Article April 15, 2010

Beyond Symptomatic Improvement: Assessing Real-World Outcomes in Patients With Major Depressive Disorder

Alan M. Langlieb; Christine J. Guico-Pabia

Prim Care Companion J Clin Psychiatry 2010;12(2):e1-e14

Article Abstract

Objective: To quantify the negative impact that major depressive disorder (MDD) has on quality of life, disability, and work, family, and overall psychosocial functioning. Available scales that assess these areas of impairment as they relate to patients with MDD are described.

Data Sources: PubMed searches were conducted using the following terms: (MDD OR major depressive disorder) AND (absenteeism OR absente*); AND (quality of life OR QOL); AND (psychosocial function*); AND (presente* OR presenteeism); AND (health care cost* OR [health care] cost*); AND (health outcome*); AND (functional outcome*); AND (family life); AND (disabil* OR disability); AND (work function*); AND (unemployment OR unemploy*). The literature search was conducted in July 2008 and was restricted to English language articles. There were no limits set on the dates of the search.

Study Selection: Two hundred twenty potential articles were identified. Among these studies, 48 presented primary data directly demonstrating the effect of MDD on quality of life, disability, and work, family, and overall psychosocial functioning.

Data Extraction: Primary data were compiled from these studies and are summarily described. Available scales that assess quality of life, disability, and work, family, and overall psychosocial functioning are also described.

Data Synthesis: MDD was found to be associated with significant disability and declines in functioning and quality of life. The Sheehan Disability Scale, the 36-item Short-Form Health Survey, and the Work Limitations Questionnaire were the most commonly used scales according to this review of the literature, but the majority of studies used direct and indirect disability measures, such as health care and other disability-related costs.

Conclusions: In addition to assessing symptomatic outcomes, physicians should routinely assess their depressed patients on “real-world” outcomes. The development of a concise functional outcome measure specific to MDD is necessary for busy clinical practices.

Prim Care Companion J Clin Psychiatry 2010;12(2):e1-e14

Submitted: April 14, 2009; accepted August 4, 2009.

Published online: April 15, 2010 (doi:10.4088/PCC.09r00826blu).

Corresponding author: Alan M. Langlieb, MD, The Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Baltimore, MD 21205 ([email protected]).

 

Beyond Symptomatic Improvement: Assessing Real-World Outcomes in Patients With Major Depressive Disorder

Objective: To quantify the negative impact that major depressive disorder (MDD) has on quality of life, disability, and work, family, and overall psychosocial functioning. Available scales that assess these areas of impairment as they relate to patients with MDD are described.

Data Sources: PubMed searches were conducted using the following terms: (MDD OR major depressive disorder) AND (absenteeism OR absente*); AND (quality of life OR QOL); AND (psychosocial function*); AND (presente* OR presenteeism); AND (health care cost* OR [health care] cost*); AND (health outcome*); AND (functional outcome*); AND (family life); AND (disabil* OR disability); AND (work function*); AND (unemployment OR unemploy*). The literature search was conducted in July 2008 and was restricted to English language articles. There were no limits set on the dates of the search.

Study Selection: Two hundred twenty potential articles were identified. Among these studies, 48 presented primary data directly demonstrating the effect of MDD on quality of life, disability, and work, family, and overall psychosocial functioning.

Data Extraction: Primary data were compiled from these studies and are summarily described. Available scales that assess quality of life, disability, and work, family, and overall psychosocial functioning are also described.

Data Synthesis: MDD was found to be associated with significant disability and declines in functioning and quality of life. The Sheehan Disability Scale, the 36-item Short-Form Health Survey, and the Work Limitations Questionnaire were the most commonly used scales according to this review of the literature, but the majority of studies used direct and indirect disability measures, such as health care and other disability-related costs.

Conclusions: In addition to assessing symptomatic outcomes, physicians should routinely assess their depressed patients on “real-world” outcomes. The development of a concise functional outcome measure specific to MDD is necessary for busy clinical practices.

Prim Care Companion J Clin Psychiatry 2010;12(2):e1-e14

Submitted: April 14, 2009; accepted August 4, 2009.

Published online: April 15, 2010 (doi:10.4088/PCC.09r00826blu).

Corresponding author: Alan M. Langlieb, MD, The Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Baltimore, MD 21205 ([email protected]).

According to the National Comorbidity Survey (NCS), major depressive disorder (MDD) has an estimated lifetime prevalence of 16%. NCS data also reveal that the majority of participants that met MDD criteria were currently employed and during the past year experienced some form of role impairment in work, family, or social functioning. The degree of impairment was commensurate with the severity of depressive symptomatology.1 Furthermore, the World Health Organization has estimated that, among the 10 most disabling diseases (eg, diabetes, tuberculosis, hepatitis, sexually transmitted diseases), MDD is responsible for 5% of the total global disease burden associated with these disorders2 and is ranked fourth among the leading causes of disease burden.3

Clinical Points

  • Major depressive disorder is associated with significant declines in functioning and quality of life.
  • In addition to measuring the severity of depressive symptoms, clinicians and researchers should assess depressed patients’ level of functioning and quality of life.
  • A number of scales are currently available that are valid and reliable measures of functioning and quality of life.

Despite the overwhelming evidence demonstrating that MDD exerts a significantly negative effect on functioning and quality of life (Table 1), when depressed patients are assessed, either in a clinical or research setting, the focus primarily remains on the severity of depressive symptoms, with significantly less attention being paid to the impact that MDD has on these “real-world” outcomes. Other areas of medicine (eg, cardiovascular medicine,4,5 diabetes6) have begun to expand the assessment of treatment outcomes from simply measuring symptomatic improvement to include a broader range of outcomes, thereby providing a useful example of how assessing these outcomes can help in the decision-making process of the various health care stakeholders (ie, physicians, employers, and payors/managed care plans) involved in the treatment of depressed patients.

The objective of this systematic review was to quantify the negative impact that MDD has on quality of life, disability, and work, family, and overall psychosocial functioning. Available scales that assess these areas of impairment as they relate to patients with MDD are also described.

