAMD-17), MATRICS Consensus Cognitive Battery (MCCB) and Global Assessment of Functioning (GAF). Participants received treatment with a SSRI (escitalopram or venlafaxine) for 4 weeks. Logistic regression was used to analyze the association between patients' characteristics, symptom profiles, cognitive performance, and global functioning and the antidepressant outcome at the end of 4 weeks, and ROC curve analysis was performed for predictive accuracy with area under the receiver operating curve (AUC).RESULTS:Antidepressant improvement, response and remission rate at week 4 was 87.7%, 64.7% and 42.8%, respectively. The combination of pretreatment clinical profiles, speed of processing and global functioning showed moderate discrimination of acute improvement, response and remission with AUCs of 0.863, 0.812 and 0.734, respectively.LIMITATIONS:The major limitation of the present study is the study did not combine pharmacogenomics from the perspective of antidepressant drug metabolism.CONCLUSION:Aside from the baseline clinical symptoms, cognitive function and global functioning could be predictors of acute treatment outcome in first episode MDD using escitalopram or venlafaxine. This relatively simple application based on clinical symptoms and function seems to be cost-effective method to identify individuals who are more likely to respond to antidepressant treatment.