Elsevier

Psychiatry Research

Volume 169, Issue 2, 30 September 2009, Pages 124-131
Psychiatry Research

Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: Results of the BRITE-MD study

https://doi.org/10.1016/j.psychres.2009.06.004Get rights and content

Abstract

Patients with Major Depressive Disorder (MDD) may not respond to antidepressants for 8 weeks or longer. A biomarker that predicted treatment effectiveness after only 1 week could be clinically useful. We examined a frontal quantitative electroencephalographic (QEEG) biomarker, the Antidepressant Treatment Response (ATR) index, as a predictor of response to escitalopram, and compared ATR with other putative predictors. Three hundred seventy-five subjects meeting DSM-IV criteria for MDD had a baseline QEEG study. After 1 week of treatment with escitalopram, 10 mg, a second QEEG was performed, and the ATR was calculated. Subjects then were randomly assigned to continue with escitalopram, 10 mg, or change to alternative treatments. Seventy-three evaluable subjects received escitalopram for a total of 49 days. Response and remission rates were 52.1% and 38.4%, respectively. The ATR predicted both response and remission with 74% accuracy. Neither serum drug levels nor 5HTTLPR and 5HT2a genetic polymorphisms were significant predictors. Responders had larger decreases in Hamilton Depression Rating Scale (Ham-D17) scores at day 7 (P = 0.005), but remitters did not. Clinician prediction based upon global impression of improvement at day 7 did not predict outcome. Logistic regression showed that the ATR and early Ham-D17 changes were additive predictors of response, but the ATR was the only significant predictor of remission. Future studies should replicate these results prior to clinical use.

Introduction

Major Depressive Disorder (MDD) is a leading cause of disability with total costs to society in excess of $80 billion annually; approximately two-thirds of these costs reflect the enormous disability associated with MDD (Greenberg et al., 2003, Kessler et al., 2006, Kessler et al., 2003, Kessler et al., 1994). One reason for these high costs is the length of time it takes for patients to recover. Although controlled efficacy trials suggest that most patients respond to treatment within 8 weeks (Papakostas et al., 2007), the Sequenced Treatment Alternatives to Relieve Depression (STAR⁎D) trial found that fewer than 50% of patients responded to the first trial of a serotonin selective reuptake inhibitor (SSRI) antidepressant (citalopram) and fewer than one-third achieved remission (Trivedi et al., 2006). Under standard care, the proportion of patients responding and remitting usually is even lower (Katon et al., 1996, Katon et al., 1999, Trivedi et al., 2004). Consequently, achieving response or remission with an initial medication remains a challenge for most patients with MDD and their physicians.

At present, there is no reliable method for predicting whether a medication will lead to response or remission other than “watchful waiting.” Methods to predict which medication would most likely benefit an individual patient could reduce patients' suffering. Such tools might include clinical features, biomarkers such as brain-imaging findings, or genetic polymorphisms (Bearden and Freimer, 2006).

Clinical characteristics have the advantage of being relatively easy to determine, but generally have not been useful for predicting response to particular medications. Symptom clusters such as anxiety or melancholia are associated with the overall likelihood of recovery but have not been shown to be reliable predictors of response to a specific medication for an individual patient (Fava et al., 2008, Rush, 2007, Small et al., 1995, Trivedi et al., 2006). Brain imaging also has been shown to have some promise for predicting response to treatment. Data suggest that pretreatment cerebral metabolism, white-matter lesions, or atrophy may be associated with outcome (Konarski et al., 2007), but the burden and cost of these procedures have limited their clinical adoption. Some genetic biomarkers, most notably genetic polymorphisms in the serotonin system, have been shown to influence the outcome of SSRI treatment. Two common and promising candidate polymorphisms are those in the promoter region of the serotonin transporter (5HTTLPR) and in the 5HT2a postsynaptic receptor, which in some studies have been associated with treatment response (Anguelova et al., 2003, McMahon et al., 2006).