Table 1a

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Table 1b

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Table 1c

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Table 1d

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Table 1e

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Table 1f

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METHOD

PubMed searches were conducted using the following terms: (MDD OR major depressive disorder) AND (absenteeism OR absente*); AND (quality of life OR QOL); AND (psychosocial function*); AND (presente* OR presenteeism); AND (health care cost* OR [health care] cost*); AND (health outcome*); AND (functional outcome*); AND (family life); AND (disabil* OR disability); AND (work function*); AND (unemployment OR unemploy*). The literature search was conducted in July 2008 and was restricted to English language articles. There were no limits set on the dates of the search.

Two hundred twenty potential articles were identified. Among these studies, 48 presented primary data directly demonstrating the effect of MDD on these outcomes. Primary data were compiled from these studies and are summarily described. Available scales that assess these outcomes are also described.

Costs Associated With MDD

The substantial direct and indirect health care costs associated with depression alone7-9 and comorbid with other conditions10-13 have been quantified by a number of large-scale evaluations. Correspondingly, depression also has been shown to negatively impact an individual’s overall health and can lead to increased costs for treating any co-occurring disorders. For instance, in 2 studies that assessed diabetic patients with and without comorbid depression, significantly higher health care costs14 and worse clinical outcomes, including higher mortality rates,15 were observed in those with a co-occurring depressive disorder.

In a large-scale assessment of employees of a major corporation,10 the per-capita health and disability costs (including direct health care expenditures and sick/disability days) associated with depression were $5,415 annually, equivalent to diabetes ($5,472), heart disease ($5,523), and back problems ($4,388), but significantly greater than hypertension ($3,372; P=.002) and a category containing “all other” reasons for filing a health claim ($1,292; P<.001). In addition, when MDD co-occurred with one of these general medical conditions, the associated health care costs increased nearly 2-fold compared to patients with the medical disorder alone. The resulting cost to the corporation was $2.2 million.10,11 In addition, other studies have demonstrated a significant association between MDD, cardiac death,16,17 and total mortality.16 Beyond medical comorbidities, MDD is also commonly comorbid with other psychiatric disorders. In particular, MDD commonly co-occurs with generalized anxiety disorder, which results in significant disability.18

Impaired Functioning and Quality of Life Associated With MDD

The terms functioning and quality of life are often used interchangeably; however, the disability associated with each and the means in which they are assessed are multidimensional and can differ significantly. Assessments of functioning generally include performance-based metrics, such as one’s ability to engage in expected or usual responsibilities at work or home, and can be assessed using objective measures, such as days of work missed, or subjectively, using patient-rated assessments. However, functioning does not distinctly involve work performance; functioning in other areas, such as in familial, societal, and marital roles, also can be adversely affected by MDD. Quality-of-life measures, on the other hand, generally describe the subjective quality of an individual’s day-to-day experiences, which involve enjoyment and satisfaction with one’s life, but also can be related to the patient’s performance in his or her expected role.

Work Functioning

A number of studies have empirically demonstrated that MDD not only negatively impacts those who are currently employed19-22 but also is associated with an increased risk for job loss.23 One large-scale analysis of NCS data suggested that those in the middle of their careers are more likely than their younger counterparts to lose their jobs as the result of a major depressive episode.24 The most obvious way that MDD impacts work performance is the elevated rates of absenteeism among depressed employees.9,10 However, the negative effect that MDD has on work performance extends beyond whether an employee is present to perform his or her job.

Presenteeism describes the impaired functioning that employees experience when they attend work but suboptimally perform their daily activities, in this case, due to their depressive symptoms. Depressed employees have been shown to be particularly prone to detriments in mental-interpersonal and time management tasks, as well as overall job performance, compared to nondepressed employees.25-28 In 1 study conducted in a large company, the lost productive time associated with MDD was reported to be nearly 6 hours per week, at a cost of $44 billion annually.28 In addition, less severe forms of depression (ie, subthreshold depressive symptoms,29,30 minor depression,31-33 and dysthymia34) also have been shown to negatively impact work functioning.

In 1 large-scale work performance study, NCS participants currently experiencing a depressive episode were compared to those with episodes that resolved >1 to 6 months ago, >6 to 12 months ago, and >12 months ago. These patients had responded to treatment but continued to experience significant residual symptoms that were more pronounced than the level seen in the euthymic controls. Patients who were currently experiencing a depressive episode were significantly more likely to experience lost days than healthy controls and those with residual symptoms; however, compared to healthy controls, depressed patients and even those with residual symptoms were significantly more likely to experience difficult days and cutback days (in which the depressed patient did not get as much done as usual) than healthy controls.29,30

A growing body of data has demonstrated that depressive symptoms include impairments in cognitive functioning that can result in declining work performance. A recently published study that assessed untreated MDD patients using work performance measures following an error or receipt of negative feedback demonstrates that dysfunctional information processing associated with depression can lead to declines in productivity.19 This study and a number of other neuroimaging studies have suggested that these maladaptive cognitive processes involve areas of the brain that are thought to be associated with the symptoms of MDD (eg, the prefrontal cortex, anterior cingulate cortex, hippocampus).19-22

Psychosocial Functioning

The components of psychosocial functioning vary between scales and sometimes overlap with assessments of work performance but are mainly differentiated by the assessment of other areas of functioning beyond the workplace. Several studies have been conducted that support the claim that MDD has a negative impact on overall social functioning.35,36 Results from an analysis of patients experiencing different levels of depressive symptomatology (ie, subthreshold depressive symptoms, minor depression/dysthymia, and MDD) have suggested that psychosocial disability increases correspondingly with the severity of depressive symptoms.37 In a more recently conducted study, which assessed patients with MDD and bipolar I and II disorder, those experiencing MDD were found to experience significant psychosocial impairment during the majority of follow-up visits.38

Quality of Life

Quality of life is difficult to concisely define due to its subjective nature and the overlap between assessing functional outcomes; therefore, measuring quality of life is more complex than the other outcomes described. For example, assessing the quality of a person’s life without examining how the individual functions in his or her expected roles, in either family life or work performance, is difficult.

