A Review of the Clinical, Economic, and Societal Burden of Treatment-Resistant Depression: 1996–2013
Abstract
Objective
This literature review assessed the burden of treatment-resistant depression in the United States by compiling published data about the clinical, societal, and economic outcomes associated with failure to respond to one or more adequate trials of drug therapy.
Methods
PubMed and the Tufts Cost-Effectiveness Analyses Registry were searched for English-language articles published between January 1996 and August 2013 that collected primary data about treatment-resistant depression. Two researchers independently assessed study quality and extracted data.
Results
Sixty-two articles were included (N=59,462 patients). Patients with treatment-resistant depression had 3.8±2.1 prior depressive episodes and illness duration of 4.4±3.3 years and had completed 4.7±2.7 unsuccessful drug trials involving 2.1±.3 drug classes. Response rates for treatment-resistant depression were 36%±1%. A total of 17%±6% of patients had prior suicide attempts (1.1±.2 attempts per patient). Quality-of-life scores (scale of 0–1, with 0 indicating death and 1 indicating perfect health) for patients with treatment-resistant depression were .41±.8 and .26±.8 points lower, respectively, than for patients who experienced remission or response. Annual costs for health care and lost productivity were $5,481 and $4,048 higher, respectively, for patients with treatment-resistant versus treatment-responsive depression.
Conclusions
Treatment-resistant depression exacts a substantial toll on patients’ quality of life. At current rates of 12%–20% among all depressed patients, treatment-resistant depression may present an annual added societal cost of $29–$48 billion, pushing up the total societal costs of major depression by as much as $106–$118 billion. These findings underscore the need for research on the mechanisms of depression, new therapeutic targets, existing and new treatment combinations, and tests to improve the efficacy of and adherence to treatments for treatment-resistant depression.
Almost 50% of the U.S. population has experienced at least one psychiatric disorder in their lifetime (1). The lifetime prevalence of major depressive disorder is reported to be as high as 17%, and the 12-month prevalence is 5%−9% (2–4). The World Health Organization ranks major depressive disorder among the diseases that are most debilitating to society, in part because of its association with increased utilization of health care resources, diminished quality of life, and indirect personal and societal costs (5,6).
More than 50% of patients with major depressive disorder do not reach remission with an initial treatment; of those, 30%−50% also do not respond (4,5,7–9). The designation “treatment resistant” is used to describe patients who do not respond to antidepressant therapy after one or more adequate trials (9–11) (duration of at least six weeks and use of appropriate dosages [12–15]). A response to treatment is commonly measured as a ≥50% decrease in baseline scores on the Hamilton Rating Scale for Depression (HAM-D) (7). The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial studied the effectiveness of different treatments for major depressive disorder among patients who did not become symptom free after one or more treatments. Seventy-two percent of patients did not experience remission after treatment with citalopram, the initial medication used in this study; with each subsequent treatment, failure to remit increased from 79% to 84% to 93% (8,16–19).
Patients with treatment-resistant depression contribute a disproportionately high burden of illness compared with patients who respond to treatment. Several studies have documented a subset of outcomes related to treatment-resistant depression, such as societal costs and effects on quality of life, labor force participation, or medical resource utilization, but none has provided a comprehensive, systematic, and rigorous review of the overall burden.
The aim of this systematic review was to assess the aggregate burden of treatment-resistant depression in the United States by compiling the data available from published studies on clinical, societal, and economic outcomes associated with treatment-resistant depression. The review assessed characteristics and comorbid conditions, costs of treatment, mortality, quality of life, severity of symptoms, response rates to subsequent treatments, and adverse events among patients with treatment-resistant depression. This review also investigated factors that contribute most to the societal burden of treatment-resistant depression and identified potential areas for improvement.
Methods
We used PubMed to search MEDLINE for articles published between January 1996 and May 2011 by using terms related to treatment-resistant depression, outcomes, economics, and society. A supplemental search of PubMed using additional terms was conducted for articles published between May 2011 and August 2013. We also conducted a search of the Tufts Cost-Effectiveness Analysis Registry (20) for articles published from 1996 through 2013 and reviewed the reference lists of articles identified by the searches related to costs of treatment. [A complete list of search terms and a full description of the study methods are available online as a data supplement to this article.]
Two researchers screened each abstract of the retrieved articles. The articles were included if the abstract referred to primary data collection as a part of the design; if endpoints of the study were pertinent to clinical, societal, or economic outcomes; and if the study enrolled adults ages 18 and older. We defined treatment resistance as failure to respond to one or more adequate trials of drug therapy. This definition was intended to conform to accepted criteria of treatment resistance while including heterogeneous definitions. The evidence grade for each study was assessed by using the quality index developed by the Mental Disorders and Illicit Drug Use Expert Group (21). Quality index scores range from 0 to 17, with higher scores indicating that more complete reporting and higher quality methods were used.
We included articles that reported results from the STAR*D trial, even though its definition of treatment resistance as “failure to remit” is more inclusive than the one used in this review, which included patients who failed to respond. However, as the largest and longest study evaluating depression treatment, the STAR*D study provides valuable information for comparing responses to treatment, despite differences in definitions of treatment resistance.
Summary statistics were performed by using Stata, version 9.2, and were weighted by sample size. Unless stated otherwise, results are reported for the treatment-resistant population.
Results
Literature search and study characteristics
The original search identified 442 articles; 62 were included in this review. [The complete list of included articles is available in the online data supplement.] The mean±SD study duration was 7.75±1.75 years. The quality index score varied from 6 to 18 (mean±SD=13±3). Sample sizes in the studies varied from six to 24,415 patients (median=42; Table 1) and, together, enrolled 59,462 patients. Thirteen studies summarized data on outpatients, eight on inpatients, and six on both populations; 22 articles did not specify a population but likely included predominantly outpatients.
