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Research Funding:

Funding for the study derives from two grants from the National Institute of Mental Health. A Centers for Intervention Development and Applied Research (CIDAR) grant (P50 MH077083; PI: Helen Mayberg, MD) established the center and provided funds to assess participants for predictors of acute response. A subsequent grant (RO1 MH080880; PI: W Edward Craighead, PhD) provided funding to treat non-remitters to the first treatment with combination medication and psychotherapy, to allow follow-up of patients for up to two years to identify predictors of recurrence, and to add patients to the sample to adequately power these studies.

Additional support was received from PHS Grant UL1 RR025008 from the Clinical and Translational Science Award program, National Institutes of Health, National Center for Research Resources, PHS Grant M01 RR0039 from the General Clinical Research Center program, and K23 MH086690 (BWD). Forest Labs and Elli Lilly Inc donated the study medications, escitalopram and duloxetine, respectively, and are otherwise uninvolved in study design, data collection, or data analysis, or interpretation of findings.

Predictors of remission in depression to individual and combined treatments (PReDICT): study protocol for a randomized controlled trial

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Volume 13, Number 106


, Pages 1-18

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Article | Final Publisher PDF


Background Limited controlled data exist to guide treatment choices for clinicians caring for patients with major depressive disorder (MDD). Although many putative predictors of treatment response have been reported, most were identified through retrospective analyses of existing datasets and very few have been replicated in a manner that can impact clinical practice. One major confound in previous studies examining predictors of treatment response is the patient’s treatment history, which may affect both the predictor of interest and treatment outcomes. Moreover, prior treatment history provides an important source of selection bias, thereby limiting generalizability. Consequently, we initiated a randomized clinical trial designed to identify factors that moderate response to three treatments for MDD among patients never treated previously for the condition. Methods/design Treatment-naïve adults aged 18 to 65 years with moderate-to-severe, non-psychotic MDD are randomized equally to one of three 12-week treatment arms: (1) cognitive behavior therapy (CBT, 16 sessions); (2) duloxetine (30–60 mg/d); or (3) escitalopram (10–20 mg/d). Prior to randomization, patients undergo multiple assessments, including resting state functional magnetic resonance imaging (fMRI), immune markers, DNA and gene expression products, and dexamethasone-corticotropin-releasing hormone (Dex/CRH) testing. Prior to or shortly after randomization, patients also complete a comprehensive personality assessment. Repeat assessment of the biological measures (fMRI, immune markers, and gene expression products) occurs at an early time-point in treatment, and upon completion of 12-week treatment, when a second Dex/CRH test is also conducted. Patients remitting by the end of this acute treatment phase are then eligible to enter a 21-month follow-up phase, with quarterly visits to monitor for recurrence. Non-remitters are offered augmentation treatment for a second 12-week course of treatment, during which they receive a combination of CBT and antidepressant medication. Predictors of the primary outcome, remission, will be identified for overall and treatment-specific effects, and a statistical model incorporating multiple predictors will be developed to predict outcomes. Discussion The PReDICT study’s evaluation of biological, psychological, and clinical factors that may differentially impact treatment outcomes represents a sizeable step toward developing personalized treatments for MDD. Identified predictors should help guide the selection of initial treatments, and identify those patients most vulnerable to recurrence, who thus warrant maintenance or combination treatments to achieve and maintain wellness.

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© 2012 Dunlop et al.; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution 2.0 Generic License ( http://creativecommons.org/licenses/by/2.0/), which permits making multiple copies, distribution, public display, and publicly performance, distribution of derivative works, provided the original work is properly cited. This license requires credit be given to copyright holder and/or author, copyright and license notices be kept intact.

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