The impact of a major depressive episode on health-related quality of life in individuals with39-48 or without39-43 a general medical condition has been well established in the literature, and treating MDD to a full remission of symptoms can improve quality of life to a greater extent than when significant residual symptoms are present.49,50

Treatment of the Functional Disability Associated With MDD

A number of empirically supported treatment options have demonstrated effectiveness in alleviating the disability caused by MDD,30,51-56 as well as in lowering health care costs,49,57-65 improving quality of life,50,66,67 and decreasing absenteeism in depressed patients,49,68 particularly in those who receive early and adequate treatment.69,70 For example, the Sequenced Treatment Alternatives to Relieve Depression trial, a large-scale assessment of an MDD treatment algorithm conducted in a real-world clinical setting, demonstrated that following sequential treatment alternatives for patients not reaching remission with first-line treatment can lead to significant improvements in functioning and quality of life.53,71

Despite increased usage of the multiple antidepressant medications available to patients and improvements in empirically supported treatment guidelines and algorithms, data are available that demonstrate that a disproportionately large number of patients continue to receive inadequate treatment for their depressive episodes. In a cross-sectional analysis of medical records from 2 cohorts of depressed patients (ie, 1993 to 1994 and 2003 to 2004), an increase in the use of adequate antidepressant doses was observed; however, the use of sequential antidepressant treatment options and psychotherapy remained low.72

An effective way of lowering the costs associated with MDD is to encourage physicians to use guideline-derived forms of treatment and utilize enhanced treatment options, such as incorporating care managers for monitoring the patient’s symptoms, adverse events, and adherence.73 In addition, 1 study demonstrated that by taking steps to improve employee access to effective depression treatment—for example, by lowering copayments and using a selective contracting network and a mental health destigmatization program—the likelihood of initiating treatment and having more mental health visits increased.74

The relationship between MDD, functional disability, and impaired quality of life has been suggested to be bidirectional. In addition to MDD negatively impacting functioning and quality of life, the presence of these impairments at baseline has been linked to poor antidepressant treatment response.53,75,76 It also has been suggested that functional impairment and a lower quality of life are associated with an elevated risk for the recurrence of a major depressive episode.77-79

Assessing Declines in Functioning and Quality of Life Associated With MDD

Table 2 describes some commonly used functional outcome measures and assessments of quality of life. The 36-item Short-Form Health Survey (SF-36)80 was the most widely used scale in the studies identified during our systematic review of the literature. Its length and complexity have been impediments to its regular use in clinical settings; however, a shortened 12-item version (SF-12) is also available that may be better suited for use in busy practice settings.81 In addition, the Sheehan Disability Scale (SDS)82 and the Work Limitations Questionnaire (WLQ)83 were commonly used. The SDS is widely used in research settings because it has been shown to be sensitive to treatment effects, and its concise means of assessing the overall level of functioning make it desirable for use in clinical settings as well.

Table 2

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The World Health Organization 5-item Well-Being Index,84 Social Adjustment Scale-Self-Report (SAS-SR),85 and Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q)86 are commonly used to assess psychosocial functioning and quality of life, whereas the Endicott Work Productivity Scale,87 Work Productivity and Activity Impairment Questionnaire,88 and WLQ83 are commonly used assessments of work dysfunction.

Perhaps the most familiar means of assessing the functional declines associated with psychiatric disorders is Axis V of the multiaxial diagnostic methodology used in the fourth edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders.89 The Global Assessment of Functioning (GAF) asks the clinician to rate the level of functioning in relation to symptom severity. This combination of 2 distinct outcomes on 1 axis has been the primary criticism of the GAF, as a separation between these outcomes is important to obtaining an accurate level of functional disability independent of symptom severity. In addition, the Global Assessment of Relational Functioning (GARF) and Social and Occupational Functioning Assessment Scale (SOFAS) were designed as supplemental assessments of functioning to be used in conjunction with the GAF.89 The GARF was specifically designed to assess familial and other long-term relationships, whereas the SOFAS was designed to assess social and occupational functioning independent of symptom severity.89

Issues Associated With Using “Real-World” Outcome Measures

Despite the benefits of assessing functioning and quality of life to the various stakeholders involved with the treatment of MDD, the potential issues associated with using such scales must be noted. Some of the commonly used assessment tools described above have some unmet needs. Namely, they can be cumbersome for use in the clinical setting because they are generally too lengthy to administer in the ever-lessening duration of clinical visits. As was previously mentioned, a number of these scales, such as the SF-36, WLQ, SAS-SR, and Q-LES-Q, are thought to be too lengthy for use during clinical visits. In addition, there is some ambiguity as to what these scales actually measure, mainly due to the lack of consistency in the items they use and the lack of a clear gold standard. On the other hand, some scales are too specific. The assessments of work functioning, for example, focus too narrowly on the area of work dysfunction to be used alone in a clinical setting wherein a level of overall functional status is desired.

When performing follow-up assessments using these scales, it is important to note that a lag time in improvements in functional impairment has been observed in relation to improvements in depressive symptomatology. When assessing functioning, >8 weeks may be required before improvements are observed, whereas improvements in depressive symptoms generally occur sooner.90,91 A secondary analysis of data from a randomized trial investigating selective serotonin reuptake inhibitor treatment,92 which calls for a broader definition of depression remission that expands beyond symptom severity, demonstrated that depressive symptoms improve in synchrony and are correlated with work functioning, even though depressive symptoms improved to a greater degree. It is also important to note that the majority of the scales described above are not designed to diagnose MDD and are meant only to be used for screening and to assess and monitor changes in disability. If the results are suggestive of a depressive disorder, then a validated diagnostic assessment tool should be used to make a proper diagnosis.