One biomarker that has promise as a predictor of treatment response is quantitative electroencephalography (QEEG). QEEG power in the theta and alpha frequency bands (Knott et al., 1996, Ulrich et al., 1994, Ulrich et al., 1988) may identify patients who are most likely to respond to tricyclic antidepressants (TCAs) or SSRIs. Recent studies found that QEEG changes in the prefrontal region may reliably identify antidepressant medication responders within the first week of treatment (Cook et al., 2002, Leuchter et al., 1999). These findings are consistent with the fact that rhythmic midline prefrontal EEG activity has been shown to reflect the activity of the anterior cingulate and midline prefrontal cortex (Asada et al., 1999), brain areas implicated in mood regulation and the pathogenesis of depression. Refinement of this method might permit use of a limited electrode array in the prefrontal region (Iosifescu et al., 2006, Leuchter et al., 2005, Poland et al., 2006) that would be practical for routine clinical use.

The Biomarkers for Rapid Identification of Treatment Effectiveness in Major Depression (BRITE-MD) study was designed to evaluate several possible biomarkers and clinical measures that might be useful to help direct antidepressant medication decisions. The protocol assessed the predictive value of a frontal QEEG parameter, the Antidepressant Treatment Response (ATR) index (Aspect Medical Systems; Norwood, MA), which incorporates several EEG features determined from previously collected EEG datasets to be associated with response and/or remission during antidepressant treatment (Cook et al., 2002, Iosifescu et al., 2006, Leuchter et al., 2008). In this initial report from BRITE-MD, we tested the primary hypothesis that the ATR at 1 week after initiation of treatment with the SSRI escitalopram would predict response and remission after 7 weeks of treatment. We further tested the hypothesis that early changes in depressive symptom ratings, 5HTTLPR and 5HT2a genetic polymorphisms, and escitalopram serum levels, as well as investigator predictions based upon clinical impression, also would predict treatment response and remission.

Section snippets

Overview

The BRITE-MD study (ClinicalTrials.gov NCT00289523) was conducted at nine sites (departments of psychiatry at Baylor College of Medicine, Harbor-UCLA Medical Center, Massachusetts General Hospital, Northwestern University, UCLA Westwood, UCSD, University of Pittsburgh, and University of Texas Southwestern, as well as RD Clinical Research, a freestanding research facility). Institutional Review Boards approved the methods of the study.

Subjects

Three hundred seventy-five subjects, 18–75 years of age, who

Subject characteristics

A total of 375 subjects consented to participate in the study, and 331 met the criteria to participate and entered treatment. Forty-nine of these subjects did not continue through the primary endpoint for reasons including changes in life circumstances and removal by the investigators for failure to follow the study protocol (i.e., refusal to take medication or complete rating scales). There was no difference in age, gender, or severity of baseline depression between those who completed

Discussion

These results are consistent with the hypothesis that change in frontal QEEG after 1 week of treatment with a representative SSRI (escitalopram) is a useful biomarker for predicting 8-week treatment outcome. High ATR values were significantly associated with lower final depression scores, and ATR had 74% overall accuracy in predicting response and remission with escitalopram treatment.

The ATR was unique among the biomarkers examined here in that neither serum drug levels nor common genetic

Acknowledgments

Aspect Medical Systems provided financial support of this project. Aspect participated in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation and review of the manuscript. Final approval of the form and content of the manuscript rests with the authors.

The authors gratefully acknowledge the clinicians and research coordinators at Baylor College of Medicine, Harbor-UCLA Medical Center, Massachusetts General Hospital, Northwestern

Andrew Leuchter, M.D., has provided scientific consultation or served on advisory boards for Aspect Medical Systems, Eli Lilly and Company, Novartis Pharmaceuticals, MEDACorp, AstraZeneca, Takeda Pharmaceuticals, and Merck & Co. He has served on a speaker's bureau for Eli Lilly and Company and Wyeth-Ayerst Pharmaceuticals. He has received research/grant support from the National Institute of Mental Health, the National Center for Complementary and Alternative Medicine, Aspect Medical Systems,

