Background
Major depressive disorder (MDD) is a common, frequently chronic, disabling, and debilitating psychiatric disorder. Approximately 17% of US citizens will at some point in their lives experience MDD with roughly twice as many females as males suffering from the disorder[
1]. A widely cited study, Global Burden of Disease, a collaboration of the World Bank, the World Health Organization, and the Harvard School of Public Health, reported that MDD was the fourth most disabling disorder, and predicted that by 2020 MDD would be the second leading cause of disability worldwide, trailing only coronary artery disease[
2]. Although it is difficult to ascertain the financial burden of MDD, one well-conducted study in the US found that among primary care patients, healthcare costs of individuals suffering from MDD were twice those of individuals without MDD[
3]; these differences resulted largely from increased healthcare costs associated with depressed patients’ utilization of medical services at four times the rate of patients who did not suffer from depression.
The initial onset of MDD occurs most frequently between the ages of 15 years and 29 years, and recent studies have found that approximately 50% of teenagers who are diagnosed with MDD experience a second episode by the age of 25 years[
4,
5]. One particularly problematic aspect of MDD is the increased likelihood for recurrence following each successive episode[
6] with an ultimate mean of approximately 5 years between episodes[
7]. Furthermore, MDD is associated with an increased risk of medical disorders, including cardiovascular and endocrine diseases[
8‐
10]. In sum, MDD frequently begins during the teenage and early adult years, and it continues over the life span causing substantial negative social, economic, and health effects[
11]. The past few decades have witnessed the development and evaluation of new antidepressant medications and psychotherapies for MDD[
12,
13]. Despite these advances, depression treatment continues to be hampered by two major limitations: an unacceptably low rate of symptomatic remission, and the virtual absence of any practical predictors of treatment response, whether partial or complete. Although it is widely considered that current interventions benefit approximately 60% of MDD patients, only about 30% to 40% of patients show full remission of their symptoms as defined by the MacArthur criteria (for example, a 17-item Hamilton Depression Rating Scale (HDRS) score <8)[
14,
15]. Approximately 30% more demonstrate some response to treatment, indicating they experience clinically important reductions in their depressive symptom burden, yet also continue to experience clinically important residual symptoms. Patients who experience a response short of remission are more vulnerable to relapses and recurrences of the disorder[
16] and experience greater functional disability[
17].
Current treatment for MDD involves a trial-and-error approach because there are no consistently identified predictors of differential response across treatment modalities. Primary first-line treatments consist of either an evidence-based form of psychotherapy or antidepressant medication. In patients treated pharmacologically, several treatment options are available, but there are very few clinical trial data to guide clinicians as to which first step enhances the odds of remission for an individual patient[
18]. Illustrating the importance of such trials, one retrospective study found a differential advantage for psychotherapy over medication (nefazodone) in chronically depressed patients with early life trauma[
19]. A treatment regimen that ultimately proves to be ineffective results in continuing patient distress and role dysfunction, discouragement regarding possible relief from MDD, exposure to potential side effects, and unnecessary medical costs. Among the roughly 70% of depressed patients who do not remit with their first treatment, many do not return to explore other treatment options that might have proven effective[
20].
Previous efforts attempting to identify predictors of treatment response have typically been
post-hoc analyses of datasets designed to test other hypotheses[
18]. Numerous predictors have been identified by this approach, but they lack consistent prospective validation, and such predictive studies generally examine a single treatment. Examples of potential demographic predictors of treatment response have included age, gender, marital status, family history of treatment response, and socioeconomic factors[
15]. Clinical predictors have included diagnostic subtype[
21,
22], severity of depression[
23], chronicity[
15], symptom profiles[
24], patient treatment preference[
25], early life stress[
19], personality profiles[
26], previous treatment[
27], psychomotor speed[
28], and co-morbid diagnoses[
29]. Physiologic predictors have included auditory evoked potentials[
30], event-related potentials[
31], and quantitative electroencephalograms[
32]. Biochemical and endocrinology predictors include hypothalamic-pituitary-adrenal (HPA) axis measures[
33], urinary 3-methoxy-4-hydroxyphenylglycol (MHPG)[
34], and serotonergic measures in serum/platelets[
35]. Imaging predictors have included pre-treatment patterns of regional glucose metabolism and blood flow measured with positron emission tomography (PET)[
36], as well as structural and functional magnetic resonance imaging (fMRI) studies[
37].
With rare exception, the previously noted studies have retrospectively examined patterns correlated to outcomes for a specific treatment. A few have tracked differences between responders and non-responders to two different treatments, for example drug
vs. psychotherapy or drug
vs. drug[
38]. Numerous attempts at identifying genetic polymorphisms as predictors of treatment for MDD have been made[
39]. So far, except for some polymorphisms directly influencing the pharmacokinetics of antidepressant drugs[
40], no consistently replicated (and thus clinically relevant) candidates have emerged from candidate gene or genome-wide association studies[
41]. This suggests that genetic information may need to be combined with other biomarkers and clinical variables for a more reliable prediction of response[
42]. In addition, few previous studies have investigated genetic polymorphisms as differential predictors for different types of antidepressant treatments[
43].