CONCLUSIONS

The development of an assessment tool that can address the issues described above would be a benefit to the various parties involved with the treatment of MDD (eg, researchers, patients, health care plans). The SDS has many positive attributes but has not yet been widely accepted as the gold standard in assessing disability in patients with MDD. The limitations of the SDS include its assessment of patients on only 3 domains of functioning and the lack of a depression-specific focus. The SF-12, a shortened version of the SF-36, is another valuable assessment tool due to its more detailed assessment of disability yet compact enough length for use in clinical practice. Perhaps creating a “hybrid” scale adopting the best of various options that can become a standard measure for assessing the disability associated with MDD will become necessary. Along with assessing the impact on the emotional and physical symptoms of MDD, assessing functional disability and declines in quality of life should continue to become a routine part of clinical care and outcome measures in clinical trials that assess the efficacy of antidepressant treatment.43,78,93,94 As calls for the measurement-based care of MDD continue, particularly for primary care physicians, a thorough assessment of the impact that MDD has on a patient’s life will become a necessity.

Author affiliations: The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (Dr Langlieb) and Pfizer Inc, formerly Wyeth Research, Collegeville, Pennsylvania (Dr Guico-Pabia).

Author contributions: Drs Langlieb and Guico-Pabia equally contributed to the study by analyzing and interpreting data, drafting and revising the manuscript, and obtaining funding.

Potential conflicts of interest: Dr Langlieb serves on the advisory boards for Eli Lilly and Pfizer Inc. Dr Guico-Pabia is an employee of Pfizer Inc, formerly Wyeth Research.

Funding/support: This analysis was supported by Wyeth Research, Collegeville, Pennsylvania, which was acquired by Pfizer Inc in October 2009.

Acknowledgment: Medical writing/editing support was funded by Wyeth Research. Dennis A. Stancavish, MA, provided writing support and editing support was provided by Jennifer B. Karpinski, BA, both of Embryon, LLC, A Division of Advanced Health Media, LLC (formerly Medesta Publications Group, A Business of Advogent).

REFERENCES

1. 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. PubMed doi:10.1001/jama.289.23.3095

2. Murray CJ, Lopez AD. Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study. Lancet. 1997;349(9063):1436-1442. PubMed doi:10.1016/S0140-6736(96)07495-8

3. World Health Organization. The World Health Report: 2001-Mental Health: New Understanding, New Hope. Geneva, Switzerland: World Health Organization; 2001.

4. Thrall G, Lane D, Carroll D, et al. Quality of life in patients with atrial fibrillation: a systematic review. Am J Med. 2006;119(5):448-519, e1-e19. PubMed doi:10.1016/j.amjmed.2005.10.057

5. Williams RG, Pearson GD, Barst RJ, et al. Report of the National Heart, Lung, and Blood Institute Working Group on research in adult congenital heart disease. J Am Coll Cardiol. 2006;47(4):701-707. PubMed doi:10.1016/j.jacc.2005.08.074

6. Huang IC, Hwang CC, Wu MY, et al. Diabetes-specific or generic measures for health-related quality of life? evidence from psychometric validation of the D-39 and SF-36. Value Health. 2008;11(3):450-461. PubMed doi:10.1111/j.1524-4733.2007.00261.x

7. Greenberg PE, Kessler RC, Birnbaum HG, et al. The economic burden of depression in the United States: how did it change between 1990 and 2000? J Clin Psychiatry. 2003;64(12):1465-1475. PubMed

8. Birnbaum HG, Leong SA, Greenberg PE. The economics of women and depression: an employer’s perspective. J Affect Disord. 2003;74(1):15-22. PubMed doi:10.1016/S0165-0327(02)00427-5

9. 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. PubMed doi:10.1176/appi.ajp.163.9.1561

10. 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. PubMed doi:10.1176/appi.ajp.157.8.1274

11. Gameroff MJ, Olfson M. Major depressive disorder, somatic pain, and health care costs in an urban primary care practice. J Clin Psychiatry. 2006;67(8):1232-1239. PubMed

12. Emptage NP, Sturm R, Robinson RL. Depression and comorbid pain as predictors of disability, employment, insurance status, and health care costs. Psychiatr Serv. 2005;56(4):468-474. PubMed doi:10.1176/appi.ps.56.4.468

13. Katon WJ, Lin E, Russo J, et al. Increased medical costs of a population-based sample of depressed elderly patients. Arch Gen Psychiatry. 2003;60(9):897-903. PubMed doi:10.1001/archpsyc.60.9.897

14. Simon GE, Katon WJ, Lin EH, et al. Diabetes complications and depression as predictors of health service costs. Gen Hosp Psychiatry. 2005;27(5):344-351. PubMed doi:10.1016/j.genhosppsych.2005.04.008

15. Katon WJ, Rutter C, Simon G, et al. The association of comorbid depression with mortality in patients with type 2 diabetes. Diabetes Care. 2005;28(11):2668-2672. PubMed doi:10.2337/diacare.28.11.2668

16. Barefoot JC, Helms MJ, Mark DB, et al. Depression and long-term mortality risk in patients with coronary artery disease. Am J Cardiol. 1996;78(6):613-617. PubMed doi:10.1016/S0002-9149(96)00380-3

17. Kaufmann MW, Fitzgibbons JP, Sussman EJ, et al. Relation between myocardial infarction, depression, hostility, and death. Am Heart J. 1999;138(3, pt 1):549-554. PubMed doi:10.1016/S0002-8703(99)70159-6

18. Wittchen HU, Carter RM, Pfister H, et al. Disabilities and quality of life in pure and comorbid generalized anxiety disorder and major depression in a national survey. Int Clin Psychopharmacol. 2000;15(6):319-328. PubMed doi:10.1097/00004850-200015060-00002

19. Holmes AJ, Pizzagalli DA. Spatiotemporal dynamics of error processing dysfunctions in major depressive disorder. Arch Gen Psychiatry. 2008;65(2):179-188. PubMed doi:10.1001/archgenpsychiatry.2007.19

20. Mondal S, Sharma VK, Das S, et al. Neuro-cognitive functions in patients of major depression. Indian J Physiol Pharmacol. 2007;51(1):69-75. PubMed

21. Smith DJ, Muir WJ, Blackwood DH. Neurocognitive impairment in euthymic young adults with bipolar spectrum disorder and recurrent major depressive disorder. Bipolar Disord. 2006;8(1):40-46. PubMed doi:10.1111/j.1399-5618.2006.00275.x