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    Andrew Leuchter, M.D., has provided scientific consultation or served on advisory boards for Aspect Medical Systems, Eli Lilly and Company, Novartis Pharmaceuticals, MEDACorp, AstraZeneca, Takeda Pharmaceuticals, and Merck & Co. He has served on a speaker's bureau for Eli Lilly and Company and Wyeth-Ayerst Pharmaceuticals. He has received research/grant support from the National Institute of Mental Health, the National Center for Complementary and Alternative Medicine, Aspect Medical Systems, Eli Lilly and Company, Novartis Pharmaceuticals, Wyeth-Ayerst Pharmaceuticals, Merck & Co., Pfizer, Vivometrics, and MedAvante. He also is a minor stockholder in Aspect Medical Systems.

    Ian A. Cook, M.D., has served as an advisor and consultant for Ascend Media, Bristol-Meyers Squibb, Cyberonics Inc., and Janssen. He has served on the Speaker's Bureau for Bristol-Meyers Squibb, Medical Education Speakers Network, Pfizer Pharmaceuticals Inc., and Wyeth Pharmaceuticals. Dr. Cook receives Research Support from Aspect Medical Systems, Cyberonics Inc., Eli Lilly & Company, Novartis Pharmaceuticals, Pfizer, Inc., and Sepracor.

    Lauren Marangell, M.D., currently is an employee of Eli Lilly and Company, Indianapolis, IN. The work described in this manuscript was performed while she was on the faculty of the Baylor College of Medicine and does not necessarily reflect the views of Eli Lilly and Company. She previously served as a consultant for, or received lecture honoraria from, Aspect Medical Systems, Cyberonics, Inc., Medtronics, GlaxoSmithKline, Pfizer, Inc., Novartis Pharmaceuticals, and Forest Pharmaceuticals. Dr. Marangell had received research support from Bristol-Myers Squibb Company, Cyberonics, Inc., Neuronetics, National Institute of Mental Health, Stanley Foundation, NARSAD, American Foundation for Suicide Prevention, Aspect Medical Systems, and Sanofi-Aventis.

    William S. Gilmer, M.D., has served on the Speaker's Bureau for GlaxoSmithKline and Pfizer. He has also received honoraria from GlaxoSmithKline and Pfizer, Inc. Additionally, Dr. Gilmer receives Research Support from Abbott, Aspect Medical Systems, Forest Pharmaceuticals, Janssen, the National Institute of Mental Health, Neuronetics, Novartis Pharmaceuticals, and Pfizer.

    Karl S. Burgoyne, M.D., has received Research Support from Aspect Medical Systems.

    Robert H. Howland, M.D., has received Research Support from Aspect Medical Systems, Bristol-Myers Squibb, Cederroth, Cyberonics Inc., Forest Pharmaceuticals, and Novartis Pharmaceuticals.

    Madhukar H. Trivedi, M.D., has served as an advisor and consultant for Abbott Laboratories, Akzo (Organon Pharmaceuticals), Bayer, Bristol-Myers Squibb Company, Cephalon, Cyberonics, Inc., Forest Pharmaceuticals, GlaxoSmithKline, Janssen Pharmaceutica Products, Johnson & Johnson PRD, Eli Lilly & Company, Meade Johnson, Parke-Davis Pharmaceuticals, Pfizer, Inc., Pharmacia & Upjohn, Sepracor, Solvay Pharmaceuticals, Inc., and Wyeth-Ayerst Laboratories. He has served on the Speaker's Bureau for Akzo (Organon Pharmaceuticals), Bristol-Myers Squibb Company, Cephalon, Inc., Cyberonics, Inc., Forest Pharmaceuticals, Janssen Pharmaceutica Products, LP, Eli Lilly & Company, Pharmacia & Upjohn, Solvay Pharmaceuticals, Inc., and Wyeth-Ayerst Laboratories. He has received Research Support from Bristol-Myers Squibb Company, Cephalon, Inc., Corcept Therapeutics, Inc., Cyberonics, Inc., Eli Lilly & Company, Forest Pharmaceuticals, GlaxoSmithKline, Janssen Pharmaceutica, Merck, Novartis Pharmaceuticals, Pfizer, Inc., Pharmacia & Upjohn, Predix Pharmaceuticals, Solvay Pharmaceuticals, and Wyeth-Ayerst Laboratories.