One of the strategic objectives of the National Institute of Mental Health (NIMH) is to develop better, more specific interventions for patients with mental illnesses; this approach is broadly known as ‘personalized medicine’. In the field of mental health, personalized medicine has come to encompass the moderators and mediators of treatment response, including biological, genetic, behavioral, experiential, clinical, and environmental factors[
44]. Personalized medicine may gain additional importance with the increases in racial and ethnic diversity predicted by the US Census Bureau[
45]. Before these NIMH goals and objectives were fully articulated, we developed the Emory Predictors of Response in Depression to Individual and Combined Treatments (PReDICT) study that commenced recruitment in January 2007.
Aims
The primary aim of PReDICT is to identify predictors of remission with acute treatment for MDD; predictors comprise genetic, endocrine, immune, and personality measures, as well as baseline and early-treatment fMRI of the central nervous system. Predictors will be identified by utilizing sophisticated multivariate procedures to determine which variables have clinically important and statistically significant effects for the prediction of remission and response.
A secondary aim of the project is to identify predictors of recurrence of major depression during a 21-month follow-up after acute treatment. Predictors of remission will include baseline, treatment, and post-treatment measures, detailed below.
Discussion
Previous treatment with psychotherapy or medication may impact subsequent response to treatment and may produce persisting biological, behavioral, cognitive, and emotional changes[
137]. Thus, we chose to examine predictors of treatment outcomes in patients never previously treated for depression. To make the trial reflect real-world decisions, we examined not only medication versus psychotherapy, but two different medications; all three treatments are currently considered potential first-line interventions. The design considered the primary treatment decisions to be made from the start of care including: (1) whether to initiate treatment with medication or psychotherapy; and (2) if a medication option is selected, which is the most appropriate specific class of medication. Thus, we designed a three-armed trial to evaluate clinical, biological, genetic, and personality factors that may predict outcomes to common first-line treatment options for MDD. The study was further designed to expect that while individual measures might prove predictive, the more likely outcome would be that a combination of clinical, imaging, and genetic markers would predict outcomes to individual treatments. The study design and unique patient population we have chosen has limitations, and alternative designs were carefully considered. We did not include a placebo control group or extended placebo lead-in because it would undoubtedly result in a marked reduction in the number patients willing to enter the study. To maximize generalizability and feasibility, we chose our medication treatments from the classes of antidepressants most commonly used to treat depression; those classes are SSRIs, SNRIs, and bupropion. Because anxiety disorders are highly co-morbid with major depression, and because the presence of a co-morbid anxiety disorder (other than OCD) was not an exclusion criterion for entry into the study, bupropion was not selected. Unlike SSRIs and SNRIs, bupropion does not have an FDA-indication for the treatment of anxiety disorders, and is associated with poorer response than SSRIs in treating depressed patients with high levels of anxiety[
138].
Among the SSRIs, we opted for escitalopram because it is the most selective SSRI, having no or very little effects on norepinephrine or dopamine reuptake. In contrast, paroxetine is an antagonist of both the serotonin transporter (SERT) and norepinephrine transporter (NET)[
139]. Escitalopram has the lowest likelihood of drug-drug interactions of any of the SSRIs[
140]. Adverse effect rates with escitalopram are lower than with citalopram, which we expected to benefit patient retention in the study. Although one of the antidepressants clearly needed to be an SSRI, arguments could be made to replace duloxetine with any of the following: venlafaxine, mirtazapine, bupropion, nefazadone, a tricyclic antidepressant (TCA), or a monoamine oxidase inhibitor (MAOI). We opted against mirtazapine, nefazadone, TCAs, and MAOIs due to issues of lower tolerability and frequency of clinical use. Duloxetine was selected over venlafaxine as the SNRI for several reasons. First, the FDA-approved dose range of venlafaxine is much broader, and therefore less comparable to escitalopram. Second, venlafaxine has a more adverse cardiovascular toxicity profile, and it may have a greater overdose liability than duloxetine[
141]. Finally, at low doses venlafaxine acts primarily through SERT inhibition, with higher doses required to achieve NET inhibition[
142,
143].
Interpersonal psychotherapy is another form of psychotherapy we could have included, but we did not possess the statistical power to add another treatment arm, and the supporting data for the efficacy of CBT are more extensive. Other limitations include the omission of geriatric depression - necessary because of the growing evidence suggesting that vascular depression, which accounts for a sizeable percentage of the geriatric depressed population, is truly a distinct neurobiological entity[
144]. Also excluded are patients with clinically important co-morbid medical disorders or substance abuse, children and adolescents, and those with psychotic depression. Although these patients are of interest, we believe that the benefits of keeping our patient characteristics as free of potential confounding variables as possible will maximize our ability to examine our primary objectives.
We believe this study design best allows for assessment of the effects of several potentially important moderators and mediators of treatment outcomes, as well as the interactions between moderators, in a sample unconfounded by previous treatment effects. The results of this study should inform clinical treatment decisions and identify future research approaches to further improve the care of depressed patients.
Acknowledgements
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.
We thank Flavia Mercado, MD, for her assistance in operationalizing the study site at the Grady Hospital IMC.