22. Wang PS, Beck AL, Berglund P, et al. Effects of major depression on moment-in-time work performance. Am J Psychiatry. 2004;161(10):1885-1891. PubMed doi:10.1176/appi.ajp.161.10.1885

23. Lerner D, Adler DA, Chang H, et al. Unemployment, job retention, and productivity loss among employees with depression. Psychiatr Serv. 2004;55(12):1371-1378. PubMed doi:10.1176/appi.ps.55.12.1371

24. Marcotte DE, Wilcox-Gök V, Redmon PD. Prevalence and patterns of major depressive disorder in the United States labor force. J Ment Health Policy Econ. 1999;2(3):123-131. PubMed doi:10.1002/(SICI)1099-176X(199909)2:3<123::AID-MHP55>3.0.CO;2-8

25. Adler DA, McLaughlin TJ, Rogers WH, et al. Job performance deficits due to depression. Am J Psychiatry. 2006;163(9):1569-1576. PubMed doi:10.1176/appi.ajp.163.9.1569

26. Berndt ER, Finkelstein SN, Greenberg PE, et al. Workplace performance effects from chronic depression and its treatment. J Health Econ. 1998;17(5):511-535. PubMed doi:10.1016/S0167-6296(97)00043-X

27. Druss BG, Schlesinger M, Allen HM Jr. Depressive symptoms, satisfaction with health care, and 2-year work outcomes in an employed population. Am J Psychiatry. 2001;158(5):731-734. PubMed doi:10.1176/appi.ajp.158.5.731

28. Stewart WF, Ricci JA, Chee E, et al. Cost of lost productive work time among US workers with depression. JAMA. 2003;289(23):3135-3144. PubMed doi:10.1001/jama.289.23.3135

29. Mojtabai R. Residual symptoms and impairment in major depression in the community. Am J Psychiatry. 2001;158(10):1645-1651. PubMed doi:10.1176/appi.ajp.158.10.1645

30. Wells KB, Stewart A, Hays RD, et al. The functioning and well-being of depressed patients: results from the Medical Outcomes Study. JAMA. 1989;262(7):914-919. PubMed doi:10.1001/jama.262.7.914

31. Backenstrass M, Frank A, Joest K, et al. A comparative study of nonspecific depressive symptoms and minor depression regarding functional impairment and associated characteristics in primary care. Compr Psychiatry. 2006;47(1):35-41. PubMed doi:10.1016/j.comppsych.2005.04.007

32. Cuijpers P, de Graaf R, van Dorsselaer S. Minor depression: risk profiles, functional disability, health care use and risk of developing major depression. J Affect Disord. 2004;79(1-3):71-79. PubMed doi:10.1016/S0165-0327(02)00348-8

33. Wagner HR, Burns BJ, Broadhead WE, et al. Minor depression in family practice: functional morbidity, co-morbidity, service utilization and outcomes. Psychol Med. 2000;30(6):1377-1390. PubMed doi:10.1017/S0033291799002998

34. Adler DA, Irish J, McLaughlin TJ, et al. The work impact of dysthymia in a primary care population. Gen Hosp Psychiatry. 2004;26(4):269-276. PubMed doi:10.1016/j.genhosppsych.2004.04.004

35. Spitzer RL, Kroenke K, Linzer M, et al. Health-related quality of life in primary care patients with mental disorders: results from the PRIME-MD 1000 Study. JAMA. 1995;274(19):1511-1517. PubMed doi:10.1001/jama.274.19.1511

36. Saarijärvi S, Salminen JK, Toikka T, et al. Health-related quality of life among patients with major depression. Nord J Psychiatry. 2002;56(4):261-264. PubMed doi:10.1080/08039480260242741

37. Judd LL, Akiskal HS, Zeller PJ, et al. Psychosocial disability during the long-term course of unipolar major depressive disorder. Arch Gen Psychiatry. 2000;57(4):375-380. PubMed doi:10.1001/archpsyc.57.4.375

38. Judd LL, Schettler PJ, Solomon DA, et al. Psychosocial disability and work role function compared across the long-term course of bipolar I, bipolar II and unipolar major depressive disorders. J Affect Disord. 2008;108(1-2):49-58. PubMed doi:10.1016/j.jad.2007.06.014

39. Cronin-Stubbs D, de Leon CF, Beckett LA, et al. Six-year effect of depressive symptoms on the course of physical disability in community-living older adults. Arch Intern Med. 2000;160(20):3074-3080. PubMed doi:10.1001/archinte.160.20.3074

40. Katon W, Lin EH, Kroenke K. The association of depression and anxiety with medical symptom burden in patients with chronic medical illness. Gen Hosp Psychiatry. 2007;29(2):147-155. PubMed doi:10.1016/j.genhosppsych.2006.11.005

41. Stein MB, Cox BJ, Afifi TO, et al. Does co-morbid depressive illness magnify the impact of chronic physical illness? a population-based perspective. Psychol Med. 2006;36(5):587-596. PubMed doi:10.1017/S0033291706007239

42. Strine TW, Chapman DP, Kobau R, et al. Depression, anxiety, and physical impairments and quality of life in the US noninstitutionalized population. Psychiatr Serv. 2004;55(12):1408-1413. PubMed doi:10.1176/appi.ps.55.12.1408

43. Trivedi MH, Rush AJ, Wisniewski SR, et al. Factors associated with health-related quality of life among outpatients with major depressive disorder: a STAR*D report. J Clin Psychiatry. 2006;67(2):185-195. PubMed

44. Baune BT, Adrian I, Jacobi F. Medical disorders affect health outcome and general functioning depending on comorbid major depression in the general population. J Psychosom Res. 2007;62(2):109-118. PubMed doi:10.1016/j.jpsychores.2006.09.014

45. Beekman AT, Penninx BW, Deeg DJ, et al. The impact of depression on the well-being, disability and use of services in older adults: a longitudinal perspective. Acta Psychiatr Scand. 2002;105(1):20-27. PubMed doi:10.1034/j.1600-0447.2002.10078.x

