Imaging Predictors of Treatment Response in Depression
Condition: Major Depressive Disorder
MeSH terms: Depression; Depressive Disorder; Depressive Disorder, Major
Study type: Interventional

Summary: 
      While there are many effective options for treating a major depressive episode, there are no
      clinical markers that predict the likelihood of remission with an initial trial of either an
      antidepressant medication or psychotherapy. More critically, there are also no reliable
      predictors that might anticipate failure to such standard treatments either alone or in
      combination. This project will characterize imaging-based brain subtypes that distinguish
      groups of depressed patients who later remit or not to SSRI pharmacotherapy or cognitive
      behavior therapy (CBT), respectively. To define these subtypes, a prospectively-treated
      cohort of 100 patients will be randomized to receive either escitalopram (s-CIT) or CBT for
      the first 12 weeks, with non-remitters to either first treatment crossed over to receive an
      additional 12 weeks of treatment with combined treatment. Non-remitters to both treatments
      will thus define a relatively treatment resistant third subgroup. Resting-state
      18F-fluoro-deoxyglucose (FDG) positron emission tomography (PET) scans will be acquired prior
      to initiating antidepressant therapy, with pre-treatment scan patterns associated with three
      possible outcomes (CBT remission, s-CIT remission, and non-remission to both) assessed using
      multivariate analytic methods. A second PET scan, acquired early in the treatment course,
      will be used to assess the likelihood of response to the specific treatment first assigned.
      The proposed studies are a first step towards defining brain-based biomarkers predictive of
      differential treatment outcome in major depression; most critically, patterns distinguishing
      patients at risk for treatment resistance. Identification of such biomarkers has additional
      implications for future testing of novel therapies in patients with distinct brain
      signatures, including development of evidence-based treatment algorithms for individual
      patients.
    

Detailed description: 
      SPECIFIC AIMS Aim 1. To define baseline regional glucose metabolic patterns (measured using
      FDG PET) associated with differential clinical remission to each of two well-established,
      randomly delivered first-line antidepressant treatments-the SSRI escitalopram (s-CIT) or
      cognitive behavioral therapy (CBT) with cross-over treatment for non-remitters (sequential
      course of treatment model).

      Aim 2. To define metabolic change patterns, occurring early in the course of both s-CIT and
      CBT, associated with successful and unsuccessful clinical remission to each intervention.
    

Intervention name(s): escitalopram; Cognitive Behavioral Therapy (CBT)
Intervention type(s): Drug; Behavioral
Intervention description(s): Participants will receive treatment with escitalopram for 12 weeks.; CBT will include 16 1 hour sessions provided over 12 weeks.
Other intervention name(s): Lexapro; Talk Therapy
Intervention MeSH terms: Escitalopram
Allocation: Randomized
Intervention model: Crossover Assignment
Masking: None (Open Label)
Primary purpose: Treatment
Keywords: Depression, Treatment, Imaging