    Sidney Zisook, M.D., has served as an advisor and consultant for Glaxo-Smith Kline. He has served on the Speaker's Bureau for Glaxo-Smith Kline and Forest Laboratories. Additionally, Dr. Zisook has received Research Support from Aspect Medical Systems, PemLab, and Jed Foundation.

    Rakesh Jain, M.D., M.P.H., has served as an advisor and consultant for Addrenex Pharmeceuticals, Eli Lilly & Company, Forest Laboratories, Pfizer, Impax Laboratories, Shire Pharmaceuticals, and Takeda Pharmaceuticals. He has served on Speaker's Bureaus for Eli Lilly & Company, Pfizer, Inc., Shire Pharmaceuticals, and Takeda Pharmaceuticals. He has received Research Support from Abbott Laboratories, Aspect Medical Systems, Merck, Eli Lilly, GlaxoSmithKline, Shire Pharmaceuticals, Pfizer, and Forest Pharmaceuticals.

    James T. McCracken, M.D., has served as an advisor and consultant for Abbott Laboratories, Bristol-Meyers Squibb, Eli Lilly & Company, Janssen, Novartis Pharmaceutical, and Wyeth. He has served on the Speaker's Bureau for Abbott Laboratories and Genentech, Inc. Dr. McCracken receives Research Support from Bristol-Meyers Squibb, Eli Lilly & Company, and Shire.

    Maurizio Fava, M.D., has served as an advisor and consultant for Aspect Medical Systems, Astra-Zeneca, Bayer AG, Biovail Pharmaceuticals, BrainCells, Inc. Bristol-Myers Squibb, Cephalon, Compellis, Cypress Pharmaceuticals, Dov Pharmaceuticals, Eli Lilly, EPIX Pharmaceuticals, Fabre-Kramer Pharmaceuticals, Forest Pharmaceuticals, GlaxoSmithKline, Grunenthal GmBH, Janssen Pharmaceutica, Jazz Pharmaceuticals, J & J Pharmaceuticals, Knoll Pharmaceuticals, Lundbeck, MedAvante, Neuronetics, Novartis Pharmaceuticals, Nutrition 21, Organon, PamLab LLC, Pfizer, PharmaStar, Pharmavite, Roche, Sanofi/Synthelabo, Sepracor, Solvay Pharmaceuticals, Somaxon, Somerset Pharmaceuticals, and Wyeth-Ayerst Laboratories. He has served on Speaker's Bureaus for Astra-Zeneca, Boehringer-Ingelheim, Bristol-Myers Squibb, Cephalon, Eli Lilly & Company, Forest Pharmaceuticals, GlaxoSmithkline, Novartis Pharmaceuticals, Organon, Pfizer, PharmaStar, and Wyeth-Ayerst Laboratories. He has received Research Support from Abbott Laboratories, Alkermes, Aspect Medical Systems, Astra-Zeneca, Bristol-Myers Squibb, Cephalon, Eli Lilly & Company, Forest Pharmaceuticals, GlaxoSmithKline, J & J Pharmaceuticals, Lichtwer Pharma GmbH, Lorex Pharmaceuticals, Novartis Pharmaceuticals, Organon, PamLab LLC, Pfizer, Pharmavite, Roche, Sanofi/Synthelabo, Solvay Pharmaceuticals, and Wyeth-Ayerst Laboratories.

    Dan V. Iosifescu, M.D., has provided scientific consultation to Cephalon, Inc., Forest Laboratories, Gerson Lehrman Group, and Pfizer Inc. He serves on the Speaker's Bureau for Cephalon Inc., Eli Lilly & Company, Forest Laboratories, and Pfizer Inc. He has received research/grant support from Aspect Medical Systems, Forest Laboratories, and Janssen Pharmaceutica.

    Scott Greenwald, Ph.D., is an employee and a stockholder of Aspect Medical Systems, Inc.

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