46. Dorenlot P, Harboun M, Bige V, et al. Major depression as a risk factor for early institutionalization of dementia patients living in the community. Int J Geriatr Psychiatry. 2005;20(5):471-478. PubMed doi:10.1002/gps.1238

47. Egede LE. Major depression in individuals with chronic medical disorders: prevalence, correlates and association with health resource utilization, lost productivity and functional disability. Gen Hosp Psychiatry. 2007;29(5):409-416. PubMed doi:10.1016/j.genhosppsych.2007.06.002

48. Papapetropoulos S, Ellul J, Argyriou AA, et al. The effect of depression on motor function and disease severity of Parkinson’s disease. Clin Neurol Neurosurg. 2006;108(5):465-469. PubMed doi:10.1016/j.clineuro.2005.08.002

49. 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. PubMed doi:10.1016/S0163-8343(00)00072-4

50. Angermeyer MC, Holzinger A, Matschinger H, et al. Depression and quality of life: results of a follow-up study. Int J Soc Psychiatry. 2002;48(3):189-199. PubMed doi:10.1177/002076402128783235

51. Dombrovski AY, Lenze EJ, Dew MA, et al. Maintenance treatment for old-age depression preserves health-related quality of life: a randomized, controlled trial of paroxetine and interpersonal psychotherapy. J Am Geriatr Soc. 2007;55(9):1325-1332. PubMed doi:10.1111/j.1532-5415.2007.01292.x

52. Keller MB, Trivedi MH, Thase ME, et al. The Prevention of Recurrent Episodes of Depression with Venlafaxine for Two Years (PREVENT) study: outcomes from the 2-year and combined maintenance phases. J Clin Psychiatry. 2007;68(8):1246-1256. PubMed doi:10.4088/JCP.v68n0812

53. 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. PubMed doi:10.1176/appi.ajp.163.1.28

54. Wang PS, Patrick A, Avorn J, et al. The costs and benefits of enhanced depression care to employers. Arch Gen Psychiatry. 2006;63(12):1345-1353. PubMed doi:10.1001/archpsyc.63.12.1345

55. Wang PS, Simon GE, Avorn J, et al. Telephone screening, outreach, and care management for depressed workers and impact on clinical and work productivity outcomes: a randomized controlled trial. JAMA. 2007;298(12):1401-1411. PubMed doi:10.1001/jama.298.12.1401

56. Zhang M, Rost KM, Fortney JC. Earnings changes for depressed individuals treated by mental health specialists. Am J Psychiatry. 1999;156(1):108-114. PubMed

57. Goldman W, McCulloch J, Cuffel B, et al. Outpatient utilization patterns of integrated and split psychotherapy and pharmacotherapy for depression. Psychiatr Serv. 1998;49(4):477-482. PubMed

58. Hankin JR, Kessler LG, Goldberg ID, et al. A longitudinal study of offset in the use of nonpsychiatric services following specialized mental health care. Med Care. 1983;21(11):1099-1110. PubMed doi:10.1097/00005650-198311000-00006

59. Leon AC, Walkup JT, Portera L. Assessment and treatment of depression in disability claimants: a cost-benefit simulation study. J Nerv Ment Dis. 2002;190(1):3-9. PubMed doi:10.1097/00005053-200201000-00002

60. Von Korff M, Katon W, Bush T, et al. Treatment costs, cost offset, and cost-effectiveness of collaborative management of depression. Psychosom Med. 1998;60(2):143-149. PubMed

61. Von Korff M, Katon W, Rutter C, et al. Effect on disability outcomes of a depression relapse prevention program. Psychosom Med. 2003;65(6):938-943. PubMed doi:10.1097/01.PSY.0000097336.95046.0C

62. Araya R, Flynn T, Rojas G, et al. Cost-effectiveness of a primary care treatment program for depression in low-income women in Santiago, Chile. Am J Psychiatry. 2006;163(8):1379-1387. PubMed doi:10.1176/appi.ajp.163.8.1379

63. 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. Can J Psychiatry. 2005;50(7):389-397. PubMed

64. Mitchell J, Greenberg J, Finch K, et al. Effectiveness and economic impact of antidepressant medications: a review. Am J Manag Care. 1997;3(2):323-330, quiz 331. PubMed

65. von Knorring L, Akerblad AC, Bengtsson F, et al. Cost of depression: effect of adherence and treatment response. Eur Psychiatry. 2006;21(6):349-354. PubMed doi:10.1016/j.eurpsy.2006.04.005

66. Berlim MT, Pargendler J, Brenner J, et al. Significant improvement in the quality of life of Brazilian depressed outpatients 12 weeks following the start of antidepressants. Psychiatry Res. 2007;153(3):253-259. PubMed doi:10.1016/j.psychres.2006.07.006

67. Vos T, Haby MM, Barendregt JJ, et al. The burden of major depression avoidable by longer-term treatment strategies. Arch Gen Psychiatry. 2004;61(11):1097-1103. PubMed doi:10.1001/archpsyc.61.11.1097

68. Claxton AJ, Chawla AJ, Kennedy S. Absenteeism among employees treated for depression. J Occup Environ Med. 1999;41(7):605-611. PubMed doi:10.1097/00043764-199907000-00009

69. Dewa CS, Hoch JS, Lin E, et al. Pattern of antidepressant use and duration of depression-related absence from work. Br J Psychiatry. 2003;183(6):507-513. PubMed doi:10.1192/bjp.183.6.507

70. Rizzo JA, Abbott TA 3rd, Pashko S. Labour productivity effects of prescribed medicines for chronically ill workers. Health Econ. 1996;5(3):249-265. PubMed doi:10.1002/(SICI)1099-1050(199605)5:3<249::AID-HEC203>3.0.CO;2-A

71. Trivedi MH, Fava M, Wisniewski SR, et al. STAR*D Study Team. Medication augmentation after the failure of SSRIs for depression. N Engl J Med. 2006;354(12):1243-1252. PubMed doi:10.1056/NEJMoa052964

