Functional Recovery in Major Depressive Disorder: Focus on Early Optimized Treatment

Functional Recovery in Major Depressive Disorder:

Focus on Early Optimized Treatment

Jeffrey Habert, MD, CCFP, FCFPa,*; Martin A. Katzman, MD, FRCPCb; Oloruntoba J. Oluboka, MDc;
Roger S. McIntyre, MDd; Diane McIntosh, MD, FRCPCe; Glenda M. MacQueen, MD, PhDf;
Atul Khullar, MD, FRCPCg; Roumen V. Milev, MD, PhD, FRCPCh; Kevin D. Kjernisted, MDe;
Pratap R. Chokka, MDg; and Sidney H. Kennedy, MD, FRCPCi

ABSTRACT

Objective: This article presents the case that a more rapid, individualized approach to treating major depressive disorder (MDD) may increase the likelihood of achieving full symptomatic and functional recovery for individual patients and that studies show it is possible to make earlier decisions about appropriateness of treatment in order to rapidly optimize that treatment.

Data Sources: A PubMed search was conducted using terms including major depressive disorder, early improvement, predictor, duration of untreated illness, and function. English-language articles published before September 2015 were included. Additional studies were found within identified research articles and reviews.

Study Selection: Thirty antidepressant studies reporting predictor criteria and outcome measures are included in this review.

Data Extraction: Studies were reviewed to extract definitions of predictors, outcome measures, and results of the predictor analysis. Results were summarized separately for studies reporting effects of early improvement, baseline characteristics, and duration of untreated depression.

Results: Shorter duration of the current depressive episode and duration of untreated depression are associated with better symptomatic and functional outcomes in MDD. Early improvement of depressive symptoms predicts positive symptomatic outcomes (response and remission), and early functional improvement predicts an increased likelihood of functional remission.

Conclusions: The approach to treatment of depression that exhibits the greatest potential for achieving full symptomatic and functional recovery is early optimized treatment: early diagnosis followed by rapid individualized treatment. Monitoring symptoms and function early in treatment is crucial to ensuring that patients do not remain on ineffective or poorly tolerated treatment, which may delay recovery and heighten the risk of residual functional deficits.

Prim Care Companion CNS Disord 2016;18(5):doi:10.4088/PCC.15r01926

© Copyright 2016 Physicians Postgraduate Press, Inc.

aDepartment of Family and Community Medicine, University of Toronto, Ontario, Canada

bSTART Clinic for Mood and Anxiety Disorders, Toronto, Ontario, Canada

cDepartment of Psychiatry, University of Calgary, Alberta, Canada

dDepartment of Psychiatry and Pharmacology, University of Toronto, Ontario, Canada

eDepartment of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada

fMathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Alberta, Canada

gDepartment of Psychiatry, University of Alberta, Edmonton, Alberta, Canada

hDepartment of Psychiatry, Queen’s University, Kingston, Ontario, Canada

iDepartment of Psychiatry, University of Toronto, Ontario, Canada

*Corresponding author: Jeffrey Habert, MD, CCFP, FCFP, Department of Family Medicine, University of Toronto, 206–2900 Steeles Ave E, Thornhill, ON L3T 4X1 Canada (jhabert@rogers.com).

Major depressive disorder (MDD) is a common illness with a lifetime prevalence of 3%–17%,1 characterized by a persistent low mood and the loss of interest or pleasure in many aspects of life. Unfortunately, for many people who experience an episode of depression, MDD can become a chronic and recurrent condition.2,3 The World Health Organization estimates that MDD affects 350 million people worldwide.4 Twelve-month prevalence rates for MDD were estimated at 6.6% (95% CI, 5.9%–7.3%) in the US National Comorbidity Survey Replication (NCS-R)5 and 4.7% (95% CI, 4.3%–5.1%) in the Canadian Community Health Survey—Mental Health (2012; CCHS-MH).6 Rates of MDD were higher in women in both the CCHS-MH (4.9% [women] vs 2.8% [men] past-year MDD) and the NCS-R (lifetime odds ratio [95% CI] for women vs men = 1.7 [1.5–2.0]).5,6 The odds ratio for 12-month MDD among lifetime cases was highest for patients 18 to 29 years of age in the NCS-R, and 12-month prevalence in the CCHS-MH sample was highest for patients 15 years of age—the youngest patients included in each survey.6,7 CCHS-MH data suggest that the estimated past-year prevalence of major depressive episode has remained steady in Canada over the past decade.6

MDD is the second leading cause of disability worldwide8 and the leading cause of disability in adolescents aged 10 to 19 years.9 Depressive symptoms can impair an individual’s ability to perform at work or school, to fulfill family responsibilities, and to enjoy leisure activities.10,11 Indeed, 87.4% of NCS-R respondents with 12-month MDD reported at least moderate impairment in home, work, relationship, or social role functioning.5 The cost of MDD for patients who do not respond to treatment includes the increased use of health care resources and lost productivity compared with patients who achieve
remission.12–14 Impairment in role function is a critical driver of the cost of MDD. Both absenteeism and presenteeism (health-related reduction in performance at work15) contribute to the cost of lost work productivity and increase significantly with depression severity.16,17 In an analysis based on the NCS-R,18 MDD was associated with an estimated 225 million lost workdays per year and US $36.6 billion in lost productivity annually.

Many patients with MDD remain untreated, and among those who receive treatment, a large percentage does not regain their premorbid level of functioning. On the basis of data from the 2005 and 2006 National Survey on Drug Use and Health surveys,19 37.6% of participants with MDD did not seek treatment. Two separate meta-analyses20,21 examining recognition and diagnosis of depression concluded that in primary care settings, fewer than half of all true cases of depression are diagnosed. Moreover, less than half of those treated for MDD with antidepressant drugs achieve remission. Analyses of randomized controlled trials of selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and tricyclic antidepressants (TCAs) found remission rates that ranged from 38% to 61%.22,23 Although some individual clinical trials have suggested an advantage of one antidepressant drug or class over another,22,23 no one antidepressant has consistently been shown to be associated with superior efficacy for individual patients.24,25 The proportion of patients achieving remission in clinical practice is estimated to be even lower than the rates reported in clinical trials.26 Furthermore, remission of depressive symptoms does not necessarily result in a return to full function. In an analysis27 examining symptomatic and functional remission during acute treatment, 38% of patients achieved symptomatic remission (17-item Hamilton Depression Rating Scale28 [HDRS-17] total score ≤ 7) and 32% achieved functional remission (Sheehan Disability Scale29 [SDS] total score ≤ 6); however, only 23% of patients achieved combined symptomatic and functional remission. For many MDD patients, full functional recovery lags behind the improvement of depressive symptoms, even among those treated to symptomatic remission.27,30,31

The potential for functional improvement decreases with the chronicity of symptoms and treatment failure,15,31 thus underscoring the urgency of early diagnosis and effective treatment. Clinicians have previously used a “start low, go slow” approach to treatment of MDD, choosing a first treatment at the lowest effective dose and giving that treatment a trial of up to 6 to 8 weeks before deciding whether an adjustment is warranted.32–34 Using this one size fits all approach may, however, contribute to low remission rates and the failure to return patients to full function after a depressive episode. This review presents the case that a more rapid, individualized approach to treating MDD—early optimized treatment, characterized by early diagnosis followed by rapid treatment initiation, close monitoring and assessment, and prompt adjustment of treatment—offers the greatest opportunity for full functional recovery. Examination of early response to treatment suggests that it is possible to make earlier decisions about appropriateness of treatment in order to rapidly optimize treatment for individual patients. Factors involved in treatment selection for an individual patient are beyond the scope of this review.