| Treatment-resistant depression | Treatment-responsive depression | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N | % | Median(%) | Minimum(%) | Maximum(%) | N ofstudies | N | % | Median(%) | Minimum(%) | Maximum(%) | N ofstudies | |||||
| Characteristic | M | SD | M | SD | M | SD | M | SD | ||||||||
| Sample size | 1,239 | 4,756 | 42 | 6 | 24,415 | 49 | ||||||||||
| Age (M±SD) | 46.7 | 5.3 | 47.0 | 27.4 | 74.7 | 39 | ||||||||||
| Age at onset (M±SD) | 31.5 | 6.8 | 27.7 | 2.9 | 51.2 | 12 | ||||||||||
| Duration of illness (M±SD years) | 4.4 | 3.3 | 16.7 | 2.5 | 26.7 | 20 | ||||||||||
| Previous episodes of depression (M±SD) | 3.8 | 2.1 | 2.6 | .8 | 7.2 | 16 | ||||||||||
| Women | 14,310 | 6,086 | 71 | 4 | 65 | 0 | 93 | 42 | ||||||||
| Race-ethnicity | ||||||||||||||||
| Caucasian | 3,060 | 1,765 | 89 | 4 | 91 | 78 | 97 | 12 | ||||||||
| African American | 29 | 24 | 13 | 9 | 3 | 2 | 18 | 3 | ||||||||
| Other | 6 | 3 | 4 | 3 | 3 | 0 | 7 | 3 | ||||||||
| Comorbid conditionb | ||||||||||||||||
| Joint, limb, or back pain | 3,386 | 73 | 1 | 5,267 | 70 | 1 | ||||||||||
| Hypertension | 3,095 | 607 | 67 | 0 | 40 | 12 | 68 | 2 | 5,035 | 903 | 67 | 9 | 43 | 17 | 68 | 2 |
| Dyslipidemia | 2,821 | 556 | 61 | 0 | 32 | 1 | 62 | 2 | 4,739 | 853 | 63 | 11 | 34 | 3 | 64 | 2 |
| Cardiovascular disease | 2,598 | 56 | 1 | 3,702 | 666 | 49 | 9 | 25 | 1 | 50 | 2 | |||||
| Malaise and fatigue | 2,412 | 52 | 1 | 3,311 | 44 | 1 | ||||||||||
| Anxiety | 1,767 | 1,265 | 44 | 0 | 21 | 7 | 59 | 6 | 2,512 | 1,557 | 36 | 16 | 13 | 9 | 43 | 3 |
| Anemia | 3 | 39 | 1 | 2,633 | 35 | 1 | ||||||||||
| Hypothyroidism | 1,593 | 312 | 35 | 5 | 23 | 11 | 35 | 2 | 2,147 | 385 | 29 | 4 | 18 | 7 | 29 | 2 |
| Chronic obstructive pulmonary disease | 1,577 | 34 | 1 | 2,257 | 30 | 1 | ||||||||||
| Diabetes | 1,358 | 499 | 30 | 0 | 15 | 8 | 32 | 3 | 2,295 | 411 | 31 | 4 | 20 | 10 | 31 | 2 |
| Alcohol abuse, lifetime | 16 | 10 | 27 | 7 | 28 | 14 | 30 | 3 | 47 | 34 | 1 | |||||
| Alcohol abuse, current | 231 | 173 | 6 | 2 | 5 | 3 | 8 | 3 | 180 | 116 | 3 | 1 | 2 | 1 | 3 | 2 |
| Avoidant personality disorder | 18 | 2 | 24 | 7 | 28 | 20 | 30 | 2 | 35 | 33 | 1 | |||||
| Asthma | 974 | 21 | 1 | 1,354 | 18 | 1 | ||||||||||
| Self-defeating personality disorder | 11 | 21 | 1 | 15 | 14 | 1 | ||||||||||
| Chronic pain | 878 | 251 | 20 | 1 | 16 | 15 | 20 | 3 | 1,162 | 490 | 19 | 3 | 21 | 18 | 23 | 2 |
| Substance use disorder, lifetime | 8 | 4 | 18 | 12 | 14 | 7 | 39 | 3 | 30 | 22 | 1 | |||||
| Substance use disorder, current | 56 | 42 | 3 | 1 | 43 | 1 | 4 | 2 | 37 | 2 | 1 | |||||
| Obsessive-compulsive disorder | 13 | 2 | 17 | 4 | 18 | 15 | 21 | 2 | 39 | 37 | 1 | |||||
| Panic disorder | 48 | 34 | 17 | 7 | 18 | 7 | 25 | 5 | 17 | 12 | 1 | |||||
| Delusions and other psychoses | 774 | 151 | 17 | 2 | 13 | 9 | 17 | 2 | 444 | 80 | 6 | 1 | 4 | 2 | 6 | 2 |
| Obesity | 774 | 152 | 17 | 3 | 10 | 3 | 17 | 2 | 1,037 | 185 | 14 | 1 | 104 | 6 | 14 | 2 |
| Personality disorder | 728 | 142 | 16 | 2 | 11 | 6 | 16 | 2 | 296 | 53 | 4 | 0 | 43 | 2 | 4 | 2 |
| Sleep disorder | 694 | 252 | 16 | 2 | 13 | 9 | 16 | 2 | 978 | 13 | 1 | |||||
a
SDs and minimum and maximum percentages are not reported when only one study provided results.
b
The following list reports percentages of patients with treatment-resistant vs. treatment-responsive depression and other conditions: mixed personality disorder, 14% vs. data not reported (DNR); borderline personality disorder, 13% vs. 13%; paranoid personality disorder, 13% vs. 28%; migraine, 12% vs. 9%; social phobia, 12% vs. 35%; dependent personality disorder, 11% vs. 15%; simple phobia, 11% vs. 14%; generalized anxiety disorder, 10% vs. 16%; agoraphobia, 10% vs. 7%; passive-aggressive personality disorder, 9% vs. 13%; physical abuse, 9% vs. DNR; posttraumatic stress disorder, 9% vs. 4%; soft tissue disorder, 7% vs. 0%; somatoform disorder, 5% vs. 5%; antisocial personality disorder, 5% vs. 7%; eating disorder, 5% vs. 3%; narcissistic personality disorder, 4% vs. 10%; obsessive-compulsive disorder, 4% vs. 3%; acute myocardial infarction persistent, 3% vs. DNR; mood disorders, 3% vs. 1%; dysthymia, 3% vs. DNR; dementia, 2% vs. 2%; gastritis and duodenitis, 2% vs. 4%; schizoid personality disorder, 2% vs. 3%; phobic anxiety disorders, 2% vs. 3%; mild mental retardation, 1% vs. 2%; and histrionic personality disorder, 0% vs. 3%
Baseline patient characteristics
Patients’ baseline characteristics varied by study (Table 1). The mean age was 46.7, and illness duration was 4.4 years. Women represented 71% and non-Hispanic whites represented 89% of the study populations. Patients had 3.8 prior depressive episodes (range .8–7.2). On average, patients had not responded to 4.7 drug trials (range 1–10) and 2.1 drug classes (Table 2).