72. Honkonen TI, Aro TA, Isometsä ET, et al. Quality of treatment and disability compensation in depression: comparison of 2 nationally representative samples with a 10-year interval in Finland. J Clin Psychiatry. 2007;68(12):1886-1893. PubMed doi:10.4088/JCP.v68n1208

73. Lo Sasso AT, Rost K, Beck A. Modeling the impact of enhanced depression treatment on workplace functioning and costs: a cost-benefit approach. Med Care. 2006;44(4):352-358. PubMed doi:10.1097/01.mlr.0000204049.30620.1e

74. Lo Sasso AT, Lindrooth RC, Lurie IZ, et al. Expanded mental health benefits and outpatient depression treatment intensity. Med Care. 2006;44(4):366-372. PubMed doi:10.1097/01.mlr.0000204083.55544.f8

75. Bagby RM, Ryder AG, Cristi C. Psychosocial and clinical predictors of response to pharmacotherapy for depression. J Psychiatry Neurosci. 2002;27(4):250-257. PubMed

76. Lenze EJ, Miller MD, Dew MA, et al. Subjective health measures and acute treatment outcomes in geriatric depression. Int J Geriatr Psychiatry. 2001;16(12):1149-1155. PubMed doi:10.1002/gps.503

77. Solomon DA, Leon AC, Endicott J, et al. Psychosocial impairment and recurrence of major depression. Compr Psychiatry. 2004;45(6):423-430. PubMed doi:10.1016/j.comppsych.2004.07.002

78. Solomon DA, Leon AC, Coryell W, et al. Predicting recovery from episodes of major depression. J Affect Disord. 2008;107(1-3):285-291. PubMed doi:10.1016/j.jad.2007.09.001

79. Sotsky SM, Glass DR, Shea MT, et al. Patient predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH Treatment of Depression Collaborative Research Program. Am J Psychiatry. 1991;148(8):997-1008. PubMed

80. Aaronson NK, Muller M, Cohen PD, et al. Translation, validation, and norming of the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. J Clin Epidemiol. 1998;51(11):1055-1068. PubMed doi:10.1016/S0895-4356(98)00097-3

81. 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. PubMed doi:10.1097/00005650-199206000-00002

82. Sheehan DV. Sheehan Disability Scale. In: Rush AJ, Pincus HA, First MB, et al, eds. Handbook of Psychiatric Measures. 1st ed. Washington, DC: American Psychiatric Association; 2000:113-115.

83. Lerner D, Amick BC 3rd, Rogers WH, et al. The Work Limitations Questionnaire. Med Care. 2001;39(1):72-85. PubMed doi:10.1097/00005650-200101000-00009

84. World Health Organization. Wellbeing Measures in Primary Health Care/the Depcare Project. Copenhagen, Denmark: WHO Regional Office for Europe; 1998.

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

86. 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

87. Endicott J, Nee J. Endicott Work Productivity Scale (EWPS): a new measure to assess treatment effects. Psychopharmacol Bull. 1997;33(1):13-16. PubMed

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

89. American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC: American Psychiatric Association; 1994.

90. Bech P, Lunde M, Undén M. Social Adaptation Self-evaluation Scale (SASS): psychometric analysis as outcome measure in the treatment of patients with major depression in the remission phase. Int J Psychiatry Clin Pract. 2002;6:141-146. doi:10.1080/136515002760276063

91. 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. PubMed doi:10.1016/S0006-3223(01)01291-4

92. Aikens JE, Kroenke K, Nease DE Jr, et al. Trajectories of improvement for six depression-related outcomes. Gen Hosp Psychiatry. 2008;30(1):26-31. PubMed doi:10.1016/j.genhosppsych.2007.10.003

93. Bech P. Social functioning: should it become an endpoint in trials of antidepressants? CNS Drugs. 2005;19(4):313-324. PubMed doi:10.2165/00023210-200519040-00004

94. Weissman MM. Social functioning and the treatment of depression. J Clin Psychiatry. 2000;61(suppl 1):33-38. PubMed

95. Arnow BA, Hunkeler EM, Blasey CM, et al. Comorbid depression, chronic pain, and disability in primary care. Psychosom Med. 2006;68(2):262-268. PubMed doi:10.1097/01.psy.0000204851.15499.fc

96. Breslau N, Lipton RB, Stewart WF, et al. Comorbidity of migraine and depression: investigating potential etiology and prognosis. Neurology. 2003;60(8):1308-1312. PubMed

97. Breslin FC, Gnam W, Franche RL, et al. Depression and activity limitations: examining gender differences in the general population. Soc Psychiatry Psychiatr Epidemiol. 2006;41(8):648-655. PubMed doi:10.1007/s00127-006-0079-6

98. Burton WN, Pransky G, Conti DJ, et al. The association of medical conditions and presenteeism. J Occup Environ Med. 2004;46(suppl 6):S38-S45. PubMed doi:10.1097/01.jom.0000126687.49652.44

99. Carta MG, Hardoy MC, Kovess V, et al. Could health care costs for depression be decreased if the disorder were correctly diagnosed and treated? Soc Psychiatry Psychiatr Epidemiol. 2003;38(9):490-492. PubMed doi:10.1007/s00127-003-0662-z

100. Cramer JA, Blum D, Reed M, et al. Epilepsy Impact Project Group. The influence of comorbid depression on seizure severity. Epilepsia. 2003;44(12):1578-1584. PubMed doi:10.1111/j.0013-9580.2003.28403.x

101. Druss BG, Rosenheck RA. Patterns of health care costs associated with depression and substance abuse in a national sample. Psychiatr Serv. 1999;50(2):214-218. PubMed

102. Egede LE. Diabetes, major depression, and functional disability among US adults. Diabetes Care. 2004;27(2):421-428. PubMed doi:10.2337/diacare.27.2.421

103. Ford JD, Trestman RL, Steinberg K, et al. Prospective association of anxiety, depressive, and addictive disorders with high utilization of primary, specialty and emergency medical care. Soc Sci Med. 2004;58(11):2145-2148. PubMed doi:10.1016/j.socscimed.2003.08.017