METHOD

A PubMed search was conducted using terms including major depressive disorder, early improvement, predictor, duration of untreated illness, and function. English-language articles published before September 2015 were included. Additional studies were found within identified research articles and reviews. Thirty antidepressant studies reporting predictor criteria and outcome measures are included in this review.35–64

Studies were reviewed to extract definitions of predictors, outcome measures, and results of the predictor analysis. Results were summarized separately for studies reporting effects of early improvement, baseline characteristics, and duration of untreated depression.

RESULTS

Treating to Full Functional Recovery

Core features of MDD. On the basis of criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5),11 MDD is characterized by the presence of at least 5 of 9 defined symptoms: depressed mood, loss of interest or pleasure in activities, changes in weight or appetite, sleep disturbance, slowing of thought and reduction of movement, fatigue or energy loss, feelings of worthlessness or guilt, difficulty concentrating and making decisions, and suicidal thoughts or behaviors. These symptoms must also “cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.”11(p161)

Evolution of treatment goals. Symptomatic remission has long been the goal of MDD treatment.32,65,66 Remission has been defined as “an improvement of sufficient magnitude . . . that the individual is asymptomatic (ie, no longer meets syndrome criteria for the disorder and has no more than minimal symptoms).”67(p853) Definitions of remission are based on validated depression rating scales, including a HDRS-17 total score ≤ 7,67 a Montgomery-Asberg Depression Rating Scale (MADRS) score ≤ 10,68 a Quick Inventory of Depressive Symptomatology–Self-Report (QIDS-SR-16) score ≤ 6,69 a Beck Depression Inventory (BDI) score ≤ 8,67 and a 9-item Patient Health Questionnaire (PHQ-9) score < 5.70 However, it is not uncommon for patients meeting criteria for remission to continue to experience disabling residual symptoms of depression.71

Ninety percent of remitted patients may have at least mild or moderate residual symptoms.71 Residual symptoms increase the risk of relapse substantially and reduce the time to depression recurrence, even in those patients whose symptoms are treated to remission as defined by scores on depression rating scales.71–73 Residual symptoms can have a profound effect on functioning, even in patients meeting the definition for remission. The most prevalent residual symptoms are also the symptoms most likely to have an impact on psychosocial functioning: sleep disturbance, low energy or fatigability, anxiety, problems with concentration/decision making, lack of sexual interest, and pessimism about the future.71,74 Residual symptoms in remitted MDD patients can affect their ability to function at work, at home, and in social settings.72 In the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial,15 improved depression scores were associated with functional improvement, including work productivity, less time away from work, and general functionality. In STAR*D patients who met the criteria for symptom remission, work productivity improved; however, impairment continued for some in other areas of functioning.15,75

Current MDD treatment guidelines suggest that the achievement of symptomatic remission should be considered an important first step toward the more challenging and no less crucial goal of full functional recovery.24,25 Treatment objectives in depression have evolved from being based purely on symptomatic remission and now include full functional recovery.76,77 Functional improvement does not always parallel the improvement of scores on depression symptom rating scales and may lag behind.27,30,31 Functional assessments and depression symptom rating scales measure different aspects of MDD. Functional improvement may begin well after symptoms of depression begin to improve78 and often takes additional time to become consistent and quantifiable.

Achieving full functional recovery requires resolution of all core features of MDD, including residual symptoms that can have a direct impact on functioning (Figure 1).79 This definition of full functional recovery is in line with the patients’ view that symptom resolution is one factor in determining remission from depression, but returning to their usual level of function and regaining enjoyment of their usual activities and relationships are just as important.80 Critical end points in depression treatment should be empirically supported and measurable, and there exists a range of assessment tools for measuring functional outcomes. Those tools most commonly used in clinical trials include the SDS, the Quality of Life Enjoyment and Satisfaction Questionnaire81 (Q-LES-Q), the Medical Outcomes Study 36-Item Short-Form Health Survey82 (SF-36) or the 12-item version83 (SF-12), the Lam Employment Absence and Productivity Scale84 (LEAPS), and the Social Adjustment Scale–Self-Report version85 (SAS-SR).86,87 These instruments focus on a variety of functional domains such as work, social life, family activities, and self-care. Among these scales, the easiest to administer (with 3 brief self-report items) is the SDS, which also has a validated threshold score for functional remission. On the basis of a receiver operating characteristic (ROC) analysis of SDS total scores in 3,530 patients in 10 clinical trials, a cutoff defining functional remission has been determined as a total score ≤ 7.88 A clinically meaningful difference in SDS score was determined to be 2.8 in the same study.88 Because of its ease of use, the patient-administered SDS is an excellent, validated tool to assess functioning quickly in a primary care setting. The tool can be used at the initial diagnostic assessment and also to track change over time, as treatment is implemented, in order to assess whether treatment adjustment may be warranted.

Early Optimized Treatment of Depression

There is a wide range of pharmacotherapy options available for treating patients with MDD.24,34 A substantial percentage of patients will fail to remit on any given antidepressant drug,22,23 however, and the tolerability of a particular drug will differ among patients.24,34,89 Therefore, effective pharmacotherapy for depression requires that antidepressant treatment is optimized for each patient, determining the drug and dosage best suited to the individual.24,34 Ideal management of depression is therefore a multistep, ongoing process that includes screening and early diagnosis, evaluating symptoms and functional impairment, initial selection of treatment, monitoring tolerability and adherence, assessing clinical response, adjusting treatment, and continuing to monitor and assess symptomatic and functional improvement until treatment goals are achieved.34

A start low, go slow approach to treatment selection may be appropriate for specific, at-risk patient populations.34,90,91 However, results from studies reviewed in this section suggest that shortening the time between onset of depression and providing optimized treatment may result in better clinical outcomes, increasing the likelihood of achieving full functional recovery from the depressive episode. Further, optimization of treatment can take place earlier in the course of treatment if guided by earlier systematic monitoring of symptoms, functional status, side effects of medication, and adherence.

Time to treatment and efficacy outcomes. Patient clinical characteristics that are generally related to the delay between onset of symptoms and initiation of treatment have been assessed as predictors of treatment outcomes (Tables 1–3).35–49 Findings for different measures related to depression history are mixed. Studies35,36,38,39,42,44 have been largely consistent in reporting that a longer duration of current episode is associated with more negative clinical outcomes, including depression symptom scores, and symptomatic response and remission. One study37 showed that duration of current episode did not predict time to relapse (Table 1). In the single study40 that examined functional outcomes, duration of current episode did not predict functional response or remission at week 8. Number of previous depressive episodes, as either a continuous or categorical (previous episode vs no previous episode) measure, did not predict HDRS-17 total score or response and remission35–38,42,44 but was associated with time to recurrence45,46 (Table 2).