| Scale range | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Variable | M | SD | Median | Lowest | Highest | N of studies | Remissionor mild | Severe ormarkedly ill | Reference |
| Failed drug trialsb | 4.7 | 2.7 | 2.6 | 1.0 | 10.0 | 11 | |||
| Failed drug classesb | 2.1 | .3 | 2 | 2.0 | 3.0 | 6 | |||
| Depression-specific scale score | |||||||||
| HAM-D-17 | 21.9 | 1.7 | 22.6 | 19.2 | 28.4 | 18 | 0–13 | 20–52 | 22 |
| HAM-D-21 | 19.8 | 5.2 | 19.5 | 15.8 | 23.2 | 2 | 0–15 | 23–64 | 22 |
| HAM-D-24 | 27.9 | 4.2 | 27.9 | 21.0 | 33.7 | 4 | 0–18 | 27–75 | 22 |
| HAM-D-28 | 30.4 | 5.5 | 32.2 | 23.7 | 34.3 | 3 | 0–10 | 21–52 | 23 |
| MADRS | 31.8 | 3.0 | 33.0 | 25.0 | 50.0 | 12 | 0–19 | 35–60 | 22 |
| CGI-S | 4.6 | .4 | 4.8 | 3.8 | 6.3 | 11 | 1–3 | 6–7 | 24 |
| BDI | 30.9 | 6.6 | 31.7 | 16.5 | 38.2 | 5 | 0–18 | 30–63 | 22 |
| IDS-SR-30 | 41.3 | 2.0 | 40.8 | 38.2 | 43.4 | 3 | 0–25 | 39–84 | 22 |
| IDS-C-30 | 35.4 | 1 | 0–23 | 37–84 | 22 | ||||
| QIDS-SR-16 | 15.8 | 2.5 | 15.8 | 14.0 | 17.6 | 2 | 0–10 | 16–27 | 22 |
| QIDS-C-16 | 14.4 | 1 | 0–10 | 16–27 | 22 | ||||
| Other scale score | |||||||||
| GAF | 50.0 | 7.0 | 42.3 | 28.7 | 55.0 | 6 | 100–61 | 50–0 | 25 |
| HAMA | 17.8 | 1.1 | 19.6 | 17.5 | 23.3 | 4 | 0–17 | 31–56 | 26 |
| Q-LES-Q | 37.4 | 1.2 | 37.3 | 34.6 | 41.0 | 3 | 100 | 0 | 26 |
| BPRS | 17.3 | 6.9 | 25.9 | 16.0 | 35.8 | 2 | 16–31 | 53–126 | 27 |
| SF–36 MCS | 22.5 | 2.7 | 21.6 | 19.4 | 23.7 | 2 | 100 | 0 | 28 |
| SF–36 PCS | 37.5 | 3.1 | 36.5 | 34.0 | 38.9 | 2 | 100 | 0 | 28 |
| BAI | 14.1 | 1 | 0–15 | 26–63 | 29 | ||||
| MMSE | 27.7 | 1 | 24–30 | 0–23 | 30 | ||||
| SQ-SS | 6.6 | 1 | 0 | 18 | 31 | ||||
| SQ-SWB | 1.4 | 1 | 6 | 0 | 31 | ||||
| POMS | 52.5 | 1 | 0 | 200 | 32 | ||||
a
SDs and minimum and maximum scores are not reported when only one study provided results. HAM-D, Hamilton Rating Scale for Depression; MADRS, Montgomery-Asberg Depression Scale; CGI-S, Clinical Global Impression–Severity; BDI, Beck Depression Inventory; IDS, Inventory of Depressive Symptomatology; SR, Self-Report; C, Clinician Rated; QIDS, Quick Inventory of Depressive Symptomatology; GAF, Global Assessment of Functioning; BPRS, Brief Psychiatric Rating Scale; Q-LES-Q, Quality of Life Enjoyment and Satisfaction Questionnaire; BAI, Beck Anxiety Inventory; HAMA, Hamilton Anxiety Scale; MMSE, Mini-Mental State Examination; SF-36, Short-Form Health Survey Questionnaire; MCS, mental composite score; PCS, physical composite score; SQ, Symptom Questionnaire; SS, somatic subscale; SWB, somatic well-being; POMS, Profile of Mood States.
b
Excluded studies that reported the number of failed drug trials and classes as ranges.
Symptom severity
The scales used to assess symptom severity varied greatly. Commonly used scales included the HAM-D, the Montgomery-Asberg Depression Scale (MADRS), the Clinical Global Impression–Severity (CGI-S) scale, and the Quick Inventory of Depressive Symptomatology–Clinician Rated (QIDS-C). The average scores at baseline on the HAM-D-17, the MADRS, the CGI-S, and the QIDS-C indicated that symptom severity was within or close to the scoring range used to classify conditions as severe or markedly ill (Table 2) (22–32). At the end of the studies, severity scores had improved by an average of 35%±8% (improvements of 12.8±4.1, or 42%, on the HAM-D-17; 23.2±7.7, or 27%, on the MADRS; and 3.0±1.4, or 36%, on the CGI-S). Scores at the end of the studies were not reported for the QIDS-C.
Comorbid conditions
Comorbid conditions were relatively common among patients with treatment-resistant depression, as indicated in Table 1. Comorbid conditions included joint, limb, or back pain (73%); hypertension (67%); and dyslipidemia (61%) (33,34). Some psychiatric conditions, such as malaise or fatigue, anxiety, and personality disorder, were more prevalent among patients with treatment-resistant versus treatment-responsive depression (15,33–37). Suicidal ideation was reported for 15%±8% of patients with treatment-resistant depression, 6% of patients with treatment-responsive depression, and 1% of the general population (33,38,39). Approximately 17%±6% of patients with treatment-resistant depression had a history of suicide attempt, with an average of 1.1±.2 prior suicide attempts each (8,15,33,39–44).
Mortality rates (deaths per 1,000 patient-years) were similar among patients with treatment-resistant (46.2) and treatment-responsive (46.8) depression in a Medicare population and were about 4% lower than the rate for individuals in the general population (48.2). (33) No articles summarized associations between treatment-resistant depression and other outcomes, such as crime rates, incarceration, social services’ utilization, or caregivers’ quality of life.
Response and remission rates
Therapeutic options for treatment-resistant depression consisted of deep brain stimulation, transcranial magnetic stimulation, transcranial direct-current stimulation, vagus nerve stimulation, group psychoeducation, cognitive therapy, and a variety of drugs, most commonly lamotrigine, lithium, olanzapine, and venlafaxine. Sixteen studies reported rates of remission and response (Table 3) (8,9,17,38,43–54). Response rates for different treatment groups varied between 0% and 80%, for an average of 36%±1%. Remission rates varied from 8% to 80%, for an average of 20%±1%. The lowest average response and remission rates were reported in the STAR*D trial: scores on the QIDS–Self-Report–16 indicated that only 15% and 10%, respectively, had responded to treatment or were in remission (8). One study found cognitive therapy to be effective; patients averaged a significant 9-point decline in the Beck Depression Inventory score, and 26% had a “sustained recovery” at 26 weeks (55).
