CHAPTER 7

Depression

Madeline Li, M.D., Ph.D., FRCPC

Joshua Rosenblat, M.D.

Gary Rodin, M.D., FRCPC

The risk of developing depressive disorders is increased in most chronic medical conditions, and reciprocally, depression can be a risk factor for the development of medical illnesses (Ramasubbu et al. 2012). There are multiple nonspecific factors, such as disability and physical suffering, that may increase the risk of depression in serious medical illnesses. There is also speculation about whether specific biological mechanisms account for the comorbidity of depression with particular medical conditions.

Depression is frequently underdiagnosed and untreated in medical settings, despite its frequency, negative effects on health, and responsiveness to treatment. This diagnostic and therapeutic neglect may be due to underreporting of symptoms because of stigma, difficulty distinguishing normative from pathological distress, physical symptom overlap between depression and medical illness, and lack of sufficient caregiver training in or comfort with mental health inquiry. There may also be mistaken beliefs among both providers and patients about the untreatability of depression that is “understandable.” Untreated depression is of concern in medical populations because it is associated with greater somatic symptom burden (Katon et al. 2007) and worse quality of life (Katon 2003) in common medical disorders. Depression is also associated with higher rates of health care utilization, such that the cost of medical care for depressed medical patients is 50% higher than that for nondepressed medical patients; depressed patients also tend to be less compliant with medical treatment and to have less functional capacity and less occupational productivity (Unützer et al. 2009). Paradoxically, depression is also overdiagnosed in medical settings, with unnecessary prescription of antidepressant medication for nonpathological sadness or grief or diagnoses based solely on scores on depression screening instruments.

In this chapter we review the prevalence and clinical features of depression in the medically ill; discuss approaches to depression screening, diagnosis, and treatment; and explore mechanisms that may account for the etiology, course, and outcome of depression in the medical setting. We do not attempt to provide in-depth information on depression in particular diseases; for details on the effects of comorbid depression in various medical conditions, readers are referred to the chapters on specific disorders in this textbook.

The Continuum of Depression: From Experience to Disorder

Sadness is a normal, expectable response to the adverse effects of a serious medical illness, including changes in bodily appearance and functioning; pain and physical distress; limitations in the capacity to work and to engage in pleasurable activities; perceived alteration in the anticipated life trajectory; fears of disability and dependency; and alterations in intimate relationships, family life, social relationships, and other activities. Nonpathological sadness and grief lie at one end of the continuum of depression in medical populations. In the middle lie subthreshold depressions (Rodríguez et al. 2012), which are the most prevalent depressive presentations among medically ill patients (Gellis 2010). At the more severe end are depressive symptoms that clearly meet diagnostic criteria for major depressive disorder as specified in DSM-5 (American Psychiatric Association 2013). These categorical distinctions have heuristic and communicative value, although the boundaries that demarcate and distinguish them from one another are somewhat arbitrary and often difficult to determine, particularly in medically ill patients.

The eight major categories of depressive disorders specified in DSM-5 are major depressive disorder (MDD), persistent depressive disorder (PDD; formerly dysthymia), substance/medication-induced depressive disorder, depressive disorder due to another medical condition, disruptive mood dysregulation disorder (applicable only in children), premenstrual dysphoric disorder, other specified depressive disorder (formerly minor or subsyndromal depression), and unspecified depressive disorder (when insufficient information is available to make a specific diagnosis). Subthreshold disorders, including PDD and the other specified and unspecified depressive disorder categories, may substantially reduce quality of life and result in moderate functional impairment (Rowe and Rapaport 2006). At least 10%–20% of subthreshold depressions progress to MDD (Lyness et al. 2006).

DSM-5 no longer excludes recent bereavement from a diagnosis of MDD, although it should be noted that normative and nonpathological grief following a loss may meet all diagnostic criteria for a depressive episode (Horwitz and Wakefield 2007). Indeed, it may be argued that the onset, exacerbation, or progression of a serious medical illness may be experienced as a loss that can be at least as distressing as the loss of a loved one.

Notably, a diagnosis of adjustment disorder, which in DSM-5 is reconceptualized as one of the trauma- and stressor-related disorders, can be applied when a patient has symptoms of depression in reaction to a stressor, such as medical illness, that do not meet criteria for MDD or PDD. The operational criteria for this diagnosis, including what constitutes an “excessive” response to the multiple and chronic stressors of medical illness, are not clear. However, despite this ambiguity, the heuristic and nonstigmatizing appeal of the category of adjustment disorder contribute to its being one of the most common psychiatric diagnoses made in medical patients (Li et al. 2010).

Epidemiology

Depressive disorders are extremely common in the general population, with up to 17% of adults in the United States having had at least one episode of MDD during their lifetime (Kessler et al. 2003) and 2%–4% suffering from a current MDD (Ferrari et al. 2013). Medical illness has consistently been shown to be a risk factor for depression (Patten et al. 2018). PDD and subthreshold depression are the most common depressive syndromes in medical populations, reported in up to 26% of medical outpatients, a rate several times higher than that in the general population (Rowe and Rapaport 2006). The prevalence of MDD varies by population, with rates of 2%–4% in community samples, 5%–10% in primary care settings, and 6%–14% in medical inpatient settings; these progressive increases presumably are based on differences in medical disease severity (Burvill 1995). Similarly, the risk of a depressive episode in patients in primary care (Barkow et al. 2002) and in the community (Wilhelm et al. 1999) rises with the number of comorbid medical diseases. The reported prevalence rates of depressive disorders in specific medical conditions, including cancer, diabetes, cardiovascular disease, chronic obstructive pulmonary disease (COPD)/asthma, HIV/AIDS, stroke, epilepsy, multiple sclerosis, Alzheimer’s disease, and Parkinson’s disease, are listed in Table 7–1.