Although measures of duration of current depressive episode and number of previous episodes provide information about the duration of the patient’s illness, they do not address time to first treatment of depression, as study patients may have been treated in previous episodes. Several studies were specifically designed to assess duration of untreated depression (Table 3). In these studies, duration of untreated illness—the interval between the onset of the patient’s first depressive episode and appropriate treatment—significantly predicted response,48 remission,48,49 and time to remission.47 A systematic review and meta-analysis designed to assess the relationship between clinical outcomes and duration of untreated illness reported a positive effect of shorter duration of untreated illness on both response to treatment (RR = 1.70; only 2 studies reported data on this) and remission (RR = 1.65; 3 studies).92 Duration of untreated episode (for patients who had multiple episodes) was also examined, but methodological issues limited conclusions for that measure. Taken together, studies assessing baseline measures related to time to treatment generally suggest that recognizing depression early and ideally treating during the first episode may substantially improve outcomes in patients treated for MDD. When optimal treatment is delayed—by failing to diagnose and begin treatment early in the course of the depressive episode—the likelihood of optimal outcome may decline.

Time to remission. Patient outcomes over the course of the 4 treatment steps in STAR*D provide evidence that early remission benefits the patient, not only by reducing the duration of depressive symptoms, but also by giving the patient the best chance for functional recovery. In the STAR*D trial,93,94 patients who had minimal response to treatment, defined as < 15% reduction in QIDS–Clinician Rating (QIDS-C-16) score by week 6 or < 25% reduction by week 9, or could not tolerate the assigned treatment at each treatment step could move to a successive treatment step (augmentation with or switch to a new antidepressant drug or cognitive therapy). Patients could enter up to 5 treatment steps, with remission rates reported for the first 4.94 Progressively lower remission rates were observed for each successive treatment step (step 1, 37%; step 2, 31%; step 3, 14%; step 4, 13%).94 Further, STAR*D patients who remitted during the first treatment step had greater improvements in function and hours of work missed on the basis of Work Productivity and Activity Impairment95 (WPAI) scores compared with patients who had partial or nonresponse to first-step treatment.15 However, among patients who did not achieve remission with step 1 treatment and who entered a second treatment step, remission in step 2 was not associated with greater functional improvement: improvements in function for patients who remitted at step 2, after a treatment switch, were similar to those for step 2 nonresponders.15 This finding underscores the idea that effective treatment in the first, early steps in MDD management has the greatest potential for bringing the patient to full functional recovery.96

Although the STAR*D findings suggest that patients who receive an effective treatment (one that will eventually bring them to remission) earlier in their course of illness are likely to have better functional outcomes, that supposition is not addressed directly. STAR*D patients who entered successive treatment steps differed from those who remitted in step 1 in that they had both a longer overall duration of treatment and at least 1 failed treatment trial prior to achieving remission.94,97 Would reducing the amount of time on the ineffective treatment by making a treatment change earlier improve outcomes for those patients who needed a second treatment step? Romera and colleagues98 addressed this question by comparing outcomes at week 16 in nonresponders who were switched from escitalopram to duloxetine at week 4 versus week 8. Although week 16 HDRS-17 remission rates and pain scale scores were similar between those switched early versus late (duloxetine effectively treated symptoms in both groups), a significantly greater percentage of patients who were switched at week 4 returned to normal function (on the basis of SDS scores) and did so earlier in treatment compared with those who were switched later.98

How rapidly can treatment be optimized? Practice guidelines from the American Psychiatric Association34 suggest that an adequate trial of an antidepressant treatment is up to 8 weeks of treatment, but the Canadian Network for Mood and Anxiety Treatments clinical guidelines24 state that decisions about the effectiveness of an antidepressant drug and the necessity for adjustments to treatment could be made earlier, within as few as 1 to 4 weeks of starting treatment in some patients. Numerous studies50–63 have examined the relationship between early improvement in symptoms and eventual outcomes in patients treated for MDD. Early improvement, most commonly defined as a 20% decrease from baseline in depression rating scale score, has been assessed at various time points between 1 and 4 weeks of treatment. The 2-week time point is the one most commonly used for defining early improvement55; however, several of the studies41,44,50–62 reviewed here assessed early improvement at week 2 and/or other time points. Achievement of a threshold level of improvement at the early time point was then evaluated as a predictor of treatment outcome at study end (4–12 weeks). Depression rating scales (HDRS-17, MADRS, or BDI) have been used to measure both early improvement and treatment outcomes. Response (≥ 50% decrease from baseline) and remission (HDRS-17 total score ≤ 7, MADRS total score ≤ 10, BDI total score ≤ 11) at study end point are the treatment outcomes that have been examined most frequently.

Early improvement, in almost all studies,41,44,50–62 predicted treatment response and remission of MDD symptoms at study end point (Table 4). The results were similar across treatments (SSRIs, SNRIs, TCAs, and other antidepressant drugs).41,44,50–61,63 Lack of early improvement (with improvement defined as ≥ 25% decrease in MADRS) within 2 weeks was highly predictive of eventual failure to achieve MADRS response or remission (negative predictive value) in a pooled analysis of 5 studies58 utilizing combined olanzapine/fluoxetine treatment in patients with treatment-resistant depression. In fact, lack of early improvement was a better predictor of week 8 outcome than was achievement of early improvement.58 Lack of early improvement was also the better predictor of outcome in a pooled analysis of data from 6 studies utilizing desvenlafaxine versus placebo.58,63 In studies41,59,63 using ROC analysis to determine threshold cutoff values for early improvement, optimal week 2 improvement thresholds for predicting eventual positive treatment outcomes ranged from approximately 20%–40% improvement from baseline.

Early improvement analyses similar to those using depression symptom outcomes have examined whether early improvements in depression symptom or function scores predict positive functional outcomes (Table 5). In an observational study44 of patients treated for MDD, response or remission at week 6 was significantly associated with improvement in Social and Occupational Functioning Assessment Scale scores at month 12 compared with nonresponse or lack of remission, respectively. Early response was also significantly associated with better quality of life scores.44 In a placebo-controlled trial64 utilizing desvenlafaxine, week 2 improvement in depression scale (HDRS-17) total score was a significant predictor of improvement on a range of measures of function at week 12, including HDRS-17 psychomotor retardation factor, MADRS lassitude item, SDS total score, and several measures from the WPAI (presenteeism, work productivity loss, and activity impairment). The association between early improvement in function and functional and depression outcomes at study end was explored in a pooled analysis40 of 7 double-blind, placebo-controlled trials of desvenlafaxine. Functional response, functional/depression response, functional remission, and functional/depression remission at week 8 were all significantly predicted by early functional improvement, as measured by percentage decrease in SDS total score at week 2. The percentage change in SDS total score at week 2 that best predicted functional remission was 26%.40

While a growing literature has demonstrated that, on average, early symptomatic or functional improvement is an indication that continued improvement on this treatment is likely—and conversely that the lack of early improvement may signal that the treatment will not be effective for this patient—it is important to remember that response trajectories can vary considerably among individual patients. Studies such as a secondary analysis of data from the Genome-Based Therapeutic Drugs for Depression (GENDEP) study revealed that “both early and delayed improvement are common during treatment with SSRIs and TCAs. Among those who eventually show good response to a 12-week course of antidepressant treatment, 51% show delayed response, which cannot be predicted from measurements in the first 2 weeks.”60(p1482) The GENDEP results underscore the fact that, although evaluating early progress is critical to rapid treatment optimization, decisions about changes to a treatment plan must be made on a case-by-case basis, as ending an antidepressant trial based on strict criteria (eg, 20% improvement at 2 weeks) would be premature for many patients.60

CLINICAL IMPLICATIONS AND CONCLUSIONS: PROVIDING EARLY OPTIMIZED TREATMENT FOR THE INDIVIDUAL PATIENT

Evidence reviewed here indicates that the greatest potential for achieving full functional recovery from depression lies in early diagnosis and rapid implementation of optimal treatment (early optimized treatment). Analysis of clinical trial data shows that a delay between onset of symptoms and starting antidepressant treatment (longer duration of untreated episode or longer duration of untreated illness) is associated with poorer efficacy outcomes, and that reducing the time to treatment improvement is associated with better functional outcomes. More rapid optimization is possible in treatment of depression: early improvement, or lack of improvement, can be used to assess the effectiveness of a treatment as early as 2 weeks in order to ensure that the dose is optimized as early as possible.