| Study | Ratingscaleb | Lengthof study(weeks) | N ofpatients | Treatment with lowest rate of response or remission | Treatment with highest rate of response or remission | Response (%) | Remission (%) | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Average | Lowest | Highest | Average | Lowest | Highest | ||||||
| Inoue et al., 1996 (50) | HAM-D-17 | 6 | 6 | Bromocriptine | 67 | ||||||
| Shelton et al., 2001 (51) | MADRS | 8 | 34 | Olanzapine | Olanzapine and fluoxetine | 25 | 0 | 60 | |||
| Papakostas et al., 2003 (35) | HAM-D-17 | 6 | 92 | Nortriptyline; patients with comorbid avoidant personality disorder | Nortriptyline; patients without comorbid avoidant personality disorder | 42 | 17 | 49 | |||
| Seidman et al., 2005 (49) | HAM-D-17 | 6 | 23 | Placebo | Testosterone | — | 23 | 54 | |||
| Corya et al., 2006 (52) | MADRS | 7 | 483 | Olanzapine | Venlafaxine (response); olanzapine and fluoxetine combination (remission) | 38 | 25 | 50 | 23 | 14 | 30 |
| Fava et al., 2006 (8) | QIDS-SR-16 | 14 | 235 | Mirtazapine | Nortriptyline | 15 | 13 | 17 | 10 | 8 | 12 |
| Fava et al., 2006 (8) | HAM-D-17 | 14 | 235 | Mirtazapine | Nortriptyline | 16 | 12 | 20 | |||
| Doree et al., 2007 (46) | HAM-D-17 | 8 | 20 | Lithium | Quetiapine | 65 | 50 | 80 | 60 | 40 | 80 |
| Doree et al., 2007 (46) | MADRS | 8 | 20 | Lithium | Quetiapine | 65 | 50 | 80 | 55 | 30 | 80 |
| Mahmoud et al., 2007 (48) | HAM-D-17 | 6 | 258 | Placebo | Risperidone | — | 30 | 46 | 25 | 11 | 25 |
| Schindler and Anghelescu, 2007 (45) | HAM-D-17 | 8 | 34 | Lithium | Lamotrigine | 47 | 41 | 53 | 21 | 18 | 23 |
| Avery et al., 2008 (17) | MADRS | 9 | 158 | Sham, then transcranial magnetic stimulation (TMS) | Extended TMS | 40 | 34 | 45 | 25 | 18 | 31 |
| Avery et al., 2008 (17) | MADRS | 6 | 158 | Sham, then TMS | Extended TMS | 35 | 26 | 42 | 16 | 11 | 20 |
| Avery et al., 2008 (17) | HAM-D-24 | 6 | 158 | Sham, then TMS | Extended TMS | 37 | 32 | 42 | 22 | 16 | 27 |
| Avery et al., 2008 (17) | HAM-D-24 | 9 | 158 | Sham, then TMS | Extended TMS | 39 | 32 | 46 | 29 | 19 | 37 |
| Bares et al., 2008 (9) | MADRS | 4 | 25 | Venlafaxine | 48 | ||||||
| Karp et al., 2008 (47) | HAM-D-17 | 6.9 | 20 | Duloxetine | 50 | ||||||
| Lozano et al., 2008 (53) | HAM-D-17 | 26 | 20 | Deep brain stimulation | 60 | ||||||
| Lozano et al., 2008 (53) | HAM-D-17 | 52 | 20 | Deep brain stimulation | 55 | 35 | |||||
| Bewernick et al., 2010 (23) | HAM-D-28 | 52 | 11 | Deep brain stimulation | 46 | 9 | |||||
| Kopell et al., 2011 (44) | HAM-D-28 | 91 | 11 | Epidural cortical stimulation | 46 | 36 | |||||
| Taneja et al., 2012 (54) | MADRS | 6 | 1,034 | Meta-analysis: antidepressant | 30 | 20 | 39 | ||||
| Taneja et al., 2012 (54) | MADRS | 6 | 540 | Meta-analysis: aripiprazole with antidepressant | 49 | 41 | 60 | ||||
| Taneja et al., 2012 (54) | MADRS | 6 | 309 | Meta-analysis: quetiapine 150 mg with antidepressant | 34 | 28 | 40 | ||||
| Taneja et al., 2012 (54) | MADRS | 6 | 312 | Meta-analysis: quetiapine 300 mg with antidepressant | 38 | 32 | 44 | ||||
| Taneja et al., 2012 (54) | MADRS | 6 | 200 | Meta-analysis: olanzapine and fluoxetine | 45 | 32 | 64 | ||||
| Average±SD (weighted)c | 6±20 | 176±234 | 36±1 | 26±1 | 45±1 | 20±1 | 13±1 | 25±1 | |||
a
For studies that assessed only one treatment, the treatment is listed under lowest response or remission rate, and results are listed under average response or remission rates.
b
HAM-D, Hamilton Rating Scale for Depression; MADRS, Montgomery-Asberg Depression Scale; QIDS-SR, Quick Inventory of Depressive Symptomatology–Self-Report
c
Weighted by inverse-variance method. Excludes patients on placebo
Medication-related adverse events
Twenty-seven studies reported on the incidence of adverse events among patients with treatment-resistant depression. Rush and others (56) found that 53% of patients experienced at least one adverse event, of which 81% were mild or moderate. The most frequent mild or moderate drug-related adverse events were decreased sexual desire (33%), orgasmic dysfunction (26%), and blurred vision (15%). The most frequent severe drug-related adverse events were dissociative reactions (13%), ataxia (13%), mixed states (dysphoric mania or agitated depression) (10%), and tremor and nausea (10%). The most frequent procedure-related adverse events were swollen eye (55%), headache (38%), and erythema (36%); no severe procedure-related adverse events were reported. Only four studies that reported adverse events had a placebo arm. Adverse events that occurred in more than 5% of the placebo groups were blood pressure change (40%), headache (15%), dissociative reaction (in a study utilizing ketamine) (13%), and manic reaction (13%) (10,48,54,57).
Quality of life and costs
Quality-of-life data were taken from published models that used data sources ranging from reviews of prior literature to original trials (58–63). The studies measured quality of life with a continuous scale, with 0 indicating death and 1 indicating perfect health. Average baseline scores were .552±.120 for patients with major depressive disorder (58–61), .826±.065 for patients in remission (59–63), .673±.031 for patients who responded to therapy without remission (61,62), and .417±.126 for patients who did not respond to therapy (61–63). Adverse events caused a further loss of .01 to .12 quality-of-life units (59).
Five studies provided detailed information about annual per-patient costs for treatment-resistant depression, one from Medicare and four from databases of national employers and private payer claims (Table 4) (33,36,54,64,65). Annual claims for visits to a medical facility were relatively common among patients with treatment-resistant (N=28.3 claims) versus treatment-responsive depression (N=15.1 claims) (64). Fifty-two percent of patients with treatment-resistant depression were hospitalized over their lifetimes (39).
