Does negative affectivity predict differential response to an SSRI versus a non-SSRI antidepressant?

Area of Science:

• Psychiatry and Clinical Neuroscience
• Pharmacology
• Neuroscience

Background:

• Major depressive disorder (MDD) is a complex condition with varying symptom presentations.
• Negative affectivity (NA), characterized by negative emotions, is a significant aspect of depressive disorders.
• Understanding the differential response to antidepressants based on patient characteristics like NA is crucial for personalized treatment.

Purpose of the Study:

• To test the hypothesis that patients with high negative affectivity (NA) would respond better to the serotonergic agent escitalopram than to bupropion, which is not thought to directly affect serotonin.
• To investigate the differential efficacy of escitalopram versus bupropion in patients with major depressive disorder (MDD) based on their levels of negative affectivity.

Main Methods:

• Retrospective analysis of data from a randomized, double-blind study of 245 patients with MDD.
• Patients were treated with bupropion extended-release, escitalopram, or a combination.
• Negative affectivity (NA) was estimated using specific items from validated depression rating scales. Treatment response was defined by a Clinical Global Impressions-Severity of Illness (CGI-S) score ≤ 2.

Main Results:

• A significant interaction between treatment and NA was observed (P < .03).
• In patients with high NA, escitalopram showed a significantly higher response rate (60%) compared to bupropion (34%; P = .017).
• In patients with low NA, response rates were similar between escitalopram (67%) and bupropion (58%).

Conclusions:

• These findings suggest that patients with high negative affectivity may preferentially benefit from antidepressants that selectively enhance serotonin neurotransmission, such as escitalopram.
• Patients with low NA appear to benefit from serotonin enhancement but also improved with bupropion.
• Further independent replication using accepted NA measurement tools is recommended before making clinical inferences.