Screening and early diagnosis, development of specific and targeted treatment goals, treatment selection, and assessment of improvement early in the course of treatment with subsequent adjustment in treatment if required are all critical factors in providing the best treatment for the individual patient. Primary care practitioners have the first opportunity to screen for, diagnose, and treat MDD.99 By intercepting and optimally treating depression earlier, there is potential to reduce, sometimes by many years, the substantial morbidity, mortality, and functional impairment associated with this illness. Patient self-report instruments such as the PHQ-9,100 for evaluating symptoms of depression, and the SDS, for assessing function, can be used efficiently in clinical practice for patients presenting with symptoms of depression, individuals at high risk, or those with common comorbid conditions.1,101,102 Diagnosing a young patient early in the course of his or her first depressive episode and treating to full symptomatic remission and full functioning (symptomatic and functional recovery), ideally with no residual symptoms, offers the greatest chance of success for best possible quality of life.

Ideal management of MDD should include assessment of both depressive symptoms and function at baseline utilizing rating scales (measurement-based care). The patient’s symptoms, associated functional impairment, and comorbidities, among other potential factors (summarized in Table 6), should be considered in the selection of an effective, well-tolerated treatment with minimal side effects. On average, the efficacy of antidepressants is similar, among and within classes25,103,104; however, for individual patients, there may be important efficacy and tolerability differences between drugs.23,104–108 Effective long-term treatment of MDD often involves maintenance therapy for at least 6 to 24 months after remission.1,24 Therefore, consideration of possible barriers to both short-term and long-term adherence (poor tolerability, which in itself can contribute to functional impairment; delayed onset of efficacy; suboptimal, incompletely effective dosage; and complicated dosing regimen109–113) is critical to treatment selection. A review of patients’ personal barriers to adherence may also be helpful.

Finally, monitoring for early improvement during treatment is critical to ensuring that patients do not remain on ineffective treatment, increasing the likelihood of residual symptoms, which can result in a delay in full functional recovery and an increased risk for relapse or recurrence. Clinicians should monitor patients’ response to treatment using tools to assess both symptoms and functioning.114 Although the trajectory of response to treatment varies widely with most studies showing approximately 10% of patients without early improvement may eventually remit without a change in treatment (based on ROC analyses), patients whose symptoms do improve early have the greatest likelihood of achieving the best clinical outcomes.51,63 Patients slow to improve should be followed closely so that necessary treatment adjustments can be made early to minimize the negative impact on functioning in all aspects of life. The need for psychotherapy (including behavioral activation), which can be critical for achieving full functional recovery, should also be assessed. Early optimized treatment can substantially improve patients’ chances of a timely and long-lasting return to best possible functioning.

Submitted: December 23, 2015; accepted June 30, 2016.

Published online: September 1, 2016.

Drug names: aripiprazole (Abilify), citalopram (Celexa and others), desvenlafaxine (Pristiq, Khedezla, and others), duloxetine (Cymbalta), escitalopram (Lexapro and others), fluoxetine (Prozac and others), fluvoxamine (Luvox and others), mirtazapine (Remeron and others), nortriptyline (Pamelor, Aventyl, and others), olanzapine/fluoxetine (Symbyax and others), paroxetine (Paxil, Pexeva, and others), venlafaxine (Effexor and others).

Potential conflicts of interest: Dr Habert has served on advisory boards or speakers bureaus for Bristol-Myers Squibb, Pfizer, Eli Lilly, Bayer, Lundbeck, Amgen, Boehringer Ingelheim, AstraZeneca, Astellas, Purdue, Janssen-Ortho, and Novo Nordisk. Dr Katzman has served on advisory boards for GlaxoSmithKline, Lundbeck, Eli Lilly, Boehringer Ingelheim, Organon, AstraZeneca, Janssen-Ortho, Solvay, Bristol-Myers Squibb, Shire, Sunovion, Pfizer, Purdue, Merck, Astellas, Bedrocan, and Tweed; has received research funding from Canadian Institutes of Health Research, Sick Kids Foundation, Centre for Addiction and Mental Health Foundation, Canadian Psychiatric Research Foundation, Canadian Foundation for Innovation, Lotte & John Hecht Memorial Foundation, Genuine Health, GlaxoSmithKline, Lundbeck, Eli Lilly, Organon, AstraZeneca, Janssen-Ortho, Solvay, Takeda, Bristol-Myers Squibb, Shire, Pfizer, Purdue, Astellas, Hoffman La Roche, Biotics, Forest, Actavis, Tweed, and Allergan; and has received honoraria or other fees from AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, Forest Genuine Health, GlaxoSmithKline, Janssen-Ortho, Lundbeck, Organon, Pfizer, Purdue, Shire, Solvay, Forest, Actavis, Allergan, and Bedrocan. Dr Oluboka has served on advisory boards and speakers bureaus for Bristol-Myers Squibb, Otsuka, Janssen, Pfizer, Sunovion, Lundbeck, and Eli Lilly and has received honoraria from AstraZeneca, and Sunovion. Dr McIntyre has served on advisory boards for and received speaker’s fees from Lundbeck, Pfizer, AstraZeneca, Eli Lilly, Janssen-Ortho, Purdue, Johnson & Johnson, Moksha8, Sunovion, Mitsubishi, Takeda, Forest, Otsuka, Bristol-Myers Squibb, and Shire and has received research funding from Lundbeck, Janssen-Ortho, Shire, Purdue, AstraZeneca, Pfizer, Otsuka, Allergan, and Stanley Medical Research Institute. Dr McIntosh has acted as a presenter for, participated on an advisory board for, and/or received research funding from Eli Lilly, Pfizer, Janssen, Shire, Purdue, Allergan, Sunovion, Otsuka, Lundbeck, and Bristol-Myers Squibb. Dr MacQueen has served on advisory boards or acted as a speaker for Pfizer, Janssen, Eli Lilly, and Lundbeck. Dr Khullar has acted as a presenter for, participated on an advisory board for, and/or received research funding from Sunovion, Otsuka, Bristol-Myers Squibb, Pfizer, Lundbeck, Eli Lilly, Shire, Purdue, Janssen-Ortho, Paladin, Valeant, Merck, and AstraZeneca. Dr Milev has received grant/research support from Canadian Institutes of Health Research, Ontario Mental Health Foundation, Ontario Problem Gambling Research Center, Ontario Brain Institute, and Canadian Biomarker Integration Network in Depression and has served on speakers bureaus for and received honoraria from AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen, Lundbeck, Otsuka, Pfizer, Servier, Shire, and Wyeth. Dr Kjernisted has acted as a presenter for, participated on an advisory board for, and/or received research funding from GlaxoSmithKline, Hoffman-La Roche, Lundbeck, Eli Lilly, Boehringer Ingelheim, Organon, AstraZeneca, Janssen-Ortho, Servier, Solvay, Bristol-Myers Squibb, Otsuka, Shire, Sunovion, Pfizer, Purdue, Wyeth, and Brain Cells Inc. Dr Kennedy has acted as a presenter for, participated on an advisory board for, and/or received research funding from Allergan, AstraZeneca, Bristol-Myers Squibb, Brain Cells Inc, Brain Canada, Clera, Eli Lilly, Janssen, Lundbeck, Lundbeck Institute, Ontario Mental Health Foundation, Pfizer, Servier, St Jude Medical, and Sunovion. Dr Chokka reports no financial or other affiliations relevant to the subject of this article.