TABLE 7–1. Prevalence of depression in selected medical illnesses

Medical illness	Prevalence of MDD (%)	MDD vs. subthreshold depression (%)	References
Cancer	8–24	15 vs. 22	Mitchell et al. 2011
Diabetes	9–26	14 vs. 32	Musselman et al. 2003; Roy and Lloyd 2012
	Type 2: 6–33
	Type 1: 6–44
Heart disease	17–27	18 vs. 27	Rudisch and Nemeroff 2003; Schleifer et al. 1989
COPD/asthma	20–50	28 vs. 40	Van Lieshout et al. 2009
HIV/AIDS	18–50	22 vs. 45	Arseniou et al. 2014
Stroke	15–31	14 vs. 18	Morris et al. 1990; Robinson and Jorge 2016
Epilepsy	20–29	23 vs. 29	Fiest et al. 2013
Multiple sclerosis	26–35	30 vs. 33	Boeschoten et al. 2017
Alzheimer’s disease	13–22	22 vs. 27	Chi et al. 2015; Lyketsos et al. 1997
Parkinson’s disease	18–27	23 vs. 30	Goodarzi et al. 2016b

Note. COPD=chronic obstructive pulmonary disease; MDD=major depressive disorder.

FIGURE 7–1. Pathways to depression.

Although depression is often regarded as a discrete disorder, it can also be considered as a final common pathway of distress that arises from the interaction of biological, psychological and social factors. Biological factors interact with the psychological impact of the disease which is filtered through the prism of individual and interpersonal strengths to result in a range of depressive responses from normal sadness to major depressive disorder.

Etiology

Increased rates of depressive symptoms and depressive disorders have been found in virtually all chronic medical conditions in which depression has been studied (Patten et al. 2018). It has been hypothesized that illness-specific biological mechanisms lay the foundations for depression in certain medical conditions, including hypothyroidism, stroke, Parkinson’s disease, diabetes, and some types of cancer. Although specificity for depression has not been substantiated in any of these conditions, each is associated with multiple nonspecific risk factors that may increase the prevalence of depression. In fact, depression in the context of medical illness is a prime example of the biopsychosocial model of disease, with interacting pathophysiological and psychosocial factors contributing to comorbidity. The final common pathway to depression—resulting from the interaction of disease-related, psychological, and social risk and protective factors—is shown in Figure 7–1.

Potential biological contributors to depression in medical illness include the physical effects of illness and treatment, medications, neurological involvement, genetic vulnerability, and systemic inflammation. In this regard, greater pain and treatment intensity (Patten et al. 2018), more advanced disease (Manne et al. 2001), and proximity to death (Lo et al. 2011) have all been shown to increase the risk of depression. Individuals with a genetic vulnerability to depression are also more likely to develop it in the context of medical illness (Levinson 2006), and common genetic vulnerabilities may account for the frequent comorbidity of depression and Alzheimer’s disease (Kim et al. 2002), Parkinson’s disease (Mössner et al. 2001), and coronary artery disease (Su et al. 2009). Immune-activated systemic inflammation (Miller et al. 2009), manifesting as cytokine-induced “sickness behavior,” is another proposed common pathophysiological mechanism that may underlie depression in a wide range of medical disorders, including cancer (Raison and Miller 2003), cardiovascular disease (Parissis et al. 2007), diabetes (Musselman et al. 2003), Alzheimer’s disease (Leonard 2007), stroke (Arbelaez et al. 2007), multiple sclerosis (Wallin et al. 2006), asthma (Van Lieshout et al. 2009), and infectious diseases such as HIV/AIDS (Leserman 2003). This association has led some to posit the existence of a specific subtype of depression—inflammatory cytokine-associated depression (ICAD) (Lotrich 2015), characterized by more neurovegetative and fewer core psychological symptoms (Capuron et al. 2009; Pasquini et al. 2008)—that is more common in individuals with medical conditions associated with inflammation (Dantzer et al. 2008).

It has been suggested that medication-induced depression is symptomatically different from MDD, with less prominent and milder depression and atypical features more characteristic of ICAD (Patten and Barbui 2004). The association of depression with medications such as L-dopa, calcium channel blockers, analgesics, nonsteroidal anti-inflammatory drugs, isotretinoin, and phenobarbital has largely been based on case reports, with few high-quality studies. Valid evidence linking medications to atypical depressive syndromes has been found only for corticosteroids, interferon-α, interleukin-2, gonadotropin-releasing hormone agonists, mefloquine, and progestin-releasing implanted contraceptives (Patten and Barbui 2004). Most of these drugs and their psychiatric side effects are discussed in other chapters of this textbook.

Psychosocial factors that may contribute to the development of a comorbid depressive disorder in medical illness include the stigma and personal meaning of the medical condition, illness-related disability (Talbot et al. 1999), maladaptive coping styles (Wallin et al. 2006), low self-esteem, impaired spiritual well-being (Rodin et al. 2007), and reduced capacity to express affect (Classen et al. 2008). Low social support (Lewis 2001) and poor communication with medical caregivers (Gurevich et al. 2004) also increase the likelihood of a comorbid depressive disorder. Additionally, expectations of support and the capacity for flexible use of social support, captured in the construct of attachment security, may provide protection against the emergence of depressive symptoms in medically ill patients (Rodin et al. 2007).

Age is inversely related to the severity of depressive symptoms (Gottlieb et al. 2004). Although depression in the general population has been strongly associated with female gender (Lucht et al. 2003), this gender difference has not been found consistently in depression in medical populations (Miller et al. 2011; Rodin et al. 2007). It may be that the overriding common stressors related to the medical illness obliterate gender-related differences that would otherwise emerge.