| Category | M | SDb | Median | Lowest | Highest | N ofstudies |
|---|---|---|---|---|---|---|
| Treatment-resistant depression | ||||||
| Health care (direct costs) | ||||||
| Depression drugs | 2,667 | 1,026 | 3,736 | 1,346 | 7,568 | 4 |
| Nondepression drugs | 2,556 | 141 | 2,580 | 2,216 | 2,963 | 3 |
| Hospitalizations | ||||||
| Emergency care | 392 | — | — | — | — | 1 |
| Nonpsychiatric medical care | 2,508 | 786 | 2,986 | 2,253 | 3,719 | 2 |
| Psychiatric visits | 593 | 324 | 790 | 488 | 1,092 | 2 |
| Physician visits | 4,829 | 2,431 | 3,351 | 1,085 | 5,618 | 2 |
| Psychotherapy | 978 | 344 | 770 | 449 | 1,090 | 2 |
| Totalc | 13,196 | 219 | 13,402 | 13,152 | 14,417 | 3 |
| Productivity (indirect costs) | ||||||
| Absenteeism | 2,625 | 987 | 2,025 | 1,105 | 2,945 | 2 |
| Disability | 4,299 | 815 | 3,804 | 3,044 | 4,564 | 2 |
| Total | 6,924 | 1,801 | 5,829 | 4,149 | 7,509 | 2 |
| Total direct and indirect costs | 20,120 | |||||
| Treatment-responsive depression | ||||||
| Health care (direct costs) | ||||||
| Depression drugs | 898 | 162 | 561 | 385 | 939 | 3 |
| Nondepression drugs | 1,407 | 75 | 1,369 | 1,094 | 1,422 | 3 |
| Hospitalizations | ||||||
| Emergency care | 224 | — | — | — | — | 1 |
| Nonpsychiatric medical care | 1,438 | 119 | 1,418 | 1,332 | 1,505 | 2 |
| Psychiatric visits | 99 | 23 | 95 | 79 | 112 | 2 |
| Physician visits | 1,708 | 1,864 | 2,021 | 666 | 3,376 | 2 |
| Psychotherapy | 255 | 176 | 284 | 156 | 412 | 2 |
| Totalc | 7,715 | 456 | 6,902 | 6,375 | 7,832 | 3 |
| Productivity (indirect costs) | ||||||
| Absenteeism | 1,125 | 849 | 1,268 | 651 | 1,885 | 2 |
| Productivity | 1,751 | 464 | 1,829 | 1,492 | 2,166 | 2 |
| Total | 2,876 | 1,312 | 3,096 | 2,142 | 4,050 | 2 |
| Total direct and indirect costs | 10,592 |
a
Costs are for private payers and are reported in 2012 dollars.
b
An SD and other data were not reported when only one study provided results.
c
May include other costs that are not listed
Among private payers, the mean annual direct health care costs per patient for management of treatment-resistant depression ($13,196) were $5,481 higher than for management of treatment-responsive depression ($7,715) (Table 4) (36,64,65). These comparisons were from the same studies, so observed differences were not an artifact of sample heterogeneity. Annual direct medical costs for persons in the general population were $3,997 (64). Total costs in productivity per patient-year were $4,048 higher among patients with treatment-resistant depression ($6,924) than among patients with treatment-responsive depression ($2,876) (36,64) (Table 4). For the general population, annual productivity costs were $1,098 (64). The total annual direct and indirect costs per patient-year were $20,120 for patients with treatment-resistant depression and $10,592 for an age-matched population with treatment-responsive depression (Table 4) (36,64,65). These costs were $5,095 in the general population (64).
Annual direct medical costs among Medicare patients were $20,736 for patients with treatment-resistant depression, $14,098 for patients with treatment-responsive depression, and $10,380 in the general population of Medicare patients (33). These differences in cost in the Medicare population reinforce the considerable health care benefit that could be obtained from more effectively treating major depressive disorder.
Discussion
Our review of literature shows that among the many burdens of patients with treatment-resistant depression, they experience only a 20% probability of achieving remission in the course of treatment, a 17% prevalence of prior suicide attempts, substantially lower quality-of-life scores than patients whose depression remits, and direct and indirect annual costs among private payers that are $9,529 higher than those of patients with treatment-responsive depression. Patients with treatment-resistant depression had 28.3 annual general medical visits, more than three times as many as the general population average of 8.7, whereas patients with treatment-responsive depression had less than twice as many annual general medical visits as the general population (64).
Although response and remission rates for patients with treatment-resistant depression varied widely among studies, average improvements on the CGI-S (36%), the HAM-D-17 (42%), and the MADRS (27%) were similar. The STAR*D study found particularly low rates of response (15%) and remission (10%), possibly because this study consisted of patients who did not respond to up to three well-monitored treatments, whereas many other studies used nonresponse to just one or two naturalistic treatments as their criterion for treatment resistance.
Among adults in the United States, the 12-month prevalence of major depressive disorder in 2012 was 6.7% (3), or 16 million individuals. Assuming that 12% of these patients had treatment-resistant depression, which was the lowest estimate reported by studies in this review (64), a total of 1.9 million adults in the United States had treatment-resistant depression in 2012. If annual costs of treatment per patient-year for private payers totaled $20,120, as estimated, the total costs for treatment of this population in 2012 was $38 billion. Adding in the annual cost of treatment of the 14 million patients with treatment-responsive depression ($10,592 each; $148 billion total), the societal burden of major depressive disorder for the United States in 2012 was $188 billion. By comparison, the societal cost for cancer was $131 billion (66), and in 2007, the societal cost for diabetes in 2012 dollars was $173 billion (67).
Corey-Lisle and colleagues (64) stated that treatment resistance among patients with depression might actually be as high as 20%. When this higher estimate was used, the estimated societal burden of major depressive disorder in the United States reaches $200 billion per year and the burden of treatment-resistant depression alone reaches $64 billion per year. A prior study estimated that the societal cost of major depressive disorder was $124 billion per year, in 2012 dollars (2). This estimate may be lower than our estimate of $188–$200 billion because of temporal changes in unit service costs, for example, increasing wages, and the possible exclusion of costs for patient visits that were not reported as being primarily for depression (36,64).
The burden of major depression can also be calculated as an increase in costs above those of the general population. If 12% of patients with depression are resistant to therapy, the costs of depression above general population costs are $29 billion for patients with treatment-resistant depression, $77 billion for patients with treatment-responsive depression, and $106 billion for all major depression. If 20% of depressed patients are resistant to therapy, the estimated costs are $48 billion for patients with treatment-resistant depression, $70 billion for patients with treatment-responsive depression, and $118 billion for all major depression. Conversely, if 70% more patients respond to antidepressant therapy, the costs for the 3.6% of patients who remain treatment resistant would decrease to $8.6 billion, and costs for patients with treatment-responsive depression would be $84.3 billion. The aggregate $93 billion annual cost of major depression above general population costs would save $13 billion, a 12% reduction in the annual cost of treating all patients with major depressive disorder.
Gillum and colleagues (68) recently compared 29 common conditions and diseases in terms of incidence, prevalence, and disability-adjusted life years. Depression ranked first in populationwide burden by disability-adjusted life years. The next four most impactful conditions or disorders were injuries, ischemic heart disease, alcohol abuse, and chronic obstructive pulmonary disorder. The low quality-of-life scores (.417 on a scale of 0 to 1) reported by patients with treatment-resistant depression who did not respond to therapy fell within the range of scores reported for metastatic cancer, chronic moderate-to-severe pain, or acquired blindness (20). Although these quality-of-life measures may be confounded by patients’ current mood and depressive symptoms (69), the estimates amount to one million quality-adjusted years lost due to treatment-resistant depression in the United States. Treatment-responsive depression accounts for an additional loss of more than 1.5 million quality-adjusted years.