Funding/support: Pfizer provided funding for medical writing support.

Role of the sponsor: The sponsor participated in the review and approval of the manuscript.

Acknowledgments: Medical writing support was provided by Kathleen Dorries, PhD, at Peloton Advantage and was funded by Pfizer Inc.

REFERENCES

1. Patten SB, Kennedy SH, Lam RW, et al; Canadian Network for Mood and Anxiety Treatments (CANMAT). Canadian Network for Mood and Anxiety Treatments (CANMAT) clinical guidelines for the management of major depressive disorder in adults, I: classification, burden and principles of management. J Affect Disord. 2009;117
(suppl 1):S5–S14. doi:10.1016/j.jad.2009.06.044 PubMed

2. Vuorilehto MS, Melartin TK, Isometsä ET. Course and outcome of depressive disorders in primary care: a prospective 18-month study. Psychol Med. 2009;39(10):1697–1707. doi:10.1017/S0033291709005182 PubMed

3. Judd LL, Akiskal HS, Maser JD, et al. Major depressive disorder: a prospective study of residual subthreshold depressive symptoms as predictor of rapid relapse. J Affect Disord. 1998;50(2–3):97–108. doi:10.1016/S0165-0327(98)00138-4 PubMed

4. Depression. Fact sheet 369. World Health Organization Web site. http://www.who.int/mediacentre/factsheets/fs369/en/. Accessed June 11, 2015.

5. Kessler RC, Berglund P, Demler O, et al; National Comorbidity Survey Replication. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA. 2003;289(23):3095–3105. doi:10.1001/jama.289.23.3095 PubMed

6. Patten SB, Williams JV, Lavorato DH, et al. Descriptive epidemiology of major depressive disorder in Canada in 2012. Can J Psychiatry. 2015;60(1):23–30. PubMed

7. Kessler RC. Epidemiology of women and depression. J Affect Disord. 2003;74(1):5–13. doi:10.1016/S0165-0327(02)00426-3 PubMed

8. Global Burden of Disease 2013 Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386(9995):743–800. doi:10.1016/s0140-6736(15)60692-4 PubMed

9. World Health Organization. WHO calls for stronger focus on adolescent health. Road traffic injuries, HIV/AIDS, suicide are top causes of death; depression is number 1 cause of illness and disability. Cent Eur J Public Health. 2014;22(2):139. PubMed

10. Greer TL, Kurian BT, Trivedi MH. Defining and measuring functional recovery from depression. CNS Drugs. 2010;24(4):267–284. doi:10.2165/11530230-000000000-00000 PubMed

11. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Fifth Edition. Arlington, VA: American Psychiatric Publishing; 2013.

12. Simon GE, Revicki D, Heiligenstein J, et al. Recovery from depression, work productivity, and health care costs among primary care patients. Gen Hosp Psychiatry. 2000;22(3):153–162. doi:10.1016/S0163-8343(00)00072-4 PubMed

13. Druss BG, Rosenheck RA, Sledge WH. Health and disability costs of depressive illness in a major US corporation. Am J Psychiatry. 2000;157(8):1274–1278. doi:10.1176/appi.ajp.157.8.1274 PubMed

14. Mauskopf JA, Simon GE, Kalsekar A, et al. Nonresponse, partial response, and failure to achieve remission: humanistic and cost burden in major depressive disorder. Depress Anxiety. 2009;26(1):83–97. doi:10.1002/da.20505 PubMed

15. Trivedi MH, Morris DW, Wisniewski SR, et al. Increase in work productivity of depressed individuals with improvement in depressive symptom severity. Am J Psychiatry. 2013;170(6):633–641. doi:10.1176/appi.ajp.2012.12020250 PubMed

16. Jain G, Roy A, Harikrishnan V, et al. Patient-reported depression severity measured by the PHQ-9 and impact on work productivity: results from a survey of full-time employees in the United States. J Occup Environ Med. 2013;55(3):252–258. doi:10.1097/JOM.0b013e31828349c9 PubMed

17. Tollefson GD, Souetre E, Thomander L, et al. Comorbid anxious signs and symptoms in major depression: impact on functional work capacity and comparative treatment outcomes. Int Clin Psychopharmacol. 1993;8(4):281–293. doi:10.1097/00004850-199300840-00013 PubMed

18. Kessler RC, Akiskal HS, Ames M, et al. Prevalence and effects of mood disorders on work performance in a nationally representative sample of US workers. Am J Psychiatry. 2006;163(9):1561–1568. doi:10.1176/ajp.2006.163.9.1561 PubMed

19. Mojtabai R. Unmet need for treatment of major depression in the United States. Psychiatr Serv. 2009;60(3):297–305. doi:10.1176/ps.2009.60.3.297 PubMed

20. Cepoiu M, McCusker J, Cole MG, et al. Recognition of depression by non-psychiatric physicians—a systematic literature review and meta-analysis. J Gen Intern Med. 2008;23(1):25–36. doi:10.1007/s11606-007-0428-5 PubMed

21. Mitchell AJ, Vaze A, Rao S. Clinical diagnosis of depression in primary care: a meta-analysis. Lancet. 2009;374(9690):609–619. doi:10.1016/S0140-6736(09)60879-5 PubMed

22. Thase ME, Haight BR, Richard N, et al. Remission rates following antidepressant therapy with bupropion or selective serotonin reuptake inhibitors: a meta-analysis of original data from 7 randomized controlled trials. J Clin Psychiatry. 2005;66(8):974–981. doi:10.4088/JCP.v66n0803 PubMed

23. Machado M, Iskedjian M, Ruiz I, et al. Remission, dropouts, and adverse drug reaction rates in major depressive disorder: a meta-analysis of head-to-head trials. Curr Med Res Opin. 2006;22(9):1825–1837. doi:10.1185/030079906X132415 PubMed

24. Lam RW, Kennedy SH, Grigoriadis S, et al; Canadian Network for Mood and Anxiety Treatments (CANMAT). Canadian Network for Mood and Anxiety Treatments (CANMAT) clinical guidelines for the management of major depressive disorder in adults, III: pharmacotherapy. J Affect Disord. 2009;117(suppl 1):S26–S43. doi:10.1016/j.jad.2009.06.041 PubMed

25. Work Group on Major Depressive Disorder. Practice guideline for the treatment of patients with major depressive disorder. 3rd ed. Arlington, VA: American Psychiatric Association; 2010:1–152. PsychiatryOnline Web site. http://www.psychiatryonline.com/pracGuide/pracGuideTopic_7.aspx. Accessed February 1, 2012.