Clinical Features and Diagnosis

The diagnosis of depressive disorders in medical populations is fraught with difficulties that include the following:

1. Many physical symptoms of medical illness (e.g., fatigue, anorexia, weight loss, insomnia, psychomotor retardation, diminished concentration) resemble those of depression. In addition, a variety of emotional disturbances, such as “emotionalism,” pathological crying, apathy, and fatigue in poststroke patients (Bogousslavsky 2003) or in patients with multiple sclerosis (Chwastiak and Ehde 2007), can be mistaken for depression. It may also be difficult to distinguish depression from the apathy associated with hypoactive delirium or dementia, or from akinesia and masked facies in Parkinson’s disease.

2. Thoughts of death and the desire for death in patients with advanced medical disease have been associated with depression and demoralization in the terminally ill (Breitbart et al. 2000). However, such thoughts must be distinguished from adaptive death acceptance or an attempt at cognitive mastery that does not reflect depression (Nissim et al. 2009).

3. Physical suffering and disability, in the absence of comorbid depression, may diminish the capacity to experience pleasure in many formerly enjoyable activities. Depressed mood or withdrawal from social or physical activities that is disproportionate to physical disability increases the likelihood that the loss of pleasure is secondary to depression.

4. In medical populations, depressive symptoms may manifest in atypical or masked forms, including amplification of somatic symptoms (Katon et al. 2007) and noncompliance with or refusal of medical treatment (DiMatteo et al. 2000). These symptoms or behaviors may not be recognized as manifestations of depression, leading to underdiagnosis of depression.

5. The categories of MDD, substance/medication-induced depressive disorder, and depressive disorder due to another medical condition may overlap in the context of medical illness. The latter two diagnoses imply that the etiology of the depression is a direct physiological consequence of the specified general medical condition or substance, whereas the causation of depression is most often multifactorial.

Various approaches have been proposed to diminish the confounding effect of medical symptoms in the diagnosis of MDD. In DSM-5, it is acknowledged that there are no “infallible guidelines” to follow in determining when depression is secondary to another medical condition but that the index of suspicion should be raised by 1) a temporal association between symptoms and the onset, exacerbation, or remission of a medical condition, and 2) an age at onset, course, or absence of family history that is atypical for a primary mood disorder. The criteria for determining which symptoms are due to a medical illness and which are due to other factors unrelated to the medical illness are unclear and are left to “the clinician’s best judgment” (American Psychiatric Association 2013).

A combined “exclusive” and “etiological” approach to the diagnosis of depression in patients with medical illness was previously advocated, with exclusion of symptoms judged by the clinician to be etiologically related to a general medical condition or not more frequent in depressed than nondepressed patients with such conditions (Bukberg et al. 1984). This approach was intended to avoid attributing symptoms of physical illness to a depressive syndrome. The exclusive approach is usually applied only to the somatic symptoms of depression, although this does not take into account that depressed medical patients report significantly more physical symptoms than matched nondepressed medical patients (Fitzgerald et al. 2015).

Evaluating the rates of depression in hospitalized elderly medical patients according to six different diagnostic schemes, Koenig et al. (1997) found no overall advantage of one diagnostic scheme over others. In cases in which the diagnosis remains unclear, a focus on the qualitative differences of psychological features on the continuum of depression (Table 7–2), along with a trial of treatment as appropriate, may be the most practical means of resolving the question.

TABLE 7–2. Psychological features on the continuum of depression

Normal sadness	Subthreshold depression	DSM-5 major depressive disorder
•   Maintenance of intimacy and connection •   Belief that things will get better •   Capacity to enjoy happy memories •   Sense of self-worth fluctuating with thoughts of cancer •   Capacity to look forward to the future •   Retention of capacity for pleasure •   Maintenance of will to live	•   Low mood presentation similar to major depressive disorder but not meeting full criteria for symptom number or duration •   Potentially transient and self-limited, including mood episodes lasting <2 weeks •   Includes persistent depressive disorder if >2 years’ duration	•   Feeling of isolation •   Feeling of permanence •   Excessive guilt and regret •   Self-critical ruminations/loathing •   Constant, pervasive, and nonreactive sadness •   Sense of hopelessness •   Loss of interest in activities •   Suicidal thoughts/behavior

Source. Adapted with permission from Li M., Kennedy E.B., Byrne N., et al.: The Management of Depression in Patients With Cancer: A Quality Initiative of the Program in Evidence-Based Care (PEBC), Cancer Care Ontario (CCO). Guideline #19–4. Toronto, ON, Canada, Cancer Care Ontario, 2016.

Health Outcomes

The bidirectional comorbidity between depression and medical illness is evidenced by the increased risk of acquiring certain medical conditions in patients with a prior history of depression. MDD has been shown to increase the risk of coronary artery disease 1.5- to 2-fold (Van der Kooy et al. 2007), stroke 1.8-fold (Ramasubbu and Patten 2003), cancer 1.9-fold (Gross et al. 2010), diabetes 1.4-fold (Yu et al. 2015), epilepsy 4- to 6-fold (Hesdorffer et al. 2000), and Alzheimer’s disease 2.1-fold (Green et al. 2003). These risk increases may be mediated by biological mechanisms as well as by unhealthy behaviors related to medical compliance, self-care, diet, or exercise (Katon 2003).