104. Frasure-Smith N, Lespérance F, Talajic M. Depression following myocardial infarction: impact on 6-month survival. JAMA. 1993;270(15):1819-1825. PubMed doi:10.1001/jama.270.15.1819

105. Haarasilta L, Marttunen M, Kaprio J, et al. Major depressive episode and physical health in adolescents and young adults: results from a population-based interview survey. Eur J Public Health. 2005;15(5):489-493. PubMed doi:10.1093/eurpub/cki041

106. Hoge CW, Lesikar SE, Guevara R, et al. Mental disorders among US military personnel in the 1990s: association with high levels of health care utilization and early military attrition. Am J Psychiatry. 2002;159(9):1576-1583. PubMed doi:10.1176/appi.ajp.159.9.1576

107. Janssens AC, van Doorn PA, de Boer JB, et al. Anxiety and depression influence the relation between disability status and quality of life in multiple sclerosis. Mult Scler. 2003;9(4):397-403. PubMed doi:10.1191/1352458503ms930oa

108. Keenan-Miller D, Hammen CL, Brennan PA. Health outcomes related to early adolescent depression. J Adolesc Health. 2007;41(3):256-262. PubMed doi:10.1016/j.jadohealth.2007.03.015

109. Kessler RC, Barber C, Birnbaum HG, et al. Depression in the workplace: effects on short-term disability. Health Aff (Millwood). 1999;18(5):163-171. PubMed doi:10.1377/hlthaff.18.5.163

110. Kessler RC, Ormel J, Demler O, et al. Comorbid mental disorders account for the role impairment of commonly occurring chronic physical disorders: results from the National Comorbidity Survey. J Occup Environ Med. 2003;45(12):1257-1266. PubMed doi:10.1097/01.jom.0000100000.70011.bb

111. Kouzis AC, Eaton WW. Emotional disability days: prevalence and predictors. Am J Public Health. 1994;84(8):1304-1307. PubMed doi:10.2105/AJPH.84.8.1304

112. Lerner D, Adler DA, Chang H, et al. The clinical and occupational correlates of work productivity loss among employed patients with depression. J Occup Environ Med. 2004;46(suppl 6):S46-S55. PubMed doi:10.1097/01.jom.0000126684.82825.0a

113. Lespérance F, Frasure-Smith N, Talajic M, et al. Five-year risk of cardiac mortality in relation to initial severity and one-year changes in depression symptoms after myocardial infarction. Circulation. 2002;105(9):1049-1053. PubMed doi:10.1161/hc0902.104707

114. Luber MP, Hollenberg JP, Williams-Russo P, et al. Diagnosis, treatment, comorbidity, and resource utilization of depressed patients in a general medical practice. Int J Psychiatry Med. 2000;30(1):1-13. PubMed doi:10.2190/YTRY-E86M-G1VC-LC79

115. McIntyre RS, Wilkins K, Gilmour H, et al. The effect of bipolar I disorder and major depressive disorder on workforce function. Chronic Dis Can. 2008;28(3):84-91. PubMed

116. McQuaid JR, Stein MB, Laffaye C, et al. Depression in a primary care clinic: the prevalence and impact of an unrecognized disorder. J Affect Disord. 1999;55(1):1-10. PubMed doi:10.1016/S0165-0327(98)00191-8

117. Muchmore L, Lynch WD, Gardner HH, et al. Prevalence of arthritis and associated joint disorders in an employed population and the associated healthcare, sick leave, disability, and workers’ compensation benefits cost and productivity loss of employers. J Occup Environ Med. 2003;45(4):369-378. PubMed doi:10.1097/01.jom.0000063621.37065.26

118. Mart×­nez-Mart×­n P, Gil-Nagel A, Gracia LM, et al; The Cooperative Multicentric Group. Unified Parkinson’s Disease Rating Scale characteristics and structure. Mov Disord. 1994;9(1):76-83. PubMed doi:10.1002/mds.870090112

119. Ginanneschi A, Degl’ Innocenti F, Magnolfi S, et al. Evaluation of Parkinson’s disease: reliability of three rating scales. Neuroepidemiology. 1988;7(1):38-41. PubMed doi:10.1159/000110159

120. Schwab RS, England AC Jr. Projection technique for evaluating surgery in Parkinson’s disease. In: Gillingham FJ, Donaldson MC, eds. Third Symposium of Parkinson’s Disease. Edinburgh, Scotland: E&S Livingstone; 1969:152-157.

121. Penninx BW, Beekman AT, Honig A, et al. Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry. 2001;58(3):221-227. PubMed doi:10.1001/archpsyc.58.3.221

122. Rovner BW. Depression and increased risk of mortality in the nursing home patient. Am J Med. 1993;94(5A):19S-22S PubMed.

123. Rumsfeld JS, Magid DJ, Plomondon ME, et al. History of depression, angina, and quality of life after acute coronary syndromes. Am Heart J. 2003;145(3):493-499. PubMed doi:10.1067/mhj.2003.177

124. Simon GE, VonKorff M, Barlow W. Health care costs of primary care patients with recognized depression. Arch Gen Psychiatry. 1995;52(10):850-856. PubMed

125. Sobocki P, Jönsson B, Angst J, et al. Cost of depression in Europe. J Ment Health Policy Econ. 2006;9(2):87-98. PubMed

126. Sullivan MD, LaCroix AZ, Baum C, et al. Functional status in coronary artery disease: a one-year prospective study of the role of anxiety and depression. Am J Med. 1997;103(5):348-356. PubMed doi:10.1016/S0002-9343(97)00167-8

127. Sullivan MD, LaCroix AZ, Spertus JA, et al. Five-year prospective study of the effects of anxiety and depression in patients with coronary artery disease. Am J Cardiol. 2000;86:1135-1138, A6, A9.

128. Un×¼tzer J, Patrick DL, Simon G, et al. Depressive symptoms and the cost of health services in HMO patients aged 65 years and older: a 4-year prospective study. JAMA. 1997;277(20):1618-1623. PubMed doi:10.1001/jama.277.20.1618

Table 1