26. Möller HJ. Outcomes in major depressive disorder: the evolving concept of remission and its implications for treatment. World J Biol Psychiatry. 2008;9(2):102–114. doi:10.1080/15622970801981606 PubMed

27. Sheehan DV, Harnett-Sheehan K, Spann ME, et al. Assessing remission in major depressive disorder and generalized anxiety disorder clinical trials with the discan metric of the Sheehan Disability Scale. Int Clin Psychopharmacol. 2011;26(2):75–83. doi:10.1097/YIC.0b013e328341bb5f PubMed

28. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56–62. doi:10.1136/jnnp.23.1.56 PubMed

29. Sheehan DV, Harnett-Sheehan K, Raj BA. The measurement of disability. Int Clin Psychopharmacol. 1996;11(suppl 3):89–95. doi:10.1097/00004850-199606003-00015 PubMed

30. Hirschfeld RM, Dunner DL, Keitner G, et al. Does psychosocial functioning improve independent of depressive symptoms? a comparison of nefazodone, psychotherapy, and their combination. Biol Psychiatry. 2002;51(2):123–133. doi:10.1016/S0006-3223(01)01291-4 PubMed

31. van der Voort TY, Seldenrijk A, van Meijel B, et al. Functional versus syndromal recovery in patients with major depressive disorder and bipolar disorder. J Clin Psychiatry. 2015;76(6):e809–e814. doi:10.4088/JCP.14m09548 PubMed

32. American Psychiatric Association. Practice guideline for the treatment of patients with major depressive disorder (revision). Am J Psychiatry. 2000;157(suppl 4):1–45. PubMed

33. Qaseem A, Snow V, Denberg TD, et al; Clinical Efficacy Assessment Subcommittee of American College of Physicians. Using second-generation antidepressants to treat depressive disorders: a clinical practice guideline from the American College of Physicians. Ann Intern Med. 2008;149(10):725–733. doi:10.7326/0003-4819-149-10-200811180-00007 PubMed

34. Gelenberg AJ, Freeman MP, Markowitz JC, et al. Practice Guideline for the Treatment of Patients With Major Depressive Disorder. American Psychiatric Association Web site. http://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf. Accessed March 24, 2015.

35. Trivedi MH, Rush AJ, Wisniewski SR, et al; STAR*D Study Team. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163(1):28–40. doi:10.1176/appi.ajp.163.1.28 PubMed

36. Howland RH, Wilson MG, Kornstein SG, et al. Factors predicting reduced antidepressant response: experience with the SNRI duloxetine in patients with major depression. Ann Clin Psychiatry. 2008;20(4):209–218. doi:10.1080/10401230802437639 PubMed

37. Fava M, Wiltse C, Walker D, et al. Predictors of relapse in a study of duloxetine treatment in patients with major depressive disorder. J Affect Disord. 2009;113(3):263–271. doi:10.1016/j.jad.2008.05.023 PubMed

38. Hennings JM, Owashi T, Binder EB, et al. Clinical characteristics and treatment outcome in a representative sample of depressed inpatients—findings from the Munich Antidepressant Response Signature (MARS) project. J Psychiatr Res. 2009;43(3):215–229. doi:10.1016/j.jpsychires.2008.05.002 PubMed

39. Seemüller F, Riedel M, Obermeier M, et al. Outcomes of 1,014 naturalistically treated inpatients with major depressive episode. Eur Neuropsychopharmacol. 2010;20(5):346–355. doi:10.1016/j.euroneuro.2009.11.011 PubMed

40. Soares CN, Endicott J, Boucher M, et al. Predictors of functional response and remission with desvenlafaxine 50 mg/d in patients with major depressive disorder. CNS Spectr. 2014;19(6):519–527. doi:10.1017/S1092852914000066 PubMed

41. Joel I, Begley AE, Mulsant BH, et al; IRL GREY Investigative Team. Dynamic prediction of treatment response in late-life depression. Am J Geriatr Psychiatry. 2014;22(2):167–176. doi:10.1016/j.jagp.2012.07.002 PubMed

42. Smagula SF, Butters MA, Anderson SJ, et al. Antidepressant response trajectories and associated clinical prognostic factors among older adults. JAMA Psychiatry. 2015;72(10):1021–1028. doi:10.1001/jamapsychiatry.2015.1324 PubMed

43. McGrath PJ, Stewart JW, Quitkin FM, et al. Predictors of relapse in a prospective study of fluoxetine treatment of major depression. Am J Psychiatry. 2006;163(9):1542–1548. doi:10.1176/ajp.2006.163.9.1542 PubMed

44. Ciudad A, Álvarez E, Roca M, et al. Early response and remission as predictors of a good outcome of a major depressive episode at 12-month follow-up: a prospective, longitudinal, observational study. J Clin Psychiatry. 2012;73(2):185–191. doi:10.4088/JCP.10m06314 PubMed

45. Hardeveld F, Spijker J, De Graaf R, et al. Recurrence of major depressive disorder across different treatment settings: results from the NESDA study. J Affect Disord. 2013;147(1–3):225–231. doi:10.1016/j.jad.2012.11.008 PubMed

46. Hardeveld F, Spijker J, De Graaf R, et al. Recurrence of major depressive disorder and its predictors in the general population: results from the Netherlands Mental Health Survey and Incidence Study (NEMESIS). Psychol Med. 2013;43(1):39–48. doi:10.1017/S0033291712002395 PubMed

47. Gormley N, O’Leary D, Costello F. First admissions for depression: is the ‘no-treatment interval’ a critical predictor of time to remission? J Affect Disord. 1999;54(1–2):49–54. doi:10.1016/S0165-0327(98)00133-5 PubMed

48. Okuda A, Suzuki T, Kishi T, et al. Duration of untreated illness and antidepressant fluvoxamine response in major depressive disorder. Psychiatry Clin Neurosci. 2010;64(3):268–273. doi:10.1111/j.1440-1819.2010.02091.x PubMed

49. Bukh JD, Bock C, Vinberg M, et al. The effect of prolonged duration of untreated depression on antidepressant treatment outcome. J Affect Disord. 2013;145(1):42–48. doi:10.1016/j.jad.2012.07.008 PubMed

50. Koran LM, Hamilton SH, Hertzman M, et al. Predicting response to fluoxetine in geriatric patients with major depression. J Clin Psychopharmacol. 1995;15(6):421–427. doi:10.1097/00004714-199512000-00006 PubMed

51. Szegedi A, Müller MJ, Anghelescu I, et al. Early improvement under mirtazapine and paroxetine predicts later stable response and remission with high sensitivity in patients with major depression. J Clin Psychiatry. 2003;64(4):413–420. doi:10.4088/JCP.v64n0410 PubMed

52. Henkel V, Seemüller F, Obermeier M, et al. Does early improvement triggered by antidepressants predict response/remission? analysis of data from a naturalistic study on a large sample of inpatients with major depression. J Affect Disord. 2009;115(3):439–449. doi:10.1016/j.jad.2008.10.011 PubMed

53. Katz MM, Meyers AL, Prakash A, et al. Early symptom change prediction of remission in depression treatment. Psychopharmacol Bull. 2009;42(1):94–107. PubMed

54. Kok RM, van Baarsen C, Nolen WA, et al. Early response as predictor of final remission in elderly depressed patients. Int J Geriatr Psychiatry. 2009;24(11):1299–1303. doi:10.1002/gps.2261 PubMed

55. Szegedi A, Jansen WT, van Willigenburg AP, et al. Early improvement in the first 2 weeks as a predictor of treatment outcome in patients with major depressive disorder: a meta-analysis including 6,562 patients. J Clin Psychiatry. 2009;70(3):344–353. doi:10.4088/JCP.07m03780 PubMed