The small numbers and heterogeneity that characterized the study populations and treatments described in the articles summarized here may limit the general applicability of some findings. For example, only a few studies included information about comorbid disorders and adverse events. Our summaries of the five studies that reported costs per patient-year for depression treatment and our extrapolation of the data to determine nationwide costs can be combined with results of future studies to more accurately calculate the monetary impact of treatment-resistant depression. Other limitations of this analysis included the heterogeneity of methods and the degree to which complete findings were reported, the relatively short periods of patient follow-up, and a focus primarily on clinical endpoints during follow-up.
The burden of treatment-resistant depression was likely underestimated because there is limited published research, or none at all, on the incidence of crime rates, incarceration, and use of social services among persons with depression and on costs and quality-of-life burden for family members and caregivers. The burden might also have been underestimated because we excluded studies with adolescent populations, which have similar prevalence rates for depression as adults but lower treatment rates (70–72). Among patients with treatment-resistant depression, adolescents experienced a greater burden with regard to suicide attempts compared with adults, and their rate of substance use disorders (54%) was higher than the current (3%) and lifetime (18%) rates for adults (73).
In response to these challenges, personalized medicine technologies are finding increasing application in reducing the burden of major depression. One such approach, pharmacogenomics, matches the pharmacokinetic and pharmacodynamic properties of antidepressant medications to the genetic profile of individual patients. Pharmacogenomic test results can identify variability in psychiatric drug response and, when applied clinically, can increase antidepressant responses by 70% (74–78). Identifying the right medication and dose for patients will shorten patients’ treatment odyssey, thereby decreasing the proportion that become treatment resistant. The resulting savings would diminish annual health expenditures and increase productivity. Psychiatric pharmacogenomics and other innovations may also improve the classification of major depressive disorder subtypes; define more individualized and earlier, potentially prodromal treatments; and reduce adverse event rates (79,80).
Conclusions
The studies reviewed here reveal that the personal and societal burdens of depression are disproportionately greater among patients who do not respond to antidepressant therapies. Contributory factors to this extra burden include more unsuccessful drug trials; more comorbid disorders, such as malaise, fatigue, and anxiety; and increases in suicidal ideation. The far greater personal financial burden of treatment resistance is likely to compound anxiety, depression, and comorbid disorders as financial hardships mount.
Despite multiple treatment options available to clinicians, treatment resistance remains highly prevalent and exacts a substantial toll on patients’ quality of life and on society. The burden of treatment-resistant depression is on a par with or is greater than that of other chronic conditions such as cancer and diabetes, yet depression ranks only 15th among conditions or disorders that receive National Institutes of Health research funds (68).
Improvements in technology are likely to diminish treatment resistance and mitigate its extra costs. These include pharmacogenomic tests that incorporate additional DNA variants and DNA methylation status; new medications that are based on nonmonoaminergic approaches, such as N-methyl-D-aspartate receptor antagonism; and refinements in transcranial magnetic stimulation.
Disparities in care also need to be addressed so that innovations can achieve a broad societal impact. Certain racial or ethnic groups and unemployment are associated with underdetection of mental illness and inadequate mental health care access or quality (81–84). Solutions include more social programs, better patient education, quality improvement programs, and increased resources for indigent care clinics (81–84). Consistent processes for assessing regulatory and reimbursement implications of new therapeutic and diagnostic practices are also needed (79). Expanded treatment alternatives, augmented with pharmacogenomic decision support, have the potential to improve outcomes and help patients retain productive lives. Along with decreases in health care costs and increased global productivity, there is much to achieve—and expect—by decreasing the individual and societal burdens of treatment-resistant depression.
Acknowledgments and disclosures
This study was supported by Assurex Health through a research contract with Cedar Associates.
Dr. Mrazek developed intellectual property that was licensed by Assurex Health and received research funding from Assurex Health to create and maintain a bibliographic system designed to regularly curate scientific literature. The other authors report no competing interests.
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References
1.
Kessler RC, McGonagle KA, Zhao S, et al.: Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Archives of General Psychiatry 51:8–19, 1994
2.
Eaton WW, Martins SS, Nestadt G, et al.: The burden of mental disorders. Epidemiologic Reviews 30:1–14, 2008
3.
Kessler RC, Chiu WT, Demler O, et al.: Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62:617–627, 2005
4.
Nemeroff CB: Prevalence and management of treatment-resistant depression. Journal of Clinical Psychiatry 68(suppl 8):17–25, 2007
5.
Greden JF: The burden of disease for treatment-resistant depression. Journal of Clinical Psychiatry 62(suppl 16):26–31, 2001
6.
The Global Burden of Disease: 2004 Update. Geneva, World Health Organization, 2004. Available at www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_full.pdf
7.
Nierenberg AA, DeCecco LM: Definitions of antidepressant treatment response, remission, nonresponse, partial response, and other relevant outcomes: a focus on treatment-resistant depression. Journal of Clinical Psychiatry 62(suppl 16):5–9, 2001
8.
Fava M, Rush AJ, Wisniewski SR, et al.: A comparison of mirtazapine and nortriptyline following two consecutive failed medication treatments for depressed outpatients: a STAR*D report. American Journal of Psychiatry 163:1161–1172, 2006
9.
Bares M, Brunovsky M, Kopecek M, et al.: Early reduction in prefrontal theta QEEG cordance value predicts response to venlafaxine treatment in patients with resistant depressive disorder. European Psychiatry 23:350–355, 2008
10.
Preskorn SH, Baker B, Kolluri S, et al.: An innovative design to establish proof of concept of the antidepressant effects of the NR2B subunit selective N-methyl-D-aspartate antagonist, CP-101,606, in patients with treatment-refractory major depressive disorder. Journal of Clinical Psychopharmacology 28:631–637, 2008
11.
Thase ME, Rush AJ: When at first you don’t succeed: sequential strategies for antidepressant nonresponders. Journal of Clinical Psychiatry 58(suppl 13):23–29, 1997
12.
Barbee JG, Jamhour NJ: Lamotrigine as an augmentation agent in treatment-resistant depression. Journal of Clinical Psychiatry 63:737–741, 2002
13.
Dombrovski AY, Mulsant BH, Haskett RF, et al.: Predictors of remission after electroconvulsive therapy in unipolar major depression. Journal of Clinical Psychiatry 66:1043–1049, 2005
14.
Petersen T, Gordon JA, Kant A, et al.: Treatment resistant depression and axis I co-morbidity. Psychological Medicine 31:1223–1229, 2001
15.
Souery D, Oswald P, Massat I, et al.: Clinical factors associated with treatment resistance in major depressive disorder: results from a European multicenter study. Journal of Clinical Psychiatry 68:1062–1070, 2007
16.
Rush AJ, Trivedi MH, Wisniewski SR, et al.: Bupropion-SR, sertraline, or venlafaxine-XR after failure of SSRIs for depression. New England Journal of Medicine 354:1231–1242, 2006
17.