Competing interests
In the past 5 years, the authors report the following: BWD has received honoraria for consulting work with Bristol-Myers Squibb, Imedex LLC, Medavante, and Pfizer. He has also received research support from Astra Zeneca, Bristol-Myers Squibb, Evotec, Forest, GlaxoSmithKline, NIMH, Novartis, Ono Pharmaceuticals, Pfizer, Takeda, and Transcept. EBB has received grant support from Pharma-Neuroboost and is co-inventors on the following patent applications: Means and methods for diagnosing predisposition for treatment emergent suicidal ideation (TESI). European application number: 08016477.5 International application number: PCT/EP2009/061575; FKBP5: a novel target for antidepressant therapy. International publication number: WO 2005/054500 and Polymorphisms in ABCB1 associated with a lack of clinical response to medicaments. International application number: PCT/EP2005/005194. JFC has received research support from NIDA, NIMH, NARSAD, Roche, and Seaside Therapeutics. MK has consulting agreements with Eagle Pharmaceutical and St Jude Medical Inc., and receives book royalty income from McGraw-Hill/Irwin. He also serves on the Clinical Advisory Board for the Shriners Hospital. Dr Kutner serves on an NIDDK DSMB for a multicenter trial of calcitriol compared to high and low dose cholecalciferol for the treatment of vitamin D insufficiency in patients with advanced chronic kidney failure. CBN has received research support from the NIH and Agency for Healthcare Research and Quality. He has served as a consultant to Xhale, Takeda and SK Pharma. He has been a stockholder in CeNeRx Biopharma, NovaDel Pharma Inc., PharmaNeuroboost, Revaax Pharma, and Xhale. He has had additional financial interests in Corcept, CeNeRx BioPharma. PharmaNeuroboost, Novadel Pharma, and Revaax. He has served on the scientific advisory boards of American Foundation for Suicide Prevention (AFSP); AstraZeneca, CeNeRx Biopharma, Forest Labs, Janssen/Ortho-McNeil, Mt. Cook Pharma Inc., NARSAD, NovaDel Pharma, Inc., Pharma-Neuroboost, Quintiles, and the Anxiety Disorders Association of America. He has served on the Board of Directors for the AFSP, George West Mental Health Foundation, NovaDel Pharma, Inc., and Mt. Cook Pharma Inc. Dr Nemeroff holds a patent on the method and devices for transdermal delivery of lithium (US 6,375,990 B1) and the method to estimate drug therapy via transport inhibition of monoamine neurotransmitters by
ex vivo assay (US 7,148,027B2). JDN has received lifetime research support from Eli Lilly, Glaxo SmithKline (GSK), Janssen, the National Alliance for Research on Schizophrenia and Depression (NARSAD), the National Institutes of Health (NIH), and Wyeth. He has served on speakers’ bureaus or received honoraria from Astra-Zeneca, Eli Lilly, GSK, Pfizer, and Wyeth. He has served on advisory boards for GSK. MJO reports research support from NIH, Lundbeck A/S, Cyberonics, Eli Lilly, Ortho- McNeil Janssen, AstraZeneca, Dainippon Sumitomo Pharma, SK Life Sciences, and Sunovion Pharmaceuticals. He has served as a consultant to H Lundbeck A/S, and RJ Reynolds, and has a patent for a method of assessing antidepressant drug therapy via transport inhibition of monoamine neurotransmitters (US 7,148,027 B2). TWWP has received research funding from NIH and NARSAD, and has also received funding from GSK to examine gene expression patterns in patients with major depression. He also serves on a scientific advisory board for Questcor Pharmaceuticals. JCR has received research support from Abaxis Inc., Abbott, Beckman Coulter, NIH, Roche Diagnostics, and Waters, Inc. DW is a developer and copyright holder of the Shedler-Westen Assessment Procedure (SWAP-II), an instrument used in this study for personality assessment and diagnosis. The SWAP-II is likely to have commercial applications, available at
http://www.swapassessment.org, although no funding was provided by any commercial entity for this research. WEC is an officer of Hugarheill enf, an Icelandic company dedicated to prevention of depression, and he receives book royalties from John Wiley and Sons. He is a consultant to the George West Mental Health Foundation that oversees Skyland Trail, a residential treatment facility in Atlanta, GA. HSM holds intellectual property in the field of deep brain stimulation for depression and is a consultant for St Jude Medical, Inc. MMG, BK, MEK, and VAR report no competing interests.
Authors’ contributions
BWD led the manuscript development and serves as the lead study psychiatrist. EBB, JFC, MMG, MEK, BK, MK, JDN, MJO, JCR, and DW all contributed to the study design and wrote sections of the manuscript related to their area of expertise. VAR is the lead psychiatrist for the IMC Spanish-speaking clinic site and contributed to the sections of the manuscript related to that site. CBN conceived of the project, led the study development process and served as the project‘s initial principal investigator. WEC worked with BWD in the manuscript development, and he and HSM wrote the sections of the manuscript related to their area of expertise and serve as the principal investigators for the PReDICT study. All authors edited the manuscript and approved the final version.