56. Farabaugh A, Sonawalla S, Johnson DP, et al. Early improvements in anxiety, depression, and anger/hostility symptoms and response to antidepressant treatment. Ann Clin Psychiatry. 2010;22(3):166–171. PubMed

57. Farabaugh AH, Bitran S, Witte J, et al. Anxious depression and early changes in the HAMD-17 anxiety-somatization factor items and antidepressant treatment outcome. Int Clin Psychopharmacol. 2010;25(4):214–217. doi:10.1097/YIC.0b013e328339fbbd PubMed

58. Tohen M, Case M, Trivedi MH, et al. Olanzapine/fluoxetine combination in patients with treatment-resistant depression: rapid onset of therapeutic response and its predictive value for subsequent overall response in a pooled analysis of 5 studies. J Clin Psychiatry. 2010;71(4):451–462. doi:10.4088/JCP.08m04984gre PubMed

59. Lin CH, Lane HY, Chen CC, et al. Early prediction of fluoxetine response for Han Chinese inpatients with major depressive disorder. J Clin Psychopharmacol. 2011;31(2):187–193. doi:10.1097/JCP.0b013e318210856f PubMed

60. Uher R, Mors O, Rietschel M, et al. Early and delayed onset of response to antidepressants in individual trajectories of change during treatment of major depression: a secondary analysis of data from the Genome-Based Therapeutic Drugs for Depression (GENDEP) study. J Clin Psychiatry. 2011;72(11):1478–1484. doi:10.4088/JCP.10m06419 PubMed

61. Casey DE, Laubmeier KK, Marler SV, et al. Efficacy of adjunctive aripiprazole in major depressive disorder: a pooled response quartile analysis and the predictive value of week 2 early response. Prim Care Companion CNS Disord. 2012;14(3):doi:10.4088/PCC.11m01251.doi:10.4088/pcc.11m01251 PubMed

62. Mikoteit T, Beck J, Eckert A, et al. High baseline BDNF serum levels and early psychopathological improvement are predictive of treatment outcome in major depression. Psychopharmacology (Berl). 2014;231(15):2955–2965. doi:10.1007/s00213-014-3475-8 PubMed

63. Soares CN, Fayyad RS, Guico-Pabia CJ. Early improvement in depressive symptoms with desvenlafaxine 50 mg/d as a predictor of treatment success in patients with major depressive disorder. J Clin Psychopharmacol. 2014;34(1):57–65. doi:10.1097/JCP.0000000000000049 PubMed

64. Lam RW, Endicott J, Hsu MA, et al. Predictors of functional improvement in employed adults with major depressive disorder treated with desvenlafaxine. Int Clin Psychopharmacol. 2014;29(5):239–251. doi:10.1097/YIC.0000000000000031 PubMed

65. Ballenger JC. Clinical guidelines for establishing remission in patients with depression and anxiety. J Clin Psychiatry. 1999;60(suppl 22):29–34. PubMed

66. Keller MB. Past, present, and future directions for defining optimal treatment outcome in depression: remission and beyond. JAMA. 2003;289(23):3152–3160. doi:10.1001/jama.289.23.3152 PubMed

67. Frank E, Prien RF, Jarrett RB, et al. Conceptualization and rationale for consensus definitions of terms in major depressive disorder: remission, recovery, relapse, and recurrence. Arch Gen Psychiatry. 1991;48(9):851–855. doi:10.1001/archpsyc.1991.01810330075011 PubMed

68. Zimmerman M, Posternak MA, Chelminski I. Derivation of a definition of remission on the Montgomery-Asberg depression rating scale corresponding to the definition of remission on the Hamilton Rating Scale for Depression. J Psychiatr Res. 2004;38(6):577–582. doi:10.1016/j.jpsychires.2004.03.007 PubMed

69. Rush AJ, Trivedi MH, Ibrahim HM, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), Clinician Rating (QIDS-C), and Self-Report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003;54(5):573–583. doi:10.1016/S0006-3223(02)01866-8 PubMed

70. Kroenke K, Spitzer RL. The PHQ-9: a new depression diagnostic and severity measure. Psychiatr Ann. 2002;32(9):1–7. doi:10.3928/0048-5713-20020901-06

71. Nierenberg AA, Husain MM, Trivedi MH, et al. Residual symptoms after remission of major depressive disorder with citalopram and risk of relapse: a STAR*D report. Psychol Med. 2010;40(1):41–50. doi:10.1017/S0033291709006011 PubMed

72. Zajecka J, Kornstein SG, Blier P. Residual symptoms in major depressive disorder: prevalence, effects, and management. J Clin Psychiatry. 2013;74(4):407–414. doi:10.4088/JCP.12059ah1 PubMed

73. ten Doesschate MC, Bockting CL, Koeter MW, et al; DELTA Study Group. Prediction of recurrence in recurrent depression: a 5.5-year prospective study. J Clin Psychiatry. 2010;71(8):984–991. doi:10.4088/JCP.08m04858blu PubMed

74. Roca M, García-Toro M, García-Campayo J, et al. Clinical differences between early and late remission in depressive patients. J Affect Disord. 2011;134(1–3):235–241. doi:10.1016/j.jad.2011.05.051 PubMed

75. Dennehy EB, Marangell LB, Martinez J, et al. Clinical and functional outcomes of patients who experience partial response to citalopram: secondary analysis of STAR*D. J Psychiatr Pract. 2014;20(3):178–187. doi:10.1097/01.pra.0000450317.76117.62 PubMed

76. Rush AJ. Distinguishing functional from syndromal recovery: implications for clinical care and research. J Clin Psychiatry. 2015;76(6):e832–e834. doi:10.4088/JCP.15com09859 PubMed

77. McIntyre RS, Lee Y, Mansur RB. Treating to target in major depressive disorder: response to remission to functional recovery. CNS Spectr. 2015;20(s1):17–31. doi:10.1017/S1092852915000826

78. McKnight PE, Kashdan TB. The importance of functional impairment to mental health outcomes: a case for reassessing our goals in depression treatment research. Clin Psychol Rev. 2009;29(3):243–259. doi:10.1016/j.cpr.2009.01.005 PubMed

79. Zimmerman M, Martinez JA, Attiullah N, et al. Why do some depressed outpatients who are in remission according to the Hamilton Depression Rating Scale not consider themselves to be in remission? J Clin Psychiatry. 2012;73(6):790–795. doi:10.4088/JCP.11m07203 PubMed

80. Zimmerman M, McGlinchey JB, Posternak MA, et al. How should remission from depression be defined? the depressed patient’s perspective. Am J Psychiatry. 2006;163(1):148–150. doi:10.1176/appi.ajp.163.1.148 PubMed

81. Endicott J, Nee J, Harrison W, et al. Quality of Life Enjoyment and Satisfaction Questionnaire: a new measure. Psychopharmacol Bull. 1993;29(2):321–326. PubMed

82. Ware JE Jr, Sherbourne CD. The MOS 36-item Short-Form Health Survey (SF-36), I: conceptual framework and item selection. Med Care. 1992;30(6):473–483. doi:10.1097/00005650-199206000-00002 PubMed

