SMART Trial to Predict Anhedonia Response to Antidepressant Treatment

Status Recruiting

Clinical Trial Summary

The main goal of this research is to use behavioral, brain, and clinical data to determine which type of antidepressant might be optimal before people with depression start treatment.

Clinical Trial Description

The treatment of depression is often trial-and-error. Earlier research reported that only 50% of individuals with depression show a significant decline in symptoms after taking an antidepressant. The situation is even worse in primary care, where only 30% respond to first line antidepressants. The difficulty in treating depression is likely because treatment selection is not based on each person's characteristics. While some depressed individuals may benefit from selective serotonin reuptake inhibitors (SSRIs), others might benefit more from other types of medication. Finding markers that predict an individual's response to different antidepressants would provide patients and clinicians with valuable information to guide treatment selection. The present study is among the first to use clinical (e.g., responses on questionnaires), behavioral (e.g., performance in computerized tasks), and brain (e.g., MRI scans) data to guide treatment selection in order to increase the likelihood of benefiting from one of two antidepressants. After analyzing an individuals' markers, subjects will be randomly assigned to receive a full 8-week course of an SSRI or non-SSRI. Throughout the study, participants will complete 9 total sessions over the course of 9-10 weeks, including an electroencephalogram (EEG) recording, a functional magnetic resonance imaging (fMRI) scan, an electrocardiogram (EKG) exam, interviews with clinicians, and a full 8-week course of an antidepressant. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT05537584
Study type	Interventional
Source	Mclean Hospital
Contact	Sarah Woronko, BA
Phone	617-855-4431
Email	sworonko@mclean.harvard.edu
Status	Recruiting
Phase	Phase 4
Start date	September 30, 2022
Completion date	November 1, 2024

View Details

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