The World Health Organization (WHO) recently reported that depression is the leading cause of disability worldwide, with more than 320 million people affected globally (World Health Organization 2017). Remarkably, the WHO World Health Survey (Moussavi et al. 2007) found that depression reduces overall health significantly more than do chronic diseases such as coronary artery disease, arthritis, asthma, and diabetes and that the comorbid state of depression plus medical illness worsens health more than any combination of chronic diseases without depression. Comorbid depression is associated with a significant economic burden, including almost twofold higher rates of health care utilization and workplace disability (Stein et al. 2006), longer inpatient lengths of stay (Saravay et al. 1996), and at least a twofold increase in emergency room visits (Himelhoch et al. 2004). Comorbid depression is also associated with a threefold greater risk of nonadherence to medical treatment, thereby contributing to increased morbidity and mortality (DiMatteo et al. 2000). Such noncompliance may include not taking treatments that are prescribed, not following diet or lifestyle recommendations, and not appearing for medical appointments.

Comorbid depression and medical illness have been shown to be associated with worse medical outcomes and higher mortality rates in a number of medical conditions, but specific causal relationships between depression and such outcomes have not been confirmed (Cuijpers et al. 2014). Depression has been associated with more rapid progression of HIV disease (Leserman 2003) and with increased all-cause mortality in cardiovascular disease (Carney and Freedland 2017), cancer (Batty et al. 2017; Pinquart and Duberstein 2010), organ transplant (Dew et al. 2015), and diabetes (Park et al. 2013). This increased mortality rate, which persists even after factors such as smoking, disease severity, and alcohol consumption (Schulz et al. 2000) are controlled for, may be attributable to several different factors. Biological mechanisms in depression may increase mortality rates in the medically ill via effects on the autonomic nervous system and on related cardiac outcomes. The association of suicide with depression may also increase mortality rates in medical populations, a finding that has been demonstrated in medical conditions such as cancer (Steel et al. 2007), multiple sclerosis (Stenager et al. 1996), and Huntington’s disease (Almqvist et al. 1999). Depression may be associated with other health risk behaviors—such as cigarette smoking, overeating, physical inactivity, obesity, and excess alcohol consumption—that increase the prevalence of associated medical illness and affect its course adversely.

Screening for Depression

Obstacles to Diagnosis in Medical Settings

Depression and other forms of distress are commonly underdiagnosed and undertreated in medical settings (Fallowfield et al. 2001). A U.K. study suggested that fewer than one-half of cases of depression are correctly diagnosed by general practitioners (Mitchell et al. 2009). This finding warrants concern, because a missed diagnosis of MDD may represent a lost opportunity to improve quality of life, decrease the risk of suicide, shorten hospital stay, and improve treatment compliance in the medically ill. There are many explanations for the low rate of detection of clinical depression in medical settings. The structure of medical care—with medical visits often lasting less than 15 minutes, with multiple clinical concerns that may need to be addressed during each visit, and the frequent lack of privacy in clinic and hospital settings—may inhibit disclosure or elaboration of symptoms. Furthermore, some clinicians avoid emotional inquiry because they fear that they lack sufficient time or skill to manage emotional reactions. Some patients are reluctant to disclose depressive symptoms because of perceived stigma or anticipated lack of interest of their medical caregivers. However, most patients welcome the opportunity to discuss psychosocial issues that are raised by their health care providers (Rodin et al. 2009). In some cases, both patients and clinicians have difficulty differentiating the somatic symptoms of depression from those of medical disease. Even when clinically significant depression is recognized as being present, it may be perceived as an “understandable” reaction to medical illness and therefore not worth treating.

Paradoxically, time-pressured medical clinic visits that preclude adequate assessment of mood can lead to the overdiagnosis of depression and unnecessary pharmacotherapy. This may be a result of misattribution of the symptoms of physical illness to depression and use of low diagnostic thresholds for depression, with an overreadiness to prescribe antidepressant medications and/or to refer for specialized psychiatric assessment (Boland et al. 1996) because of inadequate resources or training to explore or manage psychological distress (Aragonès et al. 2006). More appropriate utilization of limited specialized psychiatric resources may be facilitated by routine use of validated depression screening tools in medical settings (Cahill et al. 2015; Caruso et al. 2017; Gill et al. 2017; Hermanns et al. 2013; McCollister 2011; Moraes et al. 2017; Quittner et al. 2016; Swartz et al. 2016), as has been recommended for primary care by the U.S. Preventive Services Task Force, “with adequate systems in place to ensure accurate diagnosis, effective treatment, and appropriate follow-up” (O’Connor et al. 2016).

Screening Process

General Considerations

Screening for depression may be particularly helpful in medical settings, where routine assessment of mood might otherwise not occur. The ideal screening instrument would be easy to administer and score, acceptable to patients, and, most importantly, accurate. However, the utility of screening for depression depends not only on the measure used but also on whether screening results are routinely assessed by medical caregivers and followed up with appropriate and effective intervention. Failure to ensure that such a response loop is implemented partially contributes to the paucity of evidence that depression screening results in improved depression outcomes (Canadian Task Force on Preventive Health Care et al. 2013; Thombs et al. 2014). The WHO’s principles of screening for disease (Andermann et al. 2008) require that medical screening tests demonstrate evidence of effectiveness, with benefits outweighing harms. Screening for depression differs from screening for conditions such as cancer because of the recurrent nature of depression, where early identification may not necessarily reduce incidence in the context of chronic medical illness. Furthermore, positive primary screening tests only identify individuals with a high risk for a medical condition and must be followed by appropriate secondary assessment to make a diagnosis. When positive depression screens automatically trigger intervention, inappropriate use of mental health resources or overprescription of antidepressants may occur. The goal of depression screening should be to initiate a clinical assessment by the health care provider (Li et al. 2016b).