Avery DH, Isenberg KE, Sampson SM, et al.: Transcranial magnetic stimulation in the acute treatment of major depressive disorder: clinical response in an open-label extension trial. Journal of Clinical Psychiatry 69:441–451, 2008
18.
Trivedi MH, Rush AJ, Wisniewski SR, et al.: Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. American Journal of Psychiatry 163:28–40, 2006
19.
McGrath PJ, Stewart JW, Fava M, et al.: Tranylcypromine versus venlafaxine plus mirtazapine following three failed antidepressant medication trials for depression: a STAR*D report. American Journal of Psychiatry 163:1531–1541, 2006
20.
Cost–Effectiveness Analysis Registry. Boston, Tufts Medical Center, 2013. Available at research.tufts-nemc.org/cear4/. Accessed Aug 22, 2013
21.
Mental Disorders and Illicit Drug Use Expert Group: Methodology Part 2: Systematic Review. Sydney, Australia, University of New South Wales, 2007. Available at www.med.unsw.edu.au/gbdweb.nsf/resources/MethodologyPart2/$file/GBD_Methodology_pt2_03Nov08.pdf
22.
Inventory of Depressive Symptomatology (IDS) and Quick Inventory of Depressive Symptomatology (QIDS). Pittsburgh, Pa, University of Pittsburgh Epidemiology Data Center, 2013. Available at www.ids-qids.org
23.
Bewernick BH, Hurlemann R, Matusch A, et al.: Nucleus accumbens deep brain stimulation decreases ratings of depression and anxiety in treatment-resistant depression. Biological Psychiatry 67:110–116, 2010
24.
Clinical Global Impression (CGI). Rockville, Md, US Department of Health, Education, and Welfare, 1976
25.
Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC, American Psychiatric Association, 1994
26.
Hamilton M: The assessment of anxiety states by rating. British Journal of Medical Psychology 32:50–55, 1959
27.
Leucht S, Kane JM, Kissling W, et al.: Clinical implications of Brief Psychiatric Rating Scale scores. British Journal of Medical Psychology 187:366–371, 2005
28.
Dumas R, Richieri R, Guedj E, et al.: Improvement of health-related quality of life in depression after transcranial magnetic stimulation in a naturalistic trial is associated with decreased perfusion in precuneus. Health and Quality of Life Outcomes 10:87, 2012
29.
Grant MM: Beck Anxiety Inventory; in Encyclopedia of Child Behavior and Development. Edited by, Goldstein S, Naglieri J. New York, Springer, 2011
30.
Kukull WA, Larson EB, Teri L, et al.: The Mini-Mental State Examination score and the clinical diagnosis of dementia. Journal of Clinical Epidemiology 47:1061–1067, 1994
31.
Papakostas GI, Petersen T, Denninger J, et al.: Somatic symptoms in treatment-resistant depression. Psychiatry Research 118:39–45, 2003
32.
Mcnair D, Lorr M, Droppleman L: EdITS Manual: Profile of Mood States. San Diego, Educational and Industrial Testing Service, 1992
33.
Feldman RL, Dunner DL, Muller JS, et al.: Medicare patient experience with vagus nerve stimulation for treatment-resistant depression. Journal of Medical Economics 16:62–74, 2013
34.
Lepine BA, Moreno RA, Campos RN, et al.: Treatment-resistant depression increases health costs and resource utilization. Revista Brasileira de Psiquiatria 34:379–388, 2012
35.
Papakostas GI, Petersen TJ, Farabaugh AH, et al.: Psychiatric comorbidity as a predictor of clinical response to nortriptyline in treatment-resistant major depressive disorder. Journal of Clinical Psychiatry 64:1357–1361, 2003
36.
Ivanova JI, Birnbaum HG, Kidolezi Y, et al.: Direct and indirect costs of employees with treatment-resistant and non-treatment-resistant major depressive disorder. Current Medical Research and Opinion 26:2475–2484, 2010
37.
Malone DA, Dougherty DD, Rezai AR, et al.: Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. Biological Psychiatry 65:267–275, 2009
38.
Papakostas GI, Petersen T, Pava J, et al.: Hopelessness and suicidal ideation in outpatients with treatment-resistant depression: prevalence and impact on treatment outcome. Journal of Nervous and Mental Disease 191:444–449, 2003
39.
DiazGranados N, Ibrahim LA, Brutsche NE, et al.: Rapid resolution of suicidal ideation after a single infusion of an N-methyl-D-aspartate antagonist in patients with treatment-resistant major depressive disorder. Journal of Clinical Psychiatry 71:1605–1611, 2010
40.
Ferrucci R, Bortolomasi M, Vergari M, et al.: Transcranial direct current stimulation in severe, drug-resistant major depression. Journal of Affective Disorders 118:215–219, 2009
41.
Prochazka H, Sjögren M, Agren H: Oral d-fenfluramine test in treatment-refractory depression. Plasma prolactin response compared in patients with and without suicide attempts and in a healthy reference group. Journal of Affective Disorders 57:201–208, 2000
42.
Kocsis JH, Gelenberg AJ, Rothbaum B, et al.: Chronic forms of major depression are still undertreated in the 21st century: systematic assessment of 801 patients presenting for treatment. Journal of Affective Disorders 110:55–61, 2008
43.
Bewernick BH, Kayser S, Sturm V, et al.: Long-term effects of nucleus accumbens deep brain stimulation in treatment-resistant depression: evidence for sustained efficacy. Neuropsychopharmacology 37:1975–1985, 2012
44.
Kopell BH, Halverson J, Butson CR, et al.: Epidural cortical stimulation of the left dorsolateral prefrontal cortex for refractory major depressive disorder. Neurosurgery 69:1015–1029, 2011
45.
Schindler F, Anghelescu IG: Lithium versus lamotrigine augmentation in treatment resistant unipolar depression: a randomized, open-label study. International Clinical Psychopharmacology 22:179–182, 2007
46.
Dorée JP, Des Rosiers J, Lew V, et al.: Quetiapine augmentation of treatment-resistant depression: a comparison with lithium. Current Medical Research and Opinion 23:333–341, 2007
47.
Karp JF, Whyte EM, Lenze EJ, et al.: Rescue pharmacotherapy with duloxetine for selective serotonin reuptake inhibitor nonresponders in late-life depression: outcome and tolerability. Journal of Clinical Psychiatry 69:457–463, 2008
48.
Mahmoud RA, Pandina GJ, Turkoz I, et al.: Risperidone for treatment-refractory major depressive disorder: a randomized trial. Annals of Internal Medicine 147:593–602, 2007
49.
Seidman SN, Miyazaki M, Roose SP: Intramuscular testosterone supplementation to selective serotonin reuptake inhibitor in treatment-resistant depressed men: randomized placebo-controlled clinical trial. Journal of Clinical Psychopharmacology 25:584–588, 2005
50.