83. Ware J Jr, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220–233. doi:10.1097/00005650-199603000-00003 PubMed

84. Lam RW, Michalak EE, Yatham LN. A new clinical rating scale for work absence and productivity: validation in patients with major depressive disorder. BMC Psychiatry. 2009;9(1):78. doi:10.1186/1471-244X-9-78 PubMed

85. Weissman MM, Bothwell S. Assessment of social adjustment by patient self-report. Arch Gen Psychiatry. 1976;33(9):1111–1115. doi:10.1001/archpsyc.1976.01770090101010 PubMed

86. Endicott J, Dorries KM. Functional outcomes in MDD: established and emerging assessment tools. Am J Manag Care. 2009;15(suppl 11):
S328–S334. PubMed

87. Langlieb AM, Guico-Pabia CJ. Beyond symptomatic improvement: assessing real-world outcomes in patients with major depressive disorder. Prim Care Companion J Clin Psychiatry. 2010;12(2): e1–e14. doi:10.4088/pcc.09r00826blu PubMed

88. Guico-Pabia CJ, Fayyad RS, Soares CN. Assessing the relationship between functional impairment/recovery and depression severity: a pooled analysis. Int Clin Psychopharmacol. 2012;27(1):1–7. doi:10.1097/YIC.0b013e32834c2488 PubMed

89. Bijl MJ, Visser LE, Hofman A, et al. Influence of the CYP2D6*4 polymorphism on dose, switching and discontinuation of antidepressants. Br J Clin Pharmacol. 2008;65(4):558–564. doi:10.1111/j.1365-2125.2007.03052.x PubMed

90. Buffum MD, Buffum JC. The psychopharmacologic treatment of depression in elders. Geriatr Nurs. 1997;18(4):144–149. doi:10.1016/S0197-4572(97)90039-2 PubMed

91. Diler RS, Avci A. Selective serotonin reuptake inhibitors in children and adolescents. Swiss Med Wkly. 2002;132(33–34):470–477. PubMed

92. Ghio L, Gotelli S, Marcenaro M, et al. Duration of untreated illness and outcomes in unipolar depression: a systematic review and meta-analysis. J Affect Disord. 2014;152–154:45–51. doi:10.1016/j.jad.2013.10.002 PubMed

93. Rush AJ, Fava M, Wisniewski SR, et al; STAR*D Investigators Group. Sequenced treatment alternatives to relieve depression (STAR*D): rationale and design. Control Clin Trials. 2004;25(1):119–142. doi:10.1016/S0197-2456(03)00112-0 PubMed

94. Rush AJ, Trivedi MH, Wisniewski SR, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905–1917. doi:10.1176/ajp.2006.163.11.1905 PubMed

95. Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics. 1993;4(5):353–365. doi:10.2165/00019053-199304050-00006 PubMed

96. Greden JF. Workplace depression: personalize, partner, or pay the price. Am J Psychiatry. 2013;170(6):578–581. doi:10.1176/appi.ajp.2012.13030382 PubMed

97. Fava M, Alpert JE, Carmin CN, et al. Clinical correlates and symptom patterns of anxious depression among patients with major depressive disorder in STAR*D. Psychol Med. 2004;34(7):1299–1308. doi:10.1017/S0033291704002612 PubMed

98. Romera I, Pérez V, Menchón JM, et al. Early vs conventional switching of antidepressants in patients with MDD and moderate to severe pain: a double-blind randomized study. J Affect Disord. 2012;143(1–3):47–55. doi:10.1016/j.jad.2012.05.024 PubMed

99. MacMillan HL, Patterson CJ, Wathen CN, et al; Canadian Task Force on Preventive Health Care. Screening for depression in primary care: recommendation statement from the Canadian Task Force on Preventive Health Care. CMAJ. 2005;172(1):33–35. doi:10.1503/cmaj.1030823 PubMed

100. The Patient Health Questionnaire (PHQ) Screeners. www.phqscreeners.com. Accessed August 2, 2016.

101. Cameron C, Habert J, Anand L, et al. Optimizing the management of depression: primary care experience. Psychiatry Res. 2014;220(suppl 1):S45–S57. doi:10.1016/S0165-1781(14)70005-8 PubMed

102. Culpepper L. Functional impairment and improvement in depression. CME Institute Web site. http://www.cmeinstitute.com/Psychlopedia/Pages/depression/26brmdd/sec2/section.aspx. Accessed December 1, 2015.

103. Schueler YB, Koesters M, Wieseler B, et al.
A systematic review of duloxetine and venlafaxine in major depression, including unpublished data. Acta Psychiatr Scand. 2011;123(4):247–265. doi:10.1111/j.1600-0447.2010.01599.x PubMed

104. Gartlehner G, Hansen RA, Morgan LC, et al. Comparative benefits and harms of second-generation antidepressants for treating major depressive disorder: an updated meta-analysis. Ann Intern Med. 2011;155(11):772–785. doi:10.7326/0003-4819-155-11-201112060-00009 PubMed

105. Gartlehner G, Thieda P, Hansen RA, et al. Comparative risk for harms of second-generation antidepressants: a systematic review and meta-analysis. Drug Saf. 2008;31(10):851–865. doi:10.2165/00002018-200831100-00004 PubMed

106. Gartlehner G, Gaynes BN, Hansen RA, et al. Comparative benefits and harms of second-generation antidepressants: background paper for the American College of Physicians. Ann Intern Med. 2008;149(10):734–750. doi:10.7326/0003-4819-149-10-200811180-00008 PubMed

107. Gartlehner G, Hansen RA, Carey TS, et al. Discontinuation rates for selective serotonin reuptake inhibitors and other second-generation antidepressants in outpatients with major depressive disorder: a systematic review and meta-analysis. Int Clin Psychopharmacol. 2005;20(2):59–69. doi:10.1097/00004850-200503000-00001 PubMed

108. Cipriani A, Furukawa TA, Salanti G, et al. Comparative efficacy and acceptability of 12 new-generation antidepressants: a multiple-treatments meta-analysis. Lancet. 2009;373(9665):746–758. doi:10.1016/S0140-6736(09)60046-5 PubMed

109. McGettigan P, Kelly A, Carvahlo M, et al. Antidepressants in primary care: analysis of treatment discontinuations. Pharmacoepidemiol Drug Saf. 2000;9(6):
521–528. doi:10.1002/1099-1557(200011)9:6<521::AID-PDS525>3.0.CO;2-K PubMed

110. Demyttenaere K. Risk factors and predictors of compliance in depression.
Eur Neuropsychopharmacol. 2003;
13(suppl 3):S69–S75. doi:10.1016/S0924-977X(03)00095-6 PubMed

111. Masand PS. Tolerability and adherence issues in antidepressant therapy. Clin Ther. 2003;25(8):2289–2304. doi:10.1016/S0149-2918(03)80220-5 PubMed

112. Burra TA, Chen E, McIntyre RS, et al. Predictors of self-reported antidepressant adherence. Behav Med. 2007;32(4):127–134. doi:10.3200/BMED.32.4.127-134 PubMed

113. Fortney JC, Pyne JM, Edlund MJ, et al. Reasons for antidepressant nonadherence among veterans treated in primary care clinics. J Clin Psychiatry. 2011;72(6):
827–834. doi:10.4088/JCP.09m05528blu PubMed

114. Lam RW, Filteau MJ, Milev R. Clinical effectiveness: the importance of psychosocial functioning outcomes. J Affect Disord. 2011;132(suppl 1):S9–S13. doi:10.1016/j.jad.2011.03.046 PubMed