Screening Instruments Commonly Used in Medical Populations

There is no true gold standard for the diagnosis of depression, particularly in the context of medical illness, but clinical interviews have traditionally been used to confirm diagnoses and to establish prevalence rates. Such interviews may be unstructured, utilizing an inclusive or substitutive approach to counting symptoms, or more structured, utilizing diagnostic instruments such as the Structured Clinical Interview for DSM-5 Disorders—Clinician Version (SCID-5-CV; First et al. 2016), the Composite International Diagnostic Interview (CIDI; World Health Organization 1997), the Mini-International Neuropsychiatric Interview (MINI; Sheehan et al. 1998), the Present State Examination (PSE; Hall et al. 1999), or the Primary Care Evaluation of Mental Disorders (PRIME-MD; Spitzer et al. 1999).

Depression rating scales can be used to screen patients to identify those who require clinical diagnostic assessment or to measure depression severity and symptom change over time. Numerous psychometric measures have been developed to measure depressive symptoms, with criterion validity and optimal cutoff scores usually established with some form of clinical interview (Wakefield et al. 2015). The cutoff scores selected determine the sensitivity and specificity of the measure and, therefore, the proportion of false-negative and false-positive cases. Use of higher cutoffs that avoid false positives may be preferable for research purposes and for determining resource allocation in more severe cases. Lower thresholds may be preferable in well-resourced treatment settings in which a premium is placed on avoiding false negatives and on detecting subthreshold disorders. In the following paragraphs we briefly discuss four commonly used self-report instruments that have been validated in medical populations: Center for Epidemiologic Studies—Depression Scale (CES-D; Radloff 1977), Hospital Anxiety and Depression Scale (HADS; Zigmond and Snaith 1983), Beck Depression Inventory–II (BDI-II; Beck et al. 1996), and Patient Health Questionnaire–9 (PHQ-9; Kroenke et al. 2001). The HADS and the BDI-II are copyrighted instruments, while the CES-D and the PHQ-9 are available in the public domain.

The CES-D is a 20-item self-report measure of depressive symptoms, in which only 4 of the 20 items are somatic. Originally designed as a measure of depressive distress in community samples, the CES-D has also been extensively used in medically ill samples, with evidence of good psychometric properties. A cutoff score of 17 was originally recommended to identify clinically significant depression (Radloff 1977), but the low positive predictive value of the CES-D suggests that it might be a better measure of general distress than of depression. Reported cutoff scores in a variety of medical populations have varied between 14 and 23. Depending on cutoffs and medical illness, sensitivity ranges from 73% to 100% and specificity from 61% to 89%.

The HADS is a 14-item self-report scale specifically designed for use in the medically ill, with separate 7-item subscales for anxiety and depression. The depression subscale emphasizes anhedonia and does not include somatic items. The HADS is highly acceptable to patients and has been extensively used in the medically ill, with reported cutoff scores ranging from 8 to 16. Depending on cutoffs and medical illness, sensitivity ranges from 39% to 87% and specificity from 64% to 95%. The HADS does not discriminate well between depression and anxiety, and like the CES-D, it may be better used as a measure of emotional distress (Cosco et al. 2012; Norton et al. 2013).

The BDI-II was originally developed as a 21-item self-report measure of symptom severity in psychiatric patients, but this instrument has been used in numerous studies in the medically ill. Concerns have been raised about its validity in patients with medical illness because of its preponderance of somatic items and about the acceptability to patients of its forced-choice format and complex response alternatives (Koenig et al. 1992). However, there are many studies of the BDI-II as a screening instrument in medically ill samples that have found it to be an accurate self-report measure (Wang and Gorenstein 2013). The cutoff scores recommended in the medically ill have ranged widely, from 7 to 22, providing sensitivity ranging from 45% to 100% and specificity ranging from 64% to 100%, depending on the medical condition (Wang and Gorenstein 2013).

The PHQ-9, the 9-item depression module of the self-administered Patient Health Questionnaire, has been studied in thousands of primary care and medical specialty outpatients in the United States, Europe, and China. The PHQ-9 measures each of the nine DSM-5 criteria for a major depressive episode, with scores ranging from 0 (not at all) to 3 (nearly every day). Reported cutoff scores used in medical populations have ranged from 5 to 10. Depending on cutoffs and medical illness, sensitivity ranges from 52% to 97% and specificity from 73% to 97% (Levis et al. 2017). Of note, Levis et al. (2017) identified significant reporting bias in studies using the PHQ-9, as primary study authors often only selectively report results from cutoffs that perform well in their study.

Single-Item and Very Brief Screening Scales

Single-item screening tests for depression have wide appeal to health care providers and patients, but not surprisingly, they have poor positive predictive value in medical settings (Mitchell 2007; Mitchell and Coyne 2007).

Kroenke et al. (2001) evaluated the two-item PHQ-2, which was derived from the PHQ-9. Meta-analytic studies using the PHQ-2 have reported sensitivity and specificity estimates of 89.3% and 75.9%, respectively, in a primary care population (Mitchell et al. 2016), and 91.8% and 67.7%, respectively, in a geriatric population (Tsoi et al. 2017).

The lower specificity of single-item or ultra-brief self-report measures of depression limits their utility, although measures such as the PHQ-2, which focuses on the core features of depressed mood and/or anhedonia, may be useful, particularly in a step-wise fashion. However, the most common shortcoming in the detection of depression is not in the nature of the instrument used or in the questions posed, but rather in the failure to screen for depression using any method.

Treatment Outcomes

Although the negative impact of depression on illness is unequivocal and the bidirectional relationship between depression and medical illness is strong, evidence that treatment of depression improves disease-specific medical outcomes is less clear. In an analysis of studies evaluating the benefits of a screen-and-treat strategy for depression in diabetes, heart failure, and coronary artery disease, Sharkey et al. (2013) found no evidence of improved chronic disease outcomes. However, Katon et al. (2010) demonstrated in a randomized controlled trial (RCT) that patients with depression and chronic illness (poorly controlled diabetes, coronary artery disease, or both) receiving collaborative care had greater overall 12-month improvements in hemoglobin A1c, low-density lipoprotein cholesterol, systolic blood pressure, and depression scores compared with those receiving usual care. The question of whether treatment of depression improves medical outcomes has been most extensively investigated in cardiovascular disease and cancer, in which several studies have explored the relationship between treatment of depression and survival.