Inoue T, Tsuchiya K, Miura J, et al.: Bromocriptine treatment of tricyclic and heterocyclic antidepressant-resistant depression. Biological Psychiatry 40:151–153, 1996
51.
Shelton RC, Tollefson GD, Tohen M, et al.: A novel augmentation strategy for treating resistant major depression. American Journal of Psychiatry 158:131–134, 2001
52.
Corya SA, Williamson D, Sanger TM, et al.: A randomized, double-blind comparison of olanzapine/fluoxetine combination, olanzapine, fluoxetine, and venlafaxine in treatment-resistant depression. Depression and Anxiety 23:364–372, 2006
53.
Lozano AM, Mayberg HS, Giacobbe P, et al.: Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression. Biological Psychiatry 64:461–467, 2008
54.
Taneja C, Papakostas GI, Jing Y, et al.: Cost-effectiveness of adjunctive therapy with atypical antipsychotics for acute treatment of major depressive disorder. Annals of Pharmacotherapy 46:642–649, 2012
55.
Swan J, Sorrell E, MacVicar B, et al.: “Coping with depression”: an open study of the efficacy of a group psychoeducational intervention in chronic, treatment-refractory depression. Journal of Affective Disorders 82:125–129, 2004
56.
Rush AJ, Bose A, Heydorn WE: Naturalistic study of the early psychiatric use of citalopram in the United States. Depression and Anxiety 16:121–127, 2002
57.
Bauer M, Bschor T, Kunz D, et al.: Double-blind, placebo-controlled trial of the use of lithium to augment antidepressant medication in continuation treatment of unipolar major depression. American Journal of Psychiatry 157:1429–1435, 2000
58.
Lenox-Smith A, Greenstreet L, Burslem K, et al.: Cost effectiveness of venlafaxine compared with generic fluoxetine or generic amitriptyline in major depressive disorder in the UK. Clinical Drug Investigation 29:173–184, 2009
59.
Revicki DA, Wood M: Patient-assigned health state utilities for depression-related outcomes: differences by depression severity and antidepressant medications. Journal of Affective Disorders 48:25–36, 1998
60.
Aziz M, Mehringer AM, Mozurkewich E, et al.: Cost-utility of 2 maintenance treatments for older adults with depression who responded to a course of electroconvulsive therapy: results from a decision analytic model. Canadian Journal of Psychiatry 50:389–397, 2005
61.
Benedict A, Arellano J, De Cock E, et al.: Economic evaluation of duloxetine versus serotonin selective reuptake inhibitors and venlafaxine XR in treating major depressive disorder in Scotland. Journal of Affective Disorders 120:94–104, 2010
62.
Nuijten MJ: Assessment of clinical guidelines for continuation treatment in major depression. Value in Health 4:281–294, 2001
63.
Sava FA, Yates BT, Lupu V, et al.: Cost-effectiveness and cost-utility of cognitive therapy, rational emotive behavioral therapy, and fluoxetine (Prozac) in treating depression: a randomized clinical trial. Journal of Clinical Psychology 65:36–52, 2009
64.
Corey-Lisle PK, Birnbaum HG, Greenberg PE, et al.: Identification of a claims data “signature” and economic consequences for treatment-resistant depression. Journal of Clinical Psychiatry 63:717–726, 2002
65.
Olchanski N, McInnis Myers M, Halseth M, et al.: The economic burden of treatment-resistant depression. Clinical Therapeutics 35:512–522, 2013
66.
Cancer Facts and Figures 2011. Atlanta, Ga, American Cancer Society, 2011
67.
American Diabetes Association: Economic costs of diabetes in the US in 2007. Diabetes Care 31:596–615, 2008
68.
Gillum LA, Gouveia C, Dorsey ER, et al.: NIH disease funding levels and burden of disease. PLoS ONE 6:e16837, 2011
69.
Pukrop R, Schlaak V, Möller-Leimkühler AM, et al.: Reliability and validity of quality of life assessed by the Short-Form 36 and the Modular System for Quality of Life in patients with schizophrenia and patients with depression. Psychiatry Research 119:63–79, 2003
70.
Birmaher B, Ryan ND, Williamson DE, et al.: Childhood and adolescent depression: a review of the past 10 years: part I. Journal of the American Academy of Child and Adolescent Psychiatry 35:1427–1439, 1996
71.
Vanheusden K, Mulder CL, van der Ende J, et al.: Young adults face major barriers to seeking help from mental health services. Patient Education and Counseling 73:97–104, 2008
72.
Fleury MJ, Grenier G, Bamvita JM, et al.: Comprehensive determinants of health service utilisation for mental health reasons in a Canadian catchment area. International Journal for Equity in Health 11:20, 2012
73.
Brent DA, Emslie GJ, Clarke GN, et al.: Predictors of spontaneous and systematically assessed suicidal adverse events in the treatment of SSRI-resistant depression in adolescents (TORDIA) study. American Journal of Psychiatry 166:418–426, 2009
74.
Wilke RA, Dolan ME: Genetics and variable drug response. JAMA 306:306–307, 2011
75.
Winner J, Allen JD, Altar CA, et al.: Psychiatric pharmacogenomics predicts health resource utilization of outpatients with anxiety and depression. Translational Psychiatry 3:e242, 2013
76.
Hall-Flavin DK, Winner JG, Allen JD, et al.: Using a pharmacogenomic algorithm to guide the treatment of depression. Translational Psychiatry 2:e172, 2012
77.
Hall-Flavin DK, Winner JG, Allen JD, et al.: Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting. Pharmacogenetics and Genomics 23:535–548, 2013
78.
Altar CA, Hornberger J, Shewade A, et al.: Clinical validity of cytochrome P450 metabolism and serotonin gene variants in psychiatric pharmacotherapy. International Review of Psychiatry 25:509–533, 2013
79.
Mrazek DA, Lerman C: Facilitating clinical implementation of pharmacogenomics. JAMA 306:304–305, 2011
80.
Simon GE, Perlis RH: Personalized medicine for depression: can we match patients with treatments? American Journal of Psychiatry 167:1445–1455, 2010
81.
Alegría M, Chatterji P, Wells K, et al.: Disparity in depression treatment among racial and ethnic minority populations in the United States. Psychiatric Services 59:1264–1272, 2008
82.
Berry JG, Bloom S, Foley S, et al.: Health inequity in children and youth with chronic health conditions. Pediatrics 126(suppl 3):S111–S119, 2010
83.
Williams DR, González HM, Neighbors H, et al.: Prevalence and distribution of major depressive disorder in African Americans, Caribbean blacks, and non-Hispanic whites: results from the National Survey of American Life. Archives of General Psychiatry 64:305–315, 2007
84.
Surault P: Mental health and social determinants [in French]. L'Encéphale 36(suppl):27–32, 2010
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Cover: Deep Cove Lobster Man, by N. C. Wyeth, ca. 1938. Oil on gessoed board (renaissance panel). Accession number 1939.16. Courtesy of the Pennsylvania Academy of Fine Arts, Philadelphia, Joseph E. Temple Fund.
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