In cardiovascular disease, no beneficial effects on cardiac outcomes were found in studies of psychotherapeutic interventions such as the Montreal Heart Attack Readjustment Trial (M-HART; Frasure-Smith 1995) and the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD; Berkman et al. 2003) trial, although these studies may have been underpowered to detected significant differences, given the modest effectiveness of treatment. Randomized trials of pharmacological treatment for depression in cardiovascular disease, such as the Sertraline Antidepressant Heart Attack Randomized Trial (SADHART; Glassman et al. 2002) and a related trial regarding congestive heart failure, SADHART-CHF (O’Connor et al. 2010), and the Myocardial INfarction and Depression—Intervention Trial (MIND-IT; van den Brink et al. 2002) of mirtazapine, also failed to demonstrate a statistically significant reduction in risk for cardiac events, although these studies similarly demonstrated little reduction in depression. However, in a subanalysis of subjects in the ENRICHD trial, there was reduced risk of death or nonfatal myocardial infarction in subjects who received antidepressants, particularly selective serotonin reuptake inhibitors (SSRIs) (adjusted hazard ratio=0.57). Similarly, secondary analysis of the subgroup of patients in the SADHART-CHF trial who achieved clinical remission of depression demonstrated a statistically significant reduction in cardiovascular events compared with the nonremission group (1.34±1.86 vs. 1.93±2.71; adjusted P=0.01) (Jiang et al. 2011). Beneficial pleiotropic effects of SSRIs, such as reduction in platelet activity (Serebruany et al. 2003) and improvement in heart rate variability (Yeragani et al. 2002), may account for these findings. Notably, one large study of enhanced depression treatment in patients with acute coronary syndrome demonstrated a reduction in major adverse cardiac events in intervention patients compared with usual-care patients (Davidson et al. 2010). Unique aspects of this study were a flexible treatment model in which patients could choose problem-solving therapy and/or antidepressants and selection for persistent (>3 months) depression. A better understanding of the temporal and mechanistic relationships between depression and coronary artery disease is needed to clarify potential medical effects of antidepressant treatment (Dickens et al. 2007; see also Chapter 17, “Heart Disease”).

Studies have yet to be published on medical outcomes associated with treatment of MDD in cancer patients, although such outcomes have been assessed in studies in which threshold depression was not an inclusion criterion. In an RCT of a 6-month course of fluoxetine versus placebo in early-stage breast cancer patients undergoing adjuvant therapy, Navari et al. (2008) reported that fluoxetine reduced depressive symptoms, improved quality of life, and increased the likelihood of completion of adjuvant treatment. The question of whether psychotherapy can improve survival in cancer has been a hotly debated one (Coyne et al. 2009; Kraemer et al. 2009), with better-designed trials demonstrating that psychosocial interventions that are effective in reducing depressive symptoms do not confer a survival benefit in metastatic cancer patients (Jassim et al. 2015; Kissane et al. 2007; see also Chapter 22, “Oncology”).

It may be that the effectiveness of currently available treatments for depression in medical illness is too limited to shift the physiological disease burden of advanced illness enough to alter survival outcomes. More effective treatments may be needed to determine whether alleviation of depression in medical illness has a significant impact on survival and to identify biologically plausible mechanisms that could account for such an effect. Emphasis instead should be on improving quality of life.

FIGURE 7–2. Stepped-care model of depression care, with treatment intensity corresponding to depression severity.

^aComplex depression includes depression that shows an inadequate response to multiple treatments, is complicated by psychotic symptoms, and/or is associated with significant psychiatric comorbidity or psychosocial factors.

Source. Reprinted from Li M, Kennedy EB, Byrne N, et al.: “Management of Depression in Patients With Cancer: A Clinical Practice Guideline.” Journal of Oncology Practice 12(8):747–756, 2016; content from National Institute for Health and Care Excellence 2015.

Treatment

Several studies have reported that both pharmacological and psychotherapeutic interventions are effective in treating depression in patients with medical disorders, although these effects may be less robust than those in individuals with MDD without medical comorbidity (Iosifescu 2007). The latter finding may be due not only to a difference in the response of MDD to treatment but also to the more prevalent subthreshold presentations in medical populations, which tend not to respond to antidepressant medications (Baumeister 2012) and for which optimal treatment approaches are less clear (Rowe and Rapaport 2006).

The primary evidence base for the effectiveness of treatment of depression in specific medical conditions is limited. Most systematic reviews and meta-analyses have demonstrated modest benefit in illnesses including diabetes (Baumeister et al. 2014), coronary artery disease (Baumeister et al. 2011), COPD (Panagioti et al. 2016), cancer (Li et al. 2017), HIV infection and AIDS (Sherr et al. 2011), chronic kidney disease (Grigoriou et al. 2015), stroke (Nabavi et al. 2014), multiple sclerosis (Fiest et al. 2016), dementia (Ford and Almeida 2017), and Parkinson’s disease (Troeung et al. 2013). All such reviews comment on the limited evidence base and the need for more RCTs of depression treatments. Most current disease-specific depression treatment guidelines recommend the use of both pharmacological and psychotherapeutic interventions, based on pooled evidence of benefit in medical populations and extrapolation from effectiveness in primary psychiatric populations (Goodarzi et al. 2016a; Li et al. 2016a; Lichtman et al. 2008; Relf et al. 2013; Towfighi et al. 2017). The National Institute for Health and Care Excellence (NICE) has synthesized the available evidence on the treatment of depression in adults with a chronic physical health problem (National Collaborating Centre for Mental Health [UK] 2010). Updated guidelines published in November 2015 identified a few new treatment trials, but none that altered NICE’s recommendations for a stepped-care approach to depression management (National Institute for Health and Care Excellence 2015). Stepped care is a framework for care delivery in which treatment is graded to the severity of depression (Figure 7–2). All patients with depression are provided with basic assessment, support, psychoeducation, monitoring, and referral (Step 1). Based on evidence that the risk–benefit ratio does not support the use of antidepressant medications in subthreshold depression, less intrusive and low-intensity psychological or psychosocial interventions are provided first (Step 2), with progression to the next step of medications and/or high-intensity psychological interventions (Step 3), which may be delivered within a collaborative care model (Archer et al. 2012) if there is inadequate response to initial treatment. Complex depression involving suicide risk, psychosis, or severe psychosocial risk may require inpatient admission and/or brain stimulation therapies. The components of these interventions are described more fully below.

Psychotherapeutic Treatment

The full range of psychosocial interventions designed to treat depression in medical populations is discussed in more detail in Chapter 37 (“Psychotherapy”) and in the chapters on specific disorders in this textbook. The stepped-care model suggests use of low-intensity psychosocial interventions for persistent subthreshold depressive symptoms or mild to moderate depression. Low-intensity interventions include structured group physical activity programs, group-based peer support or self-help programs, individual guided self-help programs based on cognitive-behavioral therapy (CBT), and computerized CBT. Such group-based therapies may protect patients from depression by diminishing stigma and feelings of isolation and by promoting self-efficacy and a sense of mastery. Patients with inadequate response to treatment or with initial presentations of moderate to severe depression should be offered high-intensity psychosocial interventions that are professionally facilitated. Such interventions include individual or group CBT or behavioral couples’ therapy. A Cochrane review of psychotherapy for depression in patients with incurable cancer concluded that psychotherapy was effective in decreasing depressive symptoms, although no studies were identified that focused specifically on patients with MDD (Akechi et al. 2008).

Although the preponderance of research evidence supports cognitive-behavioral approaches to treatment of depression in medical illness (Baumeister et al. 2014; Hummel et al. 2017; Jassim et al. 2015; Orgeta et al. 2015; Ski et al. 2016), such approaches are rarely adopted in routine clinical practice. More commonly, an individualized eclectic approach is used, combining elements of psychoeducation, behavioral activation, problem solving, interpersonal therapy, mindfulness-based therapy, and supportive–expressive psychotherapy delivered on an individual or a group basis. The relationship with the primary medical caregiver may be the most important psychotherapeutic tool to prevent or treat depression for many patients with a serious medical illness. Specific psychological therapies may alleviate or prevent depression, without the risk of physical side effects or drug interactions, and may help to modify health behaviors that adversely affect disease outcomes. The indication to refer to a mental health professional for psychotherapy will depend on the severity of the depression and on the skill and availability of practitioners. The specific psychotherapeutic intervention selected should also take into account the available support network and the patient’s capacity to learn new coping strategies and/or to engage in a process that may involve introspection and the expression of feelings. Unique features of psychotherapy in the medically ill are the importance of collaborative relationships between the therapist and the medical caregivers, the likelihood of frequent disruptions in treatment due to complications of the disease, and the need for flexible treatment goals that accommodate shifts in the patient’s physical well-being and capacity to participate. In more advanced disease, issues related to hope, existential well-being, and advance care planning may be prominent (Rodin et al. 2009).

Replicated evidence has demonstrated moderate antidepressant effects of psychotherapeutic interventions for patients with cardiovascular disease (Ski et al. 2016; Whalley et al. 2011), diabetes (Baumeister et al. 2012; Musselman et al. 2003), cognitive impairment (Orgeta et al. 2015), HIV/AIDS (van Luenen et al. 2018), multiple sclerosis (Fiest et al. 2016; Wallin et al. 2006), heart failure (Freedland et al. 2015), hemodialysis (Xing et al. 2016), and stroke (Stalder-Lüthy et al. 2013). Numerous systematic reviews and meta-analyses of psychosocial interventions in cancer have found treatment effects for depressive symptoms (Williams and Dale 2006), and systematic reviews of psychosocial interventions for categorical diagnoses of MDD (Li et al. 2016a; Williams and Dale 2006) also demonstrate a treatment effect in RCTs, although the number of studies in these reviews is small. Newly emerging therapies, including Meaning-Centered Psychotherapy (Breitbart et al. 2012), Dignity Therapy (Chochinov et al. 2011), and CALM Therapy (Lo et al. 2014, 2016), have shown benefit in reducing depressive symptoms in patients with advanced cancer, although the effectiveness of these therapies in treating MDD has yet to be demonstrated.

In summary, studies of psychotherapeutic interventions to treat depression in a variety of medical populations indicate some degree of effectiveness, which is often improved in more severe depression when psychotherapy is combined with antidepressant medication. Numerous other nonspecific psychotherapeutic and educational interventions also may be effective in reducing and preventing depressive symptoms.

Psychopharmacological Treatment

SSRIs, heterocyclic antidepressants and tricyclic antidepressants (TCAs), novel antidepressants, and psychostimulants have been evaluated in the treatment of depression comorbid with medical illness. All antidepressants are discussed fully in Chapter 36 (“Psychopharmacology”); here we summarize key points.

SSRIs are generally regarded as the first-line pharmacological treatment for depression in medically ill patients because of their tolerability and relative safety, although mixed-action antidepressants have become increasingly popular in this population because of the potential for dual benefits arising from their receptor-targeting profiles. Venlafaxine is effective for hot flashes in breast cancer (Loprinzi et al. 2000); venlafaxine, duloxetine, and milnacipran are effective for the treatment of pain syndromes (Jann and Slade 2007); mirtazapine may be useful in treating nausea, insomnia, and anorexia (de Boer 1996); and bupropion may be particularly useful in treating patients with prominent neurovegetative symptoms, such as fatigue (Raison et al. 2005). Vortioxetine and vilazodone are multimodal serotonin modulator and stimulator antidepressants recently approved for use in the treatment of MDD. Vortioxetine may have procognitive effects (Rosenblat et al. 2015), but they have yet to be evaluated in medical populations. TCAs such as amitriptyline and nortriptyline have been shown to be effective as analgesics in the treatment of chronic pain syndromes and insomnia (see Chapter 34, “Pain”). Psychostimulants such as methylphenidate and modafinil (Ballon and Feifel 2006) have been reported to rapidly alleviate depressive symptoms in a range of medical conditions, including stroke (Grade et al. 1998), HIV disease (Fernandez et al. 1995), and cancer (Andrew et al. 2017; Conley et al. 2016). Many consider psychostimulants to be the antidepressants of choice in the palliative care setting because of their rapid onset of action (Wilson et al. 2000); however, the evidence remains mixed, with both positive (Ng et al. 2014) and negative (Centeno et al. 2012; Sullivan et al. 2017) trials in palliative care. A Cochrane review (Candy et al. 2008) suggested that the improvement in depression that occurs with psychostimulants may not be clinically significant. Atypical antipsychotics such as olanzapine and quetiapine are effective as augmenting agents in the treatment of MDD in the general population, although this effect has not been studied in medical populations. However, antipsychotics used for this purpose may have additional benefits by stimulating appetite, relieving chemotherapy-induced nausea, improving sleep, and alleviating perceptual disturbances associated with delirium.

Brain Stimulation Therapies

Electroconvulsive therapy (ECT) is sometimes used in the medically ill to treat severe or refractory depression (Beale et al. 1997). It has been shown to be effective in improving depression in Parkinson’s disease and also may improve the symptoms of the Parkinson’s disease itself (Borisovskaya et al. 2016); it has also been shown to improve poststroke depression and depression associated with multiple sclerosis, endocrine disorders, and renal failure (Krystal and Coffey 1997). ECT has been associated with improvements in cognition and mood in patients with dementia (Rao and Lyketsos 2000) and is considered safe for epilepsy patients with severe or refractory depression (Lambert and Robertson 1999). ECT should be considered early in the course of depression with psychosis or catatonia, and for depression associated with severe suicidal ideation or failure to maintain adequate nutritional status. ECT and its risks are reviewed in detail in Chapter 38 (“Electroconvulsive Therapy and Other Brain Stimulation Therapies”).

Similarly, repetitive transcranial magnetic stimulation (rTMS), which does not produce the short-term memory impairment associated with ECT, is sometimes used as an alternative to pharmacotherapy, with growing evidence supporting its use in the medically ill. Replicated evidence (i.e., more than 80 RCTs) supports a robust antidepressant effect of rTMS for depression alone and in specific medical populations (Brunoni et al. 2017). In a recent meta-analysis, Shen et al. (2017) identified 22 RCTs, all in China (N=1,764 patients), of rTMS for poststroke depression. The results demonstrated that rTMS had a positive effect, with high antidepressant response and remission rates and improvement in activities of daily living. Likewise, in a meta-analysis of eight RCTs (N=312) evaluating the effects of rTMS for depression in Parkinson’s disease, Xie et al. (2015) found a positive pooled antidepressant effect for rTMS versus sham rTMS and an equivocal antidepressant effect for rTMS versus SSRIs. Furthermore, patients who received rTMS showed improvement in symptoms of Parkinson’s disease and in performance of activities of daily living compared with patients who received sham rTMS or SSRIs. Taken together, there is growing evidence to support the use of rTMS for depression in medically ill patients, particularly those with neurological disorders (McIntyre et al. 2016).

Collaborative Care

At a systems level of care, there is now strong evidence to support the effectiveness of collaborative care models for the treatment of depression in cancer (Sharpe et al. 2014; Walker et al. 2014), coronary artery disease (Atlantis et al. 2014), diabetes (Tully and Baumeister 2015), multiple sclerosis (Ehde et al. 2016), and hepatitis C (Kanwal et al. 2016). Whereas the stepped-care model suggests use of collaborative care for either refractory or moderate to severe depression, recent studies have supported the clinical and cost effectiveness of collaborative care for subthreshold depression as well (Gilbody et al. 2017; Lewis et al. 2017). (For further information on collaborative care, see Chapter 37, “Psychotherapy.”)

Conclusion

Clinical depression is common in the medically ill and is associated with impaired quality of life, decreased compliance with medical treatment, and increased medical morbidity and mortality. The elevated prevalence of depression in the medically ill is most often the result of multiple risk factors, although there is continued speculation that specific biological mechanisms operate in certain medical conditions. The diagnosis of depressive disorders in medical patients is complicated by the frequent overlap between symptoms of depression and those of medical illness. This overlap may contribute to underdiagnosis when symptoms of depression are assumed to be features of the medical condition, or to overdiagnosis when symptoms of a medical illness are attributed to depressed mood. However, the neglect of simple inquiry about the symptoms of depression may be the most common reason that the diagnosis of depression is overlooked in medical patients. Screening tests may be useful for drawing the attention of clinicians to these symptoms and identifying patients in medical settings who are most likely to have depressive disorders. Psychopharmacological and psychotherapeutic approaches are both effective in the treatment of depressive disorders in the medically ill and are often even more effective when used together in